diff --git a/python/1manifoldLearning.py b/python/1manifoldLearning.py index 0e97dd3f..52be82da 100644 --- a/python/1manifoldLearning.py +++ b/python/1manifoldLearning.py @@ -41,7 +41,7 @@ def ThresholdBetween(threshold, lower, upper): # create a new 'Python Calculator' pythonCalculator1 = PythonCalculator(Input=gaussianResampling2) pythonCalculator1.Expression = 'numpy.round_(inputs[0].PointData["SplatterValues"], 6)' -pythonCalculator1.ArrayName = 'SplatterValues' +pythonCalculator1.ArrayName = "SplatterValues" # create a new 'Slice' slice1 = Slice(Input=pythonCalculator1) diff --git a/python/hashes/macOS.json b/python/hashes/macOS.json index 1e675920..66c7d2a4 100644 --- a/python/hashes/macOS.json +++ b/python/hashes/macOS.json @@ -3,10 +3,10 @@ "1manifoldLearningCircles_Generators": "1cab3896cac8deaa160ed47ac9204c4f171b4621", "1manifoldLearning_OutputArc": "4e01e2cf9b1fb4cb2c6d289efe7d731bc57bf406", "2manifoldLearning_OutputSurface": "9718651697bf1e347db4666d6fc4bc0f83a5ba51", - "builtInExample1_CriticalPoints": "ee66975c6a1425cc5e851d5829d6f44f89805ea9", - "builtInExample1_PersistenceCurve": "99718aa7939e105e48add83e6e998b810780084b", - "builtInExample1_PersistenceDiagram": "9eee5e98bbb0e3b0f9a495b697784febd3eaebed", - "builtInExample1_warpedInput": "c01bc9de241e12884aa3cd06e401baeafbe93d37", + "BuiltInExample1_CriticalPoints": "ee66975c6a1425cc5e851d5829d6f44f89805ea9", + "BuiltInExample1_PersistenceCurve": "99718aa7939e105e48add83e6e998b810780084b", + "BuiltInExample1_PersistenceDiagram": "9eee5e98bbb0e3b0f9a495b697784febd3eaebed", + "BuiltInExample1_warpedInput": "c01bc9de241e12884aa3cd06e401baeafbe93d37", "builtInExample2_CarbonAtomsFiberSurface": "878fb9494b7e65c4757198cae6722eb23fd18a7f", "builtInExample2_CarbonAtomsRangePolygon": "128aee0f1c7e12b63bce933d18032c8a3084759b", "builtInExample2_ContinuousScatterPlot": "c2e538807506a5146c0257438a388b06f346007a", @@ -118,8 +118,24 @@ "persistenceClustering2_OutputClustering": "a0e8c1a235c7b63e9722ec6150d97cf36e3e61a7", "persistenceClustering3_OutputClustering": "6a4e1b96f4560217cbdf2c4f7320285e022502c8", "persistenceClustering4_OutputClustering": "00042f8a664fa30b2105ba8b9ed498c5022f0b9b", + "persistenceDiagramClustering_PersistenceDiagramClustering_centroids": "35e37ddc2ac4b31cd668515107d8886deada974d", + "persistenceDiagramClustering_PersistenceDiagramClustering_centroids_0_0": "89f4d390f7ecd58d1c3d65de5f4d91b0faa6410a", + "persistenceDiagramClustering_PersistenceDiagramClustering_centroids_1_0": "7da3233f85d9fc81f25230e337601434e5b21d7f", + "persistenceDiagramClustering_PersistenceDiagramClustering_centroids_2_0": "a613f71c73d894669a8b05ff61ae5ab7bbc9ac1c", + "persistenceDiagramClustering_PersistenceDiagramClustering_clustering": "a2a3ef2dab6ed9b8ed711b035f409119353a3e95", "persistenceDrivenCompression_naturalImage_persistence10_zfp50": "3739e6192201a0a820204fdc99cb889cbbc19323", "persistenceDrivenCompression_uncompressed_naturalImage_persistence10_zfp50": "bdf8e57eed284b94e83fb03f1b36e6fcc0f416fa", + "persistentGenerators_at_PersistentGeneratorsAt": "687bddc30c9a6a6a580322909c88437699325f7b", + "persistentGenerators_casting_PersistentGeneratorsCasting": "5496f3adda1fadaa21d831bb727395d01f93de1a", + "persistentGenerators_darkSky_PersistentGeneratorsDarkSky": "20762847f0afd2c0d030f16014fb4f588c3dc02c", + "persistentGenerators_fertility_PersistentGeneratorsFertility": "7950a60ac2a5ee339983c5d50254d3d64f146f6c", + "persistentGenerators_householdAnalysis_PersistentGeneratorsHouseholdAnalysis_cycle": "385404dd589bc91a3506f1963bfcc2ed945c53ee", + "persistentGenerators_householdAnalysis_PersistentGeneratorsHouseholdAnalysis_points": "a04ce48991918e163c29d228259e49cd2b473d02", + "persistentGenerators_householdAnalysis_PersistentGeneratorsHouseholdAnalysis_ripsComplex": "98ed7d07dab9f6b41108fbc9859cb0e27fa73738", + "persistentGenerators_periodicPicture_PersistentGeneratorsPeriodicPicture_cycle": "d4640bab5966864ebe94e3ca638da22031371981", + "persistentGenerators_periodicPicture_PersistentGeneratorsPeriodicPicture_points": "cf2fa56440302152d26d67d6f161f0954ad36e2f", + "persistentGenerators_periodicPicture_PersistentGeneratorsPeriodicPicture_ripsComplex": "67075b9b4507338ed8c399eee6603f2e99eecdf0", + "persistentGenerators_skull_PersistentGeneratorsSkull": "c3370dacc9104833ec64b36b4b718fea66fbba82", "run01_20_10": "13a315b7d14bad87b71503d8c5a9a6933d28e91f", "run01_30_10": "581f1cb8bdeeacec1ec6c1ed8673e39a295eb40c", "run01_40_10": "60b112f8c52f31b2234fccfbeaf0b076835d7f48", diff --git a/python/hashes/ubuntu-18.04.json b/python/hashes/ubuntu-18.04.json index 696828d4..78cb3d3c 100644 --- a/python/hashes/ubuntu-18.04.json +++ b/python/hashes/ubuntu-18.04.json @@ -3,10 +3,10 @@ "1manifoldLearningCircles_Generators": "1cab3896cac8deaa160ed47ac9204c4f171b4621", "1manifoldLearning_OutputArc": "4e01e2cf9b1fb4cb2c6d289efe7d731bc57bf406", "2manifoldLearning_OutputSurface": "d66fde5fa39b8db0e57a76b6b3815b7ce36f6edd", - "builtInExample1_CriticalPoints": "ee66975c6a1425cc5e851d5829d6f44f89805ea9", - "builtInExample1_PersistenceCurve": "99718aa7939e105e48add83e6e998b810780084b", - "builtInExample1_PersistenceDiagram": "9eee5e98bbb0e3b0f9a495b697784febd3eaebed", - "builtInExample1_warpedInput": "c01bc9de241e12884aa3cd06e401baeafbe93d37", + "BuiltInExample1_CriticalPoints": "ee66975c6a1425cc5e851d5829d6f44f89805ea9", + "BuiltInExample1_PersistenceCurve": "99718aa7939e105e48add83e6e998b810780084b", + "BuiltInExample1_PersistenceDiagram": "9eee5e98bbb0e3b0f9a495b697784febd3eaebed", + "BuiltInExample1_warpedInput": "c01bc9de241e12884aa3cd06e401baeafbe93d37", "builtInExample2_CarbonAtomsFiberSurface": "10dadd8de92ffca9aa9d066ee97bed29f7853eda", "builtInExample2_CarbonAtomsRangePolygon": "128aee0f1c7e12b63bce933d18032c8a3084759b", "builtInExample2_ContinuousScatterPlot": "c2e538807506a5146c0257438a388b06f346007a", @@ -140,8 +140,24 @@ "persistenceClustering2_OutputClustering": "a0e8c1a235c7b63e9722ec6150d97cf36e3e61a7", "persistenceClustering3_OutputClustering": "6a4e1b96f4560217cbdf2c4f7320285e022502c8", "persistenceClustering4_OutputClustering": "00042f8a664fa30b2105ba8b9ed498c5022f0b9b", + "persistenceDiagramClustering_PersistenceDiagramClustering_centroids": "35e37ddc2ac4b31cd668515107d8886deada974d", + "persistenceDiagramClustering_PersistenceDiagramClustering_centroids_0_0": "04b47053c08b0e8688d90c9b0c57b169bd6cd6b9", + "persistenceDiagramClustering_PersistenceDiagramClustering_centroids_1_0": "fa9b14abc710b75a39c04608b06e489b41708012", + "persistenceDiagramClustering_PersistenceDiagramClustering_centroids_2_0": "38d016837ed2ef97fea4ff7042d6284e9a74ab35", + "persistenceDiagramClustering_PersistenceDiagramClustering_clustering": "a2a3ef2dab6ed9b8ed711b035f409119353a3e95", "persistenceDrivenCompression_naturalImage_persistence10_zfp50": "9a7e0d8795bee2dbe814c0ea518285802315b01f", "persistenceDrivenCompression_uncompressed_naturalImage_persistence10_zfp50": "bdf8e57eed284b94e83fb03f1b36e6fcc0f416fa", + "persistentGenerators_at_PersistentGeneratorsAt": "687bddc30c9a6a6a580322909c88437699325f7b", + "persistentGenerators_casting_PersistentGeneratorsCasting": "40e5cd27bcced4d5520af6b8e4a7d2be73d0d0ea", + "persistentGenerators_darkSky_PersistentGeneratorsDarkSky": "efaaa8ce58ad46ff3f34c5f1cd498c796f544ac1", + "persistentGenerators_fertility_PersistentGeneratorsFertility": "2a0121e67897ae2e23f09dac6f4507c12eab849b", + "persistentGenerators_householdAnalysis_PersistentGeneratorsHouseholdAnalysis_cycle": "385404dd589bc91a3506f1963bfcc2ed945c53ee", + "persistentGenerators_householdAnalysis_PersistentGeneratorsHouseholdAnalysis_points": "d20c3e7ad2b86597dc1d99d1f8a6a9b02ea19ef0", + "persistentGenerators_householdAnalysis_PersistentGeneratorsHouseholdAnalysis_ripsComplex": "e3561511b859bc669635eeecbb3321a0df7aacc5", + "persistentGenerators_periodicPicture_PersistentGeneratorsPeriodicPicture_cycle": "d4640bab5966864ebe94e3ca638da22031371981", + "persistentGenerators_periodicPicture_PersistentGeneratorsPeriodicPicture_points": "a0f18cd8a1b2c4c0dc2a7a461ba721a11af0e2b2", + "persistentGenerators_periodicPicture_PersistentGeneratorsPeriodicPicture_ripsComplex": "49f1a01b47f0b05953e4b1d23b37149e7bab6a77", + "persistentGenerators_skull_PersistentGeneratorsSkull": "7191614512ad6b82e4541b77390f84ed922c786c", "run01_20_10": "13a315b7d14bad87b71503d8c5a9a6933d28e91f", "run01_30_10": "581f1cb8bdeeacec1ec6c1ed8673e39a295eb40c", "run01_40_10": "60b112f8c52f31b2234fccfbeaf0b076835d7f48", diff --git a/python/hashes/ubuntu-20.04.json b/python/hashes/ubuntu-20.04.json index ebabbf47..c5959de8 100644 --- a/python/hashes/ubuntu-20.04.json +++ b/python/hashes/ubuntu-20.04.json @@ -3,10 +3,10 @@ "1manifoldLearningCircles_Generators": "1cab3896cac8deaa160ed47ac9204c4f171b4621", "1manifoldLearning_OutputArc": "4e01e2cf9b1fb4cb2c6d289efe7d731bc57bf406", "2manifoldLearning_OutputSurface": "1d46bf2c423116c63e9352a6f6e5d71d7f7fb348", - "builtInExample1_CriticalPoints": "ee66975c6a1425cc5e851d5829d6f44f89805ea9", - "builtInExample1_PersistenceCurve": "99718aa7939e105e48add83e6e998b810780084b", - "builtInExample1_PersistenceDiagram": "9eee5e98bbb0e3b0f9a495b697784febd3eaebed", - "builtInExample1_warpedInput": "c01bc9de241e12884aa3cd06e401baeafbe93d37", + "BuiltInExample1_CriticalPoints": "ee66975c6a1425cc5e851d5829d6f44f89805ea9", + "BuiltInExample1_PersistenceCurve": "99718aa7939e105e48add83e6e998b810780084b", + "BuiltInExample1_PersistenceDiagram": "9eee5e98bbb0e3b0f9a495b697784febd3eaebed", + "BuiltInExample1_warpedInput": "c01bc9de241e12884aa3cd06e401baeafbe93d37", "builtInExample2_CarbonAtomsFiberSurface": "10dadd8de92ffca9aa9d066ee97bed29f7853eda", "builtInExample2_CarbonAtomsRangePolygon": "128aee0f1c7e12b63bce933d18032c8a3084759b", "builtInExample2_ContinuousScatterPlot": "c2e538807506a5146c0257438a388b06f346007a", @@ -140,8 +140,24 @@ "persistenceClustering2_OutputClustering": "a0e8c1a235c7b63e9722ec6150d97cf36e3e61a7", "persistenceClustering3_OutputClustering": "6a4e1b96f4560217cbdf2c4f7320285e022502c8", "persistenceClustering4_OutputClustering": "00042f8a664fa30b2105ba8b9ed498c5022f0b9b", + "persistenceDiagramClustering_PersistenceDiagramClustering_centroids": "35e37ddc2ac4b31cd668515107d8886deada974d", + "persistenceDiagramClustering_PersistenceDiagramClustering_centroids_0_0": "04b47053c08b0e8688d90c9b0c57b169bd6cd6b9", + "persistenceDiagramClustering_PersistenceDiagramClustering_centroids_1_0": "fa9b14abc710b75a39c04608b06e489b41708012", + "persistenceDiagramClustering_PersistenceDiagramClustering_centroids_2_0": "38d016837ed2ef97fea4ff7042d6284e9a74ab35", + "persistenceDiagramClustering_PersistenceDiagramClustering_clustering": "a2a3ef2dab6ed9b8ed711b035f409119353a3e95", "persistenceDrivenCompression_naturalImage_persistence10_zfp50": "9a7e0d8795bee2dbe814c0ea518285802315b01f", "persistenceDrivenCompression_uncompressed_naturalImage_persistence10_zfp50": "bdf8e57eed284b94e83fb03f1b36e6fcc0f416fa", + "persistentGenerators_at_PersistentGeneratorsAt": "687bddc30c9a6a6a580322909c88437699325f7b", + "persistentGenerators_casting_PersistentGeneratorsCasting": "9c79a094990a0e59c5263c54c6f8dbf8bbce9d6a", + "persistentGenerators_darkSky_PersistentGeneratorsDarkSky": "fe38037826c1113a7be6c92a4d95f0a6a66e0698", + "persistentGenerators_fertility_PersistentGeneratorsFertility": "2a0121e67897ae2e23f09dac6f4507c12eab849b", + "persistentGenerators_householdAnalysis_PersistentGeneratorsHouseholdAnalysis_cycle": "385404dd589bc91a3506f1963bfcc2ed945c53ee", + "persistentGenerators_householdAnalysis_PersistentGeneratorsHouseholdAnalysis_points": "5e6035a029e7d2c3a218732978e18cb33c00088b", + "persistentGenerators_householdAnalysis_PersistentGeneratorsHouseholdAnalysis_ripsComplex": "27b4a0753ad8d3bb4c508f219c217999596f503d", + "persistentGenerators_periodicPicture_PersistentGeneratorsPeriodicPicture_cycle": "d4640bab5966864ebe94e3ca638da22031371981", + "persistentGenerators_periodicPicture_PersistentGeneratorsPeriodicPicture_points": "0246157ded53190f804425600009dcea2ca1e052", + "persistentGenerators_periodicPicture_PersistentGeneratorsPeriodicPicture_ripsComplex": "0a565fe8546efcd9b0e08340d05d34b53c66a0d5", + "persistentGenerators_skull_PersistentGeneratorsSkull": "7191614512ad6b82e4541b77390f84ed922c786c", "run01_20_10": "13a315b7d14bad87b71503d8c5a9a6933d28e91f", "run01_30_10": "581f1cb8bdeeacec1ec6c1ed8673e39a295eb40c", "run01_40_10": "60b112f8c52f31b2234fccfbeaf0b076835d7f48", diff --git a/python/hashes/ubuntu-22.04.json b/python/hashes/ubuntu-22.04.json new file mode 100644 index 00000000..2ad6968d --- /dev/null +++ b/python/hashes/ubuntu-22.04.json @@ -0,0 +1,176 @@ +{ + "1manifoldLearningCircles_Clustering": "16e9d627bea35c28818b1a10c3598ab08c06ee55", + "1manifoldLearningCircles_Generators": "1cab3896cac8deaa160ed47ac9204c4f171b4621", + "1manifoldLearning_OutputArc": "4e01e2cf9b1fb4cb2c6d289efe7d731bc57bf406", + "2manifoldLearning_OutputSurface": "1d46bf2c423116c63e9352a6f6e5d71d7f7fb348", + "BuiltInExample1_CriticalPoints": "ee66975c6a1425cc5e851d5829d6f44f89805ea9", + "BuiltInExample1_PersistenceCurve": "99718aa7939e105e48add83e6e998b810780084b", + "BuiltInExample1_PersistenceDiagram": "9eee5e98bbb0e3b0f9a495b697784febd3eaebed", + "BuiltInExample1_warpedInput": "c01bc9de241e12884aa3cd06e401baeafbe93d37", + "builtInExample2_CarbonAtomsFiberSurface": "10dadd8de92ffca9aa9d066ee97bed29f7853eda", + "builtInExample2_CarbonAtomsRangePolygon": "128aee0f1c7e12b63bce933d18032c8a3084759b", + "builtInExample2_ContinuousScatterPlot": "c2e538807506a5146c0257438a388b06f346007a", + "builtInExample2_CovalentBondsFiberSurface": "f0f8b4132ac81653d7f8f120598947a95bc5a2bb", + "builtInExample2_CovalentBondsRangePolygon": "1dec2a1dcf7809c1ff395b5d9eda637a3a6b9095", + 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"385404dd589bc91a3506f1963bfcc2ed945c53ee", + "persistentGenerators_householdAnalysis_PersistentGeneratorsHouseholdAnalysis_points": "5e6035a029e7d2c3a218732978e18cb33c00088b", + "persistentGenerators_householdAnalysis_PersistentGeneratorsHouseholdAnalysis_ripsComplex": "27b4a0753ad8d3bb4c508f219c217999596f503d", + "persistentGenerators_periodicPicture_PersistentGeneratorsPeriodicPicture_cycle": "d4640bab5966864ebe94e3ca638da22031371981", + "persistentGenerators_periodicPicture_PersistentGeneratorsPeriodicPicture_points": "0246157ded53190f804425600009dcea2ca1e052", + "persistentGenerators_periodicPicture_PersistentGeneratorsPeriodicPicture_ripsComplex": "0a565fe8546efcd9b0e08340d05d34b53c66a0d5", + "persistentGenerators_skull_PersistentGeneratorsSkull": "b76463f67f068c31d08bf3a87c0bc42cecea17af", + "run01_20_10": "13a315b7d14bad87b71503d8c5a9a6933d28e91f", + "run01_30_10": "581f1cb8bdeeacec1ec6c1ed8673e39a295eb40c", + "run01_40_10": "60b112f8c52f31b2234fccfbeaf0b076835d7f48", + "run01_50_10": "b72e53f3a0cb1924831db5c912819f6bc75c96c1", + "run01_60_10": "eb0cff554469126aa9b7bbc24808197288e77973", + "run01_70_10": "1f60ebf826e03a3b8180d7153d3eaffcfa44612c", + "run01_80_10": "cbb8477619e8905ef37e8c749eb6966b49566d85", + "run01_90_10": "5139529a66889e8f3cc1bb74b5990025447c6607", + "tectonicPuzzle_Segmentation": "f084a9d53928844cf05dcf0cab2d456567be1e9a", + "timeTracking_timeTracking": "d9417c2287fbffa8233a7a911d93ffc19250e188", + "tribute_tribute_segmentation": "661581c58818796bed0c535b0e8b14f2f0d1e046", + "uncertainStartingVortex_CriticalPoints": "826393a1bd941aeca66fd9971fd334da2a29309b", + "uncertainStartingVortex_MandatoryCriticalMaxima": "0a9c1ca57d5a6b6609843a79e7bb27a3dee5155d", + "uncertainStartingVortex_MandatoryCriticalMinima": "80e2d6ec3f1efdb4267b29f705d35dc6e06f040c", + "uncertainStartingVortex_PersistenceDiagram": "58283c9e037e0556b4f9e3cf98098a6a37280297" +} diff --git a/python/hashes/windows.json b/python/hashes/windows.json index b3bde9da..af2f8655 100644 --- a/python/hashes/windows.json +++ b/python/hashes/windows.json @@ -3,10 +3,10 @@ "1manifoldLearningCircles_Generators": "64507c8e0a0db2dfe6e83754451a705d93e49447", "1manifoldLearning_OutputArc": "f1ddc9646cfa616edd0121dbb50784e0c033c3d5", "2manifoldLearning_OutputSurface": "df5481e49907e80879b62685f7c2fd3950cd62a8", - "builtInExample1_CriticalPoints": "0428da64679ba7dc6e3ec7851e4e7c139ac4ea8e", - "builtInExample1_PersistenceCurve": "7120aff7a6d2107d82bed0d41fc4fc6b5034a469", - "builtInExample1_PersistenceDiagram": "13e648ce151f4c406b666dc6be5a2b732f6ddceb", - "builtInExample1_warpedInput": "9be1d3eec060355a698ad9858fef21790d5d83a1", + "BuiltInExample1_CriticalPoints": "0428da64679ba7dc6e3ec7851e4e7c139ac4ea8e", + "BuiltInExample1_PersistenceCurve": "7120aff7a6d2107d82bed0d41fc4fc6b5034a469", + "BuiltInExample1_PersistenceDiagram": "13e648ce151f4c406b666dc6be5a2b732f6ddceb", + "BuiltInExample1_warpedInput": "9be1d3eec060355a698ad9858fef21790d5d83a1", "builtInExample2_CarbonAtomsFiberSurface": "d4e9ca0ad27b56c23f4383e15e2e0e711cb9a241", "builtInExample2_CarbonAtomsRangePolygon": "db091e366f1036e47a89576fca637baeb4a746af", "builtInExample2_ContinuousScatterPlot": "2adf3453ff5e0cbd81fede5b7509facd3a0ebc14", @@ -92,8 +92,24 @@ "persistenceClustering2_OutputClustering": "cdaa82d9d559cee0cd041512d80138b9c1851de2", "persistenceClustering3_OutputClustering": "dba6cda019cd29c364fdf36d1058d5c123c85489", "persistenceClustering4_OutputClustering": "726645866a15b44fea88ed64b10296f088c63bc6", + "persistenceDiagramClustering_PersistenceDiagramClustering_centroids": "35e37ddc2ac4b31cd668515107d8886deada974d", + "persistenceDiagramClustering_PersistenceDiagramClustering_centroids_0_0": "d92a51e30004e28bbca6bfedcf2d4d6359839ee1", + "persistenceDiagramClustering_PersistenceDiagramClustering_centroids_1_0": "6688bfa2d7582ad2f3c115c7e806564d37af310e", + "persistenceDiagramClustering_PersistenceDiagramClustering_centroids_2_0": "5b70e28c06fb36b9814c8150b0b120d5974067f1", + "persistenceDiagramClustering_PersistenceDiagramClustering_clustering": "7b2e4650fcd312b3799f3765a277b678e0c14d0f", "persistenceDrivenCompression_naturalImage_persistence10_zfp50": "9e0ce54f4a0ced7ae6c10176682864f10510ec20", "persistenceDrivenCompression_uncompressed_naturalImage_persistence10_zfp50": "bdf8e57eed284b94e83fb03f1b36e6fcc0f416fa", + "persistentGenerators_at_PersistentGeneratorsAt": "174a0857a4443e25c9424ef381ff65f23b8d9dac", + "persistentGenerators_casting_PersistentGeneratorsCasting": "a8f8a0ff88b5ec430f99bd7b2005c73db82cfeb6", + "persistentGenerators_darkSky_PersistentGeneratorsDarkSky": "f0e4fa2ab770f2b02cd558dd2869d84ba18f9836", + "persistentGenerators_fertility_PersistentGeneratorsFertility": "a4c6338c200da5eb12e899577b186a357992b926", + "persistentGenerators_householdAnalysis_PersistentGeneratorsHouseholdAnalysis_cycle": "056e3dd3bb005d1b6da4b964410dc63409936d9f", + "persistentGenerators_householdAnalysis_PersistentGeneratorsHouseholdAnalysis_points": "810234e1074c27e4617fd68b27b70170aec62d9d", + "persistentGenerators_householdAnalysis_PersistentGeneratorsHouseholdAnalysis_ripsComplex": "ed611ab6d9b4a86170adbe359669b8b72d2c74ff", + "persistentGenerators_periodicPicture_PersistentGeneratorsPeriodicPicture_cycle": "851e8410ecf7d11af8ea2472b807f044fb5b7f74", + "persistentGenerators_periodicPicture_PersistentGeneratorsPeriodicPicture_points": "52cc57c1dbcf7d6d4ebaefcdf026bdf8af2f953d", + "persistentGenerators_periodicPicture_PersistentGeneratorsPeriodicPicture_ripsComplex": "87ebf350db280f9c0cdf7ce769b6edb060efccad", + "persistentGenerators_skull_PersistentGeneratorsSkull": "e801c39c84f5111bb61d432bf97016cb4d8669bf", "run01_20_10": "13a315b7d14bad87b71503d8c5a9a6933d28e91f", "run01_30_10": "581f1cb8bdeeacec1ec6c1ed8673e39a295eb40c", "run01_40_10": "60b112f8c52f31b2234fccfbeaf0b076835d7f48", @@ -102,11 +118,11 @@ "run01_70_10": "1f60ebf826e03a3b8180d7153d3eaffcfa44612c", "run01_80_10": "cbb8477619e8905ef37e8c749eb6966b49566d85", "run01_90_10": "5139529a66889e8f3cc1bb74b5990025447c6607", - "tectonicPuzzle_Segmentation": "cb73a3276cc3f0483b6613504014883eae865182", + "tectonicPuzzle_Segmentation": "a6b30428c7cea831b6474b1410c269125a66128c", "timeTracking_timeTracking": "5d8d82c6c0d1aa40473cdb42313d25b089eece75", "tribute_tribute_segmentation": "46eb03ea0b30811ea56895694f66418526325ce0", "uncertainStartingVortex_CriticalPoints": "10f97090aa7972e43e56860cbe4ed1c3ebff57ed", - "uncertainStartingVortex_MandatoryCriticalMaxima": "4c4f70bd8ee8ab063a0dedc41ba524ab29b4a9d8", - "uncertainStartingVortex_MandatoryCriticalMinima": "67932e447f14aa825122ebcb609c9f9ae8ec0777", + "uncertainStartingVortex_MandatoryCriticalMaxima": "e7e20279a1155f2b28cdee7de9f63714601d2bad", + "uncertainStartingVortex_MandatoryCriticalMinima": "ad9cba1af8c1904d2a25813aee51d2ad595ce9a2", "uncertainStartingVortex_PersistenceDiagram": "627396aeade7fbcedf8a0f0cc0def791131f8bd3" } diff --git a/python/mergeTreeClustering.py b/python/mergeTreeClustering.py index e9bd2549..3bf7bb7d 100644 --- a/python/mergeTreeClustering.py +++ b/python/mergeTreeClustering.py @@ -17,7 +17,7 @@ def ThresholdBetween(threshold, lower, upper): # end of comphatibility ======================================================== # create a new 'TTK CinemaReader' -tTKCinemaReader1 = TTKCinemaReader(DatabasePath='./Isabel.cdb') +tTKCinemaReader1 = TTKCinemaReader(DatabasePath="./Isabel.cdb") # create a new 'TTK CinemaProductReader' tTKCinemaProductReader1 = TTKCinemaProductReader(Input=tTKCinemaReader1) @@ -25,21 +25,33 @@ def ThresholdBetween(threshold, lower, upper): # create a new 'TTK Merge and Contour Tree (FTM)' tTKMergeandContourTreeFTM26 = TTKMergeandContourTreeFTM(Input=tTKCinemaProductReader1) -tTKMergeandContourTreeFTM26.ScalarField = ['POINTS', 'velocityMag'] -tTKMergeandContourTreeFTM26.InputOffsetField = ['POINTS', 'velocityMag'] -tTKMergeandContourTreeFTM26.TreeType = 'Join Tree' +tTKMergeandContourTreeFTM26.ScalarField = ["POINTS", "velocityMag"] +tTKMergeandContourTreeFTM26.InputOffsetField = ["POINTS", "velocityMag"] +tTKMergeandContourTreeFTM26.TreeType = "Join Tree" # create a new 'Group Datasets' -mt_JT_all = GroupDatasets(Input=[tTKMergeandContourTreeFTM26, OutputPort(tTKMergeandContourTreeFTM26,1), OutputPort(tTKMergeandContourTreeFTM26,2)]) +mt_JT_all = GroupDatasets( + Input=[ + tTKMergeandContourTreeFTM26, + OutputPort(tTKMergeandContourTreeFTM26, 1), + OutputPort(tTKMergeandContourTreeFTM26, 2), + ] +) # create a new 'TTK Merge and Contour Tree (FTM)' tTKMergeandContourTreeFTM25 = TTKMergeandContourTreeFTM(Input=tTKCinemaProductReader1) -tTKMergeandContourTreeFTM25.ScalarField = ['POINTS', 'velocityMag'] -tTKMergeandContourTreeFTM25.InputOffsetField = ['POINTS', 'velocityMag'] -tTKMergeandContourTreeFTM25.TreeType = 'Split Tree' +tTKMergeandContourTreeFTM25.ScalarField = ["POINTS", "velocityMag"] +tTKMergeandContourTreeFTM25.InputOffsetField = ["POINTS", "velocityMag"] +tTKMergeandContourTreeFTM25.TreeType = "Split Tree" # create a new 'Group Datasets' -mT_all = GroupDatasets(Input=[tTKMergeandContourTreeFTM25, OutputPort(tTKMergeandContourTreeFTM25,1), OutputPort(tTKMergeandContourTreeFTM25,2)]) +mT_all = GroupDatasets( + Input=[ + tTKMergeandContourTreeFTM25, + OutputPort(tTKMergeandContourTreeFTM25, 1), + OutputPort(tTKMergeandContourTreeFTM25, 2), + ] +) # create a new 'TTK MergeTreeClustering' tTKMergeTreeClustering1 = TTKMergeTreeClustering( @@ -57,35 +69,46 @@ def ThresholdBetween(threshold, lower, upper): tTKMergeTreeClustering1.NonImportantPairsProximity = 0.15 # create a new 'Extract Block' -nodes = ExtractBlock(Input=OutputPort(tTKMergeTreeClustering1,1)) -nodes.Selectors = ['/Root/Block0'] +nodes = ExtractBlock(Input=OutputPort(tTKMergeTreeClustering1, 1)) +nodes.Selectors = ["/Root/Block0"] # create a new 'Extract Block' nodes_1 = ExtractBlock(Input=tTKMergeTreeClustering1) -nodes_1.Selectors = ['/Root/Block0'] +nodes_1.Selectors = ["/Root/Block0"] # create a new 'Extract Block' -arcs = ExtractBlock(Input=OutputPort(tTKMergeTreeClustering1,1)) -arcs.Selectors = ['/Root/Block1'] +arcs = ExtractBlock(Input=OutputPort(tTKMergeTreeClustering1, 1)) +arcs.Selectors = ["/Root/Block1"] # create a new 'Extract Block' arcs_1 = ExtractBlock(Input=tTKMergeTreeClustering1) -arcs_1.Selectors = ['/Root/Block1'] +arcs_1.Selectors = ["/Root/Block1"] # create a new 'TTK BlockAggregator' -tTKBlockAggregator1 = TTKBlockAggregator(registrationName='TTKBlockAggregator1', Input=[nodes_1, nodes]) +tTKBlockAggregator1 = TTKBlockAggregator( + registrationName="TTKBlockAggregator1", Input=[nodes_1, nodes] +) # create a new 'TTK FlattenMultiBlock' -tTKFlattenMultiBlock1 = TTKFlattenMultiBlock(registrationName='TTKFlattenMultiBlock1', Input=tTKBlockAggregator1) +tTKFlattenMultiBlock1 = TTKFlattenMultiBlock( + registrationName="TTKFlattenMultiBlock1", Input=tTKBlockAggregator1 +) # create a new 'TTK BlockAggregator' -tTKBlockAggregator2 = TTKBlockAggregator(registrationName='TTKBlockAggregator2', Input=[arcs_1, arcs]) +tTKBlockAggregator2 = TTKBlockAggregator( + registrationName="TTKBlockAggregator2", Input=[arcs_1, arcs] +) # create a new 'TTK FlattenMultiBlock' -tTKFlattenMultiBlock3 = TTKFlattenMultiBlock(registrationName='TTKFlattenMultiBlock3', Input=tTKBlockAggregator2) +tTKFlattenMultiBlock3 = TTKFlattenMultiBlock( + registrationName="TTKFlattenMultiBlock3", Input=tTKBlockAggregator2 +) # create a new 'TTK BlockAggregator' -tTKBlockAggregator3 = TTKBlockAggregator(registrationName='TTKBlockAggregator3', Input=[tTKFlattenMultiBlock1, tTKFlattenMultiBlock3]) +tTKBlockAggregator3 = TTKBlockAggregator( + registrationName="TTKBlockAggregator3", + Input=[tTKFlattenMultiBlock1, tTKFlattenMultiBlock3], +) tTKBlockAggregator3.FlattenInput = 0 # create a new 'TTK MergeTreeDistanceMatrix' @@ -97,7 +120,7 @@ def ThresholdBetween(threshold, lower, upper): Input=tTKMergeTreeDistanceMatrix2, ModulePath="default" ) tTKDimensionReduction2.SelectFieldswithaRegexp = 1 -tTKDimensionReduction2.Regexp = 'Tree[0-9]+' +tTKDimensionReduction2.Regexp = "Tree[0-9]+" tTKDimensionReduction2.InputIsaDistanceMatrix = 1 tTKDimensionReduction2.UseAllCores = 0 # MDS is unstable in parallel mode diff --git a/python/mergeTreeTemporalReduction.py b/python/mergeTreeTemporalReduction.py index f2389eb5..fc590754 100644 --- a/python/mergeTreeTemporalReduction.py +++ b/python/mergeTreeTemporalReduction.py @@ -3,7 +3,7 @@ from paraview.simple import * # create a new 'TTK CinemaReader' -tTKCinemaReader1 = TTKCinemaReader(DatabasePath='./Isabel.cdb') +tTKCinemaReader1 = TTKCinemaReader(DatabasePath="./Isabel.cdb") # create a new 'TTK CinemaProductReader' tTKCinemaProductReader1 = TTKCinemaProductReader(Input=tTKCinemaReader1) @@ -11,12 +11,18 @@ # create a new 'TTK Merge and Contour Tree (FTM)' tTKMergeandContourTreeFTM26 = TTKMergeandContourTreeFTM(Input=tTKCinemaProductReader1) -tTKMergeandContourTreeFTM26.ScalarField = ['POINTS', 'velocityMag'] -tTKMergeandContourTreeFTM26.InputOffsetField = ['POINTS', 'velocityMag'] -tTKMergeandContourTreeFTM26.TreeType = 'Split Tree' +tTKMergeandContourTreeFTM26.ScalarField = ["POINTS", "velocityMag"] +tTKMergeandContourTreeFTM26.InputOffsetField = ["POINTS", "velocityMag"] +tTKMergeandContourTreeFTM26.TreeType = "Split Tree" # create a new 'Group Datasets' -all_MT = GroupDatasets(Input=[tTKMergeandContourTreeFTM26, OutputPort(tTKMergeandContourTreeFTM26,1), OutputPort(tTKMergeandContourTreeFTM26,2)]) +all_MT = GroupDatasets( + Input=[ + tTKMergeandContourTreeFTM26, + OutputPort(tTKMergeandContourTreeFTM26, 1), + OutputPort(tTKMergeandContourTreeFTM26, 2), + ] +) # create a new 'TTK MergeTreeTemporalReductionEncoding' tTKMergeTreeTemporalReductionEncoding1 = TTKMergeTreeTemporalReductionEncoding( diff --git a/python/persistenceDiagramClustering.py b/python/persistenceDiagramClustering.py index 00169721..24cba75e 100644 --- a/python/persistenceDiagramClustering.py +++ b/python/persistenceDiagramClustering.py @@ -3,30 +3,45 @@ from paraview.simple import * # create a new 'TTK CinemaReader' -tTKCinemaReader1 = TTKCinemaReader(registrationName='TTKCinemaReader1', DatabasePath='Isabel.cdb') +tTKCinemaReader1 = TTKCinemaReader( + registrationName="TTKCinemaReader1", DatabasePath="Isabel.cdb" +) # create a new 'TTK CinemaProductReader' -tTKCinemaProductReader1 = TTKCinemaProductReader(registrationName='TTKCinemaProductReader1', Input=tTKCinemaReader1) +tTKCinemaProductReader1 = TTKCinemaProductReader( + registrationName="TTKCinemaProductReader1", Input=tTKCinemaReader1 +) # create a new 'TTK PersistenceDiagram' -tTKPersistenceDiagram13 = TTKPersistenceDiagram(registrationName='TTKPersistenceDiagram13', Input=tTKCinemaProductReader1) -tTKPersistenceDiagram13.ScalarField = ['POINTS', 'velocityMag'] -tTKPersistenceDiagram13.InputOffsetField = ['POINTS', 'velocityMag'] -tTKPersistenceDiagram13.Backend = 'FTM (IEEE TPSD 2019)' +tTKPersistenceDiagram13 = TTKPersistenceDiagram( + registrationName="TTKPersistenceDiagram13", Input=tTKCinemaProductReader1 +) +tTKPersistenceDiagram13.ScalarField = ["POINTS", "velocityMag"] +tTKPersistenceDiagram13.InputOffsetField = ["POINTS", "velocityMag"] +tTKPersistenceDiagram13.Backend = "FTM (IEEE TPSD 