def _loadReferenceInfo(self):
_referenceGroupTbl = np.rec.fromrecords(
zip(self.file["/RefGroup/ID"],
self.file["/RefGroup/RefInfoID"],
[path[1:] for path in self.file["/RefGroup/Path"]]),
dtype=[("ID" , int),
("RefInfoID", int),
("Name" , object)])
_referenceInfoTbl = np.rec.fromrecords(
zip(self.file["/RefInfo/ID"],
self.file["/RefInfo/FullName"],
self.file["/RefInfo/Length"],
self.file["/RefInfo/MD5"]) ,
dtype=[("RefInfoID", int),
("FullName" , object),
("Length" , int),
("MD5" , object)])
self._referenceInfoTable = \
rec_join("RefInfoID", _referenceGroupTbl, _referenceInfoTbl, jointype="inner")
if self.isSorted:
_offsetTable = self.file["/RefGroup/OffsetTable"].value \
.view(dtype=OFFSET_TABLE_DTYPE) \
.view(np.recarray) \
.flatten()
self._referenceInfoTable = rec_join("ID",
self._referenceInfoTable,
_offsetTable,
jointype="inner")
self._referenceDict = {}
self._readLocatorByKey = {}
for record in self._referenceInfoTable:
if record.ID != -1:
assert record.ID != record.Name
shortName = splitFastaHeader(record.FullName)[0]
if (shortName in self._referenceDict or
record.ID in self._referenceDict or
record.Name in self._referenceDict or
record.FullName in self._referenceDict or
record.MD5 in self._referenceDict):
raise ValueError, "Duplicate reference contig sequence or identifier"
else:
self._referenceDict[shortName] = record
self._referenceDict[record.ID] = record
self._referenceDict[record.Name] = record
self._referenceDict[record.FullName] = record
self._referenceDict[record.MD5] = record
if self.isSorted:
readLocator = makeReadLocator(self, record.ID)
self._readLocatorByKey[record.ID] = readLocator
self._readLocatorByKey[shortName] = readLocator
def _loadReferenceInfo(self):
_referenceGroupTbl = np.rec.fromrecords(
zip(self.file["/RefGroup/ID"][:],
self.file["/RefGroup/RefInfoID"][:],
[path[1:] for path in self.file["/RefGroup/Path"]]),
dtype=[("ID" , int),
("RefInfoID", int),
("Name" , object)])
_referenceInfoTbl = np.rec.fromrecords(
zip(self.file["/RefInfo/ID"][:],
self.file["/RefInfo/FullName"][:],
self.file["/RefInfo/Length"][:],
self.file["/RefInfo/MD5"][:]) ,
dtype=[("RefInfoID", int),
("FullName" , object),
("Length" , int),
("MD5" , object)])
self._referenceInfoTable = \
rec_join("RefInfoID", _referenceGroupTbl, _referenceInfoTbl, jointype="inner")
if self.isSorted:
_offsetTable = self.file["/RefGroup/OffsetTable"].value \
.view(dtype=OFFSET_TABLE_DTYPE) \
.view(np.recarray) \
.flatten()
self._referenceInfoTable = rec_join("ID",
self._referenceInfoTable,
_offsetTable,
jointype="inner")
self._referenceDict = {}
self._readLocatorByKey = {}
# For cmp.h5 files with large numbers of references, accessing
# the recarray fields in the inner loop was terribly slow.
# This makes things faster, though the code is less
# straightforward. (One of the tradeoffs we have to make
# without a compiler to help us...)
recordID = self._referenceInfoTable.ID
recordName = self._referenceInfoTable.Name
recordFullName = self._referenceInfoTable.FullName
recordMD5 = self._referenceInfoTable.MD5
for i, record in enumerate(self._referenceInfoTable):
if recordID[i] != -1:
assert recordID[i] != record.Name
shortName = splitFastaHeader(record.FullName)[0]
if (shortName in self._referenceDict or
recordID[i] in self._referenceDict or
recordName[i] in self._referenceDict or
recordFullName[i] in self._referenceDict or
recordMD5[i] in self._referenceDict):
raise ValueError, "Duplicate reference contig sequence or identifier"
else:
self._referenceDict[shortName] = record
self._referenceDict[recordID[i]] = record
self._referenceDict[recordName[i]] = record
self._referenceDict[recordFullName[i]] = record
self._referenceDict[recordMD5[i]] = record
if self.isSorted:
readLocator = makeReadLocator(self, recordID[i])
self._readLocatorByKey[recordID[i]] = readLocator
self._readLocatorByKey[shortName] = readLocator
def __init__(self, filenameOrH5File):
if isinstance(filenameOrH5File, h5py.File):
if filenameOrH5File.mode != "r":
raise ValueError(
"HDF5 files used by CmpH5Reader must be opened read-only!")
