X = np.zeros(N, dtype=np.complex128)含义
时间: 2023-06-05 11:05:19 浏览: 59
:请问 X = np.zeros(N, dtype=np.complex128 的含义是什么?
回答:X = np.zeros(N, dtype=np.complex128 表示创建一个由 N 个复数型数值组成的数组,每个数值都为0。此处的 dtype=np.complex128 表示数组中每个元素都是复数型数值。
相关问题
请修改以下代码使它输出正确的结果不能报错:import numpy as np import matplotlib.pyplot as plt def square_poten_well(x, N): L = 2 V0 = -1 mat_V = np.zeros((N, N)) for i, xx in enumerate(x): if abs(xx) <= L/2: mat_V[i, i] = V0 return mat_V def phi(k, x, N): return [np.exp(1.0jkx[i]) for i in range(N)] def Green_func(k, x, xp, N): G = np.ones((N, N), dtype=np.complex128) for i in range(N): for j in range(N): G[i, j] = -1.0j / k * np.exp(1.0j * k * abs(x[i] - xp[j])) return G def change_of_var(node, weight, a, b, N): nop = [(b-a) * node[i] / 2.0 + (a+b) / 2.0 for i in range(N)] wp = [(b-a) / 2.0 * weight[i] for i in range(N)] return nop, wp N = 298 # 节点的个数 a = -1.5 # 积分下限 b = 1.5 # 积分上限 k_vec = np.arange(0.5, 6.0) # 波数k的取值 x = np.linspace(a, b, N) dx = (b - a) / (N - 1) psi = np.zeros((len(k_vec), N)) for i, k in enumerate(k_vec): V = square_poten_well(x, N) phi_k = phi(k, x, N) G = Green_func(k, x, x, N) node, weight = np.polynomial.legendre.leggauss(N) node = np.flip(node, axis=0) weight = np.flip(weight, axis=0) xp, wp = change_of_var(node, weight, a, b, N) m = np.matmul(np.matmul(np.diag(phi_k), G), np.diag(phi_k.conj())) * dx psi_k = np.linalg.solve(V - k**2 * np.eye(N), np.matmul(m, phi_k)) psi[i] = np.abs(psi_k)**2 fig, ax = plt.subplots() for i, k in enumerate(k_vec): ax.plot(x, psi[i], label=f'k={k:.1f}') ax.set_xlabel('x') ax.set_ylabel('$|\psi|^2$') ax.legend() plt.show()
import numpy as np
import matplotlib.pyplot as plt
def square_poten_well(x, N):
L = 2
V0 = -1
mat_V = np.zeros((N, N))
for i, xx in enumerate(x):
if abs(xx) <= L/2:
mat_V[i, i] = V0
return mat_V
def phi(k, x, N):
return np.exp(1.0j * k * x)
def Green_func(k, x, xp, N):
G = np.ones((N, N), dtype=np.complex128)
for i in range(N):
for j in range(N):
G[i, j] = -1.0j / k * np.exp(1.0j * k * abs(x[i] - xp[j]))
return G
def change_of_var(node, weight, a, b, N):
nop = [(b-a) * node[i] / 2.0 + (a+b) / 2.0 for i in range(N)]
wp = [(b-a) / 2.0 * weight[i] for i in range(N)]
return nop, wp
N = 298 # 节点的个数
a = -1.5 # 积分下限
b = 1.5 # 积分上限
k_vec = np.arange(0.5, 6.0, 0.1) # 波数k的取值
x = np.linspace(a, b, N)
dx = (b - a) / (N - 1)
psi = np.zeros((len(k_vec), N))
for i, k in enumerate(k_vec):
V = square_poten_well(x, N)
phi_k = phi(k, x, N)
G = Green_func(k, x, x, N)
node, weight = np.polynomial.legendre.leggauss(N)
node = np.flip(node, axis=0)
weight = np.flip(weight, axis=0)
xp, wp = change_of_var(node, weight, a, b, N)
m = np.matmul(np.matmul(np.diag(phi_k), G), np.diag(phi_k.conj())) * dx
psi_k = np.linalg.solve(V - k**2 * np.eye(N), np.matmul(m, phi_k))
psi[i] = np.abs(psi_k)**2
fig, ax = plt.subplots()
for i, k in enumerate(k_vec):
ax.plot(x, psi[i], label=f'k={k:.1f}')
ax.set_xlabel('x')
ax.set_ylabel('$|\psi|^2$')
ax.legend()
plt.show()
class Givens(): def __init__(self,Tm,Tn,X): self.Tm=Tm self.Tn=Tn self.X1=X[0:10] self.X2=X[10:16] def hbf_T(self): Tm = self.Tm Tn = self.Tn a_b = np.random.uniform(0, 1, (Tm, Tn, 4)) c = a_b[:, :, 0]**2 + a_b[:, :, 1]**2 mask = c < 1 TT = np.zeros((Tm, Tn), dtype=complex) # 初始化 TT det_TT = 1 while det_TT != 0: for i in range(Tn): X1 = np.zeros(Tm, dtype=complex) X1[mask[:, i]] = a_b[:, i, 0][mask[:, i]] + 1j*a_b[:, i, 1][mask[:, i]] TT[:, i] = X1 det_TT = np.linalg.det(np.dot(np.transpose(TT), TT)) return TT
这段代码实现了一个 Givens 变换(Givens rotation)。Givens 变换是一种矩阵旋转,可以将一个矩阵的某两行或某两列通过正交变换旋转到一个新的位置,从而得到一个更简单的矩阵。这段代码中,Givens 变换作用于一个复矩阵,其中 X1 和 X2 是矩阵 X 的前 10 行和后 6 行,Tm 和 Tn 是 Givens 变换的参数。具体地,代码中通过随机生成一个 a_b 矩阵,然后选择其中符合条件的部分进行 Givens 变换,直到得到满足条件的 TT 矩阵。最后返回 TT 矩阵。
相关推荐
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)