numpy.MaskedArray.ravel()
function is used to return a 1D version of self mask array, as a view.
Syntax :
numpy.ma.ravel(self, order='C')
Parameters:
order : [‘C’, ‘F’, ‘A’, ‘K’, optional] By default, ‘C’ index order is used.
–> The elements of a are read using this index order.
–> ‘C’ means to index the elements in C-like order, with the last axis index changing fastest, back to the first axis index changing slowest.
–> ‘F’ means to index the elements in Fortran-like index order, with the first index changing fastest, and the last index changing slowest.
–> ‘A’ means to read the elements in Fortran-like index order if m is Fortran contiguous in memory, C-like order otherwise.
–> ‘K’ means to read the elements in the order they occur in memory, except for reversing the data when strides are negative.Return : [ MaskedArray] Flattened 1D masked array.
Code #1 :
# Python program explaining # numpy.MaskedArray.ravel() method # importing numpy as geek # and numpy.ma module as ma import numpy as geek import numpy.ma as ma # creating input array in_arr = geek.array([[ 1 , 2 ], [ 3 , - 1 ]]) print ( "Input array : " , in_arr) # Now we are creating a masked array. # by making two entry as invalid. mask_arr = ma.masked_array(in_arr, mask = [[ 0 , 1 ], [ 1 , 0 ]]) print ( "Masked array : " , mask_arr) # applying MaskedArray.ravel methods to mask array out_arr = mask_arr.ravel() print ( "1D view of masked array : " , out_arr) |
Input array : [[ 1 2] [ 3 -1]] Masked array : [[1 --] [-- -1]] 1D view of masked array : [1 -- -- -1]
Code #2 :
# Python program explaining # numpy.MaskedArray.ravel() method # importing numpy as geek # and numpy.ma module as ma import numpy as geek import numpy.ma as ma # creating input array in_arr = geek.array([[[ 2e8 , 3e - 5 ]], [[ - 45.0 , 2e5 ]]]) print ( "Input array : " , in_arr) # Now we are creating a masked array. # by making one entry as invalid. mask_arr = ma.masked_array(in_arr, mask = [[[ 1 , 0 ]], [[ 0 , 0 ]]]) print ( "3D Masked array : " , mask_arr) # applying MaskedArray.ravel methods to mask array out_arr = mask_arr.ravel() print ( "1D view of masked array : " , out_arr) |
Input array : [[[ 2.0e+08 3.0e-05]] [[-4.5e+01 2.0e+05]]] 3D Masked array : [[[-- 3e-05]] [[-45.0 200000.0]]] 1D view of masked array : [-- 3e-05 -45.0 200000.0]