diff --git a/causy/causal_discovery/constraint/orientation_rules/pc.html b/causy/causal_discovery/constraint/orientation_rules/pc.html index 3dae7e3..4e2d54f 100644 --- a/causy/causal_discovery/constraint/orientation_rules/pc.html +++ b/causy/causal_discovery/constraint/orientation_rules/pc.html @@ -351,261 +351,267 @@

256 u=y, 257 v=z, 258 action=TestResultAction.DO_NOTHING, -259 data={"orientation_conflict": True}, -260 ) -261 return TestResult( -262 u=y, -263 v=z, -264 action=TestResultAction.REMOVE_EDGE_DIRECTED, -265 data={}, -266 ) -267 -268 if graph.only_directed_edge_exists(y, z) and graph.undirected_edge_exists( -269 z, x -270 ): -271 for node in graph.nodes: -272 if graph.only_directed_edge_exists(graph.nodes[node], x): -273 breakflag = True -274 break -275 if breakflag is True: -276 return TestResult( -277 u=x, -278 v=z, -279 action=TestResultAction.DO_NOTHING, -280 data={"orientation_conflict": True}, -281 ) -282 return TestResult( -283 u=x, -284 v=z, -285 action=TestResultAction.REMOVE_EDGE_DIRECTED, -286 data={}, -287 ) -288 -289 -290class FurtherOrientTripleTest( -291 PipelineStepInterface[PipelineStepInterfaceType], Generic[PipelineStepInterfaceType] -292): -293 generator: Optional[GeneratorInterface] = AllCombinationsGenerator( -294 comparison_settings=ComparisonSettings(min=2, max=2) -295 ) -296 chunk_size_parallel_processing: IntegerParameter = 1 -297 parallel: BoolParameter = False -298 -299 def process( -300 self, nodes: Tuple[str], graph: BaseGraphInterface -301 ) -> Optional[List[TestResult] | TestResult]: -302 """ -303 Further orientation rule. -304 :param nodes: list of nodes -305 :param graph: the current graph -306 :returns: list of actions that will be executed on graph -307 """ -308 -309 x = graph.nodes[nodes[0]] -310 y = graph.nodes[nodes[1]] -311 -312 results = [] -313 for z in graph.nodes: -314 z = graph.nodes[z] -315 # check if it is a potential z -316 if not (graph.edge_exists(y, z) and graph.edge_exists(x, z)): -317 continue -318 -319 if ( -320 graph.undirected_edge_exists(x, y) -321 and graph.only_directed_edge_exists(x, z) -322 and graph.only_directed_edge_exists(z, y) -323 ): -324 results.append( -325 TestResult( -326 u=y, -327 v=x, -328 action=TestResultAction.REMOVE_EDGE_DIRECTED, -329 data={}, -330 ) -331 ) -332 if ( -333 graph.undirected_edge_exists(x, y) -334 and graph.only_directed_edge_exists(y, z) -335 and graph.only_directed_edge_exists(z, x) -336 ): -337 results.append( -338 TestResult( -339 u=x, -340 v=y, -341 action=TestResultAction.REMOVE_EDGE_DIRECTED, -342 data={}, -343 ) -344 ) -345 return results -346 -347 -348class OrientQuadrupleTest( -349 PipelineStepInterface[PipelineStepInterfaceType], Generic[PipelineStepInterfaceType] -350): -351 generator: Optional[GeneratorInterface] = AllCombinationsGenerator( -352 comparison_settings=ComparisonSettings(min=2, max=2) -353 ) -354 chunk_size_parallel_processing: IntegerParameter = 1 -355 parallel: BoolParameter = False -356 -357 def process( -358 self, nodes: Tuple[str], graph: BaseGraphInterface -359 ) -> Optional[List[TestResult] | TestResult]: -360 """ -361 Further orientation rule. -362 :param nodes: list of nodes -363 :param graph: the current graph -364 :returns: list of actions that will be executed on graph -365 """ -366 -367 y = graph.nodes[nodes[0]] -368 w = graph.nodes[nodes[1]] -369 -370 potential_zs = set() -371 -372 # TODO: just iterate over edges -373 for z in graph.nodes: -374 z = graph.nodes[z] -375 if graph.edge_exists(y, z) and graph.edge_exists(z, w): -376 potential_zs.add(z) +259 data={ +260 "orientation_conflict": True, +261 "between": {"x": x, "y": y, "z": z}, +262 }, +263 ) +264 return TestResult( +265 u=y, +266 v=z, +267 action=TestResultAction.REMOVE_EDGE_DIRECTED, +268 data={"between": {"x": x, "y": y, "z": z}}, +269 ) +270 +271 if graph.only_directed_edge_exists(y, z) and graph.undirected_edge_exists( +272 z, x +273 ): +274 for node in graph.nodes: +275 if graph.only_directed_edge_exists(graph.nodes[node], x): +276 breakflag = True +277 break +278 if breakflag is True: +279 return TestResult( +280 u=x, +281 v=z, +282 action=TestResultAction.DO_NOTHING, +283 data={ +284 "orientation_conflict": True, +285 "between": {"x": x, "y": y, "z": z}, +286 }, +287 ) +288 return TestResult( +289 u=x, +290 v=z, +291 action=TestResultAction.REMOVE_EDGE_DIRECTED, +292 data={}, +293 ) +294 +295 +296class FurtherOrientTripleTest( +297 PipelineStepInterface[PipelineStepInterfaceType], Generic[PipelineStepInterfaceType] +298): +299 generator: Optional[GeneratorInterface] = AllCombinationsGenerator( +300 comparison_settings=ComparisonSettings(min=2, max=2) +301 ) +302 chunk_size_parallel_processing: IntegerParameter = 1 +303 parallel: BoolParameter = False +304 +305 def process( +306 self, nodes: Tuple[str], graph: BaseGraphInterface +307 ) -> Optional[List[TestResult] | TestResult]: +308 """ +309 Further orientation rule. +310 :param nodes: list of nodes +311 :param graph: the current graph +312 :returns: list of actions that will be executed on graph +313 """ +314 +315 x = graph.nodes[nodes[0]] +316 y = graph.nodes[nodes[1]] +317 +318 results = [] +319 for z in graph.nodes: +320 z = graph.nodes[z] +321 # check if it is a potential z +322 if not (graph.edge_exists(y, z) and graph.edge_exists(x, z)): +323 continue +324 +325 if ( +326 graph.undirected_edge_exists(x, y) +327 and graph.only_directed_edge_exists(x, z) +328 and graph.only_directed_edge_exists(z, y) +329 ): +330 results.append( +331 TestResult( +332 u=y, +333 v=x, +334 action=TestResultAction.REMOVE_EDGE_DIRECTED, +335 data={"between": {"x": x, "y": y, "z": z}}, +336 ) +337 ) +338 if ( +339 graph.undirected_edge_exists(x, y) +340 and graph.only_directed_edge_exists(y, z) +341 and graph.only_directed_edge_exists(z, x) +342 ): +343 results.append( +344 TestResult( +345 u=x, +346 v=y, +347 action=TestResultAction.REMOVE_EDGE_DIRECTED, +348 data={"between": {"x": x, "y": y, "z": z}}, +349 ) +350 ) +351 return results +352 +353 +354class OrientQuadrupleTest( +355 PipelineStepInterface[PipelineStepInterfaceType], Generic[PipelineStepInterfaceType] +356): +357 generator: Optional[GeneratorInterface] = AllCombinationsGenerator( +358 comparison_settings=ComparisonSettings(min=2, max=2) +359 ) +360 chunk_size_parallel_processing: IntegerParameter = 1 +361 parallel: BoolParameter = False +362 +363 def process( +364 self, nodes: Tuple[str], graph: BaseGraphInterface +365 ) -> Optional[List[TestResult] | TestResult]: +366 """ +367 Further orientation rule. +368 :param nodes: list of nodes +369 :param graph: the current graph +370 :returns: list of actions that will be executed on graph +371 """ +372 +373 y = graph.nodes[nodes[0]] +374 w = graph.nodes[nodes[1]] +375 +376 potential_zs = set() 377 -378 results = [] -379 for zs in itertools.combinations(potential_zs, 2): -380 x, z = zs -381 if ( -382 not graph.edge_exists(y, w) -383 and graph.only_directed_edge_exists(y, z) -384 and graph.only_directed_edge_exists(w, z) -385 and graph.undirected_edge_exists(x, y) -386 and graph.undirected_edge_exists(x, w) -387 and graph.undirected_edge_exists(x, z) -388 ): -389 results.append( -390 TestResult( -391 u=z, -392 v=x, -393 action=TestResultAction.REMOVE_EDGE_DIRECTED, -394 data={}, -395 ) -396 ) -397 if ( -398 not graph.edge_exists(y, w) -399 and graph.only_directed_edge_exists(y, x) -400 and graph.only_directed_edge_exists(w, x) -401 and graph.undirected_edge_exists(y, z) -402 and graph.undirected_edge_exists(w, z) -403 and graph.undirected_edge_exists(x, z) -404 ): -405 results.append( -406 TestResult( -407 u=x, -408 v=z, -409 action=TestResultAction.REMOVE_EDGE_DIRECTED, -410 data={}, -411 ) -412 ) -413 return results -414 -415 -416class FurtherOrientQuadrupleTest( -417 PipelineStepInterface[PipelineStepInterfaceType], Generic[PipelineStepInterfaceType] -418): -419 generator: Optional[GeneratorInterface] = AllCombinationsGenerator( -420 comparison_settings=ComparisonSettings(min=2, max=2) -421 ) -422 chunk_size_parallel_processing: int = 1 -423 parallel: bool = False -424 -425 def process( -426 self, nodes: Tuple[str], graph: BaseGraphInterface -427 ) -> Optional[List[TestResult] | TestResult]: -428 """ -429 Further orientation rule. -430 :param nodes: list of nodes -431 :param graph: the current graph -432 :returns: list of actions that will be executed on graph -433 """ -434 -435 x = graph.nodes[nodes[0]] -436 w = graph.nodes[nodes[1]] -437 -438 potential_zs = set() -439 -440 # TODO: just iterate over edges -441 for z in graph.nodes: -442 z = graph.nodes[z] -443 if graph.edge_exists(x, z) and graph.edge_exists(z, w): -444 potential_zs.add(z) +378 # TODO: just iterate over edges +379 for z in graph.nodes: +380 z = graph.nodes[z] +381 if graph.edge_exists(y, z) and graph.edge_exists(z, w): +382 potential_zs.add(z) +383 +384 results = [] +385 for zs in itertools.combinations(potential_zs, 2): +386 x, z = zs +387 if ( +388 not graph.edge_exists(y, w) +389 and graph.only_directed_edge_exists(y, z) +390 and graph.only_directed_edge_exists(w, z) +391 and graph.undirected_edge_exists(x, y) +392 and graph.undirected_edge_exists(x, w) +393 and graph.undirected_edge_exists(x, z) +394 ): +395 results.append( +396 TestResult( +397 u=z, +398 v=x, +399 action=TestResultAction.REMOVE_EDGE_DIRECTED, +400 data={}, +401 ) +402 ) +403 if ( +404 not graph.edge_exists(y, w) +405 and graph.only_directed_edge_exists(y, x) +406 and graph.only_directed_edge_exists(w, x) +407 and graph.undirected_edge_exists(y, z) +408 and graph.undirected_edge_exists(w, z) +409 and graph.undirected_edge_exists(x, z) +410 ): +411 results.append( +412 TestResult( +413 u=x, +414 v=z, +415 action=TestResultAction.REMOVE_EDGE_DIRECTED, +416 data={}, +417 ) +418 ) +419 return results +420 +421 +422class FurtherOrientQuadrupleTest( +423 PipelineStepInterface[PipelineStepInterfaceType], Generic[PipelineStepInterfaceType] +424): +425 generator: Optional[GeneratorInterface] = AllCombinationsGenerator( +426 comparison_settings=ComparisonSettings(min=2, max=2) +427 ) +428 chunk_size_parallel_processing: int = 1 +429 parallel: bool = False +430 +431 def process( +432 self, nodes: Tuple[str], graph: BaseGraphInterface +433 ) -> Optional[List[TestResult] | TestResult]: +434 """ +435 Further orientation rule. +436 :param nodes: list of nodes +437 :param graph: the current graph +438 :returns: list of actions that will be executed on graph +439 """ +440 +441 x = graph.nodes[nodes[0]] +442 w = graph.nodes[nodes[1]] +443 +444 potential_zs = set() 445 -446 results = [] -447 for zs in itertools.combinations(potential_zs, 2): -448 y, z = zs -449 if ( -450 not graph.edge_exists(y, z) -451 and graph.undirected_edge_exists(x, z) -452 and graph.undirected_edge_exists(x, w) -453 and graph.undirected_edge_exists(x, y) -454 and graph.only_directed_edge_exists(y, w) -455 and graph.only_directed_edge_exists(w, z) -456 ): -457 results.append( -458 TestResult( -459 u=z, -460 v=x, -461 action=TestResultAction.REMOVE_EDGE_DIRECTED, -462 data={}, -463 ) -464 ) -465 elif ( -466 not graph.edge_exists(z, y) -467 and graph.undirected_edge_exists(x, y) -468 and graph.undirected_edge_exists(x, w) -469 and graph.undirected_edge_exists(x, z) -470 and graph.only_directed_edge_exists(z, w) -471 and graph.only_directed_edge_exists(w, y) -472 ): -473 results.append( -474 TestResult( -475 u=y, -476 v=x, -477 action=TestResultAction.REMOVE_EDGE_DIRECTED, -478 data={}, -479 ) -480 ) -481 elif ( -482 not graph.edge_exists(y, z) -483 and graph.undirected_edge_exists(w, z) -484 and graph.undirected_edge_exists(x, w) -485 and graph.undirected_edge_exists(w, y) -486 and graph.only_directed_edge_exists(y, x) -487 and graph.only_directed_edge_exists(x, z) -488 ): -489 results.append( -490 TestResult( -491 u=z, -492 v=w, -493 action=TestResultAction.REMOVE_EDGE_DIRECTED, -494 data={}, -495 ) -496 ) -497 elif ( -498 not graph.edge_exists(z, y) -499 and graph.undirected_edge_exists(w, y) -500 and graph.undirected_edge_exists(x, w) -501 and graph.undirected_edge_exists(w, z) -502 and graph.only_directed_edge_exists(z, x) -503 and graph.only_directed_edge_exists(x, y) -504 ): -505 results.append( -506 TestResult( -507 u=y, -508 v=w, -509 action=TestResultAction.REMOVE_EDGE_DIRECTED, -510 data={}, -511 ) -512 ) -513 return results +446 # TODO: just iterate over edges +447 for z in graph.nodes: +448 z = graph.nodes[z] +449 if graph.edge_exists(x, z) and graph.edge_exists(z, w): +450 potential_zs.add(z) +451 +452 results = [] +453 for zs in itertools.combinations(potential_zs, 2): +454 y, z = zs +455 if ( +456 not graph.edge_exists(y, z) +457 and graph.undirected_edge_exists(x, z) +458 and graph.undirected_edge_exists(x, w) +459 and graph.undirected_edge_exists(x, y) +460 and graph.only_directed_edge_exists(y, w) +461 and graph.only_directed_edge_exists(w, z) +462 ): +463 results.append( +464 TestResult( +465 u=z, +466 v=x, +467 action=TestResultAction.REMOVE_EDGE_DIRECTED, +468 data={}, +469 ) +470 ) +471 elif ( +472 not graph.edge_exists(z, y) +473 and graph.undirected_edge_exists(x, y) +474 and graph.undirected_edge_exists(x, w) +475 and graph.undirected_edge_exists(x, z) +476 and graph.only_directed_edge_exists(z, w) +477 and graph.only_directed_edge_exists(w, y) +478 ): +479 results.append( +480 TestResult( +481 u=y, +482 v=x, +483 action=TestResultAction.REMOVE_EDGE_DIRECTED, +484 data={}, +485 ) +486 ) +487 elif ( +488 not graph.edge_exists(y, z) +489 and graph.undirected_edge_exists(w, z) +490 and graph.undirected_edge_exists(x, w) +491 and graph.undirected_edge_exists(w, y) +492 and graph.only_directed_edge_exists(y, x) +493 and graph.only_directed_edge_exists(x, z) +494 ): +495 results.append( +496 TestResult( +497 u=z, +498 v=w, +499 action=TestResultAction.REMOVE_EDGE_DIRECTED, +500 data={}, +501 ) +502 ) +503 elif ( +504 not graph.edge_exists(z, y) +505 and graph.undirected_edge_exists(w, y) +506 and graph.undirected_edge_exists(x, w) +507 and graph.undirected_edge_exists(w, z) +508 and graph.only_directed_edge_exists(z, x) +509 and graph.only_directed_edge_exists(x, y) +510 ): +511 results.append( +512 TestResult( +513 u=y, +514 v=w, +515 action=TestResultAction.REMOVE_EDGE_DIRECTED, +516 data={}, +517 ) +518 ) +519 return results @@ -1108,35 +1114,41 @@

Inherited Members
257 u=y, 258 v=z, 259 action=TestResultAction.DO_NOTHING, -260 data={"orientation_conflict": True}, -261 ) -262 return TestResult( -263 u=y, -264 v=z, -265 action=TestResultAction.REMOVE_EDGE_DIRECTED, -266 data={}, -267 ) -268 -269 if graph.only_directed_edge_exists(y, z) and graph.undirected_edge_exists( -270 z, x -271 ): -272 for node in graph.nodes: -273 if graph.only_directed_edge_exists(graph.nodes[node], x): -274 breakflag = True -275 break -276 if breakflag is True: -277 return TestResult( -278 u=x, -279 v=z, -280 action=TestResultAction.DO_NOTHING, -281 data={"orientation_conflict": True}, -282 ) -283 return TestResult( -284 u=x, -285 v=z, -286 action=TestResultAction.REMOVE_EDGE_DIRECTED, -287 data={}, -288 ) +260 data={ +261 "orientation_conflict": True, +262 "between": {"x": x, "y": y, "z": z}, +263 }, +264 ) +265 return TestResult( +266 u=y, +267 v=z, +268 action=TestResultAction.REMOVE_EDGE_DIRECTED, +269 data={"between": {"x": x, "y": y, "z": z}}, +270 ) +271 +272 if graph.only_directed_edge_exists(y, z) and graph.undirected_edge_exists( +273 z, x +274 ): +275 for node in graph.nodes: +276 if graph.only_directed_edge_exists(graph.nodes[node], x): +277 breakflag = True +278 break +279 if breakflag is True: +280 return TestResult( +281 u=x, +282 v=z, +283 action=TestResultAction.DO_NOTHING, +284 data={ +285 "orientation_conflict": True, +286 "between": {"x": x, "y": y, "z": z}, +287 }, +288 ) +289 return TestResult( +290 u=x, +291 v=z, +292 action=TestResultAction.REMOVE_EDGE_DIRECTED, +293 data={}, +294 ) @@ -1206,62 +1218,62 @@
Inherited Members
- 
291class FurtherOrientTripleTest(
-292    PipelineStepInterface[PipelineStepInterfaceType], Generic[PipelineStepInterfaceType]
-293):
-294    generator: Optional[GeneratorInterface] = AllCombinationsGenerator(
-295        comparison_settings=ComparisonSettings(min=2, max=2)
-296    )
-297    chunk_size_parallel_processing: IntegerParameter = 1
-298    parallel: BoolParameter = False
-299
-300    def process(
-301        self, nodes: Tuple[str], graph: BaseGraphInterface
-302    ) -> Optional[List[TestResult] | TestResult]:
-303        """
-304        Further orientation rule.
-305        :param nodes: list of nodes
-306        :param graph: the current graph
-307        :returns: list of actions that will be executed on graph
-308        """
-309
-310        x = graph.nodes[nodes[0]]
-311        y = graph.nodes[nodes[1]]
-312
-313        results = []
-314        for z in graph.nodes:
-315            z = graph.nodes[z]
-316            # check if it is a potential z
-317            if not (graph.edge_exists(y, z) and graph.edge_exists(x, z)):
-318                continue
-319
-320            if (
-321                graph.undirected_edge_exists(x, y)
-322                and graph.only_directed_edge_exists(x, z)
-323                and graph.only_directed_edge_exists(z, y)
-324            ):
-325                results.append(
-326                    TestResult(
-327                        u=y,
-328                        v=x,
-329                        action=TestResultAction.REMOVE_EDGE_DIRECTED,
-330                        data={},
-331                    )
-332                )
-333            if (
-334                graph.undirected_edge_exists(x, y)
-335                and graph.only_directed_edge_exists(y, z)
-336                and graph.only_directed_edge_exists(z, x)
-337            ):
-338                results.append(
-339                    TestResult(
-340                        u=x,
-341                        v=y,
-342                        action=TestResultAction.REMOVE_EDGE_DIRECTED,
-343                        data={},
-344                    )
-345                )
-346        return results
+            
297class FurtherOrientTripleTest(
+298    PipelineStepInterface[PipelineStepInterfaceType], Generic[PipelineStepInterfaceType]
+299):
+300    generator: Optional[GeneratorInterface] = AllCombinationsGenerator(
+301        comparison_settings=ComparisonSettings(min=2, max=2)
+302    )
+303    chunk_size_parallel_processing: IntegerParameter = 1
+304    parallel: BoolParameter = False
+305
+306    def process(
+307        self, nodes: Tuple[str], graph: BaseGraphInterface
+308    ) -> Optional[List[TestResult] | TestResult]:
+309        """
+310        Further orientation rule.
+311        :param nodes: list of nodes
+312        :param graph: the current graph
+313        :returns: list of actions that will be executed on graph
+314        """
+315
+316        x = graph.nodes[nodes[0]]
+317        y = graph.nodes[nodes[1]]
+318
+319        results = []
+320        for z in graph.nodes:
+321            z = graph.nodes[z]
+322            # check if it is a potential z
+323            if not (graph.edge_exists(y, z) and graph.edge_exists(x, z)):
+324                continue
+325
+326            if (
+327                graph.undirected_edge_exists(x, y)
+328                and graph.only_directed_edge_exists(x, z)
+329                and graph.only_directed_edge_exists(z, y)
+330            ):
+331                results.append(
+332                    TestResult(
+333                        u=y,
+334                        v=x,
+335                        action=TestResultAction.REMOVE_EDGE_DIRECTED,
+336                        data={"between": {"x": x, "y": y, "z": z}},
+337                    )
+338                )
+339            if (
+340                graph.undirected_edge_exists(x, y)
+341                and graph.only_directed_edge_exists(y, z)
+342                and graph.only_directed_edge_exists(z, x)
+343            ):
+344                results.append(
+345                    TestResult(
+346                        u=x,
+347                        v=y,
+348                        action=TestResultAction.REMOVE_EDGE_DIRECTED,
+349                        data={"between": {"x": x, "y": y, "z": z}},
+350                    )
+351                )
+352        return results
 

 
 
@@ -1331,72 +1343,72 @@ 
Inherited Members
- 
349class OrientQuadrupleTest(
-350    PipelineStepInterface[PipelineStepInterfaceType], Generic[PipelineStepInterfaceType]
-351):
-352    generator: Optional[GeneratorInterface] = AllCombinationsGenerator(
-353        comparison_settings=ComparisonSettings(min=2, max=2)
-354    )
-355    chunk_size_parallel_processing: IntegerParameter = 1
-356    parallel: BoolParameter = False
-357
-358    def process(
-359        self, nodes: Tuple[str], graph: BaseGraphInterface
-360    ) -> Optional[List[TestResult] | TestResult]:
-361        """
-362        Further orientation rule.
-363        :param nodes: list of nodes
-364        :param graph: the current graph
-365        :returns: list of actions that will be executed on graph
-366        """
-367
-368        y = graph.nodes[nodes[0]]
-369        w = graph.nodes[nodes[1]]
-370
-371        potential_zs = set()
-372
-373        # TODO: just iterate over edges
-374        for z in graph.nodes:
-375            z = graph.nodes[z]
-376            if graph.edge_exists(y, z) and graph.edge_exists(z, w):
-377                potential_zs.add(z)
+            
355class OrientQuadrupleTest(
+356    PipelineStepInterface[PipelineStepInterfaceType], Generic[PipelineStepInterfaceType]
+357):
+358    generator: Optional[GeneratorInterface] = AllCombinationsGenerator(
+359        comparison_settings=ComparisonSettings(min=2, max=2)
+360    )
+361    chunk_size_parallel_processing: IntegerParameter = 1
+362    parallel: BoolParameter = False
+363
+364    def process(
+365        self, nodes: Tuple[str], graph: BaseGraphInterface
+366    ) -> Optional[List[TestResult] | TestResult]:
+367        """
+368        Further orientation rule.
+369        :param nodes: list of nodes
+370        :param graph: the current graph
+371        :returns: list of actions that will be executed on graph
+372        """
+373
+374        y = graph.nodes[nodes[0]]
+375        w = graph.nodes[nodes[1]]
+376
+377        potential_zs = set()
 378
-379        results = []
-380        for zs in itertools.combinations(potential_zs, 2):
-381            x, z = zs
-382            if (
-383                not graph.edge_exists(y, w)
-384                and graph.only_directed_edge_exists(y, z)
-385                and graph.only_directed_edge_exists(w, z)
-386                and graph.undirected_edge_exists(x, y)
-387                and graph.undirected_edge_exists(x, w)
-388                and graph.undirected_edge_exists(x, z)
-389            ):
-390                results.append(
-391                    TestResult(
-392                        u=z,
-393                        v=x,
-394                        action=TestResultAction.REMOVE_EDGE_DIRECTED,
-395                        data={},
-396                    )
-397                )
-398            if (
-399                not graph.edge_exists(y, w)
-400                and graph.only_directed_edge_exists(y, x)
-401                and graph.only_directed_edge_exists(w, x)
-402                and graph.undirected_edge_exists(y, z)
-403                and graph.undirected_edge_exists(w, z)
-404                and graph.undirected_edge_exists(x, z)
-405            ):
-406                results.append(
-407                    TestResult(
-408                        u=x,
-409                        v=z,
-410                        action=TestResultAction.REMOVE_EDGE_DIRECTED,
-411                        data={},
-412                    )
-413                )
-414        return results
+379        # TODO: just iterate over edges
+380        for z in graph.nodes:
+381            z = graph.nodes[z]
+382            if graph.edge_exists(y, z) and graph.edge_exists(z, w):
+383                potential_zs.add(z)
+384
+385        results = []
+386        for zs in itertools.combinations(potential_zs, 2):
+387            x, z = zs
+388            if (
+389                not graph.edge_exists(y, w)
+390                and graph.only_directed_edge_exists(y, z)
+391                and graph.only_directed_edge_exists(w, z)
+392                and graph.undirected_edge_exists(x, y)
+393                and graph.undirected_edge_exists(x, w)
+394                and graph.undirected_edge_exists(x, z)
+395            ):
+396                results.append(
+397                    TestResult(
+398                        u=z,
+399                        v=x,
+400                        action=TestResultAction.REMOVE_EDGE_DIRECTED,
+401                        data={},
+402                    )
+403                )
+404            if (
+405                not graph.edge_exists(y, w)
+406                and graph.only_directed_edge_exists(y, x)
+407                and graph.only_directed_edge_exists(w, x)
+408                and graph.undirected_edge_exists(y, z)
+409                and graph.undirected_edge_exists(w, z)
+410                and graph.undirected_edge_exists(x, z)
+411            ):
+412                results.append(
+413                    TestResult(
+414                        u=x,
+415                        v=z,
+416                        action=TestResultAction.REMOVE_EDGE_DIRECTED,
+417                        data={},
+418                    )
+419                )
+420        return results
 

 
 
@@ -1466,104 +1478,104 @@ 
Inherited Members
- 
417class FurtherOrientQuadrupleTest(
-418    PipelineStepInterface[PipelineStepInterfaceType], Generic[PipelineStepInterfaceType]
-419):
-420    generator: Optional[GeneratorInterface] = AllCombinationsGenerator(
-421        comparison_settings=ComparisonSettings(min=2, max=2)
-422    )
-423    chunk_size_parallel_processing: int = 1
-424    parallel: bool = False
-425
-426    def process(
-427        self, nodes: Tuple[str], graph: BaseGraphInterface
-428    ) -> Optional[List[TestResult] | TestResult]:
-429        """
-430        Further orientation rule.
-431        :param nodes: list of nodes
-432        :param graph: the current graph
-433        :returns: list of actions that will be executed on graph
-434        """
-435
-436        x = graph.nodes[nodes[0]]
-437        w = graph.nodes[nodes[1]]
-438
-439        potential_zs = set()
-440
-441        # TODO: just iterate over edges
-442        for z in graph.nodes:
-443            z = graph.nodes[z]
-444            if graph.edge_exists(x, z) and graph.edge_exists(z, w):
-445                potential_zs.add(z)
+            
423class FurtherOrientQuadrupleTest(
+424    PipelineStepInterface[PipelineStepInterfaceType], Generic[PipelineStepInterfaceType]
+425):
+426    generator: Optional[GeneratorInterface] = AllCombinationsGenerator(
+427        comparison_settings=ComparisonSettings(min=2, max=2)
+428    )
+429    chunk_size_parallel_processing: int = 1
+430    parallel: bool = False
+431
+432    def process(
+433        self, nodes: Tuple[str], graph: BaseGraphInterface
+434    ) -> Optional[List[TestResult] | TestResult]:
+435        """
+436        Further orientation rule.
+437        :param nodes: list of nodes
+438        :param graph: the current graph
+439        :returns: list of actions that will be executed on graph
+440        """
+441
+442        x = graph.nodes[nodes[0]]
+443        w = graph.nodes[nodes[1]]
+444
+445        potential_zs = set()
 446
-447        results = []
-448        for zs in itertools.combinations(potential_zs, 2):
-449            y, z = zs
-450            if (
-451                not graph.edge_exists(y, z)
-452                and graph.undirected_edge_exists(x, z)
-453                and graph.undirected_edge_exists(x, w)
-454                and graph.undirected_edge_exists(x, y)
-455                and graph.only_directed_edge_exists(y, w)
-456                and graph.only_directed_edge_exists(w, z)
-457            ):
-458                results.append(
-459                    TestResult(
-460                        u=z,
-461                        v=x,
-462                        action=TestResultAction.REMOVE_EDGE_DIRECTED,
-463                        data={},
-464                    )
-465                )
-466            elif (
-467                not graph.edge_exists(z, y)
-468                and graph.undirected_edge_exists(x, y)
-469                and graph.undirected_edge_exists(x, w)
-470                and graph.undirected_edge_exists(x, z)
-471                and graph.only_directed_edge_exists(z, w)
-472                and graph.only_directed_edge_exists(w, y)
-473            ):
-474                results.append(
-475                    TestResult(
-476                        u=y,
-477                        v=x,
-478                        action=TestResultAction.REMOVE_EDGE_DIRECTED,
-479                        data={},
-480                    )
-481                )
-482            elif (
-483                not graph.edge_exists(y, z)
-484                and graph.undirected_edge_exists(w, z)
-485                and graph.undirected_edge_exists(x, w)
-486                and graph.undirected_edge_exists(w, y)
-487                and graph.only_directed_edge_exists(y, x)
-488                and graph.only_directed_edge_exists(x, z)
-489            ):
-490                results.append(
-491                    TestResult(
-492                        u=z,
-493                        v=w,
-494                        action=TestResultAction.REMOVE_EDGE_DIRECTED,
-495                        data={},
-496                    )
-497                )
-498            elif (
-499                not graph.edge_exists(z, y)
-500                and graph.undirected_edge_exists(w, y)
-501                and graph.undirected_edge_exists(x, w)
-502                and graph.undirected_edge_exists(w, z)
-503                and graph.only_directed_edge_exists(z, x)
-504                and graph.only_directed_edge_exists(x, y)
-505            ):
-506                results.append(
-507                    TestResult(
-508                        u=y,
-509                        v=w,
-510                        action=TestResultAction.REMOVE_EDGE_DIRECTED,
-511                        data={},
-512                    )
-513                )
-514        return results
+447        # TODO: just iterate over edges
+448        for z in graph.nodes:
+449            z = graph.nodes[z]
+450            if graph.edge_exists(x, z) and graph.edge_exists(z, w):
+451                potential_zs.add(z)
+452
+453        results = []
+454        for zs in itertools.combinations(potential_zs, 2):
+455            y, z = zs
+456            if (
+457                not graph.edge_exists(y, z)
+458                and graph.undirected_edge_exists(x, z)
+459                and graph.undirected_edge_exists(x, w)
+460                and graph.undirected_edge_exists(x, y)
+461                and graph.only_directed_edge_exists(y, w)
+462                and graph.only_directed_edge_exists(w, z)
+463            ):
+464                results.append(
+465                    TestResult(
+466                        u=z,
+467                        v=x,
+468                        action=TestResultAction.REMOVE_EDGE_DIRECTED,
+469                        data={},
+470                    )
+471                )
+472            elif (
+473                not graph.edge_exists(z, y)
+474                and graph.undirected_edge_exists(x, y)
+475                and graph.undirected_edge_exists(x, w)
+476                and graph.undirected_edge_exists(x, z)
+477                and graph.only_directed_edge_exists(z, w)
+478                and graph.only_directed_edge_exists(w, y)
+479            ):
+480                results.append(
+481                    TestResult(
+482                        u=y,
+483                        v=x,
+484                        action=TestResultAction.REMOVE_EDGE_DIRECTED,
+485                        data={},
+486                    )
+487                )
+488            elif (
+489                not graph.edge_exists(y, z)
+490                and graph.undirected_edge_exists(w, z)
+491                and graph.undirected_edge_exists(x, w)
+492                and graph.undirected_edge_exists(w, y)
+493                and graph.only_directed_edge_exists(y, x)
+494                and graph.only_directed_edge_exists(x, z)
+495            ):
+496                results.append(
+497                    TestResult(
+498                        u=z,
+499                        v=w,
+500                        action=TestResultAction.REMOVE_EDGE_DIRECTED,
+501                        data={},
+502                    )
+503                )
+504            elif (
+505                not graph.edge_exists(z, y)
+506                and graph.undirected_edge_exists(w, y)
+507                and graph.undirected_edge_exists(x, w)
+508                and graph.undirected_edge_exists(w, z)
+509                and graph.only_directed_edge_exists(z, x)
+510                and graph.only_directed_edge_exists(x, y)
+511            ):
+512                results.append(
+513                    TestResult(
+514                        u=y,
+515                        v=w,
+516                        action=TestResultAction.REMOVE_EDGE_DIRECTED,
+517                        data={},
+518                    )
+519                )
+520        return results
 

 
 
diff --git a/causy/graph.html b/causy/graph.html
index 43e51ae..0b9c907 100644
--- a/causy/graph.html
+++ b/causy/graph.html
@@ -3120,7 +3120,7 @@ 
Returns

 

             
     class
-    Graph(GraphBaseAccessMixin, pydantic.main.BaseModel, causy.interfaces.ExtensionInterface.GraphAccessMixin, causy.edge_types.DirectedEdge.GraphAccessMixin, causy.interfaces.EdgeTypeInterface.GraphAccessMixin):
+    Graph(causy.interfaces.ExtensionInterface.GraphAccessMixin, causy.edge_types.DirectedEdge.GraphAccessMixin, GraphBaseAccessMixin, causy.interfaces.EdgeTypeInterface.GraphAccessMixin, pydantic.main.BaseModel):
 
                 
 
@@ -3136,33 +3136,8 @@ 
Returns
-

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

- -

A base class for creating Pydantic models.

- -

Attributes: - __class_vars__: The names of classvars defined on the model. - __private_attributes__: Metadata about the private attributes of the model. - __signature__: The signature for instantiating the model.

- -
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.
-__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.
-__pydantic_custom_init__: Whether the model has a custom `__init__` function.
-__pydantic_decorators__: Metadata containing the decorators defined on the model.
-    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.
-__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to
-    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.
-__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.
-__pydantic_post_init__: The name of the post-init method for the model, if defined.
-__pydantic_root_model__: Whether the model is a `RootModel`.
-__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.
-__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.
-
-__pydantic_extra__: An instance attribute with the values of extra fields from validation when
-    `model_config['extra'] == 'allow'`.
-__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.
-__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.
-
+

Helper class that provides a standard way to create an ABC using +inheritance.

@@ -3318,6 +3293,11 @@
Inherited Members
validate
update_forward_refs
+
+
causy.edge_types.DirectedEdge.GraphAccessMixin
+
only_directed_edge_exists
+
directed_paths
+
GraphBaseAccessMixin
directed_edge_is_soft_deleted
@@ -3338,11 +3318,6 @@
Inherited Members
all_paths_on_underlying_undirected_graph
retrieve_edges
-
-
causy.edge_types.DirectedEdge.GraphAccessMixin
-
only_directed_edge_exists
-
directed_paths
-
diff --git a/causy/graph_model.html b/causy/graph_model.html index 0b313d9..c363c70 100644 --- a/causy/graph_model.html +++ b/causy/graph_model.html @@ -1268,7 +1268,7 @@

- pool: <bound method BaseContext.Pool of <multiprocessing.context.DefaultContext object at 0x7f6aea3b4b00>> + pool: <bound method BaseContext.Pool of <multiprocessing.context.DefaultContext object at 0x7f4ad89b9460>>
diff --git a/causy/interfaces.html b/causy/interfaces.html index d1153da..c63c2d9 100644 --- a/causy/interfaces.html +++ b/causy/interfaces.html @@ -2706,7 +2706,7 @@
Inherited Members
- pool: <bound method BaseContext.Pool of <multiprocessing.context.DefaultContext object at 0x7f6aea3b4b00>> + pool: <bound method BaseContext.Pool of <multiprocessing.context.DefaultContext object at 0x7f4ad89b9460>>
diff --git a/search.js b/search.js index b8e1e58..049acb4 100644 --- a/search.js +++ b/search.js @@ -1,6 +1,6 @@ window.pdocSearch = (function(){ /** elasticlunr - http://weixsong.github.io * Copyright (C) 2017 Oliver Nightingale * Copyright (C) 2017 Wei Song * MIT Licensed */!function(){function e(e){if(null===e||"object"!=typeof e)return e;var t=e.constructor();for(var n in e)e.hasOwnProperty(n)&&(t[n]=e[n]);return t}var t=function(e){var n=new t.Index;return n.pipeline.add(t.trimmer,t.stopWordFilter,t.stemmer),e&&e.call(n,n),n};t.version="0.9.5",lunr=t,t.utils={},t.utils.warn=function(e){return function(t){e.console&&console.warn&&console.warn(t)}}(this),t.utils.toString=function(e){return void 0===e||null===e?"":e.toString()},t.EventEmitter=function(){this.events={}},t.EventEmitter.prototype.addListener=function(){var e=Array.prototype.slice.call(arguments),t=e.pop(),n=e;if("function"!=typeof t)throw new TypeError("last argument must be a function");n.forEach(function(e){this.hasHandler(e)||(this.events[e]=[]),this.events[e].push(t)},this)},t.EventEmitter.prototype.removeListener=function(e,t){if(this.hasHandler(e)){var n=this.events[e].indexOf(t);-1!==n&&(this.events[e].splice(n,1),0==this.events[e].length&&delete this.events[e])}},t.EventEmitter.prototype.emit=function(e){if(this.hasHandler(e)){var t=Array.prototype.slice.call(arguments,1);this.events[e].forEach(function(e){e.apply(void 0,t)},this)}},t.EventEmitter.prototype.hasHandler=function(e){return e in this.events},t.tokenizer=function(e){if(!arguments.length||null===e||void 0===e)return[];if(Array.isArray(e)){var n=e.filter(function(e){return null===e||void 0===e?!1:!0});n=n.map(function(e){return t.utils.toString(e).toLowerCase()});var i=[];return n.forEach(function(e){var n=e.split(t.tokenizer.seperator);i=i.concat(n)},this),i}return e.toString().trim().toLowerCase().split(t.tokenizer.seperator)},t.tokenizer.defaultSeperator=/[\s\-]+/,t.tokenizer.seperator=t.tokenizer.defaultSeperator,t.tokenizer.setSeperator=function(e){null!==e&&void 0!==e&&"object"==typeof e&&(t.tokenizer.seperator=e)},t.tokenizer.resetSeperator=function(){t.tokenizer.seperator=t.tokenizer.defaultSeperator},t.tokenizer.getSeperator=function(){return t.tokenizer.seperator},t.Pipeline=function(){this._queue=[]},t.Pipeline.registeredFunctions={},t.Pipeline.registerFunction=function(e,n){n in t.Pipeline.registeredFunctions&&t.utils.warn("Overwriting existing registered function: "+n),e.label=n,t.Pipeline.registeredFunctions[n]=e},t.Pipeline.getRegisteredFunction=function(e){return e in t.Pipeline.registeredFunctions!=!0?null:t.Pipeline.registeredFunctions[e]},t.Pipeline.warnIfFunctionNotRegistered=function(e){var n=e.label&&e.label in this.registeredFunctions;n||t.utils.warn("Function is not registered with pipeline. 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e.elements=this.toArray(),e.length=e.elements.length,e},lunr.SortedSet.prototype.union=function(e){var t,n,i;this.length>=e.length?(t=this,n=e):(t=e,n=this),i=t.clone();for(var o=0,r=n.toArray();ocausy

\n\n

Causal discovery made easy. Causy allows you to use and implement causal discovery algorithms with easy to use, extend and maintain pipelines. It is built based on pytorch which allows you to run the algorithms on CPUs as well as GPUs seamlessly.

\n\n

Learn more at https://causy.dev.

\n"}, "causy.causal_discovery": {"fullname": "causy.causal_discovery", "modulename": "causy.causal_discovery", "kind": "module", "doc": "

\n"}, "causy.causal_discovery.constraint": {"fullname": "causy.causal_discovery.constraint", "modulename": "causy.causal_discovery.constraint", "kind": "module", "doc": "

\n"}, "causy.causal_discovery.constraint.algorithms": {"fullname": "causy.causal_discovery.constraint.algorithms", "modulename": "causy.causal_discovery.constraint.algorithms", "kind": "module", "doc": "

\n"}, "causy.causal_discovery.constraint.algorithms.AVAILABLE_ALGORITHMS": {"fullname": "causy.causal_discovery.constraint.algorithms.AVAILABLE_ALGORITHMS", "modulename": "causy.causal_discovery.constraint.algorithms", "qualname": "AVAILABLE_ALGORITHMS", "kind": "variable", "doc": "

\n", "default_value": "{'PC': <class 'causy.graph_model.graph_model_factory.<locals>.GraphModel'>, 'ParallelPC': <class 'causy.graph_model.graph_model_factory.<locals>.GraphModel'>}"}, "causy.causal_discovery.constraint.algorithms.fci": {"fullname": "causy.causal_discovery.constraint.algorithms.fci", "modulename": "causy.causal_discovery.constraint.algorithms.fci", "kind": "module", "doc": "

\n"}, "causy.causal_discovery.constraint.algorithms.fci.InducingPathExtension": {"fullname": "causy.causal_discovery.constraint.algorithms.fci.InducingPathExtension", "modulename": "causy.causal_discovery.constraint.algorithms.fci", "qualname": "InducingPathExtension", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel, typing.Generic[~ExtensionType]"}, "causy.causal_discovery.constraint.algorithms.fci.InducingPathExtension.GraphAccessMixin": {"fullname": "causy.causal_discovery.constraint.algorithms.fci.InducingPathExtension.GraphAccessMixin", "modulename": "causy.causal_discovery.constraint.algorithms.fci", "qualname": "InducingPathExtension.GraphAccessMixin", "kind": "class", "doc": "

\n"}, "causy.causal_discovery.constraint.algorithms.fci.InducingPathExtension.GraphAccessMixin.inducing_path_exists": {"fullname": "causy.causal_discovery.constraint.algorithms.fci.InducingPathExtension.GraphAccessMixin.inducing_path_exists", "modulename": "causy.causal_discovery.constraint.algorithms.fci", "qualname": "InducingPathExtension.GraphAccessMixin.inducing_path_exists", "kind": "function", "doc": "

Check if an inducing path from u to v exists.\nAn inducing path from u to v is a directed reference from u to v on which all mediators are colliders.

\n\n
Parameters
\n\n
    \n
  • u: node u
    • \n
  • v: node v
    • \n
\n\n
Returns
\n\n
\n

True if an inducing path exists, False otherwise

\n
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str]) -> bool:", "funcdef": "def"}, "causy.causal_discovery.constraint.algorithms.pc": {"fullname": "causy.causal_discovery.constraint.algorithms.pc", "modulename": "causy.causal_discovery.constraint.algorithms.pc", "kind": "module", "doc": "

\n"}, "causy.causal_discovery.constraint.algorithms.pc.PC_DEFAULT_THRESHOLD": {"fullname": "causy.causal_discovery.constraint.algorithms.pc.PC_DEFAULT_THRESHOLD", "modulename": "causy.causal_discovery.constraint.algorithms.pc", "qualname": "PC_DEFAULT_THRESHOLD", "kind": "variable", "doc": "

\n", "default_value": "0.005"}, "causy.causal_discovery.constraint.algorithms.pc.PC_ORIENTATION_RULES": {"fullname": "causy.causal_discovery.constraint.algorithms.pc.PC_ORIENTATION_RULES", "modulename": "causy.causal_discovery.constraint.algorithms.pc", "qualname": "PC_ORIENTATION_RULES", "kind": "variable", "doc": "

\n", "default_value": "[ColliderTest(generator=AllCombinationsGenerator(comparison_settings=ComparisonSettings(min=2, max=2, name='causy.models.ComparisonSettings'), chunked=False, every_nth=None, generator=None, shuffle_combinations=None, name='causy.generators.AllCombinationsGenerator'), threshold=0.01, chunk_size_parallel_processing=1, parallel=False, display_name='Collider Test', needs_unapplied_actions=True, apply_synchronous=False, conflict_resolution_strategy=<ColliderTestConflictResolutionStrategies.KEEP_FIRST: 'KEEP_FIRST'>, name='causy.causal_discovery.constraint.orientation_rules.pc.ColliderTest'), Loop(pipeline_steps=[NonColliderTest(generator=AllCombinationsGenerator(comparison_settings=ComparisonSettings(min=2, max=2, name='causy.models.ComparisonSettings'), chunked=False, every_nth=None, generator=None, shuffle_combinations=None, name='causy.generators.AllCombinationsGenerator'), threshold=0.01, chunk_size_parallel_processing=1, parallel=False, display_name='Non-Collider Test', needs_unapplied_actions=False, apply_synchronous=False, name='causy.causal_discovery.constraint.orientation_rules.pc.NonColliderTest'), FurtherOrientTripleTest(generator=AllCombinationsGenerator(comparison_settings=ComparisonSettings(min=2, max=2, name='causy.models.ComparisonSettings'), chunked=False, every_nth=None, generator=None, shuffle_combinations=None, name='causy.generators.AllCombinationsGenerator'), threshold=0.01, chunk_size_parallel_processing=1, parallel=False, display_name='Further Orient Triple Test', needs_unapplied_actions=False, apply_synchronous=False, name='causy.causal_discovery.constraint.orientation_rules.pc.FurtherOrientTripleTest'), OrientQuadrupleTest(generator=AllCombinationsGenerator(comparison_settings=ComparisonSettings(min=2, max=2, name='causy.models.ComparisonSettings'), chunked=False, every_nth=None, generator=None, shuffle_combinations=None, name='causy.generators.AllCombinationsGenerator'), threshold=0.01, chunk_size_parallel_processing=1, parallel=False, display_name='Orient Quadruple Test', needs_unapplied_actions=False, apply_synchronous=False, name='causy.causal_discovery.constraint.orientation_rules.pc.OrientQuadrupleTest'), FurtherOrientQuadrupleTest(generator=AllCombinationsGenerator(comparison_settings=ComparisonSettings(min=2, max=2, name='causy.models.ComparisonSettings'), chunked=False, every_nth=None, generator=None, shuffle_combinations=None, name='causy.generators.AllCombinationsGenerator'), threshold=0.01, chunk_size_parallel_processing=1, parallel=False, display_name='Further Orient Quadruple Test', needs_unapplied_actions=False, apply_synchronous=False, name='causy.causal_discovery.constraint.orientation_rules.pc.FurtherOrientQuadrupleTest')], exit_condition=ExitOnNoActions(name='causy.common_pipeline_steps.exit_conditions.ExitOnNoActions'), display_name='Orientation Rules Loop', name='causy.common_pipeline_steps.logic.Loop')]"}, "causy.causal_discovery.constraint.algorithms.pc.PC_GRAPH_UI_EXTENSION": {"fullname": "causy.causal_discovery.constraint.algorithms.pc.PC_GRAPH_UI_EXTENSION", "modulename": "causy.causal_discovery.constraint.algorithms.pc", "qualname": "PC_GRAPH_UI_EXTENSION", "kind": "variable", "doc": "

\n", "default_value": "GraphUIExtension(edges=[DirectedEdgeUIConfig(edge_type='DIRECTED', default_ui_config=EdgeUIConfig(color='#333', width=4, style='dashed', marker_start=None, marker_end='ArrowClosed', label_field='correlation', animated=True, label='Direct Effect: ${correlation.toFixed(4)}'), conditional_ui_configs=[ConditionalEdgeUIConfig(ui_config=EdgeUIConfig(color='#f00000', width=4, style='dashed', marker_start=None, marker_end='ArrowClosed', label_field='direct_effect', animated=True, label='Direct Effect: ${direct_effect.toFixed(4)}'), condition_field='direct_effect', condition_value=0.0, condition_comparison=<ConditionalEdgeUIConfigComparison.LESS: 'LESS'>), ConditionalEdgeUIConfig(ui_config=EdgeUIConfig(color='#0f0fff', width=4, style='dashed', marker_start=None, marker_end='ArrowClosed', label_field='direct_effect', animated=True, label='Direct Effect: ${direct_effect.toFixed(4)}'), condition_field='direct_effect', condition_value=0.0, condition_comparison=<ConditionalEdgeUIConfigComparison.GREATER: 'GREATER'>)]), UndirectedEdgeUIConfig(edge_type='UNDIRECTED', default_ui_config=EdgeUIConfig(color='#333', width=4, style='solid', marker_start=None, marker_end=None, label_field='direct_effect', animated=False, label='Correlation: ${correlation.toFixed(4)}'), conditional_ui_configs=None)], name='causy.contrib.graph_ui.GraphUIExtension')"}, "causy.causal_discovery.constraint.algorithms.pc.PC_EDGE_TYPES": {"fullname": "causy.causal_discovery.constraint.algorithms.pc.PC_EDGE_TYPES", "modulename": "causy.causal_discovery.constraint.algorithms.pc", "qualname": "PC_EDGE_TYPES", "kind": "variable", "doc": "

\n", "default_value": "[DIRECTED, UNDIRECTED]"}, "causy.causal_discovery.constraint.algorithms.pc.PC": {"fullname": "causy.causal_discovery.constraint.algorithms.pc.PC", "modulename": "causy.causal_discovery.constraint.algorithms.pc", "qualname": "PC", "kind": "variable", "doc": "

\n", "default_value": "<class 'causy.graph_model.graph_model_factory.<locals>.GraphModel'>"}, "causy.causal_discovery.constraint.algorithms.pc.PCClassic": {"fullname": "causy.causal_discovery.constraint.algorithms.pc.PCClassic", "modulename": "causy.causal_discovery.constraint.algorithms.pc", "qualname": "PCClassic", "kind": "variable", "doc": "

\n", "default_value": "<class 'causy.graph_model.graph_model_factory.<locals>.GraphModel'>"}, "causy.causal_discovery.constraint.algorithms.pc.PCStable": {"fullname": "causy.causal_discovery.constraint.algorithms.pc.PCStable", "modulename": "causy.causal_discovery.constraint.algorithms.pc", "qualname": "PCStable", "kind": "variable", "doc": "

\n", "default_value": "<class 'causy.graph_model.graph_model_factory.<locals>.GraphModel'>"}, "causy.causal_discovery.constraint.algorithms.pc.ParallelPC": {"fullname": "causy.causal_discovery.constraint.algorithms.pc.ParallelPC", "modulename": "causy.causal_discovery.constraint.algorithms.pc", "qualname": "ParallelPC", "kind": "variable", "doc": "

\n", "default_value": "<class 'causy.graph_model.graph_model_factory.<locals>.GraphModel'>"}, "causy.causal_discovery.constraint.independence_tests": {"fullname": "causy.causal_discovery.constraint.independence_tests", "modulename": "causy.causal_discovery.constraint.independence_tests", "kind": "module", "doc": "

\n"}, "causy.causal_discovery.constraint.independence_tests.common": {"fullname": "causy.causal_discovery.constraint.independence_tests.common", "modulename": "causy.causal_discovery.constraint.independence_tests.common", "kind": "module", "doc": "

\n"}, "causy.causal_discovery.constraint.independence_tests.common.logger": {"fullname": "causy.causal_discovery.constraint.independence_tests.common.logger", "modulename": "causy.causal_discovery.constraint.independence_tests.common", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.causal_discovery.constraint.independence_tests.common (WARNING)>"}, "causy.causal_discovery.constraint.independence_tests.common.CorrelationCoefficientTest": {"fullname": "causy.causal_discovery.constraint.independence_tests.common.CorrelationCoefficientTest", "modulename": "causy.causal_discovery.constraint.independence_tests.common", "qualname": "CorrelationCoefficientTest", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.causal_discovery.constraint.independence_tests.common.PartialCorrelationTest": {"fullname": "causy.causal_discovery.constraint.independence_tests.common.PartialCorrelationTest", "modulename": "causy.causal_discovery.constraint.independence_tests.common", "qualname": "PartialCorrelationTest", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.causal_discovery.constraint.independence_tests.common.ExtendedPartialCorrelationTestMatrix": {"fullname": "causy.causal_discovery.constraint.independence_tests.common.ExtendedPartialCorrelationTestMatrix", "modulename": "causy.causal_discovery.constraint.independence_tests.common", "qualname": "ExtendedPartialCorrelationTestMatrix", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.causal_discovery.constraint.independence_tests.common.partial_correlation_regression": {"fullname": "causy.causal_discovery.constraint.independence_tests.common.partial_correlation_regression", "modulename": "causy.causal_discovery.constraint.independence_tests.common", "qualname": "partial_correlation_regression", "kind": "function", "doc": "

Compute the partial correlation coefficient between x and y controlling for other variables in z using linear regression.

\n\n

Arguments:\nx, y : torch.Tensor : Variables for which the partial correlation is computed.\nz : torch.Tensor : Other variables used to control for in the partial correlation.

\n\n

Returns:\npartial_corr : torch.Tensor : Partial correlation coefficient between x and y.

