[subbarray] logging

GPy/inference/latent_function_inference/var_dtc.py

@@ -221,9 +221,11 @@ class VarDTCMissingData(LatentFunctionInference):
             inan = self._inan
             has_none = True
         if has_none:
+            print "caching missing data slices, this can take several minutes..."
             from ...util.subarray_and_sorting import common_subarrays
             self._subarray_indices = []
-            for v,ind in common_subarrays(inan, 1).iteritems():
+            csa = common_subarrays(inan, 1)
+            for v,ind in csa.iteritems():
                 if not np.all(v):
                     v = ~np.array(v, dtype=bool)
                     ind = np.array(ind, dtype=int)

GPy/util/subarray_and_sorting.py

@@ -16,13 +16,13 @@ def common_subarrays(X, axis=0):
     for the subarray in X, where index is the index to the remaining axis.
 
     :param :class:`np.ndarray` X: 2d array to check for common subarrays in
-    :param int axis: axis to apply subarray detection over. 
-        When the index is 0, compare rows -- columns, otherwise.   
+    :param int axis: axis to apply subarray detection over.
+        When the index is 0, compare rows -- columns, otherwise.
 
     Examples:
     =========
 
-    In a 2d array:    
+    In a 2d array:
     >>> import numpy as np
     >>> X = np.zeros((3,6), dtype=bool)
     >>> X[[1,1,1],[0,4,5]] = 1; X[1:,[2,3]] = 1
@@ -48,6 +48,8 @@ def common_subarrays(X, axis=0):
     assert X.ndim == 2 and axis in (0,1), "Only implemented for 2D arrays"
     subarrays = defaultdict(list)
     cnt = count()
+    if axis == 0: size = X.shape[0]
+    else: size = X.shape[1]
     logger = logging.getLogger("common_subarrays")
     def accumulate(x, s, c):
         logger.debug("creating tuple")
@@ -55,7 +57,7 @@ def common_subarrays(X, axis=0):
         logger.debug("tuple done")
         col = c.next()
         iadd(s[t], [col])
-        logger.debug("added col {}".format(col))
+        logger.info("added col {} {:.2%}".format(col, col/float(size)))
         return None
     if axis == 0: [accumulate(x, subarrays, cnt) for x in X]
     else: [accumulate(x, subarrays, cnt) for x in X.T]
@@ -63,4 +65,4 @@ def common_subarrays(X, axis=0):
 
 if __name__ == '__main__':
     import doctest
-    doctest.testmod()
+    doctest.testmod()