removed dataclass from NoiesMeasurement

src/scgenerator/noise.py

@@ -1,6 +1,5 @@
 from __future__ import annotations
 
-from dataclasses import dataclass, field
 from typing import Self, Sequence
 
 import numpy as np
@@ -10,11 +9,28 @@ from scipy.integrate import cumulative_trapezoid
 from scgenerator import math, units
 
 
-@dataclass
 class NoiseMeasurement:
     freq: np.ndarray
     psd: np.ndarray
-    rng: np.random.Generator = field(default_factory=np.random.default_rng)
+    rng: np.random.Generator
+
+    def __init__(
+        self, freq: np.ndarray, psd: np.ndarray, rng: np.random.Generator | int | None = None
+    ):
+        if freq.ndim > 1:
+            raise TypeError(f"freq must be 1 dim, got {freq.shape}")
+        elif psd.shape[-1] != freq.shape[-1]:
+            raise TypeError(
+                "last axis of psd must be of same len as freq, "
+                f"got {psd.shape[-1]} and {freq.shape[-1]}"
+            )
+
+        if rng is None or isinstance(rng, int):
+            rng = np.random.default_rng(rng)
+
+        self.freq = freq
+        self.psd = psd
+        self.rng = rng
 
     @classmethod
     def from_dBc(cls, freq: np.ndarray, psd_dBc: np.ndarray) -> NoiseMeasurement:
@@ -194,12 +210,14 @@ class NoiseMeasurement:
             interp = np.interp(f, self.freq, self.psd, left=left, right=self.psd[-1])
         return f, interp
 
-    def resampled(self, nf: int, dt: float | None = None, log_mode: bool = False) -> Self:
-        return self.__class__(*self.sample_spectrum(nf, dt, log_mode))
+    def resampled(
+        self, nf: int, dt: float | None = None, log_mode: bool = False, left: float | None = None
+    ) -> Self:
+        return self.__class__(*self.sample_spectrum(nf, dt, log_mode, left))
 
     def time_series(
         self,
-        nf: int,
+        nf: int | None = None,
         nseg: int = 1,
         dt: float | None = None,
         log_mode: bool = False,
@@ -209,8 +227,9 @@ class NoiseMeasurement:
 
         Parameters
         ----------
-        nf : int
-            number of frequency points to sample. Recommended is a power of 2 + 1 (129, 513, ...)
+        nf : int | None, optional
+            number of frequency points to sample. if None (default), will sample len(self.freq)
+            Recommended is a power of 2 + 1 (129, 513, ...)
         nseg : int | None,
             number of times to sample the spectrum, each time with a different random phase
         dt : float | None, optional
@@ -218,6 +237,7 @@ class NoiseMeasurement:
         log_mode : bool, optional
             sample on a log-log scale rather than on a linear scale, by default False
         """
+        nf = nf or len(self.freq)
 
         freq, amp = self.sample_spectrum(nf, dt, log_mode, left=0)
         fs = freq[-1] * 2