[med-svn] [python-mne] 89/376: ENH : handling EEG layout files

[Yaroslav Halchenko]

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

commit f9defd671ce71fff51b83df4adc8507ee0b1b257
Author: Alexandre Gramfort <alexandre.gramfort at inria.fr>
Date:   Sun Feb 20 11:04:03 2011 -0500

    ENH : handling EEG layout files
---
 mne/layouts/layout.py | 20 ++++++++++++++------
 1 file changed, 14 insertions(+), 6 deletions(-)

diff --git a/mne/layouts/layout.py b/mne/layouts/layout.py
index 8eac6b4..d205e38 100644
--- a/mne/layouts/layout.py
+++ b/mne/layouts/layout.py
@@ -6,14 +6,18 @@ import pylab as pl
 
 class Layout(object):
     """Sensor layouts"""
-    def __init__(self, kind='Vectorview-all'):
+    def __init__(self, kind='Vectorview-all', path=None):
         """
         Parameters
         ----------
         kind : 'Vectorview-all' | 'CTF-275' | 'Vectorview-grad' | 'Vectorview-mag'
-            Type of layout
+            Type of layout (can also be custom for EEG)
+        path : string
+            Path to folder where to find the layout file.
         """
-        lout_fname = op.join(op.dirname(__file__), kind + '.lout')
+        if path is None:
+            path = op.dirname(__file__)
+        lout_fname = op.join(path, kind + '.lout')
 
         f = open(lout_fname)
         f.readline() # skip first line
@@ -22,8 +26,12 @@ class Layout(object):
         pos = []
 
         for line in f:
-            _, x, y, dx, dy, chkind, nb = line.split()
-            name = chkind + ' ' + nb
+            splits = line.split()
+            if len(splits) == 7:
+                _, x, y, dx, dy, chkind, nb = splits
+                name = chkind + ' ' + nb
+            else:
+                _, x, y, dx, dy, name = splits
             pos.append(np.array([x, y, dx, dy], dtype=np.float))
             names.append(name)
 
@@ -31,7 +39,7 @@ class Layout(object):
         pos[:, 0] -= np.min(pos[:, 0])
         pos[:, 1] -= np.min(pos[:, 1])
 
-        scaling = max(np.max(pos[:, 0]), np.max(pos[:, 1]))
+        scaling = max(np.max(pos[:, 0]), np.max(pos[:, 1])) + pos[0, 2]
         pos /= scaling
         pos[:,:2] += 0.03
         pos[:,:2] *= 0.97 / 1.03

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