moved examples

src/scgenerator/examples/dudley2006.py

@@ -1,3 +1,4 @@
+import click
 import colorcet as cc
 import matplotlib.pyplot as plt
 import numpy as np
@@ -6,6 +7,7 @@ from plotapp import PlotApp
 import scgenerator as sc
 
 params = sc.Parameters(
+    name="Dudley2006 example",
     wavelength=835e-9,
     width=50e-15,
     peak_power=10e3,
@@ -35,14 +37,12 @@ params = sc.Parameters(
 )
 
 
-def compute_manual():
+def compute_manual(save: bool):
     spec0 = params.compute("spec_0")
     w_c, w0, gamma = params.compute("w_c", "w0", "gamma")
     p = params.compile()
     print(p.dt)
-    beta_op = sc.operators.constant_polynomial_dispersion(
-        params.beta2_coefficients, w_c, params.compute("dispersion_ind")
-    )
+    beta_op = sc.operators.constant_polynomial_dispersion(params.beta2_coefficients, w_c)
     linear = sc.operators.envelope_linear_operator(
         beta_op,
         # sc.operators.constant_quantity(0),
@@ -94,7 +94,10 @@ def compute_manual():
     def linear(_):
         return linear_arr
 
+    if save:
         prop = sc.propagation("examples/dudley_manual.zip", params)
+    else:
+        prop = sc.propagation(params)
     z = []
     for i, (spec, stat) in enumerate(
         sc.solve43(spec0, linear, nonlinear, params.length, 1e-6, 1e-6, 0.9, h_const=20e-6)
@@ -106,8 +109,11 @@ def compute_manual():
         z.append(stat["z"])
 
 
-def compute_auto():
+def compute_auto(save: bool):
+    if save:
         sc.compute(params, True, "examples/dudley2006")
+    else:
+        sc.compute(params)
 
 
 def plot():
@@ -120,6 +126,15 @@ def plot():
     plt.show()
 
 
-if __name__ == "__main__":
-    # compute_auto()
+@click.command()
+@click.option("--show/--no-show", default=False)
+@click.option("--save/--no-save", default=False)
+def main(show: bool, save: bool):
+    compute_manual(save)
+    compute_auto(save)
+    if show:
         plot()
+
+
+if __name__ == "__main__":
+    main()

src/scgenerator/helpers.py

@@ -1,6 +1,7 @@
 """
 series of helper functions
 """
+
 import os
 import warnings
 from pathlib import Path
@@ -166,19 +167,17 @@ def extend_axis(axis: np.ndarray) -> np.ndarray:
 def compute(
     parameters: Parameters, overwrite: bool = False, output: os.PathLike | None = None
 ) -> Propagation:
+    prop_params = parameters.compile()
     if output is None:
-        name = Path(parameters.compute("name")).stem + ".zip"
+        prop = propagation(prop_params)
     else:
         path = Path(output)
         name = path.parent / (path.stem + ".zip")
-
-    prop_params = parameters.compile()
         prop = propagation(name, prop_params, bundle_data=True, overwrite=overwrite)
 
     with warnings.catch_warnings(), tqdm(total=prop_params.z_num) as pbar:
         warnings.filterwarnings("error")
-        for i, (spec, new_stat) in enumerate(
-            solve43(
+        for spec, _ in solve43(
             prop_params.spec_0,
             prop_params.linear_operator,
             prop_params.nonlinear_operator,
@@ -187,7 +186,6 @@ def compute(
             prop_params.tolerated_error,
             0.9,
             targets=prop_params.z_targets,
-            )
         ):
             pbar.update()
             prop.append(spec)

src/scgenerator/math.py

@@ -22,16 +22,10 @@ c = 299792458.0
 def fft_functions(
     full_field: bool,
 ) -> tuple[Callable[[np.ndarray], np.ndarray], Callable[[np.ndarray], np.ndarray]]:
-    if platform.processor() == "arm":
     if full_field:
         return sfft.rfft, sfft.irfft
     else:
         return sfft.fft, sfft.ifft
-    else:
-        if full_field:
-            return np.fft.rfft, np.fft.irfft
-        else:
-            return np.fft.fft, np.fft.ifft
 
 
 def expm1_int(y: np.ndarray, dx: float) -> np.ndarray: