improved from_time_series constructor

src/scgenerator/noise.py

@@ -42,7 +42,12 @@ class NoiseMeasurement:
 
     @classmethod
     def from_time_series(
-        cls, signal: Sequence[float], dt: float, window: str = "Hann", num_segments: int = 1
+        cls,
+        signal: Sequence[float],
+        dt: float,
+        window: str = "Hann",
+        num_segments: int = 1,
+        force_no_dc: bool = True,
     ) -> NoiseMeasurement:
         """
         compute a PSD from a time-series measurement.
@@ -61,11 +66,21 @@ class NoiseMeasurement:
         num_segments : int, optional
             number of segments to cut the signal into. This will trade lower frequency information
             for better variance of the estimated PSD. The default 1 means no cutting.
+        force_no_dc : bool, optional
+            take out the DC component (0-frequency) of each segement after segmentation
         """
         signal = np.asanyarray(signal)
         signal_segments = segments(signal, num_segments)
+        if force_no_dc:
+            signal_segments = (signal_segments.T - signal_segments.mean(axis=1)).T
         n = signal_segments.shape[-1]
-        window_arr = cls._window_functions[window](n)
+        try:
+            window_arr = cls._window_functions[window](n)
+        except KeyError:
+            raise ValueError(
+                f"window function {window!r} not found. "
+                f"Possible values are {set(cls._window_functions)}"
+            ) from None
         window_correction = np.sum(window_arr**2) / n
         signal_segments = signal_segments * window_arr