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        "\n# Compute real-time power spectrum density with FieldTrip client\n\n\nPlease refer to `ftclient_rt_average.py` for instructions on\nhow to get the FieldTrip connector working in MNE-Python.\n\nThis example demonstrates how to use it for continuous\ncomputation of power spectra in real-time using the\nget_data_as_epoch function.\n\n\n"
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      "source": [
        "# Author: Mainak Jas <mainak@neuro.hut.fi>\n#\n# License: BSD (3-clause)\n\nimport numpy as np\nimport matplotlib.pyplot as plt\n\nimport mne\nfrom mne.realtime import FieldTripClient\nfrom mne.time_frequency import psd_welch\n\nprint(__doc__)\n\n# user must provide list of bad channels because\n# FieldTrip header object does not provide that\nbads = ['MEG 2443', 'EEG 053']\n\nfig, ax = plt.subplots(1)\nwith FieldTripClient(host='localhost', port=1972,\n                     tmax=150, wait_max=10) as rt_client:\n\n    # get measurement info guessed by MNE-Python\n    raw_info = rt_client.get_measurement_info()\n\n    # select gradiometers\n    picks = mne.pick_types(raw_info, meg='grad', eeg=False, eog=True,\n                           stim=False, include=[], exclude=bads)\n\n    n_fft = 256  # the FFT size. Ideally a power of 2\n    n_samples = 2048  # time window on which to compute FFT\n    for ii in range(20):\n        epoch = rt_client.get_data_as_epoch(n_samples=n_samples, picks=picks)\n        psd, freqs = psd_welch(epoch, fmin=2, fmax=200, n_fft=n_fft)\n\n        cmap = 'RdBu_r'\n        freq_mask = freqs < 150\n        freqs = freqs[freq_mask]\n        log_psd = 10 * np.log10(psd[0])\n\n        tmin = epoch.events[0][0] / raw_info['sfreq']\n        tmax = (epoch.events[0][0] + n_samples) / raw_info['sfreq']\n\n        if ii == 0:\n            im = ax.imshow(log_psd[:, freq_mask].T, aspect='auto',\n                           origin='lower', cmap=cmap)\n\n            ax.set_yticks(np.arange(0, len(freqs), 10))\n            ax.set_yticklabels(freqs[::10].round(1))\n            ax.set_xlabel('Frequency (Hz)')\n            ax.set_xticks(np.arange(0, len(picks), 30))\n            ax.set_xticklabels(picks[::30])\n            ax.set_xlabel('MEG channel index')\n            im.set_clim()\n        else:\n            im.set_data(log_psd[:, freq_mask].T)\n\n        plt.title('continuous power spectrum (t = %0.2f sec to %0.2f sec)'\n                  % (tmin, tmax), fontsize=10)\n\n        plt.pause(0.5)\nplt.close()"
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