 # Numpy MaskedArray.any () function | python

`numpy.MaskedArray.any()` returns True if any of the elements in the masked array evaluates to True.Masked values ​​are considered False during computation.

Syntax: ` numpy.MaskedArray.any (axis = None, out = None, keepdims) `

Parameters:
axis: [None or int or tuple of ints, optional] Axis or axes along which a logical AND reduction is performed.
out : [ndarray, optional] A location into which the result is stored.
– & gt; If provided, it must have a shape that the inputs broadcast to.
– & gt; If not provided or None, a freshly-allocated array is returned.
keepdims: [bool, optional] If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the input array.

Return: [bool or ndarray] A new boolean or ndarray is returned unless out is specified, in which case a reference to out is returned.

Code # 1:

 ` # Python program explaining ` ` # numpy.MaskedArray.any () method ` `   # import numy as geek # and numpy.ma module as ma ```` import numpy as geek import numpy.ma as ma   # create input array in_a rr = geek.array ([ 1 , 2 , 3 , - 1 , 5 ]) print ( "Input array:" , in_arr)   # Now we create a masked array # making the third record is invalid. mask_arr = ma .masked_array (in_arr, mask = [ 0 , 0 , 1 , 0 , 0 ]) print ( "Masked array:" , mask_arr)   # applying MaskedArray.anom methods to mask an array out_arr = mask_arr.anom () print ( "Output anomalies array:" , out_arr) ```

Output :

``` Input array: [1 2 3 -1 5] Masked array: [1 2 - -1 5] Output array: True     Code # 2:      ` ``       # Python program explaining    # numpy.MaskedArray.any () method        # import numy as geek    # and numpy.ma module as ma     import   numpy as geek    import   numpy.ma as ma       # create input array        in_arr   =   geek.array ([  1  ,   20  ,   30  ,   40  ,   50  ] )    print   (  "Input array: " , in_arr)       # We now create a masked array, making    # all entries as invalid.     mask_arr   =   ma.masked_array (in_arr, mask   =   `True`  )    print   (  "Masked array:"  , mask_arr)       # using MaskedArray.any methods to mask the array     out_arr   =   mask_arr.   any   ()    print   (  "Output array:"  , out_arr)     `` `  Output :  Input array: [1 20 30 40 50] Masked array: [- - - - -] Output array: -

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