Question

I do not understand the behavior of this numpy.ma.max (min, mean, etc.)

import numpy as np
arr = np.ma.array([0,np.nan,1])
np.ma.max(arr)
-> nan

I thought this was supposed to return a value excluding nan‘s? The only way I can get a real value is

np.nanmax(np.asarray(arr))

Is this right, or am I using numpy.ma.max incorrectly?

Answer 1

You need to create the mask:

import numpy as np
arr = np.ma.array([0,np.nan,1])
print(np.ma.max(arr))
# >>>nan    # since there is no mask
marr = np.ma.masked_array([0,np.nan,1], np.isnan(arr))
print(np.ma.max(marr))
# >>>1.0    # since the mask tells mask to ignore the nan. The max of the rest (0,1) is 1.