Python read_data_agent_result Exemples

Exemple #1

Fichier : data2.py Projet : congxueyang/disk_perf_test_tool

def main(argv):
    data = read_data_agent_result(sys.argv[1])
    grouped = groupby_globally(data, key)

    print template.format(**headers)

    for (bs, cache_tp, act, conc), curr_data in sorted(grouped.items()):
        iops = med_dev([i['iops'] * int(conc) for i in curr_data])
        bw = med_dev([i['bw'] * int(conc) for i in curr_data])
        lat = med_dev([i['lat'] / 1000 for i in curr_data])

        iops = round_deviation(iops)
        bw = round_deviation(bw)
        lat = round_deviation(lat)

        params = dict(
            bs=bs,
            action=act,
            cache_tp=cache_tp,
            iops=iops,
            bw=bw,
            lat=lat,
            conc=conc
        )

        print template.format(**params)

Exemple #2

Fichier : data2.py Projet : vrovachev/disk_perf_test_tool

def main(argv):
    data = read_data_agent_result(sys.argv[1])
    grouped = groupby_globally(data, key)

    print template.format(**headers)

    for (bs, cache_tp, act, conc), curr_data in sorted(grouped.items()):
        iops = med_dev([i['iops'] * int(conc) for i in curr_data])
        bw = med_dev([i['bw'] * int(conc) for i in curr_data])
        lat = med_dev([i['lat'] / 1000 for i in curr_data])

        iops = round_deviation(iops)
        bw = round_deviation(bw)
        lat = round_deviation(lat)

        params = dict(bs=bs,
                      action=act,
                      cache_tp=cache_tp,
                      iops=iops,
                      bw=bw,
                      lat=lat,
                      conc=conc)

        print template.format(**params)

Exemple #3

Fichier : disk_io_pp.py Projet : congxueyang/disk_perf_test_tool

import sys
import collections

import scipy.stats as stats
import matplotlib.mlab as mlab
import matplotlib.pyplot as plt

from data_stat import med_dev, round_deviation
from data_stat import read_data_agent_result

data = read_data_agent_result(sys.argv[1])

# for run in data:
#     for name, numbers in run['res'].items():
#         # med, dev = round_deviation(med_dev(numbers['iops']))
#         # print name, med, '~', dev
#         distr = collections.defaultdict(lambda: 0.0)
#         for i in numbers['iops']:
#             distr[i] += 1

#         print name
#         for key, val in sorted(distr.items()):
#             print "    ", key, val
#         print



# # example data
# mu = 100 # mean of distribution
# sigma = 15 # standard deviation of distribution
# x = mu + sigma * np.random.randn(10000)

Exemple #4

import sys
import collections

import scipy.stats as stats
import matplotlib.mlab as mlab
import matplotlib.pyplot as plt

from data_stat import med_dev, round_deviation
from data_stat import read_data_agent_result

data = read_data_agent_result(sys.argv[1])

# for run in data:
#     for name, numbers in run['res'].items():
#         # med, dev = round_deviation(med_dev(numbers['iops']))
#         # print name, med, '~', dev
#         distr = collections.defaultdict(lambda: 0.0)
#         for i in numbers['iops']:
#             distr[i] += 1

#         print name
#         for key, val in sorted(distr.items()):
#             print "    ", key, val
#         print

# # example data
# mu = 100 # mean of distribution
# sigma = 15 # standard deviation of distribution
# x = mu + sigma * np.random.randn(10000)

x = data[0]['res'][sys.argv[2]]['iops']