211 lines
7.5 KiB
Python
211 lines
7.5 KiB
Python
# -*- coding: utf-8 -*-
|
|
from ..Qt import QtCore
|
|
from .. import parametertree as ptree
|
|
import numpy as np
|
|
from collections import OrderedDict
|
|
from .. import functions as fn
|
|
from ..python2_3 import basestring
|
|
|
|
__all__ = ['DataFilterWidget']
|
|
|
|
|
|
class DataFilterWidget(ptree.ParameterTree):
|
|
"""
|
|
This class allows the user to filter multi-column data sets by specifying
|
|
multiple criteria
|
|
|
|
Wraps methods from DataFilterParameter: setFields, generateMask,
|
|
filterData, and describe.
|
|
"""
|
|
|
|
sigFilterChanged = QtCore.Signal(object)
|
|
|
|
def __init__(self):
|
|
ptree.ParameterTree.__init__(self, showHeader=False)
|
|
self.params = DataFilterParameter()
|
|
|
|
self.setParameters(self.params)
|
|
self.params.sigFilterChanged.connect(self.sigFilterChanged)
|
|
|
|
self.setFields = self.params.setFields
|
|
self.generateMask = self.params.generateMask
|
|
self.filterData = self.params.filterData
|
|
self.describe = self.params.describe
|
|
|
|
def parameters(self):
|
|
return self.params
|
|
|
|
def addFilter(self, name):
|
|
"""Add a new filter and return the created parameter item.
|
|
"""
|
|
return self.params.addNew(name)
|
|
|
|
|
|
class DataFilterParameter(ptree.types.GroupParameter):
|
|
"""A parameter group that specifies a set of filters to apply to tabular data.
|
|
"""
|
|
sigFilterChanged = QtCore.Signal(object)
|
|
|
|
def __init__(self):
|
|
self.fields = {}
|
|
ptree.types.GroupParameter.__init__(self, name='Data Filter', addText='Add filter..', addList=[])
|
|
self.sigTreeStateChanged.connect(self.filterChanged)
|
|
|
|
def filterChanged(self):
|
|
self.sigFilterChanged.emit(self)
|
|
|
|
def addNew(self, name):
|
|
mode = self.fields[name].get('mode', 'range')
|
|
if mode == 'range':
|
|
child = self.addChild(RangeFilterItem(name, self.fields[name]))
|
|
elif mode == 'enum':
|
|
child = self.addChild(EnumFilterItem(name, self.fields[name]))
|
|
return child
|
|
|
|
def fieldNames(self):
|
|
return self.fields.keys()
|
|
|
|
def setFields(self, fields):
|
|
"""Set the list of fields that are available to be filtered.
|
|
|
|
*fields* must be a dict or list of tuples that maps field names
|
|
to a specification describing the field. Each specification is
|
|
itself a dict with either ``'mode':'range'`` or ``'mode':'enum'``::
|
|
|
|
filter.setFields([
|
|
('field1', {'mode': 'range'}),
|
|
('field2', {'mode': 'enum', 'values': ['val1', 'val2', 'val3']}),
|
|
('field3', {'mode': 'enum', 'values': {'val1':True, 'val2':False, 'val3':True}}),
|
|
])
|
|
"""
|
|
with fn.SignalBlock(self.sigTreeStateChanged, self.filterChanged):
|
|
self.fields = OrderedDict(fields)
|
|
names = self.fieldNames()
|
|
self.setAddList(names)
|
|
|
|
# update any existing filters
|
|
for ch in self.children():
|
|
name = ch.fieldName
|
|
if name in fields:
|
|
ch.updateFilter(fields[name])
|
|
self.sigFilterChanged.emit(self)
|
|
|
|
def filterData(self, data):
|
|
if len(data) == 0:
|
|
return data
|
|
return data[self.generateMask(data)]
|
|
|
|
def generateMask(self, data):
|
|
"""Return a boolean mask indicating whether each item in *data* passes
|
|
the filter critera.
