diff --git a/fsl/data/featresults.py b/fsl/data/featresults.py
index 719092a03771d78867d36c69ae7d241fa2231b59..138c0379e11563504f39f4aac6ece0cb44db0036 100644
--- a/fsl/data/featresults.py
+++ b/fsl/data/featresults.py
@@ -134,7 +134,7 @@ def loadDesign(featdir):
if line.strip() == '/Matrix':
break
- matrix = np.loadtxt(f)
+ matrix = np.loadtxt(f, ndmin=2)
if matrix is None or matrix.size == 0:
raise RuntimeError('{} does not appear to be a '
diff --git a/fsl/data/melodicimage.py b/fsl/data/melodicimage.py
index 1456386c9689ed78fe4a14e2ca8294b76fbb637a..3a2087da9a028717e832374be773ff89d3d07dfc 100644
--- a/fsl/data/melodicimage.py
+++ b/fsl/data/melodicimage.py
@@ -31,6 +31,7 @@ class MelodicImage(fslimage.Image):
tr
getComponentTimeSeries
numComponents
+ getTopLevelAnalysisDir
getDataFile
"""
@@ -98,6 +99,15 @@ class MelodicImage(fslimage.Image):
return self.shape[3]
+ def getTopLevelAnalysisDir(self):
+ """Returns the top level analysis, if the melodic analysis for this
+ ``MelodicImage`` is contained within another analysis. Otherwise,
+ returnsa ``None``. See the
+ :func:`.melodicresults.getTopLevelAnalysisDir` function.
+ """
+ return melresults.getTopLevelAnalysisDir(self.__meldir)
+
+
def getDataFile(self):
"""Returns the file name of the data image from which this
``MelodicImage`` was generated, if possible. See the
diff --git a/fsl/data/melodicresults.py b/fsl/data/melodicresults.py
index f020003fb06c67c371c91ff0a69f756c35b7ebbf..c31811723bd78e2ce8036072d3c5d3f0e19734d5 100644
--- a/fsl/data/melodicresults.py
+++ b/fsl/data/melodicresults.py
@@ -142,6 +142,10 @@ def getMixFile(meldir):
return op.join(meldir, 'melodic_mix')
+def getReportFile(meldir):
+ pass
+
+
def getNumComponents(meldir):
"""Returns the number of components generated in the melodic analysis
contained in the given directrory.
diff --git a/fsl/data/strings.py b/fsl/data/strings.py
index 27ec5ed61ebbe336a80ad5fae945d5651d4660c7..ba3d4892673728f3355987b81ad0675045178298 100644
--- a/fsl/data/strings.py
+++ b/fsl/data/strings.py
@@ -325,13 +325,17 @@ labels = TypeDict({
'OverlayInfoPanel.Image.transform' : 'Transform/space',
'OverlayInfoPanel.Image.orient' : 'Orientation',
- 'OverlayInfoPanel.Image' : 'NIFTI1 image',
- 'OverlayInfoPanel.FEATImage' : 'NIFTI1 image (FEAT analysis)',
- 'OverlayInfoPanel.FEATImage.featInfo' : 'FEAT information',
- 'OverlayInfoPanel.Model' : 'VTK model',
- 'OverlayInfoPanel.Model.numVertices' : 'Number of vertices',
- 'OverlayInfoPanel.Model.numIndices' : 'Number of indices',
- 'OverlayInfoPanel.dataSource' : 'Data source',
+ 'OverlayInfoPanel.Image' : 'NIFTI1 image',
+ 'OverlayInfoPanel.FEATImage' : 'NIFTI1 image '
+ '(FEAT analysis)',
+ 'OverlayInfoPanel.FEATImage.featInfo' : 'FEAT information',
+ 'OverlayInfoPanel.MelodicImage' : 'NIFTI1 image '
+ '(MELODIC analysis)',
+ 'OverlayInfoPanel.MelodicImage.melodicInfo' : 'MELODIC information',
+ 'OverlayInfoPanel.Model' : 'VTK model',
+ 'OverlayInfoPanel.Model.numVertices' : 'Number of vertices',
+ 'OverlayInfoPanel.Model.numIndices' : 'Number of indices',
+ 'OverlayInfoPanel.dataSource' : 'Data source',
})
@@ -708,4 +712,14 @@ feat = TypeDict({
'numPoints' : 'Number of volumes',
'numEVs' : 'Number of EVs',
'numContrasts' : 'Number of contrasts',
+ 'report' : 'Link to report',
+})
+
+
+melodic = TypeDict({
+ 'dataFile' : 'Data file',
+ 'partOfAnalysis' : 'Part of analysis',
+ 'numComponents' : 'Number of ICs',
+ 'tr' : 'TR time',
+ 'report' : 'Link to report',
})
diff --git a/fsl/fsleyes/colourmaps.py b/fsl/fsleyes/colourmaps.py
index 46e1a2f1b07ceb429367d8cfc18b728280ac1d5f..0589151de45b3242394a6b55c768d8af5991bd9c 100644
--- a/fsl/fsleyes/colourmaps.py
+++ b/fsl/fsleyes/colourmaps.py
@@ -626,7 +626,7 @@ def randomBrightColour():
def randomDarkColour():
"""Generates a random saturated and darkened RGB colour."""
