def _display_output_image(outp):
if self.dsviewer.mode == 'visGUI':
mode = 'visGUI'
elif 'out_tracks' in self.activeRecipe.namespace.keys():
mode = 'tracking'
else:
mode = 'default'
dv = ViewIm3D(outp, mode=mode, glCanvas=self.dsviewer.glCanvas)
if 'out_meas' in self.activeRecipe.namespace.keys():
#have measurements as well - add to / overlay with output image
if not 'pipeline' in dir(dv):
dv.pipeline = pipeline.Pipeline()
from PYME.IO import tabular
cache = tabular.CachingResultsFilter(
self.activeRecipe.namespace['out_meas'])
dv.pipeline.OpenFile(ds=cache)
dv.view.filter = dv.pipeline
#set scaling to (0,1)
for i in range(outp.data.shape[3]):
dv.do.Gains[i] = 1.0
if ('out_tracks' in self.activeRecipe.namespace.keys()
) and 'tracker' in dir(dv):
dv.tracker.SetTracks(
self.activeRecipe.namespace['out_tracks'])
def SetData(self, data):
if isinstance(data, tabular.TabularBase):
table = TabularTable(tabular.CachingResultsFilter(data))
else:
table = RecArrayTable(data)
# The second parameter means that the grid is to take ownership of the
# table and will destroy it when done. Otherwise you would need to keep
# a reference to it and call it's Destroy method later.
self.SetTable(table, True)
def execute(self, namespace):
input = namespace[self.input]
mdh = input.mdh
if self.ratios_from_metadata:
# turn off invalidation so we don't get a recursive loop. TODO - fix this properly as it's gross to be changing
# our parameters here
invalidate = self._invalidate_parent
self._invalidate_parent = False
self._get_dye_ratios_from_metadata(mdh)
self._invalidate_parent = invalidate
output = tabular.MappingFilter(input)
output.mdh = mdh
if 'gFrac' in output.keys():
#ratiometric
#raise NotImplementedError('Ratiometric processing in recipes not implemented yet')
for structure, ratio in self.species_ratios.items():
if not ratio is None:
output.setMapping(
'p_%s' % structure,
'exp(-(%f - gFrac)**2/(2*error_gFrac**2))/(error_gFrac*sqrt(2*numpy.pi))'
% ratio)
else:
if 'probe' in output.keys():
#non-ratiometric (i.e. sequential) colour
#color channel is given in 'probe' column
output.setMapping('ColourNorm', '1.0 + 0*probe')
for i in range(int(output['probe'].min()),
int(output['probe'].max() + 1)):
output.setMapping('p_chan%d' % i, '1.0*(probe == %d)' % i)
nSeqCols = mdh.getOrDefault('Protocol.NumberSequentialColors', 1)
if nSeqCols > 1:
for i in range(nSeqCols):
output.setMapping('ColourNorm', '1.0 + 0*t')
cr = mdh['Protocol.ColorRange%d' % i]
output.setMapping('p_chan%d' % i, '(t>= %d)*(t<%d)' % cr)
cached_output = tabular.CachingResultsFilter(output)
#cached_output.mdh = output.mdh
namespace[self.output] = cached_output
def OnLoadOutputs(self, event):
import pandas
from PYME.IO import tabular
filename = wx.FileSelector(
'Save results as ...',
wildcard=
"CSV files (*.csv)|*.csv|Excell files (*.xlsx)|*.xlsx|HDF5 files (*.hdf)|*.hdf",
flags=wx.FD_OPEN)
if not filename == '':
if filename.endswith('.csv'):
data = pandas.read_csv(filename)
elif filename.endswith('.xlsx'):
data = pandas.read_excel(filename)
elif filename.endswith('.hdf'):
data = pandas.read_hdf(filename)
if not 'pipeline' in dir(self.dsviewer):
self.dsviewer.pipeline = pipeline.Pipeline()
cache = tabular.CachingResultsFilter(data)
self.dsviewer.pipeline.OpenFile(ds=cache)
self.dsviewer.view.filter = self.dsviewer.pipeline
def RunCurrentRecipe(self, event=None, testMode=False, saveResults=False):
if self.activeRecipe:
if testMode:
#just run on current frame # FIXME - this breaks SUPERTILE datasources and anything that needs to carry datasource attributes forward
self.outp = self.activeRecipe.execute(
input=ImageStack([
np.atleast_3d(self.image.data[:, :, self.do.zp, c])
for c in range(self.image.data.shape[3])
],
mdh=self.image.mdh))
else:
#run normally
self.outp = self.activeRecipe.execute(input=self.image)
if saveResults:
dir_dialog = wx.DirDialog(None,
'Set output directory',
style=wx.FD_OPEN)
succ = dir_dialog.ShowModal()
if (succ == wx.ID_OK):
output_dir = dir_dialog.GetPath()
file_stub = os.path.splitext(
os.path.split(self.image.filename)[-1])[0]
self.activeRecipe.save({
'output_dir': output_dir,
'file_stub': file_stub
})
def _display_output_image(outp):
if self.dsviewer.mode == 'visGUI':
mode = 'visGUI'
elif 'out_tracks' in self.activeRecipe.namespace.keys():
mode = 'tracking'
else:
mode = 'default'
dv = ViewIm3D(outp, mode=mode, glCanvas=self.dsviewer.glCanvas)
if 'out_meas' in self.activeRecipe.namespace.keys():
#have measurements as well - add to / overlay with output image
if not 'pipeline' in dir(dv):
dv.pipeline = pipeline.Pipeline()
from PYME.IO import tabular
cache = tabular.CachingResultsFilter(
self.activeRecipe.namespace['out_meas'])
dv.pipeline.OpenFile(ds=cache)
dv.view.filter = dv.pipeline
#set scaling to (0,1)
for i in range(outp.data.shape[3]):
dv.do.Gains[i] = 1.0
if ('out_tracks' in self.activeRecipe.namespace.keys()
) and 'tracker' in dir(dv):
dv.tracker.SetTracks(
self.activeRecipe.namespace['out_tracks'])
def _display_output_report(outp):
import wx.html2
html_view = wx.html2.WebView.New(self.dsviewer)
self.dsviewer.AddPage(html_view, True, 'Recipe Report')
html_view.SetPage(outp, 'Recipe Report')
if ('out_tracks' in self.activeRecipe.namespace.keys()
) and 'tracker' in dir(self.dsviewer):
self.dsviewer.tracker.SetTracks(
self.activeRecipe.namespace['out_tracks'])
#assume we made measurements - put in pipeline
#TODO - put an explict check in here
if not 'pipeline' in dir(self.dsviewer):
self.dsviewer.pipeline = pipeline.Pipeline()
if isinstance(self.outp, ImageStack):
_display_output_image(self.outp)
elif not self.outp is None:
from PYME.IO import tabular
cache = tabular.CachingResultsFilter(self.outp)
self.dsviewer.pipeline.OpenFile(ds=cache, clobber_recipe=False)
self.dsviewer.pipeline.filterKeys = {}
self.dsviewer.pipeline.Rebuild()
self.dsviewer.view.filter = self.dsviewer.pipeline
for out_ in self.activeRecipe.gather_outputs():
if isinstance(out_, ImageStack):
_display_output_image(out_)
elif isinstance(out_, six.string_types):
_display_output_report(out_)
