From 552cbf9c6e4053a5660dede8eba003a0b10e3c79 Mon Sep 17 00:00:00 2001
From: idc9 <idc9@cornell.edu>
Date: Thu, 15 Oct 2020 15:45:17 -0400
Subject: [PATCH] fixed tests

---
 mvdr/mcca/tests/test_mcca.py |  2 +-
 mvdr/mcca/tests/utils.py     | 12 ++++++++----
 setup.py                     |  2 +-
 3 files changed, 10 insertions(+), 6 deletions(-)

diff --git a/mvdr/mcca/tests/test_mcca.py b/mvdr/mcca/tests/test_mcca.py
index 7c6eff5..32e9915 100644
--- a/mvdr/mcca/tests/test_mcca.py
+++ b/mvdr/mcca/tests/test_mcca.py
@@ -25,7 +25,7 @@ def test_mcca():
                 assert not out['centerers'][b].with_std
                 if params['center']:
                     assert np.allclose(out['centerers'][b].mean_,
-                                       Xs[b].mean(axis=1))
+                                       Xs[b].mean(axis=0))
                 else:
                     assert out['centerers'][b].mean_ is None
 
diff --git a/mvdr/mcca/tests/utils.py b/mvdr/mcca/tests/utils.py
index 9307fb3..0dbf3c5 100644
--- a/mvdr/mcca/tests/utils.py
+++ b/mvdr/mcca/tests/utils.py
@@ -1,8 +1,8 @@
 import numpy as np
 from sklearn.utils import check_random_state
 
+from mvlearn.utils import check_Xs
 
-from mvdr.mcca.block_processing import get_blocks_metadata
 from mvdr.linalg_utils import normalize_cols
 from mvdr.mcca.mcca import check_regs, get_mcca_gevp_data
 
@@ -51,7 +51,9 @@ def check_mcca_scores_and_loadings(Xs, out,
     common_norm_scores = out['common_norm_scores']
     centerers = out['centerers']
 
-    n_blocks, n_samples, n_features = get_blocks_metadata(Xs)
+    Xs, n_blocks, n_samples, n_features = check_Xs(Xs, multiview=True,
+                                                   return_dimensions=True)
+
 
     # make sure to apply centering transformations
     Xs = [centerers[b].transform(Xs[b]) for b in range(n_blocks)]
@@ -63,7 +65,7 @@ def check_mcca_scores_and_loadings(Xs, out,
 
     # check common norm scores are the column normalized sum of the
     # block scores
-    cns_pred = normalize_cols(sum(bs for bs in block_scores))
+    cns_pred = normalize_cols(sum(bs for bs in block_scores))[0]
     assert np.allclose(cns_pred, common_norm_scores)
 
     if check_normalization:
@@ -90,7 +92,9 @@ def check_mcca_gevp(Xs, out, regs):
     evals = out['evals']
     centerers = out['centerers']
 
-    n_blocks, n_samples, n_features = get_blocks_metadata(Xs)
+    Xs, n_blocks, n_samples, n_features = check_Xs(Xs, multiview=True,
+                                                   return_dimensions=True)
+
     regs = check_regs(regs=regs, n_blocks=n_blocks)
 
     # make sure to apply centering transformations
diff --git a/setup.py b/setup.py
index e64fdbd..c3d3557 100644
--- a/setup.py
+++ b/setup.py
@@ -5,7 +5,7 @@
 #            return f.read()
 
 install_requires = ['numpy', 'scipy', 'scikit-learn', 'matplotlib', 'seaborn',
-                    'joblib']
+                    'joblib', 'mvlearn']
 
 
 setup(name='mvdr',