def __init__(self, project_name, model):
self.project_name = project_name
self.model = model
self.data = DataRepository.provide_project_data(project_name)
self.format_strategies = {
'ttf': TTFFormatStrategy,
'fpd': FPDFormatStrategy
}
self.format_strategy = self.choose_format_strategy(
self.data.get_format())
def fit(self, project_name, **kwargs):
fitted_stages = []
for i in range(len(self.stages)):
stage = self.stages[i]
fit_strategy = self.get_model_strategy(stage.get_model())(project_name)
data = DataRepository.provide_project_data(project_name)
stage_number = i + 1
stage_fitter = StageFitter()
fitted_stage = stage_fitter.fit(stage, fit_strategy, data, stage_number, **kwargs)
fitted_stages.append(fitted_stage)
return MultistageFit(project_name, fitted_stages)
from src.data.data_repository import DataRepository
from src.domain.models.delayed_s_shaped.delayed_s_shaped_estimator import DelayedSShapedEstimator
from src.domain.models.logistic.logistic_estimator import LogisticEstimator
from src.domain.fitters.model_fitter import ModelFitter
fpd_fitter = ModelFitter()
data = DataRepository.provide_project_data('mixed-waterfall-agile')
x_axis_data = data.get_formated_times()
cumulative_failures = data.get_cumulative_failures()
ds = DelayedSShapedEstimator()
log = LogisticEstimator()
'''
ds_fit = fpd_fitter.fit('delayed-s-shaped', 'mixed-waterfall-agile')
log_fit = fpd_fitter.fit('logistic', 'mixed-waterfall-agile')
ds_lsq_a = ds_fit.get_lsq_parameters()[0]
ds_lsq_b = ds_fit.get_lsq_parameters()[1]
log_lsq_a = log_fit.get_lsq_parameters()[0]
log_lsq_b = log_fit.get_lsq_parameters()[1]
log_lsq_c = log_fit.get_lsq_parameters()[2]
fig, axes = plt.subplots()
axes.set_xlabel('Tiempo (días)')
axes.set_ylabel('Numero esperado de fallas')
axes.set_xlim(left=0, auto=True)
axes.set_ylim(auto=True)
axes.patch.set_facecolor("#ffffff")
def obtain_full_data(self, project_name):
data = DataRepository.provide_project_data(project_name)
return data.get_project_title(), [0] + data.get_times(), [0] + data.get_cumulative_failures()
ds_fit = ttf_fitter.fit('delayed-s-shaped',
'agile-n4',
initial_approx=(100, 0.001),
lsq_only=True,
mt_formula='regular')
log_fit = ttf_fitter.fit('logistic',
'agile-n4',
initial_approx=(30, 0.03, 300),
lsq_only=True,
mt_formula='regular')
bc_fit = ttf_fitter.fit('barraza-contagion',
'agile-n4',
lsq_only=True,
mt_formula='conditional')
data = DataRepository.provide_project_data('agile-n4')
real_tbf = data.get_time_between_failures()
x_axis_data = np.linspace(1, len(real_tbf), len(real_tbf))
ds_mtbf = ds_fit.get_all_mtbf()
log_mtbf = log_fit.get_all_mtbf()
bc_mtbf = bc_fit.get_all_mtbf()
fig, axes = plt.subplots(figsize=(6, 4))
axes.set_xlabel('Failure number', fontsize=12)
axes.xaxis.set_tick_params(labelsize=10)
axes.xaxis.labelpad = 4
axes.set_ylabel('Mean time between failures', fontsize=12)
axes.yaxis.set_tick_params(labelsize=10)
axes.yaxis.labelpad = 8
axes.set_xlim(left=0, auto=True)
def setUpClass(cls):
cls.ntds_data = DataRepository.provide_project_data('ntds')
cls.ttf_formater = TTFDataFormater.get_instance()
import numpy as np
from matplotlib import pyplot as plt
