Matplotlib#
Matplotlib是Python的二维绘图库，用于生成符合出版质量或跨平台交互环境的各类图形。
准备数据#
一维数据#
import numpy as np
x = np.linspace(0, 10, 100)
y = np.cos(x)
z = np.sin(x)
二维数据或图片#
data = 2 * np.random.random((10, 10))
data2 = 3 * np.random.random((10, 10))
Y, X = np.mgrid[-3:3:100j, -3:3:100j]
U = -1 - X**2 + Y
V = 1 + X - Y**2
绘制图形#
导入库#
import matplotlib.pyplot as plt
%matplotlib inline
Matplotlib is building the font cache; this may take a moment.
---------------------------------------------------------------------------
KeyboardInterrupt Traceback (most recent call last)
Cell In[10], line 1
----> 1 import matplotlib.pyplot as plt
2 get_ipython().run_line_magic('matplotlib', 'inline')
File ~/checkouts/readthedocs.org/user_builds/getstarted/envs/latest/lib/python3.12/site-packages/matplotlib/pyplot.py:57
55 from cycler import cycler # noqa: F401
56 import matplotlib
---> 57 import matplotlib.image
58 from matplotlib import _api
59 # Re-exported (import x as x) for typing.
File ~/checkouts/readthedocs.org/user_builds/getstarted/envs/latest/lib/python3.12/site-packages/matplotlib/image.py:25
23 import matplotlib.artist as martist
24 import matplotlib.colorizer as mcolorizer
---> 25 from matplotlib.backend_bases import FigureCanvasBase
26 import matplotlib.colors as mcolors
27 from matplotlib.transforms import (
28 Affine2D, BboxBase, Bbox, BboxTransform, BboxTransformTo,
29 IdentityTransform, TransformedBbox)
File ~/checkouts/readthedocs.org/user_builds/getstarted/envs/latest/lib/python3.12/site-packages/matplotlib/backend_bases.py:49
46 import numpy as np
48 import matplotlib as mpl
---> 49 from matplotlib import (
50 _api, backend_tools as tools, cbook, colors, _docstring, text,
51 _tight_bbox, transforms, widgets, is_interactive, rcParams)
52 from matplotlib._pylab_helpers import Gcf
53 from matplotlib.backend_managers import ToolManager
File ~/checkouts/readthedocs.org/user_builds/getstarted/envs/latest/lib/python3.12/site-packages/matplotlib/text.py:16
14 from . import _api, artist, cbook, _docstring
15 from .artist import Artist
---> 16 from .font_manager import FontProperties
17 from .patches import FancyArrowPatch, FancyBboxPatch, Rectangle
18 from .textpath import TextPath, TextToPath # noqa # Logically located here
File ~/checkouts/readthedocs.org/user_builds/getstarted/envs/latest/lib/python3.12/site-packages/matplotlib/font_manager.py:1643
1639 _log.info("generated new fontManager")
1640 return fm
-> 1643 fontManager = _load_fontmanager()
1644 findfont = fontManager.findfont
1645 get_font_names = fontManager.get_font_names
File ~/checkouts/readthedocs.org/user_builds/getstarted/envs/latest/lib/python3.12/site-packages/matplotlib/font_manager.py:1637, in _load_fontmanager(try_read_cache)
1635 _log.debug("Using fontManager instance from %s", fm_path)
1636 return fm
-> 1637 fm = FontManager()
1638 json_dump(fm, fm_path)
1639 _log.info("generated new fontManager")
File ~/checkouts/readthedocs.org/user_builds/getstarted/envs/latest/lib/python3.12/site-packages/matplotlib/font_manager.py:1103, in FontManager.__init__(self, size, weight)
1100 for path in [*findSystemFonts(paths, fontext=fontext),
1101 *findSystemFonts(fontext=fontext)]:
1102 try:
-> 1103 self.addfont(path)
1104 except OSError as exc:
1105 _log.info("Failed to open font file %s: %s", path, exc)
File ~/checkouts/readthedocs.org/user_builds/getstarted/envs/latest/lib/python3.12/site-packages/matplotlib/font_manager.py:1136, in FontManager.addfont(self, path)
1134 self.afmlist.append(prop)
1135 else:
-> 1136 font = ft2font.FT2Font(path)
1137 prop = ttfFontProperty(font)
1138 self.ttflist.append(prop)
KeyboardInterrupt:
画布#
