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python折线图绘制——记录
小編覺得挺不錯的,現(xiàn)在分享給大家,幫大家做個參考.
最近忙著文章出圖,大家都習慣于Excel或者Dplot等等出圖,這些工具對于幾張圖瞬間能搞定的,使用使用倒是很方便,但是我現(xiàn)在遇到了多種工況,還要出很多,所以不得不借助于python實現(xiàn)一鍵操作。不多說,直接先看下出來的結果圖,后面附上代碼,方便大家以及自己后面copy,我覺得應該基本上可以滿足大部分要求了。
記得也查了不少CSDN的博客和知乎上的一些內(nèi)容,也直接引用了他們的一些代碼,已經(jīng)不記得有哪些了,在此表示感謝,如果有侵權,請告知!也歡迎大家留言討論。
import numpy
as np
import matplotlib
.pyplot
as plt
from collections
import OrderedDict
from matplotlib
.pyplot
import MultipleLocatorplt
.rcParams
['font.sans-serif']=['Times New Roman']
plt
.rcParams
['axes.unicode_minus']=False
plt
.rcParams
['savefig.dpi'] = 200
def readData(path
):rname
=path
+r'\1.txt'sname
=path
+r'\2.txt'rlist
= np
.loadtxt
(roundname
,dtype
=np
.float)slist
= np
.loadtxt
(scourname
,dtype
=np
.float)return rlist
,slist
def plot(clist
,slist
,name
):lineStylesDict
= OrderedDict
([('solid', (0, ())),('loosely dotted', (0, (1, 10))),('dotted', (0, (1, 5))),('densely dotted', (0, (1, 1))),('loosely dashed', (0, (5, 10))),('dashed', (0, (5, 5))),('densely dashed', (0, (5, 1))),('loosely dashdotted', (0, (3, 10, 1, 10))),('dashdotted', (0, (3, 5, 1, 5))),('densely dashdotted', (0, (3, 1, 1, 1))),('loosely dashdotdotted', (0, (3, 10, 1, 10, 1, 10))),('dashdotdotted', (0, (3, 5, 1, 5, 1, 5))),('densely dashdotdotted', (0, (3, 1, 1, 1, 1, 1)))])font1
= {'family': 'Times New Roman','weight': 'bold','style':'italic','size': 26,}plt
.figure
(figsize
=(18,4))plt
.subplot
(111)plt
.subplots_adjust
(left
=0.05,bottom
=0.2,right
=0.90,top
=0.95)
plt
.plot
(clist
[:,0],clist
[:,1],linewidth
=2.0,color
='black')plt
.plot
(clist
[:,2],clist
[:,3],linewidth
=2.0,color
='black')plt
.plot
(clist
[:,4],clist
[:,5],linewidth
=2.0,color
='black')plt
.plot
(clist
[:,6],clist
[:,7],linewidth
=2.0,color
='black')
plt
.plot
(slist
[:,0],slist
[:,2],linewidth
=2.0,color
='black',linestyle
='--',label
='1')plt
.plot
(slist
[:,0],slist
[:,3],linewidth
=2.0,color
='black',linestyle
=linestyles_dict
['dashdotted'],label
='2')plt
.plot
(slist
[:,0],slist
[:,4],linewidth
=2.0,color
='black',linestyle
='-.',label
='3')plt
.plot
(slist
[:,0],slist
[:,5],linewidth
=2.0,color
='black',linestyle
=lineStylesDict
['densely dashdotdotted'],label
='4')plt
.scatter
(slist
[:,0],slist
[:,7],50,linewidths
=1.0,alpha
=1,color
='black',marker
='^',label
='5')plt
.axis
('scaled') plt
.xticks
(fontsize
=24) plt
.yticks
(fontsize
=24)xlocator
=MultipleLocator
(1)ax
=plt
.gca
()ax
.xaxis
.set_major_locator
(xlocator
)plt
.xlim
((-2,10))plt
.ylim
((-1.0,1.5))plt
.ylabel
("y/D",font1
)plt
.xlabel
("x/D",font1
)ax
.spines
['bottom'].set_linewidth
(2)ax
.spines
['left'].set_linewidth
(2)ax
.spines
['right'].set_linewidth
(2)ax
.spines
['top'].set_linewidth
(2)plt
.legend
(fontsize
=21, loc
='best',frameon
=False,handletextpad
=0.1,labelspacing
=0.1)plt
.savefig
(name
+".tiff")def start():path
=r'I:\sensibility_analysis\0.5D'figname
=path
[-4:]rlist
,slist
=readData
(path
)plot
(rlist
,slist
,figname
)if __name__
=='__main__':start
()
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