问题
I have an (n, m) array that I've been visualizing with matplotlib.pyplot.imshow. I'd like to save this data in some type of raster graphics file (e.g. a png) so that:
- The colors are the ones shown with
imshow - Each element of the underlying array is exactly one pixel in the saved image -- meaning that if the underlying array is (n, m) elements, the image is NxM pixels. (I'm not interested in
interpolation='nearest'inimshow.) - There is nothing in the saved image except for the pixels corresponding to the data in the array. (I.e. there's no white space around the edges, axes, etc.)
How can I do this?
I've seen some code that can kind of do this by using interpolation='nearest' and forcing matplotlib to (grudgingly) turn off axes, whitespace, etc. However, there must be some way to do this more directly -- maybe with PIL? After all, I have the underlying data. If I can get an RGB value for each element of the underlying array, then I can save it with PIL. Is there some way to extract the RGB data from imshow? I can write my own code to map the array values to RGB values, but I don't want to reinvent the wheel, since that functionality already exists in matplotlib.
回答1:
As you already guessed there is no need to create a figure. You basically need three steps. Normalize your data, apply the colormap, save the image. matplotlib provides all the necessary functionality:
import numpy as np
import matplotlib.pyplot as plt
# some data (512x512)
import scipy.misc
data = scipy.misc.lena()
# a colormap and a normalization instance
cmap = plt.cm.jet
norm = plt.Normalize(vmin=data.min(), vmax=data.max())
# map the normalized data to colors
# image is now RGBA (512x512x4)
image = cmap(norm(data))
# save the image
plt.imsave('test.png', image)
While the code above explains the single steps, you can also let imsave do all three steps (similar to imshow):
plt.imsave('test.png', data, cmap=cmap)
Result (test.png):
来源：https://stackoverflow.com/questions/31544130/saving-an-imshow-like-image-while-preserving-resolution