forgot to commit this file in my last commit!
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Guillaume Raffy
parent
bfca19e039
commit
2505d69692
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@ -36,86 +36,86 @@ class TestLipase(unittest.TestCase):
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print("uninitializing TestLipase instance")
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print("uninitializing TestLipase instance")
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self.catalog = None
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self.catalog = None
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# def test_estimate_white(self):
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def test_estimate_white(self):
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# sequence = self.catalog.sequences['res_soleil2018/GGH/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos2']
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sequence = self.catalog.sequences['res_soleil2018/GGH/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos2']
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# white_estimator = WhiteEstimator(open_size=75, close_size=75, average_size=75)
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white_estimator = WhiteEstimator(open_size=75, close_size=75, average_size=75)
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# white_estimate = white_estimator.estimate_white([sequence], ['DM300_327-353_fluo'])
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white_estimate = white_estimator.estimate_white([sequence], ['DM300_327-353_fluo'])
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# # find_white_reference_image(white_estimate, sequence.get_white())
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# find_white_reference_image(white_estimate, sequence.get_white())
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# print(white_estimate)
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print(white_estimate)
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# IImageEngine.get_instance().debugger.on_image(white_estimate, 'white_estimate')
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IImageEngine.get_instance().debugger.on_image(white_estimate, 'white_estimate')
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# # assert False, "hellooooo"
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# assert False, "hellooooo"
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# print('end of test_estimate_white')
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print('end of test_estimate_white')
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# def test_uniform_lighting_correction(self):
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def test_uniform_lighting_correction(self):
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# non_uniform_sequence = self.catalog.sequences['res_soleil2018/GGH/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos0']
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non_uniform_sequence = self.catalog.sequences['res_soleil2018/GGH/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos0']
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# uniform_sequence = correct_non_uniform_lighting(non_uniform_sequence, 'DM300_nofilter_vis', white_estimator=WhiteEstimator(open_size=75, close_size=75, average_size=75)) # pylint: disable=unused-variable
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uniform_sequence = correct_non_uniform_lighting(non_uniform_sequence, 'DM300_nofilter_vis', white_estimator=WhiteEstimator(open_size=75, close_size=75, average_size=75)) # pylint: disable=unused-variable
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# def test_template_matcher(self):
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def test_template_matcher(self):
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# sequence = self.catalog.sequences['res_soleil2018/GGH/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos0']
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sequence = self.catalog.sequences['res_soleil2018/GGH/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos0']
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# stack = sequence.as_hyperstack(['DM300_nofilter_vis'], selected_frames=[0])
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stack = sequence.as_hyperstack(['DM300_nofilter_vis'], selected_frames=[0])
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# first_image = stack.get_image(frame_index=0)
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first_image = stack.get_image(frame_index=0)
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# x_min = 423
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x_min = 423
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# x_max = 553
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x_max = 553
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# y_min = 419
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y_min = 419
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# y_max = 533
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y_max = 533
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# template_trap_aabb = Aabb(x_min, y_min, x_max, y_max)
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template_trap_aabb = Aabb(x_min, y_min, x_max, y_max)
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# template_trap_image = first_image.get_subimage(template_trap_aabb)
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template_trap_image = first_image.get_subimage(template_trap_aabb)
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# for image in [first_image, template_trap_image]:
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for image in [first_image, template_trap_image]:
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# print(image.get_pixel_type(), image.get_width(), image.get_height())
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print(image.get_pixel_type(), image.get_width(), image.get_height())
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# # the typical value of peaks is -2.e10 and the value between peaks is below -8.0e10
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# the typical value of peaks is -2.e10 and the value between peaks is below -8.0e10
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# threshold = -3.0e10
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threshold = -3.0e10
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# tolerance = 1.0e10
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tolerance = 1.0e10
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# maxima_finder = MaximaFinder(threshold, tolerance)
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maxima_finder = MaximaFinder(threshold, tolerance)
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# template_matcher = TemplateMatcher(maxima_finder)
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template_matcher = TemplateMatcher(maxima_finder)
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# matches = template_matcher.match_template(first_image, template_trap_image)
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matches = template_matcher.match_template(first_image, template_trap_image)
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# num_traps = len(matches)
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num_traps = len(matches)
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# print("number of traps found : %d" % num_traps)
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print("number of traps found : %d" % num_traps)
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# num_expected_traps = 13 # 13 traps are completely visible in the first image
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num_expected_traps = 13 # 13 traps are completely visible in the first image
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# self.assertAlmostEqual(len(matches), num_expected_traps, delta=1.0)
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self.assertAlmostEqual(len(matches), num_expected_traps, delta=1.0)
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# def test_traps_detector(self):
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def test_traps_detector(self):
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# # the typical value of peaks is -500 and the value between peaks is below -2500
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# the typical value of peaks is -500 and the value between peaks is below -2500
