Fix color functions

and remove bob.math and bob.core

bob/bio/face/algorithm/Histogram.py

@@ -2,12 +2,63 @@
 # vim: set fileencoding=utf-8 :
 # Manuel Guenther <Manuel.Guenther@idiap.ch>
 
-import bob.math
-
 import numpy
 
 from bob.bio.base.algorithm import Algorithm
 
+def chi_square(*args):
+  """
+  Calculates the chi-square distance between two histograms.
+
+  @param hist1  The first histogram
+  @param hist2  The second histogram
+
+  @returns The chi-square distance between the two histograms
+  """
+  if len(args) == 2:
+    h1, h2 = args
+    d = 0
+    for i in range(h1.shape[0]):
+      if h1[i] != h2[i]: d += int(((h1[i] - h2[i])**2) / (h1[i] + h2[i]))
+    return d
+  else:
+    # histogram intersection with sparse histograms
+    index_1, value_1, index_2, value_2 = args
+    raise NotImplementedError("chi_square distance with sparse histograms is not implemented yet")
+
+
+def histogram_intersection(*args):
+  """
+  Calculates the histogram intersection between two histograms.
+
+  @param hist1  The first histogram
+  @param hist2  The second histogram
+
+  @returns The histogram intersection between the two histograms
+  """
+  if len(args) == 2:
+    hist1, hist2 = args
+    return numpy.sum(numpy.minimum(hist1, hist2))
+  else:
+    # histogram intersection with sparse histograms
+    index_1, value_1, index_2, value_2 = args
+    i1, i2, i1_end, i2_end = 0, 0, index_1.shape[0], index_2.shape[0]
+    p1, p2 = index_1[i1], index_2[i2]
+    sum = 0
+    while i1 < i1_end and i2 < i2_end:
+      p1 = index_1[i1]
+      p2 = index_2[i2]
+      if p1 == p2:
+        sum += numpy.minimum(value_1[i1], value_2[i2])
+        i1 += 1
+        i2 += 1
+      elif p1 < p2:
+        i1 += 1
+      else:
+        i2 += 1
+    return sum
+
+
 class Histogram (Algorithm):
   """Computes the distance between histogram sequences.
 
@@ -30,7 +81,7 @@ class Histogram (Algorithm):
 
   def __init__(
       self,
-      distance_function = bob.math.chi_square,
+      distance_function = chi_square,
       is_distance_function = True,
       multiple_probe_scoring = 'average'
   ):