fig = plt.figure()
<Figure size 640x480 with 0 Axes>
fig2 = plt.figure(figsize=plt.figaspect(2.0))
<Figure size 400x800 with 0 Axes>
坐标轴#
图形是以坐标轴为核心绘制的，大多数情况下，子图就可以满足需求。子图是栅格系统的坐标轴。
ax1 = fig.add_subplot(221) # row-col-num
ax3 = fig.add_subplot(212)
fig3, axes = plt.subplots(nrows=2, ncols=2)
fig4, axes2 = plt.subplots(ncols=3)
fig.add_axes(ax1)
<Axes: >
绘图例程#
一维数据#
fig, ax = plt.subplots()
lines = ax.plot(x, y) # 用线或标记连接点
ax.scatter(x, y) # 缩放或着色未连接的点
<matplotlib.collections.PathCollection at 0x1f5851f3b80>
axes[0, 0].bar([1, 2, 3], [3, 4, 5]) # 绘制柱状图
<BarContainer object of 3 artists>
axes[1, 0].barh([0.5, 1, 2.5], [0, 1, 2]) # 绘制水平柱状图
<BarContainer object of 3 artists>
axes[1, 1].axhline(0.45) # 绘制与轴平行的横线
<matplotlib.lines.Line2D at 0x1f58555a040>
axes[0, 1].axvline(0.65) # 绘制与轴垂直的竖线
<matplotlib.lines.Line2D at 0x1f585dbd640>
ax.fill(x, y, color="blue") # 绘制填充多边形
[<matplotlib.patches.Polygon at 0x1f585dbdca0>]
ax.fill_between(x, y, color="yellow") # 填充 y 值和 0 之间
<matplotlib.collections.PolyCollection at 0x1f585dc61c0>
向量场#
axes[0, 1].arrow(0, 0, 0.5, 0.5) # 为坐标轴添加箭头
<matplotlib.patches.FancyArrow at 0x1f585dc6520>
axes[1, 1].quiver(y, z) # 二维箭头
<matplotlib.quiver.Quiver at 0x1f585dc6760>
axes[0, 1].streamplot(X, Y, U, V) # 二维箭头
<matplotlib.streamplot.StreamplotSet at 0x1f58555a220>
数据分布#
ax1.hist(y) # 直方图
(array([26., 8., 7., 6., 6., 6., 6., 7., 8., 20.]),
array([-9.99947166e-01, -7.99952450e-01, -5.99957733e-01, -3.99963016e-01,
-1.99968300e-01, 2.64169119e-05, 2.00021134e-01, 4.00015850e-01,
6.00010567e-01, 8.00005283e-01, 1.00000000e+00]),
<BarContainer object of 10 artists>)
ax3.boxplot(y) # 箱形图
{'whiskers': [<matplotlib.lines.Line2D at 0x1f5855b16d0>,
<matplotlib.lines.Line2D at 0x1f5855c14c0>],
'caps': [<matplotlib.lines.Line2D at 0x1f5855c1d90>,
<matplotlib.lines.Line2D at 0x1f585627580>],
'boxes': [<matplotlib.lines.Line2D at 0x1f5855b1520>],
'medians': [<matplotlib.lines.Line2D at 0x1f585627e80>],
'fliers': [<matplotlib.lines.Line2D at 0x1f58564d310>],
'means': []}
ax3.violinplot(z) # 小提琴图
{'bodies': [<matplotlib.collections.PolyCollection at 0x1f58564c550>],
'cmaxes': <matplotlib.collections.LineCollection at 0x1f58564ddc0>,
'cmins': <matplotlib.collections.LineCollection at 0x1f585886670>,
'cbars': <matplotlib.collections.LineCollection at 0x1f585894700>}
二维数据或图片#
fig, ax = plt.subplots()
axes2[0].pcolor(data2) # 二维数组伪彩色图
<matplotlib.collections.PolyCollection at 0x1f58587a4c0>
axes2[0].pcolormesh(data) # 二维数组等高线伪彩色图
<matplotlib.collections.QuadMesh at 0x1f583c46af0>
CS = plt.contour(Y, X, U) # 等高线图
axes2[2] = ax.clabel(CS) # 等高线图标签
图形解析与工作流#
图形解析#
工作流#
Matplotlib 绘图的基本步骤：
Step 1 准备数据
Step 2 创建图形
Step 3 绘图
Step 4 自定义设置
Step 5 保存图形
Step 6 显示图形
import matplotlib.pyplot as plt
x = [1, 2, 3, 4] # Step 1
y = [10, 20, 25, 30]
fig = plt.figure() # Step 2
<Figure size 640x480 with 0 Axes>
ax = fig.add_subplot(111) # Step 3
ax.plot(x, y, color="lightblue", linewidth=3) # Step 3, 4
[<matplotlib.lines.Line2D at 0x1f584d73190>]
ax.scatter([2, 4, 6], [5, 15, 25], color="darkgreen", marker="^")
<matplotlib.collections.PathCollection at 0x1f584d73370>
ax.set_xlim(1, 6.5)
(1.0, 6.5)
plt.savefig("../_tmp/plt_savefig.png") # Step 5
<Figure size 640x480 with 0 Axes>
plt.show() # Step 6
自定义图形#
颜色、色条与色彩表#
plt.plot(x, x, x, [i**2 for i in x], x, [i**3 for i in x])
[<matplotlib.lines.Line2D at 0x1f584df7700>,
<matplotlib.lines.Line2D at 0x1f584df7760>,
<matplotlib.lines.Line2D at 0x1f584df7790>]
ax.plot(x, y, alpha=0.4)
[<matplotlib.lines.Line2D at 0x1f584e2cf70>]
ax.plot(x, y, c="k")
[<matplotlib.lines.Line2D at 0x1f584d80a90>]
标记#
fig, ax = plt.subplots()
ax.scatter(x, y, marker=".")