\n", "signature": "(x, y, z):", "funcdef": "def"}, "causy.causal_discovery.constraint.independence_tests.common.ExtendedPartialCorrelationTestLinearRegression": {"fullname": "causy.causal_discovery.constraint.independence_tests.common.ExtendedPartialCorrelationTestLinearRegression", "modulename": "causy.causal_discovery.constraint.independence_tests.common", "qualname": "ExtendedPartialCorrelationTestLinearRegression", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.causal_discovery.constraint.orientation_rules": {"fullname": "causy.causal_discovery.constraint.orientation_rules", "modulename": "causy.causal_discovery.constraint.orientation_rules", "kind": "module", "doc": "

\n"}, "causy.causal_discovery.constraint.orientation_rules.fci": {"fullname": "causy.causal_discovery.constraint.orientation_rules.fci", "modulename": "causy.causal_discovery.constraint.orientation_rules.fci", "kind": "module", "doc": "

\n"}, "causy.causal_discovery.constraint.orientation_rules.fci.ColliderRuleFCI": {"fullname": "causy.causal_discovery.constraint.orientation_rules.fci.ColliderRuleFCI", "modulename": "causy.causal_discovery.constraint.orientation_rules.fci", "qualname": "ColliderRuleFCI", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.causal_discovery.constraint.orientation_rules.pc": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "kind": "module", "doc": "

\n"}, "causy.causal_discovery.constraint.orientation_rules.pc.logger": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.logger", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.causal_discovery.constraint.orientation_rules.pc (WARNING)>"}, "causy.causal_discovery.constraint.orientation_rules.pc.filter_unapplied_actions": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.filter_unapplied_actions", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "filter_unapplied_actions", "kind": "function", "doc": "

Filter out actions that have not been applied to the graph yet.

\n\n
Parameters
\n\n
    \n
  • actions: list of actions
    • \n
  • u: node u
    • \n
  • v: node v
    • \n
\n\n
Returns
\n\n
\n

list of actions that have not been applied to the graph yet

\n
\n", "signature": "(actions, u, v):", "funcdef": "def"}, "causy.causal_discovery.constraint.orientation_rules.pc.generate_restores": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.generate_restores", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "generate_restores", "kind": "function", "doc": "

Generate restore actions for unapplied actions.

\n\n
Parameters
\n\n
    \n
  • unapplied_actions: list of unapplied actions
    • \n
  • x: node x
    • \n
  • y: node y
    • \n
\n\n
Returns
\n\n
\n

list of restore actions

\n
\n", "signature": "(unapplied_actions):", "funcdef": "def"}, "causy.causal_discovery.constraint.orientation_rules.pc.ColliderTestConflictResolutionStrategies": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.ColliderTestConflictResolutionStrategies", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "ColliderTestConflictResolutionStrategies", "kind": "class", "doc": "

Enum for the conflict resolution strategies for the ColliderTest.

\n", "bases": "builtins.str, enum.Enum"}, "causy.causal_discovery.constraint.orientation_rules.pc.ColliderTestConflictResolutionStrategies.KEEP_FIRST": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.ColliderTestConflictResolutionStrategies.KEEP_FIRST", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "ColliderTestConflictResolutionStrategies.KEEP_FIRST", "kind": "variable", "doc": "

\n", "default_value": "<ColliderTestConflictResolutionStrategies.KEEP_FIRST: 'KEEP_FIRST'>"}, "causy.causal_discovery.constraint.orientation_rules.pc.ColliderTestConflictResolutionStrategies.KEEP_LAST": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.ColliderTestConflictResolutionStrategies.KEEP_LAST", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "ColliderTestConflictResolutionStrategies.KEEP_LAST", "kind": "variable", "doc": "

\n", "default_value": "<ColliderTestConflictResolutionStrategies.KEEP_LAST: 'KEEP_LAST'>"}, "causy.causal_discovery.constraint.orientation_rules.pc.ColliderTest": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.ColliderTest", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "ColliderTest", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.causal_discovery.constraint.orientation_rules.pc.ColliderTest.conflict_resolution_strategy": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.ColliderTest.conflict_resolution_strategy", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "ColliderTest.conflict_resolution_strategy", "kind": "variable", "doc": "

\n", "annotation": ": Union[str, causy.variables.VariableReference]"}, "causy.causal_discovery.constraint.orientation_rules.pc.NonColliderTest": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.NonColliderTest", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "NonColliderTest", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.causal_discovery.constraint.orientation_rules.pc.FurtherOrientTripleTest": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.FurtherOrientTripleTest", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "FurtherOrientTripleTest", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.causal_discovery.constraint.orientation_rules.pc.OrientQuadrupleTest": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.OrientQuadrupleTest", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "OrientQuadrupleTest", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.causal_discovery.constraint.orientation_rules.pc.FurtherOrientQuadrupleTest": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.FurtherOrientQuadrupleTest", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "FurtherOrientQuadrupleTest", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.cli": {"fullname": "causy.cli", "modulename": "causy.cli", "kind": "module", "doc": "

\n"}, "causy.cli.app": {"fullname": "causy.cli.app", "modulename": "causy.cli", "qualname": "app", "kind": "variable", "doc": "

\n", "default_value": "<typer.main.Typer object>"}, "causy.cli.eject": {"fullname": "causy.cli.eject", "modulename": "causy.cli", "qualname": "eject", "kind": "function", "doc": "

\n", "signature": "(algorithm: str, output_file: str):", "funcdef": "def"}, "causy.cli.execute": {"fullname": "causy.cli.execute", "modulename": "causy.cli", "qualname": "execute", "kind": "function", "doc": "

\n", "signature": "(\tdata_file: str,\tpipeline: str = None,\talgorithm: str = None,\toutput_file: str = None,\tlog_level: str = 'ERROR'):", "funcdef": "def"}, "causy.common_pipeline_steps": {"fullname": "causy.common_pipeline_steps", "modulename": "causy.common_pipeline_steps", "kind": "module", "doc": "

\n"}, "causy.common_pipeline_steps.calculation": {"fullname": "causy.common_pipeline_steps.calculation", "modulename": "causy.common_pipeline_steps.calculation", "kind": "module", "doc": "

\n"}, "causy.common_pipeline_steps.calculation.CalculatePearsonCorrelations": {"fullname": "causy.common_pipeline_steps.calculation.CalculatePearsonCorrelations", "modulename": "causy.common_pipeline_steps.calculation", "qualname": "CalculatePearsonCorrelations", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.common_pipeline_steps.exit_conditions": {"fullname": "causy.common_pipeline_steps.exit_conditions", "modulename": "causy.common_pipeline_steps.exit_conditions", "kind": "module", "doc": "

\n"}, "causy.common_pipeline_steps.exit_conditions.ExitOnNoActions": {"fullname": "causy.common_pipeline_steps.exit_conditions.ExitOnNoActions", "modulename": "causy.common_pipeline_steps.exit_conditions", "qualname": "ExitOnNoActions", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.ExitConditionInterface"}, "causy.common_pipeline_steps.exit_conditions.ExitOnNoActions.check": {"fullname": "causy.common_pipeline_steps.exit_conditions.ExitOnNoActions.check", "modulename": "causy.common_pipeline_steps.exit_conditions", "qualname": "ExitOnNoActions.check", "kind": "function", "doc": "

Check if there are no actions taken in the last iteration and if so, break the loop\nIf it is the first iteration, do not break the loop (we need to execute the first step)

\n\n
Parameters
\n\n
    \n
  • graph: the graph
    • \n
  • graph_model_instance_: the graph model instance
    • \n
  • actions_taken: the actions taken in the last iteration
    • \n
  • iteration: iteration number
    • \n
\n\n
Returns
\n\n
\n

True if you want to break an iteration, False otherwise

\n
\n", "signature": "(self, graph, graph_model_instance_, actions_taken, iteration) -> bool:", "funcdef": "def"}, "causy.common_pipeline_steps.exit_conditions.ExitOnNoActions.model_config": {"fullname": "causy.common_pipeline_steps.exit_conditions.ExitOnNoActions.model_config", "modulename": "causy.common_pipeline_steps.exit_conditions", "qualname": "ExitOnNoActions.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.common_pipeline_steps.exit_conditions.ExitOnNoActions.model_fields": {"fullname": "causy.common_pipeline_steps.exit_conditions.ExitOnNoActions.model_fields", "modulename": "causy.common_pipeline_steps.exit_conditions", "qualname": "ExitOnNoActions.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.common_pipeline_steps.exit_conditions.ExitOnNoActions.model_computed_fields": {"fullname": "causy.common_pipeline_steps.exit_conditions.ExitOnNoActions.model_computed_fields", "modulename": "causy.common_pipeline_steps.exit_conditions", "qualname": "ExitOnNoActions.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': ComputedFieldInfo(wrapped_property=<property object>, return_type=<class 'str'>, alias=None, alias_priority=None, title=None, field_title_generator=None, description=None, deprecated=None, examples=None, json_schema_extra=None, repr=True)}"}, "causy.common_pipeline_steps.logic": {"fullname": "causy.common_pipeline_steps.logic", "modulename": "causy.common_pipeline_steps.logic", "kind": "module", "doc": "

\n"}, "causy.common_pipeline_steps.logic.Loop": {"fullname": "causy.common_pipeline_steps.logic.Loop", "modulename": "causy.common_pipeline_steps.logic", "qualname": "Loop", "kind": "class", "doc": "

A loop which executes a list of pipeline_steps until the exit_condition is met.

\n", "bases": "causy.interfaces.LogicStepInterface, typing.Generic[~LogicStepInterfaceType]"}, "causy.common_pipeline_steps.logic.ApplyActionsTogether": {"fullname": "causy.common_pipeline_steps.logic.ApplyActionsTogether", "modulename": "causy.common_pipeline_steps.logic", "qualname": "ApplyActionsTogether", "kind": "class", "doc": "

A logic step which collects all actions and only takes them at the end of the pipeline

\n", "bases": "causy.interfaces.LogicStepInterface, typing.Generic[~LogicStepInterfaceType]"}, "causy.common_pipeline_steps.placeholder": {"fullname": "causy.common_pipeline_steps.placeholder", "modulename": "causy.common_pipeline_steps.placeholder", "kind": "module", "doc": "

\n"}, "causy.common_pipeline_steps.placeholder.logger": {"fullname": "causy.common_pipeline_steps.placeholder.logger", "modulename": "causy.common_pipeline_steps.placeholder", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.common_pipeline_steps.placeholder (WARNING)>"}, "causy.common_pipeline_steps.placeholder.PlaceholderTest": {"fullname": "causy.common_pipeline_steps.placeholder.PlaceholderTest", "modulename": "causy.common_pipeline_steps.placeholder", "qualname": "PlaceholderTest", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.common_pipeline_steps.placeholder.PlaceholderTest.placeholder_str": {"fullname": "causy.common_pipeline_steps.placeholder.PlaceholderTest.placeholder_str", "modulename": "causy.common_pipeline_steps.placeholder", "qualname": "PlaceholderTest.placeholder_str", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.variables.StringVariable]"}, "causy.common_pipeline_steps.placeholder.PlaceholderTest.placeholder_int": {"fullname": "causy.common_pipeline_steps.placeholder.PlaceholderTest.placeholder_int", "modulename": "causy.common_pipeline_steps.placeholder", "qualname": "PlaceholderTest.placeholder_int", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.variables.IntegerVariable]"}, "causy.common_pipeline_steps.placeholder.PlaceholderTest.placeholder_float": {"fullname": "causy.common_pipeline_steps.placeholder.PlaceholderTest.placeholder_float", "modulename": "causy.common_pipeline_steps.placeholder", "qualname": "PlaceholderTest.placeholder_float", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.variables.FloatVariable]"}, "causy.common_pipeline_steps.placeholder.PlaceholderTest.placeholder_bool": {"fullname": "causy.common_pipeline_steps.placeholder.PlaceholderTest.placeholder_bool", "modulename": "causy.common_pipeline_steps.placeholder", "qualname": "PlaceholderTest.placeholder_bool", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.variables.BoolVariable]"}, "causy.data_loader": {"fullname": "causy.data_loader", "modulename": "causy.data_loader", "kind": "module", "doc": "

\n"}, "causy.data_loader.DataLoaderType": {"fullname": "causy.data_loader.DataLoaderType", "modulename": "causy.data_loader", "qualname": "DataLoaderType", "kind": "class", "doc": "

str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str

\n\n

Create a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to sys.getdefaultencoding().\nerrors defaults to 'strict'.

\n", "bases": "builtins.str, enum.Enum"}, "causy.data_loader.DataLoaderType.DYNAMIC": {"fullname": "causy.data_loader.DataLoaderType.DYNAMIC", "modulename": "causy.data_loader", "qualname": "DataLoaderType.DYNAMIC", "kind": "variable", "doc": "

\n", "default_value": "<DataLoaderType.DYNAMIC: 'dynamic'>"}, "causy.data_loader.DataLoaderType.JSON": {"fullname": "causy.data_loader.DataLoaderType.JSON", "modulename": "causy.data_loader", "qualname": "DataLoaderType.JSON", "kind": "variable", "doc": "

\n", "default_value": "<DataLoaderType.JSON: 'json'>"}, "causy.data_loader.DataLoaderType.JSONL": {"fullname": "causy.data_loader.DataLoaderType.JSONL", "modulename": "causy.data_loader", "qualname": "DataLoaderType.JSONL", "kind": "variable", "doc": "

\n", "default_value": "<DataLoaderType.JSONL: 'jsonl'>"}, "causy.data_loader.DataLoaderReference": {"fullname": "causy.data_loader.DataLoaderReference", "modulename": "causy.data_loader", "qualname": "DataLoaderReference", "kind": "class", "doc": "

represents a single data loader

\n\n
Parameters
\n\n
    \n
  • type: the type of dataloader
    • \n
  • reference: path to either the python class which can be executed to load the data or the data source file itself
    • \n
\n", "bases": "pydantic.main.BaseModel"}, "causy.data_loader.DataLoaderReference.type": {"fullname": "causy.data_loader.DataLoaderReference.type", "modulename": "causy.data_loader", "qualname": "DataLoaderReference.type", "kind": "variable", "doc": "

\n", "annotation": ": causy.data_loader.DataLoaderType"}, "causy.data_loader.DataLoaderReference.reference": {"fullname": "causy.data_loader.DataLoaderReference.reference", "modulename": "causy.data_loader", "qualname": "DataLoaderReference.reference", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.data_loader.DataLoaderReference.options": {"fullname": "causy.data_loader.DataLoaderReference.options", "modulename": "causy.data_loader", "qualname": "DataLoaderReference.options", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict[str, Any]]"}, "causy.data_loader.DataLoaderReference.model_config": {"fullname": "causy.data_loader.DataLoaderReference.model_config", "modulename": "causy.data_loader", "qualname": "DataLoaderReference.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.data_loader.DataLoaderReference.model_fields": {"fullname": "causy.data_loader.DataLoaderReference.model_fields", "modulename": "causy.data_loader", "qualname": "DataLoaderReference.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'type': FieldInfo(annotation=DataLoaderType, required=True), 'reference': FieldInfo(annotation=str, required=True), 'options': FieldInfo(annotation=Union[Dict[str, Any], NoneType], required=False, default=None)}"}, "causy.data_loader.DataLoaderReference.model_computed_fields": {"fullname": "causy.data_loader.DataLoaderReference.model_computed_fields", "modulename": "causy.data_loader", "qualname": "DataLoaderReference.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.data_loader.AbstractDataLoader": {"fullname": "causy.data_loader.AbstractDataLoader", "modulename": "causy.data_loader", "qualname": "AbstractDataLoader", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC"}, "causy.data_loader.AbstractDataLoader.reference": {"fullname": "causy.data_loader.AbstractDataLoader.reference", "modulename": "causy.data_loader", "qualname": "AbstractDataLoader.reference", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.data_loader.AbstractDataLoader.options": {"fullname": "causy.data_loader.AbstractDataLoader.options", "modulename": "causy.data_loader", "qualname": "AbstractDataLoader.options", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict[str, Any]]", "default_value": "None"}, "causy.data_loader.AbstractDataLoader.load": {"fullname": "causy.data_loader.AbstractDataLoader.load", "modulename": "causy.data_loader", "qualname": "AbstractDataLoader.load", "kind": "function", "doc": "

loads the data from the source and returns it as an iterator

\n\n
Returns
\n", "signature": "(self) -> Iterator[Dict[str, Union[float, int, str]]]:", "funcdef": "def"}, "causy.data_loader.AbstractDataLoader.hash": {"fullname": "causy.data_loader.AbstractDataLoader.hash", "modulename": "causy.data_loader", "qualname": "AbstractDataLoader.hash", "kind": "function", "doc": "

returns a hash of the data that is loaded

\n\n
Returns
\n", "signature": "(self) -> str:", "funcdef": "def"}, "causy.data_loader.FileDataLoader": {"fullname": "causy.data_loader.FileDataLoader", "modulename": "causy.data_loader", "qualname": "FileDataLoader", "kind": "class", "doc": "

A data loader which loads data from a file reference (e.g. json, csv, etc.)

\n", "bases": "AbstractDataLoader, abc.ABC"}, "causy.data_loader.FileDataLoader.reference": {"fullname": "causy.data_loader.FileDataLoader.reference", "modulename": "causy.data_loader", "qualname": "FileDataLoader.reference", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.data_loader.FileDataLoader.options": {"fullname": "causy.data_loader.FileDataLoader.options", "modulename": "causy.data_loader", "qualname": "FileDataLoader.options", "kind": "variable", "doc": "

\n", "default_value": "None"}, "causy.data_loader.FileDataLoader.hash": {"fullname": "causy.data_loader.FileDataLoader.hash", "modulename": "causy.data_loader", "qualname": "FileDataLoader.hash", "kind": "function", "doc": "

returns a hash of the data that is loaded

\n\n
Returns
\n", "signature": "(self) -> str:", "funcdef": "def"}, "causy.data_loader.JSONDataLoader": {"fullname": "causy.data_loader.JSONDataLoader", "modulename": "causy.data_loader", "qualname": "JSONDataLoader", "kind": "class", "doc": "

A data loader which loads data from a json file

\n", "bases": "FileDataLoader"}, "causy.data_loader.JSONDataLoader.load": {"fullname": "causy.data_loader.JSONDataLoader.load", "modulename": "causy.data_loader", "qualname": "JSONDataLoader.load", "kind": "function", "doc": "

loads the data from the source and returns it as an iterator

\n\n
Returns
\n", "signature": "(self) -> Iterator[Dict[str, Union[float, int, str]]]:", "funcdef": "def"}, "causy.data_loader.JSONLDataLoader": {"fullname": "causy.data_loader.JSONLDataLoader", "modulename": "causy.data_loader", "qualname": "JSONLDataLoader", "kind": "class", "doc": "

A data loader which loads data from a jsonl file

\n", "bases": "FileDataLoader"}, "causy.data_loader.JSONLDataLoader.load": {"fullname": "causy.data_loader.JSONLDataLoader.load", "modulename": "causy.data_loader", "qualname": "JSONLDataLoader.load", "kind": "function", "doc": "

loads the data from the source and returns it as an iterator

\n\n
Returns
\n", "signature": "(self) -> Iterator[Dict[str, Union[float, int, str]]]:", "funcdef": "def"}, "causy.data_loader.DynamicDataLoader": {"fullname": "causy.data_loader.DynamicDataLoader", "modulename": "causy.data_loader", "qualname": "DynamicDataLoader", "kind": "class", "doc": "

A data loader which loads another data loader dynamically based on the reference

\n", "bases": "AbstractDataLoader"}, "causy.data_loader.DynamicDataLoader.reference": {"fullname": "causy.data_loader.DynamicDataLoader.reference", "modulename": "causy.data_loader", "qualname": "DynamicDataLoader.reference", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.data_loader.DynamicDataLoader.data_loader": {"fullname": "causy.data_loader.DynamicDataLoader.data_loader", "modulename": "causy.data_loader", "qualname": "DynamicDataLoader.data_loader", "kind": "variable", "doc": "

\n", "annotation": ": causy.data_loader.AbstractDataLoader"}, "causy.data_loader.DynamicDataLoader.options": {"fullname": "causy.data_loader.DynamicDataLoader.options", "modulename": "causy.data_loader", "qualname": "DynamicDataLoader.options", "kind": "variable", "doc": "

\n", "default_value": "None"}, "causy.data_loader.DynamicDataLoader.load": {"fullname": "causy.data_loader.DynamicDataLoader.load", "modulename": "causy.data_loader", "qualname": "DynamicDataLoader.load", "kind": "function", "doc": "

loads the data from the source and returns it as an iterator

\n\n
Returns
\n", "signature": "(self) -> Iterator[Dict[str, Union[float, int, str]]]:", "funcdef": "def"}, "causy.data_loader.DATA_LOADERS": {"fullname": "causy.data_loader.DATA_LOADERS", "modulename": "causy.data_loader", "qualname": "DATA_LOADERS", "kind": "variable", "doc": "

\n", "default_value": "{<DataLoaderType.JSON: 'json'>: <class 'causy.data_loader.JSONDataLoader'>, <DataLoaderType.JSONL: 'jsonl'>: <class 'causy.data_loader.JSONLDataLoader'>, <DataLoaderType.DYNAMIC: 'dynamic'>: <class 'causy.data_loader.DynamicDataLoader'>}"}, "causy.data_loader.load_data_loader": {"fullname": "causy.data_loader.load_data_loader", "modulename": "causy.data_loader", "qualname": "load_data_loader", "kind": "function", "doc": "

loads the data loader based on the reference

\n\n
Parameters
\n\n
    \n
  • reference: a data loader reference
    • \n
\n\n
Returns
\n", "signature": "(\treference: causy.data_loader.DataLoaderReference) -> causy.data_loader.AbstractDataLoader:", "funcdef": "def"}, "causy.edge_types": {"fullname": "causy.edge_types", "modulename": "causy.edge_types", "kind": "module", "doc": "

\n"}, "causy.edge_types.EdgeTypeEnum": {"fullname": "causy.edge_types.EdgeTypeEnum", "modulename": "causy.edge_types", "qualname": "EdgeTypeEnum", "kind": "class", "doc": "

str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str

\n\n

Create a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to sys.getdefaultencoding().\nerrors defaults to 'strict'.

\n", "bases": "builtins.str, enum.Enum"}, "causy.edge_types.EdgeTypeEnum.DIRECTED": {"fullname": "causy.edge_types.EdgeTypeEnum.DIRECTED", "modulename": "causy.edge_types", "qualname": "EdgeTypeEnum.DIRECTED", "kind": "variable", "doc": "

\n", "default_value": "<EdgeTypeEnum.DIRECTED: 'directed'>"}, "causy.edge_types.EdgeTypeEnum.UNDIRECTED": {"fullname": "causy.edge_types.EdgeTypeEnum.UNDIRECTED", "modulename": "causy.edge_types", "qualname": "EdgeTypeEnum.UNDIRECTED", "kind": "variable", "doc": "

\n", "default_value": "<EdgeTypeEnum.UNDIRECTED: 'undirected'>"}, "causy.edge_types.EdgeTypeEnum.BIDIRECTED": {"fullname": "causy.edge_types.EdgeTypeEnum.BIDIRECTED", "modulename": "causy.edge_types", "qualname": "EdgeTypeEnum.BIDIRECTED", "kind": "variable", "doc": "

\n", "default_value": "<EdgeTypeEnum.BIDIRECTED: 'bidirected'>"}, "causy.edge_types.DirectedEdge": {"fullname": "causy.edge_types.DirectedEdge", "modulename": "causy.edge_types", "qualname": "DirectedEdge", "kind": "class", "doc": "

Edge type interface for the graph\nAn edge type is defined by a name

\n", "bases": "causy.interfaces.EdgeTypeInterface, typing.Generic[~EdgeTypeInterfaceType]"}, "causy.edge_types.DirectedEdgeUIConfig": {"fullname": "causy.edge_types.DirectedEdgeUIConfig", "modulename": "causy.edge_types", "qualname": "DirectedEdgeUIConfig", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "causy.contrib.graph_ui.EdgeTypeConfig"}, "causy.edge_types.DirectedEdgeUIConfig.edge_type": {"fullname": "causy.edge_types.DirectedEdgeUIConfig.edge_type", "modulename": "causy.edge_types", "qualname": "DirectedEdgeUIConfig.edge_type", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.edge_types.DirectedEdgeUIConfig.default_ui_config": {"fullname": "causy.edge_types.DirectedEdgeUIConfig.default_ui_config", "modulename": "causy.edge_types", "qualname": "DirectedEdgeUIConfig.default_ui_config", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.contrib.graph_ui.EdgeUIConfig]"}, "causy.edge_types.DirectedEdgeUIConfig.conditional_ui_configs": {"fullname": "causy.edge_types.DirectedEdgeUIConfig.conditional_ui_configs", "modulename": "causy.edge_types", "qualname": "DirectedEdgeUIConfig.conditional_ui_configs", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[causy.contrib.graph_ui.ConditionalEdgeUIConfig]]"}, "causy.edge_types.DirectedEdgeUIConfig.model_config": {"fullname": "causy.edge_types.DirectedEdgeUIConfig.model_config", "modulename": "causy.edge_types", "qualname": "DirectedEdgeUIConfig.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.edge_types.DirectedEdgeUIConfig.model_fields": {"fullname": "causy.edge_types.DirectedEdgeUIConfig.model_fields", "modulename": "causy.edge_types", "qualname": "DirectedEdgeUIConfig.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'edge_type': FieldInfo(annotation=str, required=False, default='DIRECTED'), 'default_ui_config': FieldInfo(annotation=Union[EdgeUIConfig, NoneType], required=False, default=EdgeUIConfig(color='#333', width=4, style='dashed', marker_start=None, marker_end='ArrowClosed', label_field='correlation', animated=True, label='Direct Effect: ${correlation.toFixed(4)}')), 'conditional_ui_configs': FieldInfo(annotation=Union[List[ConditionalEdgeUIConfig], NoneType], required=False, default=[ConditionalEdgeUIConfig(ui_config=EdgeUIConfig(color='#f00000', width=4, style='dashed', marker_start=None, marker_end='ArrowClosed', label_field='direct_effect', animated=True, label='Direct Effect: ${direct_effect.toFixed(4)}'), condition_field='direct_effect', condition_value=0.0, condition_comparison=<ConditionalEdgeUIConfigComparison.LESS: 'LESS'>), ConditionalEdgeUIConfig(ui_config=EdgeUIConfig(color='#0f0fff', width=4, style='dashed', marker_start=None, marker_end='ArrowClosed', label_field='direct_effect', animated=True, label='Direct Effect: ${direct_effect.toFixed(4)}'), condition_field='direct_effect', condition_value=0.0, condition_comparison=<ConditionalEdgeUIConfigComparison.GREATER: 'GREATER'>)])}"}, "causy.edge_types.DirectedEdgeUIConfig.model_computed_fields": {"fullname": "causy.edge_types.DirectedEdgeUIConfig.model_computed_fields", "modulename": "causy.edge_types", "qualname": "DirectedEdgeUIConfig.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.edge_types.UndirectedEdge": {"fullname": "causy.edge_types.UndirectedEdge", "modulename": "causy.edge_types", "qualname": "UndirectedEdge", "kind": "class", "doc": "

Edge type interface for the graph\nAn edge type is defined by a name

\n", "bases": "causy.interfaces.EdgeTypeInterface, typing.Generic[~EdgeTypeInterfaceType]"}, "causy.edge_types.UndirectedEdgeUIConfig": {"fullname": "causy.edge_types.UndirectedEdgeUIConfig", "modulename": "causy.edge_types", "qualname": "UndirectedEdgeUIConfig", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "causy.contrib.graph_ui.EdgeTypeConfig"}, "causy.edge_types.UndirectedEdgeUIConfig.edge_type": {"fullname": "causy.edge_types.UndirectedEdgeUIConfig.edge_type", "modulename": "causy.edge_types", "qualname": "UndirectedEdgeUIConfig.edge_type", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.edge_types.UndirectedEdgeUIConfig.default_ui_config": {"fullname": "causy.edge_types.UndirectedEdgeUIConfig.default_ui_config", "modulename": "causy.edge_types", "qualname": "UndirectedEdgeUIConfig.default_ui_config", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.contrib.graph_ui.EdgeUIConfig]"}, "causy.edge_types.UndirectedEdgeUIConfig.model_config": {"fullname": "causy.edge_types.UndirectedEdgeUIConfig.model_config", "modulename": "causy.edge_types", "qualname": "UndirectedEdgeUIConfig.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.edge_types.UndirectedEdgeUIConfig.model_fields": {"fullname": "causy.edge_types.UndirectedEdgeUIConfig.model_fields", "modulename": "causy.edge_types", "qualname": "UndirectedEdgeUIConfig.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'edge_type': FieldInfo(annotation=str, required=False, default='UNDIRECTED'), 'default_ui_config': FieldInfo(annotation=Union[EdgeUIConfig, NoneType], required=False, default=EdgeUIConfig(color='#333', width=4, style='solid', marker_start=None, marker_end=None, label_field='direct_effect', animated=False, label='Correlation: ${correlation.toFixed(4)}')), 'conditional_ui_configs': FieldInfo(annotation=Union[List[ConditionalEdgeUIConfig], NoneType], required=False, default=None)}"}, "causy.edge_types.UndirectedEdgeUIConfig.model_computed_fields": {"fullname": "causy.edge_types.UndirectedEdgeUIConfig.model_computed_fields", "modulename": "causy.edge_types", "qualname": "UndirectedEdgeUIConfig.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.edge_types.BiDirectedEdge": {"fullname": "causy.edge_types.BiDirectedEdge", "modulename": "causy.edge_types", "qualname": "BiDirectedEdge", "kind": "class", "doc": "

Edge type interface for the graph\nAn edge type is defined by a name

\n", "bases": "causy.interfaces.EdgeTypeInterface, typing.Generic[~EdgeTypeInterfaceType]"}, "causy.edge_types.BiDirectedEdgeUIConfig": {"fullname": "causy.edge_types.BiDirectedEdgeUIConfig", "modulename": "causy.edge_types", "qualname": "BiDirectedEdgeUIConfig", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "causy.contrib.graph_ui.EdgeTypeConfig"}, "causy.edge_types.BiDirectedEdgeUIConfig.edge_type": {"fullname": "causy.edge_types.BiDirectedEdgeUIConfig.edge_type", "modulename": "causy.edge_types", "qualname": "BiDirectedEdgeUIConfig.edge_type", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.edge_types.BiDirectedEdgeUIConfig.default_ui_config": {"fullname": "causy.edge_types.BiDirectedEdgeUIConfig.default_ui_config", "modulename": "causy.edge_types", "qualname": "BiDirectedEdgeUIConfig.default_ui_config", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.contrib.graph_ui.EdgeUIConfig]"}, "causy.edge_types.BiDirectedEdgeUIConfig.model_config": {"fullname": "causy.edge_types.BiDirectedEdgeUIConfig.model_config", "modulename": "causy.edge_types", "qualname": "BiDirectedEdgeUIConfig.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.edge_types.BiDirectedEdgeUIConfig.model_fields": {"fullname": "causy.edge_types.BiDirectedEdgeUIConfig.model_fields", "modulename": "causy.edge_types", "qualname": "BiDirectedEdgeUIConfig.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'edge_type': FieldInfo(annotation=str, required=False, default='BIDIRECTED'), 'default_ui_config': FieldInfo(annotation=Union[EdgeUIConfig, NoneType], required=False, default=EdgeUIConfig(color='#333', width=4, style='solid', marker_start='ArrowClosed', marker_end='ArrowClosed', label_field='direct_effect', animated=False, label=None)), 'conditional_ui_configs': FieldInfo(annotation=Union[List[ConditionalEdgeUIConfig], NoneType], required=False, default=None)}"}, "causy.edge_types.BiDirectedEdgeUIConfig.model_computed_fields": {"fullname": "causy.edge_types.BiDirectedEdgeUIConfig.model_computed_fields", "modulename": "causy.edge_types", "qualname": "BiDirectedEdgeUIConfig.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.edge_types.EDGE_TYPES": {"fullname": "causy.edge_types.EDGE_TYPES", "modulename": "causy.edge_types", "qualname": "EDGE_TYPES", "kind": "variable", "doc": "

\n", "default_value": "{'DIRECTED': <class 'causy.edge_types.DirectedEdge'>, 'UNDIRECTED': <class 'causy.edge_types.UndirectedEdge'>, 'BIDIRECTED': <class 'causy.edge_types.BiDirectedEdge'>}"}, "causy.generators": {"fullname": "causy.generators", "modulename": "causy.generators", "kind": "module", "doc": "

\n"}, "causy.generators.logger": {"fullname": "causy.generators.logger", "modulename": "causy.generators", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.generators (WARNING)>"}, "causy.generators.AllCombinationsGenerator": {"fullname": "causy.generators.AllCombinationsGenerator", "modulename": "causy.generators", "qualname": "AllCombinationsGenerator", "kind": "class", "doc": "

Generates all combinations of nodes in the graph in accordance with the configured amount of nodes to compare.\nYields node combinations as tuples, but only in one ordering, i.e. mathematically it returns sets.\ne.g. if your graph consists of the nodes [X, Y, Z] and you want to compare 2 nodes,\nit will yield (X, Y), (X, Z), (Y, Z). It will not additionally yield (Y, X), (Z, X), (Z, Y).

\n", "bases": "causy.interfaces.GeneratorInterface"}, "causy.generators.AllCombinationsGenerator.generate": {"fullname": "causy.generators.AllCombinationsGenerator.generate", "modulename": "causy.generators", "qualname": "AllCombinationsGenerator.generate", "kind": "function", "doc": "

\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tgraph_model_instance_: causy.interfaces.GraphModelInterface):", "funcdef": "def"}, "causy.generators.AllCombinationsGenerator.model_config": {"fullname": "causy.generators.AllCombinationsGenerator.model_config", "modulename": "causy.generators", "qualname": "AllCombinationsGenerator.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.generators.AllCombinationsGenerator.model_fields": {"fullname": "causy.generators.AllCombinationsGenerator.model_fields", "modulename": "causy.generators", "qualname": "AllCombinationsGenerator.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'comparison_settings': FieldInfo(annotation=Union[ComparisonSettingsInterface, NoneType], required=False, default=None), 'chunked': FieldInfo(annotation=Union[bool, VariableReference, NoneType], required=False, default=False), 'every_nth': FieldInfo(annotation=Union[int, VariableReference, NoneType], required=False, default=None), 'generator': FieldInfo(annotation=Union[GeneratorInterface, NoneType], required=False, default=None), 'shuffle_combinations': FieldInfo(annotation=Union[bool, VariableReference, NoneType], required=False, default=None)}"}, "causy.generators.AllCombinationsGenerator.model_computed_fields": {"fullname": "causy.generators.AllCombinationsGenerator.model_computed_fields", "modulename": "causy.generators", "qualname": "AllCombinationsGenerator.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': ComputedFieldInfo(wrapped_property=<property object>, return_type=<class 'str'>, alias=None, alias_priority=None, title=None, field_title_generator=None, description=None, deprecated=None, examples=None, json_schema_extra=None, repr=True)}"}, "causy.generators.PairsWithEdgesInBetweenGenerator": {"fullname": "causy.generators.PairsWithEdgesInBetweenGenerator", "modulename": "causy.generators", "qualname": "PairsWithEdgesInBetweenGenerator", "kind": "class", "doc": "

Generates all pairs of nodes that have edges in between them. It does not matter if the edge is directed or not.\nHowever, if it is an edge which points in both/no directions, it will be iterated over them twice.

\n", "bases": "causy.interfaces.GeneratorInterface"}, "causy.generators.PairsWithEdgesInBetweenGenerator.__init__": {"fullname": "causy.generators.PairsWithEdgesInBetweenGenerator.__init__", "modulename": "causy.generators", "qualname": "PairsWithEdgesInBetweenGenerator.__init__", "kind": "function", "doc": "

Create a new model by parsing and validating input data from keyword arguments.

\n\n

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be\nvalidated to form a valid model.

\n\n

self is explicitly positional-only to allow self as a field name.

\n", "signature": "(\t*args,\tchunk_size: Union[int, causy.variables.VariableReference, NoneType] = None,\tchunked: Union[bool, causy.variables.VariableReference, NoneType] = None,\t**kwargs)"}, "causy.generators.PairsWithEdgesInBetweenGenerator.chunk_size": {"fullname": "causy.generators.PairsWithEdgesInBetweenGenerator.chunk_size", "modulename": "causy.generators", "qualname": "PairsWithEdgesInBetweenGenerator.chunk_size", "kind": "variable", "doc": "

\n", "annotation": ": Union[int, causy.variables.VariableReference]"}, "causy.generators.PairsWithEdgesInBetweenGenerator.chunked": {"fullname": "causy.generators.PairsWithEdgesInBetweenGenerator.chunked", "modulename": "causy.generators", "qualname": "PairsWithEdgesInBetweenGenerator.chunked", "kind": "variable", "doc": "

\n", "annotation": ": Union[bool, causy.variables.VariableReference, NoneType]"}, "causy.generators.PairsWithEdgesInBetweenGenerator.generate": {"fullname": "causy.generators.PairsWithEdgesInBetweenGenerator.generate", "modulename": "causy.generators", "qualname": "PairsWithEdgesInBetweenGenerator.generate", "kind": "function", "doc": "

\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tgraph_model_instance_: causy.interfaces.GraphModelInterface):", "funcdef": "def"}, "causy.generators.PairsWithEdgesInBetweenGenerator.model_config": {"fullname": "causy.generators.PairsWithEdgesInBetweenGenerator.model_config", "modulename": "causy.generators", "qualname": "PairsWithEdgesInBetweenGenerator.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.generators.PairsWithEdgesInBetweenGenerator.model_fields": {"fullname": "causy.generators.PairsWithEdgesInBetweenGenerator.model_fields", "modulename": "causy.generators", "qualname": "PairsWithEdgesInBetweenGenerator.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'comparison_settings': FieldInfo(annotation=Union[ComparisonSettingsInterface, NoneType], required=False, default=None), 'chunked': FieldInfo(annotation=Union[bool, VariableReference, NoneType], required=False, default=None), 'every_nth': FieldInfo(annotation=Union[int, VariableReference, NoneType], required=False, default=None), 'generator': FieldInfo(annotation=Union[GeneratorInterface, NoneType], required=False, default=None), 'shuffle_combinations': FieldInfo(annotation=Union[bool, VariableReference, NoneType], required=False, default=None), 'chunk_size': FieldInfo(annotation=Union[int, VariableReference], required=False, default=100)}"}, "causy.generators.PairsWithEdgesInBetweenGenerator.model_computed_fields": {"fullname": "causy.generators.PairsWithEdgesInBetweenGenerator.model_computed_fields", "modulename": "causy.generators", "qualname": "PairsWithEdgesInBetweenGenerator.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': ComputedFieldInfo(wrapped_property=<property object>, return_type=<class 'str'>, alias=None, alias_priority=None, title=None, field_title_generator=None, description=None, deprecated=None, examples=None, json_schema_extra=None, repr=True)}"}, "causy.generators.PairsWithNeighboursGenerator": {"fullname": "causy.generators.PairsWithNeighboursGenerator", "modulename": "causy.generators", "qualname": "PairsWithNeighboursGenerator", "kind": "class", "doc": "

Generates all combinations of pairs of nodes that are neighbours and the neighbours of the first input node.\ne.g. if your graph consists of the nodes [X, Y, Z, W, V] your output could be:\n[X, Y, neighbours(X)], [Y, X, neighbours(Y)], [X, Z, neighbours(X)], [Z, X, neighbours(Z)], ...\n(if, among others, X and Y are neighbours and X and Z are neighbours)

\n", "bases": "causy.interfaces.GeneratorInterface"}, "causy.generators.PairsWithNeighboursGenerator.__init__": {"fullname": "causy.generators.PairsWithNeighboursGenerator.__init__", "modulename": "causy.generators", "qualname": "PairsWithNeighboursGenerator.__init__", "kind": "function", "doc": "

Create a new model by parsing and validating input data from keyword arguments.

\n\n

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be\nvalidated to form a valid model.

\n\n

self is explicitly positional-only to allow self as a field name.

\n", "signature": "(*args, **kwargs)"}, "causy.generators.PairsWithNeighboursGenerator.shuffle_combinations": {"fullname": "causy.generators.PairsWithNeighboursGenerator.shuffle_combinations", "modulename": "causy.generators", "qualname": "PairsWithNeighboursGenerator.shuffle_combinations", "kind": "variable", "doc": "

\n", "annotation": ": Union[bool, causy.variables.VariableReference]"}, "causy.generators.PairsWithNeighboursGenerator.chunked": {"fullname": "causy.generators.PairsWithNeighboursGenerator.chunked", "modulename": "causy.generators", "qualname": "PairsWithNeighboursGenerator.chunked", "kind": "variable", "doc": "

\n", "annotation": ": Union[bool, causy.variables.VariableReference]"}, "causy.generators.PairsWithNeighboursGenerator.generate": {"fullname": "causy.generators.PairsWithNeighboursGenerator.generate", "modulename": "causy.generators", "qualname": "PairsWithNeighboursGenerator.generate", "kind": "function", "doc": "

\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tgraph_model_instance_: causy.interfaces.GraphModelInterface):", "funcdef": "def"}, "causy.generators.PairsWithNeighboursGenerator.model_config": {"fullname": "causy.generators.PairsWithNeighboursGenerator.model_config", "modulename": "causy.generators", "qualname": "PairsWithNeighboursGenerator.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.generators.PairsWithNeighboursGenerator.model_fields": {"fullname": "causy.generators.PairsWithNeighboursGenerator.model_fields", "modulename": "causy.generators", "qualname": "PairsWithNeighboursGenerator.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'comparison_settings': FieldInfo(annotation=Union[ComparisonSettingsInterface, NoneType], required=False, default=None), 'chunked': FieldInfo(annotation=Union[bool, VariableReference], required=False, default=True), 'every_nth': FieldInfo(annotation=Union[int, VariableReference, NoneType], required=False, default=None), 'generator': FieldInfo(annotation=Union[GeneratorInterface, NoneType], required=False, default=None), 'shuffle_combinations': FieldInfo(annotation=Union[bool, VariableReference], required=False, default=True)}"}, "causy.generators.PairsWithNeighboursGenerator.model_computed_fields": {"fullname": "causy.generators.PairsWithNeighboursGenerator.model_computed_fields", "modulename": "causy.generators", "qualname": "PairsWithNeighboursGenerator.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': ComputedFieldInfo(wrapped_property=<property object>, return_type=<class 'str'>, alias=None, alias_priority=None, title=None, field_title_generator=None, description=None, deprecated=None, examples=None, json_schema_extra=None, repr=True)}"}, "causy.generators.RandomSampleGenerator": {"fullname": "causy.generators.RandomSampleGenerator", "modulename": "causy.generators", "qualname": "RandomSampleGenerator", "kind": "class", "doc": "

Executes another generator and returns a random sample of the results

\n", "bases": "causy.interfaces.GeneratorInterface, pydantic.main.BaseModel"}, "causy.generators.RandomSampleGenerator.__init__": {"fullname": "causy.generators.RandomSampleGenerator.__init__", "modulename": "causy.generators", "qualname": "RandomSampleGenerator.__init__", "kind": "function", "doc": "

Create a new model by parsing and validating input data from keyword arguments.

\n\n

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be\nvalidated to form a valid model.

\n\n

self is explicitly positional-only to allow self as a field name.

\n", "signature": "(\t*args,\tgenerator: Union[causy.interfaces.GeneratorInterface, Dict[<built-in function any>, <built-in function any>], NoneType] = None,\t**kwargs)"}, "causy.generators.RandomSampleGenerator.every_nth": {"fullname": "causy.generators.RandomSampleGenerator.every_nth", "modulename": "causy.generators", "qualname": "RandomSampleGenerator.every_nth", "kind": "variable", "doc": "

\n", "annotation": ": Union[int, causy.variables.VariableReference]"}, "causy.generators.RandomSampleGenerator.generator": {"fullname": "causy.generators.RandomSampleGenerator.generator", "modulename": "causy.generators", "qualname": "RandomSampleGenerator.generator", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.interfaces.GeneratorInterface]"}, "causy.generators.RandomSampleGenerator.generate": {"fullname": "causy.generators.RandomSampleGenerator.generate", "modulename": "causy.generators", "qualname": "RandomSampleGenerator.generate", "kind": "function", "doc": "

Executes another generator and returns a random sample of the results

\n\n
Parameters
\n\n
    \n
  • graph:
    • \n
  • graph_model_instance_:
    • \n
\n\n
Returns
\n\n
\n

yields a random sample of the results

\n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tgraph_model_instance_: dict):", "funcdef": "def"}, "causy.generators.RandomSampleGenerator.model_config": {"fullname": "causy.generators.RandomSampleGenerator.model_config", "modulename": "causy.generators", "qualname": "RandomSampleGenerator.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.generators.RandomSampleGenerator.model_fields": {"fullname": "causy.generators.RandomSampleGenerator.model_fields", "modulename": "causy.generators", "qualname": "RandomSampleGenerator.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'comparison_settings': FieldInfo(annotation=Union[ComparisonSettingsInterface, NoneType], required=False, default=None), 'chunked': FieldInfo(annotation=Union[bool, VariableReference, NoneType], required=False, default=False), 'every_nth': FieldInfo(annotation=Union[int, VariableReference], required=False, default=100), 'generator': FieldInfo(annotation=Union[GeneratorInterface, NoneType], required=False, default=None), 'shuffle_combinations': FieldInfo(annotation=Union[bool, VariableReference, NoneType], required=False, default=None)}"}, "causy.generators.RandomSampleGenerator.model_computed_fields": {"fullname": "causy.generators.RandomSampleGenerator.model_computed_fields", "modulename": "causy.generators", "qualname": "RandomSampleGenerator.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': ComputedFieldInfo(wrapped_property=<property object>, return_type=<class 'str'>, alias=None, alias_priority=None, title=None, field_title_generator=None, description=None, deprecated=None, examples=None, json_schema_extra=None, repr=True)}"}, "causy.graph": {"fullname": "causy.graph", "modulename": "causy.graph", "kind": "module", "doc": "

\n"}, "causy.graph.logger": {"fullname": "causy.graph.logger", "modulename": "causy.graph", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.graph (WARNING)>"}, "causy.graph.Node": {"fullname": "causy.graph.Node", "modulename": "causy.graph", "qualname": "Node", "kind": "class", "doc": "

A node is a variable in the graph. It has a name, an id and values. The values are stored as a torch.Tensor.\nA node can also have metadata.

\n", "bases": "causy.interfaces.NodeInterface"}, "causy.graph.Node.name": {"fullname": "causy.graph.Node.name", "modulename": "causy.graph", "qualname": "Node.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.graph.Node.id": {"fullname": "causy.graph.Node.id", "modulename": "causy.graph", "qualname": "Node.id", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.graph.Node.values": {"fullname": "causy.graph.Node.values", "modulename": "causy.graph", "qualname": "Node.values", "kind": "variable", "doc": "

\n", "annotation": ": Optional[torch.Tensor]"}, "causy.graph.Node.metadata": {"fullname": "causy.graph.Node.metadata", "modulename": "causy.graph", "qualname": "Node.metadata", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict[str, Union[str, int, float, bool, List[Union[str, int, float, bool]], Dict[str, Union[str, int, float, bool]]]]]"}, "causy.graph.Node.model_config": {"fullname": "causy.graph.Node.model_config", "modulename": "causy.graph", "qualname": "Node.model_config", "kind": "variable", "doc": "

\n", "default_value": "{'arbitrary_types_allowed': True}"}, "causy.graph.Node.model_fields": {"fullname": "causy.graph.Node.model_fields", "modulename": "causy.graph", "qualname": "Node.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': FieldInfo(annotation=str, required=True), 'id': FieldInfo(annotation=str, required=True), 'values': FieldInfo(annotation=Union[Tensor, NoneType], required=False, default=None), 'metadata': FieldInfo(annotation=Union[Dict[str, Union[str, int, float, bool, List[Union[str, int, float, bool]], Dict[str, Union[str, int, float, bool]]]], NoneType], required=False, default=None)}"}, "causy.graph.Node.model_computed_fields": {"fullname": "causy.graph.Node.model_computed_fields", "modulename": "causy.graph", "qualname": "Node.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.graph.Edge": {"fullname": "causy.graph.Edge", "modulename": "causy.graph", "qualname": "Edge", "kind": "class", "doc": "

An edge is a connection between two nodes. It has a direction defined by the edge_type and metadata.\nA metadata example could be the p-value of a statistical test.\nAn edge can be e.g. undirected, directed or bidirected. Which option is available/chosen depends on the algorithm and the current state of the graph.\nBy default an edge always has an undirected and a directed edge_type.

\n", "bases": "causy.interfaces.EdgeInterface"}, "causy.graph.Edge.__init__": {"fullname": "causy.graph.Edge.__init__", "modulename": "causy.graph", "qualname": "Edge.__init__", "kind": "function", "doc": "

Create a new model by parsing and validating input data from keyword arguments.

\n\n

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be\nvalidated to form a valid model.

\n\n

self is explicitly positional-only to allow self as a field name.

\n", "signature": "(*args, **kwargs)"}, "causy.graph.Edge.u": {"fullname": "causy.graph.Edge.u", "modulename": "causy.graph", "qualname": "Edge.u", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.NodeInterface"}, "causy.graph.Edge.v": {"fullname": "causy.graph.Edge.v", "modulename": "causy.graph", "qualname": "Edge.v", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.NodeInterface"}, "causy.graph.Edge.edge_type": {"fullname": "causy.graph.Edge.edge_type", "modulename": "causy.graph", "qualname": "Edge.edge_type", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.EdgeTypeInterface"}, "causy.graph.Edge.metadata": {"fullname": "causy.graph.Edge.metadata", "modulename": "causy.graph", "qualname": "Edge.metadata", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict[str, Union[str, int, float, bool, List[Union[str, int, float, bool]], Dict[str, Union[str, int, float, bool]]]]]"}, "causy.graph.Edge.deleted": {"fullname": "causy.graph.Edge.deleted", "modulename": "causy.graph", "qualname": "Edge.deleted", "kind": "variable", "doc": "

\n", "annotation": ": Optional[bool]"}, "causy.graph.Edge.model_config": {"fullname": "causy.graph.Edge.model_config", "modulename": "causy.graph", "qualname": "Edge.model_config", "kind": "variable", "doc": "

\n", "default_value": "{'arbitrary_types_allowed': True}"}, "causy.graph.Edge.model_fields": {"fullname": "causy.graph.Edge.model_fields", "modulename": "causy.graph", "qualname": "Edge.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'u': FieldInfo(annotation=NodeInterface, required=True), 'v': FieldInfo(annotation=NodeInterface, required=True), 'edge_type': FieldInfo(annotation=EdgeTypeInterface, required=True), 'metadata': FieldInfo(annotation=Union[Dict[str, Union[str, int, float, bool, List[Union[str, int, float, bool]], Dict[str, Union[str, int, float, bool]]]], NoneType], required=False, default=None), 'deleted': FieldInfo(annotation=Union[bool, NoneType], required=False, default=False)}"}, "causy.graph.Edge.model_computed_fields": {"fullname": "causy.graph.Edge.model_computed_fields", "modulename": "causy.graph", "qualname": "Edge.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.graph.GraphError": {"fullname": "causy.graph.GraphError", "modulename": "causy.graph", "qualname": "GraphError", "kind": "class", "doc": "

Common base class for all non-exit exceptions.

\n", "bases": "builtins.Exception"}, "causy.graph.GraphBaseAccessMixin": {"fullname": "causy.graph.GraphBaseAccessMixin", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin", "kind": "class", "doc": "

\n"}, "causy.graph.GraphBaseAccessMixin.directed_edge_is_soft_deleted": {"fullname": "causy.graph.GraphBaseAccessMixin.directed_edge_is_soft_deleted", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.directed_edge_is_soft_deleted", "kind": "function", "doc": "

Check if an edge is soft deleted

\n\n
Parameters
\n\n
    \n
  • u:
    • \n
  • v:
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str]) -> bool:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.parents_of_node": {"fullname": "causy.graph.GraphBaseAccessMixin.parents_of_node", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.parents_of_node", "kind": "function", "doc": "

Return all parents of a node u

\n\n
Parameters
\n\n
    \n
  • u: node u
    • \n
\n\n
Returns
\n\n
\n

list of nodes (parents)

\n
\n", "signature": "(self, u: Union[causy.graph.Node, str]):", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.edge_exists": {"fullname": "causy.graph.GraphBaseAccessMixin.edge_exists", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.edge_exists", "kind": "function", "doc": "

Check if any edge exists between u and v. Cases: u -> v, u <-> v, u <- v

\n\n
Parameters
\n\n
    \n
  • u: node u
    • \n
  • v: node v
    • \n
\n\n
Returns
\n\n
\n

True if any edge exists, False otherwise

\n
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str]) -> bool:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.directed_edge_exists": {"fullname": "causy.graph.GraphBaseAccessMixin.directed_edge_exists", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.directed_edge_exists", "kind": "function", "doc": "

Check if a directed edge exists between u and v. Cases: u -> v, u <-> v

\n\n
Parameters
\n\n
    \n
  • u: node u
    • \n
  • v: node v
    • \n
\n\n
Returns
\n\n
\n

True if a directed edge exists, False otherwise

\n
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str]) -> bool:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.node_by_id": {"fullname": "causy.graph.GraphBaseAccessMixin.node_by_id", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.node_by_id", "kind": "function", "doc": "

Retrieve a node by its id

\n\n
Parameters
\n\n
    \n
  • id_:
    • \n
\n\n
Returns
\n", "signature": "(self, id_: str) -> Optional[causy.graph.Node]:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.edge_value": {"fullname": "causy.graph.GraphBaseAccessMixin.edge_value", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.edge_value", "kind": "function", "doc": "

retrieve the value of an edge

\n\n
Parameters
\n\n
    \n
  • u:
    • \n
  • v:
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str]) -> Optional[Dict]:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.edge_type": {"fullname": "causy.graph.GraphBaseAccessMixin.edge_type", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.edge_type", "kind": "function", "doc": "

retrieve the value of an edge

\n\n
Parameters
\n\n
    \n
  • u:
    • \n
  • v:
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str]) -> Optional[causy.interfaces.EdgeTypeInterface]:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.undirected_edge_exists": {"fullname": "causy.graph.GraphBaseAccessMixin.undirected_edge_exists", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.undirected_edge_exists", "kind": "function", "doc": "

Check if an undirected edge exists between u and v. Note: currently, an undirected edges is implemented just as\na directed edge. However, they are two functions as they mean different things in different algorithms.\nCurrently, this function is used in the PC algorithm, where an undirected edge is an edge which could not be\noriented in any direction by orientation rules.\nLater, a cohersive naming scheme should be implemented.

\n\n
Parameters
\n\n
    \n
  • u: node u
    • \n
  • v: node v
    • \n
\n\n
Returns
\n\n
\n

True if an undirected edge exists, False otherwise

\n
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str]) -> bool:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.get_siblings": {"fullname": "causy.graph.GraphBaseAccessMixin.get_siblings", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.get_siblings", "kind": "function", "doc": "

Get the set of nodes that are connected to the node v with an undirected edge.