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# threshold = -1500.0
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threshold = -1500.0
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# tolerance = 1500
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tolerance = 1500
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# maxima_finder = MaximaFinder(threshold, tolerance)
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maxima_finder = MaximaFinder(threshold, tolerance)
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# template_matcher = TemplateMatcher(maxima_finder)
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template_matcher = TemplateMatcher(maxima_finder)
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# traps_detector = TrapsDetector(template_matcher)
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traps_detector = TrapsDetector(template_matcher)
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# sequence = self.catalog.sequences['res_soleil2018/GGH/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos0']
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sequence = self.catalog.sequences['res_soleil2018/GGH/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos0']
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# x_min = 423
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x_min = 423
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# x_max = 553
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x_max = 553
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# y_min = 419
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y_min = 419
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# y_max = 533
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y_max = 533
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# trap_aabb = Aabb(x_min, y_min, x_max, y_max)
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trap_aabb = Aabb(x_min, y_min, x_max, y_max)
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# traps_mask = traps_detector.compute_traps_mask(sequence, 'DM300_nofilter_vis', trap_aabb)
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traps_mask = traps_detector.compute_traps_mask(sequence, 'DM300_nofilter_vis', trap_aabb)
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# measured_mean_value = traps_mask.get_mean_value()
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measured_mean_value = traps_mask.get_mean_value()
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# expected_traps_coverage = 0.07909
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expected_traps_coverage = 0.07909
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# traps_pixel_value = 255.0
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traps_pixel_value = 255.0
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# expected_mean_value = expected_traps_coverage * traps_pixel_value
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expected_mean_value = expected_traps_coverage * traps_pixel_value
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# print("expected_mean_value: %f" % expected_mean_value)
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print("expected_mean_value: %f" % expected_mean_value)
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# print("measured_mean_value: %f" % measured_mean_value)
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print("measured_mean_value: %f" % measured_mean_value)
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# self.assertAlmostEqual(measured_mean_value, expected_mean_value, delta=0.01)
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self.assertAlmostEqual(measured_mean_value, expected_mean_value, delta=0.01)
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# def test_visible_traps_sequence_processing(self):
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def test_visible_traps_sequence_processing(self):
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# traps_sequence = self.catalog.sequences['res_soleil2018/GGH/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos0']
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traps_sequence = self.catalog.sequences['res_soleil2018/GGH/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos0']
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# visible_traps_sequence = traps_sequence.as_hyperstack(['DM300_nofilter_vis'])
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visible_traps_sequence = traps_sequence.as_hyperstack(['DM300_nofilter_vis'])
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# background_estimator = EmptyFrameBackgroundEstimator(empty_frame_index=39)
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background_estimator = EmptyFrameBackgroundEstimator(empty_frame_index=39)
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# processor = GlobulesAreaEstimator(background_estimator=background_estimator, particle_threshold=2000.0)
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processor = GlobulesAreaEstimator(background_estimator=background_estimator, particle_threshold=2000.0)
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# results = processor.detect_particles(visible_traps_sequence)
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results = processor.detect_particles(visible_traps_sequence)
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# save_hdf5_file('results.h5', results)
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save_hdf5_file('results.h5', results)
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# # results file could be checked with "h5dump --xml ./lipase.git/results.h5"
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# results file could be checked with "h5dump --xml ./lipase.git/results.h5"
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# first_frame_measured_ratio = results['globules_area_ratio'][(0,)]
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first_frame_measured_ratio = results['globules_area_ratio'][(0,)]
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# first_frame_expected_ratio = 0.008
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first_frame_expected_ratio = 0.008
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# self.assertAlmostEqual(first_frame_measured_ratio, first_frame_expected_ratio, delta=0.01)
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self.assertAlmostEqual(first_frame_measured_ratio, first_frame_expected_ratio, delta=0.01)
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def test_circle_detector(self):
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def test_circle_detector(self):
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traps_sequence = self.catalog.sequences['res_soleil2018/GGH/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos0']
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traps_sequence = self.catalog.sequences['res_soleil2018/GGH/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos0']
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visible_traps_sequence = traps_sequence.as_hyperstack(['DM300_nofilter_vis'])
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visible_traps_sequence = traps_sequence.as_hyperstack(['DM300_nofilter_vis'])
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src_image = visible_traps_sequence.get_image(frame_index=0)
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src_image = visible_traps_sequence.get_image(frame_index=0)
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ie = IImageEngine.get_instance()
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# ie = IImageEngine.get_instance()
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detector = CircularSymmetryDetector(max_radius=10.0)
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detector = CircularSymmetryDetector(max_radius=32.0, num_angular_sectors=4, num_radial_sectors=8)
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radial_profiles = detector.compute_radial_profiles(src_image)
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radial_profiles, angular_variance_avg_image = detector.compute_radial_profiles(src_image) # pylint: disable=unused-variable
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# def test_lipase_process(self):
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# def test_lipase_process(self):
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# lipase = Lipase(self.catalog, debugger=NullDebugger())
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# lipase = Lipase(self.catalog, debugger=NullDebugger())
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