6.23 warehouse operation on Thursday

6.23 Thursday warehouse operation

Numpy practice

Exercise one ： Create from 0 To 9 One dimensional array of numbers

import numpy as np

arr = np.arange(10)
print(arr)

Exercise 2 ： Create an element all for True Of 3×3 Array

import numpy as np

arr = np.full([3, 3], True, dtype=np.bool)
print(arr)

Practice three ： Create a 2D array , Where the boundary value is 1, The rest are 0

import numpy as np
Z = np.ones((10,10))
Z[1:-1,1:-1] = 0
print(Z)

Pandas practice

Exercise one ： Write matrix multiplication using list derivation

The general matrix multiplication is based on the formula , It can be written by a triple loop , Please rewrite it in the form of list derivation .

M1 = np.random.rand(2,3)
M2 = np.random.rand(3,4)
res = np.empty((M1.shape[0],M2.shape[1]))
for i in range(M1.shape[0]):
    for j in range(M2.shape[1]):
        item = 0
        for k in range(M1.shape[1]):
            item += M1[i][k] * M2[k][j]
        res[i][j] = item
(np.abs(([email protected] - res) < 1e-15)).all() #  Eliminate numerical errors 

The form of list derivation

import numpy as np
M1 = np.random.rand(2,3)
M2 = np.random.rand(3,4)
res = [[sum([M1[i][k] * M2[k][j] for k in range(M1.shape[1])]) for j in range(M2.shape[1])] for i in range(M1.shape[0])]
(np.abs(([email protected] - res) < 1e-15)).all()

Matplotlib practice

Exercise one ： Two drawing interfaces

matplotlib Provides two of the most commonly used drawing interfaces

1. Create explicitly figure and axes, Call the drawing method above , Also known as OO Pattern （object-oriented style)
2. rely on pyplot Automatically create figure and axes, And draw

Using the first drawing interface , That's true ：

x = np.linspace(0, 2, 100)

fig, ax = plt.subplots()
ax.plot(x, x, label='linear')
ax.plot(x, x**2, label='quadratic')
ax.plot(x, x**3, label='cubic')
ax.set_xlabel('x label')
ax.set_ylabel('y label')
ax.set_title("Simple Plot")
ax.legend()

The second drawing interface

x = np.linspace(0, 2, 100)

plt.plot(x, x, label='linear')
plt.plot(x, x**2, label='quadratic')
plt.plot(x, x**3, label='cubic')
plt.xlabel('x label')
plt.ylabel('y label')
plt.title("Simple Plot")
plt.legend()