Numpy array splitting based on data type?

Question

I have the following array:

arr = [ nan nan nan 1.600e-01 1.000e+00 1.600e-01 9.999e-01 1.000e-04 1.600e-01 1.010e-01 nan 1.600e-01]

How I can obtain the following lists?

listA = [nan nan nan] #values in position 0, 1, 2
listB = [1.600e-01 1.000e+00 1.600e-01 9.999e-01 1.000e-04 1.600e-01 1.010e-01] #values in position 3 to 9
listC = [nan] #the values in position 10
listD = [1.600e-01] # the values in position 11

Thank you

listA has 2 items, but in comment you said there were 3 values. Is it a typo? — lsv
– lsv, Commented Oct 11, 2018 at 12:31
listA = [nan nan nan] #values in position 0, 1, 2 listB = [1.600e-01 1.000e+00 1.600e-01 9.999e-01 1.000e-04 1.600e-01 1.010e-01] #values in position 3 to 9 listC = [nan] #the values in position 10 listD = [1.600e-01] # the values in position 11 — Raffaele Salzano
– Raffaele Salzano, Commented Oct 11, 2018 at 12:44

Khalil Al Hooti · Accepted Answer · 2018-10-11 13:06:47Z

3

use numpy split to split array based on a condition. the condition is defined whenever np.diff(np.isnan(arr))== True

np.split(arr, np.where(np.diff(np.isnan(arr))== True)[0]+1)

[array([nan, nan, nan]),
 array([1.600e-01, 1.000e+00, 1.600e-01, 9.999e-01, 1.000e-04, 1.600e-01,
        1.010e-01]),
 array([nan]),
 array([0.16])]

answered Oct 11, 2018 at 13:06

Khalil Al Hooti

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