def isolateClusters(selection, datasetName):
"""
Create a new data set from a selection of clusters.
@type selection: list
@var selection: The indices of the clusters to be merged.
@type datasetName: str
@var datasetName: The display name for the new data set.
"""
if (len(selection) > 0):
currFCData = DataStore.getCurrentDataSet()
if (datasetName == ""):
datasetName = currFCData.displayname
clusters = separate(currFCData.data, currFCData.getCurrentClustering())
# merge selected clusters
newData = dh.mergeData(selection, clusters)
# assign new data set to the store
newFCData = FacsData('', currFCData.labels, newData, parent=currFCData.ID)
newFCData.displayname = datasetName
newFCData.selDims = currFCData.selDims
# add basic text annotations
textAnn = {'parent': currFCData.displayname}
textAnn['events'] = len(newFCData.data)
newFCData.annotations['text'] = textAnn
DataStore.add(newFCData)
def loadState(dir, filename):
"""
Restore the system state as stored to disk.
@type dir: string
@param path: The directory under which the the saved system state is stored
@type filename: str
@param filename: The name of the saved project file (.find)
@rtype: tuple
@return: A list of subplot settings (dicts) retrieved from the file,
The index of the currently selected subplot,
The currently selected axes,
The number of rows and columns in the figure (grid size)
"""
store = shelve.open(os.path.join(dir, filename))
#store = dbopen(os.path.join(dir, filename))
datakeys = store['data']
try:
bindata = np.load(os.path.join(dir,store['binfile']))
except IOError:
bindata = None
except BadZipfile:
wx.MessageBox('The file \'%s\' may have become corrupted. Project loading has been cancelled' % store['binfile'],
'Data Loading Error',
wx.OK|wx.ICON_ERROR)
raise ProjectLoadingError('BadZipfile: %s' % os.path.join(dir,store['binfile']))
# Parse data sets
for dID in datakeys:
dStr = 'data-%s' % dID
dsett = store[dStr]
ann = dsett['annotations'] if 'annotations' in dsett else {}
ana = dsett['analysis'] if 'analysis' in dsett else {}
fdata = FacsData(dsett['filename'], dsett['labels'], bindata[dStr],
annotations=ann, analysis=ana,
parent=dsett['parent'])
fdata.displayname = dsett['displayname']
fdata.ID = dsett['ID']
fdata.children = dsett['children']
fdata.selDims = dsett['selDims']
fdata.nodeExpanded = dsett['nodeExpanded']
# Parse clusterings
for cID in dsett['clustering']:
cStr = 'clust-%i-%i' % (dID, cID)
csett = store[cStr]
clusterIDs = bindata[cStr]
fdata.addClustering(csett['method'], clusterIDs, csett['opts'], cID)
fdata.clusteringSelDims[cID] = csett['clusteringSelDims']
fdata.infoExpanded[cID] = csett['infoExpanded']
DataStore.add(fdata)
DataStore.selectDataSet(store['current-data'])
# Figures
if 'figures' in store:
for fStr in store['figures']:
fDict = store[fStr]
splots = []
for pStr in fDict['subplots']:
splots.append(store[pStr])
fDict['subplots'] = splots
f = Figure()
f.load(fDict)
FigureStore.add(f)
# handle older save files w/o Figure support
else:
# load the saved subplots into a new 'Default' Figure
plots = []
for pStr in store['plots']:
plots.append(store[pStr])
defFig = Figure('Default', plots, store['current-subplot'], store['grid'], store['selected-axes'])
FigureStore.add(defFig)
if 'current-figure' in store:
FigureStore.setSelectedFigure(store['current-figure'])
else:
FigureStore.setSelectedFigure(0)