Created
February 20, 2018 06:13
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Python script to compute multiple regression equation with NumPy.
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#! /usr/local/bin/python3.6 | |
""" | |
Computation of a multiple regression with NumPy | |
""" | |
import sys | |
import traceback | |
import numpy as np | |
class RegressionMulti: | |
def reg_multi(self, x, y): | |
""" Regression line computation | |
:param list x: list of explanatory variables | |
:param list y: list of objective variables | |
:return list [b, a_0, a_1]: b, a_0, a_1 value | |
""" | |
try: | |
if type(x) != list: | |
print("Argument(X) is not a list!") | |
sys.exit() | |
if type(y) != list: | |
print("Argument(Y) is not a list!") | |
sys.exit() | |
if len(x) == 0: | |
print("List(X) is none!") | |
sys.exit() | |
if len(y) == 0: | |
print("List(Y) is none!") | |
sys.exit() | |
if len(x[0]) != len(y): | |
print("Argument list size is invalid!") | |
sys.exit() | |
for i in range(1, len(x)): | |
if len(x[0]) != len(x[i]): | |
print("Argument list size is invalid!") | |
sys.exit() | |
e = np.array(x) | |
o = np.array(y) | |
e = np.vstack([np.ones(e.shape[1]), e]) | |
return np.linalg.lstsq(e.T, o)[0] | |
except Exception as e: | |
raise | |
if __name__ == '__main__': | |
try: | |
x = [ | |
[10, 9, 8, 6, 8, 4, 9, 10, 2, 3, 8, 6, 7, 5], | |
[83, 71, 64, 69, 69, 64, 68, 59, 81, 91, 57, 65, 58, 62] | |
] | |
y = [183, 168, 171, 178, 176, 172, 165, 158, 183, 182, 163, 175, 164, 175] | |
for i, a in enumerate(x): | |
print("説明変数 X{} = {}".format(i + 1, x[i])) | |
print("目的変数 Y =", y) | |
print("---") | |
obj = RegressionMulti() | |
res = obj.reg_multi(x, y) | |
print("b =", res[0]) | |
print("a_0 =", res[1]) | |
print("a_1 =", res[2]) | |
except Exception as e: | |
traceback.print_exc() | |
sys.exit(1) |
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