Remove old signal tool
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1 changed files with 0 additions and 275 deletions
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from __future__ import annotations
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from numpy.typing import ArrayLike, NDArray
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from backscattering_analyzer.settings import Settings
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from backscattering_analyzer import interpolate
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from scipy.signal import welch, detrend
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from scipy.fft import irfft, rfft, rfftfreq
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from scipy.interpolate import CubicSpline
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from numpy import logical_and, where, sin, cos, array, sqrt, float64
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class Signal:
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"""
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A given signal, with its time/frequency coordinates
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"""
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def __init__(
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self,
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x: NDArray[float64],
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value: NDArray[float64],
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settings: Settings,
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) -> None:
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if x.shape != value.shape:
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raise Exception(
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"x and y does not have the same dimension ({x} and {y})".format(
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x=x.shape, y=value.shape
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)
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)
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self.sampling = x[1] - x[0]
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self.rate = 1 / self.sampling
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self.x = x
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self.frequencies = self.x # alias
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self.time = self.x # alias
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self.y = value
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self.value = self.y # alias
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self.settings = settings
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self.length = value.shape[0]
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def psd(self, fft_length: int = 10) -> Signal:
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"""
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Compute psd of a given signal
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"""
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self.settings.log("computing psd of the signal")
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return Signal(
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*welch(
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self.value,
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self.rate,
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nperseg=int(fft_length * self.rate),
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detrend="linear",
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),
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self.settings,
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)
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def sqrt(self) -> Signal:
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""" """
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return Signal(
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self.x,
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sqrt(self.y),
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self.settings,
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)
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def detrend(self, type: str = "linear") -> Signal:
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"""
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Short alias for scipy.detrend with default value
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"""
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return Signal(
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self.x,
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detrend(self.y, type=type),
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self.settings,
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)
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def cut_x(self, start: float, end: float) -> Signal:
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"""
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Cut signal from a start value to an end value
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"""
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indexes = where(logical_and(self.x > start, self.x < end))
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return Signal(
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self.x[indexes],
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self.y[indexes],
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self.settings,
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)
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def low_pass_filter(self, cutoff: float) -> Signal:
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"""
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Cut higher frequencies than cutoff for this signal
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"""
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self.settings.log("filtering with a low pass filter")
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freq_x = rfftfreq(self.length, self.sampling)
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freq_y = rfft(self.y)
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index_to_remove = where(abs(freq_x) > cutoff)
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freq_y[index_to_remove] = 0
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y = irfft(freq_y)
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signal = Signal(
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self.x[: len(y)],
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y[: len(self.x)],
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self.settings,
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)
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return signal
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def plot(self) -> None:
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"""
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Plot the signal
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"""
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import matplotlib.pyplot as plt
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plt.plot(self.x, self.y)
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plt.show()
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def abs(self) -> Signal:
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"""
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Abs of the signal (alias)
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"""
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return self.__abs__()
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def cos(self) -> Signal:
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"""
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Cosinus of the signal (hacky way)
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"""
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return Signal(
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self.x,
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cos(self.y),
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self.settings,
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)
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def sin(self) -> Signal:
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"""
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Sinus of the signal (hacky way)
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"""
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return Signal(
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self.x,
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sin(self.y),
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self.settings,
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)
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def spline(self) -> CubicSpline:
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"""
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Return interpolation of this signal
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"""
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return CubicSpline(
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self.x,
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self.y,
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)
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def __sub__(self, other: ArrayLike | Signal) -> Signal:
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"""
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Substract float or a signal to another
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"""
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if isinstance(other, Signal):
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if len(other) != len(self):
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signal_1, signal_2 = interpolate((self, other))
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else:
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signal_1, signal_2 = self, other
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return Signal(
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signal_1.frequencies,
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signal_2.y - signal_1.y,
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self.settings,
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)
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else:
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return Signal(
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self.x,
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self.y - other,
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self.settings,
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)
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def __add__(self, other: ArrayLike | Signal) -> Signal:
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"""
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Add a float or a signal to another
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"""
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if isinstance(other, Signal):
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if len(other) != len(self):
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signal_1, signal_2 = interpolate((self, other))
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else:
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signal_1, signal_2 = self, other
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return Signal(
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signal_1.x,
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signal_1.y + signal_2.y,
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self.settings,
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)
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else:
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return Signal(
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self.x,
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self.y + other,
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self.settings,
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)
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def __mul__(self, other: ArrayLike | Signal) -> Signal:
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"""
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Multiply a signal by a value or another signal
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"""
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if isinstance(other, Signal):
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if len(other) != len(self):
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signal_1, signal_2 = interpolate((self, other))
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else:
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signal_1, signal_2 = self, other
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return Signal(
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signal_1.frequencies,
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signal_1.y * signal_2.y,
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self.settings,
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)
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else:
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return Signal(
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self.x,
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other * self.y,
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self.settings,
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)
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def __truediv__(self, other: ArrayLike | Signal) -> Signal:
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"""
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Divide a signal by a value
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"""
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if isinstance(other, Signal):
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if len(other) != len(self):
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signal_1, signal_2 = interpolate((self, other))
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else:
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signal_1, signal_2 = self, other
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return Signal(
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signal_1.frequencies,
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signal_1.y / signal_2.y,
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self.settings,
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)
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else:
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return Signal(
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self.x,
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self.y / other,
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self.settings,
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)
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def __array__(self) -> NDArray[float64]:
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"""
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Convert to a numpy array
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"""
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return array(
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[
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self.x,
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self.y,
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]
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)
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def __abs__(self) -> Signal:
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"""
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Absolute value of the signal
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"""
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return Signal(
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self.x,
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abs(self.y),
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self.settings,
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)
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def __getitem__(self, key: int) -> float64:
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"""
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Get an element of the signal
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"""
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return self.y[key]
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def __len__(self) -> int:
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"""
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Get length of a signal
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"""
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return len(self.x)
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def __pow__(self, other: float | int) -> Signal:
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"""
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Signal put to power
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"""
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return Signal(
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self.x,
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self.y**other,
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self.settings,
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)
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