其他
Matplotlib 1.4W+字教程（收藏吃灰去吧~~）
"pythonic生物人"的第之前分享
❝❞
本文结合上一篇Matplotlib官方Cheat sheet与之前自己对Matplotlib的学习，「系统梳理了Matplotlib教程」。 每节内容配上了Matplotlib官网快速使用代码及部分章节个人详细实战代码。
「博文速览」
❝本文篇幅长「1.4W+字」，如果时间紧张，建议只看标有「star」的部分。
❞
更多教程：「pythonic生物人」
star一、Matplotlib使用Tips
Matplotlib获取帮助途径
绘图十规则
常见绘图设置问题
二、图形快速绘制
star1、line plot【折线图】
star2、scatter plot【散点图】
star3、bar plot【条形图】
star4、imshow plot【格子图】
5、contour plot【等高线图】
6、quiver plot【箭头】
star7、pie plot【饼图】
star8、text plot【添加文本】
9、fill_between plot【曲线填充图】
10、step plot【阶梯图】
star11、box plot【箱图】
12、errorbar plot【误差棒】
star13、hist plot【直方图】
star14、violin plot【小提琴图】
15、barbs plot【风羽图】
16、even plot【栅格图】
17、hexbin plot【二元直方图】
18、xcorr plot【相关图】
star三、多子图绘制
subplot
add_gridspec
add_axes
make_axes_locatable
star四、文本text设置
文本位置
文本属性：字体|字号|磅值
star五、注释设置
注释箭头形状设置
注释箭头弯曲度设置
star五、坐标轴刻度Tick设置
刻度间距设置
刻度标签格式化输出
star六、图例(legend)设置
starstar七、Colors和Colormaps
star八、line和marker设置
star九、子图与figure之间位置
star一、Matplotlib使用Tips
Matplotlib获取帮助途径
当使用Matplotlib遇到问题时，可通过以下6条路径获取：
❝「Matplotlib官网」：https://matplotlib.org/
❞
「github」：https://github.com/matplotlib/matplotlib/issues
「discourse」：https://discourse.matplotlib.org
「stackoverflow」：https://stackoverflow.com/questions/tagged/matplotlib
「twitter」：https://twitter.com/matplotlib
「matplotlib-users」：https://mail.python.org/mailman/listinfo/matplotlib-users
绘图十规则
参考：Rougier N P, Droettboom M, Bourne P E, et al. Ten Simple Rules for Better Figures[J]. PLOS Computational Biology【IF 4.7】, 2014, 10(9).感兴趣戳：https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4161295/pdf/pcbi.1003833.pdf
❝1. Know Your Audience
2. Identify Your Message
3. Adapt the Figure
4. Captions Are Not Optional
5. Do Not Trust the Defaults
6. Use Color Effectively
7. Do Not Mislead the Reader
8. Avoid “Chartjunk”
9. Message Trumps Beauty
10. Get the Right Too
❞
常见绘图设置问题
❝… resize a figure?
→ fig.set_size_inches(w,h)
… save a figure?
→ fig.savefig(”figure.pdf”)
… save a transparent figure?
→ fig.savefig(”figure.pdf”, transparent=True)
… clear a figure?
→ ax.clear()
… close all figures?
→ plt.close(”all”)
… remove ticks?
→ ax.set_xticks([])
… remove tick labels ?
→ ax.set_[xy]ticklabels([])
… rotate tick labels ?
→ ax.set_[xy]ticks(rotation=90)
… hide top spine?
→ ax.spines[’top’].set_visible(False)
… hide legend border?
→ ax.legend(frameon=False)
… show error as shaded region?
→ ax.fill_between(X, Y+error, Y‐error)
… draw a rectangle?
→ ax.add_patch(plt.Rectangle((0, 0),1,1)
… draw a vertical line?
→ ax.axvline(x=0.5)
… draw outside frame?
→ ax.plot(…, clip_on=False)
… use transparency?
→ ax.plot(…, alpha=0.25)
… convert an RGB image into a gray image?
→ gray = 0.2989*R+0.5870*G+0.1140*B
… set figure background color?
→ fig.patch.set_facecolor(“grey”)
… get a reversed colormap?
→ plt.get_cmap(“viridis_r”)
… get a discrete colormap?
→ plt.get_cmap(“viridis”, 10)
… show a figure for one second?
→ fig.show(block=False), time.sleep(1)
ax.grid()
ax.patch.set_alpha(0)
ax.set_[xy]lim(vmin, vmax)
ax.set_[xy]label(label)
ax.set_[xy]ticks(list)
ax.set_[xy]ticklabels(list)
ax.set_[sup]title(title)
ax.tick_params(width=10, …)
ax.set_axis_[on|off]()
ax.tight_layout()
plt.gcf(), plt.gca()
mpl.rc(’axes’, linewidth=1, …)
fig.patch.set_alpha(0)
text=r’’
❞
二、图形快速绘制
star1、line plot【折线图】
官网教程：https://matplotlib.org/api/_as_gen/matplotlib.pyplot.plot.html 详细实战教程：Python可视化|matplotlib11-折线图plt.plot 快速教程：
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
my_dpi=126
fig = plt.figure(figsize=(580/my_dpi,480/my_dpi))
mpl.rcParams['axes.linewidth'] = 0.5
mpl.rcParams['xtick.major.size'] = 0.0
mpl.rcParams['ytick.major.size'] = 0.0
d = 0.01
ax = fig.add_axes([d,d,1-2*d,1-2*d])
X = np.linspace(0, 10, 100)
Y = 4+2*np.sin(2*X)
ax.plot(X, Y, color="C1", linewidth=0.75)
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1,8))
ax.set_ylim(0, 8), ax.set_yticks(np.arange(1,8))
ax.grid(linewidth=0.125)
plt.show()
star2、scatter plot【散点图】
官网教程：https://matplotlib.org/api/_as_gen/matplotlib.pyplot.scatter.html 详细实战教程：Python可视化|matplotlib10-散点图plt.scatter 快速教程：
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
my_dpi=126
fig = plt.figure(figsize=(580/my_dpi,480/my_dpi))
mpl.rcParams['axes.linewidth'] = 0.5
mpl.rcParams['xtick.major.size'] = 0.0
mpl.rcParams['ytick.major.size'] = 0.0
d = 0.01
ax = fig.add_axes([d,d,1-2*d,1-2*d])
np.random.seed(3)
X = 4+np.random.normal(0, 1.25, 24)
Y = 4+np.random.normal(0, 1.25, len(X))
ax.scatter(X, Y, 55, zorder=10,
edgecolor="white", facecolor="C1", linewidth=0.25)
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1,8))
ax.set_ylim(0, 8), ax.set_yticks(np.arange(1,8))
ax.grid(linewidth=0.125)
plt.show()
star3、bar plot【条形图】
