def genRandomSeqDbIid(path, lengths):
"""Generate random reference sequences as SeqDbFasta.
Each generated sequence is generated independently"""
seqDb = SeqDbFasta(path, save=True)
# assert len(set(lengths)) == len(lengths),"Reference lengths must be unique"
seqLen = {}
for (iIcm, length) in enumerate(lengths):
idIcm = iIcm
writer = seqDb.fastaWriter(idIcm)
seq = randomSeq(length)
writer.record(str(idIcm), seq)
writer.close()
seqDb.finById(idIcm)
seqLen[idIcm] = length
seqDb.opt.seqLen = seqLen
seqDb.save()
from MGT.ImmApp import *
from MGT.SeqDbFasta import *
seqDbPath = pjoin(options.testDataDir, "seqdb-fasta")
jobs = []
opt = Struct()
opt.runMode = "inproc" # "batchDep"
opt.seqDb = seqDbPath
opt.immDb = pabs("test.immdb")
seqDb = SeqDbFasta(opt.seqDb)
ids = seqDb.getIdList()
for id in ids:
seqDb.finById(id=id)
immIdToSeqIds = dict(((id, [id]) for id in ids))
immIdToSeqIdsFile = pabs("test.immapp.seqids.pkl")
dumpObj(immIdToSeqIds, immIdToSeqIdsFile)
opt.immIdToSeqIds = immIdToSeqIdsFile
opt.mode = "train"
ImmApp.fillWithDefaultOptions(opt)
# imm = ImmApp(opt=opt)
# jobs = imm.run()
for (reduceScoresEarly, cwd) in ((1, "imm.test.red_early_1"), (0, "imm.test.red_early_0")):
immIds = ImmStore.open(path=opt.immDb, mode="r").listImmIdsWithIdScoreIdent()
immIdsFile = pabs("test.immapp.immids.pkl")
