def get_notebook_code(self, idx):
op = ImportOp()
op.copy_traits(self, op.copyable_trait_names())
return dedent("""
op_{idx} = {repr}
ex_{idx} = op_{idx}.apply()""".format(repr=repr(op), idx=idx))
def apply(self, experiment):
if self.blank_file != self._blank_exp_file:
self._blank_exp = ImportOp(tubes=[Tube(
file=self.blank_file)]).apply()
self._blank_exp_file = self.blank_file
self._blank_exp_channels = self._blank_exp.channels
self.changed = (Changed.PREV_RESULT, None)
return
out_dir = Path(self.output_directory)
for path in self.input_files:
in_file_path = Path(path)
out_file_path = out_dir / in_file_path.name
if out_file_path.exists():
raise util.CytoflowOpError(
None, "File {} already exists".format(out_file_path))
tubes = [
Tube(file=path, conditions={'filename': Path(path).stem})
for path in self.input_files
]
for tube in tubes:
self.status = "Converting " + Path(tube.file).stem
experiment = ImportOp(tubes=[tube],
conditions={
'filename': 'category'
}).apply()
experiment = self._af_op.apply(experiment)
experiment = self._bleedthrough_op.apply(experiment)
experiment = self._bead_calibration_op.apply(experiment)
if self.do_color_translation:
experiment = self._color_translation_op.apply(experiment)
ExportFCS(path=self.output_directory,
by=['filename'],
_include_by=False).export(experiment)
self.input_files = []
self.status = "Done converting!"
def get_notebook_code(self, idx):
op = ImportOp()
op.copy_traits(self, op.copyable_trait_names())
op.channels = {c.channel: c.name for c in self.channels_list}
return dedent("""
op_{idx} = {repr}
ex_{idx} = op_{idx}.apply()""".format(repr=repr(op), idx=idx))
def _on_add_tubes(self):
"""
Handle "Add tubes..." button. Add tubes to the experiment.
"""
file_dialog = FileDialog()
file_dialog.wildcard = "Flow cytometry files (*.fcs *.lmd)|*.fcs *.lmd|"
file_dialog.action = 'open files'
file_dialog.open()
if file_dialog.return_code != PyfaceOK:
return
for path in file_dialog.paths:
try:
metadata, _ = parse_tube(path, metadata_only=True)
except Exception as e:
raise RuntimeError("FCS reader threw an error on tube {0}: {1}"\
.format(path, e.value))
# if we're the first tube loaded, create a dummy experiment
# and setup default metadata columns
if not self.model.dummy_experiment:
self.model.dummy_experiment = \
ImportOp(tubes = [CytoflowTube(file = path)]).apply(metadata_only = True)
# check the next tube against the dummy experiment
try:
check_tube(path, self.model.dummy_experiment)
except util.CytoflowError as e:
error(None, e.__str__(), "Error importing tube")
return
metadata['CF_File'] = Path(path).stem
tube = Tube(file=path,
parent=self.model,
metadata=sanitize_metadata(metadata))
self.model.tubes.append(tube)
for trait in self.model.tube_traits:
if trait.type != 'metadata' and trait.name:
tube.on_trait_change(self._try_multiedit, trait.name)
def get_operation(self):
ret = ImportOp()
ret.add_trait("handler_factory", Callable)
ret.handler_factory = ImportHandler
return ret
def _on_add_tubes(self):
"""
Handle "Add tubes..." button. Add tubes to the experiment.
"""
file_dialog = FileDialog()
file_dialog.wildcard = "Flow cytometry files (*.fcs)|*.fcs|"
file_dialog.action = 'open files'
file_dialog.open()
if file_dialog.return_code != PyfaceOK:
return
for path in file_dialog.paths:
try:
tube_meta = fcsparser.parse(path,
meta_data_only = True,
reformat_meta = True)
#tube_channels = tube_meta["_channels_"].set_index("$PnN")
except Exception as e:
raise RuntimeError("FCS reader threw an error on tube {0}: {1}"\
.format(path, e.value))
# if we're the first tube loaded, create a dummy experiment
if not self.model.dummy_experiment:
self.model.dummy_experiment = ImportOp(tubes = [CytoflowTube(file = path)],
coarse_events = 1).apply()
# check the next tube against the dummy experiment
try:
check_tube(path, self.model.dummy_experiment)
except util.CytoflowError as e:
error(None, e.__str__(), "Error importing tube")
return
tube = Tube()
for trait_name, trait in self.model.tube_traits.items():
tube.add_trait(trait_name, trait)
