matplotlib.pyplot.plot()參數(shù)使用詳解

更新時間：2020年07月28日 11:14:25 作者：ims-

這篇文章主要介紹了matplotlib.pyplot.plot()參數(shù)詳解，文中通過示例代碼介紹的非常詳細(xì)，對大家的學(xué)習(xí)或者工作具有一定的參考學(xué)習(xí)價值，需要的朋友們下面隨著小編來一起學(xué)習(xí)學(xué)習(xí)吧

在交互環(huán)境中查看幫助文檔：

import matplotlib.pyplot as plt
help(plt.plot)

以下是對幫助文檔重要部分的翻譯：

plot函數(shù)的一般的調(diào)用形式：

#單條線：
plot([x], y, [fmt], data=None, **kwargs)
#多條線一起畫
plot([x], y, [fmt], [x2], y2, [fmt2], ..., **kwargs)

可選參數(shù)[fmt] 是一個字符串來定義圖的基本屬性如：顏色（color），點(diǎn)型（marker），線型（linestyle），

具體形式 fmt = '[color][marker][line]'

fmt接收的是每個屬性的單個字母縮寫，例如：

plot(x, y, 'bo-') # 藍(lán)色圓點(diǎn)實線

若屬性用的是全名則不能用*fmt*參數(shù)來組合賦值，應(yīng)該用關(guān)鍵字參數(shù)對單個屬性賦值如：

plot(x,y2,color='green', marker='o', linestyle='dashed', linewidth=1, markersize=6)

plot(x,y3,color='#900302',marker='+',linestyle='-')

常見的顏色參數(shù)：**Colors**

也可以對關(guān)鍵字參數(shù)color賦十六進(jìn)制的RGB字符串如 color='#900302'

 ============= ===============================
 character  color
 ============= ===============================
 ``'b'``   blue 藍(lán)
 ``'g'``   green 綠
 ``'r'``   red 紅
 ``'c'``   cyan 藍(lán)綠
 ``'m'``   magenta 洋紅
 ``'y'``   yellow 黃
 ``'k'``   black 黑
 ``'w'``   white 白
 ============= ===============================

點(diǎn)型參數(shù)**Markers**,如：marker='+' 這個只有簡寫，英文描述不被識別

============= ===============================
 character  description
 ============= ===============================
 ``'.'``   point marker
 ``','``   pixel marker
 ``'o'``   circle marker
 ``'v'``   triangle_down marker
 ``'^'``   triangle_up marker
 ``'<'``   triangle_left marker
 ``'>'``   triangle_right marker
 ``'1'``   tri_down marker
 ``'2'``   tri_up marker
 ``'3'``   tri_left marker
 ``'4'``   tri_right marker
 ``'s'``   square marker
 ``'p'``   pentagon marker
 ``'*'``   star marker
 ``'h'``   hexagon1 marker
 ``'H'``   hexagon2 marker
 ``'+'``   plus marker
 ``'x'``   x marker
 ``'D'``   diamond marker
 ``'d'``   thin_diamond marker
 ``'|'``   vline marker
 ``'_'``   hline marker
 ============= ===============================

線型參數(shù)**Line Styles**，linestyle='-'

 ============= ===============================
 character  description
 ============= ===============================
 ``'-'``   solid line style 實線
 ``'--'``   dashed line style 虛線
 ``'-.'``   dash-dot line style 點(diǎn)畫線
 ``':'``   dotted line style 點(diǎn)線
 ============= ===============================

樣例1

函數(shù)原型：matplotlib.pyplot.plot(*args, scalex=True, scaley=True, data=None, **kwargs)

>>> plot('xlabel', 'ylabel', data=obj)

解釋：All indexable objects are supported. This could e.g. be a dict, a pandas.DataFame or a structured numpy array.

data 參數(shù)接受一個對象數(shù)據(jù)類型，所有可被索引的對象都支持，如 dict 等

import matplotlib.pyplot as plt 
import numpy as np
'''read file 
fin=open("para.txt")
a=[]
for i in fin:
 a.append(float(i.strip()))
a=np.array(a)
a=a.reshape(9,3)
'''
a=np.random.random((9,3))*2 #隨機(jī)生成y
 
y1=a[0:,0]
y2=a[0:,1]
y3=a[0:,2]
 
x=np.arange(1,10)
 
ax = plt.subplot(111)
width=10
hight=3
ax.arrow(0,0,0,hight,width=0.01,head_width=0.1, head_length=0.3,length_includes_head=True,fc='k',ec='k')
ax.arrow(0,0,width,0,width=0.01,head_width=0.1, head_length=0.3,length_includes_head=True,fc='k',ec='k')
 
ax.axes.set_xlim(-0.5,width+0.2)
ax.axes.set_ylim(-0.5,hight+0.2)
 
plotdict = { 'dx': x, 'dy': y1 }
ax.plot('dx','dy','bD-',data=plotdict)
 
ax.plot(x,y2,'r^-')
ax.plot(x,y3,color='#900302',marker='*',linestyle='-')
 
plt.show()

樣例2，

import matplotlib.pyplot as plt 
import numpy as np 
 
x = np.arange(0, 2*np.pi, 0.02) 
y = np.sin(x) 
y1 = np.sin(2*x) 
y2 = np.sin(3*x) 
ym1 = np.ma.masked_where(y1 > 0.5, y1) 
ym2 = np.ma.masked_where(y2 < -0.5, y2) 
 
lines = plt.plot(x, y, x, ym1, x, ym2, 'o') 
#設(shè)置線的屬性
plt.setp(lines[0], linewidth=1) 
plt.setp(lines[1], linewidth=2) 
plt.setp(lines[2], linestyle='-',marker='^',markersize=4) 
#線的標(biāo)簽
plt.legend(('No mask', 'Masked if > 0.5', 'Masked if < -0.5'), loc='upper right') 
plt.title('Masked line demo') 
plt.show()

例3 ：圓

import numpy as np
import matplotlib.pyplot as plt
 
theta = np.arange(0, 2*np.pi, 0.01)
xx = [1,2,3,10,15,8]
yy = [1,-1,0,0,7,0]
rr = [7,7,3,6,9,9]
 
fig = plt.figure()
axes = flg.add_subplot(111)
 
i = 0
while i < len(xx):
 x = xx[i] + rr[i] *np.cos(theta)
 x = xx[i] + rr[i] *np.cos(theta)
 axes.plot(x,y)
 axes.plot(xx[i], yy[i], color='#900302', marker='*')
  i = i+1
width = 20
hight = 20
axes.arrow(0,0,0,hight,width=0.01,head_width=0.1,head_length=0.3,fc='k',ec='k')
axes.arrow(0,0,width,0,width=0.01,head_width=0.1,head_length=0.3,fc='k',ec='k')
plt.show()

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