293 lines
3.4 KiB
Markdown
293 lines
3.4 KiB
Markdown
# 原创
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: Numpy学习(一)——Numpy 简介
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# Numpy学习(一)——Numpy 简介
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# Numpy 简介
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## 导入numpy
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Numpy是Python的一个很重要的第三方库,很多其他科学计算的第三方库都是以Numpy为基础建立的。
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Numpy的一个重要特性是它的**数组计算**。
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```
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from numpy import *
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```
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以下几种导入方式都行
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```
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import numpy
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import numpy as np
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from numpy import *
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from numpy import array, sin
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```
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ipython中可以使用magic命令来快速导入Numpy的内容。
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```
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%pylab
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```
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```
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Using matplotlib backend: TkAgg
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Populating the interactive namespace from numpy and matplotlib
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```
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## 数组上的数学操作
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```
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a = [1, 2, 3, 4]
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a + 1 # 直接运行报错
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```
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```
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TypeErrorTraceback (most recent call last)
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<ipython-input-3-eb27785ac8c2> in <module>()
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1 a = [1, 2, 3, 4]
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----> 2 a + 1 # 直接运行报错
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TypeError: can only concatenate list (not "int") to list
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```
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```
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# 使用array数组
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a = array(a)
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a
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```
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```
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array([1, 2, 3, 4])
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```
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```
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a + 1
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```
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```
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array([2, 3, 4, 5])
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```
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```
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b = array([2, 3, 4, 5])
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a+b
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```
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```
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array([3, 5, 7, 9])
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```
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```
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a*b
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```
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```
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array([ 2, 6, 12, 20])
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```
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```
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a**b
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```
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```
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array([ 1, 8, 81, 1024])
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```
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## 提取数组中的元素
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```
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a[0]
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```
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```
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1
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```
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```
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a[:2]
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```
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```
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array([1, 2])
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```
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```
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a[-2:]
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```
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```
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array([3, 4])
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```
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```
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a[:2]+a[-2:]
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```
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```
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array([4, 6])
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```
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## 修改数组形状
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```
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# 查看array的形状
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a.shape
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```
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```
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(4,)
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```
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```
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# 修改array的形状
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a.shape = 2,2
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a
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```
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```
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array([[1, 2],
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[3, 4]])
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```
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## 多维数组
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```
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a
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```
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```
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array([[1, 2],
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[3, 4]])
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```
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```
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a+a
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```
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```
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array([[2, 4],
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[6, 8]])
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```
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```
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a*a
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```
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```
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array([[ 1, 4],
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[ 9, 16]])
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```
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## 画图
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**linspace** 用来生成一组等间隔的数据:
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```
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# precision该方法用来定义小数点后的位数
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a = linspace(0, 2*pi, 21)
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%precision 3
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a
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```
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```
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array([0. , 0.314, 0.628, 0.942, 1.257, 1.571, 1.885, 2.199, 2.513,
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2.827, 3.142, 3.456, 3.77 , 4.084, 4.398, 4.712, 5.027, 5.341,
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5.655, 5.969, 6.283])
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```
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```
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# 三角函数
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b = sin(a)
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b
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```
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```
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array([ 0.000e+00, 3.090e-01, 5.878e-01, 8.090e-01, 9.511e-01,
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1.000e+00, 9.511e-01, 8.090e-01, 5.878e-01, 3.090e-01,
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1.225e-16, -3.090e-01, -5.878e-01, -8.090e-01, -9.511e-01,
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-1.000e+00, -9.511e-01, -8.090e-01, -5.878e-01, -3.090e-01,
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-2.449e-16])
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```
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```
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# 画出三角函数图像
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%matplotlib inline
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plot(a, b)
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```
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```
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[<matplotlib.lines.Line2D at 0xab0fe10>]
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```
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## 从数组中选择元素
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```
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b
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```
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```
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array([ 0.000e+00, 3.090e-01, 5.878e-01, 8.090e-01, 9.511e-01,
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1.000e+00, 9.511e-01, 8.090e-01, 5.878e-01, 3.090e-01,
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1.225e-16, -3.090e-01, -5.878e-01, -8.090e-01, -9.511e-01,
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-1.000e+00, -9.511e-01, -8.090e-01, -5.878e-01, -3.090e-01,
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-2.449e-16])
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```
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```
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# 假设我们想选取数组b中所有非负的部分,首先可以利用 b 产生一组布尔值
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b >= 0
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```
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```
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array([ True, True, True, True, True, True, True, True, True,
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True, True, False, False, False, False, False, False, False,
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False, False, False])
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```
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```
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mask = b >= 0
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```
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```
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# 画出所有对应的非负值对应的点:
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plot(a[mask], b[mask], 'ro')
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```
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```
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[<matplotlib.lines.Line2D at 0xafd0e50>]
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```
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```
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plot(a[mask], b[mask], 'r')
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```
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```
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[<matplotlib.lines.Line2D at 0xa833ad0>]
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```
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