Changeset 822

Timestamp:

08/17/15 05:56:16 (9 months ago)

Author:

mmckerns

Message:

moved Lnorm to mystic.math.distance; fix: typo in mystic.math.mad

Location:

mystic/_math

Files:

• distance.py (modified) (1 diff)
• measures.py (modified) (3 diffs)

mystic/_math/distance.py

@@ -15 +15 @@
 """
 debug = False 
+
+def Lnorm(weights, p=1):
+  "calculate L-p norm of weights"
+  # weights is a numpy array
+  # p is an int
+  if not p:
+    w = float(len(weights[weights != 0.0])) # total number of nonzero elements
+  else:
+    w = float(sum(abs(weights**p)))**(1./p)
+  return w
 
 def absolute_distance(x, xp, up=False, dmin=0):

mystic/_math/measures.py

@@ -15 +15 @@
 from mystic.symbolic import generate_conditions, generate_penalty
 from mystic.math import almostEqual
+from mystic.math.distance import Lnorm
 
 def weighted_select(samples, weights, mass=1.0):
@@ -388 +389 @@
 
 
-def Lnorm(weights, n=1):
-  "calculate L-n norm of weights"
-  # weights is a numpy array
-  # n is an int
-  if not n:
-    w = float(len(weights[weights != 0.0])) # total number of nonzero elements
-  else:
-    w = float(sum(abs(weights**n)))**(1./n)
-  return w
-
-
 def normalize(weights, mass='l2', zsum=False, zmass=1.0):
   """normalize a list of points (e.g. normalize to 1.0)
@@ -575 +565 @@
     weights -- a list of sample weights
 """
-    s = sarray(samples)
+    s = asarray(samples)
     return median(abs(s - median(samples,weights)),weights) # * scale