\n\n
Parameters
\n\n
    \n
  • v: node v
    • \n
\n\n
Returns
\n\n
\n

A set of nodes that are connected to v with an undirected edge.

\n
\n", "signature": "(\tself,\tv: Union[causy.graph.Node, str]) -> Set[Union[causy.graph.Node, str]]:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.retrieve_edge_history": {"fullname": "causy.graph.GraphBaseAccessMixin.retrieve_edge_history", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.retrieve_edge_history", "kind": "function", "doc": "

Retrieve the edge history

\n\n
Parameters
\n\n
    \n
  • u:
    • \n
  • v:
    • \n
  • action:
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str],\taction: causy.models.TestResultAction = None) -> List[causy.models.TestResult]:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.directed_path_exists": {"fullname": "causy.graph.GraphBaseAccessMixin.directed_path_exists", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.directed_path_exists", "kind": "function", "doc": "

Check if a directed path from u to v exists

\n\n
Parameters
\n\n
    \n
  • u: node u
    • \n
  • v: node v
    • \n
\n\n
Returns
\n\n
\n

True if a directed path exists, False otherwise

\n
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str]) -> bool:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.edge_of_type_exists": {"fullname": "causy.graph.GraphBaseAccessMixin.edge_of_type_exists", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.edge_of_type_exists", "kind": "function", "doc": "

Check if an edge of a specific type exists between u and v.

\n\n
Parameters
\n\n
    \n
  • u: node u
    • \n
  • v: node v
    • \n
  • edge_type: the type of the edge to check for
    • \n
\n\n
Returns
\n\n
\n

True if an edge of this type exists, False otherwise

\n
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str],\tedge_type: causy.interfaces.EdgeTypeInterface = DIRECTED) -> bool:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.descendants_of_node": {"fullname": "causy.graph.GraphBaseAccessMixin.descendants_of_node", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.descendants_of_node", "kind": "function", "doc": "

Returns a list of all descendants of the given node in a directed graph, including the input node itself.

\n\n
Parameters
\n\n
    \n
  • u: The node or node ID to find descendants for.
    • \n
\n\n
Returns
\n\n
\n

A list of descendants of a node including the input node itself.

\n
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tvisited=None) -> List[Union[causy.graph.Node, str]]:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.are_nodes_d_separated_dag": {"fullname": "causy.graph.GraphBaseAccessMixin.are_nodes_d_separated_dag", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.are_nodes_d_separated_dag", "kind": "function", "doc": "

Check if nodes u and v are d-separated given a conditioning set in a DAG. We check whether there is an open path, i.e. a path on which all colliders are in the conditioning set and all non-colliders are not in the conditioning set. If there is no open path, u and v are d-separated.

\n\n
Parameters
\n\n
    \n
  • u: First node
    • \n
  • v: Second node
    • \n
  • conditioning_set: Set of nodes to condition on
    • \n
\n\n
Returns
\n\n
\n

True if u and v are d-separated given conditioning_set, False otherwise

\n
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str],\tconditioning_set: List[Union[causy.graph.Node, str]]) -> bool:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.are_nodes_d_separated_cpdag": {"fullname": "causy.graph.GraphBaseAccessMixin.are_nodes_d_separated_cpdag", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.are_nodes_d_separated_cpdag", "kind": "function", "doc": "

Check if nodes u and v are d-separated given a conditioning set in a CPDAG following Perkovic, 2020. (Identifying causal effects in maximally oriented partially directed acyclic graphs)

\n\n
Parameters
\n\n
    \n
  • u: First node
    • \n
  • v: Second node
    • \n
  • conditioning_set: Set of nodes to condition on
    • \n
\n\n
Returns
\n\n
\n

True if u and v are d-separated given conditioning_set, False otherwise

\n
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str],\tconditioning_set: List[Union[causy.graph.Node, str]]) -> bool:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.all_paths_on_underlying_undirected_graph": {"fullname": "causy.graph.GraphBaseAccessMixin.all_paths_on_underlying_undirected_graph", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.all_paths_on_underlying_undirected_graph", "kind": "function", "doc": "

\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str],\tvisited=None,\tpath=None) -> List[List[causy.graph.Node]]:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.retrieve_edges": {"fullname": "causy.graph.GraphBaseAccessMixin.retrieve_edges", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.retrieve_edges", "kind": "function", "doc": "

Retrieve all edges

\n\n
Returns
\n\n
\n

all edges

\n
\n", "signature": "(self) -> List[causy.graph.Edge]:", "funcdef": "def"}, "causy.graph.Graph": {"fullname": "causy.graph.Graph", "modulename": "causy.graph", "qualname": "Graph", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "GraphBaseAccessMixin, pydantic.main.BaseModel, causy.interfaces.ExtensionInterface.GraphAccessMixin, causy.edge_types.DirectedEdge.GraphAccessMixin, causy.interfaces.EdgeTypeInterface.GraphAccessMixin"}, "causy.graph.Graph.nodes": {"fullname": "causy.graph.Graph.nodes", "modulename": "causy.graph", "qualname": "Graph.nodes", "kind": "variable", "doc": "

\n", "annotation": ": OrderedDict[str, causy.graph.Node]"}, "causy.graph.Graph.edges": {"fullname": "causy.graph.Graph.edges", "modulename": "causy.graph", "qualname": "Graph.edges", "kind": "variable", "doc": "

\n", "annotation": ": Dict[str, Dict[str, causy.graph.Edge]]"}, "causy.graph.Graph.edge_history": {"fullname": "causy.graph.Graph.edge_history", "modulename": "causy.graph", "qualname": "Graph.edge_history", "kind": "variable", "doc": "

\n", "annotation": ": Dict[Tuple[str, str], List[causy.models.TestResult]]"}, "causy.graph.Graph.action_history": {"fullname": "causy.graph.Graph.action_history", "modulename": "causy.graph", "qualname": "Graph.action_history", "kind": "variable", "doc": "

\n", "annotation": ": List[causy.models.ActionHistoryStep]"}, "causy.graph.Graph.model_config": {"fullname": "causy.graph.Graph.model_config", "modulename": "causy.graph", "qualname": "Graph.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.graph.Graph.model_post_init": {"fullname": "causy.graph.Graph.model_post_init", "modulename": "causy.graph", "qualname": "Graph.model_post_init", "kind": "function", "doc": "

This function is meant to behave like a BaseModel method to initialise private attributes.

\n\n

It takes context as an argument since that's what pydantic-core passes when calling it.

\n\n

Args:\n self: The BaseModel instance.\n context: The context.

\n", "signature": "(self: pydantic.main.BaseModel, context: Any, /) -> None:", "funcdef": "def"}, "causy.graph.Graph.model_fields": {"fullname": "causy.graph.Graph.model_fields", "modulename": "causy.graph", "qualname": "Graph.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'nodes': FieldInfo(annotation=OrderedDict[str, Node], required=False, default=OrderedDict()), 'edges': FieldInfo(annotation=Dict[str, Dict[str, Edge]], required=False, default={}), 'edge_history': FieldInfo(annotation=Dict[Tuple[str, str], List[TestResult]], required=False, default={}), 'action_history': FieldInfo(annotation=List[ActionHistoryStep], required=False, default=[])}"}, "causy.graph.Graph.model_computed_fields": {"fullname": "causy.graph.Graph.model_computed_fields", "modulename": "causy.graph", "qualname": "Graph.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.graph.GraphManager": {"fullname": "causy.graph.GraphManager", "modulename": "causy.graph", "qualname": "GraphManager", "kind": "class", "doc": "

The graph represents the internal data structure of causy. It is a simple graph with nodes and edges.\nBut it supports to be handled as a directed graph, undirected graph and bidirected graph, which is important to implement different algorithms in different stages.\nIt also stores the history of the actions taken on the graph.

\n", "bases": "GraphBaseAccessMixin, causy.interfaces.BaseGraphInterface"}, "causy.graph.GraphManager.__init__": {"fullname": "causy.graph.GraphManager.__init__", "modulename": "causy.graph", "qualname": "GraphManager.__init__", "kind": "function", "doc": "

\n", "signature": "(graph_class=<class 'causy.graph.Graph'>)"}, "causy.graph.GraphManager.nodes": {"fullname": "causy.graph.GraphManager.nodes", "modulename": "causy.graph", "qualname": "GraphManager.nodes", "kind": "variable", "doc": "

\n", "annotation": ": OrderedDict[str, causy.graph.Node]"}, "causy.graph.GraphManager.edges": {"fullname": "causy.graph.GraphManager.edges", "modulename": "causy.graph", "qualname": "GraphManager.edges", "kind": "variable", "doc": "

\n", "annotation": ": Dict[str, Dict[str, causy.graph.Edge]]"}, "causy.graph.GraphManager.edge_history": {"fullname": "causy.graph.GraphManager.edge_history", "modulename": "causy.graph", "qualname": "GraphManager.edge_history", "kind": "variable", "doc": "

\n", "annotation": ": Dict[Tuple[str, str], List[causy.models.TestResult]]"}, "causy.graph.GraphManager.action_history": {"fullname": "causy.graph.GraphManager.action_history", "modulename": "causy.graph", "qualname": "GraphManager.action_history", "kind": "variable", "doc": "

\n", "annotation": ": List[Dict[str, List[causy.models.TestResult]]]"}, "causy.graph.GraphManager.graph": {"fullname": "causy.graph.GraphManager.graph", "modulename": "causy.graph", "qualname": "GraphManager.graph", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.graph.Graph]", "default_value": "None"}, "causy.graph.GraphManager.get_edge": {"fullname": "causy.graph.GraphManager.get_edge", "modulename": "causy.graph", "qualname": "GraphManager.get_edge", "kind": "function", "doc": "

Get an edge between two nodes

\n\n
Parameters
\n\n
    \n
  • u: u node
    • \n
  • v: v node
    • \n
\n\n
Returns
\n\n
\n

the edge

\n
\n", "signature": "(self, u: causy.graph.Node, v: causy.graph.Node) -> causy.graph.Edge:", "funcdef": "def"}, "causy.graph.GraphManager.add_edge": {"fullname": "causy.graph.GraphManager.add_edge", "modulename": "causy.graph", "qualname": "GraphManager.add_edge", "kind": "function", "doc": "

Add an edge to the graph

\n\n
Parameters
\n\n
    \n
  • edge_type: the type of the edge (e.g. undirected, directed, bidirected)
    • \n
  • u: u node
    • \n
  • v: v node
    • \n
  • metadata: metadata of the edge
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tu: causy.graph.Node,\tv: causy.graph.Node,\tmetadata: Dict,\tedge_type: causy.interfaces.EdgeTypeInterface = UNDIRECTED):", "funcdef": "def"}, "causy.graph.GraphManager.add_directed_edge": {"fullname": "causy.graph.GraphManager.add_directed_edge", "modulename": "causy.graph", "qualname": "GraphManager.add_directed_edge", "kind": "function", "doc": "

Add a directed edge from u to v to the graph

\n\n
Parameters
\n\n
    \n
  • edge_type:
    • \n
  • u: u node
    • \n
  • v: v node
    • \n
  • metadata: metadata of the edge
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tu: causy.graph.Node,\tv: causy.graph.Node,\tmetadata: Dict,\tedge_type: causy.interfaces.EdgeTypeInterface = DIRECTED):", "funcdef": "def"}, "causy.graph.GraphManager.add_edge_history": {"fullname": "causy.graph.GraphManager.add_edge_history", "modulename": "causy.graph", "qualname": "GraphManager.add_edge_history", "kind": "function", "doc": "

Add an action to the edge history

\n\n
Parameters
\n\n
    \n
  • u:
    • \n
  • v:
    • \n
  • action:
    • \n
\n\n
Returns
\n", "signature": "(self, u, v, action: causy.models.TestResult):", "funcdef": "def"}, "causy.graph.GraphManager.remove_edge": {"fullname": "causy.graph.GraphManager.remove_edge", "modulename": "causy.graph", "qualname": "GraphManager.remove_edge", "kind": "function", "doc": "

Remove an edge from the graph (undirected)

\n\n
Parameters
\n\n
    \n
  • u: u node
    • \n
  • v: v node
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tu: causy.graph.Node,\tv: causy.graph.Node,\tsoft_delete: bool = False):", "funcdef": "def"}, "causy.graph.GraphManager.restore_edge": {"fullname": "causy.graph.GraphManager.restore_edge", "modulename": "causy.graph", "qualname": "GraphManager.restore_edge", "kind": "function", "doc": "

Restore a deleted edge

\n\n
Parameters
\n\n
    \n
  • u:
    • \n
  • v:
    • \n
\n\n
Returns
\n", "signature": "(self, u: causy.graph.Node, v: causy.graph.Node):", "funcdef": "def"}, "causy.graph.GraphManager.remove_directed_edge": {"fullname": "causy.graph.GraphManager.remove_directed_edge", "modulename": "causy.graph", "qualname": "GraphManager.remove_directed_edge", "kind": "function", "doc": "
Parameters
\n\n
    \n
  • u:
    • \n
  • v:
    • \n
  • soft_delete: does not remove the edge, but marks it as deleted (useful in multithreading)
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tu: causy.graph.Node,\tv: causy.graph.Node,\tsoft_delete: bool = False):", "funcdef": "def"}, "causy.graph.GraphManager.restore_directed_edge": {"fullname": "causy.graph.GraphManager.restore_directed_edge", "modulename": "causy.graph", "qualname": "GraphManager.restore_directed_edge", "kind": "function", "doc": "

Restore a soft deleted edge

\n\n
Parameters
\n\n
    \n
  • u:
    • \n
  • v:
    • \n
\n\n
Returns
\n", "signature": "(self, u: causy.graph.Node, v: causy.graph.Node):", "funcdef": "def"}, "causy.graph.GraphManager.update_edge": {"fullname": "causy.graph.GraphManager.update_edge", "modulename": "causy.graph", "qualname": "GraphManager.update_edge", "kind": "function", "doc": "

Update an undirected edge in the graph

\n\n
Parameters
\n\n
    \n
  • u: u node
    • \n
  • v: v node
    • \n
  • value:
    • \n
  • edge_type:
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tu: causy.graph.Node,\tv: causy.graph.Node,\tmetadata: Dict = None,\tedge_type: causy.interfaces.EdgeTypeInterface = None):", "funcdef": "def"}, "causy.graph.GraphManager.update_directed_edge": {"fullname": "causy.graph.GraphManager.update_directed_edge", "modulename": "causy.graph", "qualname": "GraphManager.update_directed_edge", "kind": "function", "doc": "

Update an edge in the graph

\n\n
Parameters
\n\n
    \n
  • u: u node
    • \n
  • v: v node
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tu: causy.graph.Node,\tv: causy.graph.Node,\tmetadata: Dict = None,\tedge_type: causy.interfaces.EdgeTypeInterface = None):", "funcdef": "def"}, "causy.graph.GraphManager.purge_soft_deleted_edges": {"fullname": "causy.graph.GraphManager.purge_soft_deleted_edges", "modulename": "causy.graph", "qualname": "GraphManager.purge_soft_deleted_edges", "kind": "function", "doc": "

Remove all edges that are marked as soft deleted from the graph

\n", "signature": "(self):", "funcdef": "def"}, "causy.graph.GraphManager.add_node": {"fullname": "causy.graph.GraphManager.add_node", "modulename": "causy.graph", "qualname": "GraphManager.add_node", "kind": "function", "doc": "

Add a node to the graph

\n\n
Parameters
\n\n
    \n
  • metadata: add metadata to the node
    • \n
  • name: name of the node
    • \n
  • values: values of the node
    • \n
  • id_: id_ of the node\n:param : node
    • \n
\n\n
Returns
\n\n
\n

created Node

\n
\n", "signature": "(\tself,\tname: str,\tvalues: Union[List[float], torch.Tensor],\tid_: str = None,\tmetadata: Optional[Dict[str, Any]] = None) -> causy.graph.Node:", "funcdef": "def"}, "causy.graph_model": {"fullname": "causy.graph_model", "modulename": "causy.graph_model", "kind": "module", "doc": "

\n"}, "causy.graph_model.logger": {"fullname": "causy.graph_model.logger", "modulename": "causy.graph_model", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.graph_model (WARNING)>"}, "causy.graph_model.AbstractGraphModel": {"fullname": "causy.graph_model.AbstractGraphModel", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel", "kind": "class", "doc": "

The graph model is the main class of causy. It is responsible for creating a graph from data and executing the pipeline_steps.

\n\n

The graph model is responsible for the following tasks:

\n\n
    \n
  • Create a graph from data (create_graph_from_data)
    • \n
  • Execute the pipeline_steps (execute_pipeline_steps)
    • \n
  • Take actions on the graph (execute_pipeline_step & _take_action which is called by execute_pipeline_step)
    • \n
\n\n

It also initializes and takes care of the multiprocessing pool.

\n", "bases": "causy.interfaces.GraphModelInterface, abc.ABC"}, "causy.graph_model.AbstractGraphModel.__init__": {"fullname": "causy.graph_model.AbstractGraphModel.__init__", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel.__init__", "kind": "function", "doc": "

\n", "signature": "(graph=None, algorithm: causy.models.Algorithm = None)"}, "causy.graph_model.AbstractGraphModel.algorithm": {"fullname": "causy.graph_model.AbstractGraphModel.algorithm", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel.algorithm", "kind": "variable", "doc": "

\n", "annotation": ": causy.models.Algorithm"}, "causy.graph_model.AbstractGraphModel.pipeline_steps": {"fullname": "causy.graph_model.AbstractGraphModel.pipeline_steps", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel.pipeline_steps", "kind": "variable", "doc": "

\n", "annotation": ": List[causy.interfaces.PipelineStepInterface]"}, "causy.graph_model.AbstractGraphModel.graph": {"fullname": "causy.graph_model.AbstractGraphModel.graph", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel.graph", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.BaseGraphInterface"}, "causy.graph_model.AbstractGraphModel.pool": {"fullname": "causy.graph_model.AbstractGraphModel.pool", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel.pool", "kind": "variable", "doc": "

\n", "annotation": ": <bound method BaseContext.Pool of <multiprocessing.context.DefaultContext object at 0x7f6aea3b4b00>>"}, "causy.graph_model.AbstractGraphModel.create_graph_from_data": {"fullname": "causy.graph_model.AbstractGraphModel.create_graph_from_data", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel.create_graph_from_data", "kind": "function", "doc": "

Create a graph from data

\n\n
Parameters
\n\n
    \n
  • data: is a list of dictionaries or a dictionary with lists
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tdata: Union[List[Dict[str, float]], Dict[str, List[float]], causy.data_loader.AbstractDataLoader]):", "funcdef": "def"}, "causy.graph_model.AbstractGraphModel.create_all_possible_edges": {"fullname": "causy.graph_model.AbstractGraphModel.create_all_possible_edges", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel.create_all_possible_edges", "kind": "function", "doc": "

Create all possible edges on a graph\nTODO: replace me with the skeleton builders

\n\n
Returns
\n", "signature": "(self):", "funcdef": "def"}, "causy.graph_model.AbstractGraphModel.execute_pipeline_steps": {"fullname": "causy.graph_model.AbstractGraphModel.execute_pipeline_steps", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel.execute_pipeline_steps", "kind": "function", "doc": "

Execute all pipeline_steps

\n\n
Returns
\n\n
\n

the steps taken during the step execution

\n
\n", "signature": "(self) -> List[causy.models.ActionHistoryStep]:", "funcdef": "def"}, "causy.graph_model.AbstractGraphModel.execute_pipeline_step_with_progress": {"fullname": "causy.graph_model.AbstractGraphModel.execute_pipeline_step_with_progress", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel.execute_pipeline_step_with_progress", "kind": "function", "doc": "

\n", "signature": "(self) -> Generator:", "funcdef": "def"}, "causy.graph_model.AbstractGraphModel.execute_pipeline_step": {"fullname": "causy.graph_model.AbstractGraphModel.execute_pipeline_step", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel.execute_pipeline_step", "kind": "function", "doc": "

Execute a single pipeline_step on the graph. either in parallel or in a single process depending on the test_fn.parallel flag

\n\n
Parameters
\n\n
    \n
  • apply_to_graph: if the action should be applied to the graph
    • \n
  • test_fn: the test function
    • \n
  • threshold: the threshold
    • \n
\n\n
Returns
\n", "signature": "(\tself,\ttest_fn: causy.interfaces.PipelineStepInterface,\tapply_to_graph=True) -> Tuple[List[causy.models.TestResultAction], List[causy.models.TestResultAction]]:", "funcdef": "def"}, "causy.graph_model.graph_model_factory": {"fullname": "causy.graph_model.graph_model_factory", "modulename": "causy.graph_model", "qualname": "graph_model_factory", "kind": "function", "doc": "

Create a graph model based on a List of pipeline_steps

\n\n
Parameters
\n\n
    \n
  • algorithm: the algorithm which should be used to create the graph model
    • \n
\n\n
Returns
\n\n
\n

the graph model

\n
\n", "signature": "(\talgorithm: causy.models.Algorithm = None,\tvariables: Dict[str, causy.variables.VariableTypes] = None) -> type[causy.graph_model.AbstractGraphModel]:", "funcdef": "def"}, "causy.graph_utils": {"fullname": "causy.graph_utils", "modulename": "causy.graph_utils", "kind": "module", "doc": "

\n"}, "causy.graph_utils.unpack_run": {"fullname": "causy.graph_utils.unpack_run", "modulename": "causy.graph_utils", "qualname": "unpack_run", "kind": "function", "doc": "

\n", "signature": "(args):", "funcdef": "def"}, "causy.graph_utils.serialize_module_name": {"fullname": "causy.graph_utils.serialize_module_name", "modulename": "causy.graph_utils", "qualname": "serialize_module_name", "kind": "function", "doc": "

\n", "signature": "(cls):", "funcdef": "def"}, "causy.graph_utils.load_pipeline_artefact_by_definition": {"fullname": "causy.graph_utils.load_pipeline_artefact_by_definition", "modulename": "causy.graph_utils", "qualname": "load_pipeline_artefact_by_definition", "kind": "function", "doc": "

\n", "signature": "(step):", "funcdef": "def"}, "causy.graph_utils.load_pipeline_steps_by_definition": {"fullname": "causy.graph_utils.load_pipeline_steps_by_definition", "modulename": "causy.graph_utils", "qualname": "load_pipeline_steps_by_definition", "kind": "function", "doc": "

\n", "signature": "(steps):", "funcdef": "def"}, "causy.graph_utils.retrieve_edges": {"fullname": "causy.graph_utils.retrieve_edges", "modulename": "causy.graph_utils", "qualname": "retrieve_edges", "kind": "function", "doc": "

Returns a list of edges from the graph

\n\n
Parameters
\n\n
    \n
  • graph: a graph
    • \n
\n\n
Returns
\n\n
\n

a list of edges

\n
\n", "signature": "(graph) -> List[Tuple[str, str]]:", "funcdef": "def"}, "causy.graph_utils.hash_dictionary": {"fullname": "causy.graph_utils.hash_dictionary", "modulename": "causy.graph_utils", "qualname": "hash_dictionary", "kind": "function", "doc": "

Hash a dictionary using SHA256 (e.g. for caching)

\n\n
Parameters
\n\n
    \n
  • dct:
    • \n
\n\n
Returns
\n", "signature": "(dct: Dict):", "funcdef": "def"}, "causy.interfaces": {"fullname": "causy.interfaces", "modulename": "causy.interfaces", "kind": "module", "doc": "

\n"}, "causy.interfaces.logger": {"fullname": "causy.interfaces.logger", "modulename": "causy.interfaces", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.interfaces (WARNING)>"}, "causy.interfaces.DEFAULT_THRESHOLD": {"fullname": "causy.interfaces.DEFAULT_THRESHOLD", "modulename": "causy.interfaces", "qualname": "DEFAULT_THRESHOLD", "kind": "variable", "doc": "

\n", "default_value": "0.01"}, "causy.interfaces.AS_MANY_AS_FIELDS": {"fullname": "causy.interfaces.AS_MANY_AS_FIELDS", "modulename": "causy.interfaces", "qualname": "AS_MANY_AS_FIELDS", "kind": "variable", "doc": "

\n", "default_value": "0"}, "causy.interfaces.MetadataBaseType": {"fullname": "causy.interfaces.MetadataBaseType", "modulename": "causy.interfaces", "qualname": "MetadataBaseType", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[str, int, float, bool]"}, "causy.interfaces.MetadataType": {"fullname": "causy.interfaces.MetadataType", "modulename": "causy.interfaces", "qualname": "MetadataType", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[str, int, float, bool, typing.List[typing.Union[str, int, float, bool]], typing.Dict[str, typing.Union[str, int, float, bool]]]"}, "causy.interfaces.ComparisonSettingsInterface": {"fullname": "causy.interfaces.ComparisonSettingsInterface", "modulename": "causy.interfaces", "qualname": "ComparisonSettingsInterface", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel, abc.ABC"}, "causy.interfaces.ComparisonSettingsInterface.min": {"fullname": "causy.interfaces.ComparisonSettingsInterface.min", "modulename": "causy.interfaces", "qualname": "ComparisonSettingsInterface.min", "kind": "variable", "doc": "

\n", "annotation": ": Union[int, causy.variables.VariableReference]"}, "causy.interfaces.ComparisonSettingsInterface.max": {"fullname": "causy.interfaces.ComparisonSettingsInterface.max", "modulename": "causy.interfaces", "qualname": "ComparisonSettingsInterface.max", "kind": "variable", "doc": "

\n", "annotation": ": Union[int, causy.variables.VariableReference]"}, "causy.interfaces.ComparisonSettingsInterface.name": {"fullname": "causy.interfaces.ComparisonSettingsInterface.name", "modulename": "causy.interfaces", "qualname": "ComparisonSettingsInterface.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.ComparisonSettingsInterface.model_config": {"fullname": "causy.interfaces.ComparisonSettingsInterface.model_config", "modulename": "causy.interfaces", "qualname": "ComparisonSettingsInterface.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.interfaces.ComparisonSettingsInterface.model_fields": {"fullname": "causy.interfaces.ComparisonSettingsInterface.model_fields", "modulename": "causy.interfaces", "qualname": "ComparisonSettingsInterface.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'min': FieldInfo(annotation=Union[int, VariableReference], required=True), 'max': FieldInfo(annotation=Union[int, VariableReference], required=True)}"}, "causy.interfaces.ComparisonSettingsInterface.model_computed_fields": {"fullname": "causy.interfaces.ComparisonSettingsInterface.model_computed_fields", "modulename": "causy.interfaces", "qualname": "ComparisonSettingsInterface.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': ComputedFieldInfo(wrapped_property=<property object>, return_type=<class 'str'>, alias=None, alias_priority=None, title=None, field_title_generator=None, description=None, deprecated=None, examples=None, json_schema_extra=None, repr=True)}"}, "causy.interfaces.NodeInterface": {"fullname": "causy.interfaces.NodeInterface", "modulename": "causy.interfaces", "qualname": "NodeInterface", "kind": "class", "doc": "

Node interface for the graph. A node is defined by a name and a value.

\n", "bases": "pydantic.main.BaseModel, abc.ABC"}, "causy.interfaces.NodeInterface.name": {"fullname": "causy.interfaces.NodeInterface.name", "modulename": "causy.interfaces", "qualname": "NodeInterface.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.NodeInterface.id": {"fullname": "causy.interfaces.NodeInterface.id", "modulename": "causy.interfaces", "qualname": "NodeInterface.id", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.NodeInterface.values": {"fullname": "causy.interfaces.NodeInterface.values", "modulename": "causy.interfaces", "qualname": "NodeInterface.values", "kind": "variable", "doc": "

\n", "annotation": ": Annotated[Optional[torch.DoubleTensor], WithJsonSchema(json_schema={'type': 'array', 'items': {'type': 'number'}, 'description': 'Node values'}, mode=None)]"}, "causy.interfaces.NodeInterface.Config": {"fullname": "causy.interfaces.NodeInterface.Config", "modulename": "causy.interfaces", "qualname": "NodeInterface.Config", "kind": "class", "doc": "

\n"}, "causy.interfaces.NodeInterface.Config.arbitrary_types_allowed": {"fullname": "causy.interfaces.NodeInterface.Config.arbitrary_types_allowed", "modulename": "causy.interfaces", "qualname": "NodeInterface.Config.arbitrary_types_allowed", "kind": "variable", "doc": "

\n", "default_value": "True"}, "causy.interfaces.NodeInterface.model_config": {"fullname": "causy.interfaces.NodeInterface.model_config", "modulename": "causy.interfaces", "qualname": "NodeInterface.model_config", "kind": "variable", "doc": "

\n", "default_value": "{'arbitrary_types_allowed': True}"}, "causy.interfaces.NodeInterface.model_fields": {"fullname": "causy.interfaces.NodeInterface.model_fields", "modulename": "causy.interfaces", "qualname": "NodeInterface.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': FieldInfo(annotation=str, required=True), 'id': FieldInfo(annotation=str, required=True), 'values': FieldInfo(annotation=Union[DoubleTensor, NoneType], required=False, default=None, exclude=True, metadata=[WithJsonSchema(json_schema={'type': 'array', 'items': {'type': 'number'}, 'description': 'Node values'}, mode=None)])}"}, "causy.interfaces.NodeInterface.model_computed_fields": {"fullname": "causy.interfaces.NodeInterface.model_computed_fields", "modulename": "causy.interfaces", "qualname": "NodeInterface.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.interfaces.EdgeTypeInterface": {"fullname": "causy.interfaces.EdgeTypeInterface", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface", "kind": "class", "doc": "

Edge type interface for the graph\nAn edge type is defined by a name

\n", "bases": "abc.ABC, pydantic.main.BaseModel, typing.Generic[~EdgeTypeInterfaceType]"}, "causy.interfaces.EdgeTypeInterface.name": {"fullname": "causy.interfaces.EdgeTypeInterface.name", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.EdgeTypeInterface.IS_DIRECTED": {"fullname": "causy.interfaces.EdgeTypeInterface.IS_DIRECTED", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.IS_DIRECTED", "kind": "variable", "doc": "

\n", "annotation": ": bool"}, "causy.interfaces.EdgeTypeInterface.STR_REPRESENTATION": {"fullname": "causy.interfaces.EdgeTypeInterface.STR_REPRESENTATION", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.STR_REPRESENTATION", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.EdgeTypeInterface.GraphAccessMixin": {"fullname": "causy.interfaces.EdgeTypeInterface.GraphAccessMixin", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.GraphAccessMixin", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC"}, "causy.interfaces.EdgeTypeInterface.pre_edge_remove_hook": {"fullname": "causy.interfaces.EdgeTypeInterface.pre_edge_remove_hook", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.pre_edge_remove_hook", "kind": "function", "doc": "

Hook that is executed before an edge is deleted.

\n\n
Parameters
\n\n
    \n
  • graph: the graph
    • \n
  • edge: the edge
    • \n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tedge: causy.interfaces.EdgeInterface):", "funcdef": "def"}, "causy.interfaces.EdgeTypeInterface.post_edge_remove_hook": {"fullname": "causy.interfaces.EdgeTypeInterface.post_edge_remove_hook", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.post_edge_remove_hook", "kind": "function", "doc": "

Hook that is executed after an edge is deleted.

\n\n
Parameters
\n\n
    \n
  • graph: the graph
    • \n
  • edge: the edge
    • \n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tedge: causy.interfaces.EdgeInterface):", "funcdef": "def"}, "causy.interfaces.EdgeTypeInterface.pre_edge_add_hook": {"fullname": "causy.interfaces.EdgeTypeInterface.pre_edge_add_hook", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.pre_edge_add_hook", "kind": "function", "doc": "

Hook that is executed before an edge is added.

\n\n
Parameters
\n\n
    \n
  • graph: the graph
    • \n
  • edge: the edge
    • \n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tedge: causy.interfaces.EdgeInterface):", "funcdef": "def"}, "causy.interfaces.EdgeTypeInterface.post_edge_add_hook": {"fullname": "causy.interfaces.EdgeTypeInterface.post_edge_add_hook", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.post_edge_add_hook", "kind": "function", "doc": "

Hook that is executed after an edge is added.

\n\n
Parameters
\n\n
    \n
  • graph: the graph
    • \n
  • edge: the edge
    • \n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tedge: causy.interfaces.EdgeInterface):", "funcdef": "def"}, "causy.interfaces.EdgeTypeInterface.pre_edge_update_hook": {"fullname": "causy.interfaces.EdgeTypeInterface.pre_edge_update_hook", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.pre_edge_update_hook", "kind": "function", "doc": "

Hook that is executed before an edge is updated.

\n\n
Parameters
\n\n
    \n
  • graph: the graph
    • \n
  • edge: the edge
    • \n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tedge: causy.interfaces.EdgeInterface):", "funcdef": "def"}, "causy.interfaces.EdgeTypeInterface.post_edge_update_hook": {"fullname": "causy.interfaces.EdgeTypeInterface.post_edge_update_hook", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.post_edge_update_hook", "kind": "function", "doc": "

Hook that is executed after an edge is updated.

\n\n
Parameters
\n\n
    \n
  • graph: the graph
    • \n
  • edge: the edge
    • \n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tedge: causy.interfaces.EdgeInterface):", "funcdef": "def"}, "causy.interfaces.EdgeTypeInterface.pre_edge_type_change_hook": {"fullname": "causy.interfaces.EdgeTypeInterface.pre_edge_type_change_hook", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.pre_edge_type_change_hook", "kind": "function", "doc": "

Hook that is executed before an edge type is changed.

\n\n
Parameters
\n\n
    \n
  • graph: the graph
    • \n
  • edge: the edge
    • \n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tedge: causy.interfaces.EdgeInterface):", "funcdef": "def"}, "causy.interfaces.EdgeTypeInterface.post_edge_type_change_hook": {"fullname": "causy.interfaces.EdgeTypeInterface.post_edge_type_change_hook", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.post_edge_type_change_hook", "kind": "function", "doc": "

Hook that is executed after an edge type is changed.

\n\n
Parameters
\n\n
    \n
  • graph: the graph
    • \n
  • edge: the edge
    • \n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tedge: causy.interfaces.EdgeInterface):", "funcdef": "def"}, "causy.interfaces.EdgeInterface": {"fullname": "causy.interfaces.EdgeInterface", "modulename": "causy.interfaces", "qualname": "EdgeInterface", "kind": "class", "doc": "

Edge interface for the graph\nA graph edge is defined by two nodes and an edge type. It can also have metadata.

\n", "bases": "pydantic.main.BaseModel, abc.ABC"}, "causy.interfaces.EdgeInterface.u": {"fullname": "causy.interfaces.EdgeInterface.u", "modulename": "causy.interfaces", "qualname": "EdgeInterface.u", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.NodeInterface"}, "causy.interfaces.EdgeInterface.v": {"fullname": "causy.interfaces.EdgeInterface.v", "modulename": "causy.interfaces", "qualname": "EdgeInterface.v", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.NodeInterface"}, "causy.interfaces.EdgeInterface.edge_type": {"fullname": "causy.interfaces.EdgeInterface.edge_type", "modulename": "causy.interfaces", "qualname": "EdgeInterface.edge_type", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.EdgeTypeInterface"}, "causy.interfaces.EdgeInterface.metadata": {"fullname": "causy.interfaces.EdgeInterface.metadata", "modulename": "causy.interfaces", "qualname": "EdgeInterface.metadata", "kind": "variable", "doc": "

\n", "annotation": ": Dict[str, Union[str, int, float, bool, List[Union[str, int, float, bool]], Dict[str, Union[str, int, float, bool]]]]"}, "causy.interfaces.EdgeInterface.Config": {"fullname": "causy.interfaces.EdgeInterface.Config", "modulename": "causy.interfaces", "qualname": "EdgeInterface.Config", "kind": "class", "doc": "

\n"}, "causy.interfaces.EdgeInterface.Config.arbitrary_types_allowed": {"fullname": "causy.interfaces.EdgeInterface.Config.arbitrary_types_allowed", "modulename": "causy.interfaces", "qualname": "EdgeInterface.Config.arbitrary_types_allowed", "kind": "variable", "doc": "

\n", "default_value": "True"}, "causy.interfaces.EdgeInterface.is_connection_between_same_nodes": {"fullname": "causy.interfaces.EdgeInterface.is_connection_between_same_nodes", "modulename": "causy.interfaces", "qualname": "EdgeInterface.is_connection_between_same_nodes", "kind": "function", "doc": "

\n", "signature": "(self, edge):", "funcdef": "def"}, "causy.interfaces.EdgeInterface.model_config": {"fullname": "causy.interfaces.EdgeInterface.model_config", "modulename": "causy.interfaces", "qualname": "EdgeInterface.model_config", "kind": "variable", "doc": "

\n", "default_value": "{'arbitrary_types_allowed': True}"}, "causy.interfaces.EdgeInterface.model_fields": {"fullname": "causy.interfaces.EdgeInterface.model_fields", "modulename": "causy.interfaces", "qualname": "EdgeInterface.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'u': FieldInfo(annotation=NodeInterface, required=True), 'v': FieldInfo(annotation=NodeInterface, required=True), 'edge_type': FieldInfo(annotation=EdgeTypeInterface, required=True), 'metadata': FieldInfo(annotation=Dict[str, Union[str, int, float, bool, List[Union[str, int, float, bool]], Dict[str, Union[str, int, float, bool]]]], required=False, default=None)}"}, "causy.interfaces.EdgeInterface.model_computed_fields": {"fullname": "causy.interfaces.EdgeInterface.model_computed_fields", "modulename": "causy.interfaces", "qualname": "EdgeInterface.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.interfaces.TestResultInterface": {"fullname": "causy.interfaces.TestResultInterface", "modulename": "causy.interfaces", "qualname": "TestResultInterface", "kind": "class", "doc": "

Test result interface for the graph\nA test result is defined by two nodes and an action. It can also have metadata.

\n", "bases": "pydantic.main.BaseModel, abc.ABC"}, "causy.interfaces.TestResultInterface.u": {"fullname": "causy.interfaces.TestResultInterface.u", "modulename": "causy.interfaces", "qualname": "TestResultInterface.u", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.NodeInterface"}, "causy.interfaces.TestResultInterface.v": {"fullname": "causy.interfaces.TestResultInterface.v", "modulename": "causy.interfaces", "qualname": "TestResultInterface.v", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.NodeInterface"}, "causy.interfaces.TestResultInterface.action": {"fullname": "causy.interfaces.TestResultInterface.action", "modulename": "causy.interfaces", "qualname": "TestResultInterface.action", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.TestResultInterface.data": {"fullname": "causy.interfaces.TestResultInterface.data", "modulename": "causy.interfaces", "qualname": "TestResultInterface.data", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict]"}, "causy.interfaces.TestResultInterface.Config": {"fullname": "causy.interfaces.TestResultInterface.Config", "modulename": "causy.interfaces", "qualname": "TestResultInterface.Config", "kind": "class", "doc": "

\n"}, "causy.interfaces.TestResultInterface.Config.arbitrary_types_allowed": {"fullname": "causy.interfaces.TestResultInterface.Config.arbitrary_types_allowed", "modulename": "causy.interfaces", "qualname": "TestResultInterface.Config.arbitrary_types_allowed", "kind": "variable", "doc": "

\n", "default_value": "True"}, "causy.interfaces.TestResultInterface.model_config": {"fullname": "causy.interfaces.TestResultInterface.model_config", "modulename": "causy.interfaces", "qualname": "TestResultInterface.model_config", "kind": "variable", "doc": "

\n", "default_value": "{'arbitrary_types_allowed': True}"}, "causy.interfaces.TestResultInterface.model_fields": {"fullname": "causy.interfaces.TestResultInterface.model_fields", "modulename": "causy.interfaces", "qualname": "TestResultInterface.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'u': FieldInfo(annotation=NodeInterface, required=True), 'v': FieldInfo(annotation=NodeInterface, required=True), 'action': FieldInfo(annotation=str, required=True), 'data': FieldInfo(annotation=Union[Dict, NoneType], required=False, default=None)}"}, "causy.interfaces.TestResultInterface.model_computed_fields": {"fullname": "causy.interfaces.TestResultInterface.model_computed_fields", "modulename": "causy.interfaces", "qualname": "TestResultInterface.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.interfaces.BaseGraphInterface": {"fullname": "causy.interfaces.BaseGraphInterface", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC"}, "causy.interfaces.BaseGraphInterface.nodes": {"fullname": "causy.interfaces.BaseGraphInterface.nodes", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.nodes", "kind": "variable", "doc": "

\n", "annotation": ": Dict[str, causy.interfaces.NodeInterface]"}, "causy.interfaces.BaseGraphInterface.edges": {"fullname": "causy.interfaces.BaseGraphInterface.edges", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.edges", "kind": "variable", "doc": "

\n", "annotation": ": Dict[str, Dict[str, Dict]]"}, "causy.interfaces.BaseGraphInterface.retrieve_edge_history": {"fullname": "causy.interfaces.BaseGraphInterface.retrieve_edge_history", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.retrieve_edge_history", "kind": "function", "doc": "

\n", "signature": "(self, u, v, action: str) -> List[causy.interfaces.TestResultInterface]:", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.add_edge_history": {"fullname": "causy.interfaces.BaseGraphInterface.add_edge_history", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.add_edge_history", "kind": "function", "doc": "

\n", "signature": "(self, u, v, action: causy.interfaces.TestResultInterface):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.add_edge": {"fullname": "causy.interfaces.BaseGraphInterface.add_edge", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.add_edge", "kind": "function", "doc": "

\n", "signature": "(self, u, v, metadata):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.remove_edge": {"fullname": "causy.interfaces.BaseGraphInterface.remove_edge", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.remove_edge", "kind": "function", "doc": "

\n", "signature": "(self, u, v):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.remove_directed_edge": {"fullname": "causy.interfaces.BaseGraphInterface.remove_directed_edge", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.remove_directed_edge", "kind": "function", "doc": "

\n", "signature": "(self, u, v):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.update_edge": {"fullname": "causy.interfaces.BaseGraphInterface.update_edge", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.update_edge", "kind": "function", "doc": "

\n", "signature": "(self, u, v, metadata=None, edge_type=None):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.update_directed_edge": {"fullname": "causy.interfaces.BaseGraphInterface.update_directed_edge", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.update_directed_edge", "kind": "function", "doc": "

\n", "signature": "(self, u, v, metadata=None, edge_type=None):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.add_node": {"fullname": "causy.interfaces.BaseGraphInterface.add_node", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.add_node", "kind": "function", "doc": "

\n", "signature": "(self, name, values) -> causy.interfaces.NodeInterface:", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.edge_value": {"fullname": "causy.interfaces.BaseGraphInterface.edge_value", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.edge_value", "kind": "function", "doc": "

\n", "signature": "(self, u, v):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.undirected_edge_exists": {"fullname": "causy.interfaces.BaseGraphInterface.undirected_edge_exists", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.undirected_edge_exists", "kind": "function", "doc": "

\n", "signature": "(self, u, v):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.directed_edge_exists": {"fullname": "causy.interfaces.BaseGraphInterface.directed_edge_exists", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.directed_edge_exists", "kind": "function", "doc": "

\n", "signature": "(self, u, v):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.edge_exists": {"fullname": "causy.interfaces.BaseGraphInterface.edge_exists", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.edge_exists", "kind": "function", "doc": "

\n", "signature": "(self, u, v, ignore_soft_deleted=False):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.restore_edge": {"fullname": "causy.interfaces.BaseGraphInterface.restore_edge", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.restore_edge", "kind": "function", "doc": "

\n", "signature": "(self, u, v):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.restore_directed_edge": {"fullname": "causy.interfaces.BaseGraphInterface.restore_directed_edge", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.restore_directed_edge", "kind": "function", "doc": "

\n", "signature": "(self, u, v):", "funcdef": "def"}, "causy.interfaces.GraphModelInterface": {"fullname": "causy.interfaces.GraphModelInterface", "modulename": "causy.interfaces", "qualname": "GraphModelInterface", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC"}, "causy.interfaces.GraphModelInterface.pool": {"fullname": "causy.interfaces.GraphModelInterface.pool", "modulename": "causy.interfaces", "qualname": "GraphModelInterface.pool", "kind": "variable", "doc": "

\n", "annotation": ": <bound method BaseContext.Pool of <multiprocessing.context.DefaultContext object at 0x7f6aea3b4b00>>"}, "causy.interfaces.GraphModelInterface.create_graph_from_data": {"fullname": "causy.interfaces.GraphModelInterface.create_graph_from_data", "modulename": "causy.interfaces", "qualname": "GraphModelInterface.create_graph_from_data", "kind": "function", "doc": "

\n", "signature": "(self, data: List[Dict]):", "funcdef": "def"}, "causy.interfaces.GraphModelInterface.execute_pipeline_steps": {"fullname": "causy.interfaces.GraphModelInterface.execute_pipeline_steps", "modulename": "causy.interfaces", "qualname": "GraphModelInterface.execute_pipeline_steps", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "causy.interfaces.GraphModelInterface.execute_pipeline_step": {"fullname": "causy.interfaces.GraphModelInterface.execute_pipeline_step", "modulename": "causy.interfaces", "qualname": "GraphModelInterface.execute_pipeline_step", "kind": "function", "doc": "

\n", "signature": "(self, step, apply_to_graph: bool = True):", "funcdef": "def"}, "causy.interfaces.GeneratorInterface": {"fullname": "causy.interfaces.GeneratorInterface", "modulename": "causy.interfaces", "qualname": "GeneratorInterface", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC, pydantic.main.BaseModel"}, "causy.interfaces.GeneratorInterface.comparison_settings": {"fullname": "causy.interfaces.GeneratorInterface.comparison_settings", "modulename": "causy.interfaces", "qualname": "GeneratorInterface.comparison_settings", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.interfaces.ComparisonSettingsInterface]"}, "causy.interfaces.GeneratorInterface.chunked": {"fullname": "causy.interfaces.GeneratorInterface.chunked", "modulename": "causy.interfaces", "qualname": "GeneratorInterface.chunked", "kind": "variable", "doc": "

\n", "annotation": ": Union[bool, causy.variables.VariableReference, NoneType]"}, "causy.interfaces.GeneratorInterface.every_nth": {"fullname": "causy.interfaces.GeneratorInterface.every_nth", "modulename": "causy.interfaces", "qualname": "GeneratorInterface.every_nth", "kind": "variable", "doc": "

\n", "annotation": ": Union[int, causy.variables.VariableReference, NoneType]"}, "causy.interfaces.GeneratorInterface.generator": {"fullname": "causy.interfaces.GeneratorInterface.generator", "modulename": "causy.interfaces", "qualname": "GeneratorInterface.generator", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.interfaces.GeneratorInterface]"}, "causy.interfaces.GeneratorInterface.shuffle_combinations": {"fullname": "causy.interfaces.GeneratorInterface.shuffle_combinations", "modulename": "causy.interfaces", "qualname": "GeneratorInterface.shuffle_combinations", "kind": "variable", "doc": "

\n", "annotation": ": Union[bool, causy.variables.VariableReference, NoneType]"}, "causy.interfaces.GeneratorInterface.generate": {"fullname": "causy.interfaces.GeneratorInterface.generate", "modulename": "causy.interfaces", "qualname": "GeneratorInterface.generate", "kind": "function", "doc": "

\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tgraph_model_instance_: dict):", "funcdef": "def"}, "causy.interfaces.GeneratorInterface.name": {"fullname": "causy.interfaces.GeneratorInterface.name", "modulename": "causy.interfaces", "qualname": "GeneratorInterface.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.GeneratorInterface.model_config": {"fullname": "causy.interfaces.GeneratorInterface.model_config", "modulename": "causy.interfaces", "qualname": "GeneratorInterface.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.interfaces.GeneratorInterface.model_fields": {"fullname": "causy.interfaces.GeneratorInterface.model_fields", "modulename": "causy.interfaces", "qualname": "GeneratorInterface.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'comparison_settings': FieldInfo(annotation=Union[ComparisonSettingsInterface, NoneType], required=False, default=None), 'chunked': FieldInfo(annotation=Union[bool, VariableReference, NoneType], required=False, default=False), 'every_nth': FieldInfo(annotation=Union[int, VariableReference, NoneType], required=False, default=None), 'generator': FieldInfo(annotation=Union[GeneratorInterface, NoneType], required=False, default=None), 'shuffle_combinations': FieldInfo(annotation=Union[bool, VariableReference, NoneType], required=False, default=None)}"}, "causy.interfaces.GeneratorInterface.model_computed_fields": {"fullname": "causy.interfaces.GeneratorInterface.model_computed_fields", "modulename": "causy.interfaces", "qualname": "GeneratorInterface.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': ComputedFieldInfo(wrapped_property=<property object>, return_type=<class 'str'>, alias=None, alias_priority=None, title=None, field_title_generator=None, description=None, deprecated=None, examples=None, json_schema_extra=None, repr=True)}"}, "causy.interfaces.PipelineStepInterface": {"fullname": "causy.interfaces.PipelineStepInterface", "modulename": "causy.interfaces", "qualname": "PipelineStepInterface", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC, pydantic.main.BaseModel, typing.Generic[~PipelineStepInterfaceType]"}, "causy.interfaces.PipelineStepInterface.generator": {"fullname": "causy.interfaces.PipelineStepInterface.generator", "modulename": "causy.interfaces", "qualname": "PipelineStepInterface.generator", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.interfaces.GeneratorInterface]"}, "causy.interfaces.PipelineStepInterface.threshold": {"fullname": "causy.interfaces.PipelineStepInterface.threshold", "modulename": "causy.interfaces", "qualname": "PipelineStepInterface.threshold", "kind": "variable", "doc": "

\n", "annotation": ": Union[float, causy.variables.VariableReference, NoneType]"}, "causy.interfaces.PipelineStepInterface.chunk_size_parallel_processing": {"fullname": "causy.interfaces.PipelineStepInterface.chunk_size_parallel_processing", "modulename": "causy.interfaces", "qualname": "PipelineStepInterface.chunk_size_parallel_processing", "kind": "variable", "doc": "

\n", "annotation": ": Union[int, causy.variables.VariableReference]"}, "causy.interfaces.PipelineStepInterface.parallel": {"fullname": "causy.interfaces.PipelineStepInterface.parallel", "modulename": "causy.interfaces", "qualname": "PipelineStepInterface.parallel", "kind": "variable", "doc": "

\n", "annotation": ": Union[bool, causy.variables.VariableReference]"}, "causy.interfaces.PipelineStepInterface.display_name": {"fullname": "causy.interfaces.PipelineStepInterface.display_name", "modulename": "causy.interfaces", "qualname": "PipelineStepInterface.display_name", "kind": "variable", "doc": "

\n", "annotation": ": Union[str, causy.variables.VariableReference, NoneType]"}, "causy.interfaces.PipelineStepInterface.needs_unapplied_actions": {"fullname": "causy.interfaces.PipelineStepInterface.needs_unapplied_actions", "modulename": "causy.interfaces", "qualname": "PipelineStepInterface.needs_unapplied_actions", "kind": "variable", "doc": "

\n", "annotation": ": Union[bool, causy.variables.VariableReference, NoneType]"}, "causy.interfaces.PipelineStepInterface.apply_synchronous": {"fullname": "causy.interfaces.PipelineStepInterface.apply_synchronous", "modulename": "causy.interfaces", "qualname": "PipelineStepInterface.apply_synchronous", "kind": "variable", "doc": "

\n", "annotation": ": Union[bool, causy.variables.VariableReference, NoneType]"}, "causy.interfaces.PipelineStepInterface.name": {"fullname": "causy.interfaces.PipelineStepInterface.name", "modulename": "causy.interfaces", "qualname": "PipelineStepInterface.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.PipelineStepInterface.process": {"fullname": "causy.interfaces.PipelineStepInterface.process", "modulename": "causy.interfaces", "qualname": "PipelineStepInterface.process", "kind": "function", "doc": "

Test if u and v are independent

\n\n
Parameters
\n\n
    \n
  • u: u values
    • \n
  • v: v values
    • \n
\n\n
Returns
\n\n
\n

True if independent, False otherwise

\n
\n", "signature": "(\tself,\tnodes: List[str],\tgraph: causy.interfaces.BaseGraphInterface,\tunapplied_actions: Optional[List[causy.interfaces.TestResultInterface]] = None) -> Optional[causy.interfaces.TestResultInterface]:", "funcdef": "def"}, "causy.interfaces.ExitConditionInterface": {"fullname": "causy.interfaces.ExitConditionInterface", "modulename": "causy.interfaces", "qualname": "ExitConditionInterface", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC, pydantic.main.BaseModel"}, "causy.interfaces.ExitConditionInterface.check": {"fullname": "causy.interfaces.ExitConditionInterface.check", "modulename": "causy.interfaces", "qualname": "ExitConditionInterface.check", "kind": "function", "doc": "
Parameters
\n\n
    \n
  • graph:
    • \n
  • graph_model_instance_:
    • \n
  • actions_taken:
    • \n
  • iteration:
    • \n
\n\n
Returns
\n\n
\n

True if you want to break an iteration, False otherwise

\n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tgraph_model_instance_: causy.interfaces.GraphModelInterface,\tactions_taken: List[causy.interfaces.TestResultInterface],\titeration: Union[int, causy.variables.VariableReference]) -> bool:", "funcdef": "def"}, "causy.interfaces.ExitConditionInterface.name": {"fullname": "causy.interfaces.ExitConditionInterface.name", "modulename": "causy.interfaces", "qualname": "ExitConditionInterface.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.ExitConditionInterface.model_config": {"fullname": "causy.interfaces.ExitConditionInterface.model_config", "modulename": "causy.interfaces", "qualname": "ExitConditionInterface.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.interfaces.ExitConditionInterface.model_fields": {"fullname": "causy.interfaces.ExitConditionInterface.model_fields", "modulename": "causy.interfaces", "qualname": "ExitConditionInterface.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.interfaces.ExitConditionInterface.model_computed_fields": {"fullname": "causy.interfaces.ExitConditionInterface.model_computed_fields", "modulename": "causy.interfaces", "qualname": "ExitConditionInterface.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': ComputedFieldInfo(wrapped_property=<property object>, return_type=<class 'str'>, alias=None, alias_priority=None, title=None, field_title_generator=None, description=None, deprecated=None, examples=None, json_schema_extra=None, repr=True)}"}, "causy.interfaces.LogicStepInterface": {"fullname": "causy.interfaces.LogicStepInterface", "modulename": "causy.interfaces", "qualname": "LogicStepInterface", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC, pydantic.main.BaseModel, typing.Generic[~LogicStepInterfaceType]"}, "causy.interfaces.LogicStepInterface.pipeline_steps": {"fullname": "causy.interfaces.LogicStepInterface.pipeline_steps", "modulename": "causy.interfaces", "qualname": "LogicStepInterface.pipeline_steps", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[~PipelineStepInterfaceType]]"}, "causy.interfaces.LogicStepInterface.exit_condition": {"fullname": "causy.interfaces.LogicStepInterface.exit_condition", "modulename": "causy.interfaces", "qualname": "LogicStepInterface.exit_condition", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.interfaces.ExitConditionInterface]"}, "causy.interfaces.LogicStepInterface.display_name": {"fullname": "causy.interfaces.LogicStepInterface.display_name", "modulename": "causy.interfaces", "qualname": "LogicStepInterface.display_name", "kind": "variable", "doc": "

\n", "annotation": ": Union[str, causy.variables.VariableReference, NoneType]"}, "causy.interfaces.LogicStepInterface.execute": {"fullname": "causy.interfaces.LogicStepInterface.execute", "modulename": "causy.interfaces", "qualname": "LogicStepInterface.execute", "kind": "function", "doc": "

\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tgraph_model_instance_: dict):", "funcdef": "def"}, "causy.interfaces.LogicStepInterface.name": {"fullname": "causy.interfaces.LogicStepInterface.name", "modulename": "causy.interfaces", "qualname": "LogicStepInterface.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.ExtensionInterface": {"fullname": "causy.interfaces.ExtensionInterface", "modulename": "causy.interfaces", "qualname": "ExtensionInterface", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel, typing.Generic[~ExtensionType]"}, "causy.interfaces.ExtensionInterface.name": {"fullname": "causy.interfaces.ExtensionInterface.name", "modulename": "causy.interfaces", "qualname": "ExtensionInterface.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.ExtensionInterface.GraphAccessMixin": {"fullname": "causy.interfaces.ExtensionInterface.GraphAccessMixin", "modulename": "causy.interfaces", "qualname": "ExtensionInterface.GraphAccessMixin", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC"}, "causy.interfaces.GraphUpdateHook": {"fullname": "causy.interfaces.GraphUpdateHook", "modulename": "causy.interfaces", "qualname": "GraphUpdateHook", "kind": "class", "doc": "

A hook that is executed before or after the graph is updated. This can be used to modify the graph before or after an update.

