Smoothing 2D map in python

Question

is there any way to smooth 2D map? Here is what I have got and I would like to smooth it. Measurement step was to big which results with such "bad" spectrum...

Here is a part of my code:

    X, Y = np.meshgrid(x,y)
    fig, ax = plt.subplots()
    plt.xlim(235,420)
    plt.xticks(np.arange(235,415,30))
    plt.yticks(np.arange(0,360,50))
    cs = ax.pcolormesh(X,Y,A,cmap=cm.rainbow, vmin = 0)#Greys_r
    plt.xlabel('wavelength [nm]')
    plt.ylabel('temperature [K]')
    plt.title(sample)
    cbar = fig.colorbar(cs)
    cbar.formatter.set_powerlimits((0, 0))
    cbar.update_ticks()

Look into [`np.convolve`](https://docs.scipy.org/doc/numpy/reference/generated/numpy.convolve.html) — pingul, May 16 '17 at 11:05
There is a Gaussian filter in the scipy.ndimage module, see [gaussian_filter](https://docs.scipy.org/doc/scipy-0.16.1/reference/generated/scipy.ndimage.filters.gaussian_filter.html). — Rob, May 16 '17 at 11:07

score 0 · Accepted Answer · answered May 17 '17 at 15:45

I found a way to do it. Here is how:

    fig = plt.figure()
    ax = fig.add_subplot(111)
    im = NonUniformImage(ax, interpolation='bilinear', extent=(180, 300, 10, 350), cmap=cm.jet)
    im.set_data(x, y, A)
    ax.images.append(im)
    ax.set_xlim(180, 300)
    ax.set_ylim(10, 350)
    plt.xlabel('wavelength [nm]')
    plt.ylabel('temperature [K]')
    plt.title(sample)
    cbar = fig.colorbar(im)
    cbar.formatter.set_powerlimits((0, 0))
    cbar.update_ticks()
    plt.savefig('map.png')
    plt.show()
    plt.close()

Smoothing 2D map in python

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