The given mapping function is used to find, for each point in the output, the corresponding coordinates in the input
Syntax: scipy.ndimage.interpolation.geometric_transform(input, mapping, order=3)
Parameters
- input : takes an array.
- mapping : accepts a tuple data structure similar to length of given output array rank.
- order : int parameter. which is a spline interpolation and the default value is 3.
Returns: Returns an n d array.
Example 1:
Python3
from scipy import ndimage # importing numpy module for # processing the arrays import numpy as np # creating an 2 dimensional array with # 5 * 5 dimensions a = np.arrange( 25 ).reshape(( 5 , 5 )) print ( 'a' ) print (a) # reducing dimensions function def shift_func(output_coords): return (output_coords[ 0 ] - 0.7 , output_coords[ 1 ] - 0.7 ) # performing geometric transform operation ndimage.geometric_transform(a, shift_func) |
Output:
Example 2:
Python3
from scipy import ndimage # importing numpy module for # processing the arrays import numpy as np # create 4 * 4 dim array. b = np.arrange( 16 ).reshape(( 4 , 4 )) # reducing dimensions function def shift_func(output_coords): return (output_coords[ 0 ] - 0.1 , output_coords[ 1 ] - 0.2 ) ndimage.geometric_transform(b, shift_func) |
Output: