def executor_derived(file_path_list: List[Path], output_path: Path, **kwargs) -> Dict:
debug = kwargs.pop('debug', False),
logger.remove()
ts = file_path_list[0].name.rstrip('.a.csv')
logger.add(
sys.stdout, level='DEBUG',
format=f"<yellow>{ts}</yellow> - {LOGURU_FORMAT}",
backtrace=True
)
logger.info(f"running squeeze for {ts}")
dfa = pd.read_csv(file_path_list[0].resolve(), engine='python', dtype='str', delimiter=r"\s*,\s*")
dfa['real'] = dfa['real'].astype(float)
dfa['predict'] = dfa['predict'].astype(float)
dfb = pd.read_csv(file_path_list[1].resolve(), engine='python', dtype='str', delimiter=r"\s*,\s*")
dfb['real'] = dfb['real'].astype(float)
dfb['predict'] = dfb['predict'].astype(float)
zero_index = (dfa.real == 0) & (dfa.predict == 0) & (dfb.real == 0) & (dfb.predict == 0)
dfa = dfa[~zero_index]
dfb = dfb[~zero_index]
try:
timestamp = int(ts)
except ValueError:
timestamp = ts
logger.warning(f"Unresolved timestamp: {timestamp}")
tic = time.time()
divide = lambda x, y: np.divide(x, y, out=np.zeros_like(x), where=y != 0)
model = Squeeze(
data_list=[dfa, dfb],
op=divide,
option=SqueezeOption(
debug=debug,
fig_save_path=f"{output_path.resolve()}/{timestamp}" + "{suffix}" + ".pdf",
enable_filter=True,
**kwargs,
)
)
model.run()
logger.info("\n" + model.report)
try:
root_cause = AC.batch_to_string(
frozenset(reduce(lambda x, y: x.union(y), model.root_cause, set()))) # type:
except IndexError:
root_cause = ""
toc = time.time()
elapsed_time = toc - tic
return {
'timestamp': timestamp,
'elapsed_time': elapsed_time,
'root_cause': root_cause,
}
def executor(file_path: Path, output_path: Path, **kwargs) -> Dict:
debug = kwargs.pop('debug', False),
logger.remove()
logger.add(
sys.stdout, level='DEBUG',
format=f"<yellow>{file_path.name}</yellow> - {LOGURU_FORMAT}",
backtrace=True
)
logger.info(f"running squeeze for {file_path}")
df = pd.read_csv(file_path.resolve(), engine='python', dtype='str', delimiter=r"\s*,\s*")
df['real'] = df['real'].astype(float)
df['predict'] = df['predict'].astype(float)
try:
timestamp = int(file_path.name.rstrip('.csv'))
except ValueError:
timestamp = file_path.name.rstrip('.csv')
logger.warning(f"Unresolved timestamp: {timestamp}")
tic = time.time()
model = Squeeze(
data_list=[df],
op=lambda x: x,
option=SqueezeOption(
debug=debug,
fig_save_path=f"{output_path.resolve()}/{timestamp}" + "{suffix}" + ".pdf",
**kwargs,
)
)
model.run()
logger.info("\n" + model.report)
try:
root_cause = AC.batch_to_string(
frozenset(reduce(lambda x, y: x.union(y), model.root_cause, set()))) # type:
except IndexError:
root_cause = ""
toc = time.time()
elapsed_time = toc - tic
return {
'timestamp': timestamp,
'elapsed_time': elapsed_time,
'root_cause': root_cause,
}