- return applyBricon(randomBrightColour(), 0.25, 0.5)
+ return applyBricon(randomBrightColour(), 0.35, 0.5)
def complementaryColour(rgb):
diff --git a/fsl/fsleyes/controls/overlayinfopanel.py b/fsl/fsleyes/controls/overlayinfopanel.py
index 8f15f85342208b794a0aca449b20e9df794764a2..f44baf5900f0e7b90c77f85db9a6a8b65d74415f 100644
--- a/fsl/fsleyes/controls/overlayinfopanel.py
+++ b/fsl/fsleyes/controls/overlayinfopanel.py
@@ -30,14 +30,15 @@ class OverlayInfoPanel(fslpanel.FSLEyesPanel):
:scale: 50%
:align: center
- Slightly different informtion is shown depending on the overlay type,
+ Slightly different information is shown depending on the overlay type,
and is generated by the following methods:
- =================== ==========================
- :class:`.Image` :meth:`__getImageInfo`
- :class:`.FEATImage` :meth:`__getFEATImageInfo`
- :class:`.Model` :meth:`__getModelInfo`
- =================== ==========================
+ ====================== =============================
+ :class:`.Image` :meth:`__getImageInfo`
+ :class:`.FEATImage` :meth:`__getFEATImageInfo`
+ :class:`.MelodicImage` :meth:`__getMelodicImageInfo`
+ :class:`.Model` :meth:`__getModelInfo`
+ ====================== =============================
"""
@@ -293,6 +294,33 @@ class OverlayInfoPanel(fslpanel.FSLEyesPanel):
return info
+
+ def __getMelodicImageInfo(self, overlay, display):
+ """Creates and returns an :class:`OverlayInfo` object containing
+ information about the given :class:`.MelodicImage` overlay.
+
+ :arg overlay: A :class:`.MelodicImage` instance.
+ :arg display: The :class:`.Display` instance assocated with the
+ ``MelodicImage``.
+ """
+
+ info = self.__getImageInfo(overlay, display)
+
+ melInfo = collections.OrderedDict([
+ ('tr', overlay.tr),
+ ('dataFile', overlay.getDataFile()),
+ ('partOfAnalysis', overlay.getTopLevelAnalysisDir()),
+ ('numComponents', overlay.numComponents()),
+ ])
+
+ secName = strings.labels[self, overlay, 'melodicInfo']
+ info.addSection(secName)
+
+ for k, v in melInfo.items():
+ info.addInfo(strings.melodic[k], v, section=secName)
+
+ return info
+
def __getModelInfo(self, overlay, display):
"""Creates and returns an :class:`OverlayInfo` object containing
diff --git a/fsl/fsleyes/controls/timeserieslistpanel.py b/fsl/fsleyes/controls/timeserieslistpanel.py
index c3d500fb48be3bc98aa70c8d1b0947d43b7ea45d..c211d35b9c7f7d5c0d98ebf94ddf4c53ac4b15c4 100644
--- a/fsl/fsleyes/controls/timeserieslistpanel.py
+++ b/fsl/fsleyes/controls/timeserieslistpanel.py
@@ -183,7 +183,7 @@ class TimeSeriesListPanel(fslpanel.FSLEyesPanel):
copy.setData(*ts.getData())
# This is hacky, and is here in order to
- # make the __onLIstSelect method work.
