def __init__(self, start_date, end_date, interval, input_dir):
"""Constructor."""
# extract time limits from 'demand.csv'
with open(os.path.join(input_dir, "demand.csv")) as profile:
min_ts, max_ts, freq = extract_date_limits(profile)
dates = pd.date_range(start=min_ts, end=max_ts, freq=freq)
start_ts = validate_time_format(start_date)
end_ts = validate_time_format(end_date, end_date=True)
# make sure the dates are within the time frame we have data for
validate_time_range(start_ts, min_ts, max_ts)
validate_time_range(end_ts, min_ts, max_ts)
if start_ts > end_ts:
raise InvalidDateArgument(
f"The start date ({start_ts}) cannot be after the end date ({end_ts})."
)
# Julia starts at 1
start_index = dates.get_loc(start_ts) + 1
end_index = dates.get_loc(end_ts) + 1
# Calculate number of intervals
ts_range = end_index - start_index + 1
if ts_range % interval > 0:
raise InvalidInterval(
"This interval does not evenly divide the given date range.")
self.start_index = start_index
self.interval = interval
self.n_interval = int(ts_range / interval)
self.input_dir = input_dir
print("Validation complete!")
def _update_outputs_labels(outputs, start_date, end_date, freq, matfile):
"""Updates outputs with the correct date index and column names
:param dict outputs: dictionary of pandas.DataFrames outputted by extract_data
:param str start_date: start date used for the simulation
:param str end_date: end date used for the simulation
:param str freq: the frequency of timestamps in the input profiles as a pandas frequency alias
:param dict matfile: dictionary representing the converted input.mat file outputted by REISE.jl
"""
# Set index of data frame
start_ts = validate_time_format(start_date)
end_ts = validate_time_format(end_date, end_date=True)
date_range = pd.date_range(start_ts, end_ts, freq=freq)
outputs_id = _get_outputs_from_converted(matfile)
for k in outputs:
outputs[k].index = date_range
outputs[k].index.name = "UTC"
outputs[k].columns = outputs_id[k]
def test_validate_time_format_end_date():
date = "2016-01-01"
assert validate_time_format(
date, end_date=True) == pd.Timestamp("2016-01-01 23:00:00")
def test_validate_time_format_sec():
date = "2016-01-01 12:30:30"
assert validate_time_format(date) == pd.Timestamp("2016-01-01 12:30:30")
def test_validate_time_format_hours():
date = "2016-01-01 12"
assert validate_time_format(date) == pd.Timestamp("2016-01-01 12:00:00")
def test_validate_time_format_day():
date = "2016-01-01"
assert validate_time_format(date) == pd.Timestamp("2016-01-01 00:00:00")
def test_validate_time_format_type():
date = "2016/01/01"
with pytest.raises(InvalidDateArgument):
validate_time_format(date)