官网教程：https://matplotlib.org/api/_as_gen/matplotlib.pyplot.bar.html 详细实战教程：Python可视化|matplotlib12-垂直|水平|堆积条形图plt.bar 快速教程：
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
my_dpi=126
fig = plt.figure(figsize=(580/my_dpi,480/my_dpi))
mpl.rcParams['axes.linewidth'] = 0.5
mpl.rcParams['xtick.major.size'] = 0.0
mpl.rcParams['ytick.major.size'] = 0.0
d = 0.01
ax = fig.add_axes([d,d,1-2*d,1-2*d])
np.random.seed(3)
X = 0.5 + np.arange(8)
Y = np.random.uniform(2, 7, len(X))
ax.bar(X, Y, bottom=0, width=1,
edgecolor="white", facecolor="C1", linewidth=0.25)
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1,8))
ax.set_ylim(0, 8), ax.set_yticks(np.arange(1,8))
ax.set_axisbelow(True)
ax.grid(linewidth=0.125)
star4、imshow plot【格子图】
官网教程：https://matplotlib.org/api/_as_gen/matplotlib.pyplot.imshow.html 详细实战教程：Python可视化|matplotlib06-外部单颜色（二） 快速教程：
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
my_dpi=126
fig = plt.figure(figsize=(580/my_dpi,480/my_dpi))
mpl.rcParams['axes.linewidth'] = 0.5
mpl.rcParams['xtick.major.size'] = 0.0
mpl.rcParams['ytick.major.size'] = 0.0
d = 0.01
ax = fig.add_axes([d,d,1-2*d,1-2*d])
np.random.seed(3)
I = np.zeros((8,8,4))
I[:,:] = mpl.colors.to_rgba("C1")
I[...,3] = np.random.uniform(0.25,1.0,(8,8))
ax.imshow(I, extent=[0,8,0,8], interpolation="nearest")
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1,8))
ax.set_ylim(0, 8), ax.set_yticks(np.arange(1,8))
ax.grid(linewidth=0.25, color="white")
plt.show()
5、contour plot【等高线图】
官网教程：https://matplotlib.org/api/_as_gen/matplotlib.pyplot.contour.html 快速教程：
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
my_dpi=126
fig = plt.figure(figsize=(580/my_dpi,480/my_dpi))
mpl.rcParams['axes.linewidth'] = 0.5
mpl.rcParams['xtick.major.size'] = 0.0
mpl.rcParams['ytick.major.size'] = 0.0
d = 0.01
ax = fig.add_axes([d,d,1-2*d,1-2*d])
np.random.seed(1)
X, Y = np.meshgrid(np.linspace(-3, 3, 256), np.linspace(-3, 3, 256))
Z = (1 - X/2. + X**5 + Y**3)*np.exp(-X**2-Y**2)
Z = Z - Z.min()
colors = np.zeros((5,4))
colors[:] = mpl.colors.to_rgba("C1")
colors[:,3] = np.linspace(0.15, 0.85, len(colors))
plt.contourf(Z, len(colors), extent=[0,8,0,8], colors=colors)
plt.contour(Z, len(colors), extent=[0,8,0,8], colors="white", linewidths=0.125,
nchunk=10)
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1,8))
ax.set_ylim(0, 8), ax.set_yticks(np.arange(1,8))
plt.show()
6、「quiver plot【箭头】」
quiver在可视化梯度变化时非常有用。
官网教程：https://matplotlib.org/api/_as_gen/matplotlib.pyplot.quiver.html 快速教程：
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
my_dpi=126
fig = plt.figure(figsize=(580/my_dpi,480/my_dpi))
mpl.rcParams['axes.linewidth'] = 0.5
mpl.rcParams['xtick.major.size'] = 0.0
mpl.rcParams['ytick.major.size'] = 0.0
d = 0.01
ax = fig.add_axes([d,d,1-2*d,1-2*d])
np.random.seed(1)
T = np.linspace(0, 2*np.pi, 8)
X, Y = 4 + 1*np.cos(T), 4 + 1*np.sin(T)
U, V = 1.5*np.cos(T), 1.5*np.sin(T)
plt.quiver(X, Y, U, V, color="C1",
angles='xy', scale_units='xy', scale=0.5, width=.05)
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1,8))
ax.set_ylim(0, 8), ax.set_yticks(np.arange(1,8))
ax.set_axisbelow(True)
ax.grid(linewidth=0.125, color="0.75")
plt.show()
star7、pie plot【饼图】
官网教程：https://matplotlib.org/api/_as_gen/matplotlib.pyplot.pie.html 详细实战教程Python可视化29|matplotlib-饼图（pie） 快速教程：
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
my_dpi=126
fig = plt.figure(figsize=(580/my_dpi,480/my_dpi))
mpl.rcParams['axes.linewidth'] = 0.5
mpl.rcParams['xtick.major.size'] = 0.0
mpl.rcParams['ytick.major.size'] = 0.0
d = 0.01
ax = fig.add_axes([d,d,1-2*d,1-2*d])
X = 1,2,3,4
colors = np.zeros((len(X),4))
colors[:] = mpl.colors.to_rgba("C1")
colors[:,3] = np.linspace(0.25, 0.75, len(X))
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1,8))
ax.set_ylim(0, 8), ax.set_yticks(np.arange(1,8))
ax.set_axisbelow(True)
ax.grid(linewidth=0.25, color="0.75")
ax.pie(X, colors=["white",]*len(X), radius=3, center=(4,4),
wedgeprops = {"linewidth": 0.25, "edgecolor": "white"}, frame=True)
ax.pie(X, colors=colors, radius=3, center=(4,4),
wedgeprops = {"linewidth": 0.25, "edgecolor": "white"}, frame=True)
plt.show()
star8、text plot【添加文本】
官网教程：https://matplotlib.org/api/_as_gen/matplotlib.pyplot.text.html 详细实战教程：Python可视化|matplotlib31-图添加文本（text）及注释（annotate） 快速教程：
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
my_dpi=126
fig = plt.figure(figsize=(580/my_dpi,480/my_dpi))
mpl.rcParams['axes.linewidth'] = 0.5
mpl.rcParams['xtick.major.size'] = 0.0
mpl.rcParams['ytick.major.size'] = 0.0
d = 0.01
ax = fig.add_axes([d,d,1-2*d,1-2*d])
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1,8))
ax.set_ylim(0, 8), ax.set_yticks(np.arange(1,8))
ax.set_axisbelow(True)