+ # make the __onListSelect method work.
if isinstance(ts, timeseries.MelodicTimeSeries):
copy.tsLoc = 'volume'
copy.coord = ts.getComponent()
diff --git a/fsl/fsleyes/overlay.py b/fsl/fsleyes/overlay.py
index 62d6c1890340963d47df8ff687d053a4a68d9d83..053801d5f8db5d2e1667920a47045449a2a696af 100644
--- a/fsl/fsleyes/overlay.py
+++ b/fsl/fsleyes/overlay.py
@@ -182,12 +182,12 @@ class OverlayList(props.HasProperties):
return self.overlays.insertAll(index, items)
-def guessDataSourceType(filename):
+def guessDataSourceType(path):
"""A convenience function which, given the name of a file or directory,
figures out a suitable overlay type.
Returns a tuple containing two values - a type which should be able to
- load the filename, and the filename, possibly adjusted. If the file type
+ load the path, and the path itself, possibly adjusted. If the type
is unrecognised, the first tuple value will be ``None``.
"""
@@ -198,30 +198,53 @@ def guessDataSourceType(filename):
import fsl.data.melodicresults as melresults
import fsl.data.featresults as featresults
- filename = op.abspath(filename)
-
- if filename.endswith('.vtk'):
- return fslmodel.Model, filename
-
- else:
- if op.isdir(filename):
- if featresults.isFEATDir(filename):
- return fslfeatimage.FEATImage, filename
- elif melresults.isMelodicDir(filename):
- return fslmelimage.MelodicImage, filename
- else:
-
- try: filename = fslimage.addExt(filename, True)
- except ValueError: return None, filename
+ path = op.abspath(path)
+
+ # VTK files are easy
+ if path.endswith('.vtk'):
+ return fslmodel.Model, path
+
+ # Now, we check to see if the given
+ # path is part of a FEAT or MELODIC
+ # analysis. The way we go about this is
+ # a bit silly, but is necessary due to
+ # the fact thet a melodic analysis can
+ # be contained within a feat analysis
+ # (or another melodic analysis). So we
+ # check for all analysis types and, if
+ # more than one analysis type matches,
+ # we return the one with the longest
+ # path name.
+ analyses = [
+ (fslfeatimage.FEATImage, featresults.getFEATDir( path)),
+ (fslmelimage .MelodicImage, melresults .getMelodicDir(path))]
+
+ # Remove the analysis types that didn't match
+ # (the get*Dir function returned None)
+ analyses = [(t, d) for (t, d) in analyses if d is not None]
+
+ # If we have one or more matches for
+ # an analysis directory, we return
+ # the one with the longest path
+ if len(analyses) > 0:
+
+ dirlens = map(len, [d for (t, d) in analyses])
+ maxidx = dirlens.index(max(dirlens))
+
+ return analyses[maxidx]
- if featresults.isFEATDir(filename):
- return fslfeatimage.FEATImage, filename
- elif melresults.isMelodicDir(filename):
- return fslmelimage.MelodicImage, filename
- else:
- return fslimage.Image, filename
+ # If the path is not an analysis directory,
+ # see if it is a regular nifti image
+ try:
+ path = fslimage.addExt(path, mustExist=True)
+ return fslimage.Image, path
+
+ except ValueError:
+ pass
- return None, filename
+ # Otherwise, I don't
+ # know what to do
+ return None, path
def makeWildcard():
diff --git a/fsl/fsleyes/plotting/timeseries.py b/fsl/fsleyes/plotting/timeseries.py
index 094d450c8106f291ed802f94734940c254193a58..64c1631098279f21448f5f4de1bc096b6ba16545 100644
--- a/fsl/fsleyes/plotting/timeseries.py
+++ b/fsl/fsleyes/plotting/timeseries.py
@@ -26,9 +26,8 @@ import numpy as np
import props
-import dataseries
-import fsl.data.strings as strings
-import fsl.data.melodicimage as fslmelimage
+import dataseries
+import fsl.data.strings as strings
class TimeSeries(dataseries.DataSeries):
@@ -72,8 +71,7 @@ class TimeSeries(dataseries.DataSeries):
def getData(self, xdata=None, ydata=None):
"""Overrides :meth:`.DataSeries.getData`. Returns the data associated
- with this ``TimeSeries`` instance, pre-processed according to the
- current :class:`.TimeSeriesPanel` settings.