self.filename = filenameOrH5File.filename
self.file = filenameOrH5File
else:
try:
self.filename = abspath(expanduser(filenameOrH5File))
self.file = h5py.File(self.filename, "r")
except IOError:
raise IOError, ("Invalid or nonexistent cmp.h5 file %s" %
filenameOrH5File)
if len(self.file["/AlnInfo/AlnIndex"]) == 0:
raise ValueError, "Empty cmp.h5 file, cannot be read by CmpH5Reader"
rawAlignmentIndex = self.file["/AlnInfo/AlnIndex"].value
self._alignmentIndex = rawAlignmentIndex.view(dtype = ALIGNMENT_INDEX_DTYPE) \
.view(np.recarray) \
.flatten()
# This is the only sneaky part of this whole class. We do not
# store the raw h5py group object; rather we cache a dict of {
# dataset_name -> dataset }. This way we avoid B-tree
# scanning in basic data access.
self._alignmentGroupById = {}
for (alnGroupId, alnGroupPath) in zip(self.file["/AlnGroup/ID"],
self.file["/AlnGroup/Path"]):
alnGroup = self.file[alnGroupPath]
self._alignmentGroupById[alnGroupId] = dict(alnGroup.items())
numMovies = len(self.file["/MovieInfo/ID"])
if "FrameRate" in self.file["/MovieInfo"]:
frameRate = self.file["/MovieInfo/FrameRate"].value
timeScale = 1.0 / frameRate
else:
frameRate = [np.nan] * numMovies
timeScale = [1.0] * numMovies
self._movieInfoTable = np.rec.fromrecords(zip(
self.file["/MovieInfo/ID"], self.file["/MovieInfo/Name"],
frameRate, timeScale),
dtype=[("ID", int),
("Name", object),
("FrameRate", float),
("TimeScale", float)])
self._movieDict = {}
for record in self._movieInfoTable:
assert record.ID not in self._movieDict
self._movieDict[record.ID] = record
_referenceGroupTbl = np.rec.fromrecords(zip(
self.file["/RefGroup/ID"], self.file["/RefGroup/RefInfoID"],
[path[1:] for path in self.file["/RefGroup/Path"]]),
dtype=[("ID", int),
("RefInfoID", int),
("Name", object)])
_referenceInfoTbl = np.rec.fromrecords(zip(
self.file["/RefInfo/ID"], self.file["/RefInfo/FullName"],
self.file["/RefInfo/Length"], self.file["/RefInfo/MD5"]),
dtype=[("RefInfoID", int),
("FullName", object),
("Length", int),
("MD5", object)])
self._referenceInfoTable = \
rec_join("RefInfoID", _referenceGroupTbl, _referenceInfoTbl, jointype="inner")
if self.isSorted:
_offsetTable = self.file["/RefGroup/OffsetTable"].value \
.view(dtype=OFFSET_TABLE_DTYPE) \
.view(np.recarray) \
.flatten()
self._referenceInfoTable = rec_join("ID",
self._referenceInfoTable,
_offsetTable,
jointype="inner")
self._referenceDict = {}
for record in self._referenceInfoTable:
if record.ID != -1:
assert record.ID != record.Name
if (record.ID in self._referenceDict
or record.Name in self._referenceDict
or record.FullName in self._referenceDict
or record.MD5 in self._referenceDict):
raise ValueError, "Duplicate reference contig sequence or identifier"
else:
self._referenceDict[record.ID] = record
self._referenceDict[record.Name] = record
self._referenceDict[record.FullName] = record
self._referenceDict[record.MD5] = record
self._readLocatorById = {}
if self.isSorted:
for refId in self.file["/RefGroup/ID"]:
