It is relatively simple to draw a cross-hair cursor in matplotlib similar to the stock software. Here we take a look at several built-in cursors:
1. The cross-hair cursor on the monograph
from matplotlib.widgets import Cursor
import matplotlib.pyplot as plt
import numpy as np
fig, (ax1, ax2) = plt.subplots(nrows=2, sharex=True)
t = np.arange(0.0, 2.0, 0.01)
ax1.plot(t, np.sin(2*np.pi*t))
ax2.plot(t, np.sin(4*np.pi*t))
cursor = Cursor(ax1, useblit=True, color='r', lw=0.5)
plt.show()See the effect
2. A crosshair cursor appears on multiple subgraphs at the same time
from matplotlib.widgets import Cursor,MultiCursor
import matplotlib.pyplot as plt
import numpy as np
fig, (ax1, ax2) = plt.subplots(nrows=2, sharex=True)
t = np.arange(0.0, 2.0, 0.01)
ax1.plot(t, np.sin(2*np.pi*t))
ax2.plot(t, np.sin(4*np.pi*t))
# cursor = Cursor(ax1, useblit=True, color='r', lw=0.5)
cursor = MultiCursor(fig.canvas, (ax1, ax2), useblit=True,
horizOn=True, vertOn=True, color='r', lw=0.5)
plt.show()result:
3. Single + multiple cross star cursor
This is very common in stock software. For example, in a straight flush, there is only one horizontal line for multiple technical indicators in the same date, and each sub-graph has a vertical line. There is no such implementation in matplotlib, so I wrote it myself After reading the code, let’s take a look at the effect.
# from matplotlib.widgets import Cursor,MultiCursor
import matplotlib.pyplot as plt
import numpy as np
fig, (ax1, ax2) = plt.subplots(nrows=2, sharex=True)
t = np.arange(0.0, 2.0, 0.01)
ax1.plot(t, np.sin(2*np.pi*t))
ax2.plot(t, np.sin(4*np.pi*t))
# cursor = Cursor(ax1, useblit=True, color='r', lw=0.5)
# cursor = MultiCursor(fig.canvas, (ax1, ax2), useblit=True, horizOn=True, vertOn=True, color='r', lw=0.5)
cursor = SingleMultiCursor(fig.canvas, (ax1, ax2), single=0, color='r', lw=0.5)
plt.show()See the effect
If you arrange the sub-pictures in the code left and right, and change the type of single to 1, see the effect
# from matplotlib.widgets import Cursor,MultiCursor
import matplotlib.pyplot as plt
import numpy as np
fig, (ax1, ax2) = plt.subplots(ncols=2, sharey=True)
t = np.arange(0.0, 2.0, 0.01)
ax1.plot(t, np.sin(2*np.pi*t))
ax2.plot(t, np.sin(4*np.pi*t))
# cursor = Cursor(ax1, useblit=True, color='r', lw=0.5)
# cursor = MultiCursor(fig.canvas, (ax1, ax2), useblit=True, horizOn=True, vertOn=True, color='r', lw=0.5)
cursor = SingleMultiCursor(fig.canvas, (ax1, ax2), single=1, color='r', lw=0.5)
plt.show()
Attached is the implementation code of SingleMultiCursor:
class SingleMultiCursor():
"""
一个用于多个子图（横排或者竖排）的十字星光标，可以在多个子图上同时出现
single=0表示仅仅一个子图显示水平线，所有子图显示垂直线，用于竖排的子图
single=1表示仅仅一个子图显示垂直线，所有子图显示水平线，用于横排的子图
注意：为了能让光标响应事件处理，必须保持对它的引用（比如有个变量保存）
用法::
import matplotlib.pyplot as plt
import numpy as np
fig, (ax1, ax2) = plt.subplots(nrows=2, sharex=True)
t = np.arange(0.0, 2.0, 0.01)
ax1.plot(t, np.sin(2*np.pi*t))
ax2.plot(t, np.sin(4*np.pi*t))
cursor = SingleMultiCursor(fig.canvas, (ax1, ax2), single=0, color='w', lw=0.5)
plt.show()
"""
def __init__(self, canvas, axes, single=0, **lineprops):
self.canvas = canvas
self.axes = axes
self.single = single
if single not in [0, 1]:
raise ValueError('Unrecognized single value: ' + str(single) + ', must be 0 or 1')
xmin, xmax = axes[-1].get_xlim()
ymin, ymax = axes[-1].get_ylim()
xmid = 0.5 * (xmin + xmax)
ymid = 0.5 * (ymin + ymax)
self.background = None
self.needclear = False
lineprops['animated'] = True # for blt
self.lines = [
[ax.axhline(ymid, visible=False, **lineprops) for ax in axes],
[ax.axvline(xmid, visible=False, **lineprops) for ax in axes]
]
self.canvas.mpl_connect('motion_notify_event', self.onmove)
self.canvas.mpl_connect('draw_event', self.clear)
def clear(self, event):
self.background = (self.canvas.copy_from_bbox(self.canvas.figure.bbox))
for line in self.lines[0] + self.lines[1]:
line.set_visible(False)
def onmove(self, event):
if event.inaxes is None: return
if not self.canvas.widgetlock.available(self): return
self.needclear = True
for i in range(len(self.axes)):
if event.inaxes == self.axes[i]:
if self.single == 0:
for line in self.lines[1]:
line.set_xdata((event.xdata, event.xdata))
line.set_visible(True)
line = self.lines[0][i]
line.set_ydata((event.ydata, event.ydata))
line.set_visible(True)
else:
for line in self.lines[0]:
line.set_ydata((event.ydata, event.ydata))
line.set_visible(True)
line = self.lines[1][i]
line.set_xdata((event.xdata, event.xdata))
line.set_visible(True)
else:
self.lines[self.single][i].set_visible(False)
if self.background is not None:
self.canvas.restore_region(self.background)
for lines in self.lines:
for line in lines:
if line.get_visible():
line.axes.draw_artist(line)
self.canvas.blit()