+ with this ``TimeSeries`` instance.
The ``xdata`` and ``ydata`` arguments may be used by sub-classes to
override the x/y data in the event that they have already performed
@@ -89,25 +87,7 @@ class TimeSeries(dataseries.DataSeries):
xdata = np.array(xdata, dtype=np.float32)
ydata = np.array(ydata, dtype=np.float32)
-
- if self.tsPanel.usePixdim:
- if isinstance(self.overlay, fslmelimage.MelodicImage):
- xdata *= self.overlay.tr
- else:
- xdata *= self.overlay.pixdim[3]
- if self.tsPanel.plotMode == 'demean':
- ydata = ydata - ydata.mean()
-
- elif self.tsPanel.plotMode == 'normalise':
- ymin = ydata.min()
- ymax = ydata.max()
- ydata = 2 * (ydata - ymin) / (ymax - ymin) - 1
-
- elif self.tsPanel.plotMode == 'percentChange':
- mean = ydata.mean()
- ydata = 100 * (ydata / mean) - 100
-
return xdata, ydata
@@ -503,7 +483,7 @@ class FEATTimeSeries(VoxelTimeSeries):
copenum)
- def __plotPEFitChanged(self, evnum):
+ def __plotPEFitChanged(self, *a):
"""Called when the :attr:`plotPEFits` setting changes.
If necessary, creates and caches one or more
diff --git a/fsl/fsleyes/views/plotpanel.py b/fsl/fsleyes/views/plotpanel.py
index 0a64d0e59dd5dcafbdf053cb7f0783f3806eb696..e80aa4b782ebd24f5dc04a026b658effb3eac796 100644
--- a/fsl/fsleyes/views/plotpanel.py
+++ b/fsl/fsleyes/views/plotpanel.py
@@ -355,13 +355,16 @@ class PlotPanel(viewpanel.ViewPanel):
self.Refresh()
- def drawDataSeries(self, extraSeries=None, **plotArgs):
+ def drawDataSeries(self, extraSeries=None, preproc=None, **plotArgs):
"""Plots all of the :class:`.DataSeries` instances in the
:attr:`dataSeries` list
:arg extraSeries: A sequence of additional ``DataSeries`` to be
plotted.
+ :arg preproc: An optional preprocessing function - passed to the
+ :meth:`__drawOneDataSeries` method.
+
:arg plotArgs: Passed through to the :meth:`__drawOneDataSeries`
method.
"""
@@ -397,7 +400,7 @@ class PlotPanel(viewpanel.ViewPanel):
ylims = []
for ds in toPlot:
- xlim, ylim = self.__drawOneDataSeries(ds, **plotArgs)
+ xlim, ylim = self.__drawOneDataSeries(ds, preproc, **plotArgs)
xlims.append(xlim)
ylims.append(ylim)
@@ -474,16 +477,26 @@ class PlotPanel(viewpanel.ViewPanel):
self.Refresh()
- def __drawOneDataSeries(self, ds, **plotArgs):
+ def __drawOneDataSeries(self, ds, preproc=None, **plotArgs):
"""Plots a single :class:`.DataSeries` instance. This method is called
by the :meth:`drawDataSeries` method.
:arg ds: The ``DataSeries`` instance.
+ :arg preproc: An optional preprocessing function which must accept
+ the ``DataSeries`` instance as its sole argument, and
+ must return the ``(xdata, ydata)`` with any required
+ processing applied. The default preprocessing function
+ returns the result of a call to
+ :meth:`.DataSeries.getData`.
+
:arg plotArgs: May be used to customise the plot - these
arguments are all passed through to the
``Axis.plot`` function.