self._readLocatorById[refId] = makeReadLocator(self, refId)
if "NumPasses" in self.file["/AlnInfo"]:
self.numPasses = self.file["/AlnInfo/NumPasses"].value
if "Barcode" in self.file["/AlnInfo"]:
# Build forward and backwards id<->label lookup tables
self._barcodeName = OrderedDict(
zip(self.file["/BarcodeInfo/ID"],
self.file["/BarcodeInfo/Name"]))
self._barcode = OrderedDict(
zip(self.file["/BarcodeInfo/Name"],
self.file["/BarcodeInfo/ID"]))
# Barcode ID per row
self._barcodes = self.file["/AlnInfo/Barcode"].value[:, 1]
if "ZScore" in self.file["/AlnInfo"]:
self.zScore = self.file["/AlnInfo/ZScore"].value
self.basH5Collection = None
self._sequencingChemistry = None
def _loadReferenceInfo(self):
_referenceGroupTbl = np.rec.fromrecords(zip(
self.file["/RefGroup/ID"][:], self.file["/RefGroup/RefInfoID"][:],
[path[1:] for path in self.file["/RefGroup/Path"]]),
dtype=[("ID", int),
("RefInfoID", int),
("Name", object)])
_referenceInfoTbl = np.rec.fromrecords(zip(
self.file["/RefInfo/ID"][:], self.file["/RefInfo/FullName"][:],
self.file["/RefInfo/Length"][:], self.file["/RefInfo/MD5"][:]),
dtype=[("RefInfoID", int),
("FullName", object),
("Length", int),
("MD5", object)])
self._referenceInfoTable = \
rec_join("RefInfoID", _referenceGroupTbl, _referenceInfoTbl, jointype="inner")
if self.isSorted:
_offsetTable = self.file["/RefGroup/OffsetTable"].value \
.view(dtype=OFFSET_TABLE_DTYPE) \
.view(np.recarray) \
.flatten()
self._referenceInfoTable = rec_join("ID",
self._referenceInfoTable,
_offsetTable,
jointype="inner")
self._referenceDict = {}
self._readLocatorByKey = {}
# For cmp.h5 files with large numbers of references, accessing
# the recarray fields in the inner loop was terribly slow.
# This makes things faster, though the code is less
# straightforward. (One of the tradeoffs we have to make
# without a compiler to help us...)
recordID = self._referenceInfoTable.ID
recordName = self._referenceInfoTable.Name
recordFullName = self._referenceInfoTable.FullName
recordMD5 = self._referenceInfoTable.MD5
for i, record in enumerate(self._referenceInfoTable):
if recordID[i] != -1:
assert recordID[i] != record.Name
shortName = splitFastaHeader(record.FullName)[0]
if (shortName in self._referenceDict
or recordID[i] in self._referenceDict
or recordName[i] in self._referenceDict
or recordFullName[i] in self._referenceDict
or recordMD5[i] in self._referenceDict):
raise ValueError(
"Duplicate reference contig sequence or identifier")
else:
self._referenceDict[shortName] = record
self._referenceDict[recordID[i]] = record
self._referenceDict[recordName[i]] = record
self._referenceDict[recordFullName[i]] = record
self._referenceDict[recordMD5[i]] = record
if self.isSorted:
readLocator = makeReadLocator(self, recordID[i])
self._readLocatorByKey[recordID[i]] = readLocator
self._readLocatorByKey[shortName] = readLocator
def __init__(self, filenameOrH5File):
if isinstance(filenameOrH5File, h5py.File):
if filenameOrH5File.mode != "r":
raise ValueError("HDF5 files used by CmpH5Reader must be opened read-only!")