ax.grid(linewidth=0.25, color="0.75")
ax.text(4, 4, "TEXT", color="C1", size=38, weight="bold",
ha="center", va="center", rotation=25)
plt.show()
9、fill_between plot【曲线填充图】
官网教程：https://matplotlib.org/api/_as_gen/matplotlib.axes.Axes.fill_between.html#matplotlib.axes.Axes.fill_between 快速教程：
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
my_dpi=126
fig = plt.figure(figsize=(580/my_dpi,480/my_dpi))
mpl.rcParams['axes.linewidth'] = 0.5
mpl.rcParams['xtick.major.size'] = 0.0
mpl.rcParams['ytick.major.size'] = 0.0
d = 0.01
ax = fig.add_axes([d,d,1-2*d,1-2*d])
np.random.seed(1)
X = np.linspace(0, 8, 16)
Y1 = 3 + 4*X/8 + np.random.uniform(0.0, 0.5, len(X))
Y2 = 1 + 2*X/8 + np.random.uniform(0.0, 0.5, len(X))
plt.fill_between(X, Y1, Y2, color="C1", alpha=.5, linewidth=0)
plt.plot(X, (Y1+Y2)/2, color="C1", linewidth=0.5)
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1,8))
ax.set_ylim(0, 8), ax.set_yticks(np.arange(1,8))
ax.set_axisbelow(True)
ax.grid(linewidth=0.125, color="0.75")
10、step plot【阶梯图】
官网教程：https://matplotlib.org/api/_as_gen/matplotlib.pyplot.step.html 快速教程：
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
my_dpi=126
fig = plt.figure(figsize=(580/my_dpi,480/my_dpi))
mpl.rcParams['axes.linewidth'] = 0.5
mpl.rcParams['xtick.major.size'] = 0.0
mpl.rcParams['ytick.major.size'] = 0.0
d = 0.01
ax = fig.add_axes([d,d,1-2*d,1-2*d])
X = np.linspace(0, 10, 16)
Y = 4+2*np.sin(2*X)
ax.step(X, Y, color="C1", linewidth=0.75)
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1,8))
ax.set_ylim(0, 8), ax.set_yticks(np.arange(1,8))
ax.grid(linewidth=0.125)
star11、box plot【箱图】
官网教程：https://matplotlib.org/api/_as_gen/matplotlib.pyplot.boxplot.html 详细实战教程：
❝❞
Python可视化|seaborn21-catplot（分类散点图stripplot|成簇散点图swarmplot|箱图boxplot|小提琴图violinplot） Python可视化17seborn-箱图boxplot
快速教程：
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
my_dpi=126
fig = plt.figure(figsize=(580/my_dpi,480/my_dpi))
mpl.rcParams['axes.linewidth'] = 0.5
mpl.rcParams['xtick.major.size'] = 0.0
mpl.rcParams['ytick.major.size'] = 0.0
d = 0.01
ax = fig.add_axes([d,d,1-2*d,1-2*d])
np.random.seed(10)
D = np.random.normal((3,5,4), (1.25, 1.00, 1.25), (100,3))
VP = ax.boxplot(D, positions=[2,4,6], widths=1.5, patch_artist=True,
showmeans=False, showfliers=False,
medianprops = {"color": "white",
"linewidth": 0.25},
boxprops = {"facecolor": "C1",
"edgecolor": "white",
"linewidth": 0.25},
whiskerprops = {"color": "C1",
"linewidth": 0.75},
capprops = {"color": "C1",
"linewidth": 0.75})
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1,8))
ax.set_ylim(0, 8), ax.set_yticks(np.arange(1,8))
ax.set_axisbelow(True)
ax.grid(linewidth=0.125)
12、errorbar plot【误差棒】
官网教程：https://matplotlib.org/api/_as_gen/matplotlib.pyplot.errorbar.html 快速教程：
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
my_dpi=126
fig = plt.figure(figsize=(580/my_dpi,480/my_dpi))
mpl.rcParams['axes.linewidth'] = 0.5
mpl.rcParams['xtick.major.size'] = 0.0
mpl.rcParams['ytick.major.size'] = 0.0
d = 0.01
ax = fig.add_axes([d,d,1-2*d,1-2*d])
np.random.seed(1)
X = [2,4,6]
Y = [4,5,4]
E = np.random.uniform(0.5, 1.5, 3)
ax.errorbar(X, Y, E, color="C1", linewidth=0.75, capsize=1)
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1,8))
ax.set_ylim(0, 8), ax.set_yticks(np.arange(1,8))
ax.set_axisbelow(True)
ax.grid(linewidth=0.125)
star13、hist plot【直方图】
官网教程：https://matplotlib.org/api/_as_gen/matplotlib.pyplot.hist.html 详细实战教程：Python可视化|matplotlib13-直方图（histogram）详解 快速教程：
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
my_dpi=126
fig = plt.figure(figsize=(580/my_dpi,480/my_dpi))
mpl.rcParams['axes.linewidth'] = 0.5
mpl.rcParams['xtick.major.size'] = 0.0
mpl.rcParams['ytick.major.size'] = 0.0
d = 0.01
ax = fig.add_axes([d,d,1-2*d,1-2*d])
np.random.seed(1)
X = 4 + np.random.normal(0,1.5,200)
ax.hist(X, bins=8, facecolor="C1", linewidth=0.25, edgecolor="white",)
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1,8))
ax.set_ylim(0, 80), ax.set_yticks(np.arange(1,80,10))
ax.set_axisbelow(True)
ax.grid(linewidth=0.125)
star14、violin plot【小提琴图】
官网教程：https://matplotlib.org/api/_as_gen/matplotlib.axes.Axes.violinplot.html 详细实战教程：Python可视化|seaborn21-catplot（分类散点图stripplot|成簇散点图swarmplot|箱图boxplot|小提琴图violinplot） 快速教程：
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
my_dpi=126
fig = plt.figure(figsize=(580/my_dpi,480/my_dpi))
mpl.rcParams['axes.linewidth'] = 0.5
mpl.rcParams['xtick.major.size'] = 0.0
mpl.rcParams['ytick.major.size'] = 0.0
d = 0.01
ax = fig.add_axes([d,d,1-2*d,1-2*d])
np.random.seed(10)
D = np.random.normal((3,5,4), (0.75, 1.00, 0.75), (200,3))
VP = ax.violinplot(D, [2,4,6], widths=1.5,
