017d156706984b88a524b146ec71415c65b42391,examples/inverse/plot_dics_source_power.py,,,#,25

Before Change


//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
// Reading the raw data:
raw = mne.io.read_raw_fif(raw_fname)
raw.info["bads"] = ["MEG 2443"]  // 1 bad MEG channel

// Set picks
picks = mne.pick_types(raw.info, meg="grad", eeg=False, eog=False,

After Change


//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
// We are interested in the beta band. Define a range of frequencies, using a
// log scale, from 12 to 30 Hz.
freqs = np.logspace(np.log10(12), np.log10(30), 9)

//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
// Computing the cross-spectral density matrix for the beta frequency band, for
// different time intervals. We use a decim value of 20 to speed up the
Italian Trulli
In pattern: SUPERPATTERN

Frequency: 3

Non-data size: 3

Instances


Project Name: mne-tools/mne-python
Commit Name: 017d156706984b88a524b146ec71415c65b42391
Time: 2019-05-14
Author: w.m.vanvliet@gmail.com
File Name: examples/inverse/plot_dics_source_power.py
Class Name:
Method Name:


Project Name: michaelhush/M-LOOP
Commit Name: 667633a06e70183b94fd5b1945ad16ebc78513a3
Time: 2020-12-24
Author: zakven@mit.edu
File Name: mloop/neuralnet.py
Class Name: NeuralNet
Method Name: fit_neural_net


Project Name: nilearn/nilearn
Commit Name: 38b1a68f9f74ebb1a0f8cf2f73a9e606f7c022c2
Time: 2015-07-28
Author: elvis.dohmatob@inria.fr
File Name: nilearn/decoding/tests/test_sklearn_compatibility.py
Class Name:
Method Name: test_get_params