new spectrogam method

examples/cli_script.py

@@ -0,0 +1,12 @@
+from pathlib import Path
+
+import scgenerator as sc
+
+
+class Config(sc.MainConfig):
+    parameters: sc.Parameters
+    root: Path
+
+
+if __name__ == "__main__":
+    Config.main()

src/scgenerator/cli.py

@@ -0,0 +1,62 @@
+import os
+import tomllib
+from dataclasses import dataclass
+from pathlib import Path
+from typing import Any, Protocol, TypeVar
+
+import click
+from matplotlib.pyplot import inspect
+
+from scgenerator.parameter import Parameters
+
+T = TypeVar("T")
+
+
+class MultiSimConfig(Protocol):
+    def prepare(self, id: int) -> Parameters:
+        ...
+
+    def output(self, id: int) -> Path:
+        ...
+
+
+def load_params(file: Path) -> tuple[Parameters, dict[str, Any]]:
+    file_config = {}
+    dico = tomllib.loads(file.read_text())
+    file_config = dico.pop("config", {})
+    params = Parameters(**dico)
+    if params.name is None:
+        params.name = file.stem
+    return params, file_config
+
+
+def main_config(cls: T) -> T:
+    param_key = None
+    for k, v in inspect.get_annotations(cls, eval_str=True).items():
+        if v is Parameters:
+            param_key = k
+            break
+
+    @click.group()
+    @click.option(
+        "-p",
+        "--parameters",
+        type=click.Path(
+            exists=True, file_okay=True, dir_okay=False, resolve_path=True, path_type=Path
+        ),
+    )
+    @click.pass_context
+    def main(ctx, parameters: Path | None):
+        params, config = load_params(Path(f"{root.stem}.toml"))
+        config = cls(**{param_key: params}, **config)
+        datadir = config.fn(0).parent
+        if not datadir.exists():
+            try:
+                os.makedirs(datadir, exist_ok=True)
+            except OSError:
+                pass
+        config.load_noise()
+        ctx.obj = config
+
+    setattr(cls, "main", main)
+    return cls

src/scgenerator/spectra.py

@@ -8,6 +8,7 @@ from pathlib import Path
 from typing import Callable, Generic, Iterable, Iterator, Sequence, TypeVar, overload
 
 import numpy as np
+import scipy.signal as ss
 
 from scgenerator import math
 from scgenerator.io import (
@@ -161,11 +162,49 @@ class Spectrum(np.ndarray):
         """
         return pulse.g12(self, axis)[..., self.wl_order]
 
-    def spectrogram(self, delays: Iterable[float], gate_width: float = 2e-13) -> np.ndarray:
-        return np.fft.fftshift(
-            pulse.spectrogram(self.t, delays, self.time_amp, gate_width), axes=-1
+    def spectrogram(
+        self,
+        gate_width: float = 100e-15,
+        wavelength: bool = True,
+        autocrop: bool | float = 1e-5,
+    ) -> np.ndarray:
+        dt = self.t[1] - self.t[0]
+        sigma = gate_width / (2 * np.sqrt(2 * np.log(2))) / dt
+        nperseg = int(sigma) * 16
+        f, t, s = ss.stft(
+            self.time_amp,
+            1 / dt,
+            window=("gaussian", sigma),
+            nperseg=nperseg,
+            noverlap=nperseg - 4,
+            detrend=False,
+            scaling="psd",
+            boundary=None,
+            return_onesided=False,
+            padded=False,
         )
 
+        f = np.fft.fftshift(f) + self.w[0] * 0.5 / np.pi
+        t += self.t[0]
+        s = np.fft.fftshift(math.abs2(s), axes=0)
+
+        if wavelength:
+            f = units.m_hz(f)
+            s = units.to_WL(s.T, f).T
+            f = f[::-1]
+            s = s[::-1]
+
+        if autocrop:
+            thr = s.max()
+            yind, xind = np.where(s > thr * autocrop)
+            xmin, xmax = xind.min(), xind.max()
+            ymin, ymax = yind.min(), yind.max()
+            t = t[xmin : xmax + 1]
+            f = f[ymin : ymax + 1]
+            s = s[ymin : ymax + 1][:, xmin : xmax + 1]
+
+        return t, f, s
+
     freq_int = afreq_int
     freq_amp = afreq_amp