showmeans=False, showmedians=False, showextrema=False)
for body in VP['bodies']:
body.set_facecolor('C1')
body.set_alpha(1)
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1,8))
ax.set_ylim(0, 8), ax.set_yticks(np.arange(1,8))
ax.set_axisbelow(True)
ax.grid(linewidth=0.125)
15、barbs plot【风羽图】
气象学中常用图。
官网教程：https://matplotlib.org/api/_as_gen/matplotlib.axes.Axes.barbs.html?highlight=barbs#matplotlib.axes.Axes.barbs 快速教程：
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
my_dpi=126
fig = plt.figure(figsize=(580/my_dpi,480/my_dpi))
mpl.rcParams['axes.linewidth'] = 0.5
mpl.rcParams['xtick.major.size'] = 0.0
mpl.rcParams['ytick.major.size'] = 0.0
d = 0.01
ax = fig.add_axes([d,d,1-2*d,1-2*d])
np.random.seed(1)
X = [[2,4,6]]
Y = [[1.5,3,2]]
U = -np.ones((1,3))*0
V = -np.ones((1,3))*np.linspace(50,100,3)
ax.barbs(X,Y,U,V, barbcolor="C1", flagcolor="C1", length=15, linewidth=0.5)
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1,8))
ax.set_ylim(0, 8), ax.set_yticks(np.arange(1,8))
ax.set_axisbelow(True)
ax.grid(linewidth=0.125)
16、even plot【栅格图】
官网教程：https://matplotlib.org/api/_as_gen/matplotlib.pyplot.eventplot.html 快速教程：
神经生物学中常用。
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
my_dpi=126
fig = plt.figure(figsize=(580/my_dpi,480/my_dpi))
mpl.rcParams['axes.linewidth'] = 0.5
mpl.rcParams['xtick.major.size'] = 0.0
mpl.rcParams['ytick.major.size'] = 0.0
d = 0.01
ax = fig.add_axes([d,d,1-2*d,1-2*d])
np.random.seed(1)
X = [2,4,6]
D = np.random.gamma(4, size=(3, 50))
ax.eventplot(D, colors="C1", orientation="vertical", lineoffsets=X, linewidth=0.45)
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1,8))
ax.set_ylim(0, 8), ax.set_yticks(np.arange(1,8))
ax.set_axisbelow(True)
ax.grid(linewidth=0.125)
17、hexbin plot【二元直方图】
官网教程：https://matplotlib.org/api/_as_gen/matplotlib.pyplot.hexbin.html 快速教程：
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
my_dpi=126
fig = plt.figure(figsize=(580/my_dpi,480/my_dpi))
mpl.rcParams['axes.linewidth'] = 0.5
mpl.rcParams['xtick.major.size'] = 0.0
mpl.rcParams['ytick.major.size'] = 0.0
d = 0.01
ax = fig.add_axes([d,d,1-2*d,1-2*d])
np.random.seed(1)
X = np.random.uniform(1.5,6.5,100)
Y = np.random.uniform(1.5,6.5,100)
C = np.random.uniform(0,1,10000)
ax.hexbin(X, Y, C, gridsize=4, linewidth=0.25, edgecolor="white",
cmap=plt.get_cmap("Wistia"), alpha=1.0)
ax.set_xlim(0, 8), ax.set_xticks(np.arange(1,8))
ax.set_ylim(0, 8), ax.set_yticks(np.arange(1,8))
ax.set_axisbelow(True)
ax.grid(linewidth=0.125)
18、xcorr plot【相关图】
官网教程：https://matplotlib.org/api/_as_gen/matplotlib.pyplot.xcorr.html 快速教程：
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
my_dpi=126
fig = plt.figure(figsize=(580/my_dpi,480/my_dpi))
mpl.rcParams['axes.linewidth'] = 0.5
mpl.rcParams['xtick.major.size'] = 0.0
mpl.rcParams['ytick.major.size'] = 0.0
mpl.rcParams['axes.unicode_minus'] =False
d = 0.01
ax = fig.add_axes([d,d,1-2*d,1-2*d])
np.random.seed(3)
Y = np.random.uniform(-4, 4, 250)
X = np.random.uniform(-4, 4, 250)
ax.xcorr(X, Y, usevlines=True, maxlags=6, normed=True, lw=2,
color="C1")
ax.set_xlim(-8, 8), ax.set_xticks(np.arange(-8,8,2))
ax.set_ylim(-.25, .25), ax.set_yticks(np.linspace(-.25,.25,9))
ax.set_axisbelow(True)
ax.grid(linewidth=0.125)
plt.show()
star三、多子图绘制
subplot
官网教程：
❝❞
https://matplotlib.org/api/_as_gen/matplotlib.pyplot.subplots.html https://matplotlib.org/tutorials/intermediate/gridspec.html https://matplotlib.org/api/_as_gen/matplotlib.axes.Axes.inset_axes.html
实战详细教程：Python可视化34|matplotlib-多子图绘制(为所欲为版) 快速教程：
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
my_dpi=126
fig = plt.figure(figsize=(580/my_dpi,480/my_dpi))
margin = 0.01
fig.subplots_adjust(left=margin, right=1-margin, top=1-margin, bottom=margin)
mpl.rc('axes', linewidth=.5)
nrows, ncols = 3,3
for i in range(nrows*ncols):
ax = plt.subplot(ncols, nrows, i+1)
ax.set_xticks([]), ax.set_yticks([])
add_gridspec
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
my_dpi=126
fig = plt.figure(figsize=(580/my_dpi,480/my_dpi))
margin = 0.01
fig.subplots_adjust(left=margin, right=1-margin, top=1-margin, bottom=margin)
mpl.rc('axes', linewidth=.5)
gs = fig.add_gridspec(3, 3)
ax1 = fig.add_subplot(gs[0, :], xticks=[], yticks=[])
ax2 = fig.add_subplot(gs[1, :-1], xticks=[], yticks=[])
ax3 = fig.add_subplot(gs[1:, -1], xticks=[], yticks=[])
ax4 = fig.add_subplot(gs[-1, 0], xticks=[], yticks=[])
ax5 = fig.add_subplot(gs[-1, -2], xticks=[], yticks=[])
add_axes
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
my_dpi=126
fig = plt.figure(figsize=(580/my_dpi,480/my_dpi))
margin = 0.01
fig.subplots_adjust(left=margin, right=1-margin, top=1-margin, bottom=margin)
mpl.rc('axes', linewidth=.5)
margin = 0.0125
ax1 = fig.add_axes([margin,margin,1-2*margin,1-2*margin], xticks=[], yticks=[])
ax2 = ax1.inset_axes([0.5, 0.5, 0.4, 0.4], xticks=[], yticks=[])
make_axes_locatable
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
my_dpi=126
fig = plt.figure(figsize=(580/my_dpi,480/my_dpi))
margin = 0.01
fig.subplots_adjust(left=margin, right=1-margin, top=1-margin, bottom=margin)
mpl.rc('axes', linewidth=.5)
from mpl_toolkits.axes_grid1 import make_axes_locatable
margin = 0.0125
ax = fig.add_axes([margin,margin,1-2*margin,1-2*margin], xticks=[], yticks=[])
divider = make_axes_locatable(ax)
cax = divider.new_horizontal(size="10%", pad=0.025)
fig.add_axes(cax)
cax.set_xticks([]), cax.set_yticks([])
plt.show()
star四、文本text设置
文本位置
官网教程：https://matplotlib.org/tutorials/text/text_props.html 实战详细教程：Python可视化31|matplotlib-图添加文本(text)及注释(annotate) 快速教程：
import numpy as np
import matplotlib.pyplot as plt
dpi = 100
fig = plt.figure(dpi=100)
ax = fig.add_axes([0,0,1,1], frameon=False,
xlim=(0,4.25), ylim=(0,1.5), xticks=[], yticks=[])
fontsize = 48
renderer = fig.canvas.get_renderer()
horizontalalignment = "left"
verticalalignment = "center"
position = (0.25, 1.5/2)
color = "0.25"
# Compute vertical and horizontal alignment offsets
text = ax.text(0, 0, "Matplotlib", fontsize=fontsize)
yoffset = {}
for alignment in ["top", "center", "baseline", "bottom"]:
text.set_verticalalignment(alignment)
y = text.get_window_extent(renderer).y0/dpi
yoffset[alignment] = y
xoffset = {}
for alignment in ["left", "center", "right"]:
text.set_horizontalalignment(alignment)
x = text.get_window_extent(renderer).x0/dpi
xoffset[alignment] = x
# Actual positioning of the text
text.set_horizontalalignment(horizontalalignment)
text.set_verticalalignment(verticalalignment)
text.set_position(position)
for name,y in yoffset.items():
y = position[1] - y + yoffset[verticalalignment]
plt.plot([0.1, 3.75], [y, y], linewidth=0.5, color=color)
plt.text(3.75, y, " "+name, color=color,
ha="left", va="center", size="x-small")
for name,x in xoffset.items():
x = position[0] - x + xoffset[horizontalalignment]
plt.plot([x,x], [0.25, 1.25], linewidth=0.5, color=color)
plt.text(x, 0.24, name, color = color,
ha="center", va="top", size="x-small")
P = []
for x in xoffset.values():
x = position[0] - x + xoffset[horizontalalignment]
for y in yoffset.values():
y = position[1] - y + yoffset[verticalalignment]
P.append((x,y))
P = np.array(P)
ax.scatter(P[:,0], P[:,1], s=10, zorder=10,
facecolor="white", edgecolor=color, linewidth=0.75)
epsilon = 0.05
plt.text(P[3,0]+epsilon, P[3,1]-epsilon, "(0,0)",
color=color, ha="left", va="top", size="xx-large")
plt.text(P[8,0]-epsilon, P[8,1]+epsilon, "(1,1)",
color=color, ha="right", va="bottom", size="xx-large")
plt.show()
文本属性：字体|字号|磅值
star五、注释设置
官网教程：https://matplotlib.org/api/_as_gen/matplotlib.pyplot.annotate.html 实战详细教程：Python可视化31|matplotlib-图添加文本(text)及注释(annotate) 快速教程：
#注释(annotate)
#https://matplotlib.org/api/_as_gen/matplotlib.pyplot.annotate.html
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
fig = plt.figure(figsize=(6,1))
#ax = plt.subplot(111, frameon=False, aspect=.1)
# b = 0.0
ax = fig.add_axes([0,0,1,1], frameon=False, aspect=1)
plt.scatter([5.5],[0.75], s=100, c="k")
plt.xlim(0,6), plt.ylim(0,1)
plt.xticks([]), plt.yticks([])
plt.annotate("Annotation", (5.5,.75), (0.1,.75), size=16, va="center",
arrowprops=dict(facecolor='black', shrink=0.05))
plt.text( 5.5, 0.6, "xy\nycoords", size=10, va="top", ha="center", color=".5")
plt.text( .75, 0.6, "xytext\ntextcoords", size=10, va="top", ha="center", color=".5")
plt.show()
##注释(annotate)箭头类型
#https://matplotlib.org/tutorials/text/annotations.html
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
styles = mpatches.ArrowStyle.get_styles()
def demo_con_style(ax, connectionstyle):
ax.text(.05, .95, connectionstyle.replace(",", ",\n"),
family="Source Code Pro",
transform=ax.transAxes, ha="left", va="top", size="x-small")
fig, ax = plt.subplots(dpi=100, frameon=False)
ax.axis("off")
for i,style in enumerate(mpatches.ArrowStyle.get_styles()):
x0, y0 = 5 + 5*(i%3), -(i//3)
x1, y1 = 1 + 5*(i%3), -(i//3)
ax.plot([x0, x1], [y0, y1], ".", color="0.25")
ax.annotate("",
xy=(x0, y0), xycoords='data',
xytext=(x1, y1), textcoords='data',
arrowprops=dict(arrowstyle=style,
color="black",
shrinkA=5, shrinkB=5,
patchA=None, patchB=None,
connectionstyle="arc3,rad=0"))
ax.text( (x1+x0)/2, y0-0.2, style,
family = "Source Code Pro", ha="center", va="top")
plt.show()
注释箭头形状设置
注释箭头弯曲度设置
#注释(annotate)箭头线型
import matplotlib.pyplot as plt
def demo_con_style(ax, connectionstyle):
x1, y1 = 0.3, 0.2
x2, y2 = 0.8, 0.6
ax.plot([x1, x2], [y1, y2], ".")
