def activated(self):
# add an import plugin
plugin = ImportPlugin()
wi = WorkflowItem(task=self)
wi.operation = plugin.get_operation()
self.model.workflow.append(wi)
self.model.selected = wi
# if we're debugging, add a few data bits
if self.debug:
from cytoflow import Tube
wi.operation.conditions["Dox"] = "log"
tube1 = Tube(file="../cytoflow/tests/data/Plate01/CFP_Well_A4.fcs",
conditions={"Dox": 0.1})
tube2 = Tube(file="../cytoflow/tests/data/Plate01/RFP_Well_A3.fcs",
conditions={"Dox": 1.0})
wi.operation.tubes.append(tube1)
wi.operation.tubes.append(tube2)
self.add_operation(
'edu.mit.synbio.cytoflowgui.op_plugins.threshold')
self.model.selected.operation.channel = "Y2-A"
self.model.selected.operation.threshold = 2000
self.model.selected.operation.name = "T"
def update_import_op(self, op):
trait_to_dtype = {"Str" : "category",
"Float" : "float",
"LogFloat" : "log",
"Bool" : "bool",
"Int" : "int"}
op.conditions.clear()
for trait_name, trait in self.tube_traits.items():
if not trait.condition:
continue
trait_type = trait.__class__.__name__
op.conditions[trait_name] = trait_to_dtype[trait_type]
for tube in self.tubes:
op_tube = CytoflowTube(source = tube.Source,
tube = tube.Tube,
file = tube._file)
if "Row" in tube.trait_names():
op_tube.row = tube.Row
if "Col" in tube.trait_names():
op_tube.col = tube.Col
op_tube.conditions = tube.trait_get(condition = True)
# AFAICT this is going to cause the op to reload THE ENTIRE
# SET each time a tube is added. >.>
# TODO - FIX THIS. need a general strategy for only updating
# if there's a "pause" in the action.
op.tubes.append(op_tube)
def activated(self):
# add the import op
self.add_operation(ImportPlugin().id)
self.model.selected = self.model.workflow[0]
# if we're debugging, add a few data bits
if self.model.debug:
from cytoflow import Tube
import_op = self.model.workflow[0].operation
import_op.conditions = {"Dox": "float", "Well": "category"}
# import_op.conditions["Dox"] = "float"
# import_op.conditions["Well"] = "category"
tube1 = Tube(file="../cytoflow/tests/data/Plate01/CFP_Well_A4.fcs",
conditions={
"Dox": 0.0,
"Well": 'A'
})
tube2 = Tube(file="../cytoflow/tests/data/Plate01/RFP_Well_A3.fcs",
conditions={
"Dox": 10.0,
"Well": 'A'
})
tube3 = Tube(file="../cytoflow/tests/data/Plate01/CFP_Well_B4.fcs",
conditions={
"Dox": 0.0,
"Well": 'B'
})
tube4 = Tube(file="../cytoflow/tests/data/Plate01/RFP_Well_A6.fcs",
conditions={
"Dox": 10.0,
"Well": 'B'
})
import_op.tubes = [tube1, tube2, tube3, tube4]
# self.add_operation(ChannelStatisticPlugin().id)
# stat_op = self.model.workflow[1].operation
# stat_op.name = "Test"
# stat_op.channel = "Y2-A"
# stat_op.statistic_name = "Geom.Mean"
# stat_op.by = ["Dox", "Well"]
# self.model.selected = self.model.workflow[1]
self.model.modified = False
def activated(self):
# if we're coming back from the TASBE task, re-load the saved
# workflow
if self.model.backup_workflow:
self.model.workflow = self.model.backup_workflow
self.model.backup_workflow = []
return