2019)" tTKPersistenceDiagram13.UseAllCores = 0 # create a new 'TTK PersistenceDiagramClustering' -tTKPersistenceDiagramClustering1 = TTKPersistenceDiagramClustering(registrationName='TTKPersistenceDiagramClustering1', Input=tTKPersistenceDiagram13) +tTKPersistenceDiagramClustering1 = TTKPersistenceDiagramClustering( + registrationName="TTKPersistenceDiagramClustering1", Input=tTKPersistenceDiagram13 +) tTKPersistenceDiagramClustering1.Numberofclusters = 3 tTKPersistenceDiagramClustering1.Maximalcomputationtimes = 10.0 -tTKPersistenceDiagramClustering1.Displayingmethod = 'Clusters as stars' +tTKPersistenceDiagramClustering1.Displayingmethod = "Clusters as stars" tTKPersistenceDiagramClustering1.Spacing = 1.1 tTKPersistenceDiagramClustering1.GeometricalLiftingalpha = 0.2 # save the output -SaveData("PersistenceDiagramClustering_centroids.vtm", OutputPort(tTKPersistenceDiagramClustering1,1)) +SaveData( + "PersistenceDiagramClustering_centroids.vtm", + OutputPort(tTKPersistenceDiagramClustering1, 1), +) -SaveData('PersistenceDiagramClustering_clustering.csv', proxy=tTKPersistenceDiagramClustering1, ChooseArraysToWrite=1, - FieldDataArrays=['FILE', 'TimeStep', 'ClusterId'], - FieldAssociation='Field Data', - AddMetaData=0) +SaveData( + "PersistenceDiagramClustering_clustering.csv", + proxy=tTKPersistenceDiagramClustering1, + ChooseArraysToWrite=1, + FieldDataArrays=["FILE", "TimeStep", "ClusterId"], + FieldAssociation="Field Data", + AddMetaData=0, +) diff --git a/python/persistenceDiagramDistance.py b/python/persistenceDiagramDistance.py index 49526fbe..eb6026cb 100644 --- a/python/persistenceDiagramDistance.py +++ b/python/persistenceDiagramDistance.py @@ -5,25 +5,25 @@ import numpy as np # create a new 'TTK CinemaReader' -tTKCinemaReader1 = TTKCinemaReader(DatabasePath='Isabel.cdb') +tTKCinemaReader1 = TTKCinemaReader(DatabasePath="Isabel.cdb") # create a new 'TTK CinemaProductReader' tTKCinemaProductReader1 = TTKCinemaProductReader(Input=tTKCinemaReader1) # create a new 'Extract Block' extractBlock1 = ExtractBlock(Input=tTKCinemaProductReader1) -extractBlock1.Selectors = ['/Root/Block0', '/Root/Block10'] +extractBlock1.Selectors = ["/Root/Block0", "/Root/Block10"] # create a new 'TTK PersistenceDiagram' tTKPersistenceDiagram3 = TTKPersistenceDiagram(Input=extractBlock1) -tTKPersistenceDiagram3.ScalarField = ['POINTS', 'velocityMag'] -tTKPersistenceDiagram3.InputOffsetField = ['POINTS', 'velocityMag'] -tTKPersistenceDiagram3.Backend = 'FTM (IEEE TPSD 2019)' +tTKPersistenceDiagram3.ScalarField = ["POINTS", "velocityMag"] +tTKPersistenceDiagram3.InputOffsetField = ["POINTS", "velocityMag"] +tTKPersistenceDiagram3.Backend = "FTM (IEEE TPSD 2019)" tTKPersistenceDiagram3.UseAllCores = 0 # create a new 'Threshold' threshold7 = Threshold(Input=tTKPersistenceDiagram3) -threshold7.Scalars = ['CELLS', 'Persistence'] +threshold7.Scalars = ["CELLS", "Persistence"] threshold7.LowerThreshold = 1.2 threshold7.UpperThreshold = 136.490955383565 @@ -32,7 +32,7 @@ Show(tTKPersistenceDiagramClustering1) # Get the data -matchings_data = FetchData(OutputPort(tTKPersistenceDiagramClustering1,2))[0] +matchings_data = FetchData(OutputPort(tTKPersistenceDiagramClustering1, 2))[0] # Get field data field_data = matchings_data.GetBlock(0).GetFieldData() diff --git a/python/persistentGenerators_at.py b/python/persistentGenerators_at.py index 6ee6b83e..ff0a71d4 100644 --- a/python/persistentGenerators_at.py +++ b/python/persistentGenerators_at.py @@ -3,13 +3,13 @@ from paraview.simple import * # create a new 'XML Image Data Reader' -atvti = XMLImageDataReader(FileName=['at.vti']) -atvti.PointArrayStatus = ['density'] +atvti = XMLImageDataReader(FileName=["at.vti"]) +atvti.PointArrayStatus = ["density"] # create a new 'TTK PersistentGenerators' tTKPersistentGenerators1 = TTKPersistentGenerators(Input=atvti) -tTKPersistentGenerators1.ScalarField = ['POINTS', 'density'] -tTKPersistentGenerators1.InputOffsetField = ['POINTS', 'density'] +tTKPersistentGenerators1.ScalarField = ["POINTS", "density"] +tTKPersistentGenerators1.InputOffsetField = ["POINTS", "density"] tTKPersistentGenerators1.PruneHandlesGenerators = 1 SaveData("PersistentGeneratorsAt.vtp", tTKPersistentGenerators1) diff --git a/python/persistentGenerators_casting.py b/python/persistentGenerators_casting.py index e03ea69e..bea492ca 100644 --- a/python/persistentGenerators_casting.py +++ b/python/persistentGenerators_casting.py @@ -3,24 +3,24 @@ from paraview.simple import * # create a new 'XML Unstructured Grid Reader' -castingvtu = XMLUnstructuredGridReader(FileName=['casting.vtu']) -castingvtu.CellArrayStatus = ['GroupIds'] -castingvtu.TimeArray = 'None' +castingvtu = XMLUnstructuredGridReader(FileName=["casting.vtu"]) +castingvtu.CellArrayStatus = ["GroupIds"] +castingvtu.TimeArray = "None" # create a new 'TTK EigenField' tTKEigenField1 = TTKEigenField(InputGeometry=castingvtu) tTKEigenField1.Numberofeigenfunctions = 98 tTKEigenField1.Computestatistics = 1 -tTKEigenField1.Outputscalarfieldname = 'E' +tTKEigenField1.Outputscalarfieldname = "E" # create a new 'Calculator' calculator1 = Calculator(Input=tTKEigenField1) -calculator1.Function = 'Statistics_EigenMagnitude' +calculator1.Function = "Statistics_EigenMagnitude" # create a new 'TTK PersistentGenerators' tTKPersistentGenerators1 = TTKPersistentGenerators(Input=calculator1) -tTKPersistentGenerators1.ScalarField = ['POINTS', 'Result'] -tTKPersistentGenerators1.InputOffsetField = ['POINTS', 'Result'] +tTKPersistentGenerators1.ScalarField = ["POINTS", "Result"] +tTKPersistentGenerators1.InputOffsetField = ["POINTS", "Result"] tTKPersistentGenerators1.PruneHandlesGenerators = 1 SaveData("PersistentGeneratorsCasting.vtp", tTKPersistentGenerators1) diff --git a/python/persistentGenerators_darkSky.py