\n", "bases": "pydantic.main.BaseModel"}, "causy.interfaces.GraphUpdateHook.execute": {"fullname": "causy.interfaces.GraphUpdateHook.execute", "modulename": "causy.interfaces", "qualname": "GraphUpdateHook.execute", "kind": "function", "doc": "

Execute the hook.

\n\n
Parameters
\n\n
    \n
  • graph: current state of the graph.
    • \n
  • updates: the planned/taken actions
    • \n
\n\n
Returns
\n\n
\n

A list of updates that should be applied to the graph if it is a pre hook. If it is a post hook, it should return None.

\n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tupdates: List[causy.interfaces.TestResultInterface]) -> Optional[List[causy.interfaces.TestResultInterface]]:", "funcdef": "def"}, "causy.interfaces.GraphUpdateHook.model_config": {"fullname": "causy.interfaces.GraphUpdateHook.model_config", "modulename": "causy.interfaces", "qualname": "GraphUpdateHook.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.interfaces.GraphUpdateHook.model_fields": {"fullname": "causy.interfaces.GraphUpdateHook.model_fields", "modulename": "causy.interfaces", "qualname": "GraphUpdateHook.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.interfaces.GraphUpdateHook.model_computed_fields": {"fullname": "causy.interfaces.GraphUpdateHook.model_computed_fields", "modulename": "causy.interfaces", "qualname": "GraphUpdateHook.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.math_utils": {"fullname": "causy.math_utils", "modulename": "causy.math_utils", "kind": "module", "doc": "

\n"}, "causy.math_utils.logger": {"fullname": "causy.math_utils.logger", "modulename": "causy.math_utils", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.math_utils (WARNING)>"}, "causy.math_utils.sum_lists": {"fullname": "causy.math_utils.sum_lists", "modulename": "causy.math_utils", "qualname": "sum_lists", "kind": "function", "doc": "
Parameters
\n\n
    \n
  • lists: lists of numbers
    • \n
\n\n
Returns
\n\n
\n

list (sum of lists)

\n
\n", "signature": "(*lists):", "funcdef": "def"}, "causy.math_utils.get_t_and_critical_t": {"fullname": "causy.math_utils.get_t_and_critical_t", "modulename": "causy.math_utils", "qualname": "get_t_and_critical_t", "kind": "function", "doc": "

\n", "signature": "(sample_size, nb_of_control_vars, par_corr, threshold):", "funcdef": "def"}, "causy.models": {"fullname": "causy.models", "modulename": "causy.models", "kind": "module", "doc": "

\n"}, "causy.models.ComparisonSettings": {"fullname": "causy.models.ComparisonSettings", "modulename": "causy.models", "qualname": "ComparisonSettings", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "causy.interfaces.ComparisonSettingsInterface"}, "causy.models.ComparisonSettings.min": {"fullname": "causy.models.ComparisonSettings.min", "modulename": "causy.models", "qualname": "ComparisonSettings.min", "kind": "variable", "doc": "

\n", "annotation": ": Union[int, causy.variables.VariableReference]"}, "causy.models.ComparisonSettings.max": {"fullname": "causy.models.ComparisonSettings.max", "modulename": "causy.models", "qualname": "ComparisonSettings.max", "kind": "variable", "doc": "

\n", "annotation": ": Union[int, causy.variables.VariableReference]"}, "causy.models.ComparisonSettings.name": {"fullname": "causy.models.ComparisonSettings.name", "modulename": "causy.models", "qualname": "ComparisonSettings.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.models.ComparisonSettings.model_config": {"fullname": "causy.models.ComparisonSettings.model_config", "modulename": "causy.models", "qualname": "ComparisonSettings.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.models.ComparisonSettings.model_fields": {"fullname": "causy.models.ComparisonSettings.model_fields", "modulename": "causy.models", "qualname": "ComparisonSettings.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'min': FieldInfo(annotation=Union[int, VariableReference], required=False, default=2), 'max': FieldInfo(annotation=Union[int, VariableReference], required=False, default=0)}"}, "causy.models.ComparisonSettings.model_computed_fields": {"fullname": "causy.models.ComparisonSettings.model_computed_fields", "modulename": "causy.models", "qualname": "ComparisonSettings.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': ComputedFieldInfo(wrapped_property=<property object>, return_type=<class 'str'>, alias=None, alias_priority=None, title=None, field_title_generator=None, description=None, deprecated=None, examples=None, json_schema_extra=None, repr=True)}"}, "causy.models.TestResultAction": {"fullname": "causy.models.TestResultAction", "modulename": "causy.models", "qualname": "TestResultAction", "kind": "class", "doc": "

Actions that can be taken on the graph. These actions are used to keep track of the history of the graph.

\n", "bases": "builtins.str, enum.Enum"}, "causy.models.TestResultAction.UPDATE_EDGE": {"fullname": "causy.models.TestResultAction.UPDATE_EDGE", "modulename": "causy.models", "qualname": "TestResultAction.UPDATE_EDGE", "kind": "variable", "doc": "

\n", "default_value": "<TestResultAction.UPDATE_EDGE: 'UPDATE_EDGE'>"}, "causy.models.TestResultAction.UPDATE_EDGE_DIRECTED": {"fullname": "causy.models.TestResultAction.UPDATE_EDGE_DIRECTED", "modulename": "causy.models", "qualname": "TestResultAction.UPDATE_EDGE_DIRECTED", "kind": "variable", "doc": "

\n", "default_value": "<TestResultAction.UPDATE_EDGE_DIRECTED: 'UPDATE_EDGE_DIRECTED'>"}, "causy.models.TestResultAction.UPDATE_EDGE_TYPE": {"fullname": "causy.models.TestResultAction.UPDATE_EDGE_TYPE", "modulename": "causy.models", "qualname": "TestResultAction.UPDATE_EDGE_TYPE", "kind": "variable", "doc": "

\n", "default_value": "<TestResultAction.UPDATE_EDGE_TYPE: 'UPDATE_EDGE_TYPE'>"}, "causy.models.TestResultAction.UPDATE_EDGE_TYPE_DIRECTED": {"fullname": "causy.models.TestResultAction.UPDATE_EDGE_TYPE_DIRECTED", "modulename": "causy.models", "qualname": "TestResultAction.UPDATE_EDGE_TYPE_DIRECTED", "kind": "variable", "doc": "

\n", "default_value": "<TestResultAction.UPDATE_EDGE_TYPE_DIRECTED: 'UPDATE_EDGE_TYPE_DIRECTED'>"}, "causy.models.TestResultAction.REMOVE_EDGE_UNDIRECTED": {"fullname": "causy.models.TestResultAction.REMOVE_EDGE_UNDIRECTED", "modulename": "causy.models", "qualname": "TestResultAction.REMOVE_EDGE_UNDIRECTED", "kind": "variable", "doc": "

\n", "default_value": "<TestResultAction.REMOVE_EDGE_UNDIRECTED: 'REMOVE_EDGE_UNDIRECTED'>"}, "causy.models.TestResultAction.REMOVE_EDGE_DIRECTED": {"fullname": "causy.models.TestResultAction.REMOVE_EDGE_DIRECTED", "modulename": "causy.models", "qualname": "TestResultAction.REMOVE_EDGE_DIRECTED", "kind": "variable", "doc": "

\n", "default_value": "<TestResultAction.REMOVE_EDGE_DIRECTED: 'REMOVE_EDGE_DIRECTED'>"}, "causy.models.TestResultAction.RESTORE_EDGE": {"fullname": "causy.models.TestResultAction.RESTORE_EDGE", "modulename": "causy.models", "qualname": "TestResultAction.RESTORE_EDGE", "kind": "variable", "doc": "

\n", "default_value": "<TestResultAction.RESTORE_EDGE: 'RESTORE_EDGE'>"}, "causy.models.TestResultAction.RESTORE_EDGE_DIRECTED": {"fullname": "causy.models.TestResultAction.RESTORE_EDGE_DIRECTED", "modulename": "causy.models", "qualname": "TestResultAction.RESTORE_EDGE_DIRECTED", "kind": "variable", "doc": "

\n", "default_value": "<TestResultAction.RESTORE_EDGE_DIRECTED: 'RESTORE_EDGE_DIRECTED'>"}, "causy.models.TestResultAction.DO_NOTHING": {"fullname": "causy.models.TestResultAction.DO_NOTHING", "modulename": "causy.models", "qualname": "TestResultAction.DO_NOTHING", "kind": "variable", "doc": "

\n", "default_value": "<TestResultAction.DO_NOTHING: 'DO_NOTHING'>"}, "causy.models.TestResult": {"fullname": "causy.models.TestResult", "modulename": "causy.models", "qualname": "TestResult", "kind": "class", "doc": "

Test result interface for the graph\nA test result is defined by two nodes and an action. It can also have metadata.

\n", "bases": "causy.interfaces.TestResultInterface"}, "causy.models.TestResult.u": {"fullname": "causy.models.TestResult.u", "modulename": "causy.models", "qualname": "TestResult.u", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.NodeInterface"}, "causy.models.TestResult.v": {"fullname": "causy.models.TestResult.v", "modulename": "causy.models", "qualname": "TestResult.v", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.NodeInterface"}, "causy.models.TestResult.action": {"fullname": "causy.models.TestResult.action", "modulename": "causy.models", "qualname": "TestResult.action", "kind": "variable", "doc": "

\n", "annotation": ": causy.models.TestResultAction"}, "causy.models.TestResult.data": {"fullname": "causy.models.TestResult.data", "modulename": "causy.models", "qualname": "TestResult.data", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict]"}, "causy.models.TestResult.model_config": {"fullname": "causy.models.TestResult.model_config", "modulename": "causy.models", "qualname": "TestResult.model_config", "kind": "variable", "doc": "

\n", "default_value": "{'arbitrary_types_allowed': True}"}, "causy.models.TestResult.model_fields": {"fullname": "causy.models.TestResult.model_fields", "modulename": "causy.models", "qualname": "TestResult.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'u': FieldInfo(annotation=NodeInterface, required=True), 'v': FieldInfo(annotation=NodeInterface, required=True), 'action': FieldInfo(annotation=TestResultAction, required=True), 'data': FieldInfo(annotation=Union[Dict, NoneType], required=False, default=None)}"}, "causy.models.TestResult.model_computed_fields": {"fullname": "causy.models.TestResult.model_computed_fields", "modulename": "causy.models", "qualname": "TestResult.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.models.AlgorithmReferenceType": {"fullname": "causy.models.AlgorithmReferenceType", "modulename": "causy.models", "qualname": "AlgorithmReferenceType", "kind": "class", "doc": "

str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str

\n\n

Create a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to sys.getdefaultencoding().\nerrors defaults to 'strict'.

\n", "bases": "builtins.str, enum.Enum"}, "causy.models.AlgorithmReferenceType.FILE": {"fullname": "causy.models.AlgorithmReferenceType.FILE", "modulename": "causy.models", "qualname": "AlgorithmReferenceType.FILE", "kind": "variable", "doc": "

\n", "default_value": "<AlgorithmReferenceType.FILE: 'file'>"}, "causy.models.AlgorithmReferenceType.NAME": {"fullname": "causy.models.AlgorithmReferenceType.NAME", "modulename": "causy.models", "qualname": "AlgorithmReferenceType.NAME", "kind": "variable", "doc": "

\n", "default_value": "<AlgorithmReferenceType.NAME: 'name'>"}, "causy.models.AlgorithmReferenceType.PYTHON_MODULE": {"fullname": "causy.models.AlgorithmReferenceType.PYTHON_MODULE", "modulename": "causy.models", "qualname": "AlgorithmReferenceType.PYTHON_MODULE", "kind": "variable", "doc": "

\n", "default_value": "<AlgorithmReferenceType.PYTHON_MODULE: 'python_module'>"}, "causy.models.AlgorithmReference": {"fullname": "causy.models.AlgorithmReference", "modulename": "causy.models", "qualname": "AlgorithmReference", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel"}, "causy.models.AlgorithmReference.reference": {"fullname": "causy.models.AlgorithmReference.reference", "modulename": "causy.models", "qualname": "AlgorithmReference.reference", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.models.AlgorithmReference.type": {"fullname": "causy.models.AlgorithmReference.type", "modulename": "causy.models", "qualname": "AlgorithmReference.type", "kind": "variable", "doc": "

\n", "annotation": ": causy.models.AlgorithmReferenceType"}, "causy.models.AlgorithmReference.model_config": {"fullname": "causy.models.AlgorithmReference.model_config", "modulename": "causy.models", "qualname": "AlgorithmReference.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.models.AlgorithmReference.model_fields": {"fullname": "causy.models.AlgorithmReference.model_fields", "modulename": "causy.models", "qualname": "AlgorithmReference.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'reference': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=AlgorithmReferenceType, required=True)}"}, "causy.models.AlgorithmReference.model_computed_fields": {"fullname": "causy.models.AlgorithmReference.model_computed_fields", "modulename": "causy.models", "qualname": "AlgorithmReference.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.models.Algorithm": {"fullname": "causy.models.Algorithm", "modulename": "causy.models", "qualname": "Algorithm", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel"}, "causy.models.Algorithm.name": {"fullname": "causy.models.Algorithm.name", "modulename": "causy.models", "qualname": "Algorithm.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.models.Algorithm.pipeline_steps": {"fullname": "causy.models.Algorithm.pipeline_steps", "modulename": "causy.models", "qualname": "Algorithm.pipeline_steps", "kind": "variable", "doc": "

\n", "annotation": ": List[Union[~PipelineStepInterfaceType, causy.interfaces.LogicStepInterface]]"}, "causy.models.Algorithm.edge_types": {"fullname": "causy.models.Algorithm.edge_types", "modulename": "causy.models", "qualname": "Algorithm.edge_types", "kind": "variable", "doc": "

\n", "annotation": ": List[~EdgeTypeInterfaceType]"}, "causy.models.Algorithm.extensions": {"fullname": "causy.models.Algorithm.extensions", "modulename": "causy.models", "qualname": "Algorithm.extensions", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[~ExtensionType]]"}, "causy.models.Algorithm.variables": {"fullname": "causy.models.Algorithm.variables", "modulename": "causy.models", "qualname": "Algorithm.variables", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[~VariableInterfaceType]]"}, "causy.models.Algorithm.pre_graph_update_hooks": {"fullname": "causy.models.Algorithm.pre_graph_update_hooks", "modulename": "causy.models", "qualname": "Algorithm.pre_graph_update_hooks", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[causy.interfaces.GraphUpdateHook]]"}, "causy.models.Algorithm.post_graph_update_hooks": {"fullname": "causy.models.Algorithm.post_graph_update_hooks", "modulename": "causy.models", "qualname": "Algorithm.post_graph_update_hooks", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[causy.interfaces.GraphUpdateHook]]"}, "causy.models.Algorithm.hash": {"fullname": "causy.models.Algorithm.hash", "modulename": "causy.models", "qualname": "Algorithm.hash", "kind": "function", "doc": "

\n", "signature": "(self) -> str:", "funcdef": "def"}, "causy.models.Algorithm.model_config": {"fullname": "causy.models.Algorithm.model_config", "modulename": "causy.models", "qualname": "Algorithm.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.models.Algorithm.model_fields": {"fullname": "causy.models.Algorithm.model_fields", "modulename": "causy.models", "qualname": "Algorithm.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': FieldInfo(annotation=str, required=True), 'pipeline_steps': FieldInfo(annotation=List[Union[TypeVar, LogicStepInterface]], required=True), 'edge_types': FieldInfo(annotation=List[TypeVar], required=True), 'extensions': FieldInfo(annotation=Union[List[TypeVar], NoneType], required=False, default=None), 'variables': FieldInfo(annotation=Union[List[TypeVar], NoneType], required=False, default=None), 'pre_graph_update_hooks': FieldInfo(annotation=Union[List[GraphUpdateHook], NoneType], required=False, default=None), 'post_graph_update_hooks': FieldInfo(annotation=Union[List[GraphUpdateHook], NoneType], required=False, default=None)}"}, "causy.models.Algorithm.model_computed_fields": {"fullname": "causy.models.Algorithm.model_computed_fields", "modulename": "causy.models", "qualname": "Algorithm.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.models.ActionHistoryStep": {"fullname": "causy.models.ActionHistoryStep", "modulename": "causy.models", "qualname": "ActionHistoryStep", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel"}, "causy.models.ActionHistoryStep.name": {"fullname": "causy.models.ActionHistoryStep.name", "modulename": "causy.models", "qualname": "ActionHistoryStep.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.models.ActionHistoryStep.duration": {"fullname": "causy.models.ActionHistoryStep.duration", "modulename": "causy.models", "qualname": "ActionHistoryStep.duration", "kind": "variable", "doc": "

\n", "annotation": ": Optional[float]"}, "causy.models.ActionHistoryStep.actions": {"fullname": "causy.models.ActionHistoryStep.actions", "modulename": "causy.models", "qualname": "ActionHistoryStep.actions", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[causy.models.TestResult]]"}, "causy.models.ActionHistoryStep.all_proposed_actions": {"fullname": "causy.models.ActionHistoryStep.all_proposed_actions", "modulename": "causy.models", "qualname": "ActionHistoryStep.all_proposed_actions", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[causy.models.TestResult]]"}, "causy.models.ActionHistoryStep.steps": {"fullname": "causy.models.ActionHistoryStep.steps", "modulename": "causy.models", "qualname": "ActionHistoryStep.steps", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[causy.models.ActionHistoryStep]]"}, "causy.models.ActionHistoryStep.model_config": {"fullname": "causy.models.ActionHistoryStep.model_config", "modulename": "causy.models", "qualname": "ActionHistoryStep.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.models.ActionHistoryStep.model_fields": {"fullname": "causy.models.ActionHistoryStep.model_fields", "modulename": "causy.models", "qualname": "ActionHistoryStep.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': FieldInfo(annotation=str, required=True), 'duration': FieldInfo(annotation=Union[float, NoneType], required=False, default=None), 'actions': FieldInfo(annotation=Union[List[TestResult], NoneType], required=False, default=[]), 'all_proposed_actions': FieldInfo(annotation=Union[List[TestResult], NoneType], required=False, default=[]), 'steps': FieldInfo(annotation=Union[List[ActionHistoryStep], NoneType], required=False, default=[])}"}, "causy.models.ActionHistoryStep.model_computed_fields": {"fullname": "causy.models.ActionHistoryStep.model_computed_fields", "modulename": "causy.models", "qualname": "ActionHistoryStep.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.models.Result": {"fullname": "causy.models.Result", "modulename": "causy.models", "qualname": "Result", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel"}, "causy.models.Result.algorithm": {"fullname": "causy.models.Result.algorithm", "modulename": "causy.models", "qualname": "Result.algorithm", "kind": "variable", "doc": "

\n", "annotation": ": causy.models.AlgorithmReference"}, "causy.models.Result.created_at": {"fullname": "causy.models.Result.created_at", "modulename": "causy.models", "qualname": "Result.created_at", "kind": "variable", "doc": "

\n", "annotation": ": datetime.datetime"}, "causy.models.Result.nodes": {"fullname": "causy.models.Result.nodes", "modulename": "causy.models", "qualname": "Result.nodes", "kind": "variable", "doc": "

\n", "annotation": ": Dict[str, causy.interfaces.NodeInterface]"}, "causy.models.Result.edges": {"fullname": "causy.models.Result.edges", "modulename": "causy.models", "qualname": "Result.edges", "kind": "variable", "doc": "

\n", "annotation": ": List[causy.interfaces.EdgeInterface]"}, "causy.models.Result.action_history": {"fullname": "causy.models.Result.action_history", "modulename": "causy.models", "qualname": "Result.action_history", "kind": "variable", "doc": "

\n", "annotation": ": List[causy.models.ActionHistoryStep]"}, "causy.models.Result.variables": {"fullname": "causy.models.Result.variables", "modulename": "causy.models", "qualname": "Result.variables", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict[str, Any]]"}, "causy.models.Result.data_loader_hash": {"fullname": "causy.models.Result.data_loader_hash", "modulename": "causy.models", "qualname": "Result.data_loader_hash", "kind": "variable", "doc": "

\n", "annotation": ": Optional[str]"}, "causy.models.Result.algorithm_hash": {"fullname": "causy.models.Result.algorithm_hash", "modulename": "causy.models", "qualname": "Result.algorithm_hash", "kind": "variable", "doc": "

\n", "annotation": ": Optional[str]"}, "causy.models.Result.variables_hash": {"fullname": "causy.models.Result.variables_hash", "modulename": "causy.models", "qualname": "Result.variables_hash", "kind": "variable", "doc": "

\n", "annotation": ": Optional[str]"}, "causy.models.Result.model_config": {"fullname": "causy.models.Result.model_config", "modulename": "causy.models", "qualname": "Result.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.models.Result.model_fields": {"fullname": "causy.models.Result.model_fields", "modulename": "causy.models", "qualname": "Result.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'algorithm': FieldInfo(annotation=AlgorithmReference, required=True), 'created_at': FieldInfo(annotation=datetime, required=False, default_factory=builtin_function_or_method), 'nodes': FieldInfo(annotation=Dict[str, NodeInterface], required=True), 'edges': FieldInfo(annotation=List[EdgeInterface], required=True), 'action_history': FieldInfo(annotation=List[ActionHistoryStep], required=True), 'variables': FieldInfo(annotation=Union[Dict[str, Any], NoneType], required=False, default=None), 'data_loader_hash': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'algorithm_hash': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'variables_hash': FieldInfo(annotation=Union[str, NoneType], required=False, default=None)}"}, "causy.models.Result.model_computed_fields": {"fullname": "causy.models.Result.model_computed_fields", "modulename": "causy.models", "qualname": "Result.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.sample_generator": {"fullname": "causy.sample_generator", "modulename": "causy.sample_generator", "kind": "module", "doc": "

\n"}, "causy.sample_generator.logger": {"fullname": "causy.sample_generator.logger", "modulename": "causy.sample_generator", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.sample_generator (WARNING)>"}, "causy.sample_generator.random_normal": {"fullname": "causy.sample_generator.random_normal", "modulename": "causy.sample_generator", "qualname": "random_normal", "kind": "function", "doc": "

Returns a random number from a normal distribution

\n\n
Returns
\n\n
\n

the random number as a float

\n
\n", "signature": "() -> float:", "funcdef": "def"}, "causy.sample_generator.NodeReference": {"fullname": "causy.sample_generator.NodeReference", "modulename": "causy.sample_generator", "qualname": "NodeReference", "kind": "class", "doc": "

A reference to a node in the sample generator

\n"}, "causy.sample_generator.NodeReference.__init__": {"fullname": "causy.sample_generator.NodeReference.__init__", "modulename": "causy.sample_generator", "qualname": "NodeReference.__init__", "kind": "function", "doc": "

\n", "signature": "(node: str)"}, "causy.sample_generator.NodeReference.node": {"fullname": "causy.sample_generator.NodeReference.node", "modulename": "causy.sample_generator", "qualname": "NodeReference.node", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.sample_generator.TimeAwareNodeReference": {"fullname": "causy.sample_generator.TimeAwareNodeReference", "modulename": "causy.sample_generator", "qualname": "TimeAwareNodeReference", "kind": "class", "doc": "

A reference to a node in the sample generator

\n", "bases": "NodeReference"}, "causy.sample_generator.TimeAwareNodeReference.__init__": {"fullname": "causy.sample_generator.TimeAwareNodeReference.__init__", "modulename": "causy.sample_generator", "qualname": "TimeAwareNodeReference.__init__", "kind": "function", "doc": "

\n", "signature": "(node: str, point_in_time: int = 0)"}, "causy.sample_generator.TimeAwareNodeReference.point_in_time": {"fullname": "causy.sample_generator.TimeAwareNodeReference.point_in_time", "modulename": "causy.sample_generator", "qualname": "TimeAwareNodeReference.point_in_time", "kind": "variable", "doc": "

\n", "annotation": ": int", "default_value": "0"}, "causy.sample_generator.SampleEdge": {"fullname": "causy.sample_generator.SampleEdge", "modulename": "causy.sample_generator", "qualname": "SampleEdge", "kind": "class", "doc": "

An edge in the sample generator that references a node and a lag

\n"}, "causy.sample_generator.SampleEdge.__init__": {"fullname": "causy.sample_generator.SampleEdge.__init__", "modulename": "causy.sample_generator", "qualname": "SampleEdge.__init__", "kind": "function", "doc": "

\n", "signature": "(\tfrom_node: causy.sample_generator.NodeReference,\tto_node: causy.sample_generator.NodeReference,\tvalue: float = 0)"}, "causy.sample_generator.SampleEdge.from_node": {"fullname": "causy.sample_generator.SampleEdge.from_node", "modulename": "causy.sample_generator", "qualname": "SampleEdge.from_node", "kind": "variable", "doc": "

\n", "annotation": ": causy.sample_generator.NodeReference"}, "causy.sample_generator.SampleEdge.to_node": {"fullname": "causy.sample_generator.SampleEdge.to_node", "modulename": "causy.sample_generator", "qualname": "SampleEdge.to_node", "kind": "variable", "doc": "

\n", "annotation": ": causy.sample_generator.NodeReference"}, "causy.sample_generator.SampleEdge.value": {"fullname": "causy.sample_generator.SampleEdge.value", "modulename": "causy.sample_generator", "qualname": "SampleEdge.value", "kind": "variable", "doc": "

\n", "annotation": ": float", "default_value": "0"}, "causy.sample_generator.TimeTravelingError": {"fullname": "causy.sample_generator.TimeTravelingError", "modulename": "causy.sample_generator", "qualname": "TimeTravelingError", "kind": "class", "doc": "

An error that is raised when a TimeProxy tries to access a value from the future

\n", "bases": "builtins.Exception"}, "causy.sample_generator.AbstractSampleGenerator": {"fullname": "causy.sample_generator.AbstractSampleGenerator", "modulename": "causy.sample_generator", "qualname": "AbstractSampleGenerator", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC"}, "causy.sample_generator.AbstractSampleGenerator.random_fn": {"fullname": "causy.sample_generator.AbstractSampleGenerator.random_fn", "modulename": "causy.sample_generator", "qualname": "AbstractSampleGenerator.random_fn", "kind": "variable", "doc": "

\n"}, "causy.sample_generator.AbstractSampleGenerator.generate": {"fullname": "causy.sample_generator.AbstractSampleGenerator.generate", "modulename": "causy.sample_generator", "qualname": "AbstractSampleGenerator.generate", "kind": "function", "doc": "

Generate data for a sample graph with a time dimension

\n\n
Parameters
\n\n
    \n
  • size: the number of time steps to generate
    • \n
\n\n
Returns
\n\n
\n

the generated data and the sample graph

\n
\n", "signature": "(self, size: int) -> types.SimpleNamespace:", "funcdef": "def"}, "causy.sample_generator.IIDSampleGenerator": {"fullname": "causy.sample_generator.IIDSampleGenerator", "modulename": "causy.sample_generator", "qualname": "IIDSampleGenerator", "kind": "class", "doc": "

A sample generator that generates data from i.i.d multivariate Gaussians.

\n\n

A variable can not depend on itself.

\n\n

Example:

\n\n
\n
>>> sg = IIDSampleGenerator(\n>>>     edges=[\n>>>      SampleEdge(NodeReference("X"), NodeReference("Y"), 5),\n>>>      SampleEdge(NodeReference("Y"), NodeReference("Z"), 7),\n>>>      ],\n>>> )\n
\n
\n", "bases": "AbstractSampleGenerator"}, "causy.sample_generator.IIDSampleGenerator.__init__": {"fullname": "causy.sample_generator.IIDSampleGenerator.__init__", "modulename": "causy.sample_generator", "qualname": "IIDSampleGenerator.__init__", "kind": "function", "doc": "

\n", "signature": "(\tedges: List[causy.sample_generator.SampleEdge],\trandom: Callable = <function random_normal>)"}, "causy.sample_generator.IIDSampleGenerator.topologic_sort": {"fullname": "causy.sample_generator.IIDSampleGenerator.topologic_sort", "modulename": "causy.sample_generator", "qualname": "IIDSampleGenerator.topologic_sort", "kind": "function", "doc": "

Sorts the nodes topologically

\n\n
Parameters
\n\n
    \n
  • nodes: list of nodes
    • \n
  • edges: list of edges
    • \n
\n\n
Returns
\n\n
\n

a list of sorted nodes

\n
\n", "signature": "(self, nodes: List[str]):", "funcdef": "def"}, "causy.sample_generator.IIDSampleGenerator.generate": {"fullname": "causy.sample_generator.IIDSampleGenerator.generate", "modulename": "causy.sample_generator", "qualname": "IIDSampleGenerator.generate", "kind": "function", "doc": "

Generate data for a sample graph with a time dimension

\n\n
Parameters
\n\n
    \n
  • size: the number of time steps to generate
    • \n
\n\n
Returns
\n\n
\n

the generated data and the sample graph

\n
\n", "signature": "(self, size):", "funcdef": "def"}, "causy.sample_generator.TimeseriesSampleGenerator": {"fullname": "causy.sample_generator.TimeseriesSampleGenerator", "modulename": "causy.sample_generator", "qualname": "TimeseriesSampleGenerator", "kind": "class", "doc": "

A sample generator that generates data for a sample graph with a time dimension.

\n\n

Edges are defined as SampleLaggedEdges, which define a directed edge from a source node to a target node with a\nag. The lag is the number of time steps between the source and the target.

\n\n

A variable can depend on itself, but only on its past values (with a lag). This corresponds to autoregressive models.

\n\n

Example:

\n\n
\n
>>> sg = TimeseriesSampleGenerator(\n>>>     edges=[\n>>>      SampleEdge(TimeAwareNodeReference("X", -1), TimeAwareNodeReference("X"), 0.9),\n>>>      SampleEdge(TimeAwareNodeReference("Y", -1), TimeAwareNodeReference("Y"), 0.9),\n>>>      SampleEdge(TimeAwareNodeReference("Z", -1), TimeAwareNodeReference("Z"), 0.9),\n>>>      SampleEdge(TimeAwareNodeReference("Z", -1), TimeAwareNodeReference("Y"), 5),\n>>>      SampleEdge(TimeAwareNodeReference("Y", -1), TimeAwareNodeReference("X"), 7),\n>>>      ],\n>>> )\n
\n
\n", "bases": "AbstractSampleGenerator"}, "causy.sample_generator.TimeseriesSampleGenerator.__init__": {"fullname": "causy.sample_generator.TimeseriesSampleGenerator.__init__", "modulename": "causy.sample_generator", "qualname": "TimeseriesSampleGenerator.__init__", "kind": "function", "doc": "

\n", "signature": "(\tedges: List[causy.sample_generator.SampleEdge],\trandom: Callable = <function random_normal>)"}, "causy.sample_generator.TimeseriesSampleGenerator.generate": {"fullname": "causy.sample_generator.TimeseriesSampleGenerator.generate", "modulename": "causy.sample_generator", "qualname": "TimeseriesSampleGenerator.generate", "kind": "function", "doc": "

Generate data for a sample graph with a time dimension

\n\n
Parameters
\n\n
    \n
  • size: the number of time steps to generate
    • \n
\n\n
Returns
\n\n
\n

the generated data and the sample graph

\n
\n", "signature": "(self, size):", "funcdef": "def"}, "causy.sample_generator.TimeseriesSampleGenerator.custom_block_diagonal": {"fullname": "causy.sample_generator.TimeseriesSampleGenerator.custom_block_diagonal", "modulename": "causy.sample_generator", "qualname": "TimeseriesSampleGenerator.custom_block_diagonal", "kind": "function", "doc": "

\n", "signature": "(self, matrices):", "funcdef": "def"}, "causy.sample_generator.TimeseriesSampleGenerator.vectorize_identity_block": {"fullname": "causy.sample_generator.TimeseriesSampleGenerator.vectorize_identity_block", "modulename": "causy.sample_generator", "qualname": "TimeseriesSampleGenerator.vectorize_identity_block", "kind": "function", "doc": "

\n", "signature": "(self, n):", "funcdef": "def"}, "causy.serialization": {"fullname": "causy.serialization", "modulename": "causy.serialization", "kind": "module", "doc": "

\n"}, "causy.serialization.serialize_algorithm": {"fullname": "causy.serialization.serialize_algorithm", "modulename": "causy.serialization", "qualname": "serialize_algorithm", "kind": "function", "doc": "

Serialize the model into a dictionary.

\n", "signature": "(model, algorithm_name: str = None):", "funcdef": "def"}, "causy.serialization.load_algorithm_from_specification": {"fullname": "causy.serialization.load_algorithm_from_specification", "modulename": "causy.serialization", "qualname": "load_algorithm_from_specification", "kind": "function", "doc": "

Load the model from a dictionary.

\n", "signature": "(algorithm_dict: Dict[str, Any]):", "funcdef": "def"}, "causy.serialization.load_algorithm_by_reference": {"fullname": "causy.serialization.load_algorithm_by_reference", "modulename": "causy.serialization", "qualname": "load_algorithm_by_reference", "kind": "function", "doc": "

\n", "signature": "(reference_type: str, algorithm: str):", "funcdef": "def"}, "causy.serialization.CausyJSONEncoder": {"fullname": "causy.serialization.CausyJSONEncoder", "modulename": "causy.serialization", "qualname": "CausyJSONEncoder", "kind": "class", "doc": "

Extensible JSON https://json.org encoder for Python data structures.

\n\n

Supports the following objects and types by default:

\n\n

+-------------------+---------------+\n| Python | JSON |\n+===================+===============+\n| dict | object |\n+-------------------+---------------+\n| list, tuple | array |\n+-------------------+---------------+\n| str | string |\n+-------------------+---------------+\n| int, float | number |\n+-------------------+---------------+\n| True | true |\n+-------------------+---------------+\n| False | false |\n+-------------------+---------------+\n| None | null |\n+-------------------+---------------+

\n\n

To extend this to recognize other objects, subclass and implement a\n.default() method with another method that returns a serializable\nobject for o if possible, otherwise it should call the superclass\nimplementation (to raise TypeError).

\n", "bases": "json.encoder.JSONEncoder"}, "causy.serialization.CausyJSONEncoder.default": {"fullname": "causy.serialization.CausyJSONEncoder.default", "modulename": "causy.serialization", "qualname": "CausyJSONEncoder.default", "kind": "function", "doc": "

Implement this method in a subclass such that it returns\na serializable object for o, or calls the base implementation\n(to raise a TypeError).

\n\n

For example, to support arbitrary iterators, you could\nimplement default like this::

\n\n
def default(self, o):\n    try:\n        iterable = iter(o)\n    except TypeError:\n        pass\n    else:\n        return list(iterable)\n    # Let the base class default method raise the TypeError\n    return super().default(o)\n
\n", "signature": "(self, obj):", "funcdef": "def"}, "causy.serialization.load_json": {"fullname": "causy.serialization.load_json", "modulename": "causy.serialization", "qualname": "load_json", "kind": "function", "doc": "

\n", "signature": "(pipeline_file: str):", "funcdef": "def"}, "causy.serialization.deserialize_result": {"fullname": "causy.serialization.deserialize_result", "modulename": "causy.serialization", "qualname": "deserialize_result", "kind": "function", "doc": "

Deserialize the result.

\n", "signature": "(result: Dict[str, Any], klass=<class 'causy.models.Result'>):", "funcdef": "def"}, "causy.ui": {"fullname": "causy.ui", "modulename": "causy.ui", "kind": "module", "doc": "

\n"}, "causy.ui.cli": {"fullname": "causy.ui.cli", "modulename": "causy.ui.cli", "kind": "module", "doc": "

\n"}, "causy.ui.cli.ui": {"fullname": "causy.ui.cli.ui", "modulename": "causy.ui.cli", "qualname": "ui", "kind": "function", "doc": "

Start the causy UI.

\n", "signature": "(result_file: str = None):", "funcdef": "def"}, "causy.ui.models": {"fullname": "causy.ui.models", "modulename": "causy.ui.models", "kind": "module", "doc": "

\n"}, "causy.ui.models.NodePosition": {"fullname": "causy.ui.models.NodePosition", "modulename": "causy.ui.models", "qualname": "NodePosition", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel"}, "causy.ui.models.NodePosition.x": {"fullname": "causy.ui.models.NodePosition.x", "modulename": "causy.ui.models", "qualname": "NodePosition.x", "kind": "variable", "doc": "

\n", "annotation": ": Optional[float]"}, "causy.ui.models.NodePosition.y": {"fullname": "causy.ui.models.NodePosition.y", "modulename": "causy.ui.models", "qualname": "NodePosition.y", "kind": "variable", "doc": "

\n", "annotation": ": Optional[float]"}, "causy.ui.models.NodePosition.model_config": {"fullname": "causy.ui.models.NodePosition.model_config", "modulename": "causy.ui.models", "qualname": "NodePosition.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.ui.models.NodePosition.model_fields": {"fullname": "causy.ui.models.NodePosition.model_fields", "modulename": "causy.ui.models", "qualname": "NodePosition.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'x': FieldInfo(annotation=Union[float, NoneType], required=True), 'y': FieldInfo(annotation=Union[float, NoneType], required=True)}"}, "causy.ui.models.NodePosition.model_computed_fields": {"fullname": "causy.ui.models.NodePosition.model_computed_fields", "modulename": "causy.ui.models", "qualname": "NodePosition.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.ui.models.ExperimentVersion": {"fullname": "causy.ui.models.ExperimentVersion", "modulename": "causy.ui.models", "qualname": "ExperimentVersion", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel"}, "causy.ui.models.ExperimentVersion.version": {"fullname": "causy.ui.models.ExperimentVersion.version", "modulename": "causy.ui.models", "qualname": "ExperimentVersion.version", "kind": "variable", "doc": "

\n", "annotation": ": int"}, "causy.ui.models.ExperimentVersion.name": {"fullname": "causy.ui.models.ExperimentVersion.name", "modulename": "causy.ui.models", "qualname": "ExperimentVersion.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.ui.models.ExperimentVersion.model_config": {"fullname": "causy.ui.models.ExperimentVersion.model_config", "modulename": "causy.ui.models", "qualname": "ExperimentVersion.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.ui.models.ExperimentVersion.model_fields": {"fullname": "causy.ui.models.ExperimentVersion.model_fields", "modulename": "causy.ui.models", "qualname": "ExperimentVersion.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'version': FieldInfo(annotation=int, required=True), 'name': FieldInfo(annotation=str, required=True)}"}, "causy.ui.models.ExperimentVersion.model_computed_fields": {"fullname": "causy.ui.models.ExperimentVersion.model_computed_fields", "modulename": "causy.ui.models", "qualname": "ExperimentVersion.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.ui.models.ExtendedExperiment": {"fullname": "causy.ui.models.ExtendedExperiment", "modulename": "causy.ui.models", "qualname": "ExtendedExperiment", "kind": "class", "doc": "

represents a single experiment

\n\n
Parameters
\n\n
    \n
  • name: name of the experiment
    • \n
  • pipeline: the name of the pipeline used
    • \n
\n", "bases": "causy.workspaces.models.Experiment"}, "causy.ui.models.ExtendedExperiment.versions": {"fullname": "causy.ui.models.ExtendedExperiment.versions", "modulename": "causy.ui.models", "qualname": "ExtendedExperiment.versions", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[causy.ui.models.ExperimentVersion]]"}, "causy.ui.models.ExtendedExperiment.name": {"fullname": "causy.ui.models.ExtendedExperiment.name", "modulename": "causy.ui.models", "qualname": "ExtendedExperiment.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.ui.models.ExtendedExperiment.model_config": {"fullname": "causy.ui.models.ExtendedExperiment.model_config", "modulename": "causy.ui.models", "qualname": "ExtendedExperiment.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.ui.models.ExtendedExperiment.model_fields": {"fullname": "causy.ui.models.ExtendedExperiment.model_fields", "modulename": "causy.ui.models", "qualname": "ExtendedExperiment.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'pipeline': FieldInfo(annotation=str, required=True), 'dataloader': FieldInfo(annotation=str, required=True), 'variables': FieldInfo(annotation=Union[Dict[str, Union[str, int, float, bool]], NoneType], required=False, default={}), 'versions': FieldInfo(annotation=Union[List[ExperimentVersion], NoneType], required=False, default=None), 'name': FieldInfo(annotation=str, required=False, default=None)}"}, "causy.ui.models.ExtendedExperiment.model_computed_fields": {"fullname": "causy.ui.models.ExtendedExperiment.model_computed_fields", "modulename": "causy.ui.models", "qualname": "ExtendedExperiment.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.ui.models.PositionedNode": {"fullname": "causy.ui.models.PositionedNode", "modulename": "causy.ui.models", "qualname": "PositionedNode", "kind": "class", "doc": "

Node interface for the graph. A node is defined by a name and a value.

\n", "bases": "causy.interfaces.NodeInterface"}, "causy.ui.models.PositionedNode.position": {"fullname": "causy.ui.models.PositionedNode.position", "modulename": "causy.ui.models", "qualname": "PositionedNode.position", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.ui.models.NodePosition]"}, "causy.ui.models.PositionedNode.model_config": {"fullname": "causy.ui.models.PositionedNode.model_config", "modulename": "causy.ui.models", "qualname": "PositionedNode.model_config", "kind": "variable", "doc": "

\n", "default_value": "{'arbitrary_types_allowed': True}"}, "causy.ui.models.PositionedNode.model_fields": {"fullname": "causy.ui.models.PositionedNode.model_fields", "modulename": "causy.ui.models", "qualname": "PositionedNode.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': FieldInfo(annotation=str, required=True), 'id': FieldInfo(annotation=str, required=True), 'values': FieldInfo(annotation=Union[DoubleTensor, NoneType], required=False, default=None, exclude=True, metadata=[WithJsonSchema(json_schema={'type': 'array', 'items': {'type': 'number'}, 'description': 'Node values'}, mode=None)]), 'position': FieldInfo(annotation=Union[NodePosition, NoneType], required=False, default=None)}"}, "causy.ui.models.PositionedNode.model_computed_fields": {"fullname": "causy.ui.models.PositionedNode.model_computed_fields", "modulename": "causy.ui.models", "qualname": "PositionedNode.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.ui.models.ExtendedResult": {"fullname": "causy.ui.models.ExtendedResult", "modulename": "causy.ui.models", "qualname": "ExtendedResult", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "causy.models.Result"}, "causy.ui.models.ExtendedResult.nodes": {"fullname": "causy.ui.models.ExtendedResult.nodes", "modulename": "causy.ui.models", "qualname": "ExtendedResult.nodes", "kind": "variable", "doc": "

\n", "annotation": ": Dict[Union[Annotated[uuid.UUID, UuidVersion(uuid_version=4)], str], causy.ui.models.PositionedNode]"}, "causy.ui.models.ExtendedResult.version": {"fullname": "causy.ui.models.ExtendedResult.version", "modulename": "causy.ui.models", "qualname": "ExtendedResult.version", "kind": "variable", "doc": "

\n", "annotation": ": Optional[int]"}, "causy.ui.models.ExtendedResult.model_config": {"fullname": "causy.ui.models.ExtendedResult.model_config", "modulename": "causy.ui.models", "qualname": "ExtendedResult.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.ui.models.ExtendedResult.model_fields": {"fullname": "causy.ui.models.ExtendedResult.model_fields", "modulename": "causy.ui.models", "qualname": "ExtendedResult.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'algorithm': FieldInfo(annotation=AlgorithmReference, required=True), 'created_at': FieldInfo(annotation=datetime, required=False, default_factory=builtin_function_or_method), 'nodes': FieldInfo(annotation=Dict[Union[Annotated[UUID, UuidVersion], str], PositionedNode], required=True), 'edges': FieldInfo(annotation=List[EdgeInterface], required=True), 'action_history': FieldInfo(annotation=List[ActionHistoryStep], required=True), 'variables': FieldInfo(annotation=Union[Dict[str, Any], NoneType], required=False, default=None), 'data_loader_hash': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'algorithm_hash': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'variables_hash': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'version': FieldInfo(annotation=Union[int, NoneType], required=False, default=None)}"}, "causy.ui.models.ExtendedResult.model_computed_fields": {"fullname": "causy.ui.models.ExtendedResult.model_computed_fields", "modulename": "causy.ui.models", "qualname": "ExtendedResult.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.ui.server": {"fullname": "causy.ui.server", "modulename": "causy.ui.server", "kind": "module", "doc": "

\n"}, "causy.ui.server.logger": {"fullname": "causy.ui.server.logger", "modulename": "causy.ui.server", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.ui.server (WARNING)>"}, "causy.ui.server.API_ROUTES": {"fullname": "causy.ui.server.API_ROUTES", "modulename": "causy.ui.server", "qualname": "API_ROUTES", "kind": "variable", "doc": "

\n", "default_value": "<fastapi.routing.APIRouter object>"}, "causy.ui.server.MODEL": {"fullname": "causy.ui.server.MODEL", "modulename": "causy.ui.server", "qualname": "MODEL", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.ui.models.ExtendedResult]", "default_value": "None"}, "causy.ui.server.WORKSPACE": {"fullname": "causy.ui.server.WORKSPACE", "modulename": "causy.ui.server", "qualname": "WORKSPACE", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.workspaces.models.Workspace]", "default_value": "None"}, "causy.ui.server.get_status": {"fullname": "causy.ui.server.get_status", "modulename": "causy.ui.server", "qualname": "get_status", "kind": "function", "doc": "

Get the current status of the API.

\n", "signature": "():", "funcdef": "async def"}, "causy.ui.server.get_model": {"fullname": "causy.ui.server.get_model", "modulename": "causy.ui.server", "qualname": "get_model", "kind": "function", "doc": "

Get the current model.

\n", "signature": "():", "funcdef": "async def"}, "causy.ui.server.get_workspace": {"fullname": "causy.ui.server.get_workspace", "modulename": "causy.ui.server", "qualname": "get_workspace", "kind": "function", "doc": "

\n", "signature": "():", "funcdef": "async def"}, "causy.ui.server.get_latest_experiment": {"fullname": "causy.ui.server.get_latest_experiment", "modulename": "causy.ui.server", "qualname": "get_latest_experiment", "kind": "function", "doc": "

Get the current experiment.

\n", "signature": "(experiment_name: str):", "funcdef": "async def"}, "causy.ui.server.get_experiment": {"fullname": "causy.ui.server.get_experiment", "modulename": "causy.ui.server", "qualname": "get_experiment", "kind": "function", "doc": "

Get the current experiment.

\n", "signature": "(experiment_name: str, version_number: int):", "funcdef": "async def"}, "causy.ui.server.get_experiments": {"fullname": "causy.ui.server.get_experiments", "modulename": "causy.ui.server", "qualname": "get_experiments", "kind": "function", "doc": "

Get the current experiment.

\n", "signature": "():", "funcdef": "async def"}, "causy.ui.server.get_algorithm": {"fullname": "causy.ui.server.get_algorithm", "modulename": "causy.ui.server", "qualname": "get_algorithm", "kind": "function", "doc": "

Get the current algorithm.

\n", "signature": "(reference_type: str, reference: str):", "funcdef": "async def"}, "causy.ui.server.is_port_in_use": {"fullname": "causy.ui.server.is_port_in_use", "modulename": "causy.ui.server", "qualname": "is_port_in_use", "kind": "function", "doc": "

\n", "signature": "(host: str, port: int) -> bool:", "funcdef": "def"}, "causy.ui.server.server": {"fullname": "causy.ui.server.server", "modulename": "causy.ui.server", "qualname": "server", "kind": "function", "doc": "

Create the FastAPI server.

\n", "signature": "(\tresult: Dict[str, Any] = None,\tworkspace: causy.workspaces.models.Workspace = None):", "funcdef": "def"}, "causy.variables": {"fullname": "causy.variables", "modulename": "causy.variables", "kind": "module", "doc": "

\n"}, "causy.variables.VariableType": {"fullname": "causy.variables.VariableType", "modulename": "causy.variables", "qualname": "VariableType", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[str, int, float, bool]"}, "causy.variables.VariableTypes": {"fullname": "causy.variables.VariableTypes", "modulename": "causy.variables", "qualname": "VariableTypes", "kind": "class", "doc": "

\n", "bases": "enum.Enum"}, "causy.variables.VariableTypes.String": {"fullname": "causy.variables.VariableTypes.String", "modulename": "causy.variables", "qualname": "VariableTypes.String", "kind": "variable", "doc": "

\n", "default_value": "<VariableTypes.String: 'string'>"}, "causy.variables.VariableTypes.Integer": {"fullname": "causy.variables.VariableTypes.Integer", "modulename": "causy.variables", "qualname": "VariableTypes.Integer", "kind": "variable", "doc": "

\n", "default_value": "<VariableTypes.Integer: 'integer'>"}, "causy.variables.VariableTypes.Float": {"fullname": "causy.variables.VariableTypes.Float", "modulename": "causy.variables", "qualname": "VariableTypes.Float", "kind": "variable", "doc": "

\n", "default_value": "<VariableTypes.Float: 'float'>"}, "causy.variables.VariableTypes.Bool": {"fullname": "causy.variables.VariableTypes.Bool", "modulename": "causy.variables", "qualname": "VariableTypes.Bool", "kind": "variable", "doc": "

\n", "default_value": "<VariableTypes.Bool: 'bool'>"}, "causy.variables.BaseVariable": {"fullname": "causy.variables.BaseVariable", "modulename": "causy.variables", "qualname": "BaseVariable", "kind": "class", "doc": "

Represents a single variable. It can be a string, int, float or bool. The type of the variable is determined by the\ntype attribute.

\n", "bases": "pydantic.main.BaseModel, typing.Generic[~VariableInterfaceType]"}, "causy.variables.BaseVariable.name": {"fullname": "causy.variables.BaseVariable.name", "modulename": "causy.variables", "qualname": "BaseVariable.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.variables.BaseVariable.value": {"fullname": "causy.variables.BaseVariable.value", "modulename": "causy.variables", "qualname": "BaseVariable.value", "kind": "variable", "doc": "

\n", "annotation": ": Union[str, int, float, bool]"}, "causy.variables.BaseVariable.choices": {"fullname": "causy.variables.BaseVariable.choices", "modulename": "causy.variables", "qualname": "BaseVariable.choices", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[Union[str, int, float, bool]]]"}, "causy.variables.BaseVariable.is_valid": {"fullname": "causy.variables.BaseVariable.is_valid", "modulename": "causy.variables", "qualname": "BaseVariable.is_valid", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "causy.variables.BaseVariable.is_valid_value": {"fullname": "causy.variables.BaseVariable.is_valid_value", "modulename": "causy.variables", "qualname": "BaseVariable.is_valid_value", "kind": "function", "doc": "

\n", "signature": "(self, value):", "funcdef": "def"}, "causy.variables.BaseVariable.validate_value": {"fullname": "causy.variables.BaseVariable.validate_value", "modulename": "causy.variables", "qualname": "BaseVariable.validate_value", "kind": "function", "doc": "

\n", "signature": "(self, value):", "funcdef": "def"}, "causy.variables.BaseVariable.type": {"fullname": "causy.variables.BaseVariable.type", "modulename": "causy.variables", "qualname": "BaseVariable.type", "kind": "variable", "doc": "

\n", "annotation": ": Optional[str]"}, "causy.variables.StringVariable": {"fullname": "causy.variables.StringVariable", "modulename": "causy.variables", "qualname": "StringVariable", "kind": "class", "doc": "

Represents a single string variable.

\n", "bases": "BaseVariable, typing.Generic[~VariableInterfaceType]"}, "causy.variables.StringVariable.model_post_init": {"fullname": "causy.variables.StringVariable.model_post_init", "modulename": "causy.variables", "qualname": "StringVariable.model_post_init", "kind": "function", "doc": "

This function is meant to behave like a BaseModel method to initialise private attributes.

\n\n

It takes context as an argument since that's what pydantic-core passes when calling it.

\n\n

Args:\n self: The BaseModel instance.\n context: The context.

\n", "signature": "(self: pydantic.main.BaseModel, context: Any, /) -> None:", "funcdef": "def"}, "causy.variables.IntegerVariable": {"fullname": "causy.variables.IntegerVariable", "modulename": "causy.variables", "qualname": "IntegerVariable", "kind": "class", "doc": "

Represents a single int variable.

\n", "bases": "BaseVariable, typing.Generic[~VariableInterfaceType]"}, "causy.variables.IntegerVariable.model_post_init": {"fullname": "causy.variables.IntegerVariable.model_post_init", "modulename": "causy.variables", "qualname": "IntegerVariable.model_post_init", "kind": "function", "doc": "

This function is meant to behave like a BaseModel method to initialise private attributes.

\n\n

It takes context as an argument since that's what pydantic-core passes when calling it.

\n\n

Args:\n self: The BaseModel instance.\n context: The context.

\n", "signature": "(self: pydantic.main.BaseModel, context: Any, /) -> None:", "funcdef": "def"}, "causy.variables.FloatVariable": {"fullname": "causy.variables.FloatVariable", "modulename": "causy.variables", "qualname": "FloatVariable", "kind": "class", "doc": "

Represents a single float variable.

\n", "bases": "BaseVariable, typing.Generic[~VariableInterfaceType]"}, "causy.variables.FloatVariable.model_post_init": {"fullname": "causy.variables.FloatVariable.model_post_init", "modulename": "causy.variables", "qualname": "FloatVariable.model_post_init", "kind": "function", "doc": "

This function is meant to behave like a BaseModel method to initialise private attributes.

