def main():

    parseXML()

    heading("Collecting phase data")
    f = open("phase.csv", "w")

    lastSampleCnt = parseInt(
        readReg(
            getNode('GEM_AMC.TTC.STATUS.CLK.PHASE_MONITOR.SAMPLE_COUNTER')))
    phaseArr = []
    for i in range(NUM_READS):
        phaseRaw = parseInt(
            readReg(getNode('GEM_AMC.TTC.STATUS.CLK.PHASE_MONITOR.PHASE')))
        phasePs = phaseRaw * PHASE_UNITS_PS
        phaseArr.append(phasePs)
        f.write("%f\n" % phasePs)
        sampleCnt = lastSampleCnt
        while sampleCnt == lastSampleCnt:
            sampleCnt = parseInt(
                readReg(
                    getNode(
                        'GEM_AMC.TTC.STATUS.CLK.PHASE_MONITOR.SAMPLE_COUNTER'))
            )
            sleep(0.0001)
        lastSampleCnt = sampleCnt
        if i % 1000 == 0:
            print("Progress: %d / %d" % (i, NUM_READS))

    histogram(phaseArr)

    f.close()
def analyzeBxDiff(events):
    ohAmcBxOffsets = []
    vfatOhBxOffsets = []
    vfatAmcBxOffsets = []

    for event in events:
        for chamber in event.chambers:
            ohAmcBxOffsets.append(chamber.ohBc - event.bxId)
            for vfat in chamber.vfats:
                vfatOhBxOffsets.append(vfat.bc - chamber.ohBc)
                vfatAmcBxOffsets.append(vfat.bc - event.bxId)

    # print "===================================================="
    # print "OH BC - AMC BC histogram:"
    # print ""
    # histogram(ohAmcBxOffsets, -3564, 3564, 100)
    #
    # print ""
    # print "===================================================="
    # print "VFAT BC - OH BC histogram:"
    # print ""
    # histogram(vfatOhBxOffsets, -3564, 3564, 100)

    print ""
    print "===================================================="
    print "VFAT BC - AMC BC histogram:"
    print ""
    # histogram(vfatAmcBxOffsets, -3564, 3564, 100)
    histogram(vfatAmcBxOffsets, -3564, 3564, 7130)
def analyzeNumChambers(events):
    numChambers = []

    for event in events:
        numChambers.append(len(event.chambers))

    print "===================================================="
    print "Number of chambers per event histogram:"
    print ""
    histogram(numChambers, 0, 8, 8)
示例#4
0
def analyzeNumChambers(events):
    numChambers = []

    for event in events:
        numChambers.append(len(event.chambers))

    print "===================================================="
    print "Number of chambers per event histogram:"
    print ""
    histogram(numChambers, 0, 8, 8)
def analyzeNumVfats(events):
    numVfats = []
    for event in events:
        vfats = 0
        for chamber in event.chambers:
            vfats += len(chamber.vfats)
            numVfats.append(vfats)

    print "===================================================="
    print "Number of VFATs per event histogram:"
    print ""
    histogram(numVfats)
示例#6
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def train(model_path=None,
          save_path='/home/cjl/tf_runet/models/20180612',
          pro_path='/home/cjl/tf_runet',
          max_size=None,
          total_step=0,
          display=False,
          displaystep=30,
          save=True,
          dataidx=10):
    print('begin_train')
    data_path = pro_path + '/data/vot2016'
    data_provider = VOT2016_Data_Provider(data_path, cfg)
    data_provider.random_batch_init()
    data_provider.dataidx = dataidx

    model = Model()
    train_writer = tf.summary.FileWriter(save_path, model.sess.graph)
    if model_path is None:
        model.init_vars_random()
    else:
        model.restore(model_path)

    import psutil
    training = True
    while training:
        total_step += 1
        print('--------------------------------------')
        print('total_step:', total_step)
        iptdata, gtdata = data_provider.get_a_random_batch(jump=2)
        weight = ave_weight(gtdata)
        summary, cost, otherlabels, predict = model.train(
            iptdata, gtdata, weight)
        #text_histogram.histogram(list(iptdata.astype(float).reshape((-1))))
        #text_histogram.histogram(list(gtdata.astype(float).reshape((-1))))
        auc = calc_auc(predict, otherlabels)
        print("cost:", cost, " auc:", auc)
        print_step_auc(predict, otherlabels)
        text_histogram.histogram(list(predict.astype(float).reshape((-1))))

        train_writer.add_summary(summary, total_step)
        if (save and total_step % 20 == 0):
            filename = save_path + '/train' + str(total_step)
            model.save(filename)
    print('========================================')
示例#7
0
def analyzeBx(events):
    ohAmcBxOffsets = []
    vfatOhBxOffsets = []
    vfatAmcBxOffsets = []

    for event in events:
        for chamber in event.chambers:
            ohAmcBxOffsets.append(chamber.ohBc - event.bxId)
            for vfat in chamber.vfats:
                vfatOhBxOffsets.append(vfat.bc - chamber.ohBc)
                vfatAmcBxOffsets.append(vfat.bc - event.bxId)

    print "===================================================="
    print "OH BC - AMC BC histogram:"
    print ""
    histogram(ohAmcBxOffsets, -3564, 3564, 100)

