Save Matplotlib as numpy array

plt2np.py

import matplotlib.pyplot as plt
import io
import numpy as np

import cv2

# === some statistics ===
x1 = np.linspace(0, 10, 100)
y1 = np.sin(x1)
x2 = np.linspace(-1, 1, 100)[:, None]
y2 = np.linspace(-1, 1, 100)[None, :]
im = np.sqrt(x2**2 + y2**2)

# your plot
fig, axs = plt.subplots(ncols=2)
axs[0].plot(x1, y1)
axs[1].imshow(im, cmap='viridis')
plt.tight_layout()

# dump to numpy array
io_buf = io.BytesIO()
fig.savefig(io_buf, format='raw')
io_buf.seek(0)

canvas = np.reshape(
    np.frombuffer(io_buf.getvalue(), dtype=np.uint8),
    (int(fig.bbox.bounds[3]), int(fig.bbox.bounds[2]), -1)
)[...,:3] # ensure only 3 channels RGB

io_buf.close()
plt.close('all')

cv2.imshow('PLOT', canvas[...,::-1]) #RGB2BGR

cv2.waitKey(0)