# else, set up a new workflow
# add the import op
if not self.model.workflow:
self.add_operation(ImportPlugin().id)
self.model.selected = self.model.workflow[0]
# if we're debugging, add a few data bits
if self.model.debug:
from cytoflow import Tube
import_op = self.model.workflow[0].operation
import_op.conditions = {"Dox" : "float", "Well" : "category"}
tube1 = Tube(file = "../cytoflow/tests/data/Plate01/CFP_Well_A4.fcs",
conditions = {"Dox" : 0.0, "Well" : 'A'})
tube2 = Tube(file = "../cytoflow/tests/data/Plate01/RFP_Well_A3.fcs",
conditions = {"Dox" : 10.0, "Well" : 'A'})
tube3 = Tube(file = "../cytoflow/tests/data/Plate01/CFP_Well_B4.fcs",
conditions = {"Dox" : 0.0, "Well" : 'B'})
tube4 = Tube(file = "../cytoflow/tests/data/Plate01/RFP_Well_A6.fcs",
conditions = {"Dox" : 10.0, "Well" : 'B'})
import_op.tubes = [tube1, tube2, tube3, tube4]
# from cytoflowgui.op_plugins import ChannelStatisticPlugin
# self.add_operation(ChannelStatisticPlugin().id)
# stat_op = self.model.workflow[1].operation
# stat_op.name = "Test"
# stat_op.channel = "Y2-A"
# stat_op.statistic_name = "Geom.Mean"
# stat_op.by = ["Dox", "Well"]
# self.model.selected = self.model.workflow[1]
self.model.modified = False
def setUp(self):
super().setUp()
plugin = ImportPlugin()
op = plugin.get_operation()
from cytoflow import Tube
self.cwd = os.path.dirname(os.path.abspath(__file__))
tube = Tube(file=self.cwd + "/../../cytoflow/tests/data/tasbe/rby.fcs")
op.tubes = [tube]
wi = WorkflowItem(operation=op,
status="waiting",
view_error="Not yet plotted")
self.workflow.workflow.append(wi)
op.do_estimate = True
self.workflow.wi_waitfor(wi, 'status', 'valid')
self.assertTrue(
self.workflow.remote_eval("self.workflow[0].result is not None"))
plugin = ThresholdPlugin()
op = plugin.get_operation()
op.name = "Morpho"
op.channel = "FSC-A"
op.threshold = 100000
wi = WorkflowItem(operation=op, status='waiting')
self.workflow.workflow.append(wi)
self.workflow.selected = wi
self.workflow.wi_waitfor(wi, 'status', 'valid')
def setUp(self):
from cytoflow import Tube
self.cwd = os.path.dirname(os.path.abspath(__file__)) + "/data/tasbe/"
tube = Tube(file = self.cwd + "rby.fcs")
self.ex = flow.ImportOp(tubes = [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)
ExportFCS(path=self.output_directory,
by=['filename'],
_include_by=False).export(experiment)
self.input_files = []
self.status = "Done converting!"
def update_import_op(self, op):
trait_to_dtype = {
"Str": "category",
"Float": "float",
"LogFloat": "log",
"Bool": "bool",
"Int": "int"
}
op.conditions.clear()
for trait_name, trait in self.tube_traits.items():
if not trait.condition:
continue
trait_type = trait.__class__.__name__
op.conditions[trait_name] = trait_to_dtype[trait_type]
for tube in self.tubes:
op_tube = CytoflowTube(source=tube.Source,
tube=tube.Tube,
file=tube._file)
if "Row" in tube.trait_names():
op_tube.row = tube.Row
if "Col" in tube.trait_names():
op_tube.col = tube.Col
op_tube.conditions = tube.trait_get(condition=True)
