Using the mask of the bool array, replace False with NaN

Question

I have two arrays,

a = array([ [ 0.93825418, 0.60731973, 0.44218921, 0.90888805, 0.97695114], [ 0.27422807, 0.75870153, 0.12154102, 0.89137678, 0.04257262], [ 0.32855867, 0.17215507, 0.00302302, 0.95395069, 0.02596567], [ 0.18385244, 0.09108341, 0.27925367, 0.0177183 , 0.41035188], [ 0.87229432, 0.73573982, 0.98554476, 0.72321398, 0.98316711], [ 0.16474265, 0.5308054 , 0.27913615, 0.59107689, 0.6480463 ], [ 0.88356436, 0.22343885, 0.74900285, 0.43895017, 0.74993129], [ 0.08097611, 0.48984607, 0.33991052, 0.06431022, 0.10753135], [ 0.67351561, 0.13165046, 0.41327765, 0.21768539, 0.7337069 ], [ 0.65609999, 0.06241059, 0.3400624 , 0.13234171, 0.23679716] ]) b = array([ [False, True, True, False, False], [ True, False, False, False, False], [ True, True, False, False, False], [False, False, True, False, True], [False, False, False, True, False], [False, True, True, True, True], [False, True, False, True, True], [False, True, True, False, False], [ True, True, True, True, True], [ True, False, True, False, True] ], dtype = bool) 

Now I want to use b to mask a , save True in a and replace False with NaN , getting a new array that has the form of type a .

How to do it?

Answer 1

You can use logical indexing :

 a[~b] = np.nan 

This replaces all the values ​​in a corresponding to the False values ​​in mask b using np.nan :

 >>> a array([[ nan, 0.60731973, 0.44218921, nan, nan], [ 0.27422807, nan, nan, nan, nan], [ 0.32855867, 0.17215507, nan, nan, nan], [ nan, nan, 0.27925367, nan, 0.41035188], [ nan, nan, nan, 0.72321398, nan], [ nan, 0.5308054 , 0.27913615, 0.59107689, 0.6480463 ], [ nan, 0.22343885, nan, 0.43895017, 0.74993129], [ nan, 0.48984607, 0.33991052, nan, nan], [ 0.67351561, 0.13165046, 0.41327765, 0.21768539, 0.7337069 ], [ 0.65609999, nan, 0.3400624 , nan, 0.23679716]])