\n\n

It takes context as an argument since that's what pydantic-core passes when calling it.

\n\n

Args:\n self: The BaseModel instance.\n context: The context.

\n", "signature": "(self: pydantic.main.BaseModel, context: Any, /) -> None:", "funcdef": "def"}, "causy.variables.BoolVariable": {"fullname": "causy.variables.BoolVariable", "modulename": "causy.variables", "qualname": "BoolVariable", "kind": "class", "doc": "

Represents a single bool variable.

\n", "bases": "BaseVariable, typing.Generic[~VariableInterfaceType]"}, "causy.variables.BoolVariable.model_post_init": {"fullname": "causy.variables.BoolVariable.model_post_init", "modulename": "causy.variables", "qualname": "BoolVariable.model_post_init", "kind": "function", "doc": "

This function is meant to behave like a BaseModel method to initialise private attributes.

\n\n

It takes context as an argument since that's what pydantic-core passes when calling it.

\n\n

Args:\n self: The BaseModel instance.\n context: The context.

\n", "signature": "(self: pydantic.main.BaseModel, context: Any, /) -> None:", "funcdef": "def"}, "causy.variables.VariableReference": {"fullname": "causy.variables.VariableReference", "modulename": "causy.variables", "qualname": "VariableReference", "kind": "class", "doc": "

Represents a reference to a variable.

\n", "bases": "pydantic.main.BaseModel, typing.Generic[~VariableInterfaceType]"}, "causy.variables.VariableReference.name": {"fullname": "causy.variables.VariableReference.name", "modulename": "causy.variables", "qualname": "VariableReference.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.variables.VariableReference.type": {"fullname": "causy.variables.VariableReference.type", "modulename": "causy.variables", "qualname": "VariableReference.type", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.variables.VARIABLE_MAPPING": {"fullname": "causy.variables.VARIABLE_MAPPING", "modulename": "causy.variables", "qualname": "VARIABLE_MAPPING", "kind": "variable", "doc": "

\n", "default_value": "{'string': <class 'causy.variables.StringVariable'>, 'integer': <class 'causy.variables.IntegerVariable'>, 'float': <class 'causy.variables.FloatVariable'>, 'bool': <class 'causy.variables.BoolVariable'>}"}, "causy.variables.BoolParameter": {"fullname": "causy.variables.BoolParameter", "modulename": "causy.variables", "qualname": "BoolParameter", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[bool, causy.variables.VariableReference]"}, "causy.variables.IntegerParameter": {"fullname": "causy.variables.IntegerParameter", "modulename": "causy.variables", "qualname": "IntegerParameter", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[int, causy.variables.VariableReference]"}, "causy.variables.FloatParameter": {"fullname": "causy.variables.FloatParameter", "modulename": "causy.variables", "qualname": "FloatParameter", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[float, causy.variables.VariableReference]"}, "causy.variables.StringParameter": {"fullname": "causy.variables.StringParameter", "modulename": "causy.variables", "qualname": "StringParameter", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[str, causy.variables.VariableReference]"}, "causy.variables.CausyParameter": {"fullname": "causy.variables.CausyParameter", "modulename": "causy.variables", "qualname": "CausyParameter", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[bool, causy.variables.VariableReference, int, float, str]"}, "causy.variables.validate_variable_values": {"fullname": "causy.variables.validate_variable_values", "modulename": "causy.variables", "qualname": "validate_variable_values", "kind": "function", "doc": "

Validate the variable values for the algorithm.

\n\n
Parameters
\n\n
    \n
  • algorithm:
    • \n
  • variable_values:
    • \n
\n\n
Returns
\n", "signature": "(algorithm, variable_values: Dict[str, Union[str, int, float, bool]]):", "funcdef": "def"}, "causy.variables.resolve_variables": {"fullname": "causy.variables.resolve_variables", "modulename": "causy.variables", "qualname": "resolve_variables", "kind": "function", "doc": "

Resolve the variables from the list of variables and the variable values coming from the user.

\n\n
Parameters
\n\n
    \n
  • variables:
    • \n
  • variable_values:
    • \n
\n\n
Returns
\n", "signature": "(\tvariables: List[causy.variables.BaseVariable],\tvariable_values: Dict[str, Union[str, int, float, bool]]) -> Dict[str, Union[str, int, float, bool]]:", "funcdef": "def"}, "causy.variables.resolve_variable_to_object": {"fullname": "causy.variables.resolve_variable_to_object", "modulename": "causy.variables", "qualname": "resolve_variable_to_object", "kind": "function", "doc": "

Resolve the variables to the object.

\n\n
Parameters
\n\n
    \n
  • obj:
    • \n
  • variables:
    • \n
\n\n
Returns
\n", "signature": "(obj: Any, variables):", "funcdef": "def"}, "causy.variables.resolve_variables_to_algorithm_for_pipeline_steps": {"fullname": "causy.variables.resolve_variables_to_algorithm_for_pipeline_steps", "modulename": "causy.variables", "qualname": "resolve_variables_to_algorithm_for_pipeline_steps", "kind": "function", "doc": "

Resolve the variables to the algorithm.

\n\n
Parameters
\n\n
    \n
  • pipeline_steps:
    • \n
  • variables:
    • \n
\n\n
Returns
\n", "signature": "(pipeline_steps, variables):", "funcdef": "def"}, "causy.variables.deserialize_variable": {"fullname": "causy.variables.deserialize_variable", "modulename": "causy.variables", "qualname": "deserialize_variable", "kind": "function", "doc": "

Deserialize the variable from the dictionary.

\n\n
Parameters
\n\n
    \n
  • variable_dict:
    • \n
\n\n
Returns
\n", "signature": "(\tvariable_dict: Dict[str, Union[str, int, float, bool]]) -> causy.variables.BaseVariable:", "funcdef": "def"}, "causy.variables.deserialize_variable_references": {"fullname": "causy.variables.deserialize_variable_references", "modulename": "causy.variables", "qualname": "deserialize_variable_references", "kind": "function", "doc": "

Deserialize the variable references from the pipeline step.

\n\n
Parameters
\n\n
    \n
  • pipeline_step:
    • \n
\n\n
Returns
\n", "signature": "(element: object) -> object:", "funcdef": "def"}, "causy.workspaces": {"fullname": "causy.workspaces", "modulename": "causy.workspaces", "kind": "module", "doc": "

Representation of a causy workspace.

\n\n

Exemplary folder structure

\n\n
    \n
  • causy.yaml (contains workspace wide settings for stuff like name, author, pipeline definitions)
    • \n
  • any_pipeline.yaml (seperate pipeline definition referenced by causy.yaml)
    • \n
  • custom_pipeline_step.py (a project specific pipeline step)
    • \n
  • some_data_loader.py (a data loader to ship data into causy)
    • \n
  • tune_pipeline_1709406402/ (a single experiment)\n
      \n
    • causy_experiment.json (contains the full definition of everything used)
      • \n
    • causy_model.json (the actual generated model)
      • \n
    • \n
\n\n

Examples

\n\n
    \n
  • the user generates a new workspace because they want to work on a new causal discovery project (causy workspace create)
    • \n
  • they add a custom data loader, pipeline steps and extend an existing pipeline (causy workspace data-loaders create)
    • \n
  • they run multiple experiments (causy workspace experiments create, causy workspace experiments execute $EXPERIMENT_NAME)
    • \n
\n"}, "causy.workspaces.cli": {"fullname": "causy.workspaces.cli", "modulename": "causy.workspaces.cli", "kind": "module", "doc": "

\n"}, "causy.workspaces.cli.workspace_app": {"fullname": "causy.workspaces.cli.workspace_app", "modulename": "causy.workspaces.cli", "qualname": "workspace_app", "kind": "variable", "doc": "

\n", "default_value": "<typer.main.Typer object>"}, "causy.workspaces.cli.pipeline_app": {"fullname": "causy.workspaces.cli.pipeline_app", "modulename": "causy.workspaces.cli", "qualname": "pipeline_app", "kind": "variable", "doc": "

\n", "default_value": "<typer.main.Typer object>"}, "causy.workspaces.cli.experiment_app": {"fullname": "causy.workspaces.cli.experiment_app", "modulename": "causy.workspaces.cli", "qualname": "experiment_app", "kind": "variable", "doc": "

\n", "default_value": "<typer.main.Typer object>"}, "causy.workspaces.cli.dataloader_app": {"fullname": "causy.workspaces.cli.dataloader_app", "modulename": "causy.workspaces.cli", "qualname": "dataloader_app", "kind": "variable", "doc": "

\n", "default_value": "<typer.main.Typer object>"}, "causy.workspaces.cli.logger": {"fullname": "causy.workspaces.cli.logger", "modulename": "causy.workspaces.cli", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.workspaces.cli (WARNING)>"}, "causy.workspaces.cli.NO_COLOR": {"fullname": "causy.workspaces.cli.NO_COLOR", "modulename": "causy.workspaces.cli", "qualname": "NO_COLOR", "kind": "variable", "doc": "

\n", "default_value": "False"}, "causy.workspaces.cli.WORKSPACE_FILE_NAME": {"fullname": "causy.workspaces.cli.WORKSPACE_FILE_NAME", "modulename": "causy.workspaces.cli", "qualname": "WORKSPACE_FILE_NAME", "kind": "variable", "doc": "

\n", "default_value": "'workspace.yml'"}, "causy.workspaces.cli.JINJA_ENV": {"fullname": "causy.workspaces.cli.JINJA_ENV", "modulename": "causy.workspaces.cli", "qualname": "JINJA_ENV", "kind": "variable", "doc": "

\n", "default_value": "<jinja2.environment.Environment object>"}, "causy.workspaces.cli.WorkspaceNotFoundError": {"fullname": "causy.workspaces.cli.WorkspaceNotFoundError", "modulename": "causy.workspaces.cli", "qualname": "WorkspaceNotFoundError", "kind": "class", "doc": "

Common base class for all non-exit exceptions.

\n", "bases": "builtins.Exception"}, "causy.workspaces.cli.show_error": {"fullname": "causy.workspaces.cli.show_error", "modulename": "causy.workspaces.cli", "qualname": "show_error", "kind": "function", "doc": "

\n", "signature": "(message: str):", "funcdef": "def"}, "causy.workspaces.cli.show_success": {"fullname": "causy.workspaces.cli.show_success", "modulename": "causy.workspaces.cli", "qualname": "show_success", "kind": "function", "doc": "

\n", "signature": "(message: str):", "funcdef": "def"}, "causy.workspaces.cli.write_to_workspace": {"fullname": "causy.workspaces.cli.write_to_workspace", "modulename": "causy.workspaces.cli", "qualname": "write_to_workspace", "kind": "function", "doc": "

\n", "signature": "(workspace: causy.workspaces.models.Workspace):", "funcdef": "def"}, "causy.workspaces.cli.create_pipeline": {"fullname": "causy.workspaces.cli.create_pipeline", "modulename": "causy.workspaces.cli", "qualname": "create_pipeline", "kind": "function", "doc": "

Create a new pipeline in the current workspace.

\n", "signature": "():", "funcdef": "def"}, "causy.workspaces.cli.remove_pipeline": {"fullname": "causy.workspaces.cli.remove_pipeline", "modulename": "causy.workspaces.cli", "qualname": "remove_pipeline", "kind": "function", "doc": "

Remove a pipeline from the current workspace.

\n", "signature": "(pipeline_name: str):", "funcdef": "def"}, "causy.workspaces.cli.create_experiment": {"fullname": "causy.workspaces.cli.create_experiment", "modulename": "causy.workspaces.cli", "qualname": "create_experiment", "kind": "function", "doc": "

Create a new experiment in the current workspace.

\n", "signature": "():", "funcdef": "def"}, "causy.workspaces.cli.remove_experiment": {"fullname": "causy.workspaces.cli.remove_experiment", "modulename": "causy.workspaces.cli", "qualname": "remove_experiment", "kind": "function", "doc": "

Remove an experiment from the current workspace.

\n", "signature": "(experiment_name: str):", "funcdef": "def"}, "causy.workspaces.cli.clear_experiment": {"fullname": "causy.workspaces.cli.clear_experiment", "modulename": "causy.workspaces.cli", "qualname": "clear_experiment", "kind": "function", "doc": "

Clear all versions of an experiment.

\n", "signature": "(experiment_name: str):", "funcdef": "def"}, "causy.workspaces.cli.update_experiment_variable": {"fullname": "causy.workspaces.cli.update_experiment_variable", "modulename": "causy.workspaces.cli", "qualname": "update_experiment_variable", "kind": "function", "doc": "

Update a variable in an experiment.

\n", "signature": "(experiment_name: str, variable_name: str, variable_value: str):", "funcdef": "def"}, "causy.workspaces.cli.create_data_loader": {"fullname": "causy.workspaces.cli.create_data_loader", "modulename": "causy.workspaces.cli", "qualname": "create_data_loader", "kind": "function", "doc": "

Create a new data loader in the current workspace.

\n", "signature": "():", "funcdef": "def"}, "causy.workspaces.cli.remove_data_loader": {"fullname": "causy.workspaces.cli.remove_data_loader", "modulename": "causy.workspaces.cli", "qualname": "remove_data_loader", "kind": "function", "doc": "

Remove a data loader from the current workspace.

\n", "signature": "(data_loader_name: str):", "funcdef": "def"}, "causy.workspaces.cli.info": {"fullname": "causy.workspaces.cli.info", "modulename": "causy.workspaces.cli", "qualname": "info", "kind": "function", "doc": "

Show general information about the workspace.

\n", "signature": "():", "funcdef": "def"}, "causy.workspaces.cli.init": {"fullname": "causy.workspaces.cli.init", "modulename": "causy.workspaces.cli", "qualname": "init", "kind": "function", "doc": "

Initialize a new workspace in the current directory.

\n", "signature": "():", "funcdef": "def"}, "causy.workspaces.cli.execute": {"fullname": "causy.workspaces.cli.execute", "modulename": "causy.workspaces.cli", "qualname": "execute", "kind": "function", "doc": "

Execute an experiment or all experiments in the workspace.

\n", "signature": "(experiment_name: str = None, force_reexecution: bool = False):", "funcdef": "def"}, "causy.workspaces.cli.diff": {"fullname": "causy.workspaces.cli.diff", "modulename": "causy.workspaces.cli", "qualname": "diff", "kind": "function", "doc": "

Show the differences between multiple experiment results.

\n", "signature": "(experiment_names: List[str], only_differences: bool = False):", "funcdef": "def"}, "causy.workspaces.models": {"fullname": "causy.workspaces.models", "modulename": "causy.workspaces.models", "kind": "module", "doc": "

\n"}, "causy.workspaces.models.Experiment": {"fullname": "causy.workspaces.models.Experiment", "modulename": "causy.workspaces.models", "qualname": "Experiment", "kind": "class", "doc": "

represents a single experiment

\n\n
Parameters
\n\n
    \n
  • name: name of the experiment
    • \n
  • pipeline: the name of the pipeline used
    • \n
\n", "bases": "pydantic.main.BaseModel"}, "causy.workspaces.models.Experiment.pipeline": {"fullname": "causy.workspaces.models.Experiment.pipeline", "modulename": "causy.workspaces.models", "qualname": "Experiment.pipeline", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.workspaces.models.Experiment.dataloader": {"fullname": "causy.workspaces.models.Experiment.dataloader", "modulename": "causy.workspaces.models", "qualname": "Experiment.dataloader", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.workspaces.models.Experiment.variables": {"fullname": "causy.workspaces.models.Experiment.variables", "modulename": "causy.workspaces.models", "qualname": "Experiment.variables", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict[str, Union[str, int, float, bool]]]"}, "causy.workspaces.models.Experiment.model_config": {"fullname": "causy.workspaces.models.Experiment.model_config", "modulename": "causy.workspaces.models", "qualname": "Experiment.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.workspaces.models.Experiment.model_fields": {"fullname": "causy.workspaces.models.Experiment.model_fields", "modulename": "causy.workspaces.models", "qualname": "Experiment.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'pipeline': FieldInfo(annotation=str, required=True), 'dataloader': FieldInfo(annotation=str, required=True), 'variables': FieldInfo(annotation=Union[Dict[str, Union[str, int, float, bool]], NoneType], required=False, default={})}"}, "causy.workspaces.models.Experiment.model_computed_fields": {"fullname": "causy.workspaces.models.Experiment.model_computed_fields", "modulename": "causy.workspaces.models", "qualname": "Experiment.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.workspaces.models.Workspace": {"fullname": "causy.workspaces.models.Workspace", "modulename": "causy.workspaces.models", "qualname": "Workspace", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel"}, "causy.workspaces.models.Workspace.name": {"fullname": "causy.workspaces.models.Workspace.name", "modulename": "causy.workspaces.models", "qualname": "Workspace.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.workspaces.models.Workspace.author": {"fullname": "causy.workspaces.models.Workspace.author", "modulename": "causy.workspaces.models", "qualname": "Workspace.author", "kind": "variable", "doc": "

\n", "annotation": ": Optional[str]"}, "causy.workspaces.models.Workspace.pipelines": {"fullname": "causy.workspaces.models.Workspace.pipelines", "modulename": "causy.workspaces.models", "qualname": "Workspace.pipelines", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict[str, causy.models.Algorithm | causy.models.AlgorithmReference]]"}, "causy.workspaces.models.Workspace.dataloaders": {"fullname": "causy.workspaces.models.Workspace.dataloaders", "modulename": "causy.workspaces.models", "qualname": "Workspace.dataloaders", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict[str, causy.data_loader.DataLoaderReference]]"}, "causy.workspaces.models.Workspace.experiments": {"fullname": "causy.workspaces.models.Workspace.experiments", "modulename": "causy.workspaces.models", "qualname": "Workspace.experiments", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict[str, causy.workspaces.models.Experiment]]"}, "causy.workspaces.models.Workspace.model_config": {"fullname": "causy.workspaces.models.Workspace.model_config", "modulename": "causy.workspaces.models", "qualname": "Workspace.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.workspaces.models.Workspace.model_fields": {"fullname": "causy.workspaces.models.Workspace.model_fields", "modulename": "causy.workspaces.models", "qualname": "Workspace.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': FieldInfo(annotation=str, required=True), 'author': FieldInfo(annotation=Union[str, NoneType], required=True), 'pipelines': FieldInfo(annotation=Union[Dict[str, Union[Algorithm, AlgorithmReference]], NoneType], required=True), 'dataloaders': FieldInfo(annotation=Union[Dict[str, DataLoaderReference], NoneType], required=True), 'experiments': FieldInfo(annotation=Union[Dict[str, Experiment], NoneType], required=True)}"}, "causy.workspaces.models.Workspace.model_computed_fields": {"fullname": "causy.workspaces.models.Workspace.model_computed_fields", "modulename": "causy.workspaces.models", "qualname": "Workspace.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}}, "docInfo": {"causy": {"qualname": 0, "fullname": 1, "annotation": 0, "default_value": 0, "signature": 0, "bases": 0, "doc": 58}, "causy.causal_discovery": {"qualname": 0, "fullname": 3, "annotation": 0, "default_value": 0, "signature": 0, "bases": 0, "doc": 3}, "causy.causal_discovery.constraint": {"qualname": 0, "fullname": 4, "annotation": 0, "default_value": 0, "signature": 0, "bases": 0, "doc": 3}, "causy.causal_discovery.constraint.algorithms": {"qualname": 0, "fullname": 5, "annotation": 0, "default_value": 0, "signature": 0, "bases": 0, "doc": 3}, "causy.causal_discovery.constraint.algorithms.AVAILABLE_ALGORITHMS": {"qualname": 2, "fullname": 7, "annotation": 0, "default_value": 40, "signature": 0, "bases": 0, "doc": 3}, "causy.causal_discovery.constraint.algorithms.fci": {"qualname": 0, "fullname": 6, "annotation": 0, "default_value": 0, "signature": 0, "bases": 0, "doc": 3}, "causy.causal_discovery.constraint.algorithms.fci.InducingPathExtension": {"qualname": 1, "fullname": 7, "annotation": 0, "default_value": 0, "signature": 0, "bases": 5, "doc": 277}, "causy.causal_discovery.constraint.algorithms.fci.InducingPathExtension.GraphAccessMixin": {"qualname": 2, "fullname": 8, "annotation": 0, "default_value": 0, "signature": 0, "bases": 0, "doc": 3}, "causy.causal_discovery.constraint.algorithms.fci.InducingPathExtension.GraphAccessMixin.inducing_path_exists": {"qualname": 5, "fullname": 11, "annotation": 0, "default_value": 0, "signature": 81, "bases": 0, "doc": 72}, "causy.causal_discovery.constraint.algorithms.pc": {"qualname": 0, "fullname": 6, "annotation": 0, "default_value": 0, "signature": 0, "bases": 0, "doc": 3}, "causy.causal_discovery.constraint.algorithms.pc.PC_DEFAULT_THRESHOLD": {"qualname": 3, "fullname": 9, "annotation": 0, "default_value": 2, "signature": 0, "bases": 0, "doc": 3}, "causy.causal_discovery.constraint.algorithms.pc.PC_ORIENTATION_RULES": {"qualname": 3, "fullname": 9, "annotation": 0, 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{"tf": 1}}, "df": 1}}}}, "q": {"docs": {}, "df": 0, "u": {"docs": {}, "df": 0, "o": {"docs": {}, "df": 0, "t": {"docs": {"causy.sample_generator.IIDSampleGenerator": {"tf": 2.8284271247461903}, "causy.sample_generator.TimeseriesSampleGenerator": {"tf": 4.47213595499958}}, "df": 2}}}}}}}, "pipeline": ["trimmer"], "_isPrebuiltIndex": true}; + /** pdoc search index */const docs = {"version": "0.9.5", "fields": ["qualname", "fullname", "annotation", "default_value", "signature", "bases", "doc"], "ref": "fullname", "documentStore": {"docs": {"causy": {"fullname": "causy", "modulename": "causy", "kind": "module", "doc": "

causy

\n\n

Causal discovery made easy. Causy allows you to use and implement causal discovery algorithms with easy to use, extend and maintain pipelines. It is built based on pytorch which allows you to run the algorithms on CPUs as well as GPUs seamlessly.

\n\n

Learn more at https://causy.dev.

\n"}, "causy.causal_discovery": {"fullname": "causy.causal_discovery", "modulename": "causy.causal_discovery", "kind": "module", "doc": "

\n"}, "causy.causal_discovery.constraint": {"fullname": "causy.causal_discovery.constraint", "modulename": "causy.causal_discovery.constraint", "kind": "module", "doc": "

\n"}, "causy.causal_discovery.constraint.algorithms": {"fullname": "causy.causal_discovery.constraint.algorithms", "modulename": "causy.causal_discovery.constraint.algorithms", "kind": "module", "doc": "

\n"}, "causy.causal_discovery.constraint.algorithms.AVAILABLE_ALGORITHMS": {"fullname": "causy.causal_discovery.constraint.algorithms.AVAILABLE_ALGORITHMS", "modulename": "causy.causal_discovery.constraint.algorithms", "qualname": "AVAILABLE_ALGORITHMS", "kind": "variable", "doc": "

\n", "default_value": "{'PC': <class 'causy.graph_model.graph_model_factory.<locals>.GraphModel'>, 'ParallelPC': <class 'causy.graph_model.graph_model_factory.<locals>.GraphModel'>}"}, "causy.causal_discovery.constraint.algorithms.fci": {"fullname": "causy.causal_discovery.constraint.algorithms.fci", "modulename": "causy.causal_discovery.constraint.algorithms.fci", "kind": "module", "doc": "

\n"}, "causy.causal_discovery.constraint.algorithms.fci.InducingPathExtension": {"fullname": "causy.causal_discovery.constraint.algorithms.fci.InducingPathExtension", "modulename": "causy.causal_discovery.constraint.algorithms.fci", "qualname": "InducingPathExtension", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel, typing.Generic[~ExtensionType]"}, "causy.causal_discovery.constraint.algorithms.fci.InducingPathExtension.GraphAccessMixin": {"fullname": "causy.causal_discovery.constraint.algorithms.fci.InducingPathExtension.GraphAccessMixin", "modulename": "causy.causal_discovery.constraint.algorithms.fci", "qualname": "InducingPathExtension.GraphAccessMixin", "kind": "class", "doc": "

\n"}, "causy.causal_discovery.constraint.algorithms.fci.InducingPathExtension.GraphAccessMixin.inducing_path_exists": {"fullname": "causy.causal_discovery.constraint.algorithms.fci.InducingPathExtension.GraphAccessMixin.inducing_path_exists", "modulename": "causy.causal_discovery.constraint.algorithms.fci", "qualname": "InducingPathExtension.GraphAccessMixin.inducing_path_exists", "kind": "function", "doc": "

Check if an inducing path from u to v exists.\nAn inducing path from u to v is a directed reference from u to v on which all mediators are colliders.

\n\n
Parameters
\n\n
    \n
  • u: node u
    • \n
  • v: node v
    • \n
\n\n
Returns
\n\n
\n

True if an inducing path exists, False otherwise

\n
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str]) -> bool:", "funcdef": "def"}, "causy.causal_discovery.constraint.algorithms.pc": {"fullname": "causy.causal_discovery.constraint.algorithms.pc", "modulename": "causy.causal_discovery.constraint.algorithms.pc", "kind": "module", "doc": "

\n"}, "causy.causal_discovery.constraint.algorithms.pc.PC_DEFAULT_THRESHOLD": {"fullname": "causy.causal_discovery.constraint.algorithms.pc.PC_DEFAULT_THRESHOLD", "modulename": "causy.causal_discovery.constraint.algorithms.pc", "qualname": "PC_DEFAULT_THRESHOLD", "kind": "variable", "doc": "

\n", "default_value": "0.005"}, "causy.causal_discovery.constraint.algorithms.pc.PC_ORIENTATION_RULES": {"fullname": "causy.causal_discovery.constraint.algorithms.pc.PC_ORIENTATION_RULES", "modulename": "causy.causal_discovery.constraint.algorithms.pc", "qualname": "PC_ORIENTATION_RULES", "kind": "variable", "doc": "

\n", "default_value": "[ColliderTest(generator=AllCombinationsGenerator(comparison_settings=ComparisonSettings(min=2, max=2, name='causy.models.ComparisonSettings'), chunked=False, every_nth=None, generator=None, shuffle_combinations=None, name='causy.generators.AllCombinationsGenerator'), threshold=0.01, chunk_size_parallel_processing=1, parallel=False, display_name='Collider Test', needs_unapplied_actions=True, apply_synchronous=False, conflict_resolution_strategy=<ColliderTestConflictResolutionStrategies.KEEP_FIRST: 'KEEP_FIRST'>, name='causy.causal_discovery.constraint.orientation_rules.pc.ColliderTest'), Loop(pipeline_steps=[NonColliderTest(generator=AllCombinationsGenerator(comparison_settings=ComparisonSettings(min=2, max=2, name='causy.models.ComparisonSettings'), chunked=False, every_nth=None, generator=None, shuffle_combinations=None, name='causy.generators.AllCombinationsGenerator'), threshold=0.01, chunk_size_parallel_processing=1, parallel=False, display_name='Non-Collider Test', needs_unapplied_actions=False, apply_synchronous=False, name='causy.causal_discovery.constraint.orientation_rules.pc.NonColliderTest'), FurtherOrientTripleTest(generator=AllCombinationsGenerator(comparison_settings=ComparisonSettings(min=2, max=2, name='causy.models.ComparisonSettings'), chunked=False, every_nth=None, generator=None, shuffle_combinations=None, name='causy.generators.AllCombinationsGenerator'), threshold=0.01, chunk_size_parallel_processing=1, parallel=False, display_name='Further Orient Triple Test', needs_unapplied_actions=False, apply_synchronous=False, name='causy.causal_discovery.constraint.orientation_rules.pc.FurtherOrientTripleTest'), OrientQuadrupleTest(generator=AllCombinationsGenerator(comparison_settings=ComparisonSettings(min=2, max=2, name='causy.models.ComparisonSettings'), chunked=False, every_nth=None, generator=None, shuffle_combinations=None, name='causy.generators.AllCombinationsGenerator'), threshold=0.01, chunk_size_parallel_processing=1, parallel=False, display_name='Orient Quadruple Test', needs_unapplied_actions=False, apply_synchronous=False, name='causy.causal_discovery.constraint.orientation_rules.pc.OrientQuadrupleTest'), FurtherOrientQuadrupleTest(generator=AllCombinationsGenerator(comparison_settings=ComparisonSettings(min=2, max=2, name='causy.models.ComparisonSettings'), chunked=False, every_nth=None, generator=None, shuffle_combinations=None, name='causy.generators.AllCombinationsGenerator'), threshold=0.01, chunk_size_parallel_processing=1, parallel=False, display_name='Further Orient Quadruple Test', needs_unapplied_actions=False, apply_synchronous=False, name='causy.causal_discovery.constraint.orientation_rules.pc.FurtherOrientQuadrupleTest')], exit_condition=ExitOnNoActions(name='causy.common_pipeline_steps.exit_conditions.ExitOnNoActions'), display_name='Orientation Rules Loop', name='causy.common_pipeline_steps.logic.Loop')]"}, "causy.causal_discovery.constraint.algorithms.pc.PC_GRAPH_UI_EXTENSION": {"fullname": "causy.causal_discovery.constraint.algorithms.pc.PC_GRAPH_UI_EXTENSION", "modulename": "causy.causal_discovery.constraint.algorithms.pc", "qualname": "PC_GRAPH_UI_EXTENSION", "kind": "variable", "doc": "

\n", "default_value": "GraphUIExtension(edges=[DirectedEdgeUIConfig(edge_type='DIRECTED', default_ui_config=EdgeUIConfig(color='#333', width=4, style='dashed', marker_start=None, marker_end='ArrowClosed', label_field='correlation', animated=True, label='Direct Effect: ${correlation.toFixed(4)}'), conditional_ui_configs=[ConditionalEdgeUIConfig(ui_config=EdgeUIConfig(color='#f00000', width=4, style='dashed', marker_start=None, marker_end='ArrowClosed', label_field='direct_effect', animated=True, label='Direct Effect: ${direct_effect.toFixed(4)}'), condition_field='direct_effect', condition_value=0.0, condition_comparison=<ConditionalEdgeUIConfigComparison.LESS: 'LESS'>), ConditionalEdgeUIConfig(ui_config=EdgeUIConfig(color='#0f0fff', width=4, style='dashed', marker_start=None, marker_end='ArrowClosed', label_field='direct_effect', animated=True, label='Direct Effect: ${direct_effect.toFixed(4)}'), condition_field='direct_effect', condition_value=0.0, condition_comparison=<ConditionalEdgeUIConfigComparison.GREATER: 'GREATER'>)]), UndirectedEdgeUIConfig(edge_type='UNDIRECTED', default_ui_config=EdgeUIConfig(color='#333', width=4, style='solid', marker_start=None, marker_end=None, label_field='direct_effect', animated=False, label='Correlation: ${correlation.toFixed(4)}'), conditional_ui_configs=None)], name='causy.contrib.graph_ui.GraphUIExtension')"}, "causy.causal_discovery.constraint.algorithms.pc.PC_EDGE_TYPES": {"fullname": "causy.causal_discovery.constraint.algorithms.pc.PC_EDGE_TYPES", "modulename": "causy.causal_discovery.constraint.algorithms.pc", "qualname": "PC_EDGE_TYPES", "kind": "variable", "doc": "

\n", "default_value": "[DIRECTED, UNDIRECTED]"}, "causy.causal_discovery.constraint.algorithms.pc.PC": {"fullname": "causy.causal_discovery.constraint.algorithms.pc.PC", "modulename": "causy.causal_discovery.constraint.algorithms.pc", "qualname": "PC", "kind": "variable", "doc": "

\n", "default_value": "<class 'causy.graph_model.graph_model_factory.<locals>.GraphModel'>"}, "causy.causal_discovery.constraint.algorithms.pc.PCClassic": {"fullname": "causy.causal_discovery.constraint.algorithms.pc.PCClassic", "modulename": "causy.causal_discovery.constraint.algorithms.pc", "qualname": "PCClassic", "kind": "variable", "doc": "

\n", "default_value": "<class 'causy.graph_model.graph_model_factory.<locals>.GraphModel'>"}, "causy.causal_discovery.constraint.algorithms.pc.PCStable": {"fullname": "causy.causal_discovery.constraint.algorithms.pc.PCStable", "modulename": "causy.causal_discovery.constraint.algorithms.pc", "qualname": "PCStable", "kind": "variable", "doc": "

\n", "default_value": "<class 'causy.graph_model.graph_model_factory.<locals>.GraphModel'>"}, "causy.causal_discovery.constraint.algorithms.pc.ParallelPC": {"fullname": "causy.causal_discovery.constraint.algorithms.pc.ParallelPC", "modulename": "causy.causal_discovery.constraint.algorithms.pc", "qualname": "ParallelPC", "kind": "variable", "doc": "

\n", "default_value": "<class 'causy.graph_model.graph_model_factory.<locals>.GraphModel'>"}, "causy.causal_discovery.constraint.independence_tests": {"fullname": "causy.causal_discovery.constraint.independence_tests", "modulename": "causy.causal_discovery.constraint.independence_tests", "kind": "module", "doc": "

\n"}, "causy.causal_discovery.constraint.independence_tests.common": {"fullname": "causy.causal_discovery.constraint.independence_tests.common", "modulename": "causy.causal_discovery.constraint.independence_tests.common", "kind": "module", "doc": "

\n"}, "causy.causal_discovery.constraint.independence_tests.common.logger": {"fullname": "causy.causal_discovery.constraint.independence_tests.common.logger", "modulename": "causy.causal_discovery.constraint.independence_tests.common", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.causal_discovery.constraint.independence_tests.common (WARNING)>"}, "causy.causal_discovery.constraint.independence_tests.common.CorrelationCoefficientTest": {"fullname": "causy.causal_discovery.constraint.independence_tests.common.CorrelationCoefficientTest", "modulename": "causy.causal_discovery.constraint.independence_tests.common", "qualname": "CorrelationCoefficientTest", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.causal_discovery.constraint.independence_tests.common.PartialCorrelationTest": {"fullname": "causy.causal_discovery.constraint.independence_tests.common.PartialCorrelationTest", "modulename": "causy.causal_discovery.constraint.independence_tests.common", "qualname": "PartialCorrelationTest", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.causal_discovery.constraint.independence_tests.common.ExtendedPartialCorrelationTestMatrix": {"fullname": "causy.causal_discovery.constraint.independence_tests.common.ExtendedPartialCorrelationTestMatrix", "modulename": "causy.causal_discovery.constraint.independence_tests.common", "qualname": "ExtendedPartialCorrelationTestMatrix", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.causal_discovery.constraint.independence_tests.common.partial_correlation_regression": {"fullname": "causy.causal_discovery.constraint.independence_tests.common.partial_correlation_regression", "modulename": "causy.causal_discovery.constraint.independence_tests.common", "qualname": "partial_correlation_regression", "kind": "function", "doc": "

Compute the partial correlation coefficient between x and y controlling for other variables in z using linear regression.

\n\n

Arguments:\nx, y : torch.Tensor : Variables for which the partial correlation is computed.\nz : torch.Tensor : Other variables used to control for in the partial correlation.

\n\n

Returns:\npartial_corr : torch.Tensor : Partial correlation coefficient between x and y.

\n", "signature": "(x, y, z):", "funcdef": "def"}, "causy.causal_discovery.constraint.independence_tests.common.ExtendedPartialCorrelationTestLinearRegression": {"fullname": "causy.causal_discovery.constraint.independence_tests.common.ExtendedPartialCorrelationTestLinearRegression", "modulename": "causy.causal_discovery.constraint.independence_tests.common", "qualname": "ExtendedPartialCorrelationTestLinearRegression", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.causal_discovery.constraint.orientation_rules": {"fullname": "causy.causal_discovery.constraint.orientation_rules", "modulename": "causy.causal_discovery.constraint.orientation_rules", "kind": "module", "doc": "

\n"}, "causy.causal_discovery.constraint.orientation_rules.fci": {"fullname": "causy.causal_discovery.constraint.orientation_rules.fci", "modulename": "causy.causal_discovery.constraint.orientation_rules.fci", "kind": "module", "doc": "

\n"}, "causy.causal_discovery.constraint.orientation_rules.fci.ColliderRuleFCI": {"fullname": "causy.causal_discovery.constraint.orientation_rules.fci.ColliderRuleFCI", "modulename": "causy.causal_discovery.constraint.orientation_rules.fci", "qualname": "ColliderRuleFCI", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.causal_discovery.constraint.orientation_rules.pc": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "kind": "module", "doc": "

\n"}, "causy.causal_discovery.constraint.orientation_rules.pc.logger": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.logger", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.causal_discovery.constraint.orientation_rules.pc (WARNING)>"}, "causy.causal_discovery.constraint.orientation_rules.pc.filter_unapplied_actions": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.filter_unapplied_actions", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "filter_unapplied_actions", "kind": "function", "doc": "

Filter out actions that have not been applied to the graph yet.

\n\n
Parameters
\n\n
    \n
  • actions: list of actions
    • \n
  • u: node u
    • \n
  • v: node v
    • \n
\n\n
Returns
\n\n
\n

list of actions that have not been applied to the graph yet

\n
\n", "signature": "(actions, u, v):", "funcdef": "def"}, "causy.causal_discovery.constraint.orientation_rules.pc.generate_restores": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.generate_restores", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "generate_restores", "kind": "function", "doc": "

Generate restore actions for unapplied actions.

\n\n
Parameters
\n\n
    \n
  • unapplied_actions: list of unapplied actions
    • \n
  • x: node x
    • \n
  • y: node y
    • \n
\n\n
Returns
\n\n
\n

list of restore actions

\n
\n", "signature": "(unapplied_actions):", "funcdef": "def"}, "causy.causal_discovery.constraint.orientation_rules.pc.ColliderTestConflictResolutionStrategies": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.ColliderTestConflictResolutionStrategies", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "ColliderTestConflictResolutionStrategies", "kind": "class", "doc": "

Enum for the conflict resolution strategies for the ColliderTest.

\n", "bases": "builtins.str, enum.Enum"}, "causy.causal_discovery.constraint.orientation_rules.pc.ColliderTestConflictResolutionStrategies.KEEP_FIRST": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.ColliderTestConflictResolutionStrategies.KEEP_FIRST", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "ColliderTestConflictResolutionStrategies.KEEP_FIRST", "kind": "variable", "doc": "

\n", "default_value": "<ColliderTestConflictResolutionStrategies.KEEP_FIRST: 'KEEP_FIRST'>"}, "causy.causal_discovery.constraint.orientation_rules.pc.ColliderTestConflictResolutionStrategies.KEEP_LAST": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.ColliderTestConflictResolutionStrategies.KEEP_LAST", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "ColliderTestConflictResolutionStrategies.KEEP_LAST", "kind": "variable", "doc": "

\n", "default_value": "<ColliderTestConflictResolutionStrategies.KEEP_LAST: 'KEEP_LAST'>"}, "causy.causal_discovery.constraint.orientation_rules.pc.ColliderTest": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.ColliderTest", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "ColliderTest", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.causal_discovery.constraint.orientation_rules.pc.ColliderTest.conflict_resolution_strategy": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.ColliderTest.conflict_resolution_strategy", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "ColliderTest.conflict_resolution_strategy", "kind": "variable", "doc": "

\n", "annotation": ": Union[str, causy.variables.VariableReference]"}, "causy.causal_discovery.constraint.orientation_rules.pc.NonColliderTest": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.NonColliderTest", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "NonColliderTest", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.causal_discovery.constraint.orientation_rules.pc.FurtherOrientTripleTest": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.FurtherOrientTripleTest", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "FurtherOrientTripleTest", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.causal_discovery.constraint.orientation_rules.pc.OrientQuadrupleTest": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.OrientQuadrupleTest", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "OrientQuadrupleTest", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.causal_discovery.constraint.orientation_rules.pc.FurtherOrientQuadrupleTest": {"fullname": "causy.causal_discovery.constraint.orientation_rules.pc.FurtherOrientQuadrupleTest", "modulename": "causy.causal_discovery.constraint.orientation_rules.pc", "qualname": "FurtherOrientQuadrupleTest", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.cli": {"fullname": "causy.cli", "modulename": "causy.cli", "kind": "module", "doc": "

\n"}, "causy.cli.app": {"fullname": "causy.cli.app", "modulename": "causy.cli", "qualname": "app", "kind": "variable", "doc": "

\n", "default_value": "<typer.main.Typer object>"}, "causy.cli.eject": {"fullname": "causy.cli.eject", "modulename": "causy.cli", "qualname": "eject", "kind": "function", "doc": "

\n", "signature": "(algorithm: str, output_file: str):", "funcdef": "def"}, "causy.cli.execute": {"fullname": "causy.cli.execute", "modulename": "causy.cli", "qualname": "execute", "kind": "function", "doc": "

\n", "signature": "(\tdata_file: str,\tpipeline: str = None,\talgorithm: str = None,\toutput_file: str = None,\tlog_level: str = 'ERROR'):", "funcdef": "def"}, "causy.common_pipeline_steps": {"fullname": "causy.common_pipeline_steps", "modulename": "causy.common_pipeline_steps", "kind": "module", "doc": "

\n"}, "causy.common_pipeline_steps.calculation": {"fullname": "causy.common_pipeline_steps.calculation", "modulename": "causy.common_pipeline_steps.calculation", "kind": "module", "doc": "

\n"}, "causy.common_pipeline_steps.calculation.CalculatePearsonCorrelations": {"fullname": "causy.common_pipeline_steps.calculation.CalculatePearsonCorrelations", "modulename": "causy.common_pipeline_steps.calculation", "qualname": "CalculatePearsonCorrelations", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.common_pipeline_steps.exit_conditions": {"fullname": "causy.common_pipeline_steps.exit_conditions", "modulename": "causy.common_pipeline_steps.exit_conditions", "kind": "module", "doc": "

\n"}, "causy.common_pipeline_steps.exit_conditions.ExitOnNoActions": {"fullname": "causy.common_pipeline_steps.exit_conditions.ExitOnNoActions", "modulename": "causy.common_pipeline_steps.exit_conditions", "qualname": "ExitOnNoActions", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.ExitConditionInterface"}, "causy.common_pipeline_steps.exit_conditions.ExitOnNoActions.check": {"fullname": "causy.common_pipeline_steps.exit_conditions.ExitOnNoActions.check", "modulename": "causy.common_pipeline_steps.exit_conditions", "qualname": "ExitOnNoActions.check", "kind": "function", "doc": "

Check if there are no actions taken in the last iteration and if so, break the loop\nIf it is the first iteration, do not break the loop (we need to execute the first step)

\n\n
Parameters
\n\n
    \n
  • graph: the graph
    • \n
  • graph_model_instance_: the graph model instance
    • \n
  • actions_taken: the actions taken in the last iteration
    • \n
  • iteration: iteration number
    • \n
\n\n
Returns
\n\n
\n

True if you want to break an iteration, False otherwise

\n
\n", "signature": "(self, graph, graph_model_instance_, actions_taken, iteration) -> bool:", "funcdef": "def"}, "causy.common_pipeline_steps.exit_conditions.ExitOnNoActions.model_config": {"fullname": "causy.common_pipeline_steps.exit_conditions.ExitOnNoActions.model_config", "modulename": "causy.common_pipeline_steps.exit_conditions", "qualname": "ExitOnNoActions.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.common_pipeline_steps.exit_conditions.ExitOnNoActions.model_fields": {"fullname": "causy.common_pipeline_steps.exit_conditions.ExitOnNoActions.model_fields", "modulename": "causy.common_pipeline_steps.exit_conditions", "qualname": "ExitOnNoActions.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.common_pipeline_steps.exit_conditions.ExitOnNoActions.model_computed_fields": {"fullname": "causy.common_pipeline_steps.exit_conditions.ExitOnNoActions.model_computed_fields", "modulename": "causy.common_pipeline_steps.exit_conditions", "qualname": "ExitOnNoActions.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': ComputedFieldInfo(wrapped_property=<property object>, return_type=<class 'str'>, alias=None, alias_priority=None, title=None, field_title_generator=None, description=None, deprecated=None, examples=None, json_schema_extra=None, repr=True)}"}, "causy.common_pipeline_steps.logic": {"fullname": "causy.common_pipeline_steps.logic", "modulename": "causy.common_pipeline_steps.logic", "kind": "module", "doc": "

\n"}, "causy.common_pipeline_steps.logic.Loop": {"fullname": "causy.common_pipeline_steps.logic.Loop", "modulename": "causy.common_pipeline_steps.logic", "qualname": "Loop", "kind": "class", "doc": "

A loop which executes a list of pipeline_steps until the exit_condition is met.

\n", "bases": "causy.interfaces.LogicStepInterface, typing.Generic[~LogicStepInterfaceType]"}, "causy.common_pipeline_steps.logic.ApplyActionsTogether": {"fullname": "causy.common_pipeline_steps.logic.ApplyActionsTogether", "modulename": "causy.common_pipeline_steps.logic", "qualname": "ApplyActionsTogether", "kind": "class", "doc": "

A logic step which collects all actions and only takes them at the end of the pipeline

\n", "bases": "causy.interfaces.LogicStepInterface, typing.Generic[~LogicStepInterfaceType]"}, "causy.common_pipeline_steps.placeholder": {"fullname": "causy.common_pipeline_steps.placeholder", "modulename": "causy.common_pipeline_steps.placeholder", "kind": "module", "doc": "

\n"}, "causy.common_pipeline_steps.placeholder.logger": {"fullname": "causy.common_pipeline_steps.placeholder.logger", "modulename": "causy.common_pipeline_steps.placeholder", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.common_pipeline_steps.placeholder (WARNING)>"}, "causy.common_pipeline_steps.placeholder.PlaceholderTest": {"fullname": "causy.common_pipeline_steps.placeholder.PlaceholderTest", "modulename": "causy.common_pipeline_steps.placeholder", "qualname": "PlaceholderTest", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.PipelineStepInterface, typing.Generic[~PipelineStepInterfaceType]"}, "causy.common_pipeline_steps.placeholder.PlaceholderTest.placeholder_str": {"fullname": "causy.common_pipeline_steps.placeholder.PlaceholderTest.placeholder_str", "modulename": "causy.common_pipeline_steps.placeholder", "qualname": "PlaceholderTest.placeholder_str", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.variables.StringVariable]"}, "causy.common_pipeline_steps.placeholder.PlaceholderTest.placeholder_int": {"fullname": "causy.common_pipeline_steps.placeholder.PlaceholderTest.placeholder_int", "modulename": "causy.common_pipeline_steps.placeholder", "qualname": "PlaceholderTest.placeholder_int", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.variables.IntegerVariable]"}, "causy.common_pipeline_steps.placeholder.PlaceholderTest.placeholder_float": {"fullname": "causy.common_pipeline_steps.placeholder.PlaceholderTest.placeholder_float", "modulename": "causy.common_pipeline_steps.placeholder", "qualname": "PlaceholderTest.placeholder_float", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.variables.FloatVariable]"}, "causy.common_pipeline_steps.placeholder.PlaceholderTest.placeholder_bool": {"fullname": "causy.common_pipeline_steps.placeholder.PlaceholderTest.placeholder_bool", "modulename": "causy.common_pipeline_steps.placeholder", "qualname": "PlaceholderTest.placeholder_bool", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.variables.BoolVariable]"}, "causy.data_loader": {"fullname": "causy.data_loader", "modulename": "causy.data_loader", "kind": "module", "doc": "

\n"}, "causy.data_loader.DataLoaderType": {"fullname": "causy.data_loader.DataLoaderType", "modulename": "causy.data_loader", "qualname": "DataLoaderType", "kind": "class", "doc": "

str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str

\n\n

Create a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to sys.getdefaultencoding().\nerrors defaults to 'strict'.

\n", "bases": "builtins.str, enum.Enum"}, "causy.data_loader.DataLoaderType.DYNAMIC": {"fullname": "causy.data_loader.DataLoaderType.DYNAMIC", "modulename": "causy.data_loader", "qualname": "DataLoaderType.DYNAMIC", "kind": "variable", "doc": "

\n", "default_value": "<DataLoaderType.DYNAMIC: 'dynamic'>"}, "causy.data_loader.DataLoaderType.JSON": {"fullname": "causy.data_loader.DataLoaderType.JSON", "modulename": "causy.data_loader", "qualname": "DataLoaderType.JSON", "kind": "variable", "doc": "

\n", "default_value": "<DataLoaderType.JSON: 'json'>"}, "causy.data_loader.DataLoaderType.JSONL": {"fullname": "causy.data_loader.DataLoaderType.JSONL", "modulename": "causy.data_loader", "qualname": "DataLoaderType.JSONL", "kind": "variable", "doc": "

\n", "default_value": "<DataLoaderType.JSONL: 'jsonl'>"}, "causy.data_loader.DataLoaderReference": {"fullname": "causy.data_loader.DataLoaderReference", "modulename": "causy.data_loader", "qualname": "DataLoaderReference", "kind": "class", "doc": "

represents a single data loader

\n\n
Parameters
\n\n
    \n
  • type: the type of dataloader
    • \n
  • reference: path to either the python class which can be executed to load the data or the data source file itself
    • \n
\n", "bases": "pydantic.main.BaseModel"}, "causy.data_loader.DataLoaderReference.type": {"fullname": "causy.data_loader.DataLoaderReference.type", "modulename": "causy.data_loader", "qualname": "DataLoaderReference.type", "kind": "variable", "doc": "

\n", "annotation": ": causy.data_loader.DataLoaderType"}, "causy.data_loader.DataLoaderReference.reference": {"fullname": "causy.data_loader.DataLoaderReference.reference", "modulename": "causy.data_loader", "qualname": "DataLoaderReference.reference", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.data_loader.DataLoaderReference.options": {"fullname": "causy.data_loader.DataLoaderReference.options", "modulename": "causy.data_loader", "qualname": "DataLoaderReference.options", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict[str, Any]]"}, "causy.data_loader.DataLoaderReference.model_config": {"fullname": "causy.data_loader.DataLoaderReference.model_config", "modulename": "causy.data_loader", "qualname": "DataLoaderReference.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.data_loader.DataLoaderReference.model_fields": {"fullname": "causy.data_loader.DataLoaderReference.model_fields", "modulename": "causy.data_loader", "qualname": "DataLoaderReference.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'type': FieldInfo(annotation=DataLoaderType, required=True), 'reference': FieldInfo(annotation=str, required=True), 'options': FieldInfo(annotation=Union[Dict[str, Any], NoneType], required=False, default=None)}"}, "causy.data_loader.DataLoaderReference.model_computed_fields": {"fullname": "causy.data_loader.DataLoaderReference.model_computed_fields", "modulename": "causy.data_loader", "qualname": "DataLoaderReference.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.data_loader.AbstractDataLoader": {"fullname": "causy.data_loader.AbstractDataLoader", "modulename": "causy.data_loader", "qualname": "AbstractDataLoader", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC"}, "causy.data_loader.AbstractDataLoader.reference": {"fullname": "causy.data_loader.AbstractDataLoader.reference", "modulename": "causy.data_loader", "qualname": "AbstractDataLoader.reference", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.data_loader.AbstractDataLoader.options": {"fullname": "causy.data_loader.AbstractDataLoader.options", "modulename": "causy.data_loader", "qualname": "AbstractDataLoader.options", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict[str, Any]]", "default_value": "None"}, "causy.data_loader.AbstractDataLoader.load": {"fullname": "causy.data_loader.AbstractDataLoader.load", "modulename": "causy.data_loader", "qualname": "AbstractDataLoader.load", "kind": "function", "doc": "

loads the data from the source and returns it as an iterator

\n\n
Returns
\n", "signature": "(self) -> Iterator[Dict[str, Union[float, int, str]]]:", "funcdef": "def"}, "causy.data_loader.AbstractDataLoader.hash": {"fullname": "causy.data_loader.AbstractDataLoader.hash", "modulename": "causy.data_loader", "qualname": "AbstractDataLoader.hash", "kind": "function", "doc": "

returns a hash of the data that is loaded

\n\n
Returns
\n", "signature": "(self) -> str:", "funcdef": "def"}, "causy.data_loader.FileDataLoader": {"fullname": "causy.data_loader.FileDataLoader", "modulename": "causy.data_loader", "qualname": "FileDataLoader", "kind": "class", "doc": "

A data loader which loads data from a file reference (e.g. json, csv, etc.)

\n", "bases": "AbstractDataLoader, abc.ABC"}, "causy.data_loader.FileDataLoader.reference": {"fullname": "causy.data_loader.FileDataLoader.reference", "modulename": "causy.data_loader", "qualname": "FileDataLoader.reference", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.data_loader.FileDataLoader.options": {"fullname": "causy.data_loader.FileDataLoader.options", "modulename": "causy.data_loader", "qualname": "FileDataLoader.options", "kind": "variable", "doc": "

\n", "default_value": "None"}, "causy.data_loader.FileDataLoader.hash": {"fullname": "causy.data_loader.FileDataLoader.hash", "modulename": "causy.data_loader", "qualname": "FileDataLoader.hash", "kind": "function", "doc": "

returns a hash of the data that is loaded

\n\n
Returns
\n", "signature": "(self) -> str:", "funcdef": "def"}, "causy.data_loader.JSONDataLoader": {"fullname": "causy.data_loader.JSONDataLoader", "modulename": "causy.data_loader", "qualname": "JSONDataLoader", "kind": "class", "doc": "

A data loader which loads data from a json file

\n", "bases": "FileDataLoader"}, "causy.data_loader.JSONDataLoader.load": {"fullname": "causy.data_loader.JSONDataLoader.load", "modulename": "causy.data_loader", "qualname": "JSONDataLoader.load", "kind": "function", "doc": "

loads the data from the source and returns it as an iterator

\n\n
Returns
\n", "signature": "(self) -> Iterator[Dict[str, Union[float, int, str]]]:", "funcdef": "def"}, "causy.data_loader.JSONLDataLoader": {"fullname": "causy.data_loader.JSONLDataLoader", "modulename": "causy.data_loader", "qualname": "JSONLDataLoader", "kind": "class", "doc": "

A data loader which loads data from a jsonl file

\n", "bases": "FileDataLoader"}, "causy.data_loader.JSONLDataLoader.load": {"fullname": "causy.data_loader.JSONLDataLoader.load", "modulename": "causy.data_loader", "qualname": "JSONLDataLoader.load", "kind": "function", "doc": "

loads the data from the source and returns it as an iterator

\n\n
Returns
\n", "signature": "(self) -> Iterator[Dict[str, Union[float, int, str]]]:", "funcdef": "def"}, "causy.data_loader.DynamicDataLoader": {"fullname": "causy.data_loader.DynamicDataLoader", "modulename": "causy.data_loader", "qualname": "DynamicDataLoader", "kind": "class", "doc": "

A data loader which loads another data loader dynamically based on the reference

\n", "bases": "AbstractDataLoader"}, "causy.data_loader.DynamicDataLoader.reference": {"fullname": "causy.data_loader.DynamicDataLoader.reference", "modulename": "causy.data_loader", "qualname": "DynamicDataLoader.reference", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.data_loader.DynamicDataLoader.data_loader": {"fullname": "causy.data_loader.DynamicDataLoader.data_loader", "modulename": "causy.data_loader", "qualname": "DynamicDataLoader.data_loader", "kind": "variable", "doc": "

\n", "annotation": ": causy.data_loader.AbstractDataLoader"}, "causy.data_loader.DynamicDataLoader.options": {"fullname": "causy.data_loader.DynamicDataLoader.options", "modulename": "causy.data_loader", "qualname": "DynamicDataLoader.options", "kind": "variable", "doc": "

\n", "default_value": "None"}, "causy.data_loader.DynamicDataLoader.load": {"fullname": "causy.data_loader.DynamicDataLoader.load", "modulename": "causy.data_loader", "qualname": "DynamicDataLoader.load", "kind": "function", "doc": "

loads the data from the source and returns it as an iterator

\n\n
Returns
\n", "signature": "(self) -> Iterator[Dict[str, Union[float, int, str]]]:", "funcdef": "def"}, "causy.data_loader.DATA_LOADERS": {"fullname": "causy.data_loader.DATA_LOADERS", "modulename": "causy.data_loader", "qualname": "DATA_LOADERS", "kind": "variable", "doc": "

\n", "default_value": "{<DataLoaderType.JSON: 'json'>: <class 'causy.data_loader.JSONDataLoader'>, <DataLoaderType.JSONL: 'jsonl'>: <class 'causy.data_loader.JSONLDataLoader'>, <DataLoaderType.DYNAMIC: 'dynamic'>: <class 'causy.data_loader.DynamicDataLoader'>}"}, "causy.data_loader.load_data_loader": {"fullname": "causy.data_loader.load_data_loader", "modulename": "causy.data_loader", "qualname": "load_data_loader", "kind": "function", "doc": "

loads the data loader based on the reference

\n\n
Parameters
\n\n
    \n
  • reference: a data loader reference
    • \n
\n\n
Returns
\n", "signature": "(\treference: causy.data_loader.DataLoaderReference) -> causy.data_loader.AbstractDataLoader:", "funcdef": "def"}, "causy.edge_types": {"fullname": "causy.edge_types", "modulename": "causy.edge_types", "kind": "module", "doc": "

\n"}, "causy.edge_types.EdgeTypeEnum": {"fullname": "causy.edge_types.EdgeTypeEnum", "modulename": "causy.edge_types", "qualname": "EdgeTypeEnum", "kind": "class", "doc": "

str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str

\n\n

Create a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to sys.getdefaultencoding().\nerrors defaults to 'strict'.

