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# Python SciPy – ndimage.map_coordinates() function

• Last Updated : 06 Jul, 2021

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 â€˜constantâ€™. 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 arrays``import` `numpy as np` `# importing scipy``from` `scipy ``import` `ndimage` `# creating an array from 0 to 15 values``a ``=` `np.arrange(``16.``).reshape((``4``, ``4``))` `# finding coordinates``ndimage.map_coordinates(a, [[``0.3``, ``1``], [``0.5``, ``1``]], order``=``1``)`

Output:

`array([1.7, 5. ])`

Example 2:

## Python3

 `# importing numpy package for``# creating arrays``import` `numpy as np` `# importing scipy``from` `scipy ``import` `ndimage` `a ``=` `np.arrange(``25.``).reshape((``5``, ``5``))` `vals ``=` `[[``0.3``, ``1``], [``0.5``, ``1``]]` `# calculating mode``print``(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.]```

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