A masked array in NumPy can be reshaped using the ma.reshape() function of the numpy.ma module. The new array with a new shape will still have the same data as the original array.
A masked array is an array that has any or all of its elements hidden or masked with a
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The ma.reshape() function takes the following syntax:
ma.reshape(a, new_shape, order='C')
The ma.reshape() function takes the following parameter values:
a: This is the input array and is required. new_shape: This is the desired shape of the output array. It is also a required parameter. order: This determines the order in which the array data should be viewed. It takes any of the following orders: "C", "F", "A", or "K". This is an optional parameter. The ma.reshape() function returns an array of the same data as the input array but with a different shape.
# A code to illustrate the ma.reshape() 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)# reshaping the arraynew_array = ma.reshape(my_array, (4,2), order = "F")# printing the new arrayprint(new_array)
numpy.ma module.ma.array() function to create a masked 2D array, my_array. It has the shape of (2, 4). This means that the two arrays have four elements each. my_array.ma.reshape() function to reshape the input array to an array of the shape, (4, 2). This means that the four arrays have two elements each. The result is assigned to a variable, new_array.new_array.