user2983638 - 9 months ago 51

Python Question

I am plotting a collection of rectangles with

`matplotlib.patches`

`import matplotlib.pyplot as plt`

import matplotlib.patches as patches

fig = plt.figure(figsize=(14, 10))

for i in rectangles_list:

ax1 = fig.add_subplot(111, aspect='equal')

ax1.add_patch(patches.Rectangle(

(x[i], y[i]),

width[i],

height[i],

alpha = 1.0,

facecolor = colors_list[i]

)

)

plt.show()

The rectangles may be overlapping, therefore some of them may be completely hidden. Do you know if it is possible to get the colors of the visible rectangles? I mean the colors of the rectangles that are not completely hidden and therefore that can be actually viewed by the user. I was thinking to some function that returns the color of the pixels, but more intelligent ideas are welcome. If possible, I'd prefer to not use PIL. Unfortunately I cannot find any solution on the internet.

Answer Source

Following Vlass Sokolov comment and this Stackoverflow post by Joe Kington, here is how you could get a numpy array containing all the unique colors that are visible on a matplotlib figure:

```
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
import numpy as np
plt.close('all')
# Generate some data :
N = 1000
x, y = np.random.rand(N), np.random.rand(N)
w, h = np.random.rand(N)/10 + 0.05, np.random.rand(N)/10 + 0.05
colors = np.vstack([np.random.random_integers(0, 255, N),
np.random.random_integers(0, 255, N),
np.random.random_integers(0, 255, N)]).T
# Plot and draw the data :
fig = plt.figure(figsize=(7, 7), facecolor='white')
ax = fig.add_subplot(111, aspect='equal')
for i in range(N):
ax.add_patch(Rectangle((x[i], y[i]), w[i], h[i], fc=colors[i]/255., ec='none'))
ax.axis([0, 1, 0, 1])
ax.axis('off')
fig.canvas.draw()
# Save data in a rgb string and convert to numpy array :
rgb_data = np.fromstring(fig.canvas.tostring_rgb(), dtype=np.uint8, sep='')
rgb_data = rgb_data.reshape((int(len(rgb_data)/3), 3))
# Keep only unique colors :
rgb_data = np.vstack({tuple(row) for row in rgb_data})
# Show and save figure :
fig.savefig('rectangle_colors.png')
plt.show()
```