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fixing bug with centering

Author: Maithra

cca_core.py

@@ -321,8 +321,8 @@ def get_cca_similarity(acts1, acts2, epsilon=0., threshold=0.98,
              return_dict["invsqrt_yy"])
 
     # compute means
-    neuron_means1 = np.mean(acts1, axis=0, keepdims=True)
-    neuron_means2 = np.mean(acts2, axis=0, keepdims=True)
+    neuron_means1 = np.mean(acts1, axis=1, keepdims=True)
+    neuron_means2 = np.mean(acts2, axis=1, keepdims=True)
     return_dict["neuron_means1"] = neuron_means1
     return_dict["neuron_means2"] = neuron_means2
 

numpy_pca.py

@@ -36,7 +36,7 @@ def get_pca(acts, compute_dirns=False):
                                            "by datapoints")
 
     # center activations
-    means = np.mean(acts, axis=0, keepdims=True)
+    means = np.mean(acts, axis=1, keepdims=True)
     cacts = acts - means
 
     # compute PCA using SVD

numpy_pls.py

@@ -87,8 +87,8 @@ def get_pls_similarity(acts1, acts2):
   S = np.abs(S)
 
   # compute means 
-  neuron_means1 = np.mean(acts1, axis=0, keepdims=True)
-  neuron_means2 = np.mean(acts2, axis=0, keepdims=True)
+  neuron_means1 = np.mean(acts1, axis=1, keepdims=True)
+  neuron_means2 = np.mean(acts2, axis=1, keepdims=True)
 
   # collect return values
   return_dict = {}

pwcca.py

@@ -41,14 +41,14 @@ def compute_pwcca(acts1, acts2, epsilon=0.):
     if np.sum(sresults["x_idxs"]) <= np.sum(sresults["y_idxs"]):
         dirns = np.dot(sresults["coef_x"], 
                     (acts1[sresults["x_idxs"]] - \
-                     sresults["neuron_means1"])) + sresults["neuron_means1"]
+                     sresults["neuron_means1"][sresults["x_idxs"]])) + sresults["neuron_means1"][sresults["x_idxs"]]
         coefs = sresults["cca_coef1"]
         acts = acts1
         idxs = sresults["x_idxs"]
     else:
         dirns = np.dot(sresults["coef_y"], 
                     (acts1[sresults["y_idxs"]] - \
-                     sresults["neuron_means2"])) + sresults["neuron_means2"]
+                     sresults["neuron_means2"][sresults["y_idxs"]])) + sresults["neuron_means2"][sresults["y_idxs"]]
         coefs = sresults["cca_coef2"]
         acts = acts2
         idxs = sresults["y_idxs"]