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# -*- coding: utf-8 -*-
#
# Licensed under the terms of the BSD 3-Clause
# (see sigima/LICENSE for details)
"""
Stability analysis functions
============================
This module provides stability analysis functions for signal objects:
- Allan variance and deviation
- Overlapping Allan variance
- Modified Allan variance
- Hadamard variance
- Total variance
.. note::
All operations use functions from :mod:`sigima.tools.signal.stability` for
actual computations.
"""
from __future__ import annotations
import guidata.dataset as gds
import numpy as np
from sigima.config import _
from sigima.objects import SignalObj
from sigima.proc.decorator import computation_function
from sigima.tools.signal import stability
from .base import dst_1_to_1
class AllanVarianceParam(gds.DataSet, title=_("Allan variance")):
"""Allan variance parameters"""
max_tau = gds.IntItem("Max τ", default=100, min=1, unit="pts")
@computation_function()
def allan_variance(src: SignalObj, p: AllanVarianceParam) -> SignalObj:
"""Compute Allan variance with
:py:func:`sigima.tools.signal.stability.allan_variance`.
Args:
src: source signal
p: parameters
Returns:
Result signal object
"""
dst = dst_1_to_1(src, "allan_variance", f"max_tau={p.max_tau}")
x, y = src.get_data()
tau_values = np.arange(1, p.max_tau + 1)
avar = stability.allan_variance(x, y, tau_values)
dst.set_xydata(tau_values, avar)
return dst
@computation_function()
def allan_deviation(src: SignalObj, p: AllanVarianceParam) -> SignalObj:
"""Compute Allan deviation with
:py:func:`sigima.tools.signal.stability.allan_deviation`
Args:
src: source signal
p: parameters
Returns:
Result signal object
"""
dst = dst_1_to_1(src, "allan_deviation", f"max_tau={p.max_tau}")
x, y = src.get_data()
tau_values = np.arange(1, p.max_tau + 1)
adev = stability.allan_deviation(x, y, tau_values)
dst.set_xydata(tau_values, adev)
return dst
@computation_function()
def overlapping_allan_variance(src: SignalObj, p: AllanVarianceParam) -> SignalObj:
"""Compute Overlapping Allan variance.
Args:
src: source signal
p: parameters
Returns:
Result signal object
"""
dst = dst_1_to_1(src, "overlapping_allan_variance", f"max_tau={p.max_tau}")
x, y = src.get_data()
tau_values = np.arange(1, p.max_tau + 1)
oavar = stability.overlapping_allan_variance(x, y, tau_values)
dst.set_xydata(tau_values, oavar)
return dst
@computation_function()
def modified_allan_variance(src: SignalObj, p: AllanVarianceParam) -> SignalObj:
"""Compute Modified Allan variance.
Args:
src: source signal
p: parameters
Returns:
Result signal object
"""
dst = dst_1_to_1(src, "modified_allan_variance", f"max_tau={p.max_tau}")
x, y = src.get_data()
tau_values = np.arange(1, p.max_tau + 1)
mavar = stability.modified_allan_variance(x, y, tau_values)
dst.set_xydata(tau_values, mavar)
return dst
@computation_function()
def hadamard_variance(src: SignalObj, p: AllanVarianceParam) -> SignalObj:
"""Compute Hadamard variance.
Args:
src: source signal
p: parameters
Returns:
Result signal object
"""
dst = dst_1_to_1(src, "hadamard_variance", f"max_tau={p.max_tau}")
x, y = src.get_data()
tau_values = np.arange(1, p.max_tau + 1)
hvar = stability.hadamard_variance(x, y, tau_values)
dst.set_xydata(tau_values, hvar)
return dst
@computation_function()
def total_variance(src: SignalObj, p: AllanVarianceParam) -> SignalObj:
"""Compute Total variance.
Args:
src: source signal
p: parameters
Returns:
Result signal object
"""
dst = dst_1_to_1(src, "total_variance", f"max_tau={p.max_tau}")
x, y = src.get_data()
tau_values = np.arange(1, p.max_tau + 1)
tvar = stability.total_variance(x, y, tau_values)
dst.set_xydata(tau_values, tvar)
return dst
@computation_function()
def time_deviation(src: SignalObj, p: AllanVarianceParam) -> SignalObj:
"""Compute Time Deviation (TDEV).
Args:
src: source signal
p: parameters
Returns:
Result signal object
"""
dst = dst_1_to_1(src, "time_deviation", f"max_tau={p.max_tau}")
x, y = src.get_data()
tau_values = np.arange(1, p.max_tau + 1)
tdev = stability.time_deviation(x, y, tau_values)
dst.set_xydata(tau_values, tdev)
return dst
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