ax.annotate("",
xy=(x1, y1), xycoords='data',
xytext=(x2, y2), textcoords='data',
arrowprops=dict(arrowstyle="->", color="0.5",
shrinkA=5, shrinkB=5,
patchA=None, patchB=None,
connectionstyle=connectionstyle),
)
ax.text(.05, .95, connectionstyle.replace(",", ",\n"),
family="Source Code Pro",
transform=ax.transAxes, ha="left", va="top", size="x-small")
fig, axs = plt.subplots(3, 3, dpi=100)
demo_con_style(axs[0, 0], "arc3,rad=0")
demo_con_style(axs[0, 1], "arc3,rad=0.3")
demo_con_style(axs[0, 2], "angle3,angleA=0,angleB=90")
demo_con_style(axs[1, 0], "angle,angleA=-90,angleB=180,rad=0")
demo_con_style(axs[1, 1], "angle,angleA=-90,angleB=180,rad=25")
demo_con_style(axs[1, 2], "arc,angleA=-90,angleB=0,armA=0,armB=40,rad=0")
demo_con_style(axs[2, 0], "bar,fraction=0.3")
demo_con_style(axs[2, 1], "bar,fraction=-0.3")
demo_con_style(axs[2, 2], "bar,angle=180,fraction=-0.2")
for ax in axs.flat:
ax.set(xlim=(0, 1), ylim=(0, 1), xticks=[], yticks=[], aspect=1)
fig.tight_layout(pad=0.2)
plt.show()
star五、坐标轴刻度Tick设置
官网教程：https://matplotlib.org/api/ticker_api.html 实战详细教程：python可视化|matplotlib02-matplotlib.pyplot坐标轴|刻度值|刻度|标题设置 快速教程：
刻度间距设置
#https://matplotlib.org/api/ticker_api.html
#刻度间距设置
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
# Setup a plot such that only the bottom spine is shown
def setup(ax):
ax.spines['right'].set_color('none')
ax.spines['left'].set_color('none')
ax.yaxis.set_major_locator(ticker.NullLocator())
ax.spines['top'].set_color('none')
ax.xaxis.set_ticks_position('bottom')
ax.tick_params(which='major', width=1.00)
ax.tick_params(which='major', length=5)
ax.tick_params(which='minor', width=0.75)
ax.tick_params(which='minor', length=2.5)
ax.set_xlim(0, 5)
ax.set_ylim(0, 1)
ax.patch.set_alpha(0.0)
fig = plt.figure(figsize=(8, 5))
fig.patch.set_alpha(0.0)
n = 8
fontsize = 18
family = "Source Code Pro"
# Null Locator
ax = plt.subplot(n, 1, 1)
setup(ax)
ax.xaxis.set_major_locator(ticker.NullLocator())
ax.xaxis.set_minor_locator(ticker.NullLocator())
ax.text(0.0, 0.1, "ticker.NullLocator()",
family=family, fontsize=fontsize, transform=ax.transAxes)
# Multiple Locator
ax = plt.subplot(n, 1, 2)
setup(ax)
ax.xaxis.set_major_locator(ticker.MultipleLocator(0.5))
ax.xaxis.set_minor_locator(ticker.MultipleLocator(0.1))
ax.text(0.0, 0.1, "ticker.MultipleLocator(0.5)",
family=family, fontsize=fontsize, transform=ax.transAxes)
# Fixed Locator
ax = plt.subplot(n, 1, 3)
setup(ax)
majors = [0, 1, 5]
ax.xaxis.set_major_locator(ticker.FixedLocator(majors))
minors = np.linspace(0, 1, 11)[1:-1]
ax.xaxis.set_minor_locator(ticker.FixedLocator(minors))
ax.text(0.0, 0.1, "ticker.FixedLocator([0, 1, 5])",
family=family, fontsize=fontsize, transform=ax.transAxes)
# Linear Locator
ax = plt.subplot(n, 1, 4)
setup(ax)
ax.xaxis.set_major_locator(ticker.LinearLocator(3))
ax.xaxis.set_minor_locator(ticker.LinearLocator(31))
ax.text(0.0, 0.1, "ticker.LinearLocator(numticks=3)",
family=family, fontsize=fontsize, transform=ax.transAxes)
# Index Locator
ax = plt.subplot(n, 1, 5)
setup(ax)
ax.plot(range(0, 5), [0]*5, color='white')
ax.xaxis.set_major_locator(ticker.IndexLocator(base=.5, offset=.25))
ax.text(0.0, 0.1, "ticker.IndexLocator(base=0.5, offset=0.25)",
family=family, fontsize=fontsize, transform=ax.transAxes)
# Auto Locator
ax = plt.subplot(n, 1, 6)
setup(ax)
ax.xaxis.set_major_locator(ticker.AutoLocator())
ax.xaxis.set_minor_locator(ticker.AutoMinorLocator())
ax.text(0.0, 0.1, "ticker.AutoLocator()",
family=family, fontsize=fontsize, transform=ax.transAxes)
# MaxN Locator
ax = plt.subplot(n, 1, 7)
setup(ax)
ax.xaxis.set_major_locator(ticker.MaxNLocator(4))
ax.xaxis.set_minor_locator(ticker.MaxNLocator(40))
ax.text(0.0, 0.1, "ticker.MaxNLocator(n=4)",
family=family, fontsize=fontsize, transform=ax.transAxes)
# Log Locator
ax = plt.subplot(n, 1, 8)
setup(ax)
ax.set_xlim(10**3, 10**10)
ax.set_xscale('log')
ax.xaxis.set_major_locator(ticker.LogLocator(base=10.0, numticks=15))
ax.text(0.0, 0.1, "ticker.LogLocator(base=10, numticks=15)",
family=family, fontsize=fontsize, transform=ax.transAxes)
