带箭头刻度的 Matplotlib 曲线 [英] Matplotlib curve with arrow ticks
本文介绍了带箭头刻度的 Matplotlib 曲线的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
我想知道是否可以在带有箭头标记的 matplotlib
中绘制一条曲线.
I was wondering if it is possible to plot a curve in matplotlib
with arrow ticks.
类似的东西:
from pylab import *
y = linspace(0,10,0.01)
x = cos(y)
plot(x, y, '->')
当 x 增加时,应该得到这样的曲线 --->---->---->
并且像这样 ---<----<----<
当它减少时(当然对于 y 也是如此).此外,箭头应沿曲线方向倾斜(例如,y=x 函数为 45 度)
which should come out with a curve made like this --->---->---->
when x increases and like this ---<----<----<
whenit decreases (and for y as well, of course).
Furthermore, the arrows should be inclined in the curve's direction (for example, 45 degrees for the y=x function)
推荐答案
可以使用与 matplotlib streamplot
函数中相同的策略.基于hitzg已经给出的示例:
It is possible to use the same strategy as in matplotlib streamplot
function. Based on the example already given by hitzg:
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.lines as mlines
import matplotlib.patches as mpatches
def add_arrow_to_line2D(
axes, line, arrow_locs=[0.2, 0.4, 0.6, 0.8],
arrowstyle='-|>', arrowsize=1, transform=None):
"""
Add arrows to a matplotlib.lines.Line2D at selected locations.
Parameters:
-----------
axes:
line: Line2D object as returned by plot command
arrow_locs: list of locations where to insert arrows, % of total length
arrowstyle: style of the arrow
arrowsize: size of the arrow
transform: a matplotlib transform instance, default to data coordinates
Returns:
--------
arrows: list of arrows
"""
if not isinstance(line, mlines.Line2D):
raise ValueError("expected a matplotlib.lines.Line2D object")
x, y = line.get_xdata(), line.get_ydata()
arrow_kw = {
"arrowstyle": arrowstyle,
"mutation_scale": 10 * arrowsize,
}
color = line.get_color()
use_multicolor_lines = isinstance(color, np.ndarray)
if use_multicolor_lines:
raise NotImplementedError("multicolor lines not supported")
else:
arrow_kw['color'] = color
linewidth = line.get_linewidth()
if isinstance(linewidth, np.ndarray):
raise NotImplementedError("multiwidth lines not supported")
else:
arrow_kw['linewidth'] = linewidth
if transform is None:
transform = axes.transData
arrows = []
for loc in arrow_locs:
s = np.cumsum(np.sqrt(np.diff(x) ** 2 + np.diff(y) ** 2))
n = np.searchsorted(s, s[-1] * loc)
arrow_tail = (x[n], y[n])
arrow_head = (np.mean(x[n:n + 2]), np.mean(y[n:n + 2]))
p = mpatches.FancyArrowPatch(
arrow_tail, arrow_head, transform=transform,
**arrow_kw)
axes.add_patch(p)
arrows.append(p)
return arrows
y = np.linspace(0, 100, 200)
x = np.cos(y/5.)
fig, ax = plt.subplots(1, 1)
# print the line and the markers in seperate steps
line, = ax.plot(x, y, 'k-')
add_arrow_to_line2D(ax, line, arrow_locs=np.linspace(0., 1., 200),
arrowstyle='->')
plt.show()
也请参考此答案.
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