150 lines
5.3 KiB
Python
150 lines
5.3 KiB
Python
from pyqtgraph.Qt import QtGui, QtCore
|
|
import pyqtgraph.parametertree as ptree
|
|
import numpy as np
|
|
from pyqtgraph.pgcollections import OrderedDict
|
|
import pyqtgraph as pg
|
|
|
|
__all__ = ['DataFilterWidget']
|
|
|
|
class DataFilterWidget(ptree.ParameterTree):
|
|
"""
|
|
This class allows the user to filter multi-column data sets by specifying
|
|
multiple criteria
|
|
"""
|
|
|
|
sigFilterChanged = QtCore.Signal(object)
|
|
|
|
def __init__(self):
|
|
ptree.ParameterTree.__init__(self, showHeader=False)
|
|
self.params = DataFilterParameter()
|
|
|
|
self.setParameters(self.params)
|
|
self.params.sigTreeStateChanged.connect(self.filterChanged)
|
|
|
|
self.setFields = self.params.setFields
|
|
self.filterData = self.params.filterData
|
|
self.describe = self.params.describe
|
|
|
|
def filterChanged(self):
|
|
self.sigFilterChanged.emit(self)
|
|
|
|
def parameters(self):
|
|
return self.params
|
|
|
|
|
|
class DataFilterParameter(ptree.types.GroupParameter):
|
|
|
|
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':
|
|
self.addChild(RangeFilterItem(name, self.fields[name]))
|
|
elif mode == 'enum':
|
|
self.addChild(EnumFilterItem(name, self.fields[name]))
|
|
|
|
|
|
def fieldNames(self):
|
|
return self.fields.keys()
|
|
|
|
def setFields(self, fields):
|
|
self.fields = OrderedDict(fields)
|
|
names = self.fieldNames()
|
|
self.setAddList(names)
|
|
|
|
def filterData(self, data):
|
|
if len(data) == 0:
|
|
return data
|
|
return data[self.generateMask(data)]
|
|
|
|
def generateMask(self, data):
|
|
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" % (pg.siFormat(self['Min'], suffix=self.units), self.fieldName, pg.siFormat(self['Max'], suffix=self.units))
|
|
|
|
class EnumFilterItem(ptree.types.SimpleParameter):
|
|
def __init__(self, name, opts):
|
|
self.fieldName = name
|
|
vals = opts.get('values', [])
|
|
childs = []
|
|
if isinstance(vals, list):
|
|
vals = OrderedDict([(v,str(v)) for v in vals])
|
|
for val,vname in vals.items():
|
|
ch = ptree.Parameter.create(name=vname, type='bool', value=True)
|
|
ch.maskValue = val
|
|
childs.append(ch)
|
|
ch = ptree.Parameter.create(name='(other)', type='bool', value=True)
|
|
ch.maskValue = '__other__'
|
|
childs.append(ch)
|
|
|
|
ptree.types.SimpleParameter.__init__(self,
|
|
name=name, autoIncrementName=True, type='bool', value=True, removable=True, renamable=True,
|
|
children=childs)
|
|
|
|
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)) |