def test_period_count_starts_at_full_hour(self):
# a start offset of 15 minutes is ignored when number of periods is calculated
start = pd.Timestamp(2018, 1, 1, 0, 15)
end = pd.Timestamp(2018, 1, 2, 0)
series = full_hour_series(start, end, "15min")
assert len(series) == 24 * 4
assert series[0] == start
assert series[-1] == end
def _group_without_missing_data(group):
source = group.iloc[0]
source_zero_mw = pd.DataFrame([source])
source_zero_mw.at[source_zero_mw.index[0], "gen_MW"] = 0
# in case first 15 minutes are missing: make sure series starts at 15 minutes past
start = source["timestamp"].replace(minute=15)
end = group.iloc[-1].timestamp
series = full_hour_series(start, end, "15min")
def filler(t):
filler = source_zero_mw.copy()
filler.at[filler.index[0], "timestamp"] = t
return filler
def df_for_timestamp(t):
df = group[group["timestamp"] == t]
return df if len(df) > 0 else filler(t)
return pd.concat([df_for_timestamp(t) for t in series], ignore_index=True)
def test_two_hour_series(self):
start = pd.Timestamp(2018, 1, 1, 0)
end = pd.Timestamp(2018, 1, 1, 2)
series = full_hour_series(start, end, "15min")
assert len(series) == 8
def test_zero_hour_series(self):
start = pd.Timestamp(2018, 1, 1, 0)
end = pd.Timestamp(2018, 1, 1, 0, 0)
series = full_hour_series(start, end, "15min", min_hours=0)
assert len(series) == 0