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latest shared results 2024-02-26

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dedebenui
2024-02-26 08:34:18 +01:00
parent d5c571e705
commit 090100290a
1 changed files with 2 additions and 25 deletions
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27
src/scgenerator/examples/dudley2006.py
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@@ -1,8 +1,6 @@
import click import click
import colorcet as cc
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
import numpy as np import numpy as np
from plotapp import PlotApp
import scgenerator as sc import scgenerator as sc
@@ -45,32 +43,11 @@ def compute_manual(save: bool):
beta_op = sc.operators.constant_polynomial_dispersion(params.beta2_coefficients, w_c) beta_op = sc.operators.constant_polynomial_dispersion(params.beta2_coefficients, w_c)
linear = sc.operators.envelope_linear_operator( linear = sc.operators.envelope_linear_operator(
beta_op, beta_op,
# sc.operators.constant_quantity(0),
sc.operators.constant_quantity(0), sc.operators.constant_quantity(0),
) )
# with PlotApp() as app:
# o = np.argsort(p.l)
# sax = app["spectrum"]
# sax.set_line_data("beta2", p.l[o], beta_op(0)[o].imag)
# return
# spm = sc.operators.envelope_spm(0)
# plt.plot(p.l, sc.abs2(p.spec_0))
# plt.plot(p.l, sc.abs2(np.fft.fft(spm(np.fft.ifft(p.spec_0), 0))), ls=":")
# plt.xlim(100e-9, 1500e-9)
# plt.show()
# return
# nonlinear = sc.operators.envelope_nonlinear_operator(
# gamma_op=sc.operators.constant_quantity(params.gamma),
# ss_op=sc.operators.constant_quantity(w_c / w0),
# spm_op=sc.operators.envelope_spm(0),
# raman_op=sc.operators.no_op_time(params.t_num),
# )
hr_w = params.compute("hr_w") hr_w = params.compute("hr_w")
def nonlinear(spec, z): def nonlinear(spec, _):
field = np.fft.ifft(spec) field = np.fft.ifft(spec)
field2 = sc.abs2(field) field2 = sc.abs2(field)
fr = 0.18 fr = 0.18
@@ -86,7 +63,7 @@ def compute_manual(save: bool):
w_power_fact = np.array( w_power_fact = np.array(
[sc.math.power_fact(w_c[above0], k) for k in range(2, len(p.beta2_coefficients) + 2)] [sc.math.power_fact(w_c[above0], k) for k in range(2, len(p.beta2_coefficients) + 2)]
) )
for i, wn in reversed(list(enumerate(w_power_fact))): for i, _ in reversed(list(enumerate(w_power_fact))):
print(i, p.beta2_coefficients[i]) print(i, p.beta2_coefficients[i])
linear_arr[above0] += p.beta2_coefficients[i] * sc.math.power_fact(w_c[above0], i + 2) linear_arr[above0] += p.beta2_coefficients[i] * sc.math.power_fact(w_c[above0], i + 2)
linear_arr *= -1j linear_arr *= -1j