如果绘制了多个图形，如何获得该线的 label？

Question

plt.plot(x, y, label = name1)
plt.plot(x, y, label = name2)
plt.plot(x, y, label = name3)
plt.show()

How to get the label when I click the line or better if I can get this information directly in the graph window like I get the x and y axis values on bottom right.

Answer 1

The fastest way would be to add a legend to your graph with plt.legend() right before plt.show()

For more interactivity, maybe try bokeh instead of matplotlib.

Answer 2

Not sure exactly what you are asking for but if you want to represent each line with a name, or the series of the x-values, you could use legend() and input a string or series name as label name in the plot-line:

plt.plot(x1, y, label = "name1")   # Show the string name1
plt.plot(x2, y, label = x2)        # Shows the array x2
plt.legend()                       # Displays the legends

If you want to add title or labels for the axis you could use:

plt.xlabel('X-axis Label')
plt.ylabel('Y-axis label')
plt.title('Title')

Answer 3

I am not sure if this is what you are looking for? But you can easily name your graphs by using the Legend. the first graph will be the first in your Legendlist. The important code is between the slash:-)

import matplotlib.pyplot as plt
import numpy as np


# Select length of axes and the space between tick labels
xmin, xmax, ymin, ymax = -10, 10, -10, 10
ticks_frequency = 1

# Plot points
fig, ax = plt.subplots(figsize=(10, 10))

#//////////////////////////////////////////////////////////////////////////////

# x range
x = np.arange(-5, 5., 0.025)

# f1
y1 = 3*x+4
f1 = ax.plot(x, y1, lw = 3, alpha = 0.5, color="blue")

# f2
y2 = 1*x+1
f2 = ax.plot(x, y2, lw = 3, alpha = 0.5, color="orange")

# f3
y3 = -2*x+8
f3 = ax.plot(x, y3, lw = 3, alpha = 0.5, color="red")

# legend
ax.legend(["Gerade 1", "Gerade 2", "Gerade 3"])

#//////////////////////////////////////////////////////////////////////////////

# Set identical scales for both axes
ax.set(xlim=(xmin-1, xmax+1), ylim=(ymin-1, ymax+1), aspect='equal')

# Set bottom and left spines as x and y axes of coordinate system
ax.spines['bottom'].set_position('zero')
ax.spines['left'].set_position('zero')

# Remove top and right spines
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)

# Create 'x' and 'y' labels placed at the end of the axes
ax.set_xlabel('x', size=14, labelpad=-24, x=1.03)
ax.set_ylabel('y', size=14, labelpad=-21, y=1.02, rotation=0)

# Create custom major ticks to determine position of tick labels
x_ticks = np.arange(xmin, xmax+1, ticks_frequency)
y_ticks = np.arange(ymin, ymax+1, ticks_frequency)
ax.set_xticks(x_ticks[x_ticks != 0])
ax.set_yticks(y_ticks[y_ticks != 0])

# Create minor ticks placed at each integer to enable drawing of minor grid
# lines: note that this has no effect in this example with ticks_frequency=1
ax.set_xticks(np.arange(xmin, xmax+1), minor=True)
ax.set_yticks(np.arange(ymin, ymax+1), minor=True)

# Draw major and minor grid lines
ax.grid(which='both', color='grey', linewidth=1, linestyle='-', alpha=0.2)

# Draw arrows
arrow_fmt = dict(markersize=4, color='black', clip_on=False)
ax.plot((1), (0), marker='>', transform=ax.get_yaxis_transform(), **arrow_fmt)
ax.plot((0), (1), marker='^', transform=ax.get_xaxis_transform(), **arrow_fmt)

plt.show()