\n", "bases": "builtins.str, enum.Enum"}, "causy.edge_types.EdgeTypeEnum.DIRECTED": {"fullname": "causy.edge_types.EdgeTypeEnum.DIRECTED", "modulename": "causy.edge_types", "qualname": "EdgeTypeEnum.DIRECTED", "kind": "variable", "doc": "

\n", "default_value": "<EdgeTypeEnum.DIRECTED: 'directed'>"}, "causy.edge_types.EdgeTypeEnum.UNDIRECTED": {"fullname": "causy.edge_types.EdgeTypeEnum.UNDIRECTED", "modulename": "causy.edge_types", "qualname": "EdgeTypeEnum.UNDIRECTED", "kind": "variable", "doc": "

\n", "default_value": "<EdgeTypeEnum.UNDIRECTED: 'undirected'>"}, "causy.edge_types.EdgeTypeEnum.BIDIRECTED": {"fullname": "causy.edge_types.EdgeTypeEnum.BIDIRECTED", "modulename": "causy.edge_types", "qualname": "EdgeTypeEnum.BIDIRECTED", "kind": "variable", "doc": "

\n", "default_value": "<EdgeTypeEnum.BIDIRECTED: 'bidirected'>"}, "causy.edge_types.DirectedEdge": {"fullname": "causy.edge_types.DirectedEdge", "modulename": "causy.edge_types", "qualname": "DirectedEdge", "kind": "class", "doc": "

Edge type interface for the graph\nAn edge type is defined by a name

\n", "bases": "causy.interfaces.EdgeTypeInterface, typing.Generic[~EdgeTypeInterfaceType]"}, "causy.edge_types.DirectedEdgeUIConfig": {"fullname": "causy.edge_types.DirectedEdgeUIConfig", "modulename": "causy.edge_types", "qualname": "DirectedEdgeUIConfig", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "causy.contrib.graph_ui.EdgeTypeConfig"}, "causy.edge_types.DirectedEdgeUIConfig.edge_type": {"fullname": "causy.edge_types.DirectedEdgeUIConfig.edge_type", "modulename": "causy.edge_types", "qualname": "DirectedEdgeUIConfig.edge_type", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.edge_types.DirectedEdgeUIConfig.default_ui_config": {"fullname": "causy.edge_types.DirectedEdgeUIConfig.default_ui_config", "modulename": "causy.edge_types", "qualname": "DirectedEdgeUIConfig.default_ui_config", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.contrib.graph_ui.EdgeUIConfig]"}, "causy.edge_types.DirectedEdgeUIConfig.conditional_ui_configs": {"fullname": "causy.edge_types.DirectedEdgeUIConfig.conditional_ui_configs", "modulename": "causy.edge_types", "qualname": "DirectedEdgeUIConfig.conditional_ui_configs", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[causy.contrib.graph_ui.ConditionalEdgeUIConfig]]"}, "causy.edge_types.DirectedEdgeUIConfig.model_config": {"fullname": "causy.edge_types.DirectedEdgeUIConfig.model_config", "modulename": "causy.edge_types", "qualname": "DirectedEdgeUIConfig.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.edge_types.DirectedEdgeUIConfig.model_fields": {"fullname": "causy.edge_types.DirectedEdgeUIConfig.model_fields", "modulename": "causy.edge_types", "qualname": "DirectedEdgeUIConfig.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'edge_type': FieldInfo(annotation=str, required=False, default='DIRECTED'), 'default_ui_config': FieldInfo(annotation=Union[EdgeUIConfig, NoneType], required=False, default=EdgeUIConfig(color='#333', width=4, style='dashed', marker_start=None, marker_end='ArrowClosed', label_field='correlation', animated=True, label='Direct Effect: ${correlation.toFixed(4)}')), 'conditional_ui_configs': FieldInfo(annotation=Union[List[ConditionalEdgeUIConfig], NoneType], required=False, default=[ConditionalEdgeUIConfig(ui_config=EdgeUIConfig(color='#f00000', width=4, style='dashed', marker_start=None, marker_end='ArrowClosed', label_field='direct_effect', animated=True, label='Direct Effect: ${direct_effect.toFixed(4)}'), condition_field='direct_effect', condition_value=0.0, condition_comparison=<ConditionalEdgeUIConfigComparison.LESS: 'LESS'>), ConditionalEdgeUIConfig(ui_config=EdgeUIConfig(color='#0f0fff', width=4, style='dashed', marker_start=None, marker_end='ArrowClosed', label_field='direct_effect', animated=True, label='Direct Effect: ${direct_effect.toFixed(4)}'), condition_field='direct_effect', condition_value=0.0, condition_comparison=<ConditionalEdgeUIConfigComparison.GREATER: 'GREATER'>)])}"}, "causy.edge_types.DirectedEdgeUIConfig.model_computed_fields": {"fullname": "causy.edge_types.DirectedEdgeUIConfig.model_computed_fields", "modulename": "causy.edge_types", "qualname": "DirectedEdgeUIConfig.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.edge_types.UndirectedEdge": {"fullname": "causy.edge_types.UndirectedEdge", "modulename": "causy.edge_types", "qualname": "UndirectedEdge", "kind": "class", "doc": "

Edge type interface for the graph\nAn edge type is defined by a name

\n", "bases": "causy.interfaces.EdgeTypeInterface, typing.Generic[~EdgeTypeInterfaceType]"}, "causy.edge_types.UndirectedEdgeUIConfig": {"fullname": "causy.edge_types.UndirectedEdgeUIConfig", "modulename": "causy.edge_types", "qualname": "UndirectedEdgeUIConfig", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "causy.contrib.graph_ui.EdgeTypeConfig"}, "causy.edge_types.UndirectedEdgeUIConfig.edge_type": {"fullname": "causy.edge_types.UndirectedEdgeUIConfig.edge_type", "modulename": "causy.edge_types", "qualname": "UndirectedEdgeUIConfig.edge_type", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.edge_types.UndirectedEdgeUIConfig.default_ui_config": {"fullname": "causy.edge_types.UndirectedEdgeUIConfig.default_ui_config", "modulename": "causy.edge_types", "qualname": "UndirectedEdgeUIConfig.default_ui_config", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.contrib.graph_ui.EdgeUIConfig]"}, "causy.edge_types.UndirectedEdgeUIConfig.model_config": {"fullname": "causy.edge_types.UndirectedEdgeUIConfig.model_config", "modulename": "causy.edge_types", "qualname": "UndirectedEdgeUIConfig.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.edge_types.UndirectedEdgeUIConfig.model_fields": {"fullname": "causy.edge_types.UndirectedEdgeUIConfig.model_fields", "modulename": "causy.edge_types", "qualname": "UndirectedEdgeUIConfig.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'edge_type': FieldInfo(annotation=str, required=False, default='UNDIRECTED'), 'default_ui_config': FieldInfo(annotation=Union[EdgeUIConfig, NoneType], required=False, default=EdgeUIConfig(color='#333', width=4, style='solid', marker_start=None, marker_end=None, label_field='direct_effect', animated=False, label='Correlation: ${correlation.toFixed(4)}')), 'conditional_ui_configs': FieldInfo(annotation=Union[List[ConditionalEdgeUIConfig], NoneType], required=False, default=None)}"}, "causy.edge_types.UndirectedEdgeUIConfig.model_computed_fields": {"fullname": "causy.edge_types.UndirectedEdgeUIConfig.model_computed_fields", "modulename": "causy.edge_types", "qualname": "UndirectedEdgeUIConfig.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.edge_types.BiDirectedEdge": {"fullname": "causy.edge_types.BiDirectedEdge", "modulename": "causy.edge_types", "qualname": "BiDirectedEdge", "kind": "class", "doc": "

Edge type interface for the graph\nAn edge type is defined by a name

\n", "bases": "causy.interfaces.EdgeTypeInterface, typing.Generic[~EdgeTypeInterfaceType]"}, "causy.edge_types.BiDirectedEdgeUIConfig": {"fullname": "causy.edge_types.BiDirectedEdgeUIConfig", "modulename": "causy.edge_types", "qualname": "BiDirectedEdgeUIConfig", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "causy.contrib.graph_ui.EdgeTypeConfig"}, "causy.edge_types.BiDirectedEdgeUIConfig.edge_type": {"fullname": "causy.edge_types.BiDirectedEdgeUIConfig.edge_type", "modulename": "causy.edge_types", "qualname": "BiDirectedEdgeUIConfig.edge_type", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.edge_types.BiDirectedEdgeUIConfig.default_ui_config": {"fullname": "causy.edge_types.BiDirectedEdgeUIConfig.default_ui_config", "modulename": "causy.edge_types", "qualname": "BiDirectedEdgeUIConfig.default_ui_config", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.contrib.graph_ui.EdgeUIConfig]"}, "causy.edge_types.BiDirectedEdgeUIConfig.model_config": {"fullname": "causy.edge_types.BiDirectedEdgeUIConfig.model_config", "modulename": "causy.edge_types", "qualname": "BiDirectedEdgeUIConfig.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.edge_types.BiDirectedEdgeUIConfig.model_fields": {"fullname": "causy.edge_types.BiDirectedEdgeUIConfig.model_fields", "modulename": "causy.edge_types", "qualname": "BiDirectedEdgeUIConfig.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'edge_type': FieldInfo(annotation=str, required=False, default='BIDIRECTED'), 'default_ui_config': FieldInfo(annotation=Union[EdgeUIConfig, NoneType], required=False, default=EdgeUIConfig(color='#333', width=4, style='solid', marker_start='ArrowClosed', marker_end='ArrowClosed', label_field='direct_effect', animated=False, label=None)), 'conditional_ui_configs': FieldInfo(annotation=Union[List[ConditionalEdgeUIConfig], NoneType], required=False, default=None)}"}, "causy.edge_types.BiDirectedEdgeUIConfig.model_computed_fields": {"fullname": "causy.edge_types.BiDirectedEdgeUIConfig.model_computed_fields", "modulename": "causy.edge_types", "qualname": "BiDirectedEdgeUIConfig.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.edge_types.EDGE_TYPES": {"fullname": "causy.edge_types.EDGE_TYPES", "modulename": "causy.edge_types", "qualname": "EDGE_TYPES", "kind": "variable", "doc": "

\n", "default_value": "{'DIRECTED': <class 'causy.edge_types.DirectedEdge'>, 'UNDIRECTED': <class 'causy.edge_types.UndirectedEdge'>, 'BIDIRECTED': <class 'causy.edge_types.BiDirectedEdge'>}"}, "causy.generators": {"fullname": "causy.generators", "modulename": "causy.generators", "kind": "module", "doc": "

\n"}, "causy.generators.logger": {"fullname": "causy.generators.logger", "modulename": "causy.generators", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.generators (WARNING)>"}, "causy.generators.AllCombinationsGenerator": {"fullname": "causy.generators.AllCombinationsGenerator", "modulename": "causy.generators", "qualname": "AllCombinationsGenerator", "kind": "class", "doc": "

Generates all combinations of nodes in the graph in accordance with the configured amount of nodes to compare.\nYields node combinations as tuples, but only in one ordering, i.e. mathematically it returns sets.\ne.g. if your graph consists of the nodes [X, Y, Z] and you want to compare 2 nodes,\nit will yield (X, Y), (X, Z), (Y, Z). It will not additionally yield (Y, X), (Z, X), (Z, Y).

\n", "bases": "causy.interfaces.GeneratorInterface"}, "causy.generators.AllCombinationsGenerator.generate": {"fullname": "causy.generators.AllCombinationsGenerator.generate", "modulename": "causy.generators", "qualname": "AllCombinationsGenerator.generate", "kind": "function", "doc": "

\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tgraph_model_instance_: causy.interfaces.GraphModelInterface):", "funcdef": "def"}, "causy.generators.AllCombinationsGenerator.model_config": {"fullname": "causy.generators.AllCombinationsGenerator.model_config", "modulename": "causy.generators", "qualname": "AllCombinationsGenerator.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.generators.AllCombinationsGenerator.model_fields": {"fullname": "causy.generators.AllCombinationsGenerator.model_fields", "modulename": "causy.generators", "qualname": "AllCombinationsGenerator.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'comparison_settings': FieldInfo(annotation=Union[ComparisonSettingsInterface, NoneType], required=False, default=None), 'chunked': FieldInfo(annotation=Union[bool, VariableReference, NoneType], required=False, default=False), 'every_nth': FieldInfo(annotation=Union[int, VariableReference, NoneType], required=False, default=None), 'generator': FieldInfo(annotation=Union[GeneratorInterface, NoneType], required=False, default=None), 'shuffle_combinations': FieldInfo(annotation=Union[bool, VariableReference, NoneType], required=False, default=None)}"}, "causy.generators.AllCombinationsGenerator.model_computed_fields": {"fullname": "causy.generators.AllCombinationsGenerator.model_computed_fields", "modulename": "causy.generators", "qualname": "AllCombinationsGenerator.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': ComputedFieldInfo(wrapped_property=<property object>, return_type=<class 'str'>, alias=None, alias_priority=None, title=None, field_title_generator=None, description=None, deprecated=None, examples=None, json_schema_extra=None, repr=True)}"}, "causy.generators.PairsWithEdgesInBetweenGenerator": {"fullname": "causy.generators.PairsWithEdgesInBetweenGenerator", "modulename": "causy.generators", "qualname": "PairsWithEdgesInBetweenGenerator", "kind": "class", "doc": "

Generates all pairs of nodes that have edges in between them. It does not matter if the edge is directed or not.\nHowever, if it is an edge which points in both/no directions, it will be iterated over them twice.

\n", "bases": "causy.interfaces.GeneratorInterface"}, "causy.generators.PairsWithEdgesInBetweenGenerator.__init__": {"fullname": "causy.generators.PairsWithEdgesInBetweenGenerator.__init__", "modulename": "causy.generators", "qualname": "PairsWithEdgesInBetweenGenerator.__init__", "kind": "function", "doc": "

Create a new model by parsing and validating input data from keyword arguments.

\n\n

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be\nvalidated to form a valid model.

\n\n

self is explicitly positional-only to allow self as a field name.

\n", "signature": "(\t*args,\tchunk_size: Union[int, causy.variables.VariableReference, NoneType] = None,\tchunked: Union[bool, causy.variables.VariableReference, NoneType] = None,\t**kwargs)"}, "causy.generators.PairsWithEdgesInBetweenGenerator.chunk_size": {"fullname": "causy.generators.PairsWithEdgesInBetweenGenerator.chunk_size", "modulename": "causy.generators", "qualname": "PairsWithEdgesInBetweenGenerator.chunk_size", "kind": "variable", "doc": "

\n", "annotation": ": Union[int, causy.variables.VariableReference]"}, "causy.generators.PairsWithEdgesInBetweenGenerator.chunked": {"fullname": "causy.generators.PairsWithEdgesInBetweenGenerator.chunked", "modulename": "causy.generators", "qualname": "PairsWithEdgesInBetweenGenerator.chunked", "kind": "variable", "doc": "

\n", "annotation": ": Union[bool, causy.variables.VariableReference, NoneType]"}, "causy.generators.PairsWithEdgesInBetweenGenerator.generate": {"fullname": "causy.generators.PairsWithEdgesInBetweenGenerator.generate", "modulename": "causy.generators", "qualname": "PairsWithEdgesInBetweenGenerator.generate", "kind": "function", "doc": "

\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tgraph_model_instance_: causy.interfaces.GraphModelInterface):", "funcdef": "def"}, "causy.generators.PairsWithEdgesInBetweenGenerator.model_config": {"fullname": "causy.generators.PairsWithEdgesInBetweenGenerator.model_config", "modulename": "causy.generators", "qualname": "PairsWithEdgesInBetweenGenerator.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.generators.PairsWithEdgesInBetweenGenerator.model_fields": {"fullname": "causy.generators.PairsWithEdgesInBetweenGenerator.model_fields", "modulename": "causy.generators", "qualname": "PairsWithEdgesInBetweenGenerator.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'comparison_settings': FieldInfo(annotation=Union[ComparisonSettingsInterface, NoneType], required=False, default=None), 'chunked': FieldInfo(annotation=Union[bool, VariableReference, NoneType], required=False, default=None), 'every_nth': FieldInfo(annotation=Union[int, VariableReference, NoneType], required=False, default=None), 'generator': FieldInfo(annotation=Union[GeneratorInterface, NoneType], required=False, default=None), 'shuffle_combinations': FieldInfo(annotation=Union[bool, VariableReference, NoneType], required=False, default=None), 'chunk_size': FieldInfo(annotation=Union[int, VariableReference], required=False, default=100)}"}, "causy.generators.PairsWithEdgesInBetweenGenerator.model_computed_fields": {"fullname": "causy.generators.PairsWithEdgesInBetweenGenerator.model_computed_fields", "modulename": "causy.generators", "qualname": "PairsWithEdgesInBetweenGenerator.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': ComputedFieldInfo(wrapped_property=<property object>, return_type=<class 'str'>, alias=None, alias_priority=None, title=None, field_title_generator=None, description=None, deprecated=None, examples=None, json_schema_extra=None, repr=True)}"}, "causy.generators.PairsWithNeighboursGenerator": {"fullname": "causy.generators.PairsWithNeighboursGenerator", "modulename": "causy.generators", "qualname": "PairsWithNeighboursGenerator", "kind": "class", "doc": "

Generates all combinations of pairs of nodes that are neighbours and the neighbours of the first input node.\ne.g. if your graph consists of the nodes [X, Y, Z, W, V] your output could be:\n[X, Y, neighbours(X)], [Y, X, neighbours(Y)], [X, Z, neighbours(X)], [Z, X, neighbours(Z)], ...\n(if, among others, X and Y are neighbours and X and Z are neighbours)

\n", "bases": "causy.interfaces.GeneratorInterface"}, "causy.generators.PairsWithNeighboursGenerator.__init__": {"fullname": "causy.generators.PairsWithNeighboursGenerator.__init__", "modulename": "causy.generators", "qualname": "PairsWithNeighboursGenerator.__init__", "kind": "function", "doc": "

Create a new model by parsing and validating input data from keyword arguments.

\n\n

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be\nvalidated to form a valid model.

\n\n

self is explicitly positional-only to allow self as a field name.

\n", "signature": "(*args, **kwargs)"}, "causy.generators.PairsWithNeighboursGenerator.shuffle_combinations": {"fullname": "causy.generators.PairsWithNeighboursGenerator.shuffle_combinations", "modulename": "causy.generators", "qualname": "PairsWithNeighboursGenerator.shuffle_combinations", "kind": "variable", "doc": "

\n", "annotation": ": Union[bool, causy.variables.VariableReference]"}, "causy.generators.PairsWithNeighboursGenerator.chunked": {"fullname": "causy.generators.PairsWithNeighboursGenerator.chunked", "modulename": "causy.generators", "qualname": "PairsWithNeighboursGenerator.chunked", "kind": "variable", "doc": "

\n", "annotation": ": Union[bool, causy.variables.VariableReference]"}, "causy.generators.PairsWithNeighboursGenerator.generate": {"fullname": "causy.generators.PairsWithNeighboursGenerator.generate", "modulename": "causy.generators", "qualname": "PairsWithNeighboursGenerator.generate", "kind": "function", "doc": "

\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tgraph_model_instance_: causy.interfaces.GraphModelInterface):", "funcdef": "def"}, "causy.generators.PairsWithNeighboursGenerator.model_config": {"fullname": "causy.generators.PairsWithNeighboursGenerator.model_config", "modulename": "causy.generators", "qualname": "PairsWithNeighboursGenerator.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.generators.PairsWithNeighboursGenerator.model_fields": {"fullname": "causy.generators.PairsWithNeighboursGenerator.model_fields", "modulename": "causy.generators", "qualname": "PairsWithNeighboursGenerator.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'comparison_settings': FieldInfo(annotation=Union[ComparisonSettingsInterface, NoneType], required=False, default=None), 'chunked': FieldInfo(annotation=Union[bool, VariableReference], required=False, default=True), 'every_nth': FieldInfo(annotation=Union[int, VariableReference, NoneType], required=False, default=None), 'generator': FieldInfo(annotation=Union[GeneratorInterface, NoneType], required=False, default=None), 'shuffle_combinations': FieldInfo(annotation=Union[bool, VariableReference], required=False, default=True)}"}, "causy.generators.PairsWithNeighboursGenerator.model_computed_fields": {"fullname": "causy.generators.PairsWithNeighboursGenerator.model_computed_fields", "modulename": "causy.generators", "qualname": "PairsWithNeighboursGenerator.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': ComputedFieldInfo(wrapped_property=<property object>, return_type=<class 'str'>, alias=None, alias_priority=None, title=None, field_title_generator=None, description=None, deprecated=None, examples=None, json_schema_extra=None, repr=True)}"}, "causy.generators.RandomSampleGenerator": {"fullname": "causy.generators.RandomSampleGenerator", "modulename": "causy.generators", "qualname": "RandomSampleGenerator", "kind": "class", "doc": "

Executes another generator and returns a random sample of the results

\n", "bases": "causy.interfaces.GeneratorInterface, pydantic.main.BaseModel"}, "causy.generators.RandomSampleGenerator.__init__": {"fullname": "causy.generators.RandomSampleGenerator.__init__", "modulename": "causy.generators", "qualname": "RandomSampleGenerator.__init__", "kind": "function", "doc": "

Create a new model by parsing and validating input data from keyword arguments.

\n\n

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be\nvalidated to form a valid model.

\n\n

self is explicitly positional-only to allow self as a field name.

\n", "signature": "(\t*args,\tgenerator: Union[causy.interfaces.GeneratorInterface, Dict[<built-in function any>, <built-in function any>], NoneType] = None,\t**kwargs)"}, "causy.generators.RandomSampleGenerator.every_nth": {"fullname": "causy.generators.RandomSampleGenerator.every_nth", "modulename": "causy.generators", "qualname": "RandomSampleGenerator.every_nth", "kind": "variable", "doc": "

\n", "annotation": ": Union[int, causy.variables.VariableReference]"}, "causy.generators.RandomSampleGenerator.generator": {"fullname": "causy.generators.RandomSampleGenerator.generator", "modulename": "causy.generators", "qualname": "RandomSampleGenerator.generator", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.interfaces.GeneratorInterface]"}, "causy.generators.RandomSampleGenerator.generate": {"fullname": "causy.generators.RandomSampleGenerator.generate", "modulename": "causy.generators", "qualname": "RandomSampleGenerator.generate", "kind": "function", "doc": "

Executes another generator and returns a random sample of the results

\n\n
Parameters
\n\n
    \n
  • graph:
    • \n
  • graph_model_instance_:
    • \n
\n\n
Returns
\n\n
\n

yields a random sample of the results

\n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tgraph_model_instance_: dict):", "funcdef": "def"}, "causy.generators.RandomSampleGenerator.model_config": {"fullname": "causy.generators.RandomSampleGenerator.model_config", "modulename": "causy.generators", "qualname": "RandomSampleGenerator.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.generators.RandomSampleGenerator.model_fields": {"fullname": "causy.generators.RandomSampleGenerator.model_fields", "modulename": "causy.generators", "qualname": "RandomSampleGenerator.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'comparison_settings': FieldInfo(annotation=Union[ComparisonSettingsInterface, NoneType], required=False, default=None), 'chunked': FieldInfo(annotation=Union[bool, VariableReference, NoneType], required=False, default=False), 'every_nth': FieldInfo(annotation=Union[int, VariableReference], required=False, default=100), 'generator': FieldInfo(annotation=Union[GeneratorInterface, NoneType], required=False, default=None), 'shuffle_combinations': FieldInfo(annotation=Union[bool, VariableReference, NoneType], required=False, default=None)}"}, "causy.generators.RandomSampleGenerator.model_computed_fields": {"fullname": "causy.generators.RandomSampleGenerator.model_computed_fields", "modulename": "causy.generators", "qualname": "RandomSampleGenerator.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': ComputedFieldInfo(wrapped_property=<property object>, return_type=<class 'str'>, alias=None, alias_priority=None, title=None, field_title_generator=None, description=None, deprecated=None, examples=None, json_schema_extra=None, repr=True)}"}, "causy.graph": {"fullname": "causy.graph", "modulename": "causy.graph", "kind": "module", "doc": "

\n"}, "causy.graph.logger": {"fullname": "causy.graph.logger", "modulename": "causy.graph", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.graph (WARNING)>"}, "causy.graph.Node": {"fullname": "causy.graph.Node", "modulename": "causy.graph", "qualname": "Node", "kind": "class", "doc": "

A node is a variable in the graph. It has a name, an id and values. The values are stored as a torch.Tensor.\nA node can also have metadata.

\n", "bases": "causy.interfaces.NodeInterface"}, "causy.graph.Node.name": {"fullname": "causy.graph.Node.name", "modulename": "causy.graph", "qualname": "Node.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.graph.Node.id": {"fullname": "causy.graph.Node.id", "modulename": "causy.graph", "qualname": "Node.id", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.graph.Node.values": {"fullname": "causy.graph.Node.values", "modulename": "causy.graph", "qualname": "Node.values", "kind": "variable", "doc": "

\n", "annotation": ": Optional[torch.Tensor]"}, "causy.graph.Node.metadata": {"fullname": "causy.graph.Node.metadata", "modulename": "causy.graph", "qualname": "Node.metadata", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict[str, Union[str, int, float, bool, List[Union[str, int, float, bool]], Dict[str, Union[str, int, float, bool]]]]]"}, "causy.graph.Node.model_config": {"fullname": "causy.graph.Node.model_config", "modulename": "causy.graph", "qualname": "Node.model_config", "kind": "variable", "doc": "

\n", "default_value": "{'arbitrary_types_allowed': True}"}, "causy.graph.Node.model_fields": {"fullname": "causy.graph.Node.model_fields", "modulename": "causy.graph", "qualname": "Node.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': FieldInfo(annotation=str, required=True), 'id': FieldInfo(annotation=str, required=True), 'values': FieldInfo(annotation=Union[Tensor, NoneType], required=False, default=None), 'metadata': FieldInfo(annotation=Union[Dict[str, Union[str, int, float, bool, List[Union[str, int, float, bool]], Dict[str, Union[str, int, float, bool]]]], NoneType], required=False, default=None)}"}, "causy.graph.Node.model_computed_fields": {"fullname": "causy.graph.Node.model_computed_fields", "modulename": "causy.graph", "qualname": "Node.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.graph.Edge": {"fullname": "causy.graph.Edge", "modulename": "causy.graph", "qualname": "Edge", "kind": "class", "doc": "

An edge is a connection between two nodes. It has a direction defined by the edge_type and metadata.\nA metadata example could be the p-value of a statistical test.\nAn edge can be e.g. undirected, directed or bidirected. Which option is available/chosen depends on the algorithm and the current state of the graph.\nBy default an edge always has an undirected and a directed edge_type.

\n", "bases": "causy.interfaces.EdgeInterface"}, "causy.graph.Edge.__init__": {"fullname": "causy.graph.Edge.__init__", "modulename": "causy.graph", "qualname": "Edge.__init__", "kind": "function", "doc": "

Create a new model by parsing and validating input data from keyword arguments.

\n\n

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be\nvalidated to form a valid model.

\n\n

self is explicitly positional-only to allow self as a field name.

\n", "signature": "(*args, **kwargs)"}, "causy.graph.Edge.u": {"fullname": "causy.graph.Edge.u", "modulename": "causy.graph", "qualname": "Edge.u", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.NodeInterface"}, "causy.graph.Edge.v": {"fullname": "causy.graph.Edge.v", "modulename": "causy.graph", "qualname": "Edge.v", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.NodeInterface"}, "causy.graph.Edge.edge_type": {"fullname": "causy.graph.Edge.edge_type", "modulename": "causy.graph", "qualname": "Edge.edge_type", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.EdgeTypeInterface"}, "causy.graph.Edge.metadata": {"fullname": "causy.graph.Edge.metadata", "modulename": "causy.graph", "qualname": "Edge.metadata", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict[str, Union[str, int, float, bool, List[Union[str, int, float, bool]], Dict[str, Union[str, int, float, bool]]]]]"}, "causy.graph.Edge.deleted": {"fullname": "causy.graph.Edge.deleted", "modulename": "causy.graph", "qualname": "Edge.deleted", "kind": "variable", "doc": "

\n", "annotation": ": Optional[bool]"}, "causy.graph.Edge.model_config": {"fullname": "causy.graph.Edge.model_config", "modulename": "causy.graph", "qualname": "Edge.model_config", "kind": "variable", "doc": "

\n", "default_value": "{'arbitrary_types_allowed': True}"}, "causy.graph.Edge.model_fields": {"fullname": "causy.graph.Edge.model_fields", "modulename": "causy.graph", "qualname": "Edge.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'u': FieldInfo(annotation=NodeInterface, required=True), 'v': FieldInfo(annotation=NodeInterface, required=True), 'edge_type': FieldInfo(annotation=EdgeTypeInterface, required=True), 'metadata': FieldInfo(annotation=Union[Dict[str, Union[str, int, float, bool, List[Union[str, int, float, bool]], Dict[str, Union[str, int, float, bool]]]], NoneType], required=False, default=None), 'deleted': FieldInfo(annotation=Union[bool, NoneType], required=False, default=False)}"}, "causy.graph.Edge.model_computed_fields": {"fullname": "causy.graph.Edge.model_computed_fields", "modulename": "causy.graph", "qualname": "Edge.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.graph.GraphError": {"fullname": "causy.graph.GraphError", "modulename": "causy.graph", "qualname": "GraphError", "kind": "class", "doc": "

Common base class for all non-exit exceptions.

\n", "bases": "builtins.Exception"}, "causy.graph.GraphBaseAccessMixin": {"fullname": "causy.graph.GraphBaseAccessMixin", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin", "kind": "class", "doc": "

\n"}, "causy.graph.GraphBaseAccessMixin.directed_edge_is_soft_deleted": {"fullname": "causy.graph.GraphBaseAccessMixin.directed_edge_is_soft_deleted", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.directed_edge_is_soft_deleted", "kind": "function", "doc": "

Check if an edge is soft deleted

\n\n
Parameters
\n\n
    \n
  • u:
    • \n
  • v:
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str]) -> bool:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.parents_of_node": {"fullname": "causy.graph.GraphBaseAccessMixin.parents_of_node", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.parents_of_node", "kind": "function", "doc": "

Return all parents of a node u

\n\n
Parameters
\n\n
    \n
  • u: node u
    • \n
\n\n
Returns
\n\n
\n

list of nodes (parents)

\n
\n", "signature": "(self, u: Union[causy.graph.Node, str]):", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.edge_exists": {"fullname": "causy.graph.GraphBaseAccessMixin.edge_exists", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.edge_exists", "kind": "function", "doc": "

Check if any edge exists between u and v. Cases: u -> v, u <-> v, u <- v

\n\n
Parameters
\n\n
    \n
  • u: node u
    • \n
  • v: node v
    • \n
\n\n
Returns
\n\n
\n

True if any edge exists, False otherwise

\n
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str]) -> bool:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.directed_edge_exists": {"fullname": "causy.graph.GraphBaseAccessMixin.directed_edge_exists", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.directed_edge_exists", "kind": "function", "doc": "

Check if a directed edge exists between u and v. Cases: u -> v, u <-> v

\n\n
Parameters
\n\n
    \n
  • u: node u
    • \n
  • v: node v
    • \n
\n\n
Returns
\n\n
\n

True if a directed edge exists, False otherwise

\n
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str]) -> bool:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.node_by_id": {"fullname": "causy.graph.GraphBaseAccessMixin.node_by_id", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.node_by_id", "kind": "function", "doc": "

Retrieve a node by its id

\n\n
Parameters
\n\n
    \n
  • id_:
    • \n
\n\n
Returns
\n", "signature": "(self, id_: str) -> Optional[causy.graph.Node]:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.edge_value": {"fullname": "causy.graph.GraphBaseAccessMixin.edge_value", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.edge_value", "kind": "function", "doc": "

retrieve the value of an edge

\n\n
Parameters
\n\n
    \n
  • u:
    • \n
  • v:
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str]) -> Optional[Dict]:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.edge_type": {"fullname": "causy.graph.GraphBaseAccessMixin.edge_type", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.edge_type", "kind": "function", "doc": "

retrieve the value of an edge

\n\n
Parameters
\n\n
    \n
  • u:
    • \n
  • v:
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str]) -> Optional[causy.interfaces.EdgeTypeInterface]:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.undirected_edge_exists": {"fullname": "causy.graph.GraphBaseAccessMixin.undirected_edge_exists", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.undirected_edge_exists", "kind": "function", "doc": "

Check if an undirected edge exists between u and v. Note: currently, an undirected edges is implemented just as\na directed edge. However, they are two functions as they mean different things in different algorithms.\nCurrently, this function is used in the PC algorithm, where an undirected edge is an edge which could not be\noriented in any direction by orientation rules.\nLater, a cohersive naming scheme should be implemented.

\n\n
Parameters
\n\n
    \n
  • u: node u
    • \n
  • v: node v
    • \n
\n\n
Returns
\n\n
\n

True if an undirected edge exists, False otherwise

\n
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str]) -> bool:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.get_siblings": {"fullname": "causy.graph.GraphBaseAccessMixin.get_siblings", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.get_siblings", "kind": "function", "doc": "

Get the set of nodes that are connected to the node v with an undirected edge.

\n\n
Parameters
\n\n
    \n
  • v: node v
    • \n
\n\n
Returns
\n\n
\n

A set of nodes that are connected to v with an undirected edge.

\n
\n", "signature": "(\tself,\tv: Union[causy.graph.Node, str]) -> Set[Union[causy.graph.Node, str]]:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.retrieve_edge_history": {"fullname": "causy.graph.GraphBaseAccessMixin.retrieve_edge_history", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.retrieve_edge_history", "kind": "function", "doc": "

Retrieve the edge history

\n\n
Parameters
\n\n
    \n
  • u:
    • \n
  • v:
    • \n
  • action:
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str],\taction: causy.models.TestResultAction = None) -> List[causy.models.TestResult]:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.directed_path_exists": {"fullname": "causy.graph.GraphBaseAccessMixin.directed_path_exists", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.directed_path_exists", "kind": "function", "doc": "

Check if a directed path from u to v exists

\n\n
Parameters
\n\n
    \n
  • u: node u
    • \n
  • v: node v
    • \n
\n\n
Returns
\n\n
\n

True if a directed path exists, False otherwise

\n
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str]) -> bool:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.edge_of_type_exists": {"fullname": "causy.graph.GraphBaseAccessMixin.edge_of_type_exists", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.edge_of_type_exists", "kind": "function", "doc": "

Check if an edge of a specific type exists between u and v.

\n\n
Parameters
\n\n
    \n
  • u: node u
    • \n
  • v: node v
    • \n
  • edge_type: the type of the edge to check for
    • \n
\n\n
Returns
\n\n
\n

True if an edge of this type exists, False otherwise

\n
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str],\tedge_type: causy.interfaces.EdgeTypeInterface = DIRECTED) -> bool:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.descendants_of_node": {"fullname": "causy.graph.GraphBaseAccessMixin.descendants_of_node", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.descendants_of_node", "kind": "function", "doc": "

Returns a list of all descendants of the given node in a directed graph, including the input node itself.

\n\n
Parameters
\n\n
    \n
  • u: The node or node ID to find descendants for.
    • \n
\n\n
Returns
\n\n
\n

A list of descendants of a node including the input node itself.

\n
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tvisited=None) -> List[Union[causy.graph.Node, str]]:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.are_nodes_d_separated_dag": {"fullname": "causy.graph.GraphBaseAccessMixin.are_nodes_d_separated_dag", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.are_nodes_d_separated_dag", "kind": "function", "doc": "

Check if nodes u and v are d-separated given a conditioning set in a DAG. We check whether there is an open path, i.e. a path on which all colliders are in the conditioning set and all non-colliders are not in the conditioning set. If there is no open path, u and v are d-separated.

\n\n
Parameters
\n\n
    \n
  • u: First node
    • \n
  • v: Second node
    • \n
  • conditioning_set: Set of nodes to condition on
    • \n
\n\n
Returns
\n\n
\n

True if u and v are d-separated given conditioning_set, False otherwise

\n
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str],\tconditioning_set: List[Union[causy.graph.Node, str]]) -> bool:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.are_nodes_d_separated_cpdag": {"fullname": "causy.graph.GraphBaseAccessMixin.are_nodes_d_separated_cpdag", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.are_nodes_d_separated_cpdag", "kind": "function", "doc": "

Check if nodes u and v are d-separated given a conditioning set in a CPDAG following Perkovic, 2020. (Identifying causal effects in maximally oriented partially directed acyclic graphs)

\n\n
Parameters
\n\n
    \n
  • u: First node
    • \n
  • v: Second node
    • \n
  • conditioning_set: Set of nodes to condition on
    • \n
\n\n
Returns
\n\n
\n

True if u and v are d-separated given conditioning_set, False otherwise

\n
\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str],\tconditioning_set: List[Union[causy.graph.Node, str]]) -> bool:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.all_paths_on_underlying_undirected_graph": {"fullname": "causy.graph.GraphBaseAccessMixin.all_paths_on_underlying_undirected_graph", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.all_paths_on_underlying_undirected_graph", "kind": "function", "doc": "

\n", "signature": "(\tself,\tu: Union[causy.graph.Node, str],\tv: Union[causy.graph.Node, str],\tvisited=None,\tpath=None) -> List[List[causy.graph.Node]]:", "funcdef": "def"}, "causy.graph.GraphBaseAccessMixin.retrieve_edges": {"fullname": "causy.graph.GraphBaseAccessMixin.retrieve_edges", "modulename": "causy.graph", "qualname": "GraphBaseAccessMixin.retrieve_edges", "kind": "function", "doc": "

Retrieve all edges

\n\n
Returns
\n\n
\n

all edges

\n
\n", "signature": "(self) -> List[causy.graph.Edge]:", "funcdef": "def"}, "causy.graph.Graph": {"fullname": "causy.graph.Graph", "modulename": "causy.graph", "qualname": "Graph", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "causy.interfaces.ExtensionInterface.GraphAccessMixin, causy.edge_types.DirectedEdge.GraphAccessMixin, GraphBaseAccessMixin, causy.interfaces.EdgeTypeInterface.GraphAccessMixin, pydantic.main.BaseModel"}, "causy.graph.Graph.nodes": {"fullname": "causy.graph.Graph.nodes", "modulename": "causy.graph", "qualname": "Graph.nodes", "kind": "variable", "doc": "

\n", "annotation": ": OrderedDict[str, causy.graph.Node]"}, "causy.graph.Graph.edges": {"fullname": "causy.graph.Graph.edges", "modulename": "causy.graph", "qualname": "Graph.edges", "kind": "variable", "doc": "

\n", "annotation": ": Dict[str, Dict[str, causy.graph.Edge]]"}, "causy.graph.Graph.edge_history": {"fullname": "causy.graph.Graph.edge_history", "modulename": "causy.graph", "qualname": "Graph.edge_history", "kind": "variable", "doc": "

\n", "annotation": ": Dict[Tuple[str, str], List[causy.models.TestResult]]"}, "causy.graph.Graph.action_history": {"fullname": "causy.graph.Graph.action_history", "modulename": "causy.graph", "qualname": "Graph.action_history", "kind": "variable", "doc": "

\n", "annotation": ": List[causy.models.ActionHistoryStep]"}, "causy.graph.Graph.model_config": {"fullname": "causy.graph.Graph.model_config", "modulename": "causy.graph", "qualname": "Graph.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.graph.Graph.model_post_init": {"fullname": "causy.graph.Graph.model_post_init", "modulename": "causy.graph", "qualname": "Graph.model_post_init", "kind": "function", "doc": "

This function is meant to behave like a BaseModel method to initialise private attributes.

\n\n

It takes context as an argument since that's what pydantic-core passes when calling it.

\n\n

Args:\n self: The BaseModel instance.\n context: The context.

\n", "signature": "(self: pydantic.main.BaseModel, context: Any, /) -> None:", "funcdef": "def"}, "causy.graph.Graph.model_fields": {"fullname": "causy.graph.Graph.model_fields", "modulename": "causy.graph", "qualname": "Graph.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'nodes': FieldInfo(annotation=OrderedDict[str, Node], required=False, default=OrderedDict()), 'edges': FieldInfo(annotation=Dict[str, Dict[str, Edge]], required=False, default={}), 'edge_history': FieldInfo(annotation=Dict[Tuple[str, str], List[TestResult]], required=False, default={}), 'action_history': FieldInfo(annotation=List[ActionHistoryStep], required=False, default=[])}"}, "causy.graph.Graph.model_computed_fields": {"fullname": "causy.graph.Graph.model_computed_fields", "modulename": "causy.graph", "qualname": "Graph.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.graph.GraphManager": {"fullname": "causy.graph.GraphManager", "modulename": "causy.graph", "qualname": "GraphManager", "kind": "class", "doc": "

The graph represents the internal data structure of causy. It is a simple graph with nodes and edges.\nBut it supports to be handled as a directed graph, undirected graph and bidirected graph, which is important to implement different algorithms in different stages.\nIt also stores the history of the actions taken on the graph.

\n", "bases": "GraphBaseAccessMixin, causy.interfaces.BaseGraphInterface"}, "causy.graph.GraphManager.__init__": {"fullname": "causy.graph.GraphManager.__init__", "modulename": "causy.graph", "qualname": "GraphManager.__init__", "kind": "function", "doc": "

\n", "signature": "(graph_class=<class 'causy.graph.Graph'>)"}, "causy.graph.GraphManager.nodes": {"fullname": "causy.graph.GraphManager.nodes", "modulename": "causy.graph", "qualname": "GraphManager.nodes", "kind": "variable", "doc": "

\n", "annotation": ": OrderedDict[str, causy.graph.Node]"}, "causy.graph.GraphManager.edges": {"fullname": "causy.graph.GraphManager.edges", "modulename": "causy.graph", "qualname": "GraphManager.edges", "kind": "variable", "doc": "

\n", "annotation": ": Dict[str, Dict[str, causy.graph.Edge]]"}, "causy.graph.GraphManager.edge_history": {"fullname": "causy.graph.GraphManager.edge_history", "modulename": "causy.graph", "qualname": "GraphManager.edge_history", "kind": "variable", "doc": "

\n", "annotation": ": Dict[Tuple[str, str], List[causy.models.TestResult]]"}, "causy.graph.GraphManager.action_history": {"fullname": "causy.graph.GraphManager.action_history", "modulename": "causy.graph", "qualname": "GraphManager.action_history", "kind": "variable", "doc": "

\n", "annotation": ": List[Dict[str, List[causy.models.TestResult]]]"}, "causy.graph.GraphManager.graph": {"fullname": "causy.graph.GraphManager.graph", "modulename": "causy.graph", "qualname": "GraphManager.graph", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.graph.Graph]", "default_value": "None"}, "causy.graph.GraphManager.get_edge": {"fullname": "causy.graph.GraphManager.get_edge", "modulename": "causy.graph", "qualname": "GraphManager.get_edge", "kind": "function", "doc": "

Get an edge between two nodes

\n\n
Parameters
\n\n
    \n
  • u: u node
    • \n
  • v: v node
    • \n
\n\n
Returns
\n\n
\n

the edge

\n
\n", "signature": "(self, u: causy.graph.Node, v: causy.graph.Node) -> causy.graph.Edge:", "funcdef": "def"}, "causy.graph.GraphManager.add_edge": {"fullname": "causy.graph.GraphManager.add_edge", "modulename": "causy.graph", "qualname": "GraphManager.add_edge", "kind": "function", "doc": "

Add an edge to the graph

\n\n
Parameters
\n\n
    \n
  • edge_type: the type of the edge (e.g. undirected, directed, bidirected)
    • \n
  • u: u node
    • \n
  • v: v node
    • \n
  • metadata: metadata of the edge
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tu: causy.graph.Node,\tv: causy.graph.Node,\tmetadata: Dict,\tedge_type: causy.interfaces.EdgeTypeInterface = UNDIRECTED):", "funcdef": "def"}, "causy.graph.GraphManager.add_directed_edge": {"fullname": "causy.graph.GraphManager.add_directed_edge", "modulename": "causy.graph", "qualname": "GraphManager.add_directed_edge", "kind": "function", "doc": "

Add a directed edge from u to v to the graph

\n\n
Parameters
\n\n
    \n
  • edge_type:
    • \n
  • u: u node
    • \n
  • v: v node
    • \n
  • metadata: metadata of the edge
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tu: causy.graph.Node,\tv: causy.graph.Node,\tmetadata: Dict,\tedge_type: causy.interfaces.EdgeTypeInterface = DIRECTED):", "funcdef": "def"}, "causy.graph.GraphManager.add_edge_history": {"fullname": "causy.graph.GraphManager.add_edge_history", "modulename": "causy.graph", "qualname": "GraphManager.add_edge_history", "kind": "function", "doc": "

Add an action to the edge history

\n\n
Parameters
\n\n
    \n
  • u:
    • \n
  • v:
    • \n
  • action:
    • \n
\n\n
Returns
\n", "signature": "(self, u, v, action: causy.models.TestResult):", "funcdef": "def"}, "causy.graph.GraphManager.remove_edge": {"fullname": "causy.graph.GraphManager.remove_edge", "modulename": "causy.graph", "qualname": "GraphManager.remove_edge", "kind": "function", "doc": "

Remove an edge from the graph (undirected)

\n\n
Parameters
\n\n
    \n
  • u: u node
    • \n
  • v: v node
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tu: causy.graph.Node,\tv: causy.graph.Node,\tsoft_delete: bool = False):", "funcdef": "def"}, "causy.graph.GraphManager.restore_edge": {"fullname": "causy.graph.GraphManager.restore_edge", "modulename": "causy.graph", "qualname": "GraphManager.restore_edge", "kind": "function", "doc": "

Restore a deleted edge

\n\n
Parameters
\n\n
    \n
  • u:
    • \n
  • v:
    • \n
\n\n
Returns
\n", "signature": "(self, u: causy.graph.Node, v: causy.graph.Node):", "funcdef": "def"}, "causy.graph.GraphManager.remove_directed_edge": {"fullname": "causy.graph.GraphManager.remove_directed_edge", "modulename": "causy.graph", "qualname": "GraphManager.remove_directed_edge", "kind": "function", "doc": "
Parameters
\n\n
    \n
  • u:
    • \n
  • v:
    • \n
  • soft_delete: does not remove the edge, but marks it as deleted (useful in multithreading)
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tu: causy.graph.Node,\tv: causy.graph.Node,\tsoft_delete: bool = False):", "funcdef": "def"}, "causy.graph.GraphManager.restore_directed_edge": {"fullname": "causy.graph.GraphManager.restore_directed_edge", "modulename": "causy.graph", "qualname": "GraphManager.restore_directed_edge", "kind": "function", "doc": "

Restore a soft deleted edge

\n\n
Parameters
\n\n
    \n
  • u:
    • \n
  • v:
    • \n
\n\n
Returns
\n", "signature": "(self, u: causy.graph.Node, v: causy.graph.Node):", "funcdef": "def"}, "causy.graph.GraphManager.update_edge": {"fullname": "causy.graph.GraphManager.update_edge", "modulename": "causy.graph", "qualname": "GraphManager.update_edge", "kind": "function", "doc": "

Update an undirected edge in the graph

\n\n
Parameters
\n\n
    \n
  • u: u node
    • \n
  • v: v node
    • \n
  • value:
    • \n
  • edge_type:
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tu: causy.graph.Node,\tv: causy.graph.Node,\tmetadata: Dict = None,\tedge_type: causy.interfaces.EdgeTypeInterface = None):", "funcdef": "def"}, "causy.graph.GraphManager.update_directed_edge": {"fullname": "causy.graph.GraphManager.update_directed_edge", "modulename": "causy.graph", "qualname": "GraphManager.update_directed_edge", "kind": "function", "doc": "

Update an edge in the graph

\n\n
Parameters
\n\n
    \n
  • u: u node
    • \n
  • v: v node
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tu: causy.graph.Node,\tv: causy.graph.Node,\tmetadata: Dict = None,\tedge_type: causy.interfaces.EdgeTypeInterface = None):", "funcdef": "def"}, "causy.graph.GraphManager.purge_soft_deleted_edges": {"fullname": "causy.graph.GraphManager.purge_soft_deleted_edges", "modulename": "causy.graph", "qualname": "GraphManager.purge_soft_deleted_edges", "kind": "function", "doc": "

Remove all edges that are marked as soft deleted from the graph

\n", "signature": "(self):", "funcdef": "def"}, "causy.graph.GraphManager.add_node": {"fullname": "causy.graph.GraphManager.add_node", "modulename": "causy.graph", "qualname": "GraphManager.add_node", "kind": "function", "doc": "

Add a node to the graph

\n\n
Parameters
\n\n
    \n
  • metadata: add metadata to the node
    • \n
  • name: name of the node
    • \n
  • values: values of the node
    • \n
  • id_: id_ of the node\n:param : node
    • \n
\n\n
Returns
\n\n
\n

created Node

\n
\n", "signature": "(\tself,\tname: str,\tvalues: Union[List[float], torch.Tensor],\tid_: str = None,\tmetadata: Optional[Dict[str, Any]] = None) -> causy.graph.Node:", "funcdef": "def"}, "causy.graph_model": {"fullname": "causy.graph_model", "modulename": "causy.graph_model", "kind": "module", "doc": "

\n"}, "causy.graph_model.logger": {"fullname": "causy.graph_model.logger", "modulename": "causy.graph_model", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.graph_model (WARNING)>"}, "causy.graph_model.AbstractGraphModel": {"fullname": "causy.graph_model.AbstractGraphModel", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel", "kind": "class", "doc": "

The graph model is the main class of causy. It is responsible for creating a graph from data and executing the pipeline_steps.

\n\n

The graph model is responsible for the following tasks:

\n\n
    \n
  • Create a graph from data (create_graph_from_data)
    • \n
  • Execute the pipeline_steps (execute_pipeline_steps)
    • \n
  • Take actions on the graph (execute_pipeline_step & _take_action which is called by execute_pipeline_step)
    • \n
\n\n

It also initializes and takes care of the multiprocessing pool.

