noise improvements

src/scgenerator/noise.py

@@ -96,6 +96,7 @@ class NoiseMeasurement:
         phase = math.mean_angle(psd)
         psd = psd.real**2 + psd.imag**2
         psd[..., 1:-1] *= 2
+
         return cls(freq, psd.mean(axis=0) / window_correction, phase=phase)
 
     def plottable(

src/scgenerator/spectra.py

@@ -149,6 +149,9 @@ class Spectrum(np.ndarray):
         return self * np.exp(-(((self.l - pos) / (pulse.fwhm_to_T0_fac["gaussian"] * width)) ** 2))
 
     def measure(self) -> tuple[float, float, float]:
+        """returns fwhm, peak power and energy"""
+        if self.ndim > 1:
+            return np.asarray([p.measure() for p in self]).T
         return pulse.measure_field(self.t, self.time_amp)
 
     def coherence(self, axis: int = 0) -> np.ndarray:

tests/test_noise.py

@@ -55,6 +55,20 @@ def test_time_and_back():
     assert new_noise.psd == pytest.approx(noise.psd)
 
 
+def test_nyquist():
+    """
+    generating a time series and tranforming it back yields the same spectrum.
+    Using segements, the nyquist frequency at least is the same
+    """
+    signal = np.cos(np.arange(1024) * np.pi)
+
+    n1 = sc.noise.NoiseMeasurement.from_time_series(signal, 1, None, 1)
+    n3 = sc.noise.NoiseMeasurement.from_time_series(signal, 1, None, 3)
+    n15 = sc.noise.NoiseMeasurement.from_time_series(signal, 1, None, 15)
+
+    assert n1.psd[-1] == n3.psd[-1] == n15.psd[-1]
+
+
 def test_sampling():
     f = np.geomspace(10, 2e6, 138)
     spec = 1 / (f + 1)