def testExtra(self):
tf = TrackFormat.createInstanceFromPrefixList(["start", "a", "b", "c"], "float64", 1, "float64", 1)
self.assertTrue(tf.hasExtra(specificExtra="a"))
self.assertFalse(tf.hasExtra(specificExtra="d"))
self.assertEqual(["a", "b", "c"], tf.getExtraNames())
tfq = TrackFormatReq(interval=False, extra=["a", "b"])
self.assertFalse(tfq.isCompatibleWith(tf))
def _getRawTrackView(self, region, borderHandling, allowOverlaps):
assert len(region) == 1
from collections import OrderedDict
from gtrackcore.track.memmap.CommonMemmapFunctions import findEmptyVal
from gtrackcore.track.core.TrackView import TrackView
import numpy as np
geSource = ExternalTrackManager.getGESourceFromGalaxyOrVirtualTN(self.trackName, region.genome)
prefixList = geSource.getPrefixList()
valDataType = geSource.getValDataType()
valDim = geSource.getValDim()
weightDataType = geSource.getEdgeWeightDataType()
weightDim = geSource.getEdgeWeightDim()
startList, endList, valList, strandList, idList, edgesList, weightsList = [None]*7
extraLists=OrderedDict()
tf = TrackFormat.createInstanceFromPrefixList(prefixList, valDataType, valDim, \
weightDataType, weightDim)
if allowOverlaps and (tf.isDense() or geSource.hasNoOverlappingElements()):
raise IncompatibleTracksError(prettyPrintTrackName(self.trackName) + ' with format: '\
+ str(tf) + ' does not satisfy ' + str(self._trackFormatReq))
denseAndInterval = tf.isDense() and tf.isInterval()
numEls = 2 if denseAndInterval else 1
if valDataType == 'S':
valDataType = 'S2'
if weightDataType == 'S':
weightDataType = 'S2'
for prefix in prefixList:
if prefix == 'start':
startList = np.array([-1], dtype='int32')
elif prefix == 'end':
if denseAndInterval:
endList = np.array([0, 1], dtype='int32')
else:
endList = np.array([0], dtype='int32')
elif prefix == 'val':
valList = np.array([findEmptyVal(valDataType)] * valDim * numEls, \
dtype=valDataType).reshape((numEls, valDim) if valDim > 1 else numEls)
elif prefix == 'strand':
strandList = np.array([1] * numEls, dtype='int8')
elif prefix == 'id':
idList = np.array([''] * numEls, dtype='S1')
elif prefix == 'edges':
edgesList = np.array([['']] * numEls, dtype='S1')
elif prefix == 'weights':
weightsList = np.array([[[findEmptyVal(weightDataType)]]] * weightDim * numEls, \
dtype=weightDataType).reshape((numEls, 1, weightDim) if weightDim > 1 else (numEls, 1))
else:
extraLists[prefix] = np.array([''] * numEls, dtype='S1')
return TrackView(region, startList, endList, valList, strandList, idList, edgesList, weightsList, borderHandling, allowOverlaps, extraLists)
def testCompatibilityWithExceptions(self):
tf = TrackFormat.createInstanceFromPrefixList(["start", "val"], "float64", 1, "float64", 1)
self.assertFalse(TrackFormatReq(interval=True, strand=True, val="number").isCompatibleWith(tf))
self.assertFalse(TrackFormatReq(interval=True, strand=True, val="number").isCompatibleWith(tf, ["interval"]))
self.assertTrue(
TrackFormatReq(interval=True, strand=True, val="number").isCompatibleWith(tf, ["interval", "hasStrand"])
)
self.assertFalse(
TrackFormatReq(interval=True, strand=True, val="tc").isCompatibleWith(tf, ["interval", "hasStrand"])
)
def testWeightTypes(self):
tf = TrackFormat.createInstanceFromPrefixList(["id", "edges", "weights"], "float64", 1, "S8", 3)
self.assertTrue(tf.isWeighted(specificWeightType="category_vector"))
self.assertFalse(tf.isWeighted(specificWeightType="number"))
self.assertEqual("Vector of categories", tf.getWeightTypeName())
self.assertEqual("Linked base pairs", tf.getFormatName())
tfq = TrackFormatReq(linked=True, weights="number")
self.assertFalse(tfq.isCompatibleWith(tf))
def testValTypes(self):
tf = TrackFormat.createInstanceFromPrefixList(["start", "val"], "float128", 2, "float64", 1)
self.assertTrue(tf.isValued(specificValType="mean_sd"))
self.assertFalse(tf.isValued(specificValType="number"))
self.assertEqual("Mean and std.dev.", tf.getValTypeName())
self.assertEqual("Valued points", tf.getFormatName())
tfq = TrackFormatReq(interval=False, val="tc")
self.assertFalse(tfq.isCompatibleWith(tf))
def testExtra(self):
tf = TrackFormat.createInstanceFromPrefixList(['start', 'a', 'b', 'c'],
'float64', 1, 'float64',
1)
self.assertTrue(tf.hasExtra(specificExtra='a'))
self.assertFalse(tf.hasExtra(specificExtra='d'))
self.assertEqual(['a', 'b', 'c'], tf.getExtraNames())
tfq = TrackFormatReq(interval=False, extra=['a', 'b'])
self.assertFalse(tfq.isCompatibleWith(tf))
def testWeightTypes(self):
tf = TrackFormat.createInstanceFromPrefixList(
['id', 'edges', 'weights'], 'float64', 1, 'S8', 3)
self.assertTrue(tf.isWeighted(specificWeightType='category_vector'))
self.assertFalse(tf.isWeighted(specificWeightType='number'))
self.assertEqual('Vector of categories', tf.getWeightTypeName())
self.assertEqual('Linked base pairs', tf.getFormatName())
