Fixed bug where affinity matrix was not always correctly symmetrized …

…in sweeps. Also added plotting utility module. Updated callback tolerances to be more conservative. Implemented kEff calculators.

EMBEDR/_affinity.py

@@ -210,4 +210,20 @@ def GaussianAff_fromPrec(distances,
     return P
 
 
-
+@jit(nopython=True)
+def calculate_kEff(P, row_idx, alpha_nu=0.02):
+
+    kEff_arr = np.zeros_like(row_idx)[:-1]
+
+    for ii in range(len(kEff_arr)):
+        ## Find the max value in the row.
+        P_row_max = -1
+        for jj in range(row_idx[ii], row_idx[ii + 1]):
+            if P[jj] > P_row_max:
+                P_row_max = P[jj]
+        ## Count the number larger
+        for jj in range(row_idx[ii], row_idx[ii + 1]):
+            if P[jj] > (P_row_max * alpha_nu):
+                kEff_arr[ii] += 1
+
+    return kEff_arr

EMBEDR/callbacks.py

@@ -128,7 +128,7 @@ class QuitNoExaggerationPhase(Callback):
     gradient descent when the relative changes in DKL are less than a
     specified tolerance.
     """
-    def __init__(self, rel_err_tol=1.e-5, min_iter=250, verbose=False):
+    def __init__(self, rel_err_tol=1.e-6, min_iter=250, verbose=False):
         self.iter_count = 0
         self.last_log_time = None
         self.init_DKL = -1.0