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Description
when running Appendix A.1 code
import tmm_fast as tmmf
import numpy as np
L = 12
d = np.random.uniform(20, 150, L)*1e-9 # thicknesses of the layers
d[0] = d[-1] = np.inf # set first and last layer as injection layer
n = np.random.uniform(1.2, 5, L) # random constant refractive index
n[-1] = 1 # outcoupling into air
wl = np.linspace(500, 900, 301)*1e-9
theta = np.deg2rad(np.linspace(0, 90, 301))
result = (tmmf.coh_tmm('s', n, d, theta, wl)['R']+ tmmf.coh_tmm('p', n, d, theta, wl)['R'])/2get error
Traceback (most recent call last):
File "d:\project\tmm_fast\appendix_01.py", line 10, in <module>
result = (tmmf.coh_tmm('s', n, d, theta, wl)['R']+ tmmf.coh_tmm('p', n, d, theta, wl)['R'])/2
File "d:\project\tmm_fast\tmm_fast\vectorized_tmm_dispersive_multistack.py", line 125, in coh_vec_tmm_disp_mstack
check_inputs(N, T, lambda_vacuum, Theta)
File "d:\project\tmm_fast\tmm_fast\vectorized_tmm_dispersive_multistack.py", line 498, in check_inputs
assert N.ndim == 3, 'N is not of shape [S x L x W] (3d), as it is of dimension ' + str(N.ndim)
AssertionError: N is not of shape [S x L x W] (3d), as it is of dimension 2
tmm-fast version 0.2.1
os Windows 11
torch 2.4.0
numpy 2.0.1
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