    print ""
    print "===================================================="
    print "VFAT BC - OH BC histogram:"
    print ""
    histogram(vfatOhBxOffsets, -3564, 3564, 100)

    print ""
    print "===================================================="
    print "VFAT BC - AMC BC histogram:"
    print ""
    histogram(vfatAmcBxOffsets, -3564, 3564, 100)
示例#8
0
def benchmark(iterations, func, *args, **kwargs):
    print(f"running {func} with args {args} {iterations} times ")
    import timeit
    timer = timeit.default_timer
    times = []
    for i in range(iterations):
        times.append(timer())
        func(*args)
        times.append(timer())

    deltas = [times[i] - times[i - 1] for i in range(1, len(times))]

    print(deltas)
    from text_histogram import histogram
    print(histogram(deltas))
示例#9
0
    trace_collection.add_trace(trace_path, 'ctf')
except:
    print(howto)
    raise


class ClientStats:
    def __init__(self):
        self.buffers_in_flight = dict()
        self.buffer_delays = []


clients = dict()
for event in trace_collection.events:
    if event.name == 'mir_server_wayland:sw_buffer_committed':
        if event['client'] not in clients:
            clients[event['client']] = ClientStats()
        clients[event['client']].buffers_in_flight[
            event['buffer_id']] = event.timestamp
    if event.name == 'mir_server_compositor:buffers_in_frame':
        for buffer in event['buffer_ids']:
            for client in clients.values():
                if buffer in client.buffers_in_flight.keys():
                    client.buffer_delays.append(
                        event.timestamp - client.buffers_in_flight[buffer])
                    del client.buffers_in_flight[buffer]

for (id, client) in clients.items():
    print("Client: ", id)
    histogram([delay // 1000000 for delay in client.buffer_delays])
示例#10
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for vcf_path in vcf_paths:
    print("============================")
    alt_allele_sizes = []
    with gzip.open(vcf_path) if vcf_path.endswith(".gz") else open(
            vcf_path) as f:
        for line in f:
            if line.startswith("#"):
                continue
            fields = line.strip().split("\t")
            ref = fields[3]
            alt_alleles = fields[4]
            for alt in alt_alleles.split(","):
                c['total alleles'] += 1
                if len(ref) < len(alt):
                    c['insertions'] += 1
                    alt_allele_sizes.append(len(alt))
                elif len(ref) > len(alt):
                    c['deletions'] += 1
                elif len(ref) == 1 and len(alt) == 1:
                    c['snps'] += 1

    for label, value in sorted(c.items(),
                               key=lambda x: (x[1], x[0]),
                               reverse=True):
        print("==> %15s : %9d" % (label, value))

    print("log2(alt allele length) for insertions in " + vcf_path)
    histogram(np.log2(alt_allele_sizes),
              custbuckets=",".join(["%0.1f" % (k / 2.0)
                                    for k in range(1, 20)]))
def analyzeBx(events):
    amcBxs = []
    ohBxs = []
    vfatBxs = []

    amcBxMin = 5000
    amcBxMax = -1
    numAmcBxOvf = 0

    ohBxMin = 5000
    ohBxMax = -1
    numOhBxOvf = 0

    vfatBxMin = 5000
    vfatBxMax = -1
    numVfatBxOvf = 0

    for event in events:
        amcBxs.append(event.bxId)
        if event.bxId < amcBxMin:
            amcBxMin = event.bxId
        if event.bxId > amcBxMax:
            amcBxMax = event.bxId
        if event.bxId > 3564:
            numAmcBxOvf += 1

        for chamber in event.chambers:
            ohBxs.append(chamber.ohBc)
            if chamber.ohBc < ohBxMin:
                ohBxMin = chamber.ohBc
            if chamber.ohBc > ohBxMax:
                ohBxMax = chamber.ohBc
            if chamber.ohBc > 3564:
                numOhBxOvf += 1

            for vfat in chamber.vfats:
                vfatBxs.append(vfat.bc)
                if vfat.bc < vfatBxMin:
                    vfatBxMin = vfat.bc
                if vfat.bc > vfatBxMax:
                    vfatBxMax = vfat.bc
                if vfat.bc > 3564:
                    numVfatBxOvf += 1

    print ""
    print "===================================================="
    print "AMC BC histogram:"
    print ""
    histogram(amcBxs, 0, 4095, 4096)

    print "AMC BX Min: %d, AMC BX Max: %d, AMC BX > 3564: %d" % (
        amcBxMin, amcBxMax, numAmcBxOvf)

    print ""
    print "===================================================="
    print "OH BC histogram:"
    print ""
    histogram(ohBxs, 0, 4095, 4096)

    print "OH BX Min: %d, OH BX Max: %d, OH BX > 3564: %d" % (ohBxMin, ohBxMax,
                                                              numOhBxOvf)

    print ""
    print "===================================================="
    print "VFAT BC histogram:"
    print ""
    histogram(vfatBxs, 0, 4095, 4096)

    print "VFAT BX Min: %d, VFAT BX Max: %d, VFAT BX > 3564: %d" % (
        vfatBxMin, vfatBxMax, numVfatBxOvf)
示例#12
0
#Using text_histogram https://github.com/Kobold/text_histogram
#display histogram for Hamming's errors
from ex5_3 import errors
import text_histogram as t
t.histogram(errors, 5, 9, 4)