官方样例:https://matplotlib.org/gallery.html
API: https://matplotlib.org/api/pyplot_summary.html
一、基本绘图函数
1、mp.plot(水平座标数组, 垂直座标数组)
import numpy as np
import matplotlib.pyplot as mp
# example_first
x = np.arange(1,7)
y1 = 2 * x + 5
y2 = 3 * x - 7
mp.figure()
mp.plot(x, y1) # 水平座标数组, 垂直座标数组
mp.plot(x, y2) # 水平座标数组, 垂直座标数组
mp.show()
# example_second
x = np.linspace(-np.pi, np.pi, 1000)
cos_y = np.cos(x) / 2
sin_y = np.sin(x)
mp.plot(x, cos_y, x, sin_y) # 水平座标数组, 垂直座标数组 连续输入
mp.show()
2、mp.plot(x,y,format_string1)
import numpy as np
import matplotlib.pyplot as mp
a=np.arange(10)
mp.plot(a, a*1.5, 'go-', a, a*2, 'b-..', a, a*5, 'r1:') # 格式字符串中的顺序没有要求
mp.show()
3、mp.plot(…, linestyle=线型, linewidth=线宽,color=颜色)
import numpy as np
import matplotlib.pyplot as mp
x = np.linspace(-np.pi, np.pi, 1000)
cos_y = np.cos(x) / 2
sin_y = np.sin(x)
mp.plot(x, cos_y, linestyle='--', linewidth=6, color='dodgerblue') # 指定线性、线宽、颜色
mp.plot(x, sin_y, linestyle=':', linewidth=0.5, color='orangered') # 指定线性、线宽、颜色
mp.show()
4、mp.xlim(左边界, 右边界) / mp.ylim(底边界, 顶边界)
import numpy as np
import matplotlib.pyplot as mp
x = np.linspace(-np.pi, np.pi, 1000)
cos_y = np.cos(x) / 2
sin_y = np.sin(x)
mp.xlim(x.min(), x.max()) # 指定 左边界和右边界
mp.ylim(sin_y.min(), sin_y.max()) # 指定 底边界和顶边界
mp.plot(x, cos_y, linestyle='--', linewidth=6, color='dodgerblue')
mp.plot(x, sin_y, linestyle=':', linewidth=0.5, color='orangered')
mp.show()
5、mp.xticks(刻度位置数组, 刻度文本数组) / mp.yticks(刻度位置数组, 刻度文本数组)
import numpy as np
import matplotlib.pyplot as mp
x = np.linspace(-np.pi, np.pi, 1000)
cos_y = np.cos(x) / 2
sin_y = np.sin(x)
mp.xlim(x.min() * 1.1, x.max() * 1.1)
mp.ylim(sin_y.min() * 1.1, sin_y.max() * 1.1)
mp.xticks([-np.pi, -np.pi / 2, 0, np.pi / 2, np.pi * 3 / 4, np.pi], # 刻度位置数组
[r'$-\pi$', r'$-\frac{\pi}{2}$', r'$0$', r'$\frac{\pi}{2}$', r'$\frac{3\pi}{4}$', r'$\pi$']) # 刻度文本数组
mp.yticks([-1, -0.5, 0.5, 1])
mp.plot(x, cos_y, linestyle='-', linewidth=2, color='dodgerblue')
mp.plot(x, sin_y, linestyle='-', linewidth=2, color='orangered')
mp.show()
5、座标轴
ax = mp.gca() # 获取当前座标轴
ax.spines[‘left’].set_position((‘data’, 0))
ax.spines[‘left’].set_color(颜色)
import numpy as np
import matplotlib.pyplot as mp
x = np.linspace(-np.pi, np.pi, 1000)
cos_y = np.cos(x) / 2
sin_y = np.sin(x)
mp.xlim(x.min() * 1.1, x.max() * 1.1)
mp.ylim(sin_y.min() * 1.1, sin_y.max() * 1.1)
mp.xticks([-np.pi, -np.pi / 2, 0, np.pi / 2, np.pi * 3 / 4, np.pi],
[r'$-\pi$', r'$-\frac{\pi}{2}$', r'$0$', r'$\frac{\pi}{2}$', r'$\frac{3\pi}{4}$', r'$\pi$'])
mp.yticks([-1, -0.5, 0.5, 1])
ax = mp.gca() # 获取当前座标轴
ax.spines['left'].set_position(('data', 0)) # 设置 y 轴的位置(左边线)
ax.spines['bottom'].set_position(('data', 0)) # 设置 x 轴的位置(下边线)
ax.spines['right'].set_color('none') # 右边线 清除
ax.spines['top'].set_color('none') # 上边线 清除