# Push the top of the top axes outside the figure because we only show the
# bottom spine.
plt.subplots_adjust(left=0.05, right=0.95, bottom=0.05, top=1.05)
刻度标签格式化输出
# 刻度格式化输出
# https://matplotlib.org/api/ticker_api.html
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
# Setup a plot such that only the bottom spine is shown
def setup(ax):
ax.spines['right'].set_color('none')
ax.spines['left'].set_color('none')
ax.yaxis.set_major_locator(ticker.NullLocator())
ax.spines['top'].set_color('none')
ax.xaxis.set_ticks_position('bottom')
ax.tick_params(which='major', width=1.00, length=5)
ax.tick_params(which='minor', width=0.75, length=2.5, labelsize=10)
ax.set_xlim(0, 5)
ax.set_ylim(0, 1)
ax.patch.set_alpha(0.0)
fig = plt.figure(figsize=(8, 5))
fig.patch.set_alpha(0.0)
n = 7
fontsize = 18
family = "Source Code Pro"
# Null formatter
ax = fig.add_subplot(n, 1, 1)
setup(ax)
ax.xaxis.set_major_locator(ticker.MultipleLocator(1.00))
ax.xaxis.set_minor_locator(ticker.MultipleLocator(0.25))
ax.xaxis.set_major_formatter(ticker.NullFormatter())
ax.xaxis.set_minor_formatter(ticker.NullFormatter())
ax.text(0.0, 0.1, "ticker.NullFormatter()", family=family,
fontsize=fontsize, transform=ax.transAxes)
# Fixed formatter
ax = fig.add_subplot(n, 1, 2)
setup(ax)
ax.xaxis.set_major_locator(ticker.MultipleLocator(1.0))
ax.xaxis.set_minor_locator(ticker.MultipleLocator(0.25))
majors = ["", "0", "1", "2", "3", "4", "5"]
ax.xaxis.set_major_formatter(ticker.FixedFormatter(majors))
minors = [""] + ["%.2f" % (x-int(x)) if (x-int(x))
else "" for x in np.arange(0, 5, 0.25)]
ax.xaxis.set_minor_formatter(ticker.FixedFormatter(minors))
ax.text(0.0, 0.1, "ticker.FixedFormatter(['', '0', '1', ...])",
family=family, fontsize=fontsize, transform=ax.transAxes)
# FuncFormatter can be used as a decorator
@ticker.FuncFormatter
def major_formatter(x, pos):
return "[%.2f]" % x
ax = fig.add_subplot(n, 1, 3)
setup(ax)
ax.xaxis.set_major_locator(ticker.MultipleLocator(1.00))
ax.xaxis.set_minor_locator(ticker.MultipleLocator(0.25))
ax.xaxis.set_major_formatter(major_formatter)
ax.text(0.0, 0.1, 'ticker.FuncFormatter(lambda x, pos: "[%.2f]" % x)',
family=family, fontsize=fontsize, transform=ax.transAxes)
# FormatStr formatter
ax = fig.add_subplot(n, 1, 4)
setup(ax)
ax.xaxis.set_major_locator(ticker.MultipleLocator(1.00))
ax.xaxis.set_minor_locator(ticker.MultipleLocator(0.25))
ax.xaxis.set_major_formatter(ticker.FormatStrFormatter(">%d<"))
ax.text(0.0, 0.1, "ticker.FormatStrFormatter('>%d<')",
family=family, fontsize=fontsize, transform=ax.transAxes)
# Scalar formatter
ax = fig.add_subplot(n, 1, 5)
setup(ax)
ax.xaxis.set_major_locator(ticker.AutoLocator())
ax.xaxis.set_minor_locator(ticker.AutoMinorLocator())
ax.xaxis.set_major_formatter(ticker.ScalarFormatter(useMathText=True))
ax.text(0.0, 0.1, "ticker.ScalarFormatter()",
family=family, fontsize=fontsize, transform=ax.transAxes)
# StrMethod formatter
ax = fig.add_subplot(n, 1, 6)
setup(ax)
ax.xaxis.set_major_locator(ticker.MultipleLocator(1.00))
ax.xaxis.set_minor_locator(ticker.MultipleLocator(0.25))
ax.xaxis.set_major_formatter(ticker.StrMethodFormatter("{x}"))
ax.text(0.0, 0.1, "ticker.StrMethodFormatter('{x}')",
family=family, fontsize=fontsize, transform=ax.transAxes)
# Percent formatter
ax = fig.add_subplot(n, 1, 7)
setup(ax)
ax.xaxis.set_major_locator(ticker.MultipleLocator(1.00))
ax.xaxis.set_minor_locator(ticker.MultipleLocator(0.25))
ax.xaxis.set_major_formatter(ticker.PercentFormatter(xmax=5))
ax.text(0.0, 0.1, "ticker.PercentFormatter(xmax=5)",
family=family, fontsize=fontsize, transform=ax.transAxes)
# Push the top of the top axes outside the figure because we only show the
# bottom spine.
fig.subplots_adjust(left=0.05, right=0.95, bottom=0.05, top=1.05)
star六、图例(legend)设置
官网教程：https://matplotlib.org/api/_as_gen/matplotlib.pyplot.legend.html 实战详细教程：Python可视化32|matplotlib-断裂坐标轴(broken_axis)|图例(legend)详解 快速教程：
#图例(legend)|位置
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
fig = plt.figure(figsize=(4,4))
ax = fig.add_axes([0.15,0.15,.7,.7], frameon=True, aspect=1,
xticks=[], yticks=[])
def text(x, y, _text):
color= "C1"
if not 0 < x < 1 or not 0 < y < 1: color = "C0"
size = 0.15
ax.text(x, y, _text, color="white", #bbox={"color": "C1"},
size="xx-large", weight="bold", ha="center", va="center")
rect = plt.Rectangle((x-size/2, y-size/2), size, size, facecolor=color,
zorder=-10, clip_on=False)
ax.add_patch(rect)
def point(x, y):
ax.scatter([x], [y], facecolor="C0", edgecolor="white",
zorder=10, clip_on=False)
d = .1
e = .15/2
text( d, d, "1"), text( 0.5, d, "2"), text(1-d, d, "3")
text( d, 0.5, "4"), text( 0.5, 0.5, "5"), text(1-d, 0.5, "6")
text( d, 1-d, "7"), text( 0.5, 1-d, "8"), text(1-d, 1-d, "9")
text( -d, 1-d, "A"), text( -d, 0.5, "B"), text( -d, d, "C")
point(-d+e, 1-d+e), point(-d+e, 0.5), point(-d+e, d-e),
text( d, -d, "D"), text(0.5, -d, "E"), text( 1-d, -d, "F")
point(d-e, -d+e), point(0.5, -d+e), point(1-d+e, -d+e),
