如何在Matplotlib中绘制模糊点

Question

As the question says, I'm looking for a way to plot blurred points using Matplotlib. I don't want to plot a set of points and then apply a filter to blurry the whole image. Instead of it, I would like to plot a set of points, each of them with an associated level of blur.

Thank you in advance.

Answer 1

Here's another work around. You can display an image at each location instead of a marker using a BboxImage . That way you can blur or manipulate the image any way you want. This tutorial has more about BboxImages .

import matplotlib.pyplot as plt
from scipy import ndimage
from matplotlib.image import BboxImage
from matplotlib.transforms import Bbox, TransformedBbox
import numpy as np

# Create and save an image with just a marker in it
fig1 = plt.figure()
ax1 = fig1.add_subplot(111)
ax1.plot(0.5,0.5,'*',ms=200)
ax1.set_ylim(0,1)
ax1.set_xlim(0,1)
plt.axis('off')
fig1.savefig('marker.png')

# Read in the same marker image
marker = plt.imread('marker.png')

# New figure and data
fig2 = plt.figure()
ax2 = fig2.add_subplot(111)
x = 8*np.random.rand(10) + 1
y = 8*np.random.rand(10) + 1
sigma = np.arange(10,60,5)

# Blur the marker and image plot the blurred image at each data point. 
for xi, yi, sigmai in zip(x,y,sigma):
    markerBlur = ndimage.gaussian_filter(marker,sigmai) # Blur the marker image

    # Create an BboxImage for the blurred marker and add it to the plot. 
    bb = Bbox.from_bounds(xi,yi,1,1)  
    bb2 = TransformedBbox(bb,ax2.transData)
    bbox_image = BboxImage(bb2,
                           norm = None,
                           origin=None,
                           clip_on=False)

    bbox_image.set_data(markerBlur)
    ax2.add_artist(bbox_image)

ax2.set_xlim(0,10)
ax2.set_ylim(0,10)
plt.show()

Answer 2

When you cannot make it, fake it.

import matplotlib.pyplot as plt
import numpy as np

# some random data
x = np.random.random(100)
y = np.random.random(100)
z = np.random.random(100)

# z reflects the amount of defocus at each dot
# if z=0, the point is small (1 pt)
# if z=1, the point is large (50 pt)
# each dot is composed of different layers
fig = plt.figure()
ax = fig.add_subplot(111)
for i in np.arange(.1,1.01,.1):
    ax.scatter(x, y, s=(50*i*(z*.9+.1))**2, color=(0,0,0,.5/i/10))

This gives:

This is by no means perfect, but something along these lines might suffice your needs. Things to consider:

• the point size is now in absolute units, it does not scale (requires more maths for scaling)
• if you want to have an equal amount of ink in each point, you will have to decrease the alpha value for larger blobs
• do you want to have the blur diameter reflect the value (as here) or the blur area?
• real "blur" is usually Gaussian, this is not; this can be made, but then the size and alpha scaling become a bit longer
• what do you want to see happen when blurred points overlap each other?
• when doing maths with alpha values and color values, remember the gamma function of the display

So, this is just an ugly fake. Sometimes they look good enough, sometimes not.