mp.plot(x, cos_y, linestyle='-', linewidth=2, color='dodgerblue')
mp.plot(x, sin_y, linestyle='-', linewidth=2, color='orangered')
mp.show()
6、mp.plot(…, label=图例文本) / mp.legend(loc=‘upper left’)
import numpy as np
import matplotlib.pyplot as mp
x = np.linspace(-np.pi, np.pi, 1000)
cos_y = np.cos(x) / 2
sin_y = np.sin(x)
mp.xlim(x.min() * 1.1, x.max() * 1.1)
mp.ylim(sin_y.min() * 1.1, sin_y.max() * 1.1)
mp.xticks([-np.pi, -np.pi / 2, 0, np.pi / 2, np.pi * 3 / 4, np.pi],
[r'$-\pi$', r'$-\frac{\pi}{2}$', r'$0$', r'$\frac{\pi}{2}$', r'$\frac{3\pi}{4}$', r'$\pi$'])
mp.yticks([-1, -0.5, 0.5, 1])
ax = mp.gca()
ax.spines['left'].set_position(('data', 0))
ax.spines['bottom'].set_position(('data', 0))
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
mp.plot(x, cos_y, linestyle='-', linewidth=2, color='dodgerblue', label=r'$y=\frac{1}{2}cos(x)$') # 添加 label=图例文本
mp.plot(x, sin_y, linestyle='-', linewidth=2, color='orangered', label=r'$y=sin(x)$') # 添加 label=图例文本
mp.legend(loc='upper left') # 设置显示位置
mp.show()
7、描点
mp.scatter(水平座标数组, 垂直座标数组,marker=点型, s=大小, edgecolor=勾边色,facecolor=填充色, zorder=Z序)
import numpy as np
import matplotlib.pyplot as mp
x = np.linspace(-np.pi, np.pi, 1000)
cos_y = np.cos(x) / 2
sin_y = np.sin(x)
xo = np.pi * 3 / 4
yo_cos = np.cos(xo) / 2
yo_sin = np.sin(xo)
mp.xlim(x.min() * 1.1, x.max() * 1.1)
mp.ylim(sin_y.min() * 1.1, sin_y.max() * 1.1)
mp.xticks([-np.pi, -np.pi / 2, 0, np.pi / 2, np.pi * 3 / 4, np.pi],
[r'$-\pi$', r'$-\frac{\pi}{2}$', r'$0$', r'$\frac{\pi}{2}$', r'$\frac{3\pi}{4}$', r'$\pi$'])
mp.yticks([-1, -0.5, 0.5, 1])
ax = mp.gca()
ax.spines['left'].set_position(('data', 0))
ax.spines['bottom'].set_position(('data', 0))
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
mp.plot(x, cos_y, linestyle='-', linewidth=2, color='dodgerblue', label=r'$y=\frac{1}{2}cos(x)$')
mp.plot(x, sin_y, linestyle='-', linewidth=2, color='orangered', label=r'$y=sin(x)$')
mp.plot([xo, xo], [yo_cos, yo_sin], linestyle='--', linewidth=1, color='limegreen') # 画线
mp.scatter([xo, xo], [yo_cos, yo_sin], s=60, edgecolor='limegreen', facecolor='white', zorder=3) # 描点
mp.legend(loc='upper left')
mp.show()
7、注释
mp.annotate(备注文本,xy=目标位置,xycoords=目标座标系,xytext=文本位置,textcoords=文本座标系,fontsize=字体大小,arrowprops=箭头属性)
import numpy as np
import matplotlib.pyplot as mp
x = np.linspace(-np.pi, np.pi, 1000)
cos_y = np.cos(x) / 2
sin_y = np.sin(x)
xo = np.pi * 3 / 4
yo_cos = np.cos(xo) / 2
yo_sin = np.sin(xo)
mp.xlim(x.min() * 1.1, x.max() * 1.1)
mp.ylim(sin_y.min() * 1.1, sin_y.max() * 1.1)
mp.xticks([-np.pi, -np.pi / 2, 0, np.pi / 2, np.pi * 3 / 4, np.pi],
[r'$-\pi$', r'$-\frac{\pi}{2}$', r'$0$', r'$\frac{\pi}{2}$', r'$\frac{3\pi}{4}$', r'$\pi$'])
mp.yticks([-1, -0.5, 0.5, 1])
ax = mp.gca()
ax.spines['left'].set_position(('data', 0))