# AFAICT this is going to cause the op to reload THE ENTIRE
# SET each time a tube is added. >.>
# TODO - FIX THIS. need a general strategy for only updating
# if there's a "pause" in the action.
op.tubes.append(op_tube)
def setUp(self):
from cytoflow import Tube
self.cwd = os.path.dirname(os.path.abspath(__file__)) + "/data/Plate01/"
tube1 = Tube(file = self.cwd + "CFP_Well_A4.fcs",
conditions = {"Dox" : 0.0, "Well" : 'Aa'})
tube2 = Tube(file = self.cwd + "RFP_Well_A3.fcs",
conditions = {"Dox" : 10.0, "Well" : 'Aa'})
tube3 = Tube(file = self.cwd + "YFP_Well_A7.fcs",
conditions = {"Dox" : 100.0, "Well" : 'Aa'})
tube4 = Tube(file = self.cwd + "CFP_Well_B4.fcs",
conditions = {"Dox" : 0.0, "Well" : 'Bb'})
tube5 = Tube(file = self.cwd + "RFP_Well_A6.fcs",
conditions = {"Dox" : 10.0, "Well" : 'Bb'})
tube6 = Tube(file = self.cwd + "YFP_Well_C7.fcs",
conditions = {"Dox" : 100.0, "Well" : 'Bb'})
tube7 = Tube(file = self.cwd + "CFP_Well_B4.fcs",
conditions = {"Dox" : 0.0, "Well" : 'Cc'})
tube8 = Tube(file = self.cwd + "RFP_Well_A6.fcs",
conditions = {"Dox" : 10.0, "Well" : 'Cc'})
tube9 = Tube(file = self.cwd + "YFP_Well_C7.fcs",
conditions = {"Dox" : 100.0, "Well" : 'Cc'})
self.ex = flow.ImportOp(conditions = {"Dox" : "float", "Well" : "category"},
tubes = [tube1, tube2, tube3,
tube4, tube5, tube6,
tube7, tube8, tube9]).apply()
def setUp(self):
WorkflowTest.setUp(self)
plugin = ImportPlugin()
op = plugin.get_operation()
from cytoflow import Tube
self.cwd = os.path.dirname(os.path.abspath(__file__))
tube = Tube(file = self.cwd + "/../../cytoflow/tests/data/tasbe/rby.fcs")
op.tubes = [tube]
wi = WorkflowItem(operation = op,
view_error = "Not yet plotted")
self.workflow.workflow.append(wi)
self.assertTrue(wait_for(wi, 'status', lambda v: v == 'valid', 5))
self.assertTrue(self.workflow.remote_eval("self.workflow[0].result is not None"))
def setUp(self):
WorkflowTest.setUp(self)
plugin = ImportPlugin()
op = plugin.get_operation()
from cytoflow import Tube
op.conditions = {"Dox" : "float", "Well" : "category"}
self.cwd = os.path.dirname(os.path.abspath(__file__))
tube1 = Tube(file = self.cwd + "/../../cytoflow/tests/data/Plate01/CFP_Well_A4.fcs",
conditions = {"Dox" : 0.0, "Well" : 'A'})
tube2 = Tube(file = self.cwd + "/../../cytoflow/tests/data/Plate01/RFP_Well_A3.fcs",
conditions = {"Dox" : 10.0, "Well" : 'A'})
tube3 = Tube(file = self.cwd + "/../../cytoflow/tests/data/Plate01/YFP_Well_A7.fcs",
conditions = {"Dox" : 100.0, "Well" : 'A'})
tube4 = Tube(file = self.cwd + "/../../cytoflow/tests/data/Plate01/CFP_Well_B4.fcs",
conditions = {"Dox" : 0.0, "Well" : 'B'})
tube5 = Tube(file = self.cwd + "/../../cytoflow/tests/data/Plate01/RFP_Well_A6.fcs",
conditions = {"Dox" : 10.0, "Well" : 'B'})
tube6 = Tube(file = self.cwd + "/../../cytoflow/tests/data/Plate01/YFP_Well_C7.fcs",
conditions = {"Dox" : 100.0, "Well" : 'B'})
op.tubes = [tube1, tube2, tube3, tube4, tube5, tube6]
wi = WorkflowItem(operation = op,
view_error = "Not yet plotted")
self.workflow.workflow.append(wi)
self.assertTrue(wait_for(wi, 'status', lambda v: v == 'valid', 5))
self.assertTrue(self.workflow.remote_eval("self.workflow[0].result is not None"))
def setUp(self):
super().setUp()
import_plugin = ImportPlugin()
import_op = import_plugin.get_operation()
from cytoflow import Tube
import_op.conditions = {
"Dox": "float",
"IP": "float",
"Well": "category"
}
self.cwd = os.path.dirname(os.path.abspath(__file__))
tube1 = Tube(file=self.cwd +
"/../../cytoflow/tests/data/Plate01/CFP_Well_A4.fcs",
conditions={
"Dox": 1.0,
"IP": 1.0,
"Well": 'A'
})
tube2 = Tube(file=self.cwd +
"/../../cytoflow/tests/data/Plate01/RFP_Well_A3.fcs",
conditions={
"Dox": 1.0,
"IP": 10.0,
"Well": 'B'
})
tube3 = Tube(file=self.cwd +
"/../../cytoflow/tests/data/Plate01/YFP_Well_A7.fcs",
conditions={
"Dox": 10.0,
"IP": 1.0,
"Well": 'A'
})
tube4 = Tube(file=self.cwd +
"/../../cytoflow/tests/data/Plate01/CFP_Well_B4.fcs",
conditions={
"Dox": 10.0,
"IP": 10.0,
"Well": 'B'
})
tube5 = Tube(file=self.cwd +
"/../../cytoflow/tests/data/Plate01/RFP_Well_A6.fcs",
conditions={
"Dox": 100.0,
"IP": 1.0,
"Well": 'A'
})
tube6 = Tube(file=self.cwd +
"/../../cytoflow/tests/data/Plate01/YFP_Well_C7.fcs",
conditions={
"Dox": 100.0,
"IP": 100.0,
"Well": 'B'
})
import_op.tubes = [tube1, tube2, tube3, tube4, tube5, tube6]
wi = WorkflowItem(operation=import_op,
status="waiting",
view_error="Not yet plotted")
self.workflow.workflow.append(wi)
import_op.do_estimate = True
self.workflow.wi_waitfor(wi, 'status', 'valid')
self.assertTrue(
self.workflow.remote_eval("self.workflow[0].result is not None"))
stats_plugin = ChannelStatisticPlugin()
stats_op_1 = stats_plugin.get_operation()
stats_op_1.name = "MeanByDoxIP"
stats_op_1.channel = "Y2-A"
stats_op_1.statistic_name = "Geom.Mean"
stats_op_1.by = ['Dox', 'IP']
stats_op_1.subset_list.append(
CategorySubset(name="Well", values=['A', 'B']))
stats_op_1.subset_list.append(
RangeSubset(name="Dox", values=[1.0, 10.0, 100.0]))
stats_op_1.subset_list.append(
RangeSubset(name="IP", values=[1.0, 10.0]))
stats_wi_1 = WorkflowItem(operation=stats_op_1,
status="waiting",
view_error="Not yet plotted")
self.workflow.workflow.append(stats_wi_1)
self.workflow.wi_waitfor(stats_wi_1, 'status', 'valid')
stats_op_2 = stats_plugin.get_operation()
stats_op_2.name = "SDByDoxIP"
stats_op_2.channel = "Y2-A"
stats_op_2.statistic_name = "Geom.SD"
stats_op_2.by = ['Dox', 'IP']
stats_op_2.subset_list.append(
CategorySubset(name="Well", values=['A', 'B']))
stats_op_2.subset_list.append(
RangeSubset(name="Dox", values=[1.0, 10.0, 100.0]))
stats_op_2.subset_list.append(
RangeSubset(name="IP", values=[1.0, 10.0]))
stats_wi_2 = WorkflowItem(operation=stats_op_2,
status="waiting",
view_error="Not yet plotted")
self.workflow.workflow.append(stats_wi_2)
self.workflow.selected = stats_wi_2
self.workflow.wi_waitfor(stats_wi_2, 'status', 'valid')
def _load_tube(data, version):
return Tube(**data)
def setUp(self, thin=100):
"""Run once per test at the beginning"""
from cytoflow import Tube
self.cwd = os.path.dirname(
os.path.abspath(__file__)) + "/data/Plate01/"
tube1 = Tube(file=self.cwd + "CFP_Well_A4.fcs",
conditions={
"Dox": 0.0,
"Well": 'A'
})
tube2 = Tube(file=self.cwd + "RFP_Well_A3.fcs",
conditions={
"Dox": 10.0,
"Well": 'A'
})
tube3 = Tube(file=self.cwd + "YFP_Well_A7.fcs",
conditions={
"Dox": 100.0,
"Well": 'A'
})
tube4 = Tube(file=self.cwd + "CFP_Well_B4.fcs",
conditions={
"Dox": 0.0,
"Well": 'B'
})
tube5 = Tube(file=self.cwd + "RFP_Well_A6.fcs",
conditions={
"Dox": 10.0,
"Well": 'B'
})
tube6 = Tube(file=self.cwd + "YFP_Well_C7.fcs",
conditions={
"Dox": 100.0,
"Well": 'B'
})
tube7 = Tube(file=self.cwd + "CFP_Well_B4.fcs",
conditions={
"Dox": 0.0,
"Well": 'C'
})
tube8 = Tube(file=self.cwd + "RFP_Well_A6.fcs",
conditions={
"Dox": 10.0,
"Well": 'C'
})
tube9 = Tube(file=self.cwd + "YFP_Well_C7.fcs",
conditions={
"Dox": 100.0,
"Well": 'C'
})
self.ex = flow.ImportOp(conditions={
"Dox": "float",
"Well": "category"
},
tubes=[
tube1, tube2, tube3, tube4, tube5, tube6,
tube7, tube8, tube9
]).apply()
if thin > 1:
# thin the dataset 100-fold from 90k to 900 rows for thin=100
self.ex.add_condition("bucket", "int",
np.arange(self.ex.data.shape[0]) % thin)
self.ex = self.ex.query("bucket == 0")
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!"
