title: "Linear algebra" date: 2026-05-24T13:51:49Z Linear algebra 1import numpy as np 1np.version '1.11.2' Matrix and vector products Q1. Predict the results of the following code. 1x = [1,2] 2y = [[4, 1], [2, 2]] 3#print np.dot(x, y) 4#print np.dot(y, x) 5#print np.matmul(x, y) 6#print np.inner(x, y) 7#print …

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title: "Linear algebra" date: 2026-05-24T13:51:52Z Linear algebra 1import numpy as np 1np.version '1.11.2' Matrix and vector products Q1. Predict the results of the following code. 1x = [1,2] 2y = [[4, 1], [2, 2]] 3print np.dot(x, y) 4print np.dot(y, x) 5print np.matmul(x, y) 6print np.inner(x, y) 7print …

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title: "设计一个带通滤波器：" date: 2026-05-24T14:11:17Z 1import pylab as pl 2import numpy as np 3from scipy import signal 1import matplotlib as mpl 2mpl.rcParams['font.sans-serif'] = ['SimHei'] 信号处理-signal 中值滤波 1#%fig=使用中值滤波剔除瞬间噪声 2t = np.arange(0, 20, 0.1) 3x = np.sin(t) 4x[np.random.randint(0, len(t), 20)] += …

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title: "cf." date: 2026-05-24T13:51:55Z 1from future import print_function 2import numpy as np 3import matplotlib.pyplot as plt 4%matplotlib inline 1from datetime import date 2date.today() datetime.date(2017, 11, 2) 1author = "kyubyong. https://github.com/Kyubyong/numpy_exercises" 1np.version '1.13.1' Complex …

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title: "cf." date: 2026-05-24T13:51:58Z 1from future import print_function 2import numpy as np 3import matplotlib.pyplot as plt 4%matplotlib inline 1from datetime import date 2date.today() datetime.date(2017, 11, 2) 1author = "kyubyong. https://github.com/Kyubyong/numpy_exercises" 1np.version '1.13.1' Complex …

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title: "X-Y轴分为15*15的网格" date: 2026-05-24T14:11:20Z 1import numpy as np 2import pylab as pl 3from scipy import interpolate 1import matplotlib as mpl 2mpl.rcParams['font.sans-serif'] = ['SimHei'] 插值-interpolate 一维插值 WARNING 高次interp1d()插值的运算量很大，因此对于点数较多的数据，建议使用后面介绍的UnivariateSpline()。 1#%fig=interp1d的各阶插值 2from scipy …

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title: "Logic functions" date: 2026-05-24T13:52:01Z Logic functions 1import numpy as np 1np.version '1.11.2' Truth value testing Q1. Let x be an arbitrary array. Return True if none of the elements of x is zero. Remind that 0 evaluates to False in python. 1x = np.array([1,2,3]) 2# 3 4x = np.array([1,0,3]) 5# True …

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title: "Logic functions" date: 2026-05-24T13:52:03Z Logic functions 1import numpy as np 1np.version '1.11.2' Truth value testing Q1. Let x be an arbitrary array. Return True if none of the elements of x is zero. Remind that 0 evaluates to False in python. 1x = np.array([1,2,3]) 2print np.all(x) 3 4x = …

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title: "8.scipy-sparse" date: 2026-05-24T14:11:23Z 1%matplotlib inline 2import numpy as np 3import pylab as pl 4from scipy import sparse 5from scipy.sparse import csgraph 稀疏矩阵-sparse 稀疏矩阵的储存形式 1from scipy import sparse 2a = sparse.dok_matrix((10, 5)) 3 4a[2, 3] = 1.0 5a[3, 3] = 2.0 6a[4, 3] = 3.0 7print(a.keys()) …

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title: "Mathematical functions" date: 2026-05-24T13:52:06Z Mathematical functions 1import numpy as np 1np.version '1.11.2' 1__author__ = "kyubyong. kbpark.linguist@gmail.com. https://github.com/kyubyong" Trigonometric functions Q1. Calculate sine, cosine, and tangent of x, element-wise. 1x = np.array([0., 1., 30, …

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