Copy matplotlib figure to QClipboard with increased resolution

Question

In a pyQt application, I'm copying matplotlib figures (self.canvas) to a QClipboard instance using either

cb = QClipboard(self)
img = QImage(self.canvas.grab())
cb.setImage(img)

or

img = QPixmap(self.canvas.grab())
self.cb.setPixmap(img)

Both work well, however, I haven't managed to control the resolution of the exported image. This would be possible by creating and exporting a temporary file, however, this is slow and has potential problems due to file system restrictions:

self.canvas.figure.savefig(self.temp_file, dpi = 300, type = 'png')
temp_img = QImage(self.temp_file)
cb.setImage(temp_img)

So, is there a way to set the resolution of the copied image without taking a detour through the file system?

-------------------------------------

Edit: I just found out that the above doesn't work under pyqt4. Instead, you can use

img = QPixmap.grabWidget(self.canvas)
self.cb.setPixmap(img)

-------------------------------------

Edit: Another solution that nearly works is the following piece of code, unfortunately it changes the colors (back to matplotlib defaults?):

# construct image from raw rgba data, this changes the colormap:
size = self.canvas.size()
width, height = size.width(), size.height()
im = QImage(self.canvas.buffer_rgba(), width, height, QImage.Format_ARGB32)
self.cb.setImage(im)

Answer 1

The following is an incomplete answer. So further answers, making this complete or alternative solutions are still welcome.

You may, instead of saving the image to disk, save it to a filebuffer and read it from there. However, reading a buffer directly into QImage may be hard. This was asked here, but the answer uses a workaround to save the file to disk first. This is undesired here.

Instead, you may read the figure in terms of a numpy array into the QImage. This may involve the steps of

1. Saving the figure with the desired resolution to a buffer, then reading the buffer and creating a numpy array out of it. This is tackled in this question: How can I render a Matplotlib Axes object to an image (as a Numpy array)?
2. Creating a QImage from a numpy array. This is tackled in this question: How to set an numpy array image on a QWidget using PyQt5 and also Convert 16-bit grayscale to QImage

Unfortunately I am currently unable to get the RGB array to show correctly, but the following would the solution to showing the figure as Greyscale image:

import io
import sys
from PyQt4 import QtGui
import matplotlib.pyplot as plt
import numpy as np

def get_image():
    plt.plot([1,3,2])
    buff = io.BytesIO()
    plt.savefig(buff, format="png", dpi=100)
    buff.seek(0)
    img = plt.imread(buff)
    return img


class App(QtGui.QWidget):

    def __init__(self):
        super(App, self).__init__()
        self.setGeometry(300, 300, 250, 150)
        self.setLayout(QtGui.QVBoxLayout())
        label = QtGui.QLabel()
        label2 = QtGui.QLabel("Some other text label") 

        img = get_image()

        im = img.mean(axis=2)
        im = ((im - im.min()) / (im.ptp() / 255.0)).astype(np.uint8)
        print im.shape, im.max(), im.min()
        temp_img = QtGui.QImage(im,im.shape[1],im.shape[0],im.shape[1], QtGui.QImage.Format_Indexed8)
        pixmap = QtGui.QPixmap(temp_img)
        label.setPixmap(pixmap)

        self.layout().addWidget(label)
        self.layout().addWidget(label2)
        self.show()


if __name__ == '__main__':
    app = QtGui.QApplication([])
    ex = App()
    sys.exit(app.exec_())