This Page

misc example code: svg_filter_line.pyΒΆ

(Source code, png, pdf)

Demonstrate SVG filtering effects which might be used with mpl.

Note that the filtering effects are only effective if your svg renderer
support it.

from __future__ import print_function
import matplotlib


import matplotlib.pyplot as plt
import matplotlib.transforms as mtransforms

fig1 = plt.figure()
ax = fig1.add_axes([0.1, 0.1, 0.8, 0.8])

# draw lines
l1, = ax.plot([0.1, 0.5, 0.9], [0.1, 0.9, 0.5], "bo-",
              mec="b", lw=5, ms=10, label="Line 1")
l2, = ax.plot([0.1, 0.5, 0.9], [0.5, 0.2, 0.7], "rs-",
              mec="r", lw=5, ms=10, color="r", label="Line 2")

for l in [l1, l2]:

    # draw shadows with same lines with slight offset and gray colors.

    xx = l.get_xdata()
    yy = l.get_ydata()
    shadow, = ax.plot(xx, yy)

    # adjust color
    # adjust zorder of the shadow lines so that it is drawn below the
    # original lines
    shadow.set_zorder(l.get_zorder() - 0.5)

    # offset transform
    ot = mtransforms.offset_copy(l.get_transform(), fig1,
                                 x=4.0, y=-6.0, units='points')


    # set the id for a later use
    shadow.set_gid(l.get_label() + "_shadow")

ax.set_xlim(0., 1.)
ax.set_ylim(0., 1.)

# save the figure as a bytes string in the svg format.
from io import BytesIO
f = BytesIO()
plt.savefig(f, format="svg")

import xml.etree.cElementTree as ET

# filter definition for a gaussian blur
filter_def = """
  <defs  xmlns='' xmlns:xlink=''>
    <filter id='dropshadow' height='1.2' width='1.2'>
      <feGaussianBlur result='blur' stdDeviation='3'/>

# read in the saved svg
tree, xmlid = ET.XMLID(f.getvalue())

# insert the filter definition in the svg dom tree.
tree.insert(0, ET.XML(filter_def))

for l in [l1, l2]:
    # pick up the svg element with given id
    shadow = xmlid[l.get_label() + "_shadow"]
    # apply shadow filter
    shadow.set("filter", 'url(#dropshadow)')

fn = "svg_filter_line.svg"
print("Saving '%s'" % fn)

Keywords: python, matplotlib, pylab, example, codex (see Search examples)