Remove code needed to support Python < 3.9 and apply ruff's pyupgrade…

… rules (#725)

`math.prod` was added in Python 3.8
`math.lcm` was added in Python 3.9

`pyproject.toml` was updated to have `ruff` also check [pyupgrade rules](https://docs.astral.sh/ruff/rules/#pyupgrade-up)

Authors:
  - Gregory Lee (https://github.com/grlee77)

Approvers:
  - https://github.com/jakirkham

URL: #725

python/cucim/pyproject.toml

@@ -132,7 +132,7 @@ testpaths = [
 
 [tool.ruff]
 # see: https://docs.astral.sh/ruff/rules/
-select = ["E", "F", "W", "I"]
+select = ["E", "F", "W", "I", "UP"]
 fixable = ["ALL"]
 exclude = [
     # TODO: Remove this in a follow-up where we fix __all__.

python/cucim/src/cucim/_misc.py

@@ -1,14 +1,7 @@
 """Misc utility functions that are not from SciPy, NumPy or scikit-image.
 
 """
-import math
-
-import numpy
-
-if hasattr(math, "prod"):
-    prod = math.prod  # available in Python 3.8+ only
-else:
-    prod = numpy.prod
+import numpy as np
 
 
 def ndim(a):
@@ -46,4 +39,4 @@ def ndim(a):
     try:
         return a.ndim
     except AttributeError:
-        return numpy.asarray(a).ndim
+        return np.asarray(a).ndim

python/cucim/src/cucim/clara/converter/tiff.py

@@ -98,7 +98,7 @@ def svs2tif(
         width, height = slide_dimensions
         img_w, img_h = width, height
         for level in range(tiles.level_count):
-            memmap_filename = Path(output_folder, "level{}.mmap".format(level))
+            memmap_filename = Path(output_folder, f"level{level}.mmap")
             memmap_shape = (img_h, img_w, 3)
             np_memmap_arr = np.memmap(
                 memmap_filename, dtype=np.uint8, mode="w+", shape=memmap_shape

python/cucim/src/cucim/core/operations/color/jitter.py

@@ -13,7 +13,7 @@
 # limitations under the License.
 
 import numbers
-from typing import Any, List, Optional, Tuple
+from typing import Any, Optional
 
 import cupy
 import numpy as np
@@ -29,25 +29,19 @@ def _check_input(
     if isinstance(value, numbers.Number):
         if value < 0:
             raise ValueError(
-                "If {} is a single number, \
-                             it must be non negative.".format(
-                    name
-                )
+                f"If {name} is a single number, \
+                             it must be non negative."
             )
         value = [center - float(value), center + float(value)]
         if clip_first_on_zero:
             value[0] = max(value[0], 0.0)
     elif isinstance(value, (tuple, list)) and len(value) == 2:
         if not bound[0] <= value[0] <= value[1] <= bound[1]:
-            raise ValueError(
-                "{} values should be between {}".format(name, bound)
-            )
+            raise ValueError(f"{name} values should be between {bound}")
     else:
         raise TypeError(
-            "{} should be a single number or a \
-                        list/tuple with length 2.".format(
-                name
-            )
+            f"{name} should be a single number or a \
+                        list/tuple with length 2."
         )
     # if value is 0 or (1., 1.) for brightness/contrast/saturation
     # or (0., 0.) for hue, do nothing
@@ -57,11 +51,11 @@ def _check_input(
 
 
 def _get_params(
-    brightness: Optional[List[float]],
-    contrast: Optional[List[float]],
-    saturation: Optional[List[float]],
-    hue: Optional[List[float]],
-) -> Tuple[
+    brightness: Optional[list[float]],
+    contrast: Optional[list[float]],
+    saturation: Optional[list[float]],
+    hue: Optional[list[float]],
+) -> tuple[
     np.ndarray,
     Optional[float],
     Optional[float],
@@ -184,7 +178,7 @@ def _adjust_saturation(input_arr, saturation):
 # hue jitter
 def _adjust_hue(input_arr, hue):
     if not (-0.5 <= hue <= 0.5):
-        raise ValueError("hue factor({}) is not in [-0.5, 0.5].".format(hue))
+        raise ValueError(f"hue factor({hue}) is not in [-0.5, 0.5].")
 