self.filename = filenameOrH5File.filename
self.file = filenameOrH5File
else:
self.filename = abspath(expanduser(filenameOrH5File))
self.file = h5py.File(self.filename, "r")
rawAlignmentIndex = self.file["/AlnInfo/AlnIndex"].value
self._alignmentIndex = rawAlignmentIndex.view(dtype = ALIGNMENT_INDEX_DTYPE) \
.view(np.recarray) \
.flatten()
# This is the only sneaky part of this whole class. We do not
# store the raw h5py group object; rather we cache a dict of {
# dataset_name -> dataset }. This way we avoid B-tree
# scanning in basic data access.
self._alignmentGroupById = {}
for (alnGroupId, alnGroupPath) in zip(self.file["/AlnGroup/ID"],
self.file["/AlnGroup/Path"]):
alnGroup = self.file[alnGroupPath]
self._alignmentGroupById[alnGroupId] = dict(alnGroup.items())
numMovies = len(self.file["/MovieInfo/ID"])
if "FrameRate" in self.file["/MovieInfo"]:
frameRate = self.file["/MovieInfo/FrameRate"].value
timeScale = 1.0/frameRate
else:
frameRate = [np.nan] * numMovies
timeScale = [1.0] * numMovies
if "SequencingChemistry" in self.file["/MovieInfo"]:
sequencingChemistry = self.file["/MovieInfo/SequencingChemistry"].value
else:
sequencingChemistry = ["unknown"] * numMovies
self._movieInfoTable = np.rec.fromrecords(
zip(self.file["/MovieInfo/ID"],
self.file["/MovieInfo/Name"],
frameRate,
timeScale,
sequencingChemistry),
dtype=[("ID" , int),
("Name" , object),
("FrameRate" , float),
("TimeScale" , float),
("SequencingChemistry" , object)])
self._movieDict = {}
for record in self._movieInfoTable:
assert record.ID not in self._movieDict
self._movieDict[record.ID] = record
_referenceGroupTbl = np.rec.fromrecords(
zip(self.file["/RefGroup/ID"],
self.file["/RefGroup/RefInfoID"],
[path[1:] for path in self.file["/RefGroup/Path"]]),
dtype=[("ID" , int),
("RefInfoID", int),
("Name" , object)])
_referenceInfoTbl = np.rec.fromrecords(
zip(self.file["/RefInfo/ID"],
self.file["/RefInfo/FullName"],
self.file["/RefInfo/Length"],
self.file["/RefInfo/MD5"]) ,
dtype=[("RefInfoID", int),
("FullName" , object),
("Length" , int),
("MD5" , object)])
self._referenceInfoTable = \
rec_join("RefInfoID", _referenceGroupTbl, _referenceInfoTbl, jointype="inner")
if self.isSorted:
_offsetTable = self.file["/RefGroup/OffsetTable"].value \
.view(dtype=OFFSET_TABLE_DTYPE) \
.view(np.recarray) \
.flatten()
self._referenceInfoTable = rec_join("ID",
self._referenceInfoTable,
_offsetTable,
jointype="inner")
self._referenceDict = {}
for record in self._referenceInfoTable:
if record.ID != -1:
assert record.ID != record.Name
if (record.ID in self._referenceDict or
record.Name in self._referenceDict or
record.FullName in self._referenceDict or
record.MD5 in self._referenceDict):
raise ValueError, "Duplicate reference contig sequence or identifier"
else:
self._referenceDict[record.ID] = record
self._referenceDict[record.Name] = record
self._referenceDict[record.FullName] = record
self._referenceDict[record.MD5] = record
self._readLocatorById = {}
if self.isSorted:
for refId in self.file["/RefGroup/ID"]:
self._readLocatorById[refId] = makeReadLocator(self, refId)
if "NumPasses" in self.file["/AlnInfo"]:
self.numPasses = self.file["/AlnInfo/NumPasses"].value
if "Barcode" in self.file["/AlnInfo"]:
# Build forward and backwards id<->label lookup tables
self._barcodeName = OrderedDict(zip(self.file["/BarcodeInfo/ID"],
self.file["/BarcodeInfo/Name"]))
self._barcode = OrderedDict(zip(self.file["/BarcodeInfo/Name"],
self.file["/BarcodeInfo/ID"]))
# Barcode ID per row
self._barcodes = self.file["/AlnInfo/Barcode"].value[:,1]
if "ZScore" in self.file["/AlnInfo"]:
self.zScore = self.file["/AlnInfo/ZScore"].value
self.basH5Collection = None
