Merge branch 'dev' into targe_rules

src/scgenerator/cli/cli.py

@@ -137,16 +137,16 @@ def run_sim(args):
 
     method = prep_ray()
     run_simulation(args.config, method=method)
-    if sys.platform == "darwin" and sys.stdout.isatty():
-        subprocess.run(
-            [
-                "osascript",
-                "-e",
-                'tell app "System Events" to display dialog "simulation finished !"',
-            ],
-            stdout=subprocess.DEVNULL,
-            stderr=subprocess.DEVNULL,
-        )
+    # if sys.platform == "darwin" and sys.stdout.isatty():
+    #     subprocess.run(
+    #         [
+    #             "osascript",
+    #             "-e",
+    #             'tell app "System Events" to display dialog "simulation finished !"',
+    #         ],
+    #         stdout=subprocess.DEVNULL,
+    #         stderr=subprocess.DEVNULL,
+    #     )
 
 
 def merge(args):

src/scgenerator/physics/pulse.py

@@ -1039,14 +1039,18 @@ def rin_curve(spectra: np.ndarray) -> np.ndarray:
     ----------
     spectra : np.ndarray, shape (n, nt)
         a collection of n spectra from which to compute the RIN
+        complex amplitude is automatically converted to intensity
 
     Returns
     -------
     rin_curve : np.ndarray
         RIN curve
     """
+    if np.iscomplexobj(spectra):
         A2 = abs2(spectra)
-    return np.std(A2, axis=0) / np.mean(A2, axis=0)
+    else:
+        A2 = spectra
+    return np.std(A2, axis=-2) / np.mean(A2, axis=-2)
 
 
 def measure_field(t: np.ndarray, field: np.ndarray) -> Tuple[float, float, float]:

src/scgenerator/spectra.py

@@ -10,7 +10,12 @@ from . import math
 from .const import SPECN_FN
 from .logger import get_logger
 from .physics import pulse, units
-from .plotting import mean_values_plot, propagation_plot, single_position_plot
+from .plotting import (
+    mean_values_plot,
+    propagation_plot,
+    single_position_plot,
+    transform_2D_propagation,
+)
 from .utils.parameter import Parameters, PlotRange
 
 
@@ -356,6 +361,35 @@ class Pulse(Sequence):
             vals = vals[sim_ind]
         return plt_range, vals
 
+    def rin_propagation(
+        self, left: float, right: float, unit: str
+    ) -> tuple[np.ndarray, np.ndarray, np.ndarray]:
+        """returns the RIN as function of unit and z
+
+        Parameters
+        ----------
+        left : float
+            left limit in unit
+        right : float
+            right limit in unit
+        unit : str
+            unit descriptor
+
+        Returns
+        -------
+        x : np.ndarray, shape (nt,)
+            x axis
+        y : np.ndarray, shape (z_num, )
+            y axis
+        rin_prop : np.ndarray, shape (z_num, nt)
+            RIN
+        """
+        spectra = []
+        for spec in np.moveaxis(self.all_spectra(), 1, 0):
+            x, z, tmp = transform_2D_propagation(spec, (left, right, unit), self.params, False)
+            spectra.append(tmp)
+        return x, z, pulse.rin_curve(np.moveaxis(spectra, 0, 1))
+
     def z_ind(self, z: float) -> int:
         """return the closest z index to the given target