Possible fix for error: “ValueError: array must not contain infs or NaNs”

[pedrotnascimento]

Hi,
I received the error in subject and I looked for the reason in the source code.
I realized that my data, after the line below, in mca.py, has some of the values changed to "inf":
self.D_c = numpy.diag(1/numpy.sqrt(self.c))

then I inspect for the reason and I noticed that self.c had some 0.00000000 values.
So naturally, dividing 1/0 will give something wrong, although numpy didn't throw any error it didn't computed, but turned the value to "inf" and applied to self.D_c

So what I did was just alter the values that was 0 to some value next to 0( 0.00000000000001), and it did worked.

i'm sharing my code with you :

##my code
    # if self.c in the line below has any 0.0 then
    # self.D_c = numpy.diag(1/numpy.sqrt(self.c))
    # will occur division by 0, which numpy is not throwing
    # the code below intents to fix that error putting a number 
    # as close to 0 as founded by logs of numpy: decimal of 13 digits of 0
    # necessary use of panda 
  low_number = 0.00000000000001
  temp_dict = self.c.to_dict()
  temp_dtype = self.c.dtype
  for i in temp_dict:
  	if temp_dict[i] == 0:
  		temp_dict[i] = low_number
  self.c = pandas.Series(temp_dict, dtype=temp_dtype)
    ##end
  self.D_c = numpy.diag(1/numpy.sqrt(self.c))