ax.spines['bottom'].set_position(('data', 0))
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
mp.plot(x, cos_y, linestyle='-', linewidth=2, color='dodgerblue', label=r'$y=\frac{1}{2}cos(x)$')
mp.plot(x, sin_y, linestyle='-', linewidth=2, color='orangered', label=r'$y=sin(x)$')
mp.plot([xo, xo], [yo_cos, yo_sin], linestyle='--', linewidth=1, color='limegreen')
mp.scatter([xo, xo], [yo_cos, yo_sin], s=60, edgecolor='limegreen', facecolor='white', zorder=3)
mp.legend(loc='upper left')
mp.annotate(
r'$\frac{1}{2}cos(\frac{3\pi}{4})=-\frac{\sqrt{2}}{4}$',
xy=(xo, yo_cos), xycoords='data',
xytext=(-90, -40), textcoords='offset points',
fontsize=14,
arrowprops=dict(arrowstyle='->',connectionstyle='arc3, rad=.2')) # 注释
mp.annotate( # 注释
r'$sin(\frac{3\pi}{4})=\frac{\sqrt{2}}{2}$', # 备注文本
xy=(xo, yo_sin), xycoords='data', # 目标位置, 目标座标系
xytext=(20, 20), textcoords='offset points', # 文本位置, 文本座标系
fontsize=14, # 字体大小,
arrowprops=dict(arrowstyle='->',connectionstyle='arc3, rad=.2')) # 箭头属性
mp.show()
二、图形对象
1、mp.figure(图形对象名, figsize=窗口大小,dpi=分辨率, facecolor=颜色)
import numpy as np
import matplotlib.pyplot as mp
x = np.linspace(-np.pi, np.pi, 1000)
cos_y = np.cos(x) / 2
sin_y = np.sin(x)
mp.figure('Figure Object 1', figsize=(6, 4), dpi=120, facecolor='lightgray')
mp.title('Figure Object 1', fontsize=16)
mp.xlabel('x', fontsize=12)
mp.ylabel('y', fontsize=12)
mp.tick_params(labelsize=10)
mp.grid(linestyle=':')
mp.figure('Figure Object 2', figsize=(6, 4), dpi=120, facecolor='lightgray')
mp.title('Figure Object 2', fontsize=16)
mp.xlabel('x', fontsize=12)
mp.ylabel('y', fontsize=12)
mp.tick_params(labelsize=10)
mp.grid(linestyle=':')
mp.figure('Figure Object 1')
mp.plot(x, cos_y, label=r'$y=\frac{1}{2}cos(x)$')
mp.legend()
mp.figure('Figure Object 2')
mp.plot(x, sin_y, label=r'$y=sin(x)$')
mp.legend()
mp.show()
三、子图
1、缺省布局
mp.subplot(行数, 列数, 图号)
mp.subplot(2, 3, 1)
mp.subplot(231)
import matplotlib.pyplot as mp
mp.figure(facecolor='lightgray')
for i in range(2):
for j in range(3):
k = i * 3 + j + 1
mp.subplot(2, 3, k)
mp.xticks(())
mp.yticks(())
mp.text(0.5, 0.5, str(k), ha='center', va='center', size=36, alpha=0.5)
mp.tight_layout()
mp.show()
2、栅格布局
import matplotlib.gridspec as mg
gs = mg.GridSpec(行数, 列数) # 栅格布局器
mp.subplot(gs[行, 列])
import matplotlib.pyplot as mp
import matplotlib.gridspec as mg
mp.figure(facecolor='lightgray')
gs = mg.GridSpec(3, 3)
mp.subplot(gs[0, :2])
mp.xticks(())
mp.yticks(())
mp.text(0.5, 0.5, '1', ha='center', va='center', size=36, alpha=0.5)
mp.subplot(gs[1:, 0])
mp.xticks(())
mp.yticks(())
mp.text(0.5, 0.5, '2', ha='center', va='center', size=36, alpha=0.5)
mp.subplot(gs[2, 1:])
mp.xticks(())
mp.yticks(())
mp.text(0.5, 0.5, '3', ha='center', va='center', size=36, alpha=0.5)
mp.subplot(gs[:2, 2])
mp.xticks(())
mp.yticks(())
