diff --git a/fsl/data/featresults.py b/fsl/data/featresults.py
index 9901e55e51a118b9d82347bf86421c019a7bec7e..4d3ae675f55fd62f516e0d0ede4e28b7a3537223 100644
--- a/fsl/data/featresults.py
+++ b/fsl/data/featresults.py
@@ -10,10 +10,13 @@ contents of a FEAT analysis directory.
"""
-import logging
-import glob
-import os.path as op
-import numpy as np
+import logging
+import glob
+import os.path as op
+import numpy as np
+
+import fsl.data.image as fslimage
+import fsl.utils.transform as transform
log = logging.getLogger(__name__)
@@ -197,12 +200,59 @@ def loadClusterResults(featdir, settings, contrast):
An error will be raised if the cluster file cannot be parsed.
"""
+ # Cluster files are named like
+ # 'cluster_zstatX.txt', where
+ # X is the COPE number. And
+ # the ZMax/COG etc coordinates
+ # are usually in voxel coordinates
+ coordXform = np.eye(4)
+ clusterFile = op.join(
+ featdir, 'cluster_zstat{}.txt'.format(contrast + 1))
+
+
+ if not op.exists(clusterFile):
+
+ # If the analysis was performed in standard
+ # space (e.g. a higher level group analysis),
+ # the cluster file will instead be called
+ # 'cluster_zstatX_std.txt', so we'd better
+ # check for that too.
+ clusterFile = op.join(
+ featdir, 'cluster_zstat{}_std.txt'.format(contrast + 1))
+
+ # In higher levle analysis run in some standard
+ # space, the cluster coordinates are in standard
+ # space. We transform them to voxel coordinates.
+ # later on.
+ coordXform = fslimage.Image(
+ getDataFile(featdir),
+ loadData=False).worldToVoxMat.T
+
+ if not op.exists(clusterFile):
+ return None
+
+ log.debug('Loading cluster results for contrast {} from {}'.format(
+ contrast, clusterFile))
+
+ # The cluster.txt file is converted
+ # into a list of Cluster objects,
+ # each of which encapsulates
+ # information about one cluster.
+ class Cluster(object):
+ def __init__(self, **kwargs):
+ for name, val in kwargs.items():
+
+ attrName, atype = colmap[name]
+ if val is not None:
+ val = atype(val)
+
+ setattr(self, attrName, val)
+
# This dict provides a mapping between
- # Cluster object (see below) attribute
- # names, and the corresponding column
- # name in the cluster.txt file. And the
- # value type is thrown in as well, for
- # good measure.
+ # Cluster object attribute names, and
+ # the corresponding column name in the
+ # cluster.txt file. And the value type
+ # is thrown in as well, for good measure.
colmap = {
'Cluster Index' : ('index', int),
'Voxels' : ('nvoxels', int),
@@ -230,51 +280,6 @@ def loadClusterResults(featdir, settings, contrast):
'COPE-MAX Z (mm)' : ('copemaxz', int),
'COPE-MEAN' : ('copemean', float)}
- # The cluster.txt file is converted
- # into a list of Cluster objects,
- # each of which encapsulates
- # information about one cluster.
- #
- # TODO The coordinates (e.g. 'ZMAX X (mm)')
- # for standard space results (in e.g.
- # 'cluster_zstatX_std.txt') are in MNI152
- # space coordinates, and need to be
- # transformed into voxel coordinates. Or a
- # flag needs to be set on the Cluster object
- # so users know that the coordinates are in
- # standard space.
- class Cluster(object):
- def __init__(self, **kwargs):
- for name, val in kwargs.items():
-
- attrName, atype = colmap[name]
- if val is not None:
- val = atype(val)
-
- setattr(self, attrName, val)
-
- # Cluster files are named like
- # 'cluster_zstatX.txt', where
- # X is the COPE number
- clusterFile = op.join(
- featdir, 'cluster_zstat{}.txt'.format(contrast + 1))
-
- if not op.exists(clusterFile):
-
- # If the analysis was performed in standard
- # space (e.g. a higher level group analysis),
- # the cluster file will instead be called
- # cluster_zstatX_std.txt', so we'd better
- # check for that too.
- clusterFile = op.join(
- featdir, 'cluster_zstat{}_std.txt'.format(contrast + 1))
-
- if not op.exists(clusterFile):
- return None
-
- log.debug('Loading cluster results for contrast {} from {}'.format(
- contrast, clusterFile))
-
# An error will be raised if the
# cluster file does not exist (e.g.
# if the specified contrast index
@@ -309,7 +314,23 @@ def loadClusterResults(featdir, settings, contrast):
# are unrecognised (i.e. not in
# the colmap above), or if the
# file is poorly formed.
- return [Cluster(**dict(zip(colNames, cl))) for cl in clusterLines]
+ clusters = [Cluster(**dict(zip(colNames, cl))) for cl in clusterLines]
+
+ # Make sure all coordinates are in voxels -
+ # for first level analyses, the coordXform
+ # will be an identity transform (the coords
+ # are already in voxels). But for higher
+ # level, the coords are in mm, and need to
+ # be transformed to voxels.
+ for c in clusters:
+ c.zmaxx, c.zmaxy, c.zmaxz = transform.transform(
+ [[c.zmaxx, c.zmaxy, c.zmaxz]], coordXform)[0]
+ c.zcogx, c.zcogy, c.zcogz = transform.transform(
+ [[c.zcogx, c.zcogy, c.zcogz]], coordXform)[0]
+ c.copemaxx, c.copemaxy, c.copemaxz = transform.transform(
+ [[c.copemaxx, c.copemaxy, c.copemaxz]], coordXform)[0]
+
+ return clusters
def getDataFile(featdir):
diff --git a/fsl/fslview/views/canvaspanel.py b/fsl/fslview/views/canvaspanel.py
index 6c308e74f5a356dea0b732ba3e930eaa7d6319bb..d275473600c47c61ead4332997c0d820e8336fbd 100644
--- a/fsl/fslview/views/canvaspanel.py
+++ b/fsl/fslview/views/canvaspanel.py
@@ -169,7 +169,7 @@ class CanvasPanel(viewpanel.ViewPanel):
syncOverlayDisplay = props.Boolean(default=True)
movieMode = props.Boolean(default=False)
movieRate = props.Int(minval=100,
- maxval=2000,
+ maxval=1000,
default=250,
clamped=True)