python-3.x - 为什么向 numpy 数组分配新值不起作用？

Question

我有以下代码。开头相当长，但仅用于生成数据。问题发生在最后几行。

##### Import packages
import numpy as np
import scipy.linalg as la

##### Initial conditions
N = 5
lamda = 7
mu = 2
a = 0.5
r = - np.log(a).copy()
St_Sp = np.arange(- N, N + 1)
Card = St_Sp.shape[0]

##### Define infintesimal generator
def LL(x, y):
    if x == N or x == - N: re = 0
    elif x - y == - 1: re = lamda
    elif x - y == 1: re = mu
    elif x - y == 0: re = - (mu + lamda)
    else: re = 0
    return re

def L(x):
    return - LL(x, x)

##### Define function Phi
def Phi(x): return max(x, 0)
Phi = np.vectorize(Phi)

##### Define vector b
b = Phi(St_Sp).copy()

##### Define function Psi
def Psi(x): return L(x) / (L(x) + r)
Psi = np.vectorize(Psi)

##### Generate a Boolean vector whose all elements are False
d = np.array([0] * Card).astype(bool)

##### Define matrix A
A = np.zeros((Card, Card))
for i in range(Card):
    for j in range(Card):
        if (i != j) & (L(St_Sp[i]) != 0):
            A[i, j] = LL(St_Sp[i], St_Sp[j]) / L(St_Sp[i])
        elif (i != j) & (L(St_Sp[i]) == 0):
            A[i, j] = 0
        elif (i == j) & (Psi(St_Sp[i]) != 0):
            A[i, j] = - 1 / Psi(St_Sp[i])
        else: A[i, j] = 1

##### Row names of A
rows = np.arange(0, Card)

##### Define matrix B
B = np.zeros((Card, Card))
for i in range(Card):
    for j in range(Card):
        if i != j:
            B[i, j] = LL(St_Sp[i], St_Sp[j])
        else: B[i, j] = LL(St_Sp[i], St_Sp[j]) - r

##### Generate I_0
I = [np.array([1] * Card).astype(bool), d.copy()]
Z = b.copy()       

index0 = np.matmul(B, Z) <= 0
index1 = ~ index0

##### Generate I_1
I = [index0, index1]
Z = b.copy()

if np.sum(I[1]) > 0:
    order = np.concatenate((rows[I[1]], rows[~ I[1]]))
    A1 = A[np.ix_(rows[I[1]], order)]    
    A2 = la.lu(A1)[2]
    p = np.atleast_2d(A1).shape[0]    
    B1 = A2[:, range(p)]          
    B2 = - np.matmul(A2[:, p:], Z[I[0]])

    print('Before being assigned new values, Z is \n', Z)

    print('\n The index I[1] of elements of Z to be change \n', I[1])

    M = la.solve_triangular(B1, B2,  lower = False)

    print('\n The values to be assigned to Z[I[1]] is \n', M)

    Z[I[1]] = M

    print('\n After being assigned new values, Z is \n', Z)

结果

Before being assigned new values, Z is 
 [0 0 0 0 0 0 1 2 3 4 5]

 The index I[1] of elements of Z to be change 
 [False False False False False  True  True  True  True  True False]

 The values to be assigned to Z[I[1]] is 
 [2.08686055 2.88974949 3.40529229 3.88978577 4.41338306]

 After being assigned new values, Z is 
 [0 0 0 0 0 2 2 3 3 4 5]

令我感到非常奇怪的是，命令 Z[I[1]] = M 没有将新值从 M 分配给 Z< 的位置 由 I[1] 索引。您能详细说明一下为什么会出现这个问题以及如何解决吗？

Answer 1

数组 Z 的数据类型是 int，这些值由 python 自动进行类型转换，从而得到整数值 int([2.08686055 2.88974949 3.40529229 3.88978577 4.41338306]) = [2 2 3 3 4 5]。

如果您想更改该行为，只需添加一行来更改原始数组的类型:

Z = Z.astype(float)