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Numpy MaskedArray.ravel() function | Python

  • Last Updated : 03 Oct, 2019

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')

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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) 
Output:
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) 
Output:
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]



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