tfq = TrackFormatReq(linked=True, weights='number')
self.assertFalse(tfq.isCompatibleWith(tf))
def testCompatibilityWithExceptions(self):
tf = TrackFormat.createInstanceFromPrefixList(['start', 'val'],
'float64', 1, 'float64',
1)
self.assertFalse(TrackFormatReq(interval=True, strand=True, val='number')\
.isCompatibleWith(tf))
self.assertFalse(TrackFormatReq(interval=True, strand=True, val='number')\
.isCompatibleWith(tf, ['interval']))
self.assertTrue(TrackFormatReq(interval=True, strand=True, val='number')\
.isCompatibleWith(tf, ['interval', 'hasStrand']))
self.assertFalse(TrackFormatReq(interval=True, strand=True, val='tc')\
.isCompatibleWith(tf, ['interval', 'hasStrand']))
def testValTypes(self):
tf = TrackFormat.createInstanceFromPrefixList(['start', 'val'],
'float128', 2, 'float64',
1)
self.assertTrue(tf.isValued(specificValType='mean_sd'))
self.assertFalse(tf.isValued(specificValType='number'))
self.assertEqual('Mean and std.dev.', tf.getValTypeName())
self.assertEqual('Valued points', tf.getFormatName())
tfq = TrackFormatReq(interval=False, val='tc')
self.assertFalse(tfq.isCompatibleWith(tf))
def __iter__(self):
self = copy(self)
#does not support function, partitions and points:
if (False in [attrs in self._geSource.getPrefixList() for attrs in ['start', 'end']]):
raise NotSupportedError('Binning file must be segments. Current file format: ' + \
TrackFormat.createInstanceFromPrefixList(self._geSource.getPrefixList(), \
self._geSource.getValDataType(), \
self._geSource.getValDim(), \
self._geSource.getEdgeWeightDataType(), \
self._geSource.getEdgeWeightDim()).getFormatName() )
self._geIter = self._geSource.__iter__()
return self
def __iter__(self):
self = copy(self)
#does not support function, partitions and points:
if (False in [
attrs in self._geSource.getPrefixList()
for attrs in ['start', 'end']
]):
raise NotSupportedError('Binning file must be segments. Current file format: ' + \
TrackFormat.createInstanceFromPrefixList(self._geSource.getPrefixList(), \
self._geSource.getValDataType(), \
self._geSource.getValDim(), \
self._geSource.getEdgeWeightDataType(), \
self._geSource.getEdgeWeightDim()).getFormatName() )
self._geIter = self._geSource.__iter__()
return self
def _getRawTrackView(self, region, borderHandling, allowOverlaps):
assert len(region) == 1
from collections import OrderedDict
from gtrackcore.track.memmap.CommonMemmapFunctions import findEmptyVal
from gtrackcore.track.core.TrackView import TrackView
import numpy as np
geSource = ExternalTrackManager.getGESourceFromGalaxyOrVirtualTN(
self.trackName, region.genome)
prefixList = geSource.getPrefixList()
valDataType = geSource.getValDataType()
valDim = geSource.getValDim()
weightDataType = geSource.getEdgeWeightDataType()
weightDim = geSource.getEdgeWeightDim()
startList, endList, valList, strandList, idList, edgesList, weightsList = [
None
] * 7
extraLists = OrderedDict()
tf = TrackFormat.createInstanceFromPrefixList(prefixList, valDataType, valDim, \
weightDataType, weightDim)
if allowOverlaps and (tf.isDense()
or geSource.hasNoOverlappingElements()):
raise IncompatibleTracksError(prettyPrintTrackName(self.trackName) + ' with format: '\
+ str(tf) + ' does not satisfy ' + str(self._trackFormatReq))
denseAndInterval = tf.isDense() and tf.isInterval()
numEls = 2 if denseAndInterval else 1
if valDataType == 'S':
valDataType = 'S2'
if weightDataType == 'S':
weightDataType = 'S2'
for prefix in prefixList:
if prefix == 'start':
startList = np.array([-1], dtype='int32')
elif prefix == 'end':
if denseAndInterval:
endList = np.array([0, 1], dtype='int32')
else:
endList = np.array([0], dtype='int32')
elif prefix == 'val':
valList = np.array([findEmptyVal(valDataType)] * valDim * numEls, \
dtype=valDataType).reshape((numEls, valDim) if valDim > 1 else numEls)
elif prefix == 'strand':
strandList = np.array([1] * numEls, dtype='int8')
elif prefix == 'id':
idList = np.array([''] * numEls, dtype='S1')
elif prefix == 'edges':
edgesList = np.array([['']] * numEls, dtype='S1')
elif prefix == 'weights':
weightsList = np.array([[[findEmptyVal(weightDataType)]]] * weightDim * numEls, \
dtype=weightDataType).reshape((numEls, 1, weightDim) if weightDim > 1 else (numEls, 1))
else:
extraLists[prefix] = np.array([''] * numEls, dtype='S1')
return TrackView(region, startList, endList, valList, strandList,
idList, edgesList, weightsList, borderHandling,
allowOverlaps, extraLists)
def getTrackFormat(self):
return TrackFormat.createInstanceFromPrefixList(self._prefixList, \
self._valDataType, \
self._valDim, \
self._weightDataType, \
self._weightDim)
def getTrackFormat(self):
return TrackFormat.createInstanceFromPrefixList(self._prefixList, \
self._valDataType, \
self._valDim, \
self._weightDataType, \
self._weightDim)
