1.1 颜色¶
b---blue c---cyan(青色) g---green k----black
m---magenta(洋红) r---red w---white y----yellow1.3 标记¶
. Point marker
, Pixel marker
o Circle marker
v Triangle down marker
^ Triangle up marker
< Triangle left marker
> Triangle right marker
1 Tripod down marker
2 Tripod up marker
3 Tripod left marker
4 Tripod right marker
s Square marker
p Pentagon marker
* Star marker
h Hexagon marker
H Rotated hexagon
D Diamond marker
d Thin diamond marker
| Vertical line (vlinesymbol) marker
_ Horizontal line (hline symbol) marker
+ Plus marker
x Cross (x) markerIn [1]:
import numpy as np
import matplotlib.pyplot as plt
x = np.arange(0,np.pi*2, np.pi*2/10)
y = np.sin(x)
fig, ax = plt.subplots()
ax.plot(x,y,ls='dotted',color='r',lw=1.5,marker='>',markerfacecolor='None',markersize=15)
# markerfacecolor 可以设置marker的填充颜色，None为不填充
plt.show()
# 在 jupyter notebook 中有两种显示图片的方式：fig 或 plt.show()，两者效果相同
# 在 terminal 中 对应两种为 fig.show() 和 plt.show()
# 在 terminal 中 fig.show() 不会中止程序，而 plt.show() 会中止程序，直到你关闭图像窗口才继续运行
In [2]:
# 颜色、标记、连线 可以简化成一个字符串，例如：'go-.'
import numpy as np
import matplotlib.pyplot as plt
x = np.arange(0,np.pi*2, np.pi*2/10)
y = np.cos(x)
fig, ax = plt.subplots()
ax.plot(x,y,'go-.',lw=1.5,markerfacecolor='None',markersize=15)
plt.show()
1.4 图例¶
In [3]:
import numpy as np
import matplotlib.pyplot as plt
# Make some fake data.
a = b = np.arange(0, 3, .02)
c = np.exp(a)
d = c[::-1]
# Create plots with pre-defined labels.
fig, ax = plt.subplots()
ax.plot(a, c, 'k--', label='Model length')
ax.plot(a, d, 'k:', label='Data length')
ax.plot(a, c + d, 'k', label='Total message length')
legend = ax.legend(loc='best', shadow=True, fontsize='x-large')
# loc: best
# upper left | upper center | upper right
# lower left |lower center | lower right
# center left | center | center right
# Put a nicer background color on the legend.
# legend.get_frame().set_facecolor('#00FFCC')
legend.get_frame().set_facecolor('cyan')
plt.show()
In [4]:
import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.add_subplot(111)
ax.set_xlim([0,20]) # 坐标轴范围
ax.set_ylim([0,10])
ax.set_aspect('equal') # 坐标比例 也可以是 'auto'
# ax.set_aspect(2) # 纵坐标比横坐标
ax.set_xticks(range(0,21,2)) # 设置刻度
ax.set_yticks(range(11))
ax.grid() # 绘制网格
plt.show()
3. 文字设置¶
In [5]:
import matplotlib.pyplot as plt
fig = plt.figure()
fig.suptitle('bold figure suptitle', fontsize=14, fontweight='bold')
ax = fig.add_subplot(111)
fig.subplots_adjust(top=0.85) # 控制子图占画布的比例，在 notebook 中运行不明显
# 例如：fig.subplots_adjust(left=0.08, bottom=0.35, right=0.97, top=0.75, wspace=0.25, hspace=0.25)
# 表示：子图左侧到画布的 0.08，底部到画布的 0.35 的位置，右侧到画布的 0.97，顶部到画布的 0.75，横向子图距离0.25，纵向子图距离0.25
ax.set_title('axes title') # 子图的名称
