1. 安装numpy库:pip install numpy
2. 将numpy函数库中的所有模块引入:
from numpy import *
3. 构造一个4*4的随机数组:
randArray = random.rand(4,4) print(randArray)
4.mat()函数:将数组转化为矩阵:
randMat = mat(random.rand(4,4)) print(randMat)
5. 求逆矩阵.I操作符
randMat = mat(random.rand(4,4)) print(randMat) invRandMat = randMat.I print(invRandMat)
6.执行矩阵乘法:
randMat = mat(random.rand(4,4)) print(randMat) invRandMat = randMat.I print(invRandMat) Multi = randMat*invRandMat print(Multi)
结果应收是单位矩阵,除了对角线元素为1,其他元素应该为0,实际的输出略有不同,因为矩阵例还留下了许多非常小的元素,这是计算机处理误差产生的结果。
import numpy vector = numpy.array([5,10,15,20]) matrix = numpy.array([[5,10,15],[20,25,30]]) print(vector) print(matrix) print(vector.shape) print(matrix.shape)
.dtype查看类型
import numpy numbers = numpy.array([1,2,3,4]) print(numbers) numbers.dtype
import numpy numbers = numpy.array([1,2,3,4.0]) print(numbers) numbers.dtype
import numpy vector = numpy.array([5,10,15,20]) vector == 10
import numpy matrix = numpy.array([ [5,10,15], [20,25,30], [35,40,45] ]) matrix == 25
import numpy vector = numpy.array([5,10,15,20]) equal_to_ten = (vector == 10) print (equal_to_ten) print(vector[equal_to_ten])
与运算和或运算:
import numpy vector = numpy.array([5,10,15,20]) equal_to_ten_and_five = (vector == 10) & (vector == 5) print (equal_to_ten_and_five)
import numpy vector = numpy.array([5,10,15,20]) equal_to_ten_or_five = (vector == 10) | (vector == 5) print (equal_to_ten_and_five)
类型转换:
import numpy vector = numpy.array(["5","10","15","20"]) print(vector.dtype) print(vector) vector = vector.astype(float) print(vector.dtype) print(vector)
求最小、最大值:
import numpy vector = numpy.array([5,10,15,20]) min = vector.min() print(min) max = vector.max() print(max)
计算每一行的和值:
import numpy matrix = numpy.array([ [5,10,15], [20,25,30], [35,40,45] ]) matrix.sum(axis=1)
计算每一列的和值:
import numpy matrix = numpy.array([ [5,10,15], [20,25,30], [35,40,45] ]) matrix.sum(axis=0)
import numpy as np #用np代替numpy print(np.arange(15)) a = np.arange(15).reshape(3,5) print(a) a.shape a.size #当前矩阵包含多少个元素 a.ndim #当前矩阵的维度 a.dtype.name #当前矩阵的类型
import numpy vector = numpy.array([5,10,15,20]) matrix = numpy.array([[5,10,15],[20,25,30]]) print(vector) print(matrix) print(vector.shape) print(matrix.shape)
.dtype查看类型
import numpy numbers = numpy.array([1,2,3,4]) print(numbers) numbers.dtype
import numpy numbers = numpy.array([1,2,3,4.0]) print(numbers) numbers.dtype
import numpy vector = numpy.array([5,10,15,20]) vector == 10
import numpy matrix = numpy.array([ [5,10,15], [20,25,30], [35,40,45] ]) matrix == 25
import numpy vector = numpy.array([5,10,15,20]) equal_to_ten = (vector == 10) print (equal_to_ten) print(vector[equal_to_ten])
与运算和或运算:
import numpy vector = numpy.array([5,10,15,20]) equal_to_ten_and_five = (vector == 10) & (vector == 5) print (equal_to_ten_and_five)
import numpy vector = numpy.array([5,10,15,20]) equal_to_ten_or_five = (vector == 10) | (vector == 5) print (equal_to_ten_and_five)
类型转换:
import numpy vector = numpy.array(["5","10","15","20"]) print(vector.dtype) print(vector) vector = vector.astype(float) print(vector.dtype) print(vector)
求最小、最大值:
import numpy vector = numpy.array([5,10,15,20]) min = vector.min() print(min) max = vector.max() print(max)
计算每一行的和值:
import numpy matrix = numpy.array([ [5,10,15], [20,25,30], [35,40,45] ]) matrix.sum(axis=1)
计算每一列的和值:
import numpy matrix = numpy.array([ [5,10,15], [20,25,30], [35,40,45] ]) matrix.sum(axis=0)
import numpy as np #用np代替numpy print(np.arange(15)) a = np.arange(15).reshape(3,5) print(a) a.shape a.size #当前矩阵包含多少个元素 a.ndim #当前矩阵的维度 a.dtype.name #当前矩阵的类型