『Python』matplotlib坐标轴应用

1. 设置坐标轴的位置和展示形式

import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl

mpl.use('Qt5Agg')
mpl.rcParams['font.sans-serif'] = ['SimHei']
mpl.rcParams['font.serif'] = ['SimHei']
mpl.rcParams['axes.unicode_minus'] = False  # 解决保存图像是负号'-'显示为方块的问题,或者转换负号为字符串

plt.axes([0.05, 0.7, 0.3, 0.3], frameon=True, facecolor="y", aspect="equal")
plt.plot(np.arange(3), [0, 1, 0], color="blue", linewidth=2, linestyle="--")
plt.ylim(0, 1.5)
plt.axis("image")

plt.axes([0.3, 0.4, 0.3, 0.3], frameon=True, facecolor="y", aspect="equal")
plt.plot(2 + np.arange(3), [0, 1, 0], color="blue", linewidth=2, linestyle="-")
plt.ylim(0, 15)
plt.axis([2.1, 3.9, 0.5, 1.9])

plt.axes([0.55, 0.1, 0.3, 0.3], frameon=True, facecolor="y", aspect="equal")
plt.plot(4 + np.arange(3), [0, 1, 0], color="blue", linewidth=2, linestyle=":")
plt.ylim(0, 1.5)
plt.axis("off")

plt.show()

• 函数axes(rect, frameon=True, facecolor="y")

  • rect = [left, bottom, width, height]

    left和bottom分别表示坐标轴的左侧边缘和底部边缘距离画布边缘的距离，width和height分别表示坐标轴的宽度和高度
    
    left和width是画布宽度归一化后的距离，bottom和height是画布高度归一化后的距离。

  • frameon=True
    
    是否显示四条轴脊

  • facecolor="y"
    
    填充坐标轴背景的颜色

• 函数axis()

  • [xmin, xmax, ymin, ymax]
    
    显示坐标轴的范围
  • option，可取值为
    • 'on'：打开坐标轴
    • 'off'：关闭坐标轴显示
    • 'equal'：设置相等的比例，y轴和x轴单位刻度对应长度是一样的
    • 'scaled'：通过更改绘图框的尺寸设置相等的缩放比例
    • 'tight'：设置足够大的限制来显示所有数据
    • 'auto'：自动确定
    • 'image'：‘scaled’ with axis limits equal to data limits
    • 'square'：方形图，类似于 ‘scaled’,但是强制xmax-xmin = ymax-ymin

2. 坐标轴刻度的显示

import matplotlib.pyplot as plt
import matplotlib as mpl

mpl.rcParams['font.sans-serif'] = ['SimHei']
mpl.rcParams['font.serif'] = ['SimHei']
mpl.rcParams['axes.unicode_minus'] = False  # 解决保存图像是负号'-'显示为方块的问题,或者转换负号为字符串

ax1 = plt.subplot(121)
ax1.set_xticks(range(0, 251, 50))
plt.grid(True, axis="x")

ax2 = plt.subplot(122)
ax2.set_xticks([])
plt.grid(True, axis="x")

plt.show()

如果不设置坐标轴刻度，则网格线也不会被设置。设置刻度还包括刻度标签，可以用函数Axes.set_xticklabels()和Axes.set_yticklabels()设置对应刻度线的标签

3. 坐标轴的样式和位置的定制化展示

import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl
from matplotlib.ticker import FormatStrFormatter
from calendar import day_name

mpl.rcParams['font.sans-serif'] = ['SimHei']
mpl.rcParams['font.serif'] = ['SimHei']
mpl.rcParams['axes.unicode_minus'] = False  # 解决保存图像是负号'-'显示为方块的问题,或者转换负号为字符串

fig = plt.figure()

ax = fig.add_axes([0.2, 0.2, 0.7, 0.7])
ax.spines["bottom"].set_position(("outward", 10))
ax.spines["left"].set_position(("outward", 10))
ax.spines["top"].set_color("none")
ax.spines["right"].set_color("none")

x = np.arange(1, 8, 1)
y = 2 * x + 1

ax.scatter(x, y, c="orange", s=50, edgecolors="orange")

for tickline in ax.xaxis.get_ticklines():
    tickline.set_color("blue")
    tickline.set_markersize(8)
    tickline.set_markeredgewidth(5)

for ticklabel in ax.get_xmajorticklabels():
    ticklabel.set_color("slateblue")
    ticklabel.set_fontsize(12)
    ticklabel.set_rotation(20)

ax.yaxis.set_major_formatter(FormatStrFormatter(f"$\yen%1.1f$"))
plt.xticks(x, day_name[0:7], rotation=20)
ax.yaxis.set_ticks_position("left")
ax.xaxis.set_ticks_position("bottom")

for tickline in ax.yaxis.get_ticklines():
    tickline.set_color("lightgreen")
    tickline.set_markersize(8)
    tickline.set_markeredgewidth(5)

for ticklabel in ax.get_ymajorticklabels():
    ticklabel.set_color("green")
    ticklabel.set_fontsize(15)

ax.grid(ls=":", lw=1, color="gray", alpha=0.5)

plt.show()

4. 移动坐标轴的位置

import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl

mpl.rcParams['font.sans-serif'] = ['SimHei']
mpl.rcParams['font.serif'] = ['SimHei']
mpl.rcParams['axes.unicode_minus'] = False  # 解决保存图像是负号'-'显示为方块的问题,或者转换负号为字符串

x = np.linspace(-2 * np.pi, 2 * np.pi, 200)
y = np.sin(x)
y1 = np.cos(x)

ax = plt.subplot(111)

ax.plot(x, y, ls="-", lw=2, label=r"$\sin(x)$")
ax.plot(x, y1, ls="-", lw=2, label=r"$\cos(x)$")

ax.legend(loc="lower left")

plt.title(r"$\sin(x)$" + "和" + r"$\cos(x)$" + "函数")

ax.set_xlim(-2 * np.pi, 2 * np.pi)

plt.xticks([-2 * np.pi, -3 * np.pi / 2, -1 * np.pi, -1 * np.pi / 2,
            0, np.pi / 2, np.pi, 3 * np.pi / 2, 2 * np.pi],
           [r"$-2\pi$", r"$-3\pi/2$", r"$-\pi$", r"$-\pi/2$",
            r"$0$", r"$\pi/2$", r"$\pi$", r"$3\pi/3$", r"$2\pi$"]
           )

ax.spines["right"].set_color("none")
ax.spines["top"].set_color("none")

ax.spines["bottom"].set_position(("data", 0))
ax.spines["left"].set_position(("data", 0))

ax.xaxis.set_ticks_position("bottom")
ax.yaxis.set_ticks_position("left")

plt.show()

ax.spines[key]会调用轴脊字典，如bottom、top、right、left键值是对应位置轴脊，ax.spines["bottom"].set_position(("data", 0))表示将底轴移到数轴0坐标位置