mountainsort3.mlp

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dataset in seconds"},{"name":"samplerate"}]},"steps":[{"step_type":"processor","processor_name":"pyms.synthesize_random_waveforms","inputs":{},"outputs":{"waveforms_out":"waveforms_true","geometry_out":"geom"},"parameters":{"upsamplefac":"13"}},{"step_type":"processor","processor_name":"pyms.synthesize_random_firings","inputs":{},"outputs":{"firings_out":"firings_true"},"parameters":{"samplerate":"${samplerate}","duration":"${duration}"}},{"step_type":"processor","processor_name":"pyms.synthesize_timeseries","inputs":{"firings":"firings_true","waveforms":"waveforms_true"},"outputs":{"timeseries_out":"raw"},"parameters":{"duration":"${duration}","waveform_upsamplefac":"13"}},{"step_type":"processor","processor_name":"pyms.synthesize_random_firings","inputs":{},"outputs":{"firings_out":"test_firings","console_out":"test_cons"},"parameters":{"duration":"310"}}],"input_files":[],"output_files":[]},{"name":"sort","script":"/* Define the spec */\ninputs_opt('raw','filt','pre','geom');\noutputs('firings_out');\noutputs_opt('filt_out','pre_out','firings_original_out');\nparam('samplerate',30000);\nparam('freq_min',300);\nparam('freq_max',6000);\nparam('freq_wid',1000);\nparam('whiten','true');\nparam('detect_threshold',3);\nparam('detect_sign',0);\nparam('adjacency_radius',-1);\n\nparam('curate','false');\n      \n\n_Pipeline.run=function(X) {\n  var pp=X.parameters;\n  \n  var pre='pre';\n  if (!X.hasInput('pre')) {\n    \n    var filt='filt';\n    if (!X.hasInput('filt')) {\n      if (!X.hasInput('raw')) {\n        console.error('Missing input: raw, filt or pre');\n        return -1;\n      }\n      X.runProcess('ms3.bandpass_filter',\n                   {timeseries:'raw'},\n                   {timeseries_out:'filt_out'},\n                   {samplerate:pp.samplerate,freq_min:pp.freq_min,freq_max:pp.freq_max,freq_wid:pp.freq_wid}\n                  );\n      filt='filt_out';\n    }\n  \n  \n    if (pp.whiten=='true') {\n      X.runProcess('ms3.whiten',\n                   {timeseries:filt},\n                   {timeseries_out:'pre_out'},\n                   {}\n                  );\n    }\n    else {\n      X.runProcess('pyms.normalize_channels',\n                   {timeseries:'filt'},\n                   {timeseries_out:'pre_out'},\n                   {}\n                  );\n    }\n    pre='pre_out';\n  }\n  \n  \n  var curate=(pp.curate=='true');\n  var firings1='firings_out';\n  if (curate) firings1='firings_original_out';\n  \n  var p={\n    detect_threshold:pp.detect_threshold,\n    detect_sign:pp.detect_sign,\n    adjacency_radius:pp.adjacency_radius\n  };\n  var inputs={timeseries:pre};\n  if (X.hasInput('geom')) {\n    inputs.geom='geom';\n  }\n  X.runProcess('mountainsortalg.ms3',\n               inputs,\n               {firings_out:firings1},\n               p);\n  \n  if (curate) {\n    X.runPipeline('curate',\n               {pre:pre,firings:firings1},\n               {curated_firings:'firings_out'},\n               {samplerate:pp.samplerate});\n  }\n               \n};\n\n/////////////////////////////////////////////////////////////////////\n\n\nfunction param(str,val) {\n      if (val===undefined) {\n        _Pipeline.spec.parameters.push({name:str});\n      }\n      else {\n        _Pipeline.spec.parameters.push({name:str,optional:true,default_value:val});\n      }\n}\n                \nfunction inputs(str1,str2,str3,str4) {\n  if (str1) _Pipeline.spec.inputs.push({name:str1});\n  if (str2) _Pipeline.spec.inputs.push({name:str2});\n  if (str3) _Pipeline.spec.inputs.push({name:str3});\n  if (str4) _Pipeline.spec.inputs.push({name:str4});\n}\n\nfunction inputs_opt(str1,str2,str3,str4) {\n  if (str1) _Pipeline.spec.inputs.push({name:str1,optional:true});\n  if (str2) _Pipeline.spec.inputs.push({name:str2,optional:true});\n  if (str3) _Pipeline.spec.inputs.push({name:str3,optional:true});\n  if (str4) 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