Renames fit->kundu_fit

ME-ICA · Jun 3, 2019 · 4d13bc6 · 4d13bc6
1 parent a594872
commit 4d13bc6
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Showing 4 changed files with 10 additions and 10 deletions.
diff --git a/tedana/metrics/__init__.py b/tedana/metrics/__init__.py
@@ -1,7 +1,7 @@
 # emacs: -*- mode: python-mode; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-
 # ex: set sts=4 ts=4 sw=4 et:
 
-from .fit import (
+from .kundu_fit import (
     dependence_metrics, kundu_metrics, get_coeffs, computefeats2
 )
 

diff --git a/tedana/metrics/fit.py → tedana/metrics/kundu_fit.py b/tedana/metrics/fit.py → tedana/metrics/kundu_fit.py
diff --git a/tedana/tests/test_model_fit_dependence_metrics.py b/tedana/tests/test_model_fit_dependence_metrics.py
@@ -5,7 +5,7 @@
 import numpy as np
 import pytest
 
-from tedana.metrics import fit
+from tedana.metrics import kundu_fit
 
 
 def test_break_dependence_metrics():
@@ -27,7 +27,7 @@ def test_break_dependence_metrics():
     # Shape of catd is wrong
     catd = np.empty((n_samples+1, n_echos, n_vols))
     with pytest.raises(ValueError) as e_info:
-        fit.dependence_metrics(catd=catd, tsoc=tsoc, mmix=mmix, mask=mask,
+        kundu_fit.dependence_metrics(catd=catd, tsoc=tsoc, mmix=mmix, mask=mask,
                                t2s=t2s, tes=tes, ref_img=ref_img,
                                reindex=False, mmixN=None, algorithm='kundu_v3')
     assert str(e_info.value) == ('First dimensions (number of samples) of '
@@ -40,7 +40,7 @@ def test_break_dependence_metrics():
     catd = np.empty((n_samples, n_echos, n_vols))
     t2s = np.empty((n_samples+1, n_vols))
     with pytest.raises(ValueError) as e_info:
-        fit.dependence_metrics(catd=catd, tsoc=tsoc, mmix=mmix, mask=mask,
+        kundu_fit.dependence_metrics(catd=catd, tsoc=tsoc, mmix=mmix, mask=mask,
                                t2s=t2s, tes=tes, ref_img=ref_img,
                                reindex=False, mmixN=None, algorithm='kundu_v3')
     assert str(e_info.value) == ('First dimensions (number of samples) of '
@@ -53,7 +53,7 @@ def test_break_dependence_metrics():
     t2s = np.empty((n_samples, n_vols))
     tsoc = np.empty((n_samples+1, n_vols))
     with pytest.raises(ValueError) as e_info:
-        fit.dependence_metrics(catd=catd, tsoc=tsoc, mmix=mmix, mask=mask,
+        kundu_fit.dependence_metrics(catd=catd, tsoc=tsoc, mmix=mmix, mask=mask,
                                t2s=t2s, tes=tes, ref_img=ref_img,
                                reindex=False, mmixN=None, algorithm='kundu_v3')
     assert str(e_info.value) == ('First dimensions (number of samples) of '
@@ -66,7 +66,7 @@ def test_break_dependence_metrics():
     catd = np.empty((n_samples, n_echos+1, n_vols))
     tsoc = np.empty((n_samples, n_vols))
     with pytest.raises(ValueError) as e_info:
-        fit.dependence_metrics(catd=catd, tsoc=tsoc, mmix=mmix, mask=mask,
+        kundu_fit.dependence_metrics(catd=catd, tsoc=tsoc, mmix=mmix, mask=mask,
                                t2s=t2s, tes=tes, ref_img=ref_img,
                                reindex=False, mmixN=None, algorithm='kundu_v3')
     assert str(e_info.value) == ('Second dimension of catd ({0}) does not '
@@ -77,7 +77,7 @@ def test_break_dependence_metrics():
     # Shape of catd is wrong
     catd = np.empty((n_samples, n_echos, n_vols+1))
     with pytest.raises(ValueError) as e_info:
-        fit.dependence_metrics(catd=catd, tsoc=tsoc, mmix=mmix, mask=mask,
+        kundu_fit.dependence_metrics(catd=catd, tsoc=tsoc, mmix=mmix, mask=mask,
                                t2s=t2s, tes=tes, ref_img=ref_img,
                                reindex=False, mmixN=None, algorithm='kundu_v3')
     assert str(e_info.value) == ('Number of volumes in catd '
@@ -90,7 +90,7 @@ def test_break_dependence_metrics():
     catd = np.empty((n_samples, n_echos, n_vols))
     t2s = np.empty((n_samples, n_vols+1))
     with pytest.raises(ValueError) as e_info:
-        fit.dependence_metrics(catd=catd, tsoc=tsoc, mmix=mmix, mask=mask,
+        kundu_fit.dependence_metrics(catd=catd, tsoc=tsoc, mmix=mmix, mask=mask,
                                t2s=t2s, tes=tes, ref_img=ref_img,
                                reindex=False, mmixN=None, algorithm='kundu_v3')
     assert str(e_info.value) == ('Number of volumes in catd ({0}) '

diff --git a/tedana/tests/test_model_kundu_metrics.py b/tedana/tests/test_model_kundu_metrics.py
@@ -6,7 +6,7 @@
 import numpy as np
 import pandas as pd
 
-from tedana.metrics import fit
+from tedana.metrics import kundu_fit
 
 
 def test_smoke_kundu_metrics():
@@ -34,5 +34,5 @@ def test_smoke_kundu_metrics():
     metric_maps['Br_R2_clmaps'] = np.random.randint(low=0, high=2,
                                                     size=(n_voxels, n_comps))
 
-    comptable = fit.kundu_metrics(comptable, metric_maps)
+    comptable = kundu_fit.kundu_metrics(comptable, metric_maps)
     assert comptable is not None