b/python/persistentGenerators_darkSky.py index 29772188..572e0c21 100644 --- a/python/persistentGenerators_darkSky.py +++ b/python/persistentGenerators_darkSky.py @@ -3,12 +3,14 @@ from paraview.simple import * # create a new 'XML PolyData Reader' -ds14_scivis_0128_e4_dt04_06800vtp = XMLPolyDataReader(FileName=['ds14_scivis_0128_e4_dt04_1.0000.vtp']) -ds14_scivis_0128_e4_dt04_06800vtp.PointArrayStatus = ['DarkMatter_Phi'] +ds14_scivis_0128_e4_dt04_06800vtp = XMLPolyDataReader( + FileName=["ds14_scivis_0128_e4_dt04_1.0000.vtp"] +) +ds14_scivis_0128_e4_dt04_06800vtp.PointArrayStatus = ["DarkMatter_Phi"] # create a new 'Gaussian Resampling' gaussianResampling1 = GaussianResampling(Input=ds14_scivis_0128_e4_dt04_06800vtp) -gaussianResampling1.ResampleField = ['POINTS', 'DarkMatter_Phi'] +gaussianResampling1.ResampleField = ["POINTS", "DarkMatter_Phi"] gaussianResampling1.ResamplingGrid = [200, 200, 200] gaussianResampling1.GaussianSplatRadius = 0.008 gaussianResampling1.ScaleSplats = 0 @@ -17,23 +19,23 @@ # create a new 'TTK ScalarFieldSmoother' tTKScalarFieldSmoother1 = TTKScalarFieldSmoother(Input=gaussianResampling1) -tTKScalarFieldSmoother1.ScalarField = ['POINTS', 'SplatterValues'] +tTKScalarFieldSmoother1.ScalarField = ["POINTS", "SplatterValues"] tTKScalarFieldSmoother1.IterationNumber = 7 -tTKScalarFieldSmoother1.MaskField = ['POINTS', 'SplatterValues'] +tTKScalarFieldSmoother1.MaskField = ["POINTS", "SplatterValues"] # create a new 'Calculator' calculator1 = Calculator(Input=tTKScalarFieldSmoother1) -calculator1.ResultArrayName = 'SplatterValues' -calculator1.Function = '-SplatterValues' +calculator1.ResultArrayName = "SplatterValues" +calculator1.Function = "-SplatterValues" # create a new 'TTK PersistentGenerators' tTKPersistentGenerators1 = TTKPersistentGenerators(Input=calculator1) -tTKPersistentGenerators1.ScalarField = ['POINTS', 'SplatterValues'] -tTKPersistentGenerators1.InputOffsetField = ['POINTS', 'SplatterValues'] +tTKPersistentGenerators1.ScalarField = ["POINTS", "SplatterValues"] +tTKPersistentGenerators1.InputOffsetField = ["POINTS", "SplatterValues"] # create a new 'Threshold' threshold1 = Threshold(Input=tTKPersistentGenerators1) -threshold1.Scalars = ['CELLS', 'Persistence'] +threshold1.Scalars = ["CELLS", "Persistence"] threshold1.LowerThreshold = 0.24 threshold1.UpperThreshold = 0.2863966089734687 diff --git a/python/persistentGenerators_fertility.py b/python/persistentGenerators_fertility.py index 30d477cc..21864d74 100644 --- a/python/persistentGenerators_fertility.py +++ b/python/persistentGenerators_fertility.py @@ -3,8 +3,8 @@ from paraview.simple import * # create a new 'XML Unstructured Grid Reader' -fertilityvtu = XMLUnstructuredGridReader(FileName=['fertility.vtu']) -fertilityvtu.TimeArray = 'None' +fertilityvtu = XMLUnstructuredGridReader(FileName=["fertility.vtu"]) +fertilityvtu.TimeArray = "None" # create a new 'TTK EigenField' tTKEigenField1 = TTKEigenField(InputGeometry=fertilityvtu) @@ -17,12 +17,12 @@ # create a new 'TTK PersistentGenerators' tTKPersistentGenerators1 = TTKPersistentGenerators(Input=calculator1) -tTKPersistentGenerators1.ScalarField = ['POINTS', 'Result'] -tTKPersistentGenerators1.InputOffsetField = ['POINTS', 'Result'] +tTKPersistentGenerators1.ScalarField = ["POINTS", "Result"] +tTKPersistentGenerators1.InputOffsetField = ["POINTS", "Result"] tTKPersistentGenerators1.PruneHandlesGenerators = 1 # create a new 'Threshold' threshold1 = Threshold(Input=tTKPersistentGenerators1) -threshold1.Scalars = ['CELLS', 'IsFinite'] +threshold1.Scalars = ["CELLS", "IsFinite"] SaveData("PersistentGeneratorsFertility.vtu", threshold1) diff --git a/python/persistentGenerators_householdAnalysis.py b/python/persistentGenerators_householdAnalysis.py index f7faa080..5378d9d8 100644 --- a/python/persistentGenerators_householdAnalysis.py +++ b/python/persistentGenerators_householdAnalysis.py @@ -3,56 +3,71 @@ from paraview.simple import * # create a new 'CSV Reader' -household_part1_ID_dailycsv = CSVReader(FileName=['household_part1_ID_daily.csv']) +household_part1_ID_dailycsv = CSVReader(FileName=["household_part1_ID_daily.csv"]) household_part1_ID_dailycsv.HaveHeaders = 0 # create a new 'TTK DimensionReduction' -tTKDimensionReduction1 = TTKDimensionReduction(Input=household_part1_ID_dailycsv, - ModulePath='default') -tTKDimensionReduction1.InputColumns = ['Field 2', 'Field 3', 'Field 4', 'Field 5', 'Field 6', 'Field 7', 'Field 8'] -tTKDimensionReduction1.Method = 'Principal Component Analysis' +tTKDimensionReduction1 = TTKDimensionReduction( + Input=household_part1_ID_dailycsv, ModulePath="default" +) +tTKDimensionReduction1.InputColumns = [ + "Field 2", + "Field 3", + "Field 4", + "Field 5", + "Field 6", + "Field 7", + "Field 8", +] +tTKDimensionReduction1.Method = "Principal Component Analysis" tTKDimensionReduction1.Components = 3 # create a new 'TTK TableDistanceMatrix' tTKTableDistanceMatrix1 = TTKTableDistanceMatrix(Input=tTKDimensionReduction1) -tTKTableDistanceMatrix1.InputColumns = ['Field 2', 'Field 3', 'Field 4', 'Field 5', 'Field 6', 'Field 7', 'Field 8'] +tTKTableDistanceMatrix1.InputColumns = [ + "Field 2", + "Field 3", + "Field 4", + "Field 5", + "Field 6", + "Field 7", + "Field 8", +] # create a new 'Table To Points' tableToPoints1 = TableToPoints(Input=tTKDimensionReduction1) -tableToPoints1.XColumn = 'Component_0' -tableToPoints1.YColumn = 'Component_1' -tableToPoints1.ZColumn = 'Component_2' +tableToPoints1.XColumn = "Component_0" +tableToPoints1.YColumn = "Component_1" +tableToPoints1.ZColumn = "Component_2" tableToPoints1.KeepAllDataArrays = 1 # create a new 'K Means' -kMeans1 = KMeans(Input=tableToPoints1, - ModelInput=None) -kMeans1.VariablesofInterest = ['Component_0', 'Component_1', 'Component_2'] +kMeans1 = KMeans(Input=tableToPoints1, ModelInput=None) +kMeans1.VariablesofInterest = ["Component_0", "Component_1", "Component_2"] kMeans1.k = 8 # create a new 'TTK RipsComplex' tTKRipsComplex1 = TTKRipsComplex(Input=tTKTableDistanceMatrix1) tTKRipsComplex1.SelectFieldswithaRegexp = 1 -tTKRipsComplex1.Regexp = 'Dist.