mp.text(0.5, 0.5, '4', ha='center', va='center', size=36, alpha=0.5)
mp.subplot(gs[1, 1])
mp.xticks(())
mp.yticks(())
mp.text(0.5, 0.5, '5', ha='center', va='center', size=36, alpha=0.5)
mp.tight_layout()
mp.show()
3、自由布局
mp.axes([左下角水平座标, 左下角垂直座标, 宽度, 高度])
其中所有的尺寸参数都是相对比例。
import matplotlib.pyplot as mp
mp.figure(facecolor='lightgray')
mp.axes([0.03, 0.038, 0.94, 0.924])
mp.xticks(())
mp.yticks(())
mp.text(0.5, 0.5, '1', ha='center', va='center', size=36, alpha=0.5)
mp.axes([0.63, 0.076, 0.31, 0.308])
mp.xticks(())
mp.yticks(())
mp.text(0.5, 0.5, '2', ha='center', va='center', size=36, alpha=0.5)
mp.show()
4、座标刻度定位器
定位器对象 = mp.xxxLocator(…)
ax = mp.gca()
ax.xaxis.set_major_locator(定位器对象) # 主刻度
ax.xaxis.set_minor_locator(定位器对象) # 次刻度
import numpy as np
import matplotlib.pyplot as mp
mp.figure()
locators = [
'mp.NullLocator()',
'mp.MaxNLocator(nbins=3, steps=[1, 3, 5, 7, 9])',
'mp.FixedLocator(locs=[0, 2.5, 5, 7.5, 10])',
'mp.AutoLocator()',
'mp.IndexLocator(offset=0.5, base=1.5)',
'mp.MultipleLocator()',
'mp.LinearLocator(numticks=21)',
'mp.LogLocator(base=2, subs=[1.0])']
n_locators = len(locators)
for i, locator in enumerate(locators):
mp.subplot(n_locators, 1, i + 1) # 布局 :n_locators行,1列
mp.xlim(0, 10) # x轴 范围
mp.ylim(-1, 1) # y轴 范围
mp.yticks(()) # y赋值 空
ax = mp.gca() # 获取当前的axes绘图区域
# 清除上、左、右边界,保留底边x轴
ax.spines['left'].set_color('none')
ax.spines['top'].set_color('none')
ax.spines['right'].set_color('none')
ax.spines['bottom'].set_position(('data', 0))
ax.xaxis.set_major_locator(eval(locator)) # 主刻度
ax.xaxis.set_minor_locator(mp.MultipleLocator(0.1)) # 次刻度
mp.plot(np.arange(11), np.zeros(11), c='none') # 画线
mp.text(5, 0.3, locator[3:], ha='center', size=12) # 文本
mp.tight_layout()
mp.show()
5、散点图
import numpy as np
import matplotlib.pyplot as mp
n = 1000
x = np.random.normal(0, 1, n) # 正态分布数据获取
y = np.random.normal(0, 1, n)
d = np.sqrt(x ** 2 + y ** 2)
mp.figure('Scatter', facecolor='lightgray')
mp.title('Scatter', fontsize=20)
mp.xlabel('x', fontsize=14) # x轴标签
mp.ylabel('y', fontsize=14)
mp.tick_params(labelsize=10)
mp.grid(linestyle=':')
mp.scatter(x, y, s=60, c=d, cmap='jet_r', alpha=0.5, marker='o') # 描点 c:颜色
mp.show()
6、区域填充
mp.fill_between(水平座标数组, 垂直座标起点数组, 垂直座标终点数组, 条件, color=颜色, alpha=透明度)
import numpy as np
import matplotlib.pyplot as mp
n = 1000
x = np.linspace(0, 8 * np.pi, n)
sin_y = np.sin(x)
cos_y = np.cos(x / 2) / 2
mp.figure('Fill', facecolor='lightgray')
mp.title('Fill', fontsize=20)
mp.xlabel('x', fontsize=14)
mp.ylabel('y', fontsize=14)
mp.tick_params(labelsize=10)
mp.grid(linestyle=':')
mp.plot(x, sin_y, c='dodgerblue', label=r'$y=sin(x)$')
mp.plot(x, cos_y, c='orangered', label=r'$y=\frac{1}{2}cos(\frac{x}{2})$')
mp.fill_between(x, cos_y, sin_y, cos_y < sin_y, color='dodgerblue', alpha=0.5) # 填充