"""
+
+ if preproc is None:
+ preproc = lambda s: s.getData()
if ds.alpha == 0:
return (0, 0), (0, 0)
@@ -491,7 +504,7 @@ class PlotPanel(viewpanel.ViewPanel):
log.debug('Drawing {} for {}'.format(type(ds).__name__,
ds.overlay))
- xdata, ydata = ds.getData()
+ xdata, ydata = preproc(ds)
if len(xdata) != len(ydata) or len(xdata) == 0:
return (0, 0), (0, 0)
diff --git a/fsl/fsleyes/views/timeseriespanel.py b/fsl/fsleyes/views/timeseriespanel.py
index 5a879e526528b542ece4f59efe961faa81221d1b..d83221c9a1eee94064fc5a21b1cc3f4fa1f6351a 100644
--- a/fsl/fsleyes/views/timeseriespanel.py
+++ b/fsl/fsleyes/views/timeseriespanel.py
@@ -20,7 +20,7 @@ import fsl.data.featimage as fslfeatimage
import fsl.data.melodicimage as fslmelimage
import fsl.data.image as fslimage
import fsl.fsleyes.colourmaps as fslcmaps
-import fsl.fsleyes.plotting.timeseries as timeseries
+import fsl.fsleyes.plotting as plotting
import fsl.fsleyes.controls.timeseriescontrolpanel as timeseriescontrolpanel
import fsl.fsleyes.controls.timeserieslistpanel as timeserieslistpanel
@@ -281,14 +281,15 @@ class TimeSeriesPanel(plotpanel.PlotPanel):
tss = [ts for ts in tss if ts is not None]
for i, ts in enumerate(list(tss)):
- if isinstance(ts, timeseries.FEATTimeSeries):
+ if isinstance(ts, plotting.FEATTimeSeries):
tss.pop(i)
tss = tss[:i] + ts.getModelTimeSeries() + tss[i:]
for ts in tss:
ts.label = ts.makeLabel()
- self.drawDataSeries(extraSeries=tss)
+ self.drawDataSeries(extraSeries=tss,
+ preproc=self.__prepareTimeSeriesData)
def getTimeSeries(self, overlay):
@@ -298,6 +299,39 @@ class TimeSeriesPanel(plotpanel.PlotPanel):
return self.__currentTss.get(overlay)
+ def __prepareTimeSeriesData(self, ts):
+ """Given a :class:`.TimeSeries` instance, scales and normalises
+ the x and y data according to the current values of the
+ :attr:`usePixdim` and :attr:`plotMode` properties.
+
+ This method is used as a preprocessing function for all
+ :class:`.TimeSeries` instances that are plotted - see the
+ :meth:`.PlotPanel.drawDataSeries` method.
+ """
+
+ xdata, ydata = ts.getData()
+
+ if self.usePixdim:
+ if isinstance(ts.overlay, fslmelimage.MelodicImage):
+ xdata *= ts.overlay.tr
+ else:
+ xdata *= ts.overlay.pixdim[3]
+
+ if self.plotMode == 'demean':
+ ydata = ydata - ydata.mean()
+
+ elif self.plotMode == 'normalise':
+ ymin = ydata.min()
+ ymax = ydata.max()
+ ydata = 2 * (ydata - ymin) / (ymax - ymin) - 1
+
+ elif self.plotMode == 'percentChange':
+ mean = ydata.mean()
+ ydata = 100 * (ydata / mean) - 100
+
+ return xdata, ydata
+
+
def __overlayListChanged(self, *a):
"""Called when the :class:`.OverlayList` changes. Makes sure that
there are no :class:`.TimeSeries` instances in the
@@ -402,18 +436,18 @@ class TimeSeriesPanel(plotpanel.PlotPanel):
return None, None, None
if isinstance(overlay, fslfeatimage.FEATImage):
- ts = timeseries.FEATTimeSeries(self, overlay, self._displayCtx)
+ ts = plotting.FEATTimeSeries(self, overlay, self._displayCtx)
targets = [self._displayCtx]
propNames = ['location']
elif isinstance(overlay, fslmelimage.MelodicImage) and \
self.plotMelodicICs:
- ts = timeseries.MelodicTimeSeries(self, overlay, self._displayCtx)
+ ts = plotting.MelodicTimeSeries(self, overlay, self._displayCtx)
targets = [self._displayCtx.getOpts(overlay)]
propNames = ['volume']
else:
- ts = timeseries.VoxelTimeSeries(self, overlay, self._displayCtx)
+ ts = plotting.VoxelTimeSeries(self, overlay, self._displayCtx)
targets = [self._displayCtx]
propNames = ['location']