我正在用从高斯分布中提取的值填充两个数组field_in_k_space_REAL
和field_in_k_space_IMAGINARY
,注意要遵守对称性,以便在反向转换数组时得到实数场。以下是代码:
field_in_k_space_REAL = zeros(n, float)
field_in_k_space_IMAGINARY = zeros(n, float)
field_in_k_space_REAL[0] = 0.0
for i in range(1, int(n/2+1)):
field_in_k_space_REAL[i] = np.random.normal(mu, math.sqrt((1/2)*math.exp(-(2*math.pi*i*sigma/L)*(2*math.pi*i*sigma/L))))
x = range(int(n/2+1), int(n))
y = range(1, int(n/2))
zipped = zip(x, y)
for j, j2 in zipped:
field_in_k_space_REAL[j] = field_in_k_space_REAL[j-2*j2]
field_in_k_space_IMAGINARY[0] = 0.0
for i in range(1, int(n/2)):
field_in_k_space_IMAGINARY[i] = np.random.normal(mu, math.sqrt((1/2)*math.exp(-(2*math.pi*i*sigma/L)*(2*math.pi*i*sigma/L))))
field_in_k_space_IMAGINARY[n/2] = 0.0
for j, j2 in zipped:
field_in_k_space_IMAGINARY[j] = - field_in_k_space_IMAGINARY[j-2*j2]
print 'field_k', field_in_k_space_REAL
但我一直遇到以下错误:
field_in_k_space_REAL[0] = 0.0
IndexError: index 0 is out of bounds for axis 0 with size 0
有人能解释一下为什么会出现这个问题以及如何修复吗?
n = 32
的值,我无法重现您展示的错误。 - Cory Kramer