mp.fill_between(x, cos_y, sin_y, cos_y > sin_y, color='orangered', alpha=0.5) # 填充
mp.legend()
mp.show()
7、柱状图
mp.bar(水平座标数组, 高度数组, ec=边缘颜色, fc=填充颜色, label=标签文本, alpha=透明度)
import numpy as np
import matplotlib.pyplot as mp
n = 12
x = np.arange(n)
y1 = (1 - x / n) * np.random.uniform(0.5, 1.0, n) # 均匀分布
y2 = (1 - x / n) * np.random.uniform(0.5, 1.0, n)
mp.figure('Bar', facecolor='lightgray')
mp.title('Bar', fontsize=20)
mp.ylim(-1.25, 1.25)
mp.xlabel('x', fontsize=14)
mp.ylabel('y', fontsize=14)
mp.xticks(x, x + 1)
mp.tick_params(labelsize=10)
mp.grid(axis='y', linestyle=':')
mp.bar(x, y1, ec='white', fc='dodgerblue', label='Sample 1') # 柱状
for _x, _y in zip(x, y1):
mp.text(_x, _y, '%.2f' % _y, ha='center', va='bottom', size=8)
mp.bar(x, -y2, ec='white', fc='dodgerblue', alpha=0.5, label='Sample 2') # 柱状
for _x, _y in zip(x, y2):
mp.text(_x, -_y - 0.015, '%.2f' % _y, ha='center', va='top', size=8)
mp.legend()
mp.show()
8、等高线图
- 绘制等高线
mp.contour(x, y, z, 线数, colors=颜色, linewidths=线宽) - 等高线填充
mp.contourf(x, y, z, 线数, cmap=颜色映射)
import numpy as np
import matplotlib.pyplot as mp
n = 1000
x, y = np.meshgrid(np.linspace(-3, 3, n), np.linspace(-3, 3, n)) # 生成网格点座标矩阵 【linspace(等差列表)】
z = (1 - x / 2 + x ** 5 + y ** 3) * np.exp(-x ** 2 - y ** 2)
mp.figure('Contour', facecolor='lightgray')
mp.title('Contour', fontsize=20)
mp.xlabel('x', fontsize=14)
mp.ylabel('y', fontsize=14)
mp.tick_params(labelsize=10)
mp.grid(linestyle=':')
mp.contourf(x, y, z, 8, cmap='jet') # 等高线填充
cntr = mp.contour(x, y, z, 8, colors='black', linewidths=0.5) # 绘制等高线
mp.clabel(cntr, inline_spacing=1, fmt='%.1f', fontsize=10) # 标注等高线
mp.show()
9、热像图
mp.imshow(矩阵, cmap=颜色映射,origin=垂直轴方向)
import numpy as np
import matplotlib.pyplot as mp
n = 1000
x, y = np.meshgrid(np.linspace(-3, 3, n), np.linspace(-3, 3, n)) # 生成网格点座标矩阵 【linspace(等差列表)】
z = (1 - x / 2 + x ** 5 + y ** 3) * np.exp(-x ** 2 - y ** 2)
mp.figure('Hot', facecolor='lightgray')
mp.title('Hot', fontsize=20)
mp.xlabel('x', fontsize=14)
mp.ylabel('y', fontsize=14)
mp.tick_params(labelsize=10)
mp.grid(linestyle=':')
mp.imshow(z, cmap='jet', origin='low') # 热像图
mp.show()
10、饼图
mp.pie(值列表, 间隙列表, 标签, 颜色列表, 格式串,shadow=是否带阴影, startangle=起始角度)
import matplotlib.pyplot as mp
mp.figure('Pie', facecolor='lightgray')
mp.title('Pie', fontsize=20)
mp.pie(
[26, 17, 21, 29, 11], # 值列表
[0.05, 0.01, 0.01, 0.01, 0.01], # 间隙列表
['Python', 'JavaScript', 'C++', 'C', 'PHP'], # 标签
['dodgerblue', 'orangered', 'limegreen', 'violet', 'gold'], # 颜色列表
'%d%%', shadow=True, startangle=90) # 格式串,shadow=是否带阴影, startangle=起始角度
mp.axis('equal') # 设置x,y轴相等
mp.show()
11、三维曲面
from mpl_toolkits.mplot3d import axes3d
ax = mp.gca(projection=‘3d’)
ax.plot_surface(x, y, z, rstride=行距,cstride=列距, cmap=颜色映射)
ax.plot_wireframe(x, y, z, rstride=行距,cstride=列距, linewidth=线宽, color=颜色)