\n", "bases": "causy.interfaces.GraphModelInterface, abc.ABC"}, "causy.graph_model.AbstractGraphModel.__init__": {"fullname": "causy.graph_model.AbstractGraphModel.__init__", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel.__init__", "kind": "function", "doc": "

\n", "signature": "(graph=None, algorithm: causy.models.Algorithm = None)"}, "causy.graph_model.AbstractGraphModel.algorithm": {"fullname": "causy.graph_model.AbstractGraphModel.algorithm", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel.algorithm", "kind": "variable", "doc": "

\n", "annotation": ": causy.models.Algorithm"}, "causy.graph_model.AbstractGraphModel.pipeline_steps": {"fullname": "causy.graph_model.AbstractGraphModel.pipeline_steps", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel.pipeline_steps", "kind": "variable", "doc": "

\n", "annotation": ": List[causy.interfaces.PipelineStepInterface]"}, "causy.graph_model.AbstractGraphModel.graph": {"fullname": "causy.graph_model.AbstractGraphModel.graph", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel.graph", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.BaseGraphInterface"}, "causy.graph_model.AbstractGraphModel.pool": {"fullname": "causy.graph_model.AbstractGraphModel.pool", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel.pool", "kind": "variable", "doc": "

\n", "annotation": ": <bound method BaseContext.Pool of <multiprocessing.context.DefaultContext object at 0x7f4ad89b9460>>"}, "causy.graph_model.AbstractGraphModel.create_graph_from_data": {"fullname": "causy.graph_model.AbstractGraphModel.create_graph_from_data", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel.create_graph_from_data", "kind": "function", "doc": "

Create a graph from data

\n\n
Parameters
\n\n
    \n
  • data: is a list of dictionaries or a dictionary with lists
    • \n
\n\n
Returns
\n", "signature": "(\tself,\tdata: Union[List[Dict[str, float]], Dict[str, List[float]], causy.data_loader.AbstractDataLoader]):", "funcdef": "def"}, "causy.graph_model.AbstractGraphModel.create_all_possible_edges": {"fullname": "causy.graph_model.AbstractGraphModel.create_all_possible_edges", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel.create_all_possible_edges", "kind": "function", "doc": "

Create all possible edges on a graph\nTODO: replace me with the skeleton builders

\n\n
Returns
\n", "signature": "(self):", "funcdef": "def"}, "causy.graph_model.AbstractGraphModel.execute_pipeline_steps": {"fullname": "causy.graph_model.AbstractGraphModel.execute_pipeline_steps", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel.execute_pipeline_steps", "kind": "function", "doc": "

Execute all pipeline_steps

\n\n
Returns
\n\n
\n

the steps taken during the step execution

\n
\n", "signature": "(self) -> List[causy.models.ActionHistoryStep]:", "funcdef": "def"}, "causy.graph_model.AbstractGraphModel.execute_pipeline_step_with_progress": {"fullname": "causy.graph_model.AbstractGraphModel.execute_pipeline_step_with_progress", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel.execute_pipeline_step_with_progress", "kind": "function", "doc": "

\n", "signature": "(self) -> Generator:", "funcdef": "def"}, "causy.graph_model.AbstractGraphModel.execute_pipeline_step": {"fullname": "causy.graph_model.AbstractGraphModel.execute_pipeline_step", "modulename": "causy.graph_model", "qualname": "AbstractGraphModel.execute_pipeline_step", "kind": "function", "doc": "

Execute a single pipeline_step on the graph. either in parallel or in a single process depending on the test_fn.parallel flag

\n\n
Parameters
\n\n
    \n
  • apply_to_graph: if the action should be applied to the graph
    • \n
  • test_fn: the test function
    • \n
  • threshold: the threshold
    • \n
\n\n
Returns
\n", "signature": "(\tself,\ttest_fn: causy.interfaces.PipelineStepInterface,\tapply_to_graph=True) -> Tuple[List[causy.models.TestResultAction], List[causy.models.TestResultAction]]:", "funcdef": "def"}, "causy.graph_model.graph_model_factory": {"fullname": "causy.graph_model.graph_model_factory", "modulename": "causy.graph_model", "qualname": "graph_model_factory", "kind": "function", "doc": "

Create a graph model based on a List of pipeline_steps

\n\n
Parameters
\n\n
    \n
  • algorithm: the algorithm which should be used to create the graph model
    • \n
\n\n
Returns
\n\n
\n

the graph model

\n
\n", "signature": "(\talgorithm: causy.models.Algorithm = None,\tvariables: Dict[str, causy.variables.VariableTypes] = None) -> type[causy.graph_model.AbstractGraphModel]:", "funcdef": "def"}, "causy.graph_utils": {"fullname": "causy.graph_utils", "modulename": "causy.graph_utils", "kind": "module", "doc": "

\n"}, "causy.graph_utils.unpack_run": {"fullname": "causy.graph_utils.unpack_run", "modulename": "causy.graph_utils", "qualname": "unpack_run", "kind": "function", "doc": "

\n", "signature": "(args):", "funcdef": "def"}, "causy.graph_utils.serialize_module_name": {"fullname": "causy.graph_utils.serialize_module_name", "modulename": "causy.graph_utils", "qualname": "serialize_module_name", "kind": "function", "doc": "

\n", "signature": "(cls):", "funcdef": "def"}, "causy.graph_utils.load_pipeline_artefact_by_definition": {"fullname": "causy.graph_utils.load_pipeline_artefact_by_definition", "modulename": "causy.graph_utils", "qualname": "load_pipeline_artefact_by_definition", "kind": "function", "doc": "

\n", "signature": "(step):", "funcdef": "def"}, "causy.graph_utils.load_pipeline_steps_by_definition": {"fullname": "causy.graph_utils.load_pipeline_steps_by_definition", "modulename": "causy.graph_utils", "qualname": "load_pipeline_steps_by_definition", "kind": "function", "doc": "

\n", "signature": "(steps):", "funcdef": "def"}, "causy.graph_utils.retrieve_edges": {"fullname": "causy.graph_utils.retrieve_edges", "modulename": "causy.graph_utils", "qualname": "retrieve_edges", "kind": "function", "doc": "

Returns a list of edges from the graph

\n\n
Parameters
\n\n
    \n
  • graph: a graph
    • \n
\n\n
Returns
\n\n
\n

a list of edges

\n
\n", "signature": "(graph) -> List[Tuple[str, str]]:", "funcdef": "def"}, "causy.graph_utils.hash_dictionary": {"fullname": "causy.graph_utils.hash_dictionary", "modulename": "causy.graph_utils", "qualname": "hash_dictionary", "kind": "function", "doc": "

Hash a dictionary using SHA256 (e.g. for caching)

\n\n
Parameters
\n\n
    \n
  • dct:
    • \n
\n\n
Returns
\n", "signature": "(dct: Dict):", "funcdef": "def"}, "causy.interfaces": {"fullname": "causy.interfaces", "modulename": "causy.interfaces", "kind": "module", "doc": "

\n"}, "causy.interfaces.logger": {"fullname": "causy.interfaces.logger", "modulename": "causy.interfaces", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.interfaces (WARNING)>"}, "causy.interfaces.DEFAULT_THRESHOLD": {"fullname": "causy.interfaces.DEFAULT_THRESHOLD", "modulename": "causy.interfaces", "qualname": "DEFAULT_THRESHOLD", "kind": "variable", "doc": "

\n", "default_value": "0.01"}, "causy.interfaces.AS_MANY_AS_FIELDS": {"fullname": "causy.interfaces.AS_MANY_AS_FIELDS", "modulename": "causy.interfaces", "qualname": "AS_MANY_AS_FIELDS", "kind": "variable", "doc": "

\n", "default_value": "0"}, "causy.interfaces.MetadataBaseType": {"fullname": "causy.interfaces.MetadataBaseType", "modulename": "causy.interfaces", "qualname": "MetadataBaseType", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[str, int, float, bool]"}, "causy.interfaces.MetadataType": {"fullname": "causy.interfaces.MetadataType", "modulename": "causy.interfaces", "qualname": "MetadataType", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[str, int, float, bool, typing.List[typing.Union[str, int, float, bool]], typing.Dict[str, typing.Union[str, int, float, bool]]]"}, "causy.interfaces.ComparisonSettingsInterface": {"fullname": "causy.interfaces.ComparisonSettingsInterface", "modulename": "causy.interfaces", "qualname": "ComparisonSettingsInterface", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel, abc.ABC"}, "causy.interfaces.ComparisonSettingsInterface.min": {"fullname": "causy.interfaces.ComparisonSettingsInterface.min", "modulename": "causy.interfaces", "qualname": "ComparisonSettingsInterface.min", "kind": "variable", "doc": "

\n", "annotation": ": Union[int, causy.variables.VariableReference]"}, "causy.interfaces.ComparisonSettingsInterface.max": {"fullname": "causy.interfaces.ComparisonSettingsInterface.max", "modulename": "causy.interfaces", "qualname": "ComparisonSettingsInterface.max", "kind": "variable", "doc": "

\n", "annotation": ": Union[int, causy.variables.VariableReference]"}, "causy.interfaces.ComparisonSettingsInterface.name": {"fullname": "causy.interfaces.ComparisonSettingsInterface.name", "modulename": "causy.interfaces", "qualname": "ComparisonSettingsInterface.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.ComparisonSettingsInterface.model_config": {"fullname": "causy.interfaces.ComparisonSettingsInterface.model_config", "modulename": "causy.interfaces", "qualname": "ComparisonSettingsInterface.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.interfaces.ComparisonSettingsInterface.model_fields": {"fullname": "causy.interfaces.ComparisonSettingsInterface.model_fields", "modulename": "causy.interfaces", "qualname": "ComparisonSettingsInterface.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'min': FieldInfo(annotation=Union[int, VariableReference], required=True), 'max': FieldInfo(annotation=Union[int, VariableReference], required=True)}"}, "causy.interfaces.ComparisonSettingsInterface.model_computed_fields": {"fullname": "causy.interfaces.ComparisonSettingsInterface.model_computed_fields", "modulename": "causy.interfaces", "qualname": "ComparisonSettingsInterface.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': ComputedFieldInfo(wrapped_property=<property object>, return_type=<class 'str'>, alias=None, alias_priority=None, title=None, field_title_generator=None, description=None, deprecated=None, examples=None, json_schema_extra=None, repr=True)}"}, "causy.interfaces.NodeInterface": {"fullname": "causy.interfaces.NodeInterface", "modulename": "causy.interfaces", "qualname": "NodeInterface", "kind": "class", "doc": "

Node interface for the graph. A node is defined by a name and a value.

\n", "bases": "pydantic.main.BaseModel, abc.ABC"}, "causy.interfaces.NodeInterface.name": {"fullname": "causy.interfaces.NodeInterface.name", "modulename": "causy.interfaces", "qualname": "NodeInterface.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.NodeInterface.id": {"fullname": "causy.interfaces.NodeInterface.id", "modulename": "causy.interfaces", "qualname": "NodeInterface.id", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.NodeInterface.values": {"fullname": "causy.interfaces.NodeInterface.values", "modulename": "causy.interfaces", "qualname": "NodeInterface.values", "kind": "variable", "doc": "

\n", "annotation": ": Annotated[Optional[torch.DoubleTensor], WithJsonSchema(json_schema={'type': 'array', 'items': {'type': 'number'}, 'description': 'Node values'}, mode=None)]"}, "causy.interfaces.NodeInterface.Config": {"fullname": "causy.interfaces.NodeInterface.Config", "modulename": "causy.interfaces", "qualname": "NodeInterface.Config", "kind": "class", "doc": "

\n"}, "causy.interfaces.NodeInterface.Config.arbitrary_types_allowed": {"fullname": "causy.interfaces.NodeInterface.Config.arbitrary_types_allowed", "modulename": "causy.interfaces", "qualname": "NodeInterface.Config.arbitrary_types_allowed", "kind": "variable", "doc": "

\n", "default_value": "True"}, "causy.interfaces.NodeInterface.model_config": {"fullname": "causy.interfaces.NodeInterface.model_config", "modulename": "causy.interfaces", "qualname": "NodeInterface.model_config", "kind": "variable", "doc": "

\n", "default_value": "{'arbitrary_types_allowed': True}"}, "causy.interfaces.NodeInterface.model_fields": {"fullname": "causy.interfaces.NodeInterface.model_fields", "modulename": "causy.interfaces", "qualname": "NodeInterface.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': FieldInfo(annotation=str, required=True), 'id': FieldInfo(annotation=str, required=True), 'values': FieldInfo(annotation=Union[DoubleTensor, NoneType], required=False, default=None, exclude=True, metadata=[WithJsonSchema(json_schema={'type': 'array', 'items': {'type': 'number'}, 'description': 'Node values'}, mode=None)])}"}, "causy.interfaces.NodeInterface.model_computed_fields": {"fullname": "causy.interfaces.NodeInterface.model_computed_fields", "modulename": "causy.interfaces", "qualname": "NodeInterface.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.interfaces.EdgeTypeInterface": {"fullname": "causy.interfaces.EdgeTypeInterface", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface", "kind": "class", "doc": "

Edge type interface for the graph\nAn edge type is defined by a name

\n", "bases": "abc.ABC, pydantic.main.BaseModel, typing.Generic[~EdgeTypeInterfaceType]"}, "causy.interfaces.EdgeTypeInterface.name": {"fullname": "causy.interfaces.EdgeTypeInterface.name", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.EdgeTypeInterface.IS_DIRECTED": {"fullname": "causy.interfaces.EdgeTypeInterface.IS_DIRECTED", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.IS_DIRECTED", "kind": "variable", "doc": "

\n", "annotation": ": bool"}, "causy.interfaces.EdgeTypeInterface.STR_REPRESENTATION": {"fullname": "causy.interfaces.EdgeTypeInterface.STR_REPRESENTATION", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.STR_REPRESENTATION", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.EdgeTypeInterface.GraphAccessMixin": {"fullname": "causy.interfaces.EdgeTypeInterface.GraphAccessMixin", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.GraphAccessMixin", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC"}, "causy.interfaces.EdgeTypeInterface.pre_edge_remove_hook": {"fullname": "causy.interfaces.EdgeTypeInterface.pre_edge_remove_hook", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.pre_edge_remove_hook", "kind": "function", "doc": "

Hook that is executed before an edge is deleted.

\n\n
Parameters
\n\n
    \n
  • graph: the graph
    • \n
  • edge: the edge
    • \n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tedge: causy.interfaces.EdgeInterface):", "funcdef": "def"}, "causy.interfaces.EdgeTypeInterface.post_edge_remove_hook": {"fullname": "causy.interfaces.EdgeTypeInterface.post_edge_remove_hook", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.post_edge_remove_hook", "kind": "function", "doc": "

Hook that is executed after an edge is deleted.

\n\n
Parameters
\n\n
    \n
  • graph: the graph
    • \n
  • edge: the edge
    • \n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tedge: causy.interfaces.EdgeInterface):", "funcdef": "def"}, "causy.interfaces.EdgeTypeInterface.pre_edge_add_hook": {"fullname": "causy.interfaces.EdgeTypeInterface.pre_edge_add_hook", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.pre_edge_add_hook", "kind": "function", "doc": "

Hook that is executed before an edge is added.

\n\n
Parameters
\n\n
    \n
  • graph: the graph
    • \n
  • edge: the edge
    • \n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tedge: causy.interfaces.EdgeInterface):", "funcdef": "def"}, "causy.interfaces.EdgeTypeInterface.post_edge_add_hook": {"fullname": "causy.interfaces.EdgeTypeInterface.post_edge_add_hook", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.post_edge_add_hook", "kind": "function", "doc": "

Hook that is executed after an edge is added.

\n\n
Parameters
\n\n
    \n
  • graph: the graph
    • \n
  • edge: the edge
    • \n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tedge: causy.interfaces.EdgeInterface):", "funcdef": "def"}, "causy.interfaces.EdgeTypeInterface.pre_edge_update_hook": {"fullname": "causy.interfaces.EdgeTypeInterface.pre_edge_update_hook", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.pre_edge_update_hook", "kind": "function", "doc": "

Hook that is executed before an edge is updated.

\n\n
Parameters
\n\n
    \n
  • graph: the graph
    • \n
  • edge: the edge
    • \n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tedge: causy.interfaces.EdgeInterface):", "funcdef": "def"}, "causy.interfaces.EdgeTypeInterface.post_edge_update_hook": {"fullname": "causy.interfaces.EdgeTypeInterface.post_edge_update_hook", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.post_edge_update_hook", "kind": "function", "doc": "

Hook that is executed after an edge is updated.

\n\n
Parameters
\n\n
    \n
  • graph: the graph
    • \n
  • edge: the edge
    • \n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tedge: causy.interfaces.EdgeInterface):", "funcdef": "def"}, "causy.interfaces.EdgeTypeInterface.pre_edge_type_change_hook": {"fullname": "causy.interfaces.EdgeTypeInterface.pre_edge_type_change_hook", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.pre_edge_type_change_hook", "kind": "function", "doc": "

Hook that is executed before an edge type is changed.

\n\n
Parameters
\n\n
    \n
  • graph: the graph
    • \n
  • edge: the edge
    • \n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tedge: causy.interfaces.EdgeInterface):", "funcdef": "def"}, "causy.interfaces.EdgeTypeInterface.post_edge_type_change_hook": {"fullname": "causy.interfaces.EdgeTypeInterface.post_edge_type_change_hook", "modulename": "causy.interfaces", "qualname": "EdgeTypeInterface.post_edge_type_change_hook", "kind": "function", "doc": "

Hook that is executed after an edge type is changed.

\n\n
Parameters
\n\n
    \n
  • graph: the graph
    • \n
  • edge: the edge
    • \n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tedge: causy.interfaces.EdgeInterface):", "funcdef": "def"}, "causy.interfaces.EdgeInterface": {"fullname": "causy.interfaces.EdgeInterface", "modulename": "causy.interfaces", "qualname": "EdgeInterface", "kind": "class", "doc": "

Edge interface for the graph\nA graph edge is defined by two nodes and an edge type. It can also have metadata.

\n", "bases": "pydantic.main.BaseModel, abc.ABC"}, "causy.interfaces.EdgeInterface.u": {"fullname": "causy.interfaces.EdgeInterface.u", "modulename": "causy.interfaces", "qualname": "EdgeInterface.u", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.NodeInterface"}, "causy.interfaces.EdgeInterface.v": {"fullname": "causy.interfaces.EdgeInterface.v", "modulename": "causy.interfaces", "qualname": "EdgeInterface.v", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.NodeInterface"}, "causy.interfaces.EdgeInterface.edge_type": {"fullname": "causy.interfaces.EdgeInterface.edge_type", "modulename": "causy.interfaces", "qualname": "EdgeInterface.edge_type", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.EdgeTypeInterface"}, "causy.interfaces.EdgeInterface.metadata": {"fullname": "causy.interfaces.EdgeInterface.metadata", "modulename": "causy.interfaces", "qualname": "EdgeInterface.metadata", "kind": "variable", "doc": "

\n", "annotation": ": Dict[str, Union[str, int, float, bool, List[Union[str, int, float, bool]], Dict[str, Union[str, int, float, bool]]]]"}, "causy.interfaces.EdgeInterface.Config": {"fullname": "causy.interfaces.EdgeInterface.Config", "modulename": "causy.interfaces", "qualname": "EdgeInterface.Config", "kind": "class", "doc": "

\n"}, "causy.interfaces.EdgeInterface.Config.arbitrary_types_allowed": {"fullname": "causy.interfaces.EdgeInterface.Config.arbitrary_types_allowed", "modulename": "causy.interfaces", "qualname": "EdgeInterface.Config.arbitrary_types_allowed", "kind": "variable", "doc": "

\n", "default_value": "True"}, "causy.interfaces.EdgeInterface.is_connection_between_same_nodes": {"fullname": "causy.interfaces.EdgeInterface.is_connection_between_same_nodes", "modulename": "causy.interfaces", "qualname": "EdgeInterface.is_connection_between_same_nodes", "kind": "function", "doc": "

\n", "signature": "(self, edge):", "funcdef": "def"}, "causy.interfaces.EdgeInterface.model_config": {"fullname": "causy.interfaces.EdgeInterface.model_config", "modulename": "causy.interfaces", "qualname": "EdgeInterface.model_config", "kind": "variable", "doc": "

\n", "default_value": "{'arbitrary_types_allowed': True}"}, "causy.interfaces.EdgeInterface.model_fields": {"fullname": "causy.interfaces.EdgeInterface.model_fields", "modulename": "causy.interfaces", "qualname": "EdgeInterface.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'u': FieldInfo(annotation=NodeInterface, required=True), 'v': FieldInfo(annotation=NodeInterface, required=True), 'edge_type': FieldInfo(annotation=EdgeTypeInterface, required=True), 'metadata': FieldInfo(annotation=Dict[str, Union[str, int, float, bool, List[Union[str, int, float, bool]], Dict[str, Union[str, int, float, bool]]]], required=False, default=None)}"}, "causy.interfaces.EdgeInterface.model_computed_fields": {"fullname": "causy.interfaces.EdgeInterface.model_computed_fields", "modulename": "causy.interfaces", "qualname": "EdgeInterface.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.interfaces.TestResultInterface": {"fullname": "causy.interfaces.TestResultInterface", "modulename": "causy.interfaces", "qualname": "TestResultInterface", "kind": "class", "doc": "

Test result interface for the graph\nA test result is defined by two nodes and an action. It can also have metadata.

\n", "bases": "pydantic.main.BaseModel, abc.ABC"}, "causy.interfaces.TestResultInterface.u": {"fullname": "causy.interfaces.TestResultInterface.u", "modulename": "causy.interfaces", "qualname": "TestResultInterface.u", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.NodeInterface"}, "causy.interfaces.TestResultInterface.v": {"fullname": "causy.interfaces.TestResultInterface.v", "modulename": "causy.interfaces", "qualname": "TestResultInterface.v", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.NodeInterface"}, "causy.interfaces.TestResultInterface.action": {"fullname": "causy.interfaces.TestResultInterface.action", "modulename": "causy.interfaces", "qualname": "TestResultInterface.action", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.TestResultInterface.data": {"fullname": "causy.interfaces.TestResultInterface.data", "modulename": "causy.interfaces", "qualname": "TestResultInterface.data", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict]"}, "causy.interfaces.TestResultInterface.Config": {"fullname": "causy.interfaces.TestResultInterface.Config", "modulename": "causy.interfaces", "qualname": "TestResultInterface.Config", "kind": "class", "doc": "

\n"}, "causy.interfaces.TestResultInterface.Config.arbitrary_types_allowed": {"fullname": "causy.interfaces.TestResultInterface.Config.arbitrary_types_allowed", "modulename": "causy.interfaces", "qualname": "TestResultInterface.Config.arbitrary_types_allowed", "kind": "variable", "doc": "

\n", "default_value": "True"}, "causy.interfaces.TestResultInterface.model_config": {"fullname": "causy.interfaces.TestResultInterface.model_config", "modulename": "causy.interfaces", "qualname": "TestResultInterface.model_config", "kind": "variable", "doc": "

\n", "default_value": "{'arbitrary_types_allowed': True}"}, "causy.interfaces.TestResultInterface.model_fields": {"fullname": "causy.interfaces.TestResultInterface.model_fields", "modulename": "causy.interfaces", "qualname": "TestResultInterface.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'u': FieldInfo(annotation=NodeInterface, required=True), 'v': FieldInfo(annotation=NodeInterface, required=True), 'action': FieldInfo(annotation=str, required=True), 'data': FieldInfo(annotation=Union[Dict, NoneType], required=False, default=None)}"}, "causy.interfaces.TestResultInterface.model_computed_fields": {"fullname": "causy.interfaces.TestResultInterface.model_computed_fields", "modulename": "causy.interfaces", "qualname": "TestResultInterface.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.interfaces.BaseGraphInterface": {"fullname": "causy.interfaces.BaseGraphInterface", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC"}, "causy.interfaces.BaseGraphInterface.nodes": {"fullname": "causy.interfaces.BaseGraphInterface.nodes", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.nodes", "kind": "variable", "doc": "

\n", "annotation": ": Dict[str, causy.interfaces.NodeInterface]"}, "causy.interfaces.BaseGraphInterface.edges": {"fullname": "causy.interfaces.BaseGraphInterface.edges", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.edges", "kind": "variable", "doc": "

\n", "annotation": ": Dict[str, Dict[str, Dict]]"}, "causy.interfaces.BaseGraphInterface.retrieve_edge_history": {"fullname": "causy.interfaces.BaseGraphInterface.retrieve_edge_history", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.retrieve_edge_history", "kind": "function", "doc": "

\n", "signature": "(self, u, v, action: str) -> List[causy.interfaces.TestResultInterface]:", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.add_edge_history": {"fullname": "causy.interfaces.BaseGraphInterface.add_edge_history", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.add_edge_history", "kind": "function", "doc": "

\n", "signature": "(self, u, v, action: causy.interfaces.TestResultInterface):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.add_edge": {"fullname": "causy.interfaces.BaseGraphInterface.add_edge", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.add_edge", "kind": "function", "doc": "

\n", "signature": "(self, u, v, metadata):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.remove_edge": {"fullname": "causy.interfaces.BaseGraphInterface.remove_edge", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.remove_edge", "kind": "function", "doc": "

\n", "signature": "(self, u, v):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.remove_directed_edge": {"fullname": "causy.interfaces.BaseGraphInterface.remove_directed_edge", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.remove_directed_edge", "kind": "function", "doc": "

\n", "signature": "(self, u, v):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.update_edge": {"fullname": "causy.interfaces.BaseGraphInterface.update_edge", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.update_edge", "kind": "function", "doc": "

\n", "signature": "(self, u, v, metadata=None, edge_type=None):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.update_directed_edge": {"fullname": "causy.interfaces.BaseGraphInterface.update_directed_edge", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.update_directed_edge", "kind": "function", "doc": "

\n", "signature": "(self, u, v, metadata=None, edge_type=None):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.add_node": {"fullname": "causy.interfaces.BaseGraphInterface.add_node", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.add_node", "kind": "function", "doc": "

\n", "signature": "(self, name, values) -> causy.interfaces.NodeInterface:", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.edge_value": {"fullname": "causy.interfaces.BaseGraphInterface.edge_value", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.edge_value", "kind": "function", "doc": "

\n", "signature": "(self, u, v):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.undirected_edge_exists": {"fullname": "causy.interfaces.BaseGraphInterface.undirected_edge_exists", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.undirected_edge_exists", "kind": "function", "doc": "

\n", "signature": "(self, u, v):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.directed_edge_exists": {"fullname": "causy.interfaces.BaseGraphInterface.directed_edge_exists", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.directed_edge_exists", "kind": "function", "doc": "

\n", "signature": "(self, u, v):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.edge_exists": {"fullname": "causy.interfaces.BaseGraphInterface.edge_exists", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.edge_exists", "kind": "function", "doc": "

\n", "signature": "(self, u, v, ignore_soft_deleted=False):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.restore_edge": {"fullname": "causy.interfaces.BaseGraphInterface.restore_edge", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.restore_edge", "kind": "function", "doc": "

\n", "signature": "(self, u, v):", "funcdef": "def"}, "causy.interfaces.BaseGraphInterface.restore_directed_edge": {"fullname": "causy.interfaces.BaseGraphInterface.restore_directed_edge", "modulename": "causy.interfaces", "qualname": "BaseGraphInterface.restore_directed_edge", "kind": "function", "doc": "

\n", "signature": "(self, u, v):", "funcdef": "def"}, "causy.interfaces.GraphModelInterface": {"fullname": "causy.interfaces.GraphModelInterface", "modulename": "causy.interfaces", "qualname": "GraphModelInterface", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC"}, "causy.interfaces.GraphModelInterface.pool": {"fullname": "causy.interfaces.GraphModelInterface.pool", "modulename": "causy.interfaces", "qualname": "GraphModelInterface.pool", "kind": "variable", "doc": "

\n", "annotation": ": <bound method BaseContext.Pool of <multiprocessing.context.DefaultContext object at 0x7f4ad89b9460>>"}, "causy.interfaces.GraphModelInterface.create_graph_from_data": {"fullname": "causy.interfaces.GraphModelInterface.create_graph_from_data", "modulename": "causy.interfaces", "qualname": "GraphModelInterface.create_graph_from_data", "kind": "function", "doc": "

\n", "signature": "(self, data: List[Dict]):", "funcdef": "def"}, "causy.interfaces.GraphModelInterface.execute_pipeline_steps": {"fullname": "causy.interfaces.GraphModelInterface.execute_pipeline_steps", "modulename": "causy.interfaces", "qualname": "GraphModelInterface.execute_pipeline_steps", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "causy.interfaces.GraphModelInterface.execute_pipeline_step": {"fullname": "causy.interfaces.GraphModelInterface.execute_pipeline_step", "modulename": "causy.interfaces", "qualname": "GraphModelInterface.execute_pipeline_step", "kind": "function", "doc": "

\n", "signature": "(self, step, apply_to_graph: bool = True):", "funcdef": "def"}, "causy.interfaces.GeneratorInterface": {"fullname": "causy.interfaces.GeneratorInterface", "modulename": "causy.interfaces", "qualname": "GeneratorInterface", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC, pydantic.main.BaseModel"}, "causy.interfaces.GeneratorInterface.comparison_settings": {"fullname": "causy.interfaces.GeneratorInterface.comparison_settings", "modulename": "causy.interfaces", "qualname": "GeneratorInterface.comparison_settings", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.interfaces.ComparisonSettingsInterface]"}, "causy.interfaces.GeneratorInterface.chunked": {"fullname": "causy.interfaces.GeneratorInterface.chunked", "modulename": "causy.interfaces", "qualname": "GeneratorInterface.chunked", "kind": "variable", "doc": "

\n", "annotation": ": Union[bool, causy.variables.VariableReference, NoneType]"}, "causy.interfaces.GeneratorInterface.every_nth": {"fullname": "causy.interfaces.GeneratorInterface.every_nth", "modulename": "causy.interfaces", "qualname": "GeneratorInterface.every_nth", "kind": "variable", "doc": "

\n", "annotation": ": Union[int, causy.variables.VariableReference, NoneType]"}, "causy.interfaces.GeneratorInterface.generator": {"fullname": "causy.interfaces.GeneratorInterface.generator", "modulename": "causy.interfaces", "qualname": "GeneratorInterface.generator", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.interfaces.GeneratorInterface]"}, "causy.interfaces.GeneratorInterface.shuffle_combinations": {"fullname": "causy.interfaces.GeneratorInterface.shuffle_combinations", "modulename": "causy.interfaces", "qualname": "GeneratorInterface.shuffle_combinations", "kind": "variable", "doc": "

\n", "annotation": ": Union[bool, causy.variables.VariableReference, NoneType]"}, "causy.interfaces.GeneratorInterface.generate": {"fullname": "causy.interfaces.GeneratorInterface.generate", "modulename": "causy.interfaces", "qualname": "GeneratorInterface.generate", "kind": "function", "doc": "

\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tgraph_model_instance_: dict):", "funcdef": "def"}, "causy.interfaces.GeneratorInterface.name": {"fullname": "causy.interfaces.GeneratorInterface.name", "modulename": "causy.interfaces", "qualname": "GeneratorInterface.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.GeneratorInterface.model_config": {"fullname": "causy.interfaces.GeneratorInterface.model_config", "modulename": "causy.interfaces", "qualname": "GeneratorInterface.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.interfaces.GeneratorInterface.model_fields": {"fullname": "causy.interfaces.GeneratorInterface.model_fields", "modulename": "causy.interfaces", "qualname": "GeneratorInterface.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'comparison_settings': FieldInfo(annotation=Union[ComparisonSettingsInterface, NoneType], required=False, default=None), 'chunked': FieldInfo(annotation=Union[bool, VariableReference, NoneType], required=False, default=False), 'every_nth': FieldInfo(annotation=Union[int, VariableReference, NoneType], required=False, default=None), 'generator': FieldInfo(annotation=Union[GeneratorInterface, NoneType], required=False, default=None), 'shuffle_combinations': FieldInfo(annotation=Union[bool, VariableReference, NoneType], required=False, default=None)}"}, "causy.interfaces.GeneratorInterface.model_computed_fields": {"fullname": "causy.interfaces.GeneratorInterface.model_computed_fields", "modulename": "causy.interfaces", "qualname": "GeneratorInterface.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': ComputedFieldInfo(wrapped_property=<property object>, return_type=<class 'str'>, alias=None, alias_priority=None, title=None, field_title_generator=None, description=None, deprecated=None, examples=None, json_schema_extra=None, repr=True)}"}, "causy.interfaces.PipelineStepInterface": {"fullname": "causy.interfaces.PipelineStepInterface", "modulename": "causy.interfaces", "qualname": "PipelineStepInterface", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC, pydantic.main.BaseModel, typing.Generic[~PipelineStepInterfaceType]"}, "causy.interfaces.PipelineStepInterface.generator": {"fullname": "causy.interfaces.PipelineStepInterface.generator", "modulename": "causy.interfaces", "qualname": "PipelineStepInterface.generator", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.interfaces.GeneratorInterface]"}, "causy.interfaces.PipelineStepInterface.threshold": {"fullname": "causy.interfaces.PipelineStepInterface.threshold", "modulename": "causy.interfaces", "qualname": "PipelineStepInterface.threshold", "kind": "variable", "doc": "

\n", "annotation": ": Union[float, causy.variables.VariableReference, NoneType]"}, "causy.interfaces.PipelineStepInterface.chunk_size_parallel_processing": {"fullname": "causy.interfaces.PipelineStepInterface.chunk_size_parallel_processing", "modulename": "causy.interfaces", "qualname": "PipelineStepInterface.chunk_size_parallel_processing", "kind": "variable", "doc": "

\n", "annotation": ": Union[int, causy.variables.VariableReference]"}, "causy.interfaces.PipelineStepInterface.parallel": {"fullname": "causy.interfaces.PipelineStepInterface.parallel", "modulename": "causy.interfaces", "qualname": "PipelineStepInterface.parallel", "kind": "variable", "doc": "

\n", "annotation": ": Union[bool, causy.variables.VariableReference]"}, "causy.interfaces.PipelineStepInterface.display_name": {"fullname": "causy.interfaces.PipelineStepInterface.display_name", "modulename": "causy.interfaces", "qualname": "PipelineStepInterface.display_name", "kind": "variable", "doc": "

\n", "annotation": ": Union[str, causy.variables.VariableReference, NoneType]"}, "causy.interfaces.PipelineStepInterface.needs_unapplied_actions": {"fullname": "causy.interfaces.PipelineStepInterface.needs_unapplied_actions", "modulename": "causy.interfaces", "qualname": "PipelineStepInterface.needs_unapplied_actions", "kind": "variable", "doc": "

\n", "annotation": ": Union[bool, causy.variables.VariableReference, NoneType]"}, "causy.interfaces.PipelineStepInterface.apply_synchronous": {"fullname": "causy.interfaces.PipelineStepInterface.apply_synchronous", "modulename": "causy.interfaces", "qualname": "PipelineStepInterface.apply_synchronous", "kind": "variable", "doc": "

\n", "annotation": ": Union[bool, causy.variables.VariableReference, NoneType]"}, "causy.interfaces.PipelineStepInterface.name": {"fullname": "causy.interfaces.PipelineStepInterface.name", "modulename": "causy.interfaces", "qualname": "PipelineStepInterface.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.PipelineStepInterface.process": {"fullname": "causy.interfaces.PipelineStepInterface.process", "modulename": "causy.interfaces", "qualname": "PipelineStepInterface.process", "kind": "function", "doc": "

Test if u and v are independent

\n\n
Parameters
\n\n
    \n
  • u: u values
    • \n
  • v: v values
    • \n
\n\n
Returns
\n\n
\n

True if independent, False otherwise

\n
\n", "signature": "(\tself,\tnodes: List[str],\tgraph: causy.interfaces.BaseGraphInterface,\tunapplied_actions: Optional[List[causy.interfaces.TestResultInterface]] = None) -> Optional[causy.interfaces.TestResultInterface]:", "funcdef": "def"}, "causy.interfaces.ExitConditionInterface": {"fullname": "causy.interfaces.ExitConditionInterface", "modulename": "causy.interfaces", "qualname": "ExitConditionInterface", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC, pydantic.main.BaseModel"}, "causy.interfaces.ExitConditionInterface.check": {"fullname": "causy.interfaces.ExitConditionInterface.check", "modulename": "causy.interfaces", "qualname": "ExitConditionInterface.check", "kind": "function", "doc": "
Parameters
\n\n
    \n
  • graph:
    • \n
  • graph_model_instance_:
    • \n
  • actions_taken:
    • \n
  • iteration:
    • \n
\n\n
Returns
\n\n
\n

True if you want to break an iteration, False otherwise

\n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tgraph_model_instance_: causy.interfaces.GraphModelInterface,\tactions_taken: List[causy.interfaces.TestResultInterface],\titeration: Union[int, causy.variables.VariableReference]) -> bool:", "funcdef": "def"}, "causy.interfaces.ExitConditionInterface.name": {"fullname": "causy.interfaces.ExitConditionInterface.name", "modulename": "causy.interfaces", "qualname": "ExitConditionInterface.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.ExitConditionInterface.model_config": {"fullname": "causy.interfaces.ExitConditionInterface.model_config", "modulename": "causy.interfaces", "qualname": "ExitConditionInterface.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.interfaces.ExitConditionInterface.model_fields": {"fullname": "causy.interfaces.ExitConditionInterface.model_fields", "modulename": "causy.interfaces", "qualname": "ExitConditionInterface.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.interfaces.ExitConditionInterface.model_computed_fields": {"fullname": "causy.interfaces.ExitConditionInterface.model_computed_fields", "modulename": "causy.interfaces", "qualname": "ExitConditionInterface.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': ComputedFieldInfo(wrapped_property=<property object>, return_type=<class 'str'>, alias=None, alias_priority=None, title=None, field_title_generator=None, description=None, deprecated=None, examples=None, json_schema_extra=None, repr=True)}"}, "causy.interfaces.LogicStepInterface": {"fullname": "causy.interfaces.LogicStepInterface", "modulename": "causy.interfaces", "qualname": "LogicStepInterface", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC, pydantic.main.BaseModel, typing.Generic[~LogicStepInterfaceType]"}, "causy.interfaces.LogicStepInterface.pipeline_steps": {"fullname": "causy.interfaces.LogicStepInterface.pipeline_steps", "modulename": "causy.interfaces", "qualname": "LogicStepInterface.pipeline_steps", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[~PipelineStepInterfaceType]]"}, "causy.interfaces.LogicStepInterface.exit_condition": {"fullname": "causy.interfaces.LogicStepInterface.exit_condition", "modulename": "causy.interfaces", "qualname": "LogicStepInterface.exit_condition", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.interfaces.ExitConditionInterface]"}, "causy.interfaces.LogicStepInterface.display_name": {"fullname": "causy.interfaces.LogicStepInterface.display_name", "modulename": "causy.interfaces", "qualname": "LogicStepInterface.display_name", "kind": "variable", "doc": "

\n", "annotation": ": Union[str, causy.variables.VariableReference, NoneType]"}, "causy.interfaces.LogicStepInterface.execute": {"fullname": "causy.interfaces.LogicStepInterface.execute", "modulename": "causy.interfaces", "qualname": "LogicStepInterface.execute", "kind": "function", "doc": "

\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tgraph_model_instance_: dict):", "funcdef": "def"}, "causy.interfaces.LogicStepInterface.name": {"fullname": "causy.interfaces.LogicStepInterface.name", "modulename": "causy.interfaces", "qualname": "LogicStepInterface.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.ExtensionInterface": {"fullname": "causy.interfaces.ExtensionInterface", "modulename": "causy.interfaces", "qualname": "ExtensionInterface", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel, typing.Generic[~ExtensionType]"}, "causy.interfaces.ExtensionInterface.name": {"fullname": "causy.interfaces.ExtensionInterface.name", "modulename": "causy.interfaces", "qualname": "ExtensionInterface.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.interfaces.ExtensionInterface.GraphAccessMixin": {"fullname": "causy.interfaces.ExtensionInterface.GraphAccessMixin", "modulename": "causy.interfaces", "qualname": "ExtensionInterface.GraphAccessMixin", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC"}, "causy.interfaces.GraphUpdateHook": {"fullname": "causy.interfaces.GraphUpdateHook", "modulename": "causy.interfaces", "qualname": "GraphUpdateHook", "kind": "class", "doc": "

A hook that is executed before or after the graph is updated. This can be used to modify the graph before or after an update.

\n", "bases": "pydantic.main.BaseModel"}, "causy.interfaces.GraphUpdateHook.execute": {"fullname": "causy.interfaces.GraphUpdateHook.execute", "modulename": "causy.interfaces", "qualname": "GraphUpdateHook.execute", "kind": "function", "doc": "

Execute the hook.

\n\n
Parameters
\n\n
    \n
  • graph: current state of the graph.
    • \n
  • updates: the planned/taken actions
    • \n
\n\n
Returns
\n\n
\n

A list of updates that should be applied to the graph if it is a pre hook. If it is a post hook, it should return None.

\n
\n", "signature": "(\tself,\tgraph: causy.interfaces.BaseGraphInterface,\tupdates: List[causy.interfaces.TestResultInterface]) -> Optional[List[causy.interfaces.TestResultInterface]]:", "funcdef": "def"}, "causy.interfaces.GraphUpdateHook.model_config": {"fullname": "causy.interfaces.GraphUpdateHook.model_config", "modulename": "causy.interfaces", "qualname": "GraphUpdateHook.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.interfaces.GraphUpdateHook.model_fields": {"fullname": "causy.interfaces.GraphUpdateHook.model_fields", "modulename": "causy.interfaces", "qualname": "GraphUpdateHook.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.interfaces.GraphUpdateHook.model_computed_fields": {"fullname": "causy.interfaces.GraphUpdateHook.model_computed_fields", "modulename": "causy.interfaces", "qualname": "GraphUpdateHook.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.math_utils": {"fullname": "causy.math_utils", "modulename": "causy.math_utils", "kind": "module", "doc": "

\n"}, "causy.math_utils.logger": {"fullname": "causy.math_utils.logger", "modulename": "causy.math_utils", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.math_utils (WARNING)>"}, "causy.math_utils.sum_lists": {"fullname": "causy.math_utils.sum_lists", "modulename": "causy.math_utils", "qualname": "sum_lists", "kind": "function", "doc": "
Parameters
\n\n
    \n
  • lists: lists of numbers
    • \n
\n\n
Returns
\n\n
\n

list (sum of lists)

\n
\n", "signature": "(*lists):", "funcdef": "def"}, "causy.math_utils.get_t_and_critical_t": {"fullname": "causy.math_utils.get_t_and_critical_t", "modulename": "causy.math_utils", "qualname": "get_t_and_critical_t", "kind": "function", "doc": "

\n", "signature": "(sample_size, nb_of_control_vars, par_corr, threshold):", "funcdef": "def"}, "causy.models": {"fullname": "causy.models", "modulename": "causy.models", "kind": "module", "doc": "

\n"}, "causy.models.ComparisonSettings": {"fullname": "causy.models.ComparisonSettings", "modulename": "causy.models", "qualname": "ComparisonSettings", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "causy.interfaces.ComparisonSettingsInterface"}, "causy.models.ComparisonSettings.min": {"fullname": "causy.models.ComparisonSettings.min", "modulename": "causy.models", "qualname": "ComparisonSettings.min", "kind": "variable", "doc": "

\n", "annotation": ": Union[int, causy.variables.VariableReference]"}, "causy.models.ComparisonSettings.max": {"fullname": "causy.models.ComparisonSettings.max", "modulename": "causy.models", "qualname": "ComparisonSettings.max", "kind": "variable", "doc": "

\n", "annotation": ": Union[int, causy.variables.VariableReference]"}, "causy.models.ComparisonSettings.name": {"fullname": "causy.models.ComparisonSettings.name", "modulename": "causy.models", "qualname": "ComparisonSettings.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.models.ComparisonSettings.model_config": {"fullname": "causy.models.ComparisonSettings.model_config", "modulename": "causy.models", "qualname": "ComparisonSettings.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.models.ComparisonSettings.model_fields": {"fullname": "causy.models.ComparisonSettings.model_fields", "modulename": "causy.models", "qualname": "ComparisonSettings.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'min': FieldInfo(annotation=Union[int, VariableReference], required=False, default=2), 'max': FieldInfo(annotation=Union[int, VariableReference], required=False, default=0)}"}, "causy.models.ComparisonSettings.model_computed_fields": {"fullname": "causy.models.ComparisonSettings.model_computed_fields", "modulename": "causy.models", "qualname": "ComparisonSettings.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': ComputedFieldInfo(wrapped_property=<property object>, return_type=<class 'str'>, alias=None, alias_priority=None, title=None, field_title_generator=None, description=None, deprecated=None, examples=None, json_schema_extra=None, repr=True)}"}, "causy.models.TestResultAction": {"fullname": "causy.models.TestResultAction", "modulename": "causy.models", "qualname": "TestResultAction", "kind": "class", "doc": "

Actions that can be taken on the graph. These actions are used to keep track of the history of the graph.

\n", "bases": "builtins.str, enum.Enum"}, "causy.models.TestResultAction.UPDATE_EDGE": {"fullname": "causy.models.TestResultAction.UPDATE_EDGE", "modulename": "causy.models", "qualname": "TestResultAction.UPDATE_EDGE", "kind": "variable", "doc": "

\n", "default_value": "<TestResultAction.UPDATE_EDGE: 'UPDATE_EDGE'>"}, "causy.models.TestResultAction.UPDATE_EDGE_DIRECTED": {"fullname": "causy.models.TestResultAction.UPDATE_EDGE_DIRECTED", "modulename": "causy.models", "qualname": "TestResultAction.UPDATE_EDGE_DIRECTED", "kind": "variable", "doc": "

\n", "default_value": "<TestResultAction.UPDATE_EDGE_DIRECTED: 'UPDATE_EDGE_DIRECTED'>"}, "causy.models.TestResultAction.UPDATE_EDGE_TYPE": {"fullname": "causy.models.TestResultAction.UPDATE_EDGE_TYPE", "modulename": "causy.models", "qualname": "TestResultAction.UPDATE_EDGE_TYPE", "kind": "variable", "doc": "

\n", "default_value": "<TestResultAction.UPDATE_EDGE_TYPE: 'UPDATE_EDGE_TYPE'>"}, "causy.models.TestResultAction.UPDATE_EDGE_TYPE_DIRECTED": {"fullname": "causy.models.TestResultAction.UPDATE_EDGE_TYPE_DIRECTED", "modulename": "causy.models", "qualname": "TestResultAction.UPDATE_EDGE_TYPE_DIRECTED", "kind": "variable", "doc": "

\n", "default_value": "<TestResultAction.UPDATE_EDGE_TYPE_DIRECTED: 'UPDATE_EDGE_TYPE_DIRECTED'>"}, "causy.models.TestResultAction.REMOVE_EDGE_UNDIRECTED": {"fullname": "causy.models.TestResultAction.REMOVE_EDGE_UNDIRECTED", "modulename": "causy.models", "qualname": "TestResultAction.REMOVE_EDGE_UNDIRECTED", "kind": "variable", "doc": "

\n", "default_value": "<TestResultAction.REMOVE_EDGE_UNDIRECTED: 'REMOVE_EDGE_UNDIRECTED'>"}, "causy.models.TestResultAction.REMOVE_EDGE_DIRECTED": {"fullname": "causy.models.TestResultAction.REMOVE_EDGE_DIRECTED", "modulename": "causy.models", "qualname": "TestResultAction.REMOVE_EDGE_DIRECTED", "kind": "variable", "doc": "

\n", "default_value": "<TestResultAction.REMOVE_EDGE_DIRECTED: 'REMOVE_EDGE_DIRECTED'>"}, "causy.models.TestResultAction.RESTORE_EDGE": {"fullname": "causy.models.TestResultAction.RESTORE_EDGE", "modulename": "causy.models", "qualname": "TestResultAction.RESTORE_EDGE", "kind": "variable", "doc": "

\n", "default_value": "<TestResultAction.RESTORE_EDGE: 'RESTORE_EDGE'>"}, "causy.models.TestResultAction.RESTORE_EDGE_DIRECTED": {"fullname": "causy.models.TestResultAction.RESTORE_EDGE_DIRECTED", "modulename": "causy.models", "qualname": "TestResultAction.RESTORE_EDGE_DIRECTED", "kind": "variable", "doc": "

\n", "default_value": "<TestResultAction.RESTORE_EDGE_DIRECTED: 'RESTORE_EDGE_DIRECTED'>"}, "causy.models.TestResultAction.DO_NOTHING": {"fullname": "causy.models.TestResultAction.DO_NOTHING", "modulename": "causy.models", "qualname": "TestResultAction.DO_NOTHING", "kind": "variable", "doc": "

\n", "default_value": "<TestResultAction.DO_NOTHING: 'DO_NOTHING'>"}, "causy.models.TestResult": {"fullname": "causy.models.TestResult", "modulename": "causy.models", "qualname": "TestResult", "kind": "class", "doc": "

Test result interface for the graph\nA test result is defined by two nodes and an action. It can also have metadata.

\n", "bases": "causy.interfaces.TestResultInterface"}, "causy.models.TestResult.u": {"fullname": "causy.models.TestResult.u", "modulename": "causy.models", "qualname": "TestResult.u", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.NodeInterface"}, "causy.models.TestResult.v": {"fullname": "causy.models.TestResult.v", "modulename": "causy.models", "qualname": "TestResult.v", "kind": "variable", "doc": "

\n", "annotation": ": causy.interfaces.NodeInterface"}, "causy.models.TestResult.action": {"fullname": "causy.models.TestResult.action", "modulename": "causy.models", "qualname": "TestResult.action", "kind": "variable", "doc": "

\n", "annotation": ": causy.models.TestResultAction"}, "causy.models.TestResult.data": {"fullname": "causy.models.TestResult.data", "modulename": "causy.models", "qualname": "TestResult.data", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict]"}, "causy.models.TestResult.model_config": {"fullname": "causy.models.TestResult.model_config", "modulename": "causy.models", "qualname": "TestResult.model_config", "kind": "variable", "doc": "

\n", "default_value": "{'arbitrary_types_allowed': True}"}, "causy.models.TestResult.model_fields": {"fullname": "causy.models.TestResult.model_fields", "modulename": "causy.models", "qualname": "TestResult.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'u': FieldInfo(annotation=NodeInterface, required=True), 'v': FieldInfo(annotation=NodeInterface, required=True), 'action': FieldInfo(annotation=TestResultAction, required=True), 'data': FieldInfo(annotation=Union[Dict, NoneType], required=False, default=None)}"}, "causy.models.TestResult.model_computed_fields": {"fullname": "causy.models.TestResult.model_computed_fields", "modulename": "causy.models", "qualname": "TestResult.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.models.AlgorithmReferenceType": {"fullname": "causy.models.AlgorithmReferenceType", "modulename": "causy.models", "qualname": "AlgorithmReferenceType", "kind": "class", "doc": "

str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str

\n\n

Create a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to sys.getdefaultencoding().\nerrors defaults to 'strict'.