     if len(input_arr.shape) == 4:
         N, C, H, W = input_arr.shape

python/cucim/src/cucim/core/operations/intensity/normalize.py

@@ -12,6 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import math
 from typing import Any
 
 import cupy
@@ -108,7 +109,7 @@ def normalize_data(
     value_range = max_value - min_value
     norm_factor = norm_constant / value_range
 
-    total_size = int(np.prod(img.shape))
+    total_size = int(math.prod(img.shape))
     blockx = 128
     gridx = int((total_size - 1) / blockx + 1)
 

python/cucim/src/cucim/core/operations/intensity/scaling.py

@@ -12,6 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import math
 from typing import Any
 
 import cupy
@@ -100,7 +101,7 @@ def scale_intensity_range(
         b_min = float("-inf")
 
     sh = img.shape
-    total_size = np.prod(sh)
+    total_size = math.prod(sh)
     blockx = 128
     gridx = int((total_size - 1) / blockx + 1)
 

python/cucim/src/cucim/core/operations/intensity/zoom.py

@@ -13,7 +13,8 @@
 # limitations under the License.
 
 import math
-from typing import Any, Sequence, Union
+from collections.abc import Sequence
+from typing import Any, Union
 
 import cupy
 import numpy as np

python/cucim/src/cucim/core/operations/morphology/_pba_2d.py

@@ -1,41 +1,11 @@
-import functools
 import math
-import numbers
 import os
 
 import cupy
 
 from cucim.skimage._vendored import pad
 from cucim.skimage._vendored._ndimage_util import _get_inttype
 
-try:
-    # math.lcm was introduced in Python 3.9
-    from math import lcm
-except ImportError:
-    """Fallback implementation of least common multiple (lcm)
-
-    TODO: remove once minimum Python requirement is >= 3.9
-    """
-
-    def _lcm(a, b):
-        return abs(b * (a // math.gcd(a, b)))
-
-    @functools.lru_cache()
-    def lcm(*args):
-        nargs = len(args)
-        if not all(isinstance(a, numbers.Integral) for a in args):
-            raise TypeError("all arguments must be integers")
-        if nargs == 0:
-            return 1
-        res = int(args[0])
-        if nargs == 1:
-            return abs(res)
-        for i in range(1, nargs):
-            x = int(args[i])
-            res = _lcm(res, x)
-        return res
-
-
 pba2d_defines_template = """
 
 // MARKER is used to mark blank pixels in the texture.
@@ -76,7 +46,7 @@ def get_pba2d_src(block_size_2d=64, marker=-32768, pixel_int2_t="short2"):
         make_pixel_func=make_pixel_func,
     )
     kernel_directory = os.path.join(os.path.dirname(__file__), "cuda")
-    with open(os.path.join(kernel_directory, "pba_kernels_2d.h"), "rt") as f:
+    with open(os.path.join(kernel_directory, "pba_kernels_2d.h")) as f:
         pba2d_kernels = "\n".join(f.readlines())
 
     pba2d_code += pba2d_kernels
@@ -312,7 +282,7 @@ def _pba_2d(
         m1, m2, m3 = block_params
         if math.log2(m2) % 1 > 1e-5:
             raise ValueError("m2 must be a power of 2")
-        multiple = lcm(block_size, m1, m2, m3)
+        multiple = math.lcm(block_size, m1, m2, m3)
         padded_size = math.ceil(max(arr.shape) / multiple) * multiple
 
     if m1 > padded_size // block_size:

python/cucim/src/cucim/core/operations/morphology/_pba_3d.py

@@ -14,7 +14,6 @@
     _generate_indices_ops,
     _generate_shape,
     _get_block_size,
-    lcm,
 )
 
 pba3d_defines_template = """
@@ -85,7 +84,7 @@ def get_pba3d_src(
     else:
         pba3d_code += pba3d_defines_encode_32bit
     kernel_directory = os.path.join(os.path.dirname(__file__), "cuda")
-    with open(os.path.join(kernel_directory, "pba_kernels_3d.h"), "rt") as f:
+    with open(os.path.join(kernel_directory, "pba_kernels_3d.h")) as f:
         pba3d_kernels = "\n".join(f.readlines())
     pba3d_code += pba3d_kernels
     return pba3d_code
@@ -188,7 +187,7 @@ def decode3d(encoded, size_max=1024):
 def _determine_padding(shape, block_size, m1, m2, m3, blockx, blocky):
     # TODO: can possibly revise to consider only particular factors for LCM on
     #       a given axis
-    LCM = lcm(block_size, m1, m2, m3, blockx, blocky)
+    LCM = math.lcm(block_size, m1, m2, m3, blockx, blocky)
     orig_sz, orig_sy, orig_sx = shape
     round_up = False
     if orig_sx % LCM != 0:

