This function is used to map the given array to new coordinates by interpolation. The array of coordinates is used to find, for each point in the output, the corresponding coordinates in the input.
Syntax: scipy.ndimage.map_coordinates(input, coordinates, output=None, order=3,cval=0.0, prefilter=True)
Parameters
- input: which is of array_like – The input array.
- coordinates: which is of array_like- The coordinates at which input is evaluated.
- output: which is an array – The array in which to place the output.
- order: which is of int, – it is optional,The order of the spline interpolation,
- cval: it is a scalar,- it is optional,The Value to fill past edges of input if mode is ‘constant’. Default is 0.0.
- prefilter: it is of boolean type, it is optional. it is used to determine if the input array is prefiltered with spline_filter before interpolation.
Returns: map_coordinates: ndarray
Example 1:
Python3
# importing numpy package for# creating arraysimport numpy as np# importing scipyfrom scipy import ndimage# creating an array from 0 to 15 valuesa = np.arange(16.).reshape((4, 4))# finding coordinatesndimage.map_coordinates(a, [[0.3, 1], [0.5, 1]], order=1) |
Output:
array([1.7, 5. ])
Example 2:
Python3
# importing numpy package for# creating arraysimport numpy as np# importing scipyfrom scipy import ndimagea = np.arange(25.).reshape((5, 5))vals = [[0.3, 1], [0.5, 1]]# calculating modeprint(ndimage.map_coordinates(a, vals, order=1, mode='nearest'))print(ndimage.map_coordinates(a, vals, order=1, cval=0, output=bool))print(ndimage.map_coordinates(a, vals, order=1)) |
Output:
[2. 6.]
[ True True]
[2. 6.]
