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from collections import OrderedDict
import numpy as np
from .. import functions as fn
from .. import parametertree as ptree
from ..Qt import QtCore
__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]))
else:
raise ValueError("field mode must be 'range' or 'enum'")
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, limits=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, str):
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)
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