from src.data.data_repository import DataRepository
from src.domain.models.barraza_contagion.barraza_contagion_estimator import BarrazaContagionEstimator
from src.domain.models.delayed_s_shaped.delayed_s_shaped_estimator import DelayedSShapedEstimator
from src.domain.models.goel_okumoto.goel_okumoto_estimator import GoelOkumotoEstimator
from src.domain.models.logistic.logistic_estimator import LogisticEstimator
go = GoelOkumotoEstimator()
ds = DelayedSShapedEstimator()
log = LogisticEstimator()
bc = BarrazaContagionEstimator()
ntds = DataRepository.provide_project_data('ntds')
ntds_data = ntds.get_data()
ntds_cumfailures = ntds.get_cumulative_failures()
n = ntds_cumfailures[-1]
tbf = ntds.get_time_between_failures()
a_go = 33.5994
b_go = 0.0063
a_ds = 26.7155
b_ds = 0.0212
a_log = 24.6114
b_log = 0.0413
c_log = 76.4858
a_bc = 0.3799
import numpy as np
from src.data.data_repository import DataRepository
from src.domain.fitters.model_fitter import ModelFitter
from src.domain.models.barraza_contagion.barraza_contagion_estimator import BarrazaContagionEstimator
import matplotlib
from matplotlib import pyplot as plt
matplotlib.rcParams['pdf.fonttype'] = 42
matplotlib.rcParams['ps.fonttype'] = 42
bc = BarrazaContagionEstimator()
agile1 = DataRepository.provide_project_data('agile-n1')
agile1_times = agile1.get_times()
agile1_cf = agile1.get_cumulative_failures()
ttf_fitter = ModelFitter()
agile1_fit = ttf_fitter.fit('barraza-contagion', 'agile-n1')
a_bc, b_bc = agile1_fit.get_lsq_parameters()
mean_values_bc = bc.calculate_mean_failure_numbers(agile1_times, a_bc, b_bc)
coef_r2 = np.var(mean_values_bc)/np.var(agile1_cf)
print("rho: ", a_bc)
print("gamma: ", b_bc * a_bc)
print("gamma/rho: ", b_bc)
print("r2: ", coef_r2)
plt.style.use('bmh')
from src.data.data_repository import DataRepository
from src.domain.models.barraza_contagion.barraza_contagion_estimator import BarrazaContagionEstimator
from src.domain.models.delayed_s_shaped.delayed_s_shaped_estimator import DelayedSShapedEstimator
from src.domain.models.logistic.logistic_estimator import LogisticEstimator
from matplotlib import pyplot as plt
ds = DelayedSShapedEstimator()
log = LogisticEstimator()
bc = BarrazaContagionEstimator()
agile2 = DataRepository.provide_project_data('agile-n2')
agile2_times = agile2.get_times()
a_ds = 370.3103
b_ds = 0.0025
a_log = 309.2426
b_log = 0.0047
c_log = 580.9822
a_bc = 0.2221
b_bc = 1.0479
mean_values_ds = ds.calculate_mean_failure_numbers(agile2_times, a_ds, b_ds)
mean_values_log = log.calculate_mean_failure_numbers(agile2_times, a_log, b_log, c_log)
mean_values_bc = bc.calculate_mean_failure_numbers(agile2_times, a_bc, b_bc)
fig, axes = plt.subplots()
axes.set_xlabel('Time (days)')
axes.set_ylabel('Number of failures')
def print_project_name(self, project_name):
self.reset_console_colors()
project_data = DataRepository.provide_project_data(project_name)
project_title = project_data.get_project_title()
print((Fore.YELLOW + 'Project: ') +
(Fore.LIGHTRED_EX + project_title) + "\n")
def setUpClass(cls):
cls.mixed_data = DataRepository.provide_project_data(
'mixed-waterfall-agile')
cls.fpd_formater = FPDDataFormater.get_instance()