<matplotlib.collections.PathCollection at 0x1f584d80df0>
ax.plot(x, y, marker="o")
[<matplotlib.lines.Line2D at 0x1f584eaed00>]
线型#
plt.plot(x, y, linewidth=4.0)
[<matplotlib.lines.Line2D at 0x1f5861a7310>]
plt.plot(x, y, ls="solid")
[<matplotlib.lines.Line2D at 0x1f586230490>]
plt.plot(x, y, ls="--")
[<matplotlib.lines.Line2D at 0x1f5862b9160>]
plt.plot(x, y, "--", [i**2 for i in x], [i**2 for i in y], "-.")
[<matplotlib.lines.Line2D at 0x1f586338f40>,
<matplotlib.lines.Line2D at 0x1f5863460a0>]
plt.setp(lines, color="r", linewidth=4.0)
[None, None]
文本与标注#
ax.text(1, -2.1, "Example Graph", style="italic")
Text(1, -2.1, 'Example Graph')
ax.annotate(
"Sine",
xy=(8, 0),
xycoords="data",
xytext=(10.5, 0),
textcoords="data",
arrowprops=dict(arrowstyle="->", connectionstyle="arc3"),
)
Text(10.5, 0, 'Sine')
数学符号#
plt.title(r"$sigma_i=15$", fontsize=20)
Text(0.5, 1.0, '$sigma_i=15$')
尺寸限制、图例和布局#
尺寸限制与自动调整
ax.margins(x=0.0, y=0.1) # 添加内边距
ax.axis("equal") # 将图形纵横比设置为 1
(1.0, 4.0, 8.0, 32.0)
ax.set(xlim=[0, 10.5], ylim=[-1.5, 1.5]) # 设置 x 轴与 y 轴的限制
[(0.0, 10.5), (-1.5, 1.5)]
ax.set_xlim(0, 10.5) # 设置 x 轴的限制
(0.0, 10.5)
图例
ax.set(title="An Example Axes", ylabel="Y-Axis", xlabel="X-Axis") # 设置标题与 x、y 轴的标签
[Text(0.5, 1.0, 'An Example Axes'),
Text(4.444444444444445, 0.5, 'Y-Axis'),
Text(0.5, 4.444444444444445, 'X-Axis')]
ax.legend(loc="best") # 自动选择最佳的图例位置
No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.
<matplotlib.legend.Legend at 0x1f5875bf610>
标记
ax.xaxis.set(ticks=range(1, 5), ticklabels=[3, 100, -12, "foo"]) # 手动设置 X 轴刻度
[[<matplotlib.axis.XTick at 0x1f584e5b520>,
<matplotlib.axis.XTick at 0x1f584e5b4f0>,
<matplotlib.axis.XTick at 0x1f584e2ceb0>,
<matplotlib.axis.XTick at 0x1f584e8a8b0>],
[Text(1, 0, '3'), Text(2, 0, '100'), Text(3, 0, '-12'), Text(4, 0, 'foo')]]
ax.tick_params(axis="y", direction="inout", length=10) # 设置 Y 轴长度与方向
子图间距
fig3.subplots_adjust(
wspace=0.5, hspace=0.3, left=0.125, right=0.9, top=0.9, bottom=0.1
) # 调整子图间距
fig.tight_layout() # 设置画布的子图布局
坐标轴边线
ax1.spines["top"].set_visible(False) # 隐藏顶部坐标轴线
ax1.spines["bottom"].set_position(("outward", 10)) # 设置底部边线的位置为 outward
保存#
savefig函数
plt.savefig("../_tmp/plt_savefig.png") # 保存画布
<Figure size 640x480 with 0 Axes>
plt.savefig("../_tmp/plt_savefig_transparent.png", transparent=True) # 保存透明画布
<Figure size 640x480 with 0 Axes>
显示图形#
show函数
plt.show()
关闭与清除#
绘图清除与关闭
plt.cla() # 清除坐标轴
plt.clf() # 清除画布
<Figure size 640x480 with 0 Axes>
plt.close() # 关闭窗口