import numpy as np
import matplotlib.pyplot as mp
from mpl_toolkits.mplot3d import axes3d
n = 1000
x, y = np.meshgrid(np.linspace(-3, 3, n), np.linspace(-3, 3, n))
z = (1 - x / 2 + x ** 5 + y ** 3) * np.exp(-x ** 2 - y ** 2)
mp.figure('3D Wireframe')
ax = mp.gca(projection='3d')
mp.title('3D Wireframe', fontsize=20, y=1.2) # 标题:y 修改位置
ax.set_xlabel('x', fontsize=14)
ax.set_ylabel('y', fontsize=14)
ax.set_zlabel('z', fontsize=14)
mp.tick_params(labelsize=10)
ax.plot_wireframe(x, y, z, rstride=30,
cstride=30, linewidth=0.5,
color='orangered') # 线曲面
mp.show()
import numpy as np
import matplotlib.pyplot as mp
from mpl_toolkits.mplot3d import axes3d
n = 1000
x, y = np.meshgrid(np.linspace(-3, 3, n), np.linspace(-3, 3, n))
z = (1 - x / 2 + x ** 5 + y ** 3) * np.exp(-x ** 2 - y ** 2)
mp.figure('3D Surface')
ax = mp.gca(projection='3d')
mp.title('3D Surface', fontsize=20, y=1.2) # 标题:y 修改位置
ax.set_xlabel('x', fontsize=14)
ax.set_ylabel('y', fontsize=14)
ax.set_zlabel('z', fontsize=14)
mp.tick_params(labelsize=10)
ax.plot_surface(x, y, z, rstride=30,
cstride=30, cmap='jet') # 面曲面
mp.show()
12、三维散点
ax.scatter(x, y, z, s=大小, c=颜色, marker=点型)
import numpy as np
import matplotlib.pyplot as mp
from mpl_toolkits.mplot3d import axes3d
n = 1000
x = np.random.normal(0, 1, n)
y = np.random.normal(0, 1, n)
z = np.random.normal(0, 1, n)
d = np.sqrt(x ** 2 + y ** 2 + z ** 2)
mp.figure('Scatter3D')
ax = mp.gca(projection='3d')
mp.title('Scatter3D', fontsize=20, y=1.1)
ax.set_xlabel('x', fontsize=14)
ax.set_ylabel('y', fontsize=14)
ax.set_zlabel('z', fontsize=14)
mp.tick_params(labelsize=10)
ax.scatter(x, y, z, s=60, c=d, cmap='jet_r', alpha=0.5, marker='o') # 描点
mp.show()
13、极座标系
mp.gca(projection=‘polar’)
mp.plot …
mp.scatter …
x, y
| |
v v
极角 极径
import numpy as np
import matplotlib.pyplot as mp
t = np.linspace(0, 2 * np.pi, 1001)
r_spiral = 0.8 * t
r_rose = 5 * np.sin(6 * t)
mp.figure('Polar', facecolor='lightgray')
mp.gca(projection='polar')
mp.title('Polar', fontsize=20, y=1.1)
mp.xlabel(r'$\theta$', fontsize=14)
mp.ylabel(r'$\rho$', fontsize=14, y=0.6)
mp.tick_params(labelsize=10)
mp.grid(linestyle=':')
mp.plot(t, r_spiral, c='dodgerblue', label=r'$\rho=0.8\theta$')
mp.plot(t, r_rose, c='orangered', label=r'$\rho=5sin(6\theta)$')
mp.legend()
mp.show()
14、半对数座标
mp.semilogy(…)
import numpy as np
import matplotlib.pyplot as mp
y = np.array([1, 10, 100, 1000, 100, 10, 1])
mp.figure('Normal & Log', facecolor='lightgray')
mp.subplot(211)
mp.title('Normal', fontsize=16)
mp.ylabel('y', fontsize=12)
ax = mp.gca()
ax.xaxis.set_major_locator(mp.MultipleLocator(1))
ax.xaxis.set_minor_locator(mp.MultipleLocator(0.1))
ax.yaxis.set_major_locator(mp.MultipleLocator(250))
ax.yaxis.set_minor_locator(mp.MultipleLocator(50))
mp.tick_params(labelsize=10)
