移动轴后留下白色边框

Question

我正在尝试使 matplotlib 图形看起来更像图形计算器中使用的图形。 将轴移动到 plot 的中心时，它们原来所在的位置是空的，看起来像是有白色边框。

普通图

修改后的图表

我不知道这是否与轴或已删除的标签有关。

我知道保存图像时使用的参数，例如

plt.savefig("image.png",bbox_inches='tight')

但无论该方法是否适用于这种情况或其他类型的边界，我的意图是在 tkinter window 中显示图像，而不是将其保存到用户计算机。

有没有办法消除这些遗漏的“边界”？

这是代码

from tkinter import * 
from matplotlib.figure import Figure
from matplotlib.backends.backend_tkagg import (FigureCanvasTkAgg, NavigationToolbar2Tk)
import random
import numpy as np

root = Tk()
root.geometry("500x500")

# CREATE X VALUES
x_list = np.arange(-20, 20, .01)

# GENERATE 'RANDOM' VALUES FOR THE QUADRATIC EQUATION'S PARAMETERS
a = random.choice([-1,-0.6,0.6,1])
b = random.uniform(-5,5)
c = random.randint(-5,5)

# CREATE FIGURE
fig = Figure(figsize = (5, 5), dpi = 100)

# PLOT 
ax = fig.add_subplot(111)
ax.plot(x_list, a * np.power(x_list,2) + b * x_list + c)
ax.axis([-20,20,-20,20])

# CENTER TWO AXES
ax.spines['left'].set_position('center')
ax.spines['bottom'].set_position('zero')

# HIDE THE OTHER TWO AXES
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')

# SET TICKS POSITION
ax.xaxis.set_ticks_position('bottom')
ax.yaxis.set_ticks_position('left')

# HIDE NUMBER LABELS
ax.set_xticklabels([])
ax.set_yticklabels([])

# -------------------------- COLORS
# I want to remove the green part of the figure
# (UNCOMMENT TO SEE THE COLORS IN THE FIGURE)
#fig.set_facecolor('#68C45F')
#ax.set_facecolor('#E56361')

# CREATE CANVAS
canvas = FigureCanvasTkAgg(fig, master = root)  
canvas.draw()
canvas.get_tk_widget().pack()

root.mainloop()

Answer 1

hereimport numpy as np
import matplotlib.pyplot as plt

# Select length of axes and the space between tick labels
xmin, xmax, ymin, ymax = -5, 5, -5, 5
ticks_frequency = 1

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

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

x = np.arange(-5, 5, 0.01)

y = x**2 - 1
plt.plot(x, y, color = "red", alpha = 0.8, lw = 1)

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

# 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()

在这里，您有一个漂亮的图表，希望对您有所帮助