ax.set_xlabel('xlabel', fontsize=15, color='green') # 坐标轴的名称
ax.set_ylabel('ylabel')
ax.text(3, 8, 'boxed italics text in data coords', style='italic',
bbox={'facecolor':'red', 'alpha':0.5, 'pad':10})
ax.text(2, 6, r'an equation: $E=mc^2$', fontsize=15) # 纯字符串，里面的反斜杠不代表转义
ax.text(3, 2, u'unicode: Institut f\374r Festk\366rperphysik') # unicode
ax.text(0.95, 0.01, 'colored text in axes coords',
verticalalignment='bottom', horizontalalignment='right',
transform=ax.transAxes,
color='green', fontsize=15)
ax.plot([2], [1], 'o')
ax.annotate('annotate', xy=(2, 1), xytext=(3, 4),
arrowprops=dict(facecolor='black', shrink=0.05))
ax.axis([0, 10, 0, 10])
ax.set_xticks(range(11))
plt.show()
In [6]:
import matplotlib.pyplot as plt
import numpy as np
x = np.arange(0,2,0.005)
y = np.exp(x)
fig, axs = plt.subplots(2,3,figsize=(15,10),dpi=90)
# 2 行 3 列，前两个参数缺省时代表没有子图
# figsize 单位是英寸，参数顺序为：宽、高 如果想生成特定像素的图片，则需要设定 dpi(dots per inch)，通常 100 左右就很清晰了
# axs.shape: (2,3)
for i in range(6):
axs[i/3,i%3].plot(x, np.sin((i+1)*10*x)*y)
plt.show()
4.2 add_subplot¶
这种方法步骤最清晰，可以看到是先建立 figure 实例，再逐一添加 axis 实例。
In [7]:
import matplotlib.pyplot as plt
import numpy as np
x = np.arange(0,2,0.005)
y = np.exp(x)
fig = plt.figure(figsize=(15,10),dpi=90)
for i in range(6):
ax = fig.add_subplot(2,3,i+1)
ax.plot(x, np.sin((i+1)*10*x)*y)
fig
Out[7]:
4.3 subplot¶
这种方法最不规范，完全体现不出建立 figure 和 axis 实例的过程，但是最简洁。PS，没有找到这种方法如何设置画布参数。
In [8]:
import matplotlib.pyplot as plt
import numpy as np
x = np.arange(0,2,0.005)
y = np.exp(x)
for i in range(6):
plt.subplot(2,3,i+1)
plt.plot(x, np.sin((i+1)*10*x)*y)
plt.show()
In [9]:
import matplotlib.pyplot as plt
from matplotlib.patches import Ellipse
#fig = plt.figure()
#ax = fig.add_subplot(111)
fig, ax = plt.subplots()
ellipse = Ellipse(xy=(10,5),width=20,height=10,angle=30,edgecolor='r',fc='green',lw=2, ls='dashed')
# angle 是椭圆逆时针旋转的角度 单位是度
# fc facecolor，设置成 None 表示没有颜色，也可以设置 fill=False
# ls 或 linestyle：
# [‘solid’ | ‘dashed’, ‘dashdot’, ‘dotted’ | '-' | '--' | '-.' | ':']
ax.add_patch(ellipse)
ax.set_aspect('equal')
#ax.autoscale()
ax.set_ylim([0,10])
ax.set_xlim([0,20])
#fig.tight_layout()
ax.set_xticks(range(0,21))
ax.set_yticks(range(0,11))
#plt.xticks(range(0,21)) # 考虑到多个子图的情况，尽量不通过 plt 设置图形特征
#plt.yticks(range(0,11))
plt.grid()
plt.draw()
plt.show()
5.2 矩形¶
In [10]:
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
fig, ax = plt.subplots()
rect = Rectangle((2,1),3,4, edgecolor='g', fc='None', lw=2)
# 参数依次是 左下角坐标，宽度，高度
ax.add_patch(rect)
ax.set_aspect('equal')
ax.set_xlim([0,10])
ax.set_xticks(range(11))
ax.set_ylim([0,10])
ax.set_yticks(range(11))
ax.grid()
plt.draw()
plt.show()
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