【python】第二十次课作业

exercises

matplotlib

11.1

题目：

源代码：

<span style="font-size:16px;">import numpy as np</span>
<span style="font-size:16px;">import matplotlib.pyplot as plt</span>
<span style="font-size:16px;">import math</span>
<span style="font-size:16px;"></span>
<span style="font-size:16px;">x = np.linspace(0, 2)</span>
<span style="font-size:16px;">y = [(math.sin(i-2) ** 2) * math.exp(-(i**2)) for i in x]</span>
<span style="font-size:16px;">plt.plot(x, y)</span>
<span style="font-size:16px;">plt.xlabel('x')</span>
<span style="font-size:16px;">plt.ylabel('y')</span>
<span style="font-size:16px;">plt.title("f(x) = sin^2(x-2) * exp( -(x**2) )")</span>
<span style="font-size:16px;">plt.show()
</span>

运行结果：

11.2

题目：

源代码：

import numpy as np
from scipy.optimize import leastsq
import matplotlib.pyplot as plt

a = np.random.randint(1, 10, size = (10, 1))
b = np.random.normal(size = (20,1))
XXX = np.random.randint(1, 10, size = (20, 10))
c = np.dot(XXX, a) + b
def least(XXX, c):
    fir = np.dot(XXX.T, XXX)
    sec = np.dot(XXX.T, c)
    ans = np.linalg.solve(fir, sec)
    return ans
l = least(XXX, c)
print(l)
index = np.linspace(1, 10, 10)
plt.scatter(index, a, color="red", marker = 'x', label = "True coefficients", linewidth = 3)
plt.scatter(index, l, color="blue", marker = 'o', label = "Estimated coefficients", linewidth = 3)
plt.legend()
plt.show()

运行结果：

11.3

题目：

源代码：

import scipy as sp
from scipy import stats
import matplotlib.pyplot as plt
import numpy as np
 
x = np.linspace(-5, 15, 50)
plt.plot(x, sp.stats.norm.pdf(x=x, loc=5, scale=2))
plt.hist(sp.stats.norm.rvs(loc=5, scale=2, size=10000), bins=25, density =True, color='green', alpha=0.5)
plt.show()

运行结果：