#!/usr/bin/env python3.4
# coding: latin-1
# (c) Massachusetts Institute of Technology 2015-2018
# (c) Brian Teague 2018-2019
#
# 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.range
-------------------------
'''
from traits.api import (HasStrictTraits, Float, Str, Instance, Bool,
provides, on_trait_change, Any, Constant)
import matplotlib.pyplot as plt
from matplotlib.lines import Line2D
import cytoflow.utility as util
from cytoflow.views import HistogramView, ISelectionView
from .i_operation import IOperation
from .base_op_views import Op1DView
[docs]@provides(IOperation)
class RangeOp(HasStrictTraits):
"""
Apply a range gate to a cytometry experiment.
Attributes
----------
name : Str
The operation name. Used to name the new metadata field in the
experiment that's created by :meth:`apply`
channel : Str
The name of the channel to apply the range gate.
low : Float
The lowest value to include in this gate.
high : Float
The highest value to include in this gate.
Examples
--------
.. plot::
:context: close-figs
Make a little data set.
>>> import cytoflow as flow
>>> import_op = flow.ImportOp()
>>> import_op.tubes = [flow.Tube(file = "Plate01/RFP_Well_A3.fcs",
... conditions = {'Dox' : 10.0}),
... flow.Tube(file = "Plate01/CFP_Well_A4.fcs",
... conditions = {'Dox' : 1.0})]
>>> import_op.conditions = {'Dox' : 'float'}
>>> ex = import_op.apply()
Create and parameterize the operation.
.. plot::
:context: close-figs
>>> range_op = flow.RangeOp(name = 'Range',
... channel = 'Y2-A',
... low = 2000,
... high = 10000)
Plot a diagnostic view
.. plot::
:context: close-figs
>>> rv = range_op.default_view(scale = 'log')
>>> rv.plot(ex)
.. note::
If you want to use the interactive default view in a Jupyter notebook,
make sure you say ``%matplotlib notebook`` in the first cell
(instead of ``%matplotlib inline`` or similar). Then call
``default_view()`` with ``interactive = True``::
rv = range_op.default_view(scale = 'log',
interactive = True)
rv.plot(ex)
Apply the gate, and show the result
.. plot::
:context: close-figs
>>> ex2 = range_op.apply(ex)
>>> ex2.data.groupby('Range').size()
Range
False 16042
True 3958
dtype: int64
"""
# traits
id = Constant('edu.mit.synbio.cytoflow.operations.range')
friendly_id = Constant('Range')
name = Str
channel = Str
low = Float
high = Float
_selection_view = Instance('RangeSelection', transient = True)
[docs] def apply(self, experiment):
"""Applies the range gate to an experiment.
Parameters
----------
experiment : Experiment
the old_experiment to which this op is applied
Returns
-------
Experiment
a new experiment, the same as old :class:`~Experiment` but with a new
column of type ``bool`` with the same as the operation name. The
bool is ``True`` if the event's measurement in :attr:`channel` is
greater than :attr:`low` and less than :attr:`high`; it is ``False``
otherwise.
"""
if experiment is None:
raise util.CytoflowOpError('experiment', "No experiment specified")
# make sure name got set!
if not self.name:
raise util.CytoflowOpError('name',
"You have to set the gate's name "
"before applying it!")
if self.name != util.sanitize_identifier(self.name):
raise util.CytoflowOpError('name',
"Name can only contain letters, numbers and underscores."
