[med-svn] [python-mne] 14/376: reading stc files

[Yaroslav Halchenko]

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yoh pushed a commit to annotated tag v0.1
in repository python-mne.

commit 9072d39629f84f6c107c66d9711d5be350264dc0
Author: Alexandre Gramfort <alexandre.gramfort at inria.fr>
Date:   Wed Dec 29 18:38:48 2010 -0500

    reading stc files
---
 examples/read_cov.py    | 12 ++++++++---
 examples/read_events.py |  5 +----
 examples/read_evoked.py |  3 +--
 examples/read_raw.py    |  1 -
 examples/read_stc.py    | 18 +++++++++++++++++
 fiff/__init__.py        |  1 +
 fiff/stc.py             | 53 +++++++++++++++++++++++++++++++++++++++++++++++++
 7 files changed, 83 insertions(+), 10 deletions(-)

diff --git a/examples/read_cov.py b/examples/read_cov.py
index ee771f1..30f2406 100644
--- a/examples/read_cov.py
+++ b/examples/read_cov.py
@@ -1,14 +1,20 @@
-import pylab as pl
+"""Reading a noise covariance matrix
+"""
+print __doc__
+
 import fiff
 
-fname = 'sm02a1-cov.fif'
+fname = 'MNE-sample-data/MEG/sample/sample_audvis-cov.fif'
 
 fid, tree, _ = fiff.fiff_open(fname)
 
 cov_type = 1
 cov = fiff.read_cov(fid, tree, cov_type)
 
-print "cov size: %s x %s" % cov['data'].shape
+print "covariance matrix size: %s x %s" % cov['data'].shape
 
+###############################################################################
+# Show covariance
+import pylab as pl
 pl.matshow(cov['data'])
 pl.show()
diff --git a/examples/read_events.py b/examples/read_events.py
index 1bcab5f..4781ad1 100644
--- a/examples/read_events.py
+++ b/examples/read_events.py
@@ -2,19 +2,16 @@
 """
 print __doc__
 
-import pylab as pl
 import fiff
 
 fname = 'MNE-sample-data/MEG/sample/sample_audvis_raw-eve.fif'
-# fname = 'sm02a5_raw.fif'
 
 event_list = fiff.read_events(fname)
 
 ###############################################################################
 # Show MEG data
+import pylab as pl
 pl.plot(times, data.T)
 pl.xlabel('time (ms)')
 pl.ylabel('MEG data (T)')
 pl.show()
-
-
diff --git a/examples/read_evoked.py b/examples/read_evoked.py
index d26e4c2..8fe664f 100644
--- a/examples/read_evoked.py
+++ b/examples/read_evoked.py
@@ -4,8 +4,7 @@ print __doc__
 
 import fiff
 
-fname = 'sm02a1-ave.fif'
-# fname = 'MNE-sample-data/MEG/sample/sample_audvis-ave.fif'
+fname = 'MNE-sample-data/MEG/sample/sample_audvis-ave.fif'
 
 data = fiff.read_evoked(fname)
 
diff --git a/examples/read_raw.py b/examples/read_raw.py
index 08c135d..80666c9 100644
--- a/examples/read_raw.py
+++ b/examples/read_raw.py
@@ -6,7 +6,6 @@ import pylab as pl
 import fiff
 
 fname = 'MNE-sample-data/MEG/sample/sample_audvis_raw.fif'
-# fname = 'sm02a5_raw.fif'
 
 raw = fiff.setup_read_raw(fname)
 
diff --git a/examples/read_stc.py b/examples/read_stc.py
new file mode 100644
index 0000000..f1a8573
--- /dev/null
+++ b/examples/read_stc.py
@@ -0,0 +1,18 @@
+"""Reading a raw file segment
+"""
+print __doc__
+
+import fiff
+
+# fname = 'MNE-sample-data/MEG/sample/sample_audvis_raw.fif'
+fname = 'hk_ret12_offl-7-meg-snr-3-spm-rh.stc'
+
+stc = fiff.read_stc(fname)
+
+n_vertices, n_samples = stc['data'].shape
+print "tmin : %s (s)" % stc['tmin']
+print "tstep : %s" % stc['tstep']
+print "tmax : %s (s)" % (stc['tmin'] + stc['tstep'] * n_samples)
+print "stc data size: %s (nb of vertices) x %s (nb of samples)" % (
+                                                    n_vertices, n_samples)
+
diff --git a/fiff/__init__.py b/fiff/__init__.py
index a7c32eb..10b382e 100644
--- a/fiff/__init__.py
+++ b/fiff/__init__.py
@@ -7,4 +7,5 @@ from .cov import read_cov
 from .raw import setup_read_raw, read_raw_segment, read_raw_segment_times
 from .event import read_events
 from .forward import read_forward_solution
+from .stc import read_stc
 
diff --git a/fiff/stc.py b/fiff/stc.py
new file mode 100644
index 0000000..9c10f24
--- /dev/null
+++ b/fiff/stc.py
@@ -0,0 +1,53 @@
+import numpy as np
+
+
+def read_stc(filename):
+    """
+    %
+    % [stc] = mne_read_stc_file(filename)
+    %
+    % Reads an stc file. The returned structure has the following fields
+    %
+    %     tmin           The first time point of the data in seconds
+    %     tstep          Time between frames in seconds
+    %     vertices       vertex indices (0 based)
+    %     data           The data matrix (nvert * ntime)
+    %
+    %
+    """
+
+    fid = open(filename, 'rb')
+
+    stc = dict()
+
+    fid.seek(0, 2) # go to end of file
+    file_length = fid.tell()
+    fid.seek(0, 0) # go to beginning of file
+
+    # read tmin in ms
+    stc['tmin'] = float(np.fromfile(fid, dtype=">f4", count=1))
+    stc['tmin'] /= 1000.0
+
+    # read sampling rate in ms
+    stc['tstep'] = float(np.fromfile(fid, dtype=">f4", count=1))
+    stc['tstep'] /= 1000.0
+
+    # read number of vertices/sources
+    vertices_n = np.fromfile(fid, dtype=">I4", count=1)
+
+    # read the source vector
+    stc['vertices'] = np.fromfile(fid, dtype=">I4", count=vertices_n)
+
+    # read the number of timepts
+    data_n = np.fromfile(fid, dtype=">I4", count=1)
+
+    if ((file_length/4 -4 - vertices_n) % (data_n*vertices_n)) != 0:
+        raise ValueError, 'incorrect stc file size'
+
+    # read the data matrix
+    stc['data'] = np.fromfile(fid, dtype=">f4", count=vertices_n*data_n)
+    stc['data'] = stc['data'].reshape([data_n, vertices_n]).T
+
+    # close the file
+    fid.close()
+    return stc

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