我怎樣才能改進這個矩陣逆計算器 我做了這個矩陣逆計算器，它作業得很好，但我想知道這個程式如何才能變得更短。謝謝
from numpy import *
#inverse calculator
print(array([['a,b,c'],['d,e,f'],['g,h,i']]))
a = int(input("a: "))
b = int(input("b: "))
c = int(input("c: "))
d = int(input("d: "))
e = int(input("e: "))
f = int(input("f: "))
g = int(input("g: "))
h = int(input("h: "))
i = int(input("i: "))
x = array([[a,b,c],[d,e,f],[g,h,i]]) #we made matrixform
#print(x)
det = linalg.det(x) # we take determinant to check if it is 0 or not
if det != 0: #if its not 0 then inverse is possible
inverse = linalg.inv(x)
print("So the inverse of matrix \n",x, "is \n", inverse)
else: #if it is 0 then print this:
print(".\n .\n Matrix is singular,\n Inverse can not be calculated")
uj5u.com熱心網友回復：
我認為它可以更短的唯一方法是：
x = array([int(input(f"{ch}: ")) for ch in "abcdefghi"]).reshape((3,3))
inverse = linalg.inv(x) if linalg.det(x) != 0 else np.nan # or False or something else
uj5u.com熱心網友回復：
一種方法是使用try- except：
try:
print(f"inv of matrix {x} is {np.linalg.inv(x)}")
except np.linalg.LinAlgError:
print("Matrix is singualr")
輸出：
x1 = np.array([[1,2,3], [4,5,6], [7,8,9]])
x2 = np.array([[1,2,3], [4,5,6], [7,8,10]])
def is_inversible(x):
try:
print(f"inv of matrix \n{x} is \n{np.linalg.inv(x)}")
except np.linalg.LinAlgError:
print("Matrix is singualr")
is_inversible(x1)
# Matrix is singualr
is_inversible(x2)
#inv of matrix
#[[ 1 2 3]
# [ 4 5 6]
# [ 7 8 10]] is
#[[-0.66666667 -1.33333333 1. ]
# [-0.66666667 3.66666667 -2. ]
# [ 1. -2. 1. ]]
uj5u.com熱心網友回復：
這是更好的方法
import numpy as np
str_inp = input('Enter a b c d e f g h i \n')
elems = list(map(int,str_inp.split()[0:9]))
x = np.array(elems).reshape(3,3) # we made matrixform
print(x)
try:
inverse = np.linalg.inv(x)
print(inverse)
except np.linalg.LinAlgError:
print('Inverse doesnt exist for the given matrix')
輸出
Enter a b c d e f g h i
1 2 3 4 5 6 7 8 9
[[1 2 3]
[4 5 6]
[7 8 9]]
[[ 3.15251974e 15 -6.30503948e 15 3.15251974e 15]
[-6.30503948e 15 1.26100790e 16 -6.30503948e 15]
[ 3.15251974e 15 -6.30503948e 15 3.15251974e 15]]
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