SVG直方图
演示如何创建交互式直方图,通过单击图例标记隐藏或显示条形图。
交互性以ecmascript(javascript)编码,并在后处理步骤中插入SVG代码中。 要渲染图像,请在Web浏览器中打开它。 大多数Linux Web浏览器和OSX用户都支持SVG。 Windows IE9支持SVG,但早期版本不支持。
注意
matplotlib后端允许我们为每个对象分配id。 这是用于描述在python中创建的matplotlib对象的机制以及在第二步中解析的相应SVG构造。 虽然灵活,但它们很难用于大量物体的收集。 可以使用两种机制来简化事情:
- 系统地将对象分组为SVG <g>标签,
- 根据每个SVG对象的来源为每个SVG对象分配类。
例如,不是修改每个单独栏的属性,而是可以将列分组到PatchCollection中,或者将列分配给class =“hist _ ##”属性。
CSS也可以广泛用于替换整个SVG生成中的重复标记。
作者:david.huard@gmail.com
import numpy as np
import matplotlib.pyplot as plt
import xml.etree.ElementTree as ET
from io import BytesIO
import json
plt.rcParams['svg.fonttype'] = 'none'
# Apparently, this `register_namespace` method works only with
# python 2.7 and up and is necessary to avoid garbling the XML name
# space with ns0.
ET.register_namespace("", "http://www.w3.org/2000/svg")
# Fixing random state for reproducibility
np.random.seed(19680801)
# --- Create histogram, legend and title ---
plt.figure()
r = np.random.randn(100)
r1 = r + 1
labels = ['Rabbits', 'Frogs']
H = plt.hist([r, r1], label=labels)
containers = H[-1]
leg = plt.legend(frameon=False)
plt.title("From a web browser, click on the legend\n"
"marker to toggle the corresponding histogram.")
# --- Add ids to the svg objects we'll modify
hist_patches = {}
for ic, c in enumerate(containers):
hist_patches['hist_%d' % ic] = []
for il, element in enumerate(c):
element.set_gid('hist_%d_patch_%d' % (ic, il))
hist_patches['hist_%d' % ic].append('hist_%d_patch_%d' % (ic, il))
# Set ids for the legend patches
for i, t in enumerate(leg.get_patches()):
t.set_gid('leg_patch_%d' % i)
# Set ids for the text patches
for i, t in enumerate(leg.get_texts()):
t.set_gid('leg_text_%d' % i)
# Save SVG in a fake file object.
f = BytesIO()
plt.savefig(f, format="svg")
# Create XML tree from the SVG file.
tree, xmlid = ET.XMLID(f.getvalue())
# --- Add interactivity ---
# Add attributes to the patch objects.
for i, t in enumerate(leg.get_patches()):
el = xmlid['leg_patch_%d' % i]
el.set('cursor', 'pointer')
el.set('onclick', "toggle_hist(this)")
# Add attributes to the text objects.
for i, t in enumerate(leg.get_texts()):
el = xmlid['leg_text_%d' % i]
el.set('cursor', 'pointer')
el.set('onclick', "toggle_hist(this)")
# Create script defining the function `toggle_hist`.
# We create a global variable `container` that stores the patches id
# belonging to each histogram. Then a function "toggle_element" sets the
# visibility attribute of all patches of each histogram and the opacity
# of the marker itself.
script = """
<script type="text/ecmascript">
<![CDATA[
var container = %s
function toggle(oid, attribute, values) {
/* Toggle the style attribute of an object between two values.
Parameters
----------
oid : str
Object identifier.
attribute : str
Name of style attribute.
values : [on state, off state]
The two values that are switched between.
*/
var obj = document.getElementById(oid);
var a = obj.style[attribute];
a = (a == values[0] || a == "") ? values[1] : values[0];
obj.style[attribute] = a;
}
function toggle_hist(obj) {
var num = obj.id.slice(-1);
toggle('leg_patch_' + num, 'opacity', [1, 0.3]);
toggle('leg_text_' + num, 'opacity', [1, 0.5]);
var names = container['hist_'+num]
for (var i=0; i < names.length; i++) {
toggle(names[i], 'opacity', [1,0])
};
}
]]>
</script>
""" % json.dumps(hist_patches)
# Add a transition effect
css = tree.getchildren()[0][0]
css.text = css.text + "g {-webkit-transition:opacity 0.4s ease-out;" + \
"-moz-transition:opacity 0.4s ease-out;}"
# Insert the script and save to file.
tree.insert(0, ET.XML(script))
ET.ElementTree(tree).write("svg_histogram.svg")