python/cucim/src/cucim/skimage/_vendored/_internal.py

@@ -1,7 +1,3 @@
-import math
-from functools import reduce
-from operator import mul
-
 import cupy
 
 # TODO: when minimum numpy dependency is 1.25 use:
@@ -72,11 +68,3 @@ def _normalize_axis_indices(axes, ndim):  # NOQA
             res.append(axis)
 
         return tuple(sorted(res))
-
-
-if hasattr(math, "prod"):
-    prod = math.prod
-else:
-
-    def prod(iterable, *, start=1):
-        return reduce(mul, iterable, start)

python/cucim/src/cucim/skimage/_vendored/_ndimage_filters.py

@@ -1,4 +1,5 @@
 """A vendored subset of cupyx.scipy.ndimage._filters"""
+import math
 import warnings
 
 import cupy
@@ -1181,7 +1182,7 @@ def _get_min_or_max_kernel(
     ctype = "X" if has_weights else "double"
     value = "{value}"
     if not has_weights:
-        value = "cast<double>({})".format(value)
+        value = f"cast<double>({value})"
 
     # Having a non-flat structure biases the values
     if has_structure:
@@ -1386,7 +1387,7 @@ def _rank_filter(
     has_weights = True
     if sizes is not None:
         has_weights = False
-        filter_size = internal.prod(sizes)
+        filter_size = math.prod(sizes)
         if filter_size == 0:
             return cupy.zeros_like(input)
         footprint_shape = tuple(sizes)
@@ -1497,45 +1498,39 @@ def _get_rank_kernel(
         else:
             comp_op = ">"
         array_size = s_rank + 2
-        found_post = """
-            if (iv > {rank} + 1) {{{{
+        found_post = f"""
+            if (iv > {s_rank} + 1) {{{{
                 int target_iv = 0;
                 X target_val = values[0];
-                for (int jv = 1; jv <= {rank} + 1; jv++) {{{{
+                for (int jv = 1; jv <= {s_rank} + 1; jv++) {{{{
                     if (target_val {comp_op} values[jv]) {{{{
                         target_val = values[jv];
                         target_iv = jv;
                     }}}}
                 }}}}
-                if (target_iv <= {rank}) {{{{
-                    values[target_iv] = values[{rank} + 1];
+                if (target_iv <= {s_rank}) {{{{
+                    values[target_iv] = values[{s_rank} + 1];
                 }}}}
-                iv = {rank} + 1;
-            }}}}""".format(
-            rank=s_rank, comp_op=comp_op
-        )
-        post = """
+                iv = {s_rank} + 1;
+            }}}}"""
+        post = f"""
             X target_val = values[0];
-            for (int jv = 1; jv <= {rank}; jv++) {{
+            for (int jv = 1; jv <= {s_rank}; jv++) {{
                 if (target_val {comp_op} values[jv]) {{
                     target_val = values[jv];
                 }}
             }}
-            y=cast<Y>(target_val);""".format(
-            rank=s_rank, comp_op=comp_op
-        )
+            y=cast<Y>(target_val);"""
         sorter = ""
     else:
         array_size = filter_size
         found_post = ""
-        post = "sort(values,{});\ny=cast<Y>(values[{}]);".format(
-            filter_size, rank
-        )
+        post = f"sort(values,{filter_size});\ny=cast<Y>(values[{rank}]);"
         sorter = __SHELL_SORT.format(gap=_get_shell_gap(filter_size))
 
     return _filters_core._generate_nd_kernel(
-        "rank_{}_{}".format(filter_size, rank),
-        "int iv = 0;\nX values[{}];".format(array_size),
+        f"rank_{filter_size}_{rank}",
+        f"int iv = 0;\nX values[{array_size}];",
         "values[iv++] = {value};" + found_post,
         post,
         mode,