#!/usr/bin/env python3.8
# coding: latin-1
# (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/>.
"""
cytoflow.operations.frame_stat
------------------------------
The `frame_stat` module contains one class:
`FrameStatisticOp` -- applies a function to subsets of a data set,
and adds the resulting statistic to the `Experiment`. Unlike
`ChannelStatisticOp`, which operates on a single channel, this operation
operates on entire `pandas.DataFrame`.
"""
from warnings import warn
import pandas as pd
import numpy as np
from traits.api import (HasStrictTraits, Str, List, Constant, provides,
Callable, Any)
import cytoflow.utility as util
from .i_operation import IOperation
[docs]@provides(IOperation)
class FrameStatisticOp(HasStrictTraits):
"""
Apply a function to subsets of a data set, and add it as a statistic
to the experiment.
The `apply` function groups the data by the variables in `by`,
then applies the `function` callable to each `pandas.DataFrame`
subset. The callable should take a `pandas.DataFrame` as its only parameter.
The return type is arbitrary, but to be used with the rest of
`cytoflow` it should probably be a numeric type or an iterable of
numeric types.
Attributes
----------
name : Str
The operation name. Becomes the first element in the
`Experiment.statistics` key tuple.
function : Callable
The function used to compute the statistic. Must take a
`pandas.DataFrame` as its only argument. The return type is
arbitrary, but to be used with the rest of `cytoflow` it should
probably be a numeric type or an iterable of numeric types. If
`statistic_name` is unset, the name of the function becomes the
second in element in the `Experiment.statistics` key tuple.
statistic_name : Str
The name of the function; if present, becomes the second element in
the `Experiment.statistics` key tuple. Particularly useful if
`function` is a lambda.
by : List(Str)
A list of metadata attributes to aggregate the data before applying the
function. For example, if the experiment has two pieces of metadata,
``Time`` and ``Dox``, setting ``by = ["Time", "Dox"]`` will apply
`function` separately to each subset of the data with a unique
combination of ``Time`` and ``Dox``.
subset : Str
A Python expression sent to Experiment.query() to subset the data before
computing the statistic.
fill : Any (default = 0)
The value to use in the statistic if a slice of the data is empty.
Examples
--------
>>> stats_op = FrameStatisticOp(name = "ByDox",
... function = lambda x: np.mean(x["FITC-A"],
... statistic_name = "Mean",
... by = ["Dox"])
>>> ex2 = stats_op.apply(ex)
"""
id = Constant('edu.mit.synbio.cytoflow.operations.statistics')
friendly_id = Constant("Statistics")
name = Str
function = Callable
statistic_name = Str
by = List(Str)
subset = Str
fill = Any(0)
[docs] def apply(self, experiment):
if experiment is None:
raise util.CytoflowOpError('experiment',
"No experiment specified")
if not self.name:
raise util.CytoflowOpError('name',
"Must specify a name")
if self.name != util.sanitize_identifier(self.name):
raise util.CytoflowOpError('name',
"Name can only contain letters, numbers and underscores."
.format(self.name))
if not self.function:
raise util.CytoflowOpError('function',
"Must specify a function")
if not self.by:
raise util.CytoflowOpError('by',
"Must specify some grouping conditions "
"in 'by'")
stat_name = (self.name, self.statistic_name) \
if self.statistic_name \
else (self.name, self.function.__name__)
if stat_name in experiment.statistics:
raise util.CytoflowOpError('name',
"{} is already in the experiment's statistics"
.format(stat_name))
new_experiment = experiment.clone(deep = False)
if self.subset:
try:
experiment = experiment.query(self.subset)
except Exception as e:
raise util.CytoflowOpError('subset',
"Subset string '{0}' isn't valid"
.format(self.subset)) from e
if len(experiment) == 0:
raise util.CytoflowOpError('subset',
"Subset string '{0}' returned no events"
.format(self.subset))
for b in self.by:
if b not in experiment.conditions:
raise util.CytoflowOpError('by',
"Aggregation metadata {} not found, "
" must be one of {}"
.format(b, experiment.conditions))
unique = experiment.data[b].unique()
if len(unique) == 1:
warn("Only one category for {}".format(b), util.CytoflowOpWarning)
groupby = experiment.data.groupby(self.by)
for group, data_subset in groupby:
if len(data_subset) == 0:
warn("Group {} had no data"
.format(group),
util.CytoflowOpWarning)
# this shouldn't be necessary, but see pandas bug #38053
if len(self.by) == 1:
idx = pd.Index(experiment[self.by[0]].unique(), name = self.by[0])
else:
idx = pd.MultiIndex.from_product([experiment[x].unique() for x in self.by],
names = self.by)
stat = pd.Series(data = self.fill,
index = idx,
name = "{} : {}".format(stat_name[0], stat_name[1]),
dtype = np.dtype(object)).sort_index()
for group, data_subset in groupby:
if len(data_subset) == 0:
continue
try:
v = self.function(data_subset)
stat.at[group] = v
except Exception as e:
raise util.CytoflowOpError('function',
"Your function threw an error in group {}"
.format(group)) from e
# check for, and warn about, NaNs.
if pd.Series(stat.loc[group]).isna().any():
warn("Category {} returned {}".format(group, stat.loc[group]),
util.CytoflowOpWarning)
# try to convert to numeric, but if there are non-numeric bits ignore
stat = pd.to_numeric(stat, errors = 'ignore')
new_experiment.history.append(self.clone_traits(transient = lambda t: True))
new_experiment.statistics[stat_name] = stat
return new_experiment