Python數據分析與展示實例

一、利用numpy庫，創建兩個數組A、B，兩個數組的shape均為4*5，數組A的元素為,數組B的元素為。編程實現以下功能：

1）輸出A+B 、B-A、A*B、A/B的結果；

2）對數組A的中間兩行的元素進行求和，並輸出。

import numpy as np
arrayA = np.array([[0,1,2,3,4],
                   [5,6,7,8,9],
                   [10,11,12,13,14],
                   [15,16,17,18,19]])

arrayB = np.array([[100,101,102,103,104],
                   [105,106,107,108,109],
                   [110,111,112,113,114],
                   [115,116,117,118,119]])
print(arrayA + arrayB)
print(arrayA * arrayB)
print(arrayB - arrayA)
print(arrayA / arrayB)
print(sum(arrayA[1,:])+sum(arrayA[2,:]))

二、“雞兔同籠”問題：今有雞兔同籠，上有三十五頭，下有九十四足。問雞兔各多少？，請利用numpy庫的linalg模塊編程實現。

import numpy as np

heads , foots = 35, 94
A = np.array([[1,1],[2,4]]) #方程組的系數
B = np.array([heads,foots]) #方程組右側的常數矩陣
X = np.linalg.solve(A,B)
print(X)
print("雞為：{}只, 兔為: {}只".format(X[0],X[1]))

三、參考教材閱讀並運行“阻尼衰減曲線坐標圖”繪制代碼，理解編寫科學坐標系的方法，繪制如下圖所示阻尼衰減曲線圖：

import numpy as np
import matplotlib.pyplot as plt
import matplotlib
matplotlib.rcParams['font.family']='SimHei'
matplotlib.rcParams['font.sans-serif']=['SimHei']
def Draw(pcolor, nt_point,nt_text,nt_size):
    plt.plot(x,y,'k',label="$exp_decay$",color=pcolor,linewidth=3,linestyle="-")
    plt.plot(x,z,"b--",label="$cos(x^2)$",linewidth=1)
    plt.xlabel('時間(s)')
    plt.ylabel('幅度(mV)')
    plt.title('阻尼衰減曲線繪制')
    plt.annotate('$\cos(2 \pi t) \exp(-t)$',xy=nt_point, xytext=nt_text,fontsize=nt_size,arrowprops=dict(arrowstyle='->',connectionstyle="arc3,rad=.1"))

def Shadow(a,b):
    ix = (x>a) & (x<b)
    plt.fill_between(x,y,0,where=ix,facecolor='grey',alpha=0.25)
    plt.text(0.5 * (a + b),0.2,r"$\int_a^b f(x)\mathrm{d}x$",horizontalalignment='center')

def XY_Axis(x_start,x_end,y_start,y_end):
    plt.xlim(x_start,x_end)
    plt.ylim(y_start,y_end)
    plt.xticks([np.pi/3,2*np.pi/3,1*np.pi,4*np.pi/3,5*np.pi/3],['$\pi/3$','$2\pi/3$','$\pi$','$4\pi/3$','$5\pi/3$'])

x=np.linspace(0.0,6.0,100)
y=np.cos(2*np.pi*x)*np.exp(-x)+0.8
z=0.5*np.cos(x**2)+0.8
note_point,note_text,note_size=(1,np.cos(2*np.pi)*np.exp(-1)+0.8),(1,1.4),14
fig=plt.figure(figsize=(8,6),facecolor="white")
plt.subplot(111)
Draw("red",note_point,note_text,note_size)
XY_Axis(0,5,0,1.8)
Shadow(0.8,3)
plt.legend()
plt.savefig('sample.JPG')
plt.show()