Python NumPy矩阵运算在不同的机器上产生不同的结果_Python_Numpy

Python NumPy矩阵运算在不同的机器上产生不同的结果

python numpy

Python NumPy矩阵运算在不同的机器上产生不同的结果,python,numpy,Python,Numpy,我试图用NumPy做一些线性回归，但我遇到了一个奇怪的问题，当我在两台不同的机器上运行相同的代码时，我从矩阵计算中得到了完全不同的结果。我已经尝试了所有不同的方法，比如使用@、.T、NumPy.matmul等，你可以从NumPy中预成型矩阵数学，但似乎没有任何效果。可能是什么问题？我在下面贴出了每个汇编的结果 import numpy as np from numpy.linalg import inv import math as math with open("dataset1_

我试图用NumPy做一些线性回归，但我遇到了一个奇怪的问题，当我在两台不同的机器上运行相同的代码时，我从矩阵计算中得到了完全不同的结果。我已经尝试了所有不同的方法，比如使用@、.T、NumPy.matmul等，你可以从NumPy中预成型矩阵数学，但似乎没有任何效果。可能是什么问题？我在下面贴出了每个汇编的结果

import numpy as np
from numpy.linalg import inv
import math as math

with open("dataset1_inputs.txt") as f:
    x = [float(line.rstrip()) for line in f]
with open("dataset1_outputs.txt") as f:
    y = [float(line.rstrip()) for line in f]
testRange = 100
X = np.zeros((testRange, 30))  ##Initialize design matrix for degree M = 30
t = np.zeros((testRange, 1))

degree = 1
for i in range(0, testRange):  ##populate first column with 1's
    X[i][0] = 1
    t[i] = y[i]
for i in range(1, 30):
    for j in range(0, testRange):
        X[j][i] = math.pow(x[j], degree)
    degree = degree + 1
#Compute w
# w = (X^TX)inverse x X^Tt
w = inv(np.dot(np.transpose(X), X))
temp = np.dot(np.transpose(X), t)
w = np.dot(w, temp)
print(w)

机器1结果：（使用Python 3.8.6的windows x64机器）：

[[ 8.69848822e-01]
 [-1.25241384e+00]
 [-1.27786762e+01]
 [ 3.77876441e+01]
 [ 2.00766643e+02]
 [-1.71725266e+02]
 [-3.12058614e+03]
 [-5.10484631e+03]
 [ 2.09732643e+04]
 [ 6.86684712e+04]
 [-6.30478671e+04]
 [-3.80043816e+05]
 [ 4.60883125e+04]
 [ 1.11930829e+06]
 [ 2.32033793e+05]
 [-1.69654123e+06]
 [-6.95034616e+05]
 [ 6.45140686e+05]
 [ 6.30005602e+05]
 [ 1.85819020e+06]
 [ 4.30926381e+05]
 [-2.59695183e+06]
 [-1.57932674e+06]
 [ 1.17398766e+05]
 [ 1.60064544e+06]
 [ 2.14257091e+06]
 [-7.70042255e+05]
 [-1.69876621e+06]
 [ 1.49711718e+05]
 [ 4.26267824e+05]]

[[  8.70267528e-01]
 [ -8.50540645e-01]
 [ -1.33384212e+01]
 [  3.15603869e+01]
 [  2.25742957e+02]
 [ -1.29846687e+02]
 [ -3.60286451e+03]
 [ -5.46711670e+03]
 [  2.58659560e+04]
 [  7.25232295e+04]
 [ -9.22289163e+04]
 [ -4.05888148e+05]
 [  1.55542118e+05]
 [  1.22259802e+06]
 [ -3.41017944e+04]
 [ -1.94905014e+06]
 [ -2.78392952e+05]
 [  1.00743043e+06]
 [  2.39739902e+05]
 [  1.63609800e+06]
 [  5.81782559e+05]
 [ -2.76584288e+06]
 [ -1.48929172e+06]
 [  5.82441438e+05]
 [  1.45785456e+06]
 [  1.73243957e+06]
 [ -7.00478273e+05]
 [ -1.52249602e+06]
 [  1.37099436e+05]
 [  3.95314037e+05]]

机器2结果：（使用Python 3.8.6的windows x64机器）：

[[ 8.69848822e-01]
 [-1.25241384e+00]
 [-1.27786762e+01]
 [ 3.77876441e+01]
 [ 2.00766643e+02]
 [-1.71725266e+02]
 [-3.12058614e+03]
 [-5.10484631e+03]
 [ 2.09732643e+04]
 [ 6.86684712e+04]
 [-6.30478671e+04]
 [-3.80043816e+05]
 [ 4.60883125e+04]
 [ 1.11930829e+06]
 [ 2.32033793e+05]
 [-1.69654123e+06]
 [-6.95034616e+05]
 [ 6.45140686e+05]
 [ 6.30005602e+05]
 [ 1.85819020e+06]
 [ 4.30926381e+05]
 [-2.59695183e+06]
 [-1.57932674e+06]
 [ 1.17398766e+05]
 [ 1.60064544e+06]
 [ 2.14257091e+06]
 [-7.70042255e+05]
 [-1.69876621e+06]
 [ 1.49711718e+05]
 [ 4.26267824e+05]]

