diff --git a/examples/example_ress.ipynb b/examples/example_ress.ipynb index 376a6b40..dafcadef 100644 --- a/examples/example_ress.ipynb +++ b/examples/example_ress.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "metadata": { "collapsed": false }, @@ -20,13 +20,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "metadata": { "collapsed": false }, "outputs": [], "source": [ - "import matplotlib.pyplot as plt\nimport numpy as np\nimport scipy.signal as ss\n\nfrom meegkit import ress\nfrom meegkit.utils import unfold, rms, fold\n\n# import config\n\nnp.random.seed(1)" + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "import scipy.signal as ss\n", + "\n", + "from meegkit import ress\n", + "from meegkit.utils import unfold, rms, fold, snr_spectrum\n", + "\n", + "# import config\n", + "\n", + "np.random.seed(1)" ] }, { @@ -38,11 +47,36 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "metadata": { "collapsed": false }, - "outputs": [], + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "" + ] + }, + "metadata": {}, + "execution_count": 15 + }, + { + "output_type": "display_data", + "data": { + "text/plain": "
", + "image/png": 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\n" + }, + "metadata": { + "image/png": { + "width": 380, + "height": 248 + }, + "needs_background": "light" + } + } + ], "source": [ "n_times = 1000\nn_chans = 10\nn_trials = 50\ntarget = 12\nsfreq = 250\nnoise_dim = 8\nSNR = 1.\nt0 = 100\n\n# source\nsource = np.sin(2 * np.pi * target * np.arange(n_times - t0) / sfreq)[None].T\ns = source * np.random.randn(1, n_chans)\ns = s[:, :, np.newaxis]\ns = np.tile(s, (1, 1, n_trials))\nsignal = np.zeros((n_times, n_chans, n_trials))\nsignal[t0:, :, :] = s\n\n# noise\nnoise = np.dot(\n unfold(np.random.randn(n_times, noise_dim, n_trials)),\n np.random.randn(noise_dim, n_chans))\nnoise = fold(noise, n_times)\n\n# mix signal and noise\nsignal = SNR * signal / rms(signal.flatten())\nnoise = noise / rms(noise.flatten())\ndata = signal + noise\n\n# Plot\nf, ax = plt.subplots(3)\nax[0].plot(signal[:, 0, 0], c='C0', label='source')\nax[1].plot(noise[:, 1, 0], c='C1', label='noise')\nax[2].plot(data[:, 1, 0], c='C2', label='mixture')\nax[0].legend()\nax[1].legend()\nax[2].legend()" ] @@ -56,14 +90,56 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 20, "metadata": { "collapsed": false }, - "outputs": [], + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": "
", + "image/png": 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\n" + }, + "metadata": { + "image/png": { + "width": 388, + "height": 263 + }, + "needs_background": "light" + } + } + ], "source": [ - "# Apply RESS\nout = ress.RESS(data, sfreq=sfreq, peak_freq=target)\n\n# Compute PSD\nnfft = 250\ndf = sfreq / nfft # frequency resolution\nbins, psd = ss.welch(out, sfreq, window=\"hamming\", nperseg=nfft,\n noverlap=125, axis=0)\npsd = psd.mean(axis=1) # average over trials\n\n# Loop over frequencies and compute SNR\nskipbins = 1 # skip bins directly next to frequency of interest\nn_bins = int(3 / df) # number of bins to average over\nsnr = np.zeros(len(bins))\nfor ibin in range(n_bins + 1, len(bins) - n_bins - 1):\n numer = psd[ibin]\n irange = np.r_[np.arange(ibin - n_bins, ibin - skipbins),\n np.arange(ibin + skipbins + 1, ibin + n_bins)]\n denom = np.mean(psd[irange])\n snr[ibin] = numer / denom # divide amplitude at peak by neighbours\n\nf, ax = plt.subplots(1)\nax.plot(bins, snr, 'o')\nax.axvline(target, ls=':', c='grey', zorder=0)\nax.set_ylabel('SNR (a.u.)')