The size of an array in NumPy describes the number of elements in the given array. For example, an array whose size is (4, 2) means that it contains eight elements.
A masked array is an array that has any or all of its elements hidden or masked with a
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We use the ma.resize() function of the numpy.ma module to resize a masked array to a new dimension.
The ma.resize() function takes the following syntax:
ma.resize(a, new_shape)
The ma.resize() function takes the following parameter values:
a: This is the input array and is a required parameter. new_shape: This is the desired size of the output array. It is also a required parameter. The ma.resize() function returns an array of the same data as the input array but with a different size.
# A code to illustrate the ma.resize() function in NumPY# importing the numpy.ma moduleimport numpy.ma as ma# creating a masked arraymy_array = ma.array([[1, 2, 3, 4] ,[5, 6, 7, 8]], mask=[1,0,1,0,1,0,1,0])# printing the input arrayprint(my_array)# resizing the arraynew_array = ma.resize(my_array, (5,10))# printing the new arrayprint(new_array)
numpy.ma module.ma.array() function to create a masked 2D array my_array whose shape is (2, 4). This means that the two arrays have four elements each. my_array.ma.resize() function into an array whose size is (5, 10). This means it is an array containing 50 elements. We assign the result to a variable, new_array.new_array.