m-thesis-introduction/simulations/lib/travelsignal.py

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#!/usr/bin/env python3
"""
Define the TravelSignal class.
"""
import numpy as np
import scipy.interpolate as interp
class TravelSignal:
"""
Model an arbitrary digitised signal that can be translated to another position and time.
"""
def __init__(self, signal, sample_rate, t_0 = 0, x_0 = 0, periodic=True, interp1d_kw = None):
"""
Initialise by saving the raw signal
Parameters
----------
signal : arraylike
The raw signal to wrap.
sample_rate : float
Sample rate of the raw signal.
t_0 : float, optional
Time that this signal is sent out.
x_0 : float, optional
Location that this signal is sent out from.
periodic : bool, optional
Translated signal is 0 if it is not periodic
and the time/distance is outside the samples.
interp1d_kw : bool or dict, optional
Use scipy.interpolate's interp1d_kw for interpolation.
Set to True, or a dictionary to enable.
Dictionary will be entered in as **kwargs.
"""
self.raw = signal
self.periodic = periodic
self.sample_rate = sample_rate # Hz
self.sample_length = len(self.raw)
self.time_length = self.sample_length*sample_rate # s
self.x_0 = x_0
self.t_0 = t_0
# choose interpolation method
if not interp1d_kw:
self.interp_f = None
# offload interpolation to scipy.interpolate
else:
interp1d_kw_defaults = {
"copy": False,
"kind": 'linear',
"assume_sorted": True,
"bounds_error": True
}
if self.periodic:
interp1d_kw_defaults['bounds_error'] = False
interp1d_kw_defaults['fill_value'] = (self.raw[-1], self.raw[0])
# merge kwargs
if interp1d_kw is not True:
interp1d_kw = { **interp1d_kw_defaults, **interp1d_kw }
self.interp_f = interp.interp1d(
np.arange(0, self.sample_length),
self.raw,
**interp1d_kw
)
def __len__(self):
return self.sample_length
def __call__(self, t_f = None, x_f = None, **kwargs):
"""
Allow this class to be used as a function.
"""
return self._translate(t_f, x_f, **kwargs)[0]
def _translate(self, t_f = None, x_f = None, t_0 = None, x_0 = None, velocity = None):
"""
Translate the signal from (t_0, x_0) to (t_f, x_f) with optional velocity.
Returns the signal at (t_f, x_f)
"""
if t_0 is None:
t_0 = self.t_0
if velocity is None:
velocity = 1
## spatial offset
if x_f is None:
spatial_time_offset = 0
else:
x_f = np.asarray(x_f)
if x_0 is None:
x_0 = self.x_0
spatial_time_offset = np.sum(np.sqrt( (x_f - x_0)**2 )/velocity)
## temporal offset
if t_f is None:
temporal_time_offset = 0
else:
t_f = np.asarray(t_f)
if t_0 is None:
t_0 = self.t_0
temporal_time_offset = t_f - t_0
# total offset
2022-03-10 14:58:33 +01:00
total_time_offset = temporal_time_offset - spatial_time_offset
n_offset = (total_time_offset * self.sample_rate )
# periodic signal
if self.periodic:
n_offset = n_offset % self.sample_length
# non-periodic and possibly outside the bounds
else:
# this is a numpy array
if hasattr(n_offset, 'ndim') and n_offset.ndim > 0:
mask_idx = np.nonzero( (0 > n_offset) | (n_offset >= self.sample_length) )
n_offset[mask_idx] = 0
# not a numpy array
else:
# outside the bounds
if 0 > n_offset or n_offset > self.sample_length:
n_offset = np.nan
# n_offset is invalid
# set amplitude to zero
if n_offset is np.nan:
amplitude = 0
# n_offset is valid, interpolate the amplitude
else:
# offload to scipy interpolation
if self.interp_f:
amplitude = self.interp_f(n_offset)
# self written linear interpolation
else:
n_offset = np.asarray(n_offset)
n_offset_eps, n_offset_int = np.modf(n_offset)
n_offset_int = n_offset.astype(int)
if True:
amplitude = (1-n_offset_eps) * self.raw[n_offset_int] \
+ n_offset_eps * self.raw[(n_offset_int + 1) % self.sample_length]
# use nearest value instead of interpolation
else:
amplitude = self.raw[n_offset_int]
if not self.periodic:
if hasattr(amplitude, 'ndim'):
amplitude[mask_idx] = 0
return amplitude, total_time_offset
if __name__ == "__main__":
import matplotlib.pyplot as plt
from scipy.stats import norm
sample_rate = 3e2 # Hz
t_offset = 8
periodic = False
time = t_offset + np.arange(0, 1, 1/sample_rate) #s
time2 = t_offset + np.arange(-1.5, 1, 1/sample_rate) #s
signal = norm.pdf(time, time[len(time)//2], (time[-1] - time[0])/10)
mysignal = TravelSignal(signal, sample_rate, t_0 = t_offset, periodic=True)
mysignal2 = TravelSignal(signal, sample_rate, t_0 = t_offset, periodic=False)
fig, ax = plt.subplots(1, 1, figsize=(16,4))
ax.set_title("Raw and TravelSignal")
ax.set_ylabel("Amplitude")
ax.set_xlabel("Time")
ax.plot(time, signal, label='Raw signal')
ax.plot(time2, mysignal(time2)+0.5, '.-', label='TravelSignal(periodic)+0.5')
ax.plot(time2, mysignal2(time2)-0.5, '.-', label='TravelSignal-0.5')
ax.legend()
plt.show();