[[  8.70267528e-01]
 [ -8.50540645e-01]
 [ -1.33384212e+01]
 [  3.15603869e+01]
 [  2.25742957e+02]
 [ -1.29846687e+02]
 [ -3.60286451e+03]
 [ -5.46711670e+03]
 [  2.58659560e+04]
 [  7.25232295e+04]
 [ -9.22289163e+04]
 [ -4.05888148e+05]
 [  1.55542118e+05]
 [  1.22259802e+06]
 [ -3.41017944e+04]
 [ -1.94905014e+06]
 [ -2.78392952e+05]
 [  1.00743043e+06]
 [  2.39739902e+05]
 [  1.63609800e+06]
 [  5.81782559e+05]
 [ -2.76584288e+06]
 [ -1.48929172e+06]
 [  5.82441438e+05]
 [  1.45785456e+06]
 [  1.73243957e+06]
 [ -7.00478273e+05]
 [ -1.52249602e+06]
 [  1.37099436e+05]
 [  3.95314037e+05]]

dataset1\u inputs.txt:

[[ 8.69848822e-01]
 [-1.25241384e+00]
 [-1.27786762e+01]
 [ 3.77876441e+01]
 [ 2.00766643e+02]
 [-1.71725266e+02]
 [-3.12058614e+03]
 [-5.10484631e+03]
 [ 2.09732643e+04]
 [ 6.86684712e+04]
 [-6.30478671e+04]
 [-3.80043816e+05]
 [ 4.60883125e+04]
 [ 1.11930829e+06]
 [ 2.32033793e+05]
 [-1.69654123e+06]
 [-6.95034616e+05]
 [ 6.45140686e+05]
 [ 6.30005602e+05]
 [ 1.85819020e+06]
 [ 4.30926381e+05]
 [-2.59695183e+06]
 [-1.57932674e+06]
 [ 1.17398766e+05]
 [ 1.60064544e+06]
 [ 2.14257091e+06]
 [-7.70042255e+05]
 [-1.69876621e+06]
 [ 1.49711718e+05]
 [ 4.26267824e+05]]

[[  8.70267528e-01]
 [ -8.50540645e-01]
 [ -1.33384212e+01]
 [  3.15603869e+01]
 [  2.25742957e+02]
 [ -1.29846687e+02]
 [ -3.60286451e+03]
 [ -5.46711670e+03]
 [  2.58659560e+04]
 [  7.25232295e+04]
 [ -9.22289163e+04]
 [ -4.05888148e+05]
 [  1.55542118e+05]
 [  1.22259802e+06]
 [ -3.41017944e+04]
 [ -1.94905014e+06]
 [ -2.78392952e+05]
 [  1.00743043e+06]
 [  2.39739902e+05]
 [  1.63609800e+06]
 [  5.81782559e+05]
 [ -2.76584288e+06]
 [ -1.48929172e+06]
 [  5.82441438e+05]
 [  1.45785456e+06]
 [  1.73243957e+06]
 [ -7.00478273e+05]
 [ -1.52249602e+06]
 [  1.37099436e+05]
 [  3.95314037e+05]]

dataset1\u outputs.txt:

[[ 8.69848822e-01]
 [-1.25241384e+00]
 [-1.27786762e+01]
 [ 3.77876441e+01]
 [ 2.00766643e+02]
 [-1.71725266e+02]
 [-3.12058614e+03]
 [-5.10484631e+03]
 [ 2.09732643e+04]
 [ 6.86684712e+04]
 [-6.30478671e+04]
 [-3.80043816e+05]
 [ 4.60883125e+04]
 [ 1.11930829e+06]
 [ 2.32033793e+05]
 [-1.69654123e+06]
 [-6.95034616e+05]
 [ 6.45140686e+05]
 [ 6.30005602e+05]
 [ 1.85819020e+06]
 [ 4.30926381e+05]
 [-2.59695183e+06]
 [-1.57932674e+06]
 [ 1.17398766e+05]
 [ 1.60064544e+06]
 [ 2.14257091e+06]
 [-7.70042255e+05]
 [-1.69876621e+06]
 [ 1.49711718e+05]
 [ 4.26267824e+05]]

[[  8.70267528e-01]
 [ -8.50540645e-01]
 [ -1.33384212e+01]
 [  3.15603869e+01]
 [  2.25742957e+02]
 [ -1.29846687e+02]
 [ -3.60286451e+03]
 [ -5.46711670e+03]
 [  2.58659560e+04]
 [  7.25232295e+04]
 [ -9.22289163e+04]
 [ -4.05888148e+05]
 [  1.55542118e+05]
 [  1.22259802e+06]
 [ -3.41017944e+04]
 [ -1.94905014e+06]
 [ -2.78392952e+05]
 [  1.00743043e+06]
 [  2.39739902e+05]
 [  1.63609800e+06]
 [  5.81782559e+05]
 [ -2.76584288e+06]
 [ -1.48929172e+06]
 [  5.82441438e+05]
 [  1.45785456e+06]
 [  1.73243957e+06]
 [ -7.00478273e+05]
 [ -1.52249602e+06]
 [  1.37099436e+05]
 [  3.95314037e+05]]

您正在共享的代码有一些问题，它包含两个未定义的变量

和

。我很抱歉，我刚修好