在绘制的行上打印字符串（模拟等高线绘制标签）

Question

等高线图演示显示了如何使用绘制在曲线上的标高值绘制曲线，请参见下文。

有没有一种方法可以对一个简单的线图做同样的事情，就像下面的代码得到的一样？

import matplotlib.pyplot as plt 

x = [1.81,1.715,1.78,1.613,1.629,1.714,1.62,1.738,1.495,1.669,1.57,1.877,1.385]
y = [0.924,0.915,0.914,0.91,0.909,0.905,0.905,0.893,0.886,0.881,0.873,0.873,0.844]

# This is the string that should show somewhere over the plotted line.
line_string = 'name of line'

# plotting
plt.plot(x,y)
plt.show()

Answer 1

基于Jakob的代码，这里有一个函数，可以在数据空间中旋转文本，将标签放在给定的x或y数据坐标附近，还可以处理日志图。

def label_line(line, label_text, near_i=None, near_x=None, near_y=None, rotation_offset=0, offset=(0,0)):
    """call 
        l, = plt.loglog(x, y)
        label_line(l, "text", near_x=0.32)
    """
    def put_label(i):
        """put label at given index"""
        i = min(i, len(x)-2)
        dx = sx[i+1] - sx[i]
        dy = sy[i+1] - sy[i]
        rotation = np.rad2deg(math.atan2(dy, dx)) + rotation_offset
        pos = [(x[i] + x[i+1])/2. + offset[0], (y[i] + y[i+1])/2 + offset[1]]
        plt.text(pos[0], pos[1], label_text, size=9, rotation=rotation, color = line.get_color(),
        ha="center", va="center", bbox = dict(ec='1',fc='1'))

    x = line.get_xdata()
    y = line.get_ydata()
    ax = line.get_axes()
    if ax.get_xscale() == 'log':
        sx = np.log10(x)    # screen space
    else:
        sx = x
    if ax.get_yscale() == 'log':
        sy = np.log10(y)
    else:
        sy = y

    # find index
    if near_i is not None:
        i = near_i
        if i < 0: # sanitize negative i
            i = len(x) + i
        put_label(i)
    elif near_x is not None:
        for i in range(len(x)-2):
            if (x[i] < near_x and x[i+1] >= near_x) or (x[i+1] < near_x and x[i] >= near_x):
                put_label(i)
    elif near_y is not None:
        for i in range(len(y)-2):
            if (y[i] < near_y and y[i+1] >= near_y) or (y[i+1] < near_y and y[i] >= near_y):
                put_label(i)
    else:
        raise ValueError("Need one of near_i, near_x, near_y")

Answer 2

您可以简单地添加一些文本（MPL库），如

import matplotlib.pyplot as plt 
import numpy as np
x = [1.81,1.715,1.78,1.613,1.629,1.714,1.62,1.738,1.495,1.669,1.57,1.877,1.385]
y = [0.924,0.915,0.914,0.91,0.909,0.905,0.905,0.893,0.886,0.881,0.873,0.873,0.844]

# This is the string that should show somewhere over the plotted line.
line_string = 'name of line'

# plotting
fig, ax = plt.subplots(1,1)
l, = ax.plot(x,y)
pos = [(x[-2]+x[-1])/2., (y[-2]+y[-1])/2.]
# transform data points to screen space
xscreen = ax.transData.transform(zip(x[-2::],y[-2::]))
rot = np.rad2deg(np.arctan2(*np.abs(np.gradient(xscreen)[0][0][::-1])))
ltex = plt.text(pos[0], pos[1], line_string, size=9, rotation=rot, color = l.get_color(),
     ha="center", va="center",bbox = dict(ec='1',fc='1'))

def updaterot(event):
    """Event to update the rotation of the labels"""
    xs = ax.transData.transform(zip(x[-2::],y[-2::]))
    rot = np.rad2deg(np.arctan2(*np.abs(np.gradient(xs)[0][0][::-1])))
    ltex.set_rotation(rot)

fig.canvas.mpl_connect('button_release_event', updaterot)
plt.show()

注意，旋转是以度数和屏幕而不是数据空间为单位的。

由于我最近需要自动标签旋转，它更新缩放和平移，因此我更新了我的答案，以满足这些需求。现在标签旋转会在每次鼠标按钮释放时更新（缩放时不会触发单独的draw_event）。这种方法使用matplotlib转换来链接本教程中讨论的数据和屏幕空间。