*' +tTKRipsComplex1.Regexp = "Dist.*" tTKRipsComplex1.Diameterepsilon = 18.0 # create a new 'Cell Data to Point Data' cellDatatoPointData1 = CellDatatoPointData(Input=tTKRipsComplex1) -cellDatatoPointData1.CellDataArraytoprocess = ['Diameter'] +cellDatatoPointData1.CellDataArraytoprocess = ["Diameter"] # create a new 'Threshold' threshold1 = Threshold(Input=cellDatatoPointData1) -threshold1.Scalars = ['POINTS', 'Diameter'] +threshold1.Scalars = ["POINTS", "Diameter"] threshold1.LowerThreshold = 9.0 threshold1.UpperThreshold = 17.38239404772305 # create a new 'TTK PersistentGenerators' tTKPersistentGenerators1 = TTKPersistentGenerators(Input=threshold1) -tTKPersistentGenerators1.ScalarField = ['POINTS', 'Diameter'] -tTKPersistentGenerators1.InputOffsetField = ['POINTS', 'Component_0'] +tTKPersistentGenerators1.ScalarField = ["POINTS", "Diameter"] +tTKPersistentGenerators1.InputOffsetField = ["POINTS", "Component_0"] tTKPersistentGenerators1.PruneHandlesGenerators = 1 SaveData("PersistentGeneratorsHouseholdAnalysis_cycle.vtp", tTKPersistentGenerators1) -SaveData("PersistentGeneratorsHouseholdAnalysis_points.vtp", OutputPort(kMeans1,1)) +SaveData("PersistentGeneratorsHouseholdAnalysis_points.vtp", OutputPort(kMeans1, 1)) SaveData("PersistentGeneratorsHouseholdAnalysis_ripsComplex.vtu", tTKRipsComplex1) - diff --git a/python/persistentGenerators_periodicPicture.py b/python/persistentGenerators_periodicPicture.py index 6adf71c2..410728be 100644 --- a/python/persistentGenerators_periodicPicture.py +++ b/python/persistentGenerators_periodicPicture.py @@ -3,22 +3,22 @@ from paraview.simple import * # create a new 'TTK CinemaReader' -tTKCinemaReader1 = TTKCinemaReader(DatabasePath='periodicPicture.cdb') +tTKCinemaReader1 = TTKCinemaReader(DatabasePath="periodicPicture.cdb") # create a new 'TTK CinemaProductReader' tTKCinemaProductReader1 = TTKCinemaProductReader(Input=tTKCinemaReader1) # create a new 'Calculator' calculator1 = Calculator(Input=tTKCinemaProductReader1) -calculator1.Function = 'PNGImage_X' +calculator1.Function = "PNGImage_X" # create a new 'TTK DataSetToTable' tTKDataSetToTable1 = TTKDataSetToTable(Input=calculator1) -tTKDataSetToTable1.DataAssociation = 'Point' +tTKDataSetToTable1.DataAssociation = "Point" # create a new 'Transpose Table' transposeTable1 = TransposeTable(Input=tTKDataSetToTable1) -transposeTable1.VariablesofInterest = ['Result'] +transposeTable1.VariablesofInterest = ["Result"] transposeTable1.Addacolumnwithoriginalcolumnsname = 0 # create a new 'TTK MergeBlockTables' @@ -27,36 +27,37 @@ # create a new 'TTK TableDistanceMatrix' tTKTableDistanceMatrix1 = TTKTableDistanceMatrix(Input=tTKMergeBlockTables1) tTKTableDistanceMatrix1.SelectFieldswithaRegexp = 1 -tTKTableDistanceMatrix1.Regexp = '[01].*' +tTKTableDistanceMatrix1.Regexp = "[01].*" # create a new 'TTK DimensionReduction' -tTKDimensionReduction1 = TTKDimensionReduction(Input=tTKTableDistanceMatrix1, - ModulePath='default') +tTKDimensionReduction1 = TTKDimensionReduction( + Input=tTKTableDistanceMatrix1, ModulePath="default" +) tTKDimensionReduction1.SelectFieldswithaRegexp = 1 -tTKDimensionReduction1.Regexp = 'Dist.*' +tTKDimensionReduction1.Regexp = "Dist.*" tTKDimensionReduction1.Components = 3 tTKDimensionReduction1.InputIsaDistanceMatrix = 1 # create a new 'TTK RipsComplex' tTKRipsComplex1 = TTKRipsComplex(Input=tTKDimensionReduction1) tTKRipsComplex1.SelectFieldswithaRegexp = 1 -tTKRipsComplex1.Regexp = 'Dist.*' +tTKRipsComplex1.Regexp = "Dist.*" tTKRipsComplex1.Diameterepsilon = 1500.0 # create a new 'Cell Data to Point Data' cellDatatoPointData1 = CellDatatoPointData(Input=tTKRipsComplex1) -cellDatatoPointData1.CellDataArraytoprocess = ['Diameter'] +cellDatatoPointData1.CellDataArraytoprocess = ["Diameter"] # create a new 'TTK PersistentGenerators' tTKPersistentGenerators1 = TTKPersistentGenerators(Input=cellDatatoPointData1) -tTKPersistentGenerators1.ScalarField = ['POINTS', 'Diameter'] -tTKPersistentGenerators1.InputOffsetField = ['POINTS', ' angle'] +tTKPersistentGenerators1.ScalarField = ["POINTS", "Diameter"] +tTKPersistentGenerators1.InputOffsetField = ["POINTS", " angle"] # create a new 'Table To Points' tableToPoints1 = TableToPoints(Input=tTKDimensionReduction1) -tableToPoints1.XColumn = 'Component_0' -tableToPoints1.YColumn = 'Component_1' -tableToPoints1.ZColumn = 'Component_2' +tableToPoints1.XColumn = "Component_0" +tableToPoints1.YColumn = "Component_1" +tableToPoints1.ZColumn = "Component_2" tableToPoints1.KeepAllDataArrays = 1 SaveData("PersistentGeneratorsPeriodicPicture_cycle.vtp", tTKPersistentGenerators1) diff --git a/python/persistentGenerators_skull.py b/python/persistentGenerators_skull.py index e5dc9854..66db9d58 100644 --- a/python/persistentGenerators_skull.py +++ b/python/persistentGenerators_skull.py @@ -3,9 +3,9 @@ from paraview.simple import * # create a new 'XML Unstructured Grid Reader' -skullvtu = XMLUnstructuredGridReader(FileName=['skull.vtu']) -skullvtu.PointArrayStatus = ['Morse field'] -skullvtu.TimeArray = 'None' +skullvtu = XMLUnstructuredGridReader(FileName=["skull.vtu"]) +skullvtu.PointArrayStatus = ["Morse field"] +skullvtu.TimeArray = "None" # create a new 'Extract Surface' extractSurface1 = ExtractSurface(Input=skullvtu) @@ -24,8 +24,8 @@ # create a new 'TTK PersistentGenerators' tTKPersistentGenerators1 = TTKPersistentGenerators(Input=calculator1) -tTKPersistentGenerators1.ScalarField = ['POINTS', 'Result'] 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