mp.grid(which='major', axis='both',linewidth=0.75, linestyle='-',color='lightgray')
mp.grid(which='minor', axis='both',linewidth=0.25, linestyle='-',color='lightgray')
mp.plot(y, 'o-', c='dodgerblue', label='plot')
mp.legend()
mp.subplot(212)
mp.title('Log', fontsize=16)
mp.xlabel('x', fontsize=12)
mp.ylabel('y', fontsize=12)
ax = mp.gca()
ax.xaxis.set_major_locator(mp.MultipleLocator(1))
ax.xaxis.set_minor_locator(mp.MultipleLocator(0.1))
mp.tick_params(labelsize=10)
mp.grid(which='major', axis='both',linewidth=0.75, linestyle='-',color='lightgray')
mp.grid(which='minor', axis='both',linewidth=0.25, linestyle='-',color='lightgray')
mp.semilogy(y, 'o-', c='orangered',label='semilog') # 半对数
mp.legend()
mp.tight_layout()
mp.show()
15、简单动画
import numpy as np
import matplotlib.pyplot as mp
import matplotlib.animation as ma
n_bubbles = 100
bubbles = np.zeros(n_bubbles, dtype=[('position', float, 2),('size', float, 1),('growth', float, 1),('color', float, 4)]) # 初始化 100个点
bubbles['position'] = np.random.uniform(0, 1, (n_bubbles, 2)) # 均匀分布 位置:2个数值
bubbles['size'] = np.random.uniform(50, 750, n_bubbles) # 均匀分布 大小:1个数值
bubbles['growth'] = np.random.uniform(30, 150, n_bubbles) # 均匀分布 成长速度:1个数值
bubbles['color'] = np.random.uniform(0, 1, (n_bubbles, 4)) # 均匀分布 颜色:4个数值
mp.figure('Bubbles', facecolor='lightgray')
mp.title('Bubbles', fontsize=20)
mp.xticks(())
mp.yticks(())
sc = mp.scatter(bubbles['position'][:, 0],bubbles['position'][:, 1],s=bubbles['size'],c=bubbles['color']) # 描点:位置,大小,颜色
def update(number):
bubbles['size'] += bubbles['growth']
burst = number % n_bubbles
bubbles['position'][burst] = np.random.uniform(0, 1, 2)
bubbles['size'][burst] = 0
bubbles['growth'][burst] = np.random.uniform(30, 150)
bubbles['color'][burst] = np.random.uniform(0, 1, 4)
sc.set_offsets(bubbles['position'])
sc.set_sizes(bubbles['size'])
sc.set_facecolor(bubbles['color'])
anim = ma.FuncAnimation(mp.gcf(), update, interval=10)
mp.show()
import numpy as np
import matplotlib.pyplot as mp
import matplotlib.animation as ma
mp.figure('Signal', facecolor='lightgray')
mp.title('Signal', fontsize=20)
mp.xlabel('Time', fontsize=14)
mp.ylabel('Signal', fontsize=14)
ax = mp.gca()
ax.set_ylim(-3, 3)
ax.set_xlim(0, 10)
mp.tick_params(labelsize=10)
mp.grid(linestyle=':')
pl = mp.plot([], [], c='orangered')[0]
pl.set_data([], [])
def update(data):
t, v = data
x, y = pl.get_data()
x.append(t)
y.append(v)
x_min, x_max = ax.get_xlim()
if t >= x_max:
ax.set_xlim(t - (x_max - x_min), t)
ax.figure.canvas.draw()
pl.set_data(x, y)
def generator():
t = 0
while True:
v = np.sin(2 * np.pi * t) * np.exp(np.sin(0.2 * np.pi * t))
yield t, v
t += 0.05
anim = ma.FuncAnimation(mp.gcf(), update, generator, interval=5)
mp.show()
附录1:format_string
format_string:控制曲线的格式字符串,可选(由颜色字符、风格字符和标记字符组成),参见附录1 ↩︎