def process_interval_jobs(dataset, tag, job, conn):
data = bUtil.process_common_data(dataset, tag, 'interval', job)
sharpness = deepcopy(data)
sharpness.extend(["sharpness", job["sharpness"]])
bUtil.insert_benchmark(sharpness, conn)
resolution = deepcopy(data)
resolution.extend(["resolution", job["resolution"]])
bUtil.insert_benchmark(resolution, conn)
coverage = deepcopy(data)
coverage.extend(["coverage", job["coverage"]])
bUtil.insert_benchmark(coverage, conn)
time = deepcopy(data)
time.extend(["time", job["time"]])
bUtil.insert_benchmark(time, conn)
Q05 = deepcopy(data)
Q05.extend(["Q05", job["Q05"]])
bUtil.insert_benchmark(Q05, conn)
Q25 = deepcopy(data)
Q25.extend(["Q25", job["Q25"]])
bUtil.insert_benchmark(Q25, conn)
Q75 = deepcopy(data)
Q75.extend(["Q75", job["Q75"]])
bUtil.insert_benchmark(Q75, conn)
Q95 = deepcopy(data)
Q95.extend(["Q95", job["Q95"]])
bUtil.insert_benchmark(Q95, conn)
W05 = deepcopy(data)
W05.extend(["winkler05", job["winkler05"]])
bUtil.insert_benchmark(W05, conn)
W25 = deepcopy(data)
W25.extend(["winkler25", job["winkler25"]])
bUtil.insert_benchmark(W25, conn)
def process_point_jobs(dataset, tag, job, conn):
"""
Extract information from a dictionary with point benchmark results and save it on a database
:param dataset: the benchmark dataset name
:param tag: alias for the benchmark group being executed
:param job: a dictionary with the benchmark results
:param conn: a connection to a Sqlite database
:return:
"""
data = bUtil.process_common_data(dataset, tag, 'point',job)
rmse = deepcopy(data)
rmse.extend(["rmse", job["rmse"]])
bUtil.insert_benchmark(rmse, conn)
smape = deepcopy(data)
smape.extend(["smape", job["smape"]])
bUtil.insert_benchmark(smape, conn)
u = deepcopy(data)
u.extend(["u", job["u"]])
bUtil.insert_benchmark(u, conn)
time = deepcopy(data)
time.extend(["time", job["time"]])
bUtil.insert_benchmark(time, conn)
def process_probabilistic_jobs(dataset, tag, job, conn):
data = bUtil.process_common_data(dataset, tag, 'density', job)
crps = deepcopy(data)
crps.extend(["crps", job["CRPS"]])
bUtil.insert_benchmark(crps, conn)
time = deepcopy(data)
time.extend(["time", job["time"]])
bUtil.insert_benchmark(time, conn)
brier = deepcopy(data)
brier.extend(["brier", job["brier"]])
bUtil.insert_benchmark(brier, conn)
def process_point_jobs(dataset, tag, job, conn):
data = bUtil.process_common_data(dataset, tag, 'point', job)
rmse = deepcopy(data)
rmse.extend(["rmse", job["rmse"]])
bUtil.insert_benchmark(rmse, conn)
smape = deepcopy(data)
smape.extend(["smape", job["smape"]])
bUtil.insert_benchmark(smape, conn)
u = deepcopy(data)
u.extend(["u", job["u"]])
bUtil.insert_benchmark(u, conn)
time = deepcopy(data)
time.extend(["time", job["time"]])
bUtil.insert_benchmark(time, conn)
def process_interval_jobs(dataset, tag, job, conn):
"""
Extract information from an dictionary with interval benchmark results and save it on a database
:param dataset: the benchmark dataset name
:param tag: alias for the benchmark group being executed
:param job: a dictionary with the benchmark results
:param conn: a connection to a Sqlite database
:return:
"""
data = bUtil.process_common_data(dataset, tag, 'interval', job)
sharpness = deepcopy(data)
sharpness.extend(["sharpness", job["sharpness"]])
bUtil.insert_benchmark(sharpness, conn)
resolution = deepcopy(data)
resolution.extend(["resolution", job["resolution"]])
bUtil.insert_benchmark(resolution, conn)
coverage = deepcopy(data)
coverage.extend(["coverage", job["coverage"]])
bUtil.insert_benchmark(coverage, conn)
time = deepcopy(data)
time.extend(["time", job["time"]])
bUtil.insert_benchmark(time, conn)
Q05 = deepcopy(data)
Q05.extend(["Q05", job["Q05"]])
bUtil.insert_benchmark(Q05, conn)
Q25 = deepcopy(data)
Q25.extend(["Q25", job["Q25"]])
bUtil.insert_benchmark(Q25, conn)
Q75 = deepcopy(data)
Q75.extend(["Q75", job["Q75"]])
bUtil.insert_benchmark(Q75, conn)
Q95 = deepcopy(data)
Q95.extend(["Q95", job["Q95"]])
bUtil.insert_benchmark(Q95, conn)
W05 = deepcopy(data)
W05.extend(["winkler05", job["winkler05"]])
bUtil.insert_benchmark(W05, conn)
W25 = deepcopy(data)
W25.extend(["winkler25", job["winkler25"]])
bUtil.insert_benchmark(W25, conn)
def process_probabilistic_jobs(dataset, tag, job, conn):
"""
Extract information from an dictionary with probabilistic benchmark results and save it on a database
:param dataset: the benchmark dataset name
:param tag: alias for the benchmark group being executed
:param job: a dictionary with the benchmark results
:param conn: a connection to a Sqlite database
:return:
"""
data = bUtil.process_common_data(dataset, tag, 'density', job)
crps = deepcopy(data)
crps.extend(["crps",job["CRPS"]])
bUtil.insert_benchmark(crps, conn)
time = deepcopy(data)
time.extend(["time", job["time"]])
bUtil.insert_benchmark(time, conn)
brier = deepcopy(data)
brier.extend(["brier", job["brier"]])
bUtil.insert_benchmark(brier, conn)