This is an automated email from the git hooks/post-receive script. yoh pushed a commit to annotated tag v0.1 in repository python-mne.
commit 811c2db42f1c2fbbdfb25e5a0cd2aa3f866bff94 Author: Alexandre Gramfort <[email protected]> Date: Wed May 25 14:49:04 2011 -0400 cleanup manual + some examples --- doc/source/manual/browse.rst | 6 ++- examples/inverse/plot_compute_mne_inverse.py | 6 --- ...py => plot_compute_mne_inverse_raw_in_label.py} | 0 examples/inverse/plot_minimum_norm_estimate.py | 54 ---------------------- .../plot_source_space_time_frequency.py | 1 - 5 files changed, 4 insertions(+), 63 deletions(-) diff --git a/doc/source/manual/browse.rst b/doc/source/manual/browse.rst index f93cd6a..37f1e44 100755 --- a/doc/source/manual/browse.rst +++ b/doc/source/manual/browse.rst @@ -1986,7 +1986,8 @@ in this section. Works similarly to ignore except that a mask specifies the trigger channel bits to be included. For example, to look at trigger input lines - one to three only, ignoring others, specify ``mask 7`` (INLINE_EQUATION) + one to three only, ignoring others, specify ``mask 7`` + (:math:`2^0 + 2^1 + 2^2 = 7`). **prevevent <*number*>** @@ -2264,7 +2265,8 @@ epochs to be included in the estimation of the covariance matrix. Works similarly to ignore except that a mask specifies the trigger channel bits to be included. For example, to look at trigger input lines - one to three only, ignoring others, specify ``mask 7`` (INLINE_EQUATION) + one to three only, ignoring others, specify ``mask 7`` + (:math:`2^0 + 2^1 + 2^2 = 7`). **delay <*time / s*>** diff --git a/examples/inverse/plot_compute_mne_inverse.py b/examples/inverse/plot_compute_mne_inverse.py index 141475b..7813f7c 100644 --- a/examples/inverse/plot_compute_mne_inverse.py +++ b/examples/inverse/plot_compute_mne_inverse.py @@ -14,13 +14,10 @@ and stores the solution in stc files for visualisation. print __doc__ -import numpy as np import pylab as pl -import mne from mne.datasets import sample from mne.fiff import Evoked from mne.minimum_norm import apply_inverse, read_inverse_operator -from mne.viz import plot_source_estimate data_path = sample.data_path('..') @@ -48,6 +45,3 @@ pl.plot(1e3 * stc.times, stc.data[::100, :].T) pl.xlabel('time (ms)') pl.ylabel('dSPM value') pl.show() - -# View in 3D -plot_source_estimate(inverse_operator['src'], stc) diff --git a/examples/inverse/plot_minimum_norm_raw_data_in_label.py b/examples/inverse/plot_compute_mne_inverse_raw_in_label.py similarity index 100% rename from examples/inverse/plot_minimum_norm_raw_data_in_label.py rename to examples/inverse/plot_compute_mne_inverse_raw_in_label.py diff --git a/examples/inverse/plot_minimum_norm_estimate.py b/examples/inverse/plot_minimum_norm_estimate.py deleted file mode 100644 index 7c16887..0000000 --- a/examples/inverse/plot_minimum_norm_estimate.py +++ /dev/null @@ -1,54 +0,0 @@ -""" -================================================ -Compute MNE-dSPM inverse solution on evoked data -================================================ - -Compute dSPM inverse solution on MNE evoked dataset -and stores the solution in stc files for visualisation. - -""" - -# Author: Alexandre Gramfort <[email protected]> -# -# License: BSD (3-clause) - -print __doc__ - -import pylab as pl -import mne -from mne.datasets import sample -from mne.fiff import Evoked -from mne.minimum_norm import minimum_norm - -data_path = sample.data_path('..') -fname_fwd = data_path + '/MEG/sample/sample_audvis-meg-eeg-oct-6-fwd.fif' -fname_cov = data_path + '/MEG/sample/sample_audvis-cov.fif' -fname_evoked = data_path + '/MEG/sample/sample_audvis-ave.fif' - -setno = 0 -snr = 3.0 -lambda2 = 1.0 / snr ** 2 -dSPM = True - -# Load data -evoked = Evoked(fname_evoked, setno=setno, baseline=(None, 0)) -forward = mne.read_forward_solution(fname_fwd) -noise_cov = mne.Covariance(fname_cov) - -# Compute whitener from noise covariance matrix -whitener = noise_cov.get_whitener(evoked.info, mag_reg=0.1, - grad_reg=0.1, eeg_reg=0.1, pca=True) -# Compute inverse solution -stc = minimum_norm(evoked, forward, whitener, orientation='loose', - method='dspm', snr=3, loose=0.2) - -# Save result in stc files -stc.save('mne_dSPM_inverse') - -############################################################################### -# View activation time-series -pl.close('all') -pl.plot(1e3 * stc.times, stc.data[::100, :].T) -pl.xlabel('time (ms)') -pl.ylabel('dSPM value') -pl.show() diff --git a/examples/time_frequency/plot_source_space_time_frequency.py b/examples/time_frequency/plot_source_space_time_frequency.py index b7412d8..b5bbcc4 100644 --- a/examples/time_frequency/plot_source_space_time_frequency.py +++ b/examples/time_frequency/plot_source_space_time_frequency.py @@ -18,7 +18,6 @@ import mne from mne import fiff from mne.datasets import sample from mne.minimum_norm import read_inverse_operator, source_induced_power -from mne.viz import plot_source_estimate ############################################################################### # Set parameters -- Alioth's /usr/local/bin/git-commit-notice on /srv/git.debian.org/git/debian-med/python-mne.git _______________________________________________ debian-med-commit mailing list [email protected] http://lists.alioth.debian.org/cgi-bin/mailman/listinfo/debian-med-commit
