正在學習python編程，把一些小技巧記錄下來備查

======================計算技巧==========================

正常的條件語句如下if a>b:c=aelse:c=b

可以寫為以下簡潔的語句a=100b=200c=a if a>b else bprint(c)

======================作圖==========================

python中可以使用numpy的array來高效處理數組

下面主要列舉matplotlib的基本使用方法，以供查找

first plot

#first plot with matplotlib

import matplotlib.pyplot as plt

plt.plot([1,3,2,4])

plt.show()

in order to avoid pollution of global namespace, it is strongly recommended to never import like:

from import *

simple plot

import matplotlib as mpl

import matplotlib.pyplot as plt

import numpy as np

x = np.arange(0.0,6.0,0.1)

plt.plot(x, [xi**2 for xi in x],label = 'First',linewidth = 4,color = 'black')

plt.plot(x, [xi**2+2 for xi in x],label = 'second',color = 'red')

plt.plot(x, [xi**2+5 for xi in x],label = 'third')

plt.axis([0,7,-1,50])

plt.xlabel(r"$\alpha$",fontsize=20)

plt.ylabel(r'y')

plt.title('simple plot')

plt.legend(loc = 'upper left')

plt.grid(True)

plt.savefig('simple plot.pdf',dpi = 200)

print mpl.rcParams['figure.figsize'] #return 8.0,6.0

print mpl.rcParams['savefig.dpi'] #default to 100 the size of the pic will be 800*600

#print mpl.rcParams['interactive']

plt.show()

Python-3

Decorate plot with styles and types

import matplotlib as mpl

import matplotlib.pyplot as plt

import numpy as np

x = np.arange(0.0,6.0,0.1)

plt.plot(x, [xi**2 for xi in x],label = 'First',linewidth = 4,color = 'black') #using color string to specify color

plt.plot(x, [xi**2+2 for xi in x],'r',label = 'second') #using abbreviation to specify color

plt.plot(x, [xi**2+5 for xi in x],color = (1,0,1,1),label = 'Third') #using color tuple to specify color

plt.plot(x, [xi**2+9 for xi in x],color = '#BCD2EE',label = 'Fourth') #using hex string to specify color

plt.xticks(np.arange(0.0,6.0,2.5))

plt.xlabel(r"$\alpha$",fontsize=20)

plt.ylabel(r'y')

plt.title('simple plot')

plt.legend(loc = 'upper left')

plt.grid(True)

plt.savefig('simple plot.pdf',dpi = 200)

print mpl.rcParams['figure.figsize'] #return 8.0,6.0

print mpl.rcParams['savefig.dpi'] #default to 100 the size of the pic will be 800*600

#print mpl.rcParams['interactive']

plt.show()

image

types of graph

image

Bars

import matplotlib.pyplot as plt

import numpy as np

dict = {'A': 40, 'B': 70, 'C': 30, 'D': 85}

for i, key in enumerate(dict): plt.bar(i, dict[key]);

plt.xticks(np.arange(len(dict))+0.4, dict.keys());

plt.yticks(dict.values());

plt.grid(True)

plt.show()

image_1

Pies

import matplotlib.pyplot as plt

plt.figure(figsize=(10,10));

x = [4, 9, 21, 55, 30, 18]

labels = ['Swiss', 'Austria', 'Spain', 'Italy', 'France',

'Benelux']

explode = [0.2, 0.1, 0, 0, 0.1, 0]

plt.pie(x, labels=labels, explode=explode, autopct='%1.1f%%');

plt.show()

image_2

Scatter

import matplotlib.pyplot as plt

import numpy as np

x = np.random.randn(12,20)

y = np.random.randn(12,20)

mark = ['s','o','^','v','>','<','d','p','h','8','+','*']

for i in range(0,12):

plt.scatter(x[i],y[i],marker = mark[i],color =(np.random.rand(1,3)),s=50,label = str(i+1))

plt.legend()

plt.show()

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