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# matplotlib.pyplot.nipy_spectral() in Python

• Last Updated : 22 Apr, 2020

Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. Pyplot is a state-based interface to a Matplotlib module which provides a MATLAB-like interface.

## matplotlib.pyplot.nipy_spectral() Function:

The nipy_spectral() function in pyplot module of matplotlib library is used to set the colormap to “nipy_spectral”.

Syntax:

```matplotlib.pyplot.nipy_spectral()
```

Parameters: This method does not accepts any parameters.

Return value: This method does not returns any value.

Below examples illustrate the matplotlib.pyplot.nipy_spectral() function in matplotlib.pyplot:

Example #1:

 `# Implementation of matplotlib function``import` `matplotlib.pyplot as plt``import` `matplotlib.tri as tri``import` `numpy as np ``        ` `ang ``=` `40``rad ``=` `10``radm ``=` `0.35``radii ``=` `np.linspace(radm, ``0.95``, rad)``        ` `angles ``=` `np.linspace(``0``, ``4` `*` `np.pi, ang)``angles ``=` `np.repeat(angles[..., np.newaxis], rad, axis ``=` `1``)``angles[:, ``1``::``2``] ``+``=` `np.pi ``/` `ang``        ` `x ``=` `(radii ``*` `np.cos(angles)).flatten()``y ``=` `(radii ``*` `np.sin(angles)).flatten()``z ``=` `(np.sin(``4` `*` `radii) ``*` `np.cos(``4` `*` `angles)).flatten()``        ` `triang ``=` `tri.Triangulation(x, y)``triang.set_mask(np.hypot(x[triang.triangles].mean(axis ``=` `1``),``                         ``y[triang.triangles].mean(axis ``=` `1``))``                ``< radm)``        ` `tpc ``=` `plt.tripcolor(triang, z, shading ``=``'flat'``)``plt.nipy_spectral()``plt.title(``'matplotlib.pyplot.nipy_spectral() function Example'``, fontweight ``=``"bold"``)``plt.show()`

Output:

Example #2:

 `# Implementation of matplotlib function``import` `matplotlib.pyplot as plt``import` `numpy as np``from` `matplotlib.colors ``import` `LogNorm``           ` `dx, dy ``=` `0.015``, ``0.05``x ``=` `np.arange(``-``3.0``, ``3.0``, dx)``y ``=` `np.arange(``-``3.0``, ``3.0``, dy)``X, Y ``=` `np.meshgrid(x, y)``        ` `extent ``=` `np.``min``(x), np.``max``(x), np.``min``(y), np.``max``(y)``         ` `       ` `Z1 ``=` `np.add.outer(``range``(``6``), ``range``(``6``)) ``%` `2``plt.imshow(Z1, cmap ``=``"binary_r"``, interpolation ``=``'nearest'``,``                 ``extent ``=` `extent, alpha ``=` `1``)``        ` `def` `geeks(x, y):``    ``return` `(``1` `-` `x ``/` `2` `+` `x``*``*``5` `+` `y``*``*``6``) ``*` `np.exp(``-``(x``*``*``2` `+` `y``*``*``2``))``        ` `Z2 ``=` `geeks(X, Y)``        ` `plt.imshow(Z2, alpha ``=` `0.7``, interpolation ``=``'bilinear'``,``                 ``extent ``=` `extent)``plt.nipy_spectral()``plt.title(``'matplotlib.pyplot.nipy_spectral() function Example'``, fontweight ``=``"bold"``)``plt.show()`

Output:

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