\n", "bases": "builtins.str, enum.Enum"}, "causy.models.AlgorithmReferenceType.FILE": {"fullname": "causy.models.AlgorithmReferenceType.FILE", "modulename": "causy.models", "qualname": "AlgorithmReferenceType.FILE", "kind": "variable", "doc": "

\n", "default_value": "<AlgorithmReferenceType.FILE: 'file'>"}, "causy.models.AlgorithmReferenceType.NAME": {"fullname": "causy.models.AlgorithmReferenceType.NAME", "modulename": "causy.models", "qualname": "AlgorithmReferenceType.NAME", "kind": "variable", "doc": "

\n", "default_value": "<AlgorithmReferenceType.NAME: 'name'>"}, "causy.models.AlgorithmReferenceType.PYTHON_MODULE": {"fullname": "causy.models.AlgorithmReferenceType.PYTHON_MODULE", "modulename": "causy.models", "qualname": "AlgorithmReferenceType.PYTHON_MODULE", "kind": "variable", "doc": "

\n", "default_value": "<AlgorithmReferenceType.PYTHON_MODULE: 'python_module'>"}, "causy.models.AlgorithmReference": {"fullname": "causy.models.AlgorithmReference", "modulename": "causy.models", "qualname": "AlgorithmReference", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel"}, "causy.models.AlgorithmReference.reference": {"fullname": "causy.models.AlgorithmReference.reference", "modulename": "causy.models", "qualname": "AlgorithmReference.reference", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.models.AlgorithmReference.type": {"fullname": "causy.models.AlgorithmReference.type", "modulename": "causy.models", "qualname": "AlgorithmReference.type", "kind": "variable", "doc": "

\n", "annotation": ": causy.models.AlgorithmReferenceType"}, "causy.models.AlgorithmReference.model_config": {"fullname": "causy.models.AlgorithmReference.model_config", "modulename": "causy.models", "qualname": "AlgorithmReference.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.models.AlgorithmReference.model_fields": {"fullname": "causy.models.AlgorithmReference.model_fields", "modulename": "causy.models", "qualname": "AlgorithmReference.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'reference': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=AlgorithmReferenceType, required=True)}"}, "causy.models.AlgorithmReference.model_computed_fields": {"fullname": "causy.models.AlgorithmReference.model_computed_fields", "modulename": "causy.models", "qualname": "AlgorithmReference.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.models.Algorithm": {"fullname": "causy.models.Algorithm", "modulename": "causy.models", "qualname": "Algorithm", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel"}, "causy.models.Algorithm.name": {"fullname": "causy.models.Algorithm.name", "modulename": "causy.models", "qualname": "Algorithm.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.models.Algorithm.pipeline_steps": {"fullname": "causy.models.Algorithm.pipeline_steps", "modulename": "causy.models", "qualname": "Algorithm.pipeline_steps", "kind": "variable", "doc": "

\n", "annotation": ": List[Union[~PipelineStepInterfaceType, causy.interfaces.LogicStepInterface]]"}, "causy.models.Algorithm.edge_types": {"fullname": "causy.models.Algorithm.edge_types", "modulename": "causy.models", "qualname": "Algorithm.edge_types", "kind": "variable", "doc": "

\n", "annotation": ": List[~EdgeTypeInterfaceType]"}, "causy.models.Algorithm.extensions": {"fullname": "causy.models.Algorithm.extensions", "modulename": "causy.models", "qualname": "Algorithm.extensions", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[~ExtensionType]]"}, "causy.models.Algorithm.variables": {"fullname": "causy.models.Algorithm.variables", "modulename": "causy.models", "qualname": "Algorithm.variables", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[~VariableInterfaceType]]"}, "causy.models.Algorithm.pre_graph_update_hooks": {"fullname": "causy.models.Algorithm.pre_graph_update_hooks", "modulename": "causy.models", "qualname": "Algorithm.pre_graph_update_hooks", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[causy.interfaces.GraphUpdateHook]]"}, "causy.models.Algorithm.post_graph_update_hooks": {"fullname": "causy.models.Algorithm.post_graph_update_hooks", "modulename": "causy.models", "qualname": "Algorithm.post_graph_update_hooks", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[causy.interfaces.GraphUpdateHook]]"}, "causy.models.Algorithm.hash": {"fullname": "causy.models.Algorithm.hash", "modulename": "causy.models", "qualname": "Algorithm.hash", "kind": "function", "doc": "

\n", "signature": "(self) -> str:", "funcdef": "def"}, "causy.models.Algorithm.model_config": {"fullname": "causy.models.Algorithm.model_config", "modulename": "causy.models", "qualname": "Algorithm.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.models.Algorithm.model_fields": {"fullname": "causy.models.Algorithm.model_fields", "modulename": "causy.models", "qualname": "Algorithm.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': FieldInfo(annotation=str, required=True), 'pipeline_steps': FieldInfo(annotation=List[Union[TypeVar, LogicStepInterface]], required=True), 'edge_types': FieldInfo(annotation=List[TypeVar], required=True), 'extensions': FieldInfo(annotation=Union[List[TypeVar], NoneType], required=False, default=None), 'variables': FieldInfo(annotation=Union[List[TypeVar], NoneType], required=False, default=None), 'pre_graph_update_hooks': FieldInfo(annotation=Union[List[GraphUpdateHook], NoneType], required=False, default=None), 'post_graph_update_hooks': FieldInfo(annotation=Union[List[GraphUpdateHook], NoneType], required=False, default=None)}"}, "causy.models.Algorithm.model_computed_fields": {"fullname": "causy.models.Algorithm.model_computed_fields", "modulename": "causy.models", "qualname": "Algorithm.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.models.ActionHistoryStep": {"fullname": "causy.models.ActionHistoryStep", "modulename": "causy.models", "qualname": "ActionHistoryStep", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel"}, "causy.models.ActionHistoryStep.name": {"fullname": "causy.models.ActionHistoryStep.name", "modulename": "causy.models", "qualname": "ActionHistoryStep.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.models.ActionHistoryStep.duration": {"fullname": "causy.models.ActionHistoryStep.duration", "modulename": "causy.models", "qualname": "ActionHistoryStep.duration", "kind": "variable", "doc": "

\n", "annotation": ": Optional[float]"}, "causy.models.ActionHistoryStep.actions": {"fullname": "causy.models.ActionHistoryStep.actions", "modulename": "causy.models", "qualname": "ActionHistoryStep.actions", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[causy.models.TestResult]]"}, "causy.models.ActionHistoryStep.all_proposed_actions": {"fullname": "causy.models.ActionHistoryStep.all_proposed_actions", "modulename": "causy.models", "qualname": "ActionHistoryStep.all_proposed_actions", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[causy.models.TestResult]]"}, "causy.models.ActionHistoryStep.steps": {"fullname": "causy.models.ActionHistoryStep.steps", "modulename": "causy.models", "qualname": "ActionHistoryStep.steps", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[causy.models.ActionHistoryStep]]"}, "causy.models.ActionHistoryStep.model_config": {"fullname": "causy.models.ActionHistoryStep.model_config", "modulename": "causy.models", "qualname": "ActionHistoryStep.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.models.ActionHistoryStep.model_fields": {"fullname": "causy.models.ActionHistoryStep.model_fields", "modulename": "causy.models", "qualname": "ActionHistoryStep.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': FieldInfo(annotation=str, required=True), 'duration': FieldInfo(annotation=Union[float, NoneType], required=False, default=None), 'actions': FieldInfo(annotation=Union[List[TestResult], NoneType], required=False, default=[]), 'all_proposed_actions': FieldInfo(annotation=Union[List[TestResult], NoneType], required=False, default=[]), 'steps': FieldInfo(annotation=Union[List[ActionHistoryStep], NoneType], required=False, default=[])}"}, "causy.models.ActionHistoryStep.model_computed_fields": {"fullname": "causy.models.ActionHistoryStep.model_computed_fields", "modulename": "causy.models", "qualname": "ActionHistoryStep.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.models.Result": {"fullname": "causy.models.Result", "modulename": "causy.models", "qualname": "Result", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel"}, "causy.models.Result.algorithm": {"fullname": "causy.models.Result.algorithm", "modulename": "causy.models", "qualname": "Result.algorithm", "kind": "variable", "doc": "

\n", "annotation": ": causy.models.AlgorithmReference"}, "causy.models.Result.created_at": {"fullname": "causy.models.Result.created_at", "modulename": "causy.models", "qualname": "Result.created_at", "kind": "variable", "doc": "

\n", "annotation": ": datetime.datetime"}, "causy.models.Result.nodes": {"fullname": "causy.models.Result.nodes", "modulename": "causy.models", "qualname": "Result.nodes", "kind": "variable", "doc": "

\n", "annotation": ": Dict[str, causy.interfaces.NodeInterface]"}, "causy.models.Result.edges": {"fullname": "causy.models.Result.edges", "modulename": "causy.models", "qualname": "Result.edges", "kind": "variable", "doc": "

\n", "annotation": ": List[causy.interfaces.EdgeInterface]"}, "causy.models.Result.action_history": {"fullname": "causy.models.Result.action_history", "modulename": "causy.models", "qualname": "Result.action_history", "kind": "variable", "doc": "

\n", "annotation": ": List[causy.models.ActionHistoryStep]"}, "causy.models.Result.variables": {"fullname": "causy.models.Result.variables", "modulename": "causy.models", "qualname": "Result.variables", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict[str, Any]]"}, "causy.models.Result.data_loader_hash": {"fullname": "causy.models.Result.data_loader_hash", "modulename": "causy.models", "qualname": "Result.data_loader_hash", "kind": "variable", "doc": "

\n", "annotation": ": Optional[str]"}, "causy.models.Result.algorithm_hash": {"fullname": "causy.models.Result.algorithm_hash", "modulename": "causy.models", "qualname": "Result.algorithm_hash", "kind": "variable", "doc": "

\n", "annotation": ": Optional[str]"}, "causy.models.Result.variables_hash": {"fullname": "causy.models.Result.variables_hash", "modulename": "causy.models", "qualname": "Result.variables_hash", "kind": "variable", "doc": "

\n", "annotation": ": Optional[str]"}, "causy.models.Result.model_config": {"fullname": "causy.models.Result.model_config", "modulename": "causy.models", "qualname": "Result.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.models.Result.model_fields": {"fullname": "causy.models.Result.model_fields", "modulename": "causy.models", "qualname": "Result.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'algorithm': FieldInfo(annotation=AlgorithmReference, required=True), 'created_at': FieldInfo(annotation=datetime, required=False, default_factory=builtin_function_or_method), 'nodes': FieldInfo(annotation=Dict[str, NodeInterface], required=True), 'edges': FieldInfo(annotation=List[EdgeInterface], required=True), 'action_history': FieldInfo(annotation=List[ActionHistoryStep], required=True), 'variables': FieldInfo(annotation=Union[Dict[str, Any], NoneType], required=False, default=None), 'data_loader_hash': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'algorithm_hash': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'variables_hash': FieldInfo(annotation=Union[str, NoneType], required=False, default=None)}"}, "causy.models.Result.model_computed_fields": {"fullname": "causy.models.Result.model_computed_fields", "modulename": "causy.models", "qualname": "Result.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.sample_generator": {"fullname": "causy.sample_generator", "modulename": "causy.sample_generator", "kind": "module", "doc": "

\n"}, "causy.sample_generator.logger": {"fullname": "causy.sample_generator.logger", "modulename": "causy.sample_generator", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.sample_generator (WARNING)>"}, "causy.sample_generator.random_normal": {"fullname": "causy.sample_generator.random_normal", "modulename": "causy.sample_generator", "qualname": "random_normal", "kind": "function", "doc": "

Returns a random number from a normal distribution

\n\n
Returns
\n\n
\n

the random number as a float

\n
\n", "signature": "() -> float:", "funcdef": "def"}, "causy.sample_generator.NodeReference": {"fullname": "causy.sample_generator.NodeReference", "modulename": "causy.sample_generator", "qualname": "NodeReference", "kind": "class", "doc": "

A reference to a node in the sample generator

\n"}, "causy.sample_generator.NodeReference.__init__": {"fullname": "causy.sample_generator.NodeReference.__init__", "modulename": "causy.sample_generator", "qualname": "NodeReference.__init__", "kind": "function", "doc": "

\n", "signature": "(node: str)"}, "causy.sample_generator.NodeReference.node": {"fullname": "causy.sample_generator.NodeReference.node", "modulename": "causy.sample_generator", "qualname": "NodeReference.node", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.sample_generator.TimeAwareNodeReference": {"fullname": "causy.sample_generator.TimeAwareNodeReference", "modulename": "causy.sample_generator", "qualname": "TimeAwareNodeReference", "kind": "class", "doc": "

A reference to a node in the sample generator

\n", "bases": "NodeReference"}, "causy.sample_generator.TimeAwareNodeReference.__init__": {"fullname": "causy.sample_generator.TimeAwareNodeReference.__init__", "modulename": "causy.sample_generator", "qualname": "TimeAwareNodeReference.__init__", "kind": "function", "doc": "

\n", "signature": "(node: str, point_in_time: int = 0)"}, "causy.sample_generator.TimeAwareNodeReference.point_in_time": {"fullname": "causy.sample_generator.TimeAwareNodeReference.point_in_time", "modulename": "causy.sample_generator", "qualname": "TimeAwareNodeReference.point_in_time", "kind": "variable", "doc": "

\n", "annotation": ": int", "default_value": "0"}, "causy.sample_generator.SampleEdge": {"fullname": "causy.sample_generator.SampleEdge", "modulename": "causy.sample_generator", "qualname": "SampleEdge", "kind": "class", "doc": "

An edge in the sample generator that references a node and a lag

\n"}, "causy.sample_generator.SampleEdge.__init__": {"fullname": "causy.sample_generator.SampleEdge.__init__", "modulename": "causy.sample_generator", "qualname": "SampleEdge.__init__", "kind": "function", "doc": "

\n", "signature": "(\tfrom_node: causy.sample_generator.NodeReference,\tto_node: causy.sample_generator.NodeReference,\tvalue: float = 0)"}, "causy.sample_generator.SampleEdge.from_node": {"fullname": "causy.sample_generator.SampleEdge.from_node", "modulename": "causy.sample_generator", "qualname": "SampleEdge.from_node", "kind": "variable", "doc": "

\n", "annotation": ": causy.sample_generator.NodeReference"}, "causy.sample_generator.SampleEdge.to_node": {"fullname": "causy.sample_generator.SampleEdge.to_node", "modulename": "causy.sample_generator", "qualname": "SampleEdge.to_node", "kind": "variable", "doc": "

\n", "annotation": ": causy.sample_generator.NodeReference"}, "causy.sample_generator.SampleEdge.value": {"fullname": "causy.sample_generator.SampleEdge.value", "modulename": "causy.sample_generator", "qualname": "SampleEdge.value", "kind": "variable", "doc": "

\n", "annotation": ": float", "default_value": "0"}, "causy.sample_generator.TimeTravelingError": {"fullname": "causy.sample_generator.TimeTravelingError", "modulename": "causy.sample_generator", "qualname": "TimeTravelingError", "kind": "class", "doc": "

An error that is raised when a TimeProxy tries to access a value from the future

\n", "bases": "builtins.Exception"}, "causy.sample_generator.AbstractSampleGenerator": {"fullname": "causy.sample_generator.AbstractSampleGenerator", "modulename": "causy.sample_generator", "qualname": "AbstractSampleGenerator", "kind": "class", "doc": "

Helper class that provides a standard way to create an ABC using\ninheritance.

\n", "bases": "abc.ABC"}, "causy.sample_generator.AbstractSampleGenerator.random_fn": {"fullname": "causy.sample_generator.AbstractSampleGenerator.random_fn", "modulename": "causy.sample_generator", "qualname": "AbstractSampleGenerator.random_fn", "kind": "variable", "doc": "

\n"}, "causy.sample_generator.AbstractSampleGenerator.generate": {"fullname": "causy.sample_generator.AbstractSampleGenerator.generate", "modulename": "causy.sample_generator", "qualname": "AbstractSampleGenerator.generate", "kind": "function", "doc": "

Generate data for a sample graph with a time dimension

\n\n
Parameters
\n\n
    \n
  • size: the number of time steps to generate
    • \n
\n\n
Returns
\n\n
\n

the generated data and the sample graph

\n
\n", "signature": "(self, size: int) -> types.SimpleNamespace:", "funcdef": "def"}, "causy.sample_generator.IIDSampleGenerator": {"fullname": "causy.sample_generator.IIDSampleGenerator", "modulename": "causy.sample_generator", "qualname": "IIDSampleGenerator", "kind": "class", "doc": "

A sample generator that generates data from i.i.d multivariate Gaussians.

\n\n

A variable can not depend on itself.

\n\n

Example:

\n\n
\n
>>> sg = IIDSampleGenerator(\n>>>     edges=[\n>>>      SampleEdge(NodeReference("X"), NodeReference("Y"), 5),\n>>>      SampleEdge(NodeReference("Y"), NodeReference("Z"), 7),\n>>>      ],\n>>> )\n
\n
\n", "bases": "AbstractSampleGenerator"}, "causy.sample_generator.IIDSampleGenerator.__init__": {"fullname": "causy.sample_generator.IIDSampleGenerator.__init__", "modulename": "causy.sample_generator", "qualname": "IIDSampleGenerator.__init__", "kind": "function", "doc": "

\n", "signature": "(\tedges: List[causy.sample_generator.SampleEdge],\trandom: Callable = <function random_normal>)"}, "causy.sample_generator.IIDSampleGenerator.topologic_sort": {"fullname": "causy.sample_generator.IIDSampleGenerator.topologic_sort", "modulename": "causy.sample_generator", "qualname": "IIDSampleGenerator.topologic_sort", "kind": "function", "doc": "

Sorts the nodes topologically

\n\n
Parameters
\n\n
    \n
  • nodes: list of nodes
    • \n
  • edges: list of edges
    • \n
\n\n
Returns
\n\n
\n

a list of sorted nodes

\n
\n", "signature": "(self, nodes: List[str]):", "funcdef": "def"}, "causy.sample_generator.IIDSampleGenerator.generate": {"fullname": "causy.sample_generator.IIDSampleGenerator.generate", "modulename": "causy.sample_generator", "qualname": "IIDSampleGenerator.generate", "kind": "function", "doc": "

Generate data for a sample graph with a time dimension

\n\n
Parameters
\n\n
    \n
  • size: the number of time steps to generate
    • \n
\n\n
Returns
\n\n
\n

the generated data and the sample graph

\n
\n", "signature": "(self, size):", "funcdef": "def"}, "causy.sample_generator.TimeseriesSampleGenerator": {"fullname": "causy.sample_generator.TimeseriesSampleGenerator", "modulename": "causy.sample_generator", "qualname": "TimeseriesSampleGenerator", "kind": "class", "doc": "

A sample generator that generates data for a sample graph with a time dimension.

\n\n

Edges are defined as SampleLaggedEdges, which define a directed edge from a source node to a target node with a\nag. The lag is the number of time steps between the source and the target.

\n\n

A variable can depend on itself, but only on its past values (with a lag). This corresponds to autoregressive models.

\n\n

Example:

\n\n
\n
>>> sg = TimeseriesSampleGenerator(\n>>>     edges=[\n>>>      SampleEdge(TimeAwareNodeReference("X", -1), TimeAwareNodeReference("X"), 0.9),\n>>>      SampleEdge(TimeAwareNodeReference("Y", -1), TimeAwareNodeReference("Y"), 0.9),\n>>>      SampleEdge(TimeAwareNodeReference("Z", -1), TimeAwareNodeReference("Z"), 0.9),\n>>>      SampleEdge(TimeAwareNodeReference("Z", -1), TimeAwareNodeReference("Y"), 5),\n>>>      SampleEdge(TimeAwareNodeReference("Y", -1), TimeAwareNodeReference("X"), 7),\n>>>      ],\n>>> )\n
\n
\n", "bases": "AbstractSampleGenerator"}, "causy.sample_generator.TimeseriesSampleGenerator.__init__": {"fullname": "causy.sample_generator.TimeseriesSampleGenerator.__init__", "modulename": "causy.sample_generator", "qualname": "TimeseriesSampleGenerator.__init__", "kind": "function", "doc": "

\n", "signature": "(\tedges: List[causy.sample_generator.SampleEdge],\trandom: Callable = <function random_normal>)"}, "causy.sample_generator.TimeseriesSampleGenerator.generate": {"fullname": "causy.sample_generator.TimeseriesSampleGenerator.generate", "modulename": "causy.sample_generator", "qualname": "TimeseriesSampleGenerator.generate", "kind": "function", "doc": "

Generate data for a sample graph with a time dimension

\n\n
Parameters
\n\n
    \n
  • size: the number of time steps to generate
    • \n
\n\n
Returns
\n\n
\n

the generated data and the sample graph

\n
\n", "signature": "(self, size):", "funcdef": "def"}, "causy.sample_generator.TimeseriesSampleGenerator.custom_block_diagonal": {"fullname": "causy.sample_generator.TimeseriesSampleGenerator.custom_block_diagonal", "modulename": "causy.sample_generator", "qualname": "TimeseriesSampleGenerator.custom_block_diagonal", "kind": "function", "doc": "

\n", "signature": "(self, matrices):", "funcdef": "def"}, "causy.sample_generator.TimeseriesSampleGenerator.vectorize_identity_block": {"fullname": "causy.sample_generator.TimeseriesSampleGenerator.vectorize_identity_block", "modulename": "causy.sample_generator", "qualname": "TimeseriesSampleGenerator.vectorize_identity_block", "kind": "function", "doc": "

\n", "signature": "(self, n):", "funcdef": "def"}, "causy.serialization": {"fullname": "causy.serialization", "modulename": "causy.serialization", "kind": "module", "doc": "

\n"}, "causy.serialization.serialize_algorithm": {"fullname": "causy.serialization.serialize_algorithm", "modulename": "causy.serialization", "qualname": "serialize_algorithm", "kind": "function", "doc": "

Serialize the model into a dictionary.

\n", "signature": "(model, algorithm_name: str = None):", "funcdef": "def"}, "causy.serialization.load_algorithm_from_specification": {"fullname": "causy.serialization.load_algorithm_from_specification", "modulename": "causy.serialization", "qualname": "load_algorithm_from_specification", "kind": "function", "doc": "

Load the model from a dictionary.

\n", "signature": "(algorithm_dict: Dict[str, Any]):", "funcdef": "def"}, "causy.serialization.load_algorithm_by_reference": {"fullname": "causy.serialization.load_algorithm_by_reference", "modulename": "causy.serialization", "qualname": "load_algorithm_by_reference", "kind": "function", "doc": "

\n", "signature": "(reference_type: str, algorithm: str):", "funcdef": "def"}, "causy.serialization.CausyJSONEncoder": {"fullname": "causy.serialization.CausyJSONEncoder", "modulename": "causy.serialization", "qualname": "CausyJSONEncoder", "kind": "class", "doc": "

Extensible JSON https://json.org encoder for Python data structures.

\n\n

Supports the following objects and types by default:

\n\n

+-------------------+---------------+\n| Python | JSON |\n+===================+===============+\n| dict | object |\n+-------------------+---------------+\n| list, tuple | array |\n+-------------------+---------------+\n| str | string |\n+-------------------+---------------+\n| int, float | number |\n+-------------------+---------------+\n| True | true |\n+-------------------+---------------+\n| False | false |\n+-------------------+---------------+\n| None | null |\n+-------------------+---------------+

\n\n

To extend this to recognize other objects, subclass and implement a\n.default() method with another method that returns a serializable\nobject for o if possible, otherwise it should call the superclass\nimplementation (to raise TypeError).

\n", "bases": "json.encoder.JSONEncoder"}, "causy.serialization.CausyJSONEncoder.default": {"fullname": "causy.serialization.CausyJSONEncoder.default", "modulename": "causy.serialization", "qualname": "CausyJSONEncoder.default", "kind": "function", "doc": "

Implement this method in a subclass such that it returns\na serializable object for o, or calls the base implementation\n(to raise a TypeError).

\n\n

For example, to support arbitrary iterators, you could\nimplement default like this::

\n\n
def default(self, o):\n    try:\n        iterable = iter(o)\n    except TypeError:\n        pass\n    else:\n        return list(iterable)\n    # Let the base class default method raise the TypeError\n    return super().default(o)\n
\n", "signature": "(self, obj):", "funcdef": "def"}, "causy.serialization.load_json": {"fullname": "causy.serialization.load_json", "modulename": "causy.serialization", "qualname": "load_json", "kind": "function", "doc": "

\n", "signature": "(pipeline_file: str):", "funcdef": "def"}, "causy.serialization.deserialize_result": {"fullname": "causy.serialization.deserialize_result", "modulename": "causy.serialization", "qualname": "deserialize_result", "kind": "function", "doc": "

Deserialize the result.

\n", "signature": "(result: Dict[str, Any], klass=<class 'causy.models.Result'>):", "funcdef": "def"}, "causy.ui": {"fullname": "causy.ui", "modulename": "causy.ui", "kind": "module", "doc": "

\n"}, "causy.ui.cli": {"fullname": "causy.ui.cli", "modulename": "causy.ui.cli", "kind": "module", "doc": "

\n"}, "causy.ui.cli.ui": {"fullname": "causy.ui.cli.ui", "modulename": "causy.ui.cli", "qualname": "ui", "kind": "function", "doc": "

Start the causy UI.

\n", "signature": "(result_file: str = None):", "funcdef": "def"}, "causy.ui.models": {"fullname": "causy.ui.models", "modulename": "causy.ui.models", "kind": "module", "doc": "

\n"}, "causy.ui.models.NodePosition": {"fullname": "causy.ui.models.NodePosition", "modulename": "causy.ui.models", "qualname": "NodePosition", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel"}, "causy.ui.models.NodePosition.x": {"fullname": "causy.ui.models.NodePosition.x", "modulename": "causy.ui.models", "qualname": "NodePosition.x", "kind": "variable", "doc": "

\n", "annotation": ": Optional[float]"}, "causy.ui.models.NodePosition.y": {"fullname": "causy.ui.models.NodePosition.y", "modulename": "causy.ui.models", "qualname": "NodePosition.y", "kind": "variable", "doc": "

\n", "annotation": ": Optional[float]"}, "causy.ui.models.NodePosition.model_config": {"fullname": "causy.ui.models.NodePosition.model_config", "modulename": "causy.ui.models", "qualname": "NodePosition.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.ui.models.NodePosition.model_fields": {"fullname": "causy.ui.models.NodePosition.model_fields", "modulename": "causy.ui.models", "qualname": "NodePosition.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'x': FieldInfo(annotation=Union[float, NoneType], required=True), 'y': FieldInfo(annotation=Union[float, NoneType], required=True)}"}, "causy.ui.models.NodePosition.model_computed_fields": {"fullname": "causy.ui.models.NodePosition.model_computed_fields", "modulename": "causy.ui.models", "qualname": "NodePosition.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.ui.models.ExperimentVersion": {"fullname": "causy.ui.models.ExperimentVersion", "modulename": "causy.ui.models", "qualname": "ExperimentVersion", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel"}, "causy.ui.models.ExperimentVersion.version": {"fullname": "causy.ui.models.ExperimentVersion.version", "modulename": "causy.ui.models", "qualname": "ExperimentVersion.version", "kind": "variable", "doc": "

\n", "annotation": ": int"}, "causy.ui.models.ExperimentVersion.name": {"fullname": "causy.ui.models.ExperimentVersion.name", "modulename": "causy.ui.models", "qualname": "ExperimentVersion.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.ui.models.ExperimentVersion.model_config": {"fullname": "causy.ui.models.ExperimentVersion.model_config", "modulename": "causy.ui.models", "qualname": "ExperimentVersion.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.ui.models.ExperimentVersion.model_fields": {"fullname": "causy.ui.models.ExperimentVersion.model_fields", "modulename": "causy.ui.models", "qualname": "ExperimentVersion.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'version': FieldInfo(annotation=int, required=True), 'name': FieldInfo(annotation=str, required=True)}"}, "causy.ui.models.ExperimentVersion.model_computed_fields": {"fullname": "causy.ui.models.ExperimentVersion.model_computed_fields", "modulename": "causy.ui.models", "qualname": "ExperimentVersion.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.ui.models.ExtendedExperiment": {"fullname": "causy.ui.models.ExtendedExperiment", "modulename": "causy.ui.models", "qualname": "ExtendedExperiment", "kind": "class", "doc": "

represents a single experiment

\n\n
Parameters
\n\n
    \n
  • name: name of the experiment
    • \n
  • pipeline: the name of the pipeline used
    • \n
\n", "bases": "causy.workspaces.models.Experiment"}, "causy.ui.models.ExtendedExperiment.versions": {"fullname": "causy.ui.models.ExtendedExperiment.versions", "modulename": "causy.ui.models", "qualname": "ExtendedExperiment.versions", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[causy.ui.models.ExperimentVersion]]"}, "causy.ui.models.ExtendedExperiment.name": {"fullname": "causy.ui.models.ExtendedExperiment.name", "modulename": "causy.ui.models", "qualname": "ExtendedExperiment.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.ui.models.ExtendedExperiment.model_config": {"fullname": "causy.ui.models.ExtendedExperiment.model_config", "modulename": "causy.ui.models", "qualname": "ExtendedExperiment.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.ui.models.ExtendedExperiment.model_fields": {"fullname": "causy.ui.models.ExtendedExperiment.model_fields", "modulename": "causy.ui.models", "qualname": "ExtendedExperiment.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'pipeline': FieldInfo(annotation=str, required=True), 'dataloader': FieldInfo(annotation=str, required=True), 'variables': FieldInfo(annotation=Union[Dict[str, Union[str, int, float, bool]], NoneType], required=False, default={}), 'versions': FieldInfo(annotation=Union[List[ExperimentVersion], NoneType], required=False, default=None), 'name': FieldInfo(annotation=str, required=False, default=None)}"}, "causy.ui.models.ExtendedExperiment.model_computed_fields": {"fullname": "causy.ui.models.ExtendedExperiment.model_computed_fields", "modulename": "causy.ui.models", "qualname": "ExtendedExperiment.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.ui.models.PositionedNode": {"fullname": "causy.ui.models.PositionedNode", "modulename": "causy.ui.models", "qualname": "PositionedNode", "kind": "class", "doc": "

Node interface for the graph. A node is defined by a name and a value.

\n", "bases": "causy.interfaces.NodeInterface"}, "causy.ui.models.PositionedNode.position": {"fullname": "causy.ui.models.PositionedNode.position", "modulename": "causy.ui.models", "qualname": "PositionedNode.position", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.ui.models.NodePosition]"}, "causy.ui.models.PositionedNode.model_config": {"fullname": "causy.ui.models.PositionedNode.model_config", "modulename": "causy.ui.models", "qualname": "PositionedNode.model_config", "kind": "variable", "doc": "

\n", "default_value": "{'arbitrary_types_allowed': True}"}, "causy.ui.models.PositionedNode.model_fields": {"fullname": "causy.ui.models.PositionedNode.model_fields", "modulename": "causy.ui.models", "qualname": "PositionedNode.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'name': FieldInfo(annotation=str, required=True), 'id': FieldInfo(annotation=str, required=True), 'values': FieldInfo(annotation=Union[DoubleTensor, NoneType], required=False, default=None, exclude=True, metadata=[WithJsonSchema(json_schema={'type': 'array', 'items': {'type': 'number'}, 'description': 'Node values'}, mode=None)]), 'position': FieldInfo(annotation=Union[NodePosition, NoneType], required=False, default=None)}"}, "causy.ui.models.PositionedNode.model_computed_fields": {"fullname": "causy.ui.models.PositionedNode.model_computed_fields", "modulename": "causy.ui.models", "qualname": "PositionedNode.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.ui.models.ExtendedResult": {"fullname": "causy.ui.models.ExtendedResult", "modulename": "causy.ui.models", "qualname": "ExtendedResult", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "causy.models.Result"}, "causy.ui.models.ExtendedResult.nodes": {"fullname": "causy.ui.models.ExtendedResult.nodes", "modulename": "causy.ui.models", "qualname": "ExtendedResult.nodes", "kind": "variable", "doc": "

\n", "annotation": ": Dict[Union[Annotated[uuid.UUID, UuidVersion(uuid_version=4)], str], causy.ui.models.PositionedNode]"}, "causy.ui.models.ExtendedResult.version": {"fullname": "causy.ui.models.ExtendedResult.version", "modulename": "causy.ui.models", "qualname": "ExtendedResult.version", "kind": "variable", "doc": "

\n", "annotation": ": Optional[int]"}, "causy.ui.models.ExtendedResult.model_config": {"fullname": "causy.ui.models.ExtendedResult.model_config", "modulename": "causy.ui.models", "qualname": "ExtendedResult.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.ui.models.ExtendedResult.model_fields": {"fullname": "causy.ui.models.ExtendedResult.model_fields", "modulename": "causy.ui.models", "qualname": "ExtendedResult.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'algorithm': FieldInfo(annotation=AlgorithmReference, required=True), 'created_at': FieldInfo(annotation=datetime, required=False, default_factory=builtin_function_or_method), 'nodes': FieldInfo(annotation=Dict[Union[Annotated[UUID, UuidVersion], str], PositionedNode], required=True), 'edges': FieldInfo(annotation=List[EdgeInterface], required=True), 'action_history': FieldInfo(annotation=List[ActionHistoryStep], required=True), 'variables': FieldInfo(annotation=Union[Dict[str, Any], NoneType], required=False, default=None), 'data_loader_hash': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'algorithm_hash': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'variables_hash': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'version': FieldInfo(annotation=Union[int, NoneType], required=False, default=None)}"}, "causy.ui.models.ExtendedResult.model_computed_fields": {"fullname": "causy.ui.models.ExtendedResult.model_computed_fields", "modulename": "causy.ui.models", "qualname": "ExtendedResult.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.ui.server": {"fullname": "causy.ui.server", "modulename": "causy.ui.server", "kind": "module", "doc": "

\n"}, "causy.ui.server.logger": {"fullname": "causy.ui.server.logger", "modulename": "causy.ui.server", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.ui.server (WARNING)>"}, "causy.ui.server.API_ROUTES": {"fullname": "causy.ui.server.API_ROUTES", "modulename": "causy.ui.server", "qualname": "API_ROUTES", "kind": "variable", "doc": "

\n", "default_value": "<fastapi.routing.APIRouter object>"}, "causy.ui.server.MODEL": {"fullname": "causy.ui.server.MODEL", "modulename": "causy.ui.server", "qualname": "MODEL", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.ui.models.ExtendedResult]", "default_value": "None"}, "causy.ui.server.WORKSPACE": {"fullname": "causy.ui.server.WORKSPACE", "modulename": "causy.ui.server", "qualname": "WORKSPACE", "kind": "variable", "doc": "

\n", "annotation": ": Optional[causy.workspaces.models.Workspace]", "default_value": "None"}, "causy.ui.server.get_status": {"fullname": "causy.ui.server.get_status", "modulename": "causy.ui.server", "qualname": "get_status", "kind": "function", "doc": "

Get the current status of the API.

\n", "signature": "():", "funcdef": "async def"}, "causy.ui.server.get_model": {"fullname": "causy.ui.server.get_model", "modulename": "causy.ui.server", "qualname": "get_model", "kind": "function", "doc": "

Get the current model.

\n", "signature": "():", "funcdef": "async def"}, "causy.ui.server.get_workspace": {"fullname": "causy.ui.server.get_workspace", "modulename": "causy.ui.server", "qualname": "get_workspace", "kind": "function", "doc": "

\n", "signature": "():", "funcdef": "async def"}, "causy.ui.server.get_latest_experiment": {"fullname": "causy.ui.server.get_latest_experiment", "modulename": "causy.ui.server", "qualname": "get_latest_experiment", "kind": "function", "doc": "

Get the current experiment.

\n", "signature": "(experiment_name: str):", "funcdef": "async def"}, "causy.ui.server.get_experiment": {"fullname": "causy.ui.server.get_experiment", "modulename": "causy.ui.server", "qualname": "get_experiment", "kind": "function", "doc": "

Get the current experiment.

\n", "signature": "(experiment_name: str, version_number: int):", "funcdef": "async def"}, "causy.ui.server.get_experiments": {"fullname": "causy.ui.server.get_experiments", "modulename": "causy.ui.server", "qualname": "get_experiments", "kind": "function", "doc": "

Get the current experiment.

\n", "signature": "():", "funcdef": "async def"}, "causy.ui.server.get_algorithm": {"fullname": "causy.ui.server.get_algorithm", "modulename": "causy.ui.server", "qualname": "get_algorithm", "kind": "function", "doc": "

Get the current algorithm.

\n", "signature": "(reference_type: str, reference: str):", "funcdef": "async def"}, "causy.ui.server.is_port_in_use": {"fullname": "causy.ui.server.is_port_in_use", "modulename": "causy.ui.server", "qualname": "is_port_in_use", "kind": "function", "doc": "

\n", "signature": "(host: str, port: int) -> bool:", "funcdef": "def"}, "causy.ui.server.server": {"fullname": "causy.ui.server.server", "modulename": "causy.ui.server", "qualname": "server", "kind": "function", "doc": "

Create the FastAPI server.

\n", "signature": "(\tresult: Dict[str, Any] = None,\tworkspace: causy.workspaces.models.Workspace = None):", "funcdef": "def"}, "causy.variables": {"fullname": "causy.variables", "modulename": "causy.variables", "kind": "module", "doc": "

\n"}, "causy.variables.VariableType": {"fullname": "causy.variables.VariableType", "modulename": "causy.variables", "qualname": "VariableType", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[str, int, float, bool]"}, "causy.variables.VariableTypes": {"fullname": "causy.variables.VariableTypes", "modulename": "causy.variables", "qualname": "VariableTypes", "kind": "class", "doc": "

\n", "bases": "enum.Enum"}, "causy.variables.VariableTypes.String": {"fullname": "causy.variables.VariableTypes.String", "modulename": "causy.variables", "qualname": "VariableTypes.String", "kind": "variable", "doc": "

\n", "default_value": "<VariableTypes.String: 'string'>"}, "causy.variables.VariableTypes.Integer": {"fullname": "causy.variables.VariableTypes.Integer", "modulename": "causy.variables", "qualname": "VariableTypes.Integer", "kind": "variable", "doc": "

\n", "default_value": "<VariableTypes.Integer: 'integer'>"}, "causy.variables.VariableTypes.Float": {"fullname": "causy.variables.VariableTypes.Float", "modulename": "causy.variables", "qualname": "VariableTypes.Float", "kind": "variable", "doc": "

\n", "default_value": "<VariableTypes.Float: 'float'>"}, "causy.variables.VariableTypes.Bool": {"fullname": "causy.variables.VariableTypes.Bool", "modulename": "causy.variables", "qualname": "VariableTypes.Bool", "kind": "variable", "doc": "

\n", "default_value": "<VariableTypes.Bool: 'bool'>"}, "causy.variables.BaseVariable": {"fullname": "causy.variables.BaseVariable", "modulename": "causy.variables", "qualname": "BaseVariable", "kind": "class", "doc": "

Represents a single variable. It can be a string, int, float or bool. The type of the variable is determined by the\ntype attribute.

\n", "bases": "pydantic.main.BaseModel, typing.Generic[~VariableInterfaceType]"}, "causy.variables.BaseVariable.name": {"fullname": "causy.variables.BaseVariable.name", "modulename": "causy.variables", "qualname": "BaseVariable.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.variables.BaseVariable.value": {"fullname": "causy.variables.BaseVariable.value", "modulename": "causy.variables", "qualname": "BaseVariable.value", "kind": "variable", "doc": "

\n", "annotation": ": Union[str, int, float, bool]"}, "causy.variables.BaseVariable.choices": {"fullname": "causy.variables.BaseVariable.choices", "modulename": "causy.variables", "qualname": "BaseVariable.choices", "kind": "variable", "doc": "

\n", "annotation": ": Optional[List[Union[str, int, float, bool]]]"}, "causy.variables.BaseVariable.is_valid": {"fullname": "causy.variables.BaseVariable.is_valid", "modulename": "causy.variables", "qualname": "BaseVariable.is_valid", "kind": "function", "doc": "

\n", "signature": "(self):", "funcdef": "def"}, "causy.variables.BaseVariable.is_valid_value": {"fullname": "causy.variables.BaseVariable.is_valid_value", "modulename": "causy.variables", "qualname": "BaseVariable.is_valid_value", "kind": "function", "doc": "

\n", "signature": "(self, value):", "funcdef": "def"}, "causy.variables.BaseVariable.validate_value": {"fullname": "causy.variables.BaseVariable.validate_value", "modulename": "causy.variables", "qualname": "BaseVariable.validate_value", "kind": "function", "doc": "

\n", "signature": "(self, value):", "funcdef": "def"}, "causy.variables.BaseVariable.type": {"fullname": "causy.variables.BaseVariable.type", "modulename": "causy.variables", "qualname": "BaseVariable.type", "kind": "variable", "doc": "

\n", "annotation": ": Optional[str]"}, "causy.variables.StringVariable": {"fullname": "causy.variables.StringVariable", "modulename": "causy.variables", "qualname": "StringVariable", "kind": "class", "doc": "

Represents a single string variable.

\n", "bases": "BaseVariable, typing.Generic[~VariableInterfaceType]"}, "causy.variables.StringVariable.model_post_init": {"fullname": "causy.variables.StringVariable.model_post_init", "modulename": "causy.variables", "qualname": "StringVariable.model_post_init", "kind": "function", "doc": "

This function is meant to behave like a BaseModel method to initialise private attributes.

\n\n

It takes context as an argument since that's what pydantic-core passes when calling it.

\n\n

Args:\n self: The BaseModel instance.\n context: The context.

\n", "signature": "(self: pydantic.main.BaseModel, context: Any, /) -> None:", "funcdef": "def"}, "causy.variables.IntegerVariable": {"fullname": "causy.variables.IntegerVariable", "modulename": "causy.variables", "qualname": "IntegerVariable", "kind": "class", "doc": "

Represents a single int variable.

\n", "bases": "BaseVariable, typing.Generic[~VariableInterfaceType]"}, "causy.variables.IntegerVariable.model_post_init": {"fullname": "causy.variables.IntegerVariable.model_post_init", "modulename": "causy.variables", "qualname": "IntegerVariable.model_post_init", "kind": "function", "doc": "

This function is meant to behave like a BaseModel method to initialise private attributes.

\n\n

It takes context as an argument since that's what pydantic-core passes when calling it.

\n\n

Args:\n self: The BaseModel instance.\n context: The context.

\n", "signature": "(self: pydantic.main.BaseModel, context: Any, /) -> None:", "funcdef": "def"}, "causy.variables.FloatVariable": {"fullname": "causy.variables.FloatVariable", "modulename": "causy.variables", "qualname": "FloatVariable", "kind": "class", "doc": "

Represents a single float variable.

\n", "bases": "BaseVariable, typing.Generic[~VariableInterfaceType]"}, "causy.variables.FloatVariable.model_post_init": {"fullname": "causy.variables.FloatVariable.model_post_init", "modulename": "causy.variables", "qualname": "FloatVariable.model_post_init", "kind": "function", "doc": "

This function is meant to behave like a BaseModel method to initialise private attributes.

\n\n

It takes context as an argument since that's what pydantic-core passes when calling it.

\n\n

Args:\n self: The BaseModel instance.\n context: The context.

\n", "signature": "(self: pydantic.main.BaseModel, context: Any, /) -> None:", "funcdef": "def"}, "causy.variables.BoolVariable": {"fullname": "causy.variables.BoolVariable", "modulename": "causy.variables", "qualname": "BoolVariable", "kind": "class", "doc": "

Represents a single bool variable.

\n", "bases": "BaseVariable, typing.Generic[~VariableInterfaceType]"}, "causy.variables.BoolVariable.model_post_init": {"fullname": "causy.variables.BoolVariable.model_post_init", "modulename": "causy.variables", "qualname": "BoolVariable.model_post_init", "kind": "function", "doc": "

This function is meant to behave like a BaseModel method to initialise private attributes.

\n\n

It takes context as an argument since that's what pydantic-core passes when calling it.

\n\n

Args:\n self: The BaseModel instance.\n context: The context.

\n", "signature": "(self: pydantic.main.BaseModel, context: Any, /) -> None:", "funcdef": "def"}, "causy.variables.VariableReference": {"fullname": "causy.variables.VariableReference", "modulename": "causy.variables", "qualname": "VariableReference", "kind": "class", "doc": "

Represents a reference to a variable.

\n", "bases": "pydantic.main.BaseModel, typing.Generic[~VariableInterfaceType]"}, "causy.variables.VariableReference.name": {"fullname": "causy.variables.VariableReference.name", "modulename": "causy.variables", "qualname": "VariableReference.name", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.variables.VariableReference.type": {"fullname": "causy.variables.VariableReference.type", "modulename": "causy.variables", "qualname": "VariableReference.type", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.variables.VARIABLE_MAPPING": {"fullname": "causy.variables.VARIABLE_MAPPING", "modulename": "causy.variables", "qualname": "VARIABLE_MAPPING", "kind": "variable", "doc": "

\n", "default_value": "{'string': <class 'causy.variables.StringVariable'>, 'integer': <class 'causy.variables.IntegerVariable'>, 'float': <class 'causy.variables.FloatVariable'>, 'bool': <class 'causy.variables.BoolVariable'>}"}, "causy.variables.BoolParameter": {"fullname": "causy.variables.BoolParameter", "modulename": "causy.variables", "qualname": "BoolParameter", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[bool, causy.variables.VariableReference]"}, "causy.variables.IntegerParameter": {"fullname": "causy.variables.IntegerParameter", "modulename": "causy.variables", "qualname": "IntegerParameter", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[int, causy.variables.VariableReference]"}, "causy.variables.FloatParameter": {"fullname": "causy.variables.FloatParameter", "modulename": "causy.variables", "qualname": "FloatParameter", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[float, causy.variables.VariableReference]"}, "causy.variables.StringParameter": {"fullname": "causy.variables.StringParameter", "modulename": "causy.variables", "qualname": "StringParameter", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[str, causy.variables.VariableReference]"}, "causy.variables.CausyParameter": {"fullname": "causy.variables.CausyParameter", "modulename": "causy.variables", "qualname": "CausyParameter", "kind": "variable", "doc": "

\n", "default_value": "typing.Union[bool, causy.variables.VariableReference, int, float, str]"}, "causy.variables.validate_variable_values": {"fullname": "causy.variables.validate_variable_values", "modulename": "causy.variables", "qualname": "validate_variable_values", "kind": "function", "doc": "

Validate the variable values for the algorithm.

\n\n
Parameters
\n\n
    \n
  • algorithm:
    • \n
  • variable_values:
    • \n
\n\n
Returns
\n", "signature": "(algorithm, variable_values: Dict[str, Union[str, int, float, bool]]):", "funcdef": "def"}, "causy.variables.resolve_variables": {"fullname": "causy.variables.resolve_variables", "modulename": "causy.variables", "qualname": "resolve_variables", "kind": "function", "doc": "

Resolve the variables from the list of variables and the variable values coming from the user.

\n\n
Parameters
\n\n
    \n
  • variables:
    • \n
  • variable_values:
    • \n
\n\n
Returns
\n", "signature": "(\tvariables: List[causy.variables.BaseVariable],\tvariable_values: Dict[str, Union[str, int, float, bool]]) -> Dict[str, Union[str, int, float, bool]]:", "funcdef": "def"}, "causy.variables.resolve_variable_to_object": {"fullname": "causy.variables.resolve_variable_to_object", "modulename": "causy.variables", "qualname": "resolve_variable_to_object", "kind": "function", "doc": "

Resolve the variables to the object.

\n\n
Parameters
\n\n
    \n
  • obj:
    • \n
  • variables:
    • \n
\n\n
Returns
\n", "signature": "(obj: Any, variables):", "funcdef": "def"}, "causy.variables.resolve_variables_to_algorithm_for_pipeline_steps": {"fullname": "causy.variables.resolve_variables_to_algorithm_for_pipeline_steps", "modulename": "causy.variables", "qualname": "resolve_variables_to_algorithm_for_pipeline_steps", "kind": "function", "doc": "

Resolve the variables to the algorithm.

\n\n
Parameters
\n\n
    \n
  • pipeline_steps:
    • \n
  • variables:
    • \n
\n\n
Returns
\n", "signature": "(pipeline_steps, variables):", "funcdef": "def"}, "causy.variables.deserialize_variable": {"fullname": "causy.variables.deserialize_variable", "modulename": "causy.variables", "qualname": "deserialize_variable", "kind": "function", "doc": "

Deserialize the variable from the dictionary.

\n\n
Parameters
\n\n
    \n
  • variable_dict:
    • \n
\n\n
Returns
\n", "signature": "(\tvariable_dict: Dict[str, Union[str, int, float, bool]]) -> causy.variables.BaseVariable:", "funcdef": "def"}, "causy.variables.deserialize_variable_references": {"fullname": "causy.variables.deserialize_variable_references", "modulename": "causy.variables", "qualname": "deserialize_variable_references", "kind": "function", "doc": "

Deserialize the variable references from the pipeline step.

\n\n
Parameters
\n\n
    \n
  • pipeline_step:
    • \n
\n\n
Returns
\n", "signature": "(element: object) -> object:", "funcdef": "def"}, "causy.workspaces": {"fullname": "causy.workspaces", "modulename": "causy.workspaces", "kind": "module", "doc": "

Representation of a causy workspace.

\n\n

Exemplary folder structure

\n\n
    \n
  • causy.yaml (contains workspace wide settings for stuff like name, author, pipeline definitions)
    • \n
  • any_pipeline.yaml (seperate pipeline definition referenced by causy.yaml)
    • \n
  • custom_pipeline_step.py (a project specific pipeline step)
    • \n
  • some_data_loader.py (a data loader to ship data into causy)
    • \n
  • tune_pipeline_1709406402/ (a single experiment)\n
      \n
    • causy_experiment.json (contains the full definition of everything used)
      • \n
    • causy_model.json (the actual generated model)
      • \n
    • \n
\n\n

Examples

\n\n
    \n
  • the user generates a new workspace because they want to work on a new causal discovery project (causy workspace create)
    • \n
  • they add a custom data loader, pipeline steps and extend an existing pipeline (causy workspace data-loaders create)
    • \n
  • they run multiple experiments (causy workspace experiments create, causy workspace experiments execute $EXPERIMENT_NAME)
    • \n
\n"}, "causy.workspaces.cli": {"fullname": "causy.workspaces.cli", "modulename": "causy.workspaces.cli", "kind": "module", "doc": "

\n"}, "causy.workspaces.cli.workspace_app": {"fullname": "causy.workspaces.cli.workspace_app", "modulename": "causy.workspaces.cli", "qualname": "workspace_app", "kind": "variable", "doc": "

\n", "default_value": "<typer.main.Typer object>"}, "causy.workspaces.cli.pipeline_app": {"fullname": "causy.workspaces.cli.pipeline_app", "modulename": "causy.workspaces.cli", "qualname": "pipeline_app", "kind": "variable", "doc": "

\n", "default_value": "<typer.main.Typer object>"}, "causy.workspaces.cli.experiment_app": {"fullname": "causy.workspaces.cli.experiment_app", "modulename": "causy.workspaces.cli", "qualname": "experiment_app", "kind": "variable", "doc": "

\n", "default_value": "<typer.main.Typer object>"}, "causy.workspaces.cli.dataloader_app": {"fullname": "causy.workspaces.cli.dataloader_app", "modulename": "causy.workspaces.cli", "qualname": "dataloader_app", "kind": "variable", "doc": "

\n", "default_value": "<typer.main.Typer object>"}, "causy.workspaces.cli.logger": {"fullname": "causy.workspaces.cli.logger", "modulename": "causy.workspaces.cli", "qualname": "logger", "kind": "variable", "doc": "

\n", "default_value": "<Logger causy.workspaces.cli (WARNING)>"}, "causy.workspaces.cli.NO_COLOR": {"fullname": "causy.workspaces.cli.NO_COLOR", "modulename": "causy.workspaces.cli", "qualname": "NO_COLOR", "kind": "variable", "doc": "

\n", "default_value": "False"}, "causy.workspaces.cli.WORKSPACE_FILE_NAME": {"fullname": "causy.workspaces.cli.WORKSPACE_FILE_NAME", "modulename": "causy.workspaces.cli", "qualname": "WORKSPACE_FILE_NAME", "kind": "variable", "doc": "

\n", "default_value": "'workspace.yml'"}, "causy.workspaces.cli.JINJA_ENV": {"fullname": "causy.workspaces.cli.JINJA_ENV", "modulename": "causy.workspaces.cli", "qualname": "JINJA_ENV", "kind": "variable", "doc": "

\n", "default_value": "<jinja2.environment.Environment object>"}, "causy.workspaces.cli.WorkspaceNotFoundError": {"fullname": "causy.workspaces.cli.WorkspaceNotFoundError", "modulename": "causy.workspaces.cli", "qualname": "WorkspaceNotFoundError", "kind": "class", "doc": "

Common base class for all non-exit exceptions.

\n", "bases": "builtins.Exception"}, "causy.workspaces.cli.show_error": {"fullname": "causy.workspaces.cli.show_error", "modulename": "causy.workspaces.cli", "qualname": "show_error", "kind": "function", "doc": "

\n", "signature": "(message: str):", "funcdef": "def"}, "causy.workspaces.cli.show_success": {"fullname": "causy.workspaces.cli.show_success", "modulename": "causy.workspaces.cli", "qualname": "show_success", "kind": "function", "doc": "

\n", "signature": "(message: str):", "funcdef": "def"}, "causy.workspaces.cli.write_to_workspace": {"fullname": "causy.workspaces.cli.write_to_workspace", "modulename": "causy.workspaces.cli", "qualname": "write_to_workspace", "kind": "function", "doc": "

\n", "signature": "(workspace: causy.workspaces.models.Workspace):", "funcdef": "def"}, "causy.workspaces.cli.create_pipeline": {"fullname": "causy.workspaces.cli.create_pipeline", "modulename": "causy.workspaces.cli", "qualname": "create_pipeline", "kind": "function", "doc": "

Create a new pipeline in the current workspace.

\n", "signature": "():", "funcdef": "def"}, "causy.workspaces.cli.remove_pipeline": {"fullname": "causy.workspaces.cli.remove_pipeline", "modulename": "causy.workspaces.cli", "qualname": "remove_pipeline", "kind": "function", "doc": "

Remove a pipeline from the current workspace.

\n", "signature": "(pipeline_name: str):", "funcdef": "def"}, "causy.workspaces.cli.create_experiment": {"fullname": "causy.workspaces.cli.create_experiment", "modulename": "causy.workspaces.cli", "qualname": "create_experiment", "kind": "function", "doc": "

Create a new experiment in the current workspace.

\n", "signature": "():", "funcdef": "def"}, "causy.workspaces.cli.remove_experiment": {"fullname": "causy.workspaces.cli.remove_experiment", "modulename": "causy.workspaces.cli", "qualname": "remove_experiment", "kind": "function", "doc": "

Remove an experiment from the current workspace.

\n", "signature": "(experiment_name: str):", "funcdef": "def"}, "causy.workspaces.cli.clear_experiment": {"fullname": "causy.workspaces.cli.clear_experiment", "modulename": "causy.workspaces.cli", "qualname": "clear_experiment", "kind": "function", "doc": "

Clear all versions of an experiment.

\n", "signature": "(experiment_name: str):", "funcdef": "def"}, "causy.workspaces.cli.update_experiment_variable": {"fullname": "causy.workspaces.cli.update_experiment_variable", "modulename": "causy.workspaces.cli", "qualname": "update_experiment_variable", "kind": "function", "doc": "

Update a variable in an experiment.

\n", "signature": "(experiment_name: str, variable_name: str, variable_value: str):", "funcdef": "def"}, "causy.workspaces.cli.create_data_loader": {"fullname": "causy.workspaces.cli.create_data_loader", "modulename": "causy.workspaces.cli", "qualname": "create_data_loader", "kind": "function", "doc": "

Create a new data loader in the current workspace.

\n", "signature": "():", "funcdef": "def"}, "causy.workspaces.cli.remove_data_loader": {"fullname": "causy.workspaces.cli.remove_data_loader", "modulename": "causy.workspaces.cli", "qualname": "remove_data_loader", "kind": "function", "doc": "

Remove a data loader from the current workspace.

\n", "signature": "(data_loader_name: str):", "funcdef": "def"}, "causy.workspaces.cli.info": {"fullname": "causy.workspaces.cli.info", "modulename": "causy.workspaces.cli", "qualname": "info", "kind": "function", "doc": "

Show general information about the workspace.

\n", "signature": "():", "funcdef": "def"}, "causy.workspaces.cli.init": {"fullname": "causy.workspaces.cli.init", "modulename": "causy.workspaces.cli", "qualname": "init", "kind": "function", "doc": "

Initialize a new workspace in the current directory.

\n", "signature": "():", "funcdef": "def"}, "causy.workspaces.cli.execute": {"fullname": "causy.workspaces.cli.execute", "modulename": "causy.workspaces.cli", "qualname": "execute", "kind": "function", "doc": "

Execute an experiment or all experiments in the workspace.

\n", "signature": "(experiment_name: str = None, force_reexecution: bool = False):", "funcdef": "def"}, "causy.workspaces.cli.diff": {"fullname": "causy.workspaces.cli.diff", "modulename": "causy.workspaces.cli", "qualname": "diff", "kind": "function", "doc": "

Show the differences between multiple experiment results.

\n", "signature": "(experiment_names: List[str], only_differences: bool = False):", "funcdef": "def"}, "causy.workspaces.models": {"fullname": "causy.workspaces.models", "modulename": "causy.workspaces.models", "kind": "module", "doc": "

\n"}, "causy.workspaces.models.Experiment": {"fullname": "causy.workspaces.models.Experiment", "modulename": "causy.workspaces.models", "qualname": "Experiment", "kind": "class", "doc": "

represents a single experiment

\n\n
Parameters
\n\n
    \n
  • name: name of the experiment
    • \n
  • pipeline: the name of the pipeline used
    • \n
\n", "bases": "pydantic.main.BaseModel"}, "causy.workspaces.models.Experiment.pipeline": {"fullname": "causy.workspaces.models.Experiment.pipeline", "modulename": "causy.workspaces.models", "qualname": "Experiment.pipeline", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.workspaces.models.Experiment.dataloader": {"fullname": "causy.workspaces.models.Experiment.dataloader", "modulename": "causy.workspaces.models", "qualname": "Experiment.dataloader", "kind": "variable", "doc": "

\n", "annotation": ": str"}, "causy.workspaces.models.Experiment.variables": {"fullname": "causy.workspaces.models.Experiment.variables", "modulename": "causy.workspaces.models", "qualname": "Experiment.variables", "kind": "variable", "doc": "

\n", "annotation": ": Optional[Dict[str, Union[str, int, float, bool]]]"}, "causy.workspaces.models.Experiment.model_config": {"fullname": "causy.workspaces.models.Experiment.model_config", "modulename": "causy.workspaces.models", "qualname": "Experiment.model_config", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.workspaces.models.Experiment.model_fields": {"fullname": "causy.workspaces.models.Experiment.model_fields", "modulename": "causy.workspaces.models", "qualname": "Experiment.model_fields", "kind": "variable", "doc": "

\n", "default_value": "{'pipeline': FieldInfo(annotation=str, required=True), 'dataloader': FieldInfo(annotation=str, required=True), 'variables': FieldInfo(annotation=Union[Dict[str, Union[str, int, float, bool]], NoneType], required=False, default={})}"}, "causy.workspaces.models.Experiment.model_computed_fields": {"fullname": "causy.workspaces.models.Experiment.model_computed_fields", "modulename": "causy.workspaces.models", "qualname": "Experiment.model_computed_fields", "kind": "variable", "doc": "

\n", "default_value": "{}"}, "causy.workspaces.models.Workspace": {"fullname": "causy.workspaces.models.Workspace", "modulename": "causy.workspaces.models", "qualname": "Workspace", "kind": "class", "doc": "

Usage docs: https://docs.pydantic.dev/2.8/concepts/models/

\n\n

A base class for creating Pydantic models.

\n\n

Attributes:\n __class_vars__: The names of classvars defined on the model.\n __private_attributes__: Metadata about the private attributes of the model.\n __signature__: The signature for instantiating the model.

\n\n
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.\n__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.\n__pydantic_custom_init__: Whether the model has a custom `__init__` function.\n__pydantic_decorators__: Metadata containing the decorators defined on the model.\n    This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.\n__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to\n    __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.\n__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.\n__pydantic_post_init__: The name of the post-init method for the model, if defined.\n__pydantic_root_model__: Whether the model is a `RootModel`.\n__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.\n__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.\n\n__pydantic_extra__: An instance attribute with the values of extra fields from validation when\n    `model_config['extra'] == 'allow'`.\n__pydantic_fields_set__: An instance attribute with the names of fields explicitly set.\n__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.\n
\n", "bases": "pydantic.main.BaseModel"}, "causy.workspaces.models.Workspace.name": {"fullname": "causy.workspaces.models.Workspace.name", "modulename": "causy.workspaces.models", "qualname": "Workspace.name", "kind": "variable", "doc": "

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