\nax.set_xlabel('Frequency (Hz)')\nax.set_xlim([0, 40])\nplt.show()" + "# Apply RESS\n", + "out = ress.RESS(data, sfreq=sfreq, peak_freq=target)\n", + "\n", + "# Compute PSD\n", + "nfft = 250\n", + "df = sfreq / nfft # frequency resolution\n", + "bins, psd = ss.welch(out, sfreq, window=\"hamming\", nperseg=nfft,\n", + " noverlap=125, axis=0)\n", + "psd = psd.mean(axis=1, keepdims=True) # average over trials\n", + "snr = snr_spectrum(psd, bins, skipbins=2, n_avg=2)\n", + "\n", + "f, ax = plt.subplots(1)\n", + "ax.plot(bins, snr, 'o', label='SNR')\n", + "ax.plot(bins[bins == target], snr[bins == target], 'ro', label='Target SNR')\n", + "ax.axhline(1, ls=':', c='grey', zorder=0)\n", + "ax.axvline(target, ls=':', c='grey', zorder=0)\n", + "ax.set_ylabel('SNR (a.u.)')\n", + "ax.set_xlabel('Frequency (Hz)')\n", + "ax.set_xlim([0, 40])\n", + "ax.legend()\n", + "plt.show()" ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { @@ -82,7 +158,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.7" + "version": "3.7.7-final" } }, "nbformat": 4, diff --git a/examples/example_ress.py b/examples/example_ress.py index 081961c2..c7c1b720 100644 --- a/examples/example_ress.py +++ b/examples/example_ress.py @@ -14,7 +14,7 @@ import scipy.signal as ss from meegkit import ress -from meegkit.utils import unfold, rms, fold +from meegkit.utils import unfold, rms, fold, snr_spectrum # import config @@ -73,21 +73,13 @@ df = sfreq / nfft # frequency resolution bins, psd = ss.welch(out, sfreq, window="hamming", nperseg=nfft, noverlap=125, axis=0) -psd = psd.mean(axis=1) # average over trials - -# Loop over frequencies and compute SNR -skipbins = 1 # skip bins directly next to frequency of interest -n_bins = int(3 / df) # number of bins to average over -snr = np.zeros(len(bins)) -for ibin in range(n_bins + 1, len(bins) - n_bins - 1): - numer = psd[ibin] - irange = np.r_[np.arange(ibin - n_bins, ibin - skipbins), - np.arange(ibin + skipbins + 1, ibin + n_bins)] - denom = np.mean(psd[irange]) - snr[ibin] = numer / denom # divide amplitude at peak by neighbours +psd = psd.mean(axis=1, keepdims=True) # average over trials +snr = snr_spectrum(psd, bins, skipbins=2, n_avg=2) f, ax = plt.subplots(1) -ax.plot(bins, snr, 'o') +ax.plot(bins, snr, 'o', label='SNR') +ax.plot(bins[bins == target], snr[bins == target], 'ro', label='Target SNR') +ax.axhline(1, ls=':', c='grey', zorder=0) ax.axvline(target, ls=':', c='grey', zorder=0) ax.set_ylabel('SNR (a.u.)') ax.set_xlabel('Frequency (Hz)') diff --git a/meegkit/utils/stats.py b/meegkit/utils/stats.py index 6c1ba742..5f9195a9 100644 --- a/meegkit/utils/stats.py +++ b/meegkit/utils/stats.py @@ -287,7 +287,7 @@ def snr_spectrum(data, freqs, n_avg=1, n_harm=1, skipbins=1): Parameters ---------- - data : ndarray , shape=([n_trials, ]n_chans, n_freqs) + data : ndarray , shape=(n_freqs, n_chans, [n_trials, ]) Power spectrum. freqs : array, shape=(n_freqs,) Frequency bins. @@ -316,19 +316,19 @@ def snr_spectrum(data, freqs, n_avg=1, n_harm=1, skipbins=1): """ if data.ndim == 3: - n_trials = data.shape[0] + n_freqs = data.shape[0] n_chans = data.shape[1] - n_freqs = data.shape[-1] + n_trials = data.shape[-1] elif data.ndim == 2: n_trials = 1 - n_chans = data.shape[0] - n_freqs = data.shape[-1] + n_freqs = data.shape[0] + n_chans = data.shape[1] else: - raise ValueError('Data must have shape (n_trials, n_chans, n_freqs)' - ' or (n_chans, n_freqs)') + raise ValueError('Data must have shape (n_freqs, n_chans, [n_trials,])' + f', got {data.shape}') # Number of points to get desired resolution - data = np.reshape(data, (n_trials * n_chans, n_freqs)) + data = np.reshape(data, (n_freqs, n_chans * n_trials)) SNR = np.zeros_like(data) for i_bin in range(n_freqs): @@ -351,12 +351,12 @@ def snr_spectrum(data, freqs, n_avg=1, n_harm=1, skipbins=1): # Now get indices of noise (i.e., neighbouring FFT bins) # eg if currentbin=54, navg=3, skipbins=1 : # bin_noise = 51, 52, 56, 57 - tmp = np.stack((np.arange(bin_peaks[h] - skipbins - n_avg, - bin_peaks[h] - skipbins), - np.arange(bin_peaks[h] + skipbins + 1, - bin_peaks[h] + skipbins + 1 + n_avg) - )) - tmp = tmp.flatten().astype(int) + tmp = np.r_[ + (np.arange(bin_peaks[h] - skipbins - n_avg, + bin_peaks[h] - skipbins), + np.arange(bin_peaks[h] + skipbins + 1, + bin_peaks[h] + skipbins + 1 + n_avg))] + tmp = tmp.astype(int) # Remove impossible bin values (eg <1 or >n_samp) tmp = [t for t in tmp if t >= 0 and t < n_freqs] @@ -369,24 +369,16 @@ def snr_spectrum(data, freqs, n_avg=1, n_harm=1, skipbins=1): for i_trial in range(n_trials * n_chans): # RMS of signal over fundamental+harmonics - A = data[i_trial, bin_peaks] + A = data[bin_peaks, i_trial] # Noise around fundamental+harmonics B = np.zeros(len(bin_noise)) for h in range(len(B)): - - if n_trials > 1: - # Mean over samples and median over trials - B[h] = np.median(np.mean(data[i_trial::n_chans, - bin_noise[h]], - 1)) - else: - # Mean over samples - B[h] = np.mean(data[i_trial, bin_noise[h]]) + B[h] = np.mean(data[bin_noise[h], i_trial::n_trials].flatten()) # Ratio with np.errstate(divide='ignore', invalid='ignore'): - SNR[i_trial, i_bin] = np.sqrt(np.sum(A)) / np.sqrt(np.sum(B)) + SNR[i_bin, i_trial] = np.sqrt(np.sum(A)) / np.sqrt(np.sum(B)) SNR[np.abs(SNR) == np.inf] = 1 SNR[SNR == 0] = 1 SNR[np.isnan(SNR)] = 1 @@ -396,6 +388,6 @@ def snr_spectrum(data, freqs, n_avg=1, n_harm=1, skipbins=1): # Reshape matrix if necessary if np.min((n_trials, n_chans)) > 1: - SNR = np.reshape(SNR, (n_trials, n_chans, n_freqs)) + SNR = np.reshape(SNR, (n_freqs, n_chans, n_trials)) return SNR diff --git a/tests/test_ress.py b/tests/test_ress.py index 385f664b..9760799a 100644 --- a/tests/test_ress.py +++ b/tests/test_ress.py @@ -4,8 +4,7 @@ import pytest import scipy.signal as ss from meegkit import ress -from meegkit.utils import fold, rms, unfold -from numpy.testing import assert_allclose +from meegkit.utils import fold, rms, unfold, snr_spectrum def create_data(n_times, n_chans=10, n_trials=50, freq=12, sfreq=250, @@ -56,31 +55,22 @@ def test_ress(target, n_trials, show=False): """Test RESS.""" sfreq = 250 data, source = create_data(n_times=1000, n_trials=n_trials, freq=target, - sfreq=sfreq, show=show) + sfreq=sfreq, show=False) out = ress.RESS(data, sfreq=sfreq, peak_freq=target) nfft = 250 - df = sfreq / nfft # frequency resolution bins, psd = ss.welch(out, sfreq, window="hamming", nperseg=nfft, noverlap=125, axis=0) - psd = psd.mean(axis=1) # average over trials - skipbins = 1 # .5 Hz, hard-coded! - n_bins = int(3 / df) # 2 Hz - - # loop over frequencies and compute SNR - snr = np.zeros(len(bins)) - for ibin in range(n_bins + 1, len(bins) - n_bins - 1): - numer = psd[ibin] - irange = np.r_[np.arange(ibin - n_bins, ibin - skipbins), - np.arange(ibin + skipbins + 1, ibin + n_bins)] - denom = np.mean(psd[irange]) - snr[ibin] = numer / denom + print(psd.shape) + psd = psd.mean(axis=1, keepdims=True) # average over trials + snr = snr_spectrum(psd, bins, skipbins=2, n_avg=2) if show: f, ax = plt.subplots(1) ax.plot(bins, snr, 'o') + ax.axhline(1, ls=':', c='grey', zorder=0) ax.axvline(target, ls=':', c='grey', zorder=0) ax.set_ylabel('SNR (a.u.)') ax.set_xlabel('Frequency (Hz)') @@ -93,4 +83,5 @@ def test_ress(target, n_trials, show=False): if __name__ == '__main__': import pytest - pytest.main([__file__]) + # pytest.main([__file__]) + test_ress(12, 10, show=True)