# this magic makes sure the trait is actually defined
# in tube.__dict__, so it shows up in trait_names etc.
tube.trait_set(**{trait_name : trait.default_value})
if trait.condition:
tube.on_trait_change(self._try_multiedit, trait_name)
tube.trait_set(file = path, parent = self.model)
if '$SRC' in tube_meta:
self._add_metadata("$SRC", "$SRC", Str(condition = False))
tube.trait_set(**{"$SRC" : tube_meta['$SRC']})
if 'TUBE NAME' in tube_meta:
self._add_metadata("TUBE NAME", "TUBE NAME", Str(condition = False))
tube.trait_set(**{"TUBE NAME" : tube_meta['TUBE NAME']})
if '$SMNO' in tube_meta:
self._add_metadata("$SMNO", "$SMNO", Str(condition = False))
tube.trait_set(**{"$SMNO" : tube_meta['$SMNO']})
if 'WELL ID' in tube_meta:
self._add_metadata("Row", "Row", Str(condition = False))
self._add_metadata("Col", "Col", Int(condition = False))
pos = tube_meta['WELL ID']
row = pos[0]
col = int(pos[1:3])
tube.trait_set(**{"Row" : row, "Col" : col})
self.model.tubes.append(tube)
def init_model(self, op):
dtype_to_trait = {"category" : Str,
"float" : Float,
"bool" : Bool,
"int" : Int}
for op_tube in op.tubes:
tube = Tube(file = op_tube.file,
parent = self)
# first load the tube's metadata and set special columns
try:
tube_meta = fcsparser.parse(op_tube.file,
meta_data_only = True,
reformat_meta = True)
#tube_channels = tube_meta["_channels_"].set_index("$PnN")
except Exception as e:
error(None, "FCS reader threw an error on tube {0}: {1}"\
.format(op_tube.file, e.value),
"Error reading FCS file")
return
# if we're the first tube loaded, create a dummy experiment
if not self.dummy_experiment:
self.dummy_experiment = ImportOp(tubes = [op_tube],
conditions = op.conditions,
coarse_events = 1).apply()
if '$SRC' in tube_meta:
self.tube_traits["$SRC"] = Str(condition = False)
tube.add_trait("$SRC", Str(condition = False))
tube.trait_set(**{"$SRC" : tube_meta['$SRC']})
if 'TUBE NAME' in tube_meta:
self.tube_traits["TUBE NAME"] = Str(condition = False)
tube.add_trait("TUBE NAME", Str(condition = False))
tube.trait_set(**{"TUBE NAME" : tube_meta['TUBE NAME']})
if '$SMNO' in tube_meta:
self.tube_traits["$SMNO"] = Str(condition = False)
tube.add_trait("$SMNO", Str(condition = False))
tube.trait_set(**{"$SMNO" : tube_meta['SMNO']})
if 'WELL ID' in tube_meta:
pos = tube_meta['WELL ID']
row = pos[0]
col = int(pos[1:3])
self.tube_traits["Row"] = Str(condition = False)
self.tube_traits["Col"] = Int(condition = False)
tube.add_trait("Row", Str(condition = False))
tube.add_trait("Col", Int(condition = False))
tube.trait_set(**{"Row" : row, "Col" : col})
# next set conditions
try:
conditions_list = op_tube.conditions_list
except:
conditions_list = op_tube.conditions.keys()
for condition in conditions_list:
condition_dtype = op.conditions[condition]
condition_trait = \
dtype_to_trait[condition_dtype](condition = True)
tube.add_trait(condition, condition_trait)
if not condition in self.tube_traits:
self.tube_traits[condition] = condition_trait
tube.trait_set(**op_tube.conditions)
self.tubes.append(tube)
def apply(self, experiment):
if self.blank_file != self._blank_exp_file:
self._blank_exp = ImportOp(tubes=[Tube(
file=self.blank_file)]).apply()
self._blank_exp_file = self.blank_file
self._blank_exp_channels = self._blank_exp.channels
self.changed = (Changed.PREV_RESULT, None)
return
out_dir = Path(self.output_directory)
for path in self.input_files:
in_file_path = Path(path)
out_file_path = out_dir / in_file_path.name
if out_file_path.exists():
raise util.CytoflowOpError(
None, "File {} already exists".format(out_file_path))
tubes = [
Tube(file=path, conditions={'filename': Path(path).stem})
for path in self.input_files
]
for tube in tubes:
self.status = "Converting " + Path(tube.file).stem
experiment = ImportOp(tubes=[tube],
conditions={
'filename': 'category'
}).apply()
experiment = self._af_op.apply(experiment)
experiment = self._bleedthrough_op.apply(experiment)
experiment = self._bead_calibration_op.apply(experiment)
if self.do_color_translation:
experiment = self._color_translation_op.apply(experiment)
tube_meta = fcsparser.parse(
tube.file,
channel_naming=experiment.metadata["name_metadata"],
meta_data_only=True,
reformat_meta=False)
del tube_meta['__header__']
tube_meta = {
k: v
for (k, v) in tube_meta.items()
if not k.startswith("flowCore_")
}
tube_meta = {
k: v
for (k, v) in tube_meta.items()
if not (k.startswith("$P") and k[2].isdigit())
}
drop_kws = [
"$BEGINANALYSIS", "$ENDANALYSIS", "$BEGINSTEXT", "$ENDSTEXT",
"$BEGINDATA", "$ENDDATA", "$BYTEORD", "$DATATYPE", "$MODE",
"$NEXTDATA", "$TOT", "$PAR"
]
tube_meta = {
k: v
for (k, v) in tube_meta.items() if not k in drop_kws
}
ExportFCS(path=self.output_directory,
by=['filename'],
_include_by=False,
keywords=tube_meta).export(experiment)
self.input_files = []
self.status = "Done converting!"