|
|
"""
|
|
mask = np.ones(len(data), dtype=bool)
|
|
if len(data) == 0:
|
|
return mask
|
|
for fp in self:
|
|
if fp.value() is False:
|
|
continue
|
|
mask &= fp.generateMask(data, mask.copy())
|
|
#key, mn, mx = fp.fieldName, fp['Min'], fp['Max']
|
|
|
|
#vals = data[key]
|
|
#mask &= (vals >= mn)
|
|
#mask &= (vals < mx) ## Use inclusive minimum and non-inclusive maximum. This makes it easier to create non-overlapping selections
|
|
return mask
|
|
|
|
def describe(self):
|
|
"""Return a list of strings describing the currently enabled filters."""
|
|
desc = []
|
|
for fp in self:
|
|
if fp.value() is False:
|
|
continue
|
|
desc.append(fp.describe())
|
|
return desc
|
|
|
|
|
|
class RangeFilterItem(ptree.types.SimpleParameter):
|
|
def __init__(self, name, opts):
|
|
self.fieldName = name
|
|
units = opts.get('units', '')
|
|
self.units = units
|
|
ptree.types.SimpleParameter.__init__(self,
|
|
name=name, autoIncrementName=True, type='bool', value=True, removable=True, renamable=True,
|
|
children=[
|
|
#dict(name="Field", type='list', value=name, values=fields),
|
|
dict(name='Min', type='float', value=0.0, suffix=units, siPrefix=True),
|
|
dict(name='Max', type='float', value=1.0, suffix=units, siPrefix=True),
|
|
])
|
|
|
|
def generateMask(self, data, mask):
|
|
vals = data[self.fieldName][mask]
|
|
mask[mask] = (vals >= self['Min']) & (vals < self['Max']) ## Use inclusive minimum and non-inclusive maximum. This makes it easier to create non-overlapping selections
|
|
return mask
|
|
|
|
def describe(self):
|
|
return "%s < %s < %s" % (fn.siFormat(self['Min'], suffix=self.units), self.fieldName, fn.siFormat(self['Max'], suffix=self.units))
|
|
|
|
def updateFilter(self, opts):
|
|
pass
|
|
|
|
|
|
class EnumFilterItem(ptree.types.SimpleParameter):
|
|
def __init__(self, name, opts):
|
|
self.fieldName = name
|
|
ptree.types.SimpleParameter.__init__(self,
|
|
name=name, autoIncrementName=True, type='bool', value=True, removable=True, renamable=True)
|
|
self.setEnumVals(opts)
|
|
|
|
def generateMask(self, data, startMask):
|
|
vals = data[self.fieldName][startMask]
|
|
mask = np.ones(len(vals), dtype=bool)
|
|
otherMask = np.ones(len(vals), dtype=bool)
|
|
for c in self:
|
|
key = c.maskValue
|
|
if key == '__other__':
|
|
m = ~otherMask
|
|
else:
|
|
m = vals != key
|
|
otherMask &= m
|
|
if c.value() is False:
|
|
mask &= m
|
|
startMask[startMask] = mask
|
|
return startMask
|
|
|
|
def describe(self):
|
|
vals = [ch.name() for ch in self if ch.value() is True]
|
|
return "%s: %s" % (self.fieldName, ', '.join(vals))
|
|
|
|
def updateFilter(self, opts):
|
|
self.setEnumVals(opts)
|
|
|
|
def setEnumVals(self, opts):
|
|
vals = opts.get('values', {})
|
|
|
|
prevState = {}
|
|
for ch in self.children():
|
|
prevState[ch.name()] = ch.value()
|
|
self.removeChild(ch)
|
|
|
|
if not isinstance(vals, dict):
|
|
vals = OrderedDict([(v,(str(v), True)) for v in vals])
|
|
|
|
# Each filterable value can come with either (1) a string name, (2) a bool
|
|
# indicating whether the value is enabled by default, or (3) a tuple providing
|
|
# both.
|
|
for val,valopts in vals.items():
|
|
if isinstance(valopts, bool):
|
|
enabled = valopts
|
|
vname = str(val)
|
|
elif isinstance(valopts, basestring):
|
|
enabled = True
|
|
vname = valopts
|
|
elif isinstance(valopts, tuple):
|
|
vname, enabled = valopts
|
|
|
|
ch = ptree.Parameter.create(name=vname, type='bool', value=prevState.get(vname, enabled))
|
|
ch.maskValue = val
|
|
self.addChild(ch)
|
|
ch = ptree.Parameter.create(name='(other)', type='bool', value=prevState.get('(other)', True))
|
|
ch.maskValue = '__other__'
|
|
self.addChild(ch)
|