From a250405b48b09653124d07ace32685c24e5f5a57 Mon Sep 17 00:00:00 2001 From: e-koch Date: Tue, 7 Mar 2017 17:33:57 -0700 Subject: [PATCH 1/5] Default to p=0.2 and normalize by the spectral norm --- turbustat/statistics/threeD_to_twoD.py | 9 +++------ 1 file changed, 3 insertions(+), 6 deletions(-) diff --git a/turbustat/statistics/threeD_to_twoD.py b/turbustat/statistics/threeD_to_twoD.py index fde1f67f..71cafdb6 100644 --- a/turbustat/statistics/threeD_to_twoD.py +++ b/turbustat/statistics/threeD_to_twoD.py @@ -6,7 +6,7 @@ import numpy as np -def intensity_data(cube, p=0.1, noise_lim=0.1, norm=True): +def intensity_data(cube, p=0.2, noise_lim=-np.inf, norm=True): ''' Clips off channels below the given noise limit and keep the upper percentile specified. @@ -61,7 +61,7 @@ def intensity_data(cube, p=0.1, noise_lim=0.1, norm=True): def _format_data(cube, data_format='intensity', num_spec=1000, - noise_lim=0.0, p=0.1, normalize=True): + noise_lim=-np.inf, p=0.2, normalize=True): ''' Rearrange data into a 2D object using the given format. ''' @@ -97,10 +97,7 @@ def _format_data(cube, data_format='intensity', num_spec=1000, # Normalize by rescaling the data to an interval between 0 and 1 # Ignore all values of 0, since they're just filled in. if normalize: - nonzero = np.nonzero(data_matrix) - ptp = np.ptp(data_matrix[nonzero]) - data_matrix[nonzero] = \ - (data_matrix[nonzero] - data_matrix[nonzero].min()) / ptp + data_matrix /= np.linalg.norm(data_matrix, ord=2) return data_matrix From 4582b379fee9562f38ab2bdaf7a21daff59c7e84 Mon Sep 17 00:00:00 2001 From: e-koch Date: Tue, 7 Mar 2017 17:59:13 -0700 Subject: [PATCH 2/5] Need sqrt to be consistent w/ the Cramer kernel, which is implied by our normalization constants --- turbustat/statistics/cramer/cramer.py | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/turbustat/statistics/cramer/cramer.py b/turbustat/statistics/cramer/cramer.py index 963b2ef3..d070cc73 100644 --- a/turbustat/statistics/cramer/cramer.py +++ b/turbustat/statistics/cramer/cramer.py @@ -143,6 +143,14 @@ def cramer_statistic(self, n_jobs=1): larger, smaller, metric="euclidean", n_jobs=n_jobs) + # Take sqrt of each + # We default to using the Cramer kernel in Baringhaus & Franz (2004) + # \phi(dist) = sqrt(dist) / 2. + # The normalization values below reflect this + pairdist11 = np.sqrt(pairdist11) + pairdist12 = np.sqrt(pairdist12) + pairdist22 = np.sqrt(pairdist22) + term1 = 0.0 term2 = 0.0 term3 = 0.0 From 71db89cad06dc0aa81e0a7178712e8beb7e7cb01 Mon Sep 17 00:00:00 2001 From: e-koch Date: Tue, 7 Mar 2017 18:28:08 -0700 Subject: [PATCH 3/5] Remove importing UnitCase from Cramer tests --- turbustat/tests/test_cramer.py | 38 +++++++++++++++------------------- 1 file changed, 17 insertions(+), 21 deletions(-) diff --git a/turbustat/tests/test_cramer.py b/turbustat/tests/test_cramer.py index 4b1e5a93..d65f34dc 100644 --- a/turbustat/tests/test_cramer.py +++ b/turbustat/tests/test_cramer.py @@ -5,9 +5,6 @@ Test functions for Cramer ''' -from unittest import TestCase - -import numpy as np import numpy.testing as npt from ..statistics import Cramer_Distance @@ -15,27 +12,26 @@ dataset1, dataset2, computed_data, computed_distances -class testCramer(TestCase): +def test_cramer(): + tester = \ + Cramer_Distance(dataset1["cube"], + dataset2["cube"], + noise_value1=0.1, + noise_value2=0.1).distance_metric(normalize=False) - def test_cramer(self): - self.tester = \ - Cramer_Distance(dataset1["cube"], - dataset2["cube"], - noise_value1=0.1, - noise_value2=0.1).distance_metric(normalize=False) + npt.assert_allclose(tester.data_matrix1, + computed_data["cramer_val"]) + npt.assert_almost_equal(tester.distance, + computed_distances['cramer_distance']) - npt.assert_allclose(self.tester.data_matrix1, - computed_data["cramer_val"]) - npt.assert_almost_equal(self.tester.distance, - computed_distances['cramer_distance']) - def test_cramer_spatial_diff(self): +def test_cramer_spatial_diff(): - small_data = dataset1["cube"][0][:, :26, :26] + small_data = dataset1["cube"][0][:, :26, :26] - self.tester2 = Cramer_Distance(small_data, dataset2["cube"]) - self.tester2.distance_metric(normalize=False) - self.tester3 = Cramer_Distance(dataset2["cube"], small_data) - self.tester3.distance_metric(normalize=False) + tester2 = Cramer_Distance(small_data, dataset2["cube"]) + tester2.distance_metric(normalize=False) + tester3 = Cramer_Distance(dataset2["cube"], small_data) + tester3.distance_metric(normalize=False) - npt.assert_almost_equal(self.tester2.distance, self.tester3.distance) + npt.assert_almost_equal(tester2.distance, tester3.distance) From aae7776fa34cada2944ed90f559c351c43f2bd0d Mon Sep 17 00:00:00 2001 From: e-koch Date: Tue, 7 Mar 2017 18:28:19 -0700 Subject: [PATCH 4/5] Update unit test values for Cramer --- turbustat/tests/data/checkVals.npz | Bin 101048 -> 164424 bytes turbustat/tests/data/computed_distances.npz | Bin 3824 -> 3824 bytes 2 files changed, 0 insertions(+), 0 deletions(-) diff --git a/turbustat/tests/data/checkVals.npz 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GSN{eL1uM(| diff --git a/turbustat/tests/data/computed_distances.npz b/turbustat/tests/data/computed_distances.npz index 361c290540c0f614aad4e94fe4c2ff5a37a3af38..02686c8f9e8a9bea8d232120763a0a4392b17cd8 100644 GIT binary patch delta 380 zcmew$`$3jBz?+#xgn@y9gTZZb`b6GRW)Rg{1)?T1F@m|1s~D@n{2z>UV7ihCBL0!7 z7R)bXt_0I>nIYn-EHxZJ{ayzOj)Y8p$r3M~{rs}i?_O~h83q*VCdaeZgEc;6tpL+8 zY-M2jDjP&RoV^^(zsL@8fIkPsg5w+z2fA=V=!2ZrV0HgF9l#df+07s`nV(y1ax9ku zSfYW;0Zbp}asks^+z<^O+|FQrAGbZ2z5o^H<8eaxAcDsdEIEb86-?jZu?5pIymnwZ jmKS2^5?+Y-6JAHK=9_IwH^HuO=7YE*jSphW3O)}2HhFUV7ihCBL0!7 z7R)bXt_0I>nIYn-EHxZJ{a%c#a+xN-WQiAFtzLM{@Z;J|d<-boO^#=+2Wx!DS^=hG z*vi24RW^utID0vme~}&H0DlgM1;;rc4s_v!&<8oK!Rr2VI)E*{vztL?GC#N2 Date: Tue, 7 Mar 2017 18:46:36 -0700 Subject: [PATCH 5/5] Update CHANGE [skip ci] --- CHANGE.rst | 1 + 1 file changed, 1 insertion(+) diff --git a/CHANGE.rst b/CHANGE.rst index 65b1d49c..0e5f0e14 100644 --- a/CHANGE.rst +++ b/CHANGE.rst @@ -1,6 +1,7 @@ Version 1.0 (unreleased) ------------------------ +* #147 - Changed Cramer normalization to the spectral norm. * #146 - Allow weights to be passed in `StatsMoments`. * #144 - Fix the MVC: subtract mean velocity dispersion, not the array of dispersions. * #143 - Set periodic boundaries for dendrograms.