# -*- coding: utf-8 -*-
import numpy as np
from ..misc import listify
[docs]def signal_simulate(duration=10, sampling_rate=1000, frequency=1, amplitude=0.5, noise=0, silent=False):
"""Simulate a continuous signal.
Parameters
----------
duration : float
Desired length of duration (s).
sampling_rate : int
The desired sampling rate (in Hz, i.e., samples/second).
frequency : float or list
Oscillatory frequency of the signal (in Hz, i.e., oscillations per second).
amplitude : float or list
Amplitude of the oscillations.
noise : float
Noise level (amplitude of the laplace noise).
silent : bool
If False (default), might print warnings if impossible frequencies are queried.
Returns
-------
array
The simulated signal.
Examples
--------
>>> import numpy as np
>>> import pandas as pd
>>> import neurokit2 as nk
>>>
>>> fig = pd.DataFrame({"1Hz": nk.signal_simulate(duration=5, frequency=1),
... "2Hz": nk.signal_simulate(duration=5, frequency=2),
... "Multi": nk.signal_simulate(duration=5, frequency=[0.5, 3], amplitude=[0.5, 0.2])}).plot()
>>> fig #doctest: +SKIP
"""
n_samples = int(np.rint(duration * sampling_rate))
period = 1 / sampling_rate
seconds = np.arange(n_samples) * period
signal = np.zeros(seconds.size)
params = listify(frequency=frequency, amplitude=amplitude)
for i in range(len(params["frequency"])):
freq = params["frequency"][i]
amp = params["amplitude"][i]
# Apply a very conservative Nyquist criterion in order to ensure
# sufficiently sampled signals.
nyquist = sampling_rate * 0.1
if freq > nyquist:
if not silent:
print(
f"NeuroKit warning: Skipping requested frequency"
f" of {freq} Hz since it cannot be resolved at the"
f" sampling rate of {sampling_rate} Hz. Please increase"
f" sampling rate to {freq * 10} Hz or choose frequencies"
f" smaller than or equal to {nyquist} Hz."
)
continue
# Also make sure that at leat one period of the frequency can be
# captured over the duration of the signal.
if (1 / freq) > duration:
if not silent:
print(
f"NeuroKit warning: Skipping requested frequency"
f" of {freq} Hz since it's period of {1 / freq} seconds"
f" exceeds the signal duration of {duration} seconds."
f" Please choose frequencies larger than"
f" {1 / duration} Hz or increase the duration of the"
f" signal above {1 / freq} seconds."
)
continue
signal += _signal_simulate_sinusoidal(x=seconds, frequency=freq, amplitude=amp)
# Add random noise
if noise > 0:
signal += np.random.laplace(0, noise, len(signal))
return signal
# =============================================================================
# Simple Sinusoidal Model
# =============================================================================
def _signal_simulate_sinusoidal(x, frequency=100, amplitude=0.5):
signal = amplitude * np.sin(2 * np.pi * frequency * x)
return signal