numpy.ravel() is a function present in numpy module which allows us to change a 2 dimensional or multi dimensional array into a contiguous flattened array i.e 1 dimensional array with all input elements and of same type as it. A copy is made only when needed. If input array is masked then returned array is also masked.
Syntax:
numpy.ravel(x, order=’C’)
Parameters:
x : array_like
This reads the input array and all the elements are read in the order specified by the order parameter.
order:{‘C’,’F’,’A’,’K’} (optional)
This order parameter is optional.
- Order parameter ‘C’ means array flattens in row major order. The last axis change is fastest and the first axis change is slowest.
- Order parameter ‘F’ (Fortran contiguous memory order) means array flattens in the column major order. Here the first axis change is fastest and last axis change is slowest.
- Order parameter ‘A’ means read / write elements in Fortran like index order only if array is fortran contiguous memory order otherwise C like order.
- Order parameter ‘K’ means read / write elements in order present as it is in the system.
Returns:
This function returns a contiguous flattened array with same data type as input array and has equal size (x.size)
Example1:
import numpy as np
x = np.array([[4, 7, 8, 9], [16, 24, 86,45]])
y=np.ravel(x)
y
Example2:
import numpy as np
x = np.array([[23, 76, 11, 42], [74, 91, 8, 34]])
y = np.ravel(x)
print('Flattened array: \n', y)
y[1] = 121
print('Original array: \n', x)
The above example shows that any changes in flattened array will reflect in original array as you can see that value y[1] = 121 is changed in original array as well.
Example3:
import numpy as np
a = np.arange(12).reshape(3,4)
print('The original array is:\n',a)
print('\n')
print('After applying ravel function:',a.ravel())
print('\n' )
print('Applying ravel function in F-style ordering:',a.ravel(order = 'F'))
print('Applying ravel function in C-style ordering:',a.ravel(order = 'C'))
print('Applying ravel function in K-style ordering:',a.ravel(order = 'K'))
print('Applying ravel function in A-style ordering:',a.ravel(order = 'A'))
With the above examples we have seen about the ravel function and its ordering styles in detail. Now if you want to know more about numpy click here!
