snpmatch.py 文件源码

def pairwiseScore(inFile_1, inFile_2, logDebug, outFile):
    (snpCHR1, snpPOS1, snpGT1, snpWEI1, DPmean1) = parseInput(inFile = inFile_1, logDebug = logDebug)
    (snpCHR2, snpPOS2, snpGT2, snpWEI2, DPmean2) = parseInput(inFile = inFile_2, logDebug = logDebug)
    snpmatch_stats = {}
    unique_1, unique_2, common, scores = 0, 0, 0, 0
    chrs = np.union1d(snpCHR1, snpCHR2)
    for i in chrs:
        perchrTarPosInd1 = np.where(snpCHR1 == i)[0]
        perchrTarPosInd2 = np.where(snpCHR2 == i)[0]
        log.info("Analysing chromosome %s positions", i)
        perchrtarSNPpos1 = snpPOS1[perchrTarPosInd1]
        perchrtarSNPpos2 = snpPOS2[perchrTarPosInd2]
        matchedAccInd1 = np.where(np.in1d(perchrtarSNPpos1, perchrtarSNPpos2))[0]
        matchedAccInd2 = np.where(np.in1d(perchrtarSNPpos2, perchrtarSNPpos1))[0]
        unique_1 = unique_1 + len(perchrTarPosInd1) - len(matchedAccInd1)
        unique_2 = unique_2 + len(perchrTarPosInd2) - len(matchedAccInd2)
        common = common + len(matchedAccInd1)
        scores = scores + np.sum(np.array(snpGT1[matchedAccInd1] == snpGT2[matchedAccInd2], dtype = int))
    snpmatch_stats['unique'] = {"%s" % os.path.basename(inFile_1): [float(unique_1)/len(snpCHR1), len(snpCHR1)], "%s" % os.path.basename(inFile_2): [float(unique_2)/len(snpCHR2), len(snpCHR2)]}
    snpmatch_stats['matches'] = [float(scores)/common, common]
    if not outFile:
        outFile = "genotyper"
    log.info("writing output in a file: %s" % outFile + ".matches.json")
    with open(outFile + ".matches.json", "w") as out_stats:
        out_stats.write(json.dumps(snpmatch_stats))
    log.info("finished!")