.format(self.name))
if self.name in experiment.data.columns:
raise util.CytoflowOpError('name',
"Experiment already has a column named {0}"
.format(self.name))
if not self.channel:
raise util.CytoflowOpError('channel', "Channel not specified")
if not self.channel in experiment.channels:
raise util.CytoflowOpError('channel',
"Channel {0} not in the experiment"
.format(self.channel))
if self.high <= self.low:
raise util.CytoflowOpError('high',
"range high must be > range low")
if self.high <= experiment[self.channel].min():
raise util.CytoflowOpError('high',
"range high must be > {0}"
.format(experiment[self.channel].min()))
if self.low >= experiment[self.channel].max():
raise util.CytoflowOpError('low',
"range low must be < {0}"
.format(experiment[self.channel].max()))
gate = experiment[self.channel].between(self.low, self.high)
new_experiment = experiment.clone()
new_experiment.add_condition(self.name, "bool", gate)
new_experiment.history.append(self.clone_traits(transient = lambda _: True))
return new_experiment
[docs] def default_view(self, **kwargs):
self._selection_view = RangeSelection(op = self)
self._selection_view.trait_set(**kwargs)
return self._selection_view
[docs]@provides(ISelectionView)
class RangeSelection(Op1DView, HistogramView):
"""
Plots, and lets the user interact with, a selection on the X axis.
Attributes
----------
interactive : Bool
is this view interactive? Ie, can the user set min and max
with a mouse drag?
Notes
-----
We inherit :attr:`xfacet` and :attr:`yfacet` from `cytoflow.views.HistogramView`, but
they must both be unset!
Examples
--------
In an IPython notebook with `%matplotlib notebook`
>>> r = RangeOp(name = "RangeGate",
... channel = 'Y2-A')
>>> rv = r.default_view()
>>> rv.interactive = True
>>> rv.plot(ex2)
>>> ### draw a range on the plot ###
>>> print r.low, r.high
"""
id = Constant('edu.mit.synbio.cytoflow.views.range')
friendly_id = Constant("Range Selection")
xfacet = Constant(None)
yfacet = Constant(None)
scale = util.ScaleEnum
interactive = Bool(False, transient = True)
# internal state.
_ax = Any(transient = True)
_span = Instance(util.SpanSelector, transient = True)
_low_line = Instance(Line2D, transient = True)
_high_line = Instance(Line2D, transient = True)
_hline = Instance(Line2D, transient = True)
[docs] def plot(self, experiment, **kwargs):
"""
Plot the underlying histogram and then plot the selection on top of it.
Parameters
----------
"""
if experiment is None:
raise util.CytoflowViewError('experiment',
"No experiment specified")
super(RangeSelection, self).plot(experiment, **kwargs)
self._ax = plt.gca()
self._draw_span()
self._interactive()
@on_trait_change('op.low, op.high', post_init = True)
def _draw_span(self):
if not (self._ax and self.op.low and self.op.high):
return
if self._low_line and self._low_line in self._ax.lines:
self._low_line.remove()
if self._high_line and self._high_line in self._ax.lines:
self._high_line.remove()
if self._hline and self._hline in self._ax.lines:
self._hline.remove()
self._low_line = plt.axvline(self.op.low, linewidth=3, color='blue')
self._high_line = plt.axvline(self.op.high, linewidth=3, color='blue')
ymin, ymax = plt.ylim()
y = (ymin + ymax) / 2.0
self._hline = plt.plot([self.op.low, self.op.high],
[y, y],
color='blue',
linewidth = 2)[0]
plt.draw()
@on_trait_change('interactive', post_init = True)
def _interactive(self):
if self._ax and self.interactive:
self._span = util.SpanSelector(self._ax,
onselect=self._onselect,
span_stays=False,
useblit = True)
else:
self._span = None
def _onselect(self, xmin, xmax):
"""Update selection traits"""
self.op.low = xmin
self.op.high = xmax
util.expand_class_attributes(RangeSelection)
util.expand_method_parameters(RangeSelection, RangeSelection.plot)
if __name__ == '__main__':
import cytoflow as flow
tube1 = flow.Tube(file = '../../cytoflow/tests/data/Plate01/RFP_Well_A3.fcs',
conditions = {"Dox" : 10.0})
tube2 = flow.Tube(file = '../../cytoflow/tests/data/Plate01/CFP_Well_A4.fcs',
conditions = {"Dox" : 1.0})
ex = flow.ImportOp(conditions = {"Dox" : "float"}, tubes = [tube1, tube2])
r = flow.RangeOp(channel = 'Y2-A')
rv = r.default_view(scale = "logicle")
plt.ioff()
rv.plot(ex)
rv.interactive = True
plt.show()