nbara
commented
3 years ago Hello, you must have overriden the valuesof t in your workspace.
Try replacing the utils.trca.py file with this:
"""TRCA utils."""
import numpy as np
from scipy.signal import filtfilt, cheb1ord, cheby1
from scipy import stats
def round_half_up(num, decimals=0):
"""Round half up round the last decimal of the number.
The rules are:
from 0 to 4 rounds down
from 5 to 9 rounds up
Parameters
----------
num : float
Number to round
decimals : number of decimals
Returns
-------
num rounded
"""
multiplier = 10 ** decimals
return int(np.floor(num * multiplier + 0.5) / multiplier)
def normfit(data, ci=0.95):
"""Compute the mean, std and confidence interval for them.
Parameters
----------
data : array, shape=()
Input data.
ci : float
Confidence interval (default=0.95).
Returns
-------
m : mean
sigma : std deviation
[m - h, m + h] : confidence interval of the mean
[sigmaCI_lower, sigmaCI_upper] : confidence interval of the std
"""
arr = 1.0 * np.array(data)
num = len(arr)
avg, std_err = np.mean(arr), stats.sem(arr)
h_int = std_err * stats.t.ppf((1 + ci) / 2., num - 1)
var = np.var(data, ddof=1)
var_ci_upper = var * (num - 1) / stats.chi2.ppf((1 - ci) / 2, num - 1)
var_ci_lower = var * (num - 1) / stats.chi2.ppf(1 - (1 - ci) / 2, num - 1)
sigma = np.sqrt(var)
sigma_ci_lower = np.sqrt(var_ci_lower)
sigma_ci_upper = np.sqrt(var_ci_upper)
return avg, sigma, [avg - h_int, avg +
h_int], [sigma_ci_lower, sigma_ci_upper]
def itr(n, p, t):
"""Compute information transfer rate (ITR).
Definition in [1]_.
Parameters
----------
n : int
Number of targets.
p : float
Target identification accuracy (0 <= p <= 1).
t : float
Average time for a selection (s).
Returns
-------
itr : float
Information transfer rate [bits/min]
References
----------
.. [1] M. Cheng, X. Gao, S. Gao, and D. Xu,
"Design and Implementation of a Brain-Computer Interface With High
Transfer Rates", IEEE Trans. Biomed. Eng. 49, 1181-1186, 2002.
"""
itr = 0
if (p < 0 or 1 < p):
raise ValueError('Accuracy need to be between 0 and 1.')
elif (p < 1 / n):
raise ValueError('ITR might be incorrect because accuracy < chance')
itr = 0
elif (p == 1):
itr = np.log2(n) * 60 / t
else:
itr = (np.log2(n) + p * np.log2(p) + (1 - p) *
np.log2((1 - p) / (n - 1))) * 60 / t
return itr
def bandpass(eeg, sfreq, Wp, Ws):
"""Filter bank design for decomposing EEG data into sub-band components.
Parameters
----------
eeg : np.array, shape=(n_samples, n_chans[, n_trials])
Training data.
sfreq : int
Sampling frequency of the data.
Wp : 2-tuple
Passband for Chebyshev filter.
Ws : 2-tuple
Stopband for Chebyshev filter.
Returns
-------
y: np.array, shape=(n_trials, n_chans, n_samples)
Sub-band components decomposed by a filter bank.
See Also
--------
scipy.signal.cheb1ord :
Chebyshev type I filter order selection.
"""
# Chebyshev type I filter order selection.
N, Wn = cheb1ord(Wp, Ws, 3, 40, fs=sfreq)
# Chebyshev type I filter design
B, A = cheby1(N, 0.5, Wn, btype="bandpass", fs=sfreq)
# the arguments 'axis=0, padtype='odd', padlen=3*(max(len(B),len(A))-1)'
# correspond to Matlab filtfilt : https://dsp.stackexchange.com/a/47945
y = filtfilt(B, A, eeg, axis=0, padtype='odd',
padlen=3 * (max(len(B), len(A)) - 1))
return y
Hi @gferraro2019, I tried running example_trca.py, and encounter this error: