Source code for cytoflowgui.workflow.operations.channel_stat

#!/usr/bin/env python3.8

# (c) Massachusetts Institute of Technology 2015-2018
# (c) Brian Teague 2018-2022
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 2 of the License, or
# (at your option) any later version.
# 
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU General Public License for more details.
# 
# You should have received a copy of the GNU General Public License
# along with this program.  If not, see <http://www.gnu.org/licenses/>.

"""
cytoflowgui.workflow.operations.channel_stat
--------------------------------------------

"""

import numpy as np
import scipy.stats

from traits.api import (Str, Callable, Property, Any, List, provides, observe)

import cytoflow.utility as util
from cytoflow import ChannelStatisticOp
                       
from cytoflowgui.workflow.serialization import camel_registry, traits_repr
from .operation_base import IWorkflowOperation, WorkflowOperation

from ..subset import ISubset

mean_95ci = lambda x: util.ci(x, np.mean, boots = 100)
geomean_95ci = lambda x: util.ci(x, util.geom_mean, boots = 100)

summary_functions = {"Mean" : np.mean,
                     "Geom.Mean" : util.geom_mean,
                     "Median" : np.median,
                     "Count" : len,
                     "Std.Dev" : np.std,
                     "Geom.SD" : util.geom_sd_range,
                     "SEM" : scipy.stats.sem,
                     "Geom.SEM" : util.geom_sem_range,
                     "Mean 95% CI" : mean_95ci,
                     "Geom.Mean 95% CI" : geomean_95ci
                     }

fill = {"Mean" : 0,
        "Geom.Mean" : 0,
        "Median" : 0,
        "Count" : 0,
        "Std.Dev" : 0,
        "Geom.SD" : (0,0),
        "SEM" : 0,
        "Geom.SEM" : (0,0),
        "Mean 95% CI" : 0,
        "Geom.Mean 95% CI" : 0
        }

ChannelStatisticOp.__repr__ = traits_repr

[docs]@provides(IWorkflowOperation) class ChannelStatisticWorkflowOp(WorkflowOperation, ChannelStatisticOp): # operation traits name = Str(apply = True) channel = Str(apply = True) statistic_name = Str(apply = True) by = List(Str, apply = True) # override the base class's "subset" with one that is dynamically generated / # updated from subset_list subset = Property(Str, observe = "subset_list.items.str") subset_list = List(ISubset, apply = True) # functions aren't picklable, so make this one transient # and send the name instead function = Callable(transient = True) # automatically pick a good fill fill = Property(Any, observe = 'statistic_name', transient = True) # MAGIC - returns the value of the 'fill' property def _get_fill(self): if self.statistic_name: return fill[self.statistic_name] else: return 0 # bits to support the subset editor @observe('subset_list:items.str') def _on_subset_changed(self, _): self.changed = 'subset_list' # MAGIC - returns the value of the "subset" Property, above def _get_subset(self): return " and ".join([subset.str for subset in self.subset_list if subset.str])
[docs] def apply(self, experiment): if not self.statistic_name: raise util.CytoflowOpError("Summary function isn't set") self.function = summary_functions[self.statistic_name] return ChannelStatisticOp.apply(self, experiment)
[docs] def clear_estimate(self): # no-op return
[docs] def get_notebook_code(self, idx): op = ChannelStatisticOp() op.copy_traits(self, op.copyable_trait_names()) fn_import = {"Mean" : "from numpy import mean", "Median" : "from numpy import median", "Geom.Mean" : None, "Count" : None, "Std.Dev" : "from numpy import std", "Geom.SD" : None, "SEM" : "from scipy.stats import sem", "Geom.SEM" : None, "Mean 95% CI" : "from numpy import mean", "Geom.Mean 95% CI" : None } fn_name = {"Mean" : "mean", "Median" : "median", "Geom.Mean" : "geom_mean", "Count" : "len", "Std.Dev" : "std", "Geom.SD" : "geom_sd_range", "SEM" : "sem", "Geom.SEM" : "geom_sem_range", "Mean 95% CI" : "lambda x: ci(x, mean, boots = 100)", "Geom.Mean 95% CI" : "lambda x: ci(x, geom_mean, boots = 100)" } op.function = summary_functions[self.statistic_name] try: # this doesn't work for builtins like "len" op.function.__name__ = fn_name[self.statistic_name] except AttributeError: pass return "\n{import_statement}\nop_{idx} = {repr}\n\nex_{idx} = op_{idx}.apply(ex_{prev_idx})"\ .format(import_statement = (fn_import[self.statistic_name] if fn_import[self.statistic_name] is not None else ""), repr = repr(op), idx = idx, prev_idx = idx - 1)
### Serialization @camel_registry.dumper(ChannelStatisticWorkflowOp, 'channel-statistic', version = 1) def _dump(op): return dict(name = op.name, channel = op.channel, statistic_name = op.statistic_name, by = op.by, subset_list = op.subset_list) @camel_registry.loader('channel-statistic', version = 1) def _load(data, version): return ChannelStatisticWorkflowOp(**data)