text(1+d, d, "G"), text(1+d, 0.5, "H"), text( 1+d, 1-d, "I")
point(1+d-e, d-e), point(1+d-e, .5), point(1+d-e, 1-d+e),
text(1-d, 1+d, "J"), text(0.5, 1+d, "K"), text( d, 1+d, "L")
point(1-d+e, 1+d-e), point(0.5, 1+d-e), point(d-e, 1+d-e),
plt.xlim(0,1), plt.ylim(0,1)
plt.show()
❝1: lower left 2: lower center 3: lower right
❞
4: left 5: center 6: right
7: upper left 8: upper center 9: upper right
A: upper right / (‐.1,.9) B: right / (‐.1,.5)
C: lower right / (‐.1,.1) D: upper left / (‐.1,‐.1)
E: upper center / (.5,‐.1) F: upper right / (.9,‐.1)
G: lower left / (1.1,.1) H: left / (1.1,.5)
I: upper left / (1.1,.9) J: lower right / (.9,1.1)
K: lower center / (.5,1.1) L: lower left / (.1,1.1)
starstar七、Colors和Colormaps
实战详细教程：
关于颜色使用，之前花了不少精力整理：
❝Python可视化|matplotlib05-内置单颜色（一）
❞
Python可视化|matplotlib06-外部单颜色（二）
Python可视化|matplotlib07-自带颜色条Colormap（三）
Python可视化|08-Palettable库中颜色条Colormap（四）
Python|R可视化|09-提取图片颜色绘图（五）
颜色cheatsheet（一）
颜色cheatsheet（二）
Python可视化18|seaborn-seaborn调色盘
star八、line和marker设置
star九、子图与figure之间位置
# figure中子图位置调整
#matplotlib.pyplot.subplots_adjust
#https://matplotlib.org/api/_as_gen/matplotlib.pyplot.subplots_adjust.html
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
from matplotlib.collections import PatchCollection
fig = plt.figure(dpi=120)
ax = fig.add_axes([0,0,1,1], frameon=False, aspect=1,
xlim=(0-5,100+10), ylim=(-10,80+5), xticks=[], yticks=[])
box = mpatches.FancyBboxPatch(
(0,0), 100, 83, mpatches.BoxStyle("Round", pad=0, rounding_size=2),
linewidth=1., facecolor="0.9", edgecolor="black")
ax.add_artist(box)
box = mpatches.FancyBboxPatch(
(0,0), 100, 75, mpatches.BoxStyle("Round", pad=0, rounding_size=0),
linewidth=1., facecolor="white", edgecolor="black")
ax.add_artist(box)
box = mpatches.Rectangle(
(5,5), 45, 30, zorder=10,
linewidth=1.0, facecolor="white", edgecolor="black")
ax.add_artist(box)
box = mpatches.Rectangle(
(5,40), 45, 30, zorder=10,
linewidth=1.0, facecolor="white", edgecolor="black")
ax.add_artist(box)
box = mpatches.Rectangle(
(55,5), 40, 65, zorder=10,
linewidth=1.0, facecolor="white", edgecolor="black")
ax.add_artist(box)
# Window button
X, Y = [5,10,15], [79,79,79]
plt.scatter(X, Y, s=75, zorder=10,
edgecolor="black", facecolor="white", linewidth=1)
# Window size extension
X, Y = [0, 0], [0, -8]
plt.plot(X, Y, color="black", linestyle=":", linewidth=1, clip_on=False)
X, Y = [100, 100], [0, -8]
plt.plot(X, Y, color="black", linestyle=":", linewidth=1, clip_on=False)
X, Y = [100, 108], [0, 0]
plt.plot(X, Y, color="black", linestyle=":", linewidth=1, clip_on=False)
X, Y = [100, 108], [75, 75]
plt.plot(X, Y, color="black", linestyle=":", linewidth=1, clip_on=False)
def ext_arrow(p0,p1,p2,p3):
p0, p1 = np.asarray(p0), np.asarray(p1)
p2, p3 = np.asarray(p2), np.asarray(p3)
ax.arrow(*p0, *(p1-p0), zorder=20, linewidth=0,
length_includes_head=True, width=.4,
head_width=2, head_length=2, color="black")
ax.arrow(*p3, *(p2-p3), zorder=20, linewidth=0,
length_includes_head=True, width=.4,
head_width=2, head_length=2, color="black")
plt.plot([p1[0],p2[0]], [p1[1],p2[1]], linewidth=.9, color="black")
def int_arrow(p0,p1):
p0, p1 = np.asarray(p0), np.asarray(p1)
ax.arrow(*((p0+p1)/2), *((p1-p0)/2), zorder=20, linewidth=0,
length_includes_head=True, width=.4,
head_width=2, head_length=2, color="black")
ax.arrow(*((p0+p1)/2), *(-(p1-p0)/2), zorder=20, linewidth=0,
length_includes_head=True, width=.4,
head_width=2, head_length=2, color="black")
x = 0
y = 10
ext_arrow( (x-4,y), (x,y), (x+5,y), (x+9,y) )
ax.text(x+9.5, y, "left", ha="left", va="center", size="x-small", zorder=20)
x += 50
ext_arrow( (x-4,y), (x,y), (x+5,y), (x+9,y) )
ax.text(x-4.5, y, "wspace", ha="right", va="center", size="x-small", zorder=20)
x += 45
ext_arrow( (x-4,y), (x,y), (x+5,y), (x+9,y) )
ax.text(x-4.5, y, "right", ha="right", va="center", size="x-small", zorder=20)
y = 0
x = 25
ext_arrow( (x,y-4), (x,y), (x,y+5), (x,y+9) )
ax.text(x, y+9.5, "bottom", ha="center", va="bottom", size="x-small", zorder=20)
y += 35
ext_arrow( (x,y-4), (x,y), (x,y+5), (x,y+9) )
ax.text(x, y-4.5, "hspace", ha="center", va="top", size="x-small", zorder=20)
y += 35
ext_arrow( (x,y-4), (x,y), (x,y+5), (x,y+9) )
ax.text(x, y-4.5, "top", ha="center", va="top", size="x-small", zorder=20)
int_arrow((0,-5), (100,-5))
ax.text(50, -5, "figure width", backgroundcolor="white", zorder=30,
ha="center", va="center", size="x-small")
int_arrow((105,0), (105,75))
ax.text(105, 75/2, "figure height", backgroundcolor="white", zorder=30,
rotation = "vertical", ha="center", va="center", size="x-small")
int_arrow((55,62.5), (95,62.5))
ax.text(75, 62.5, "axes width", backgroundcolor="white", zorder=30,
ha="center", va="center", size="x-small")
int_arrow((62.5,5), (62.5,70))
ax.text(62.5, 35, "axes height", backgroundcolor="white", zorder=30,
rotation = "vertical", ha="center", va="center", size="x-small")
plt.show()
参考资料
❝❞
https://github.com/matplotlib https://github.com/rougier 【快速绘图代码来源】
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