def reporting_model_hourly(il_electricity_cdd_hdd_hourly):
meter_data = il_electricity_cdd_hdd_hourly["meter_data"]
temperature_data = il_electricity_cdd_hdd_hourly["temperature_data"]
blackout_end_date = il_electricity_cdd_hdd_hourly["blackout_end_date"]
reporting_meter_data, warnings = get_reporting_data(
meter_data, start=blackout_end_date)
preliminary_hourly_design_matrix = create_caltrack_hourly_preliminary_design_matrix(
reporting_meter_data, temperature_data)
segmentation = segment_time_series(preliminary_hourly_design_matrix.index,
"three_month_weighted")
occupancy_lookup = estimate_hour_of_week_occupancy(
preliminary_hourly_design_matrix, segmentation=segmentation)
occupied_temperature_bins, unoccupied_temperature_bins = fit_temperature_bins(
preliminary_hourly_design_matrix,
segmentation=segmentation,
occupancy_lookup=occupancy_lookup,
)
design_matrices = create_caltrack_hourly_segmented_design_matrices(
preliminary_hourly_design_matrix,
segmentation,
occupancy_lookup,
occupied_temperature_bins,
unoccupied_temperature_bins,
)
segmented_model = fit_caltrack_hourly_model(
design_matrices,
occupancy_lookup,
occupied_temperature_bins,
unoccupied_temperature_bins,
)
return segmented_model
def test_segment_time_series_drop_zero_weight_segments(index_8760):
weights = segment_time_series(index_8760[:100],
segment_type="one_month",
drop_zero_weight_segments=True)
assert list(weights.columns) == ["jan"]
assert weights.shape == (100, 1)
assert weights.sum().sum() == 100.0
def test_segment_time_series_three_month(index_8760):
weights = segment_time_series(index_8760, segment_type="three_month")
assert list(weights.columns) == [
"dec-jan-feb",
"jan-feb-mar",
"feb-mar-apr",
"mar-apr-may",
"apr-may-jun",
"may-jun-jul",
"jun-jul-aug",
"jul-aug-sep",
"aug-sep-oct",
"sep-oct-nov",
"oct-nov-dec",
"nov-dec-jan",
]
assert weights.shape == (8760, 12)
assert weights.sum().sum() == 26280.0
def test_segment_time_series_one_month(index_8760):
weights = segment_time_series(index_8760, segment_type="one_month")
assert list(weights.columns) == [
"jan",
"feb",
"mar",
"apr",
"may",
"jun",
"jul",
"aug",
"sep",
"oct",
"nov",
"dec",
]
assert weights.shape == (8760, 12)
assert weights.sum().sum() == 8760.0
def test_segment_time_series_three_month_weighted(index_8760):
weights = segment_time_series(index_8760, segment_type="three_month_weighted")
assert list(weights.columns) == [
"dec-jan-feb-weighted",
"jan-feb-mar-weighted",
"feb-mar-apr-weighted",
"mar-apr-may-weighted",
"apr-may-jun-weighted",
"may-jun-jul-weighted",
"jun-jul-aug-weighted",
"jul-aug-sep-weighted",
"aug-sep-oct-weighted",
"sep-oct-nov-weighted",
"oct-nov-dec-weighted",
"nov-dec-jan-weighted",
]
assert weights.shape == (8760, 12)
assert weights.sum().sum() == 17520.0
def segmentation(preliminary_hourly_design_matrix):
return segment_time_series(preliminary_hourly_design_matrix.index,
"three_month_weighted")
def one_month_segmentation(occupancy_precursor):
return segment_time_series(occupancy_precursor.index,
segment_type="one_month")
def segmentation_only_nan(occupancy_precursor_only_nan):
return segment_time_series(occupancy_precursor_only_nan.index,
segment_type="three_month_weighted")
def test_segment_time_series_single(index_8760):
weights = segment_time_series(index_8760, segment_type="single")
assert list(weights.columns) == ["all"]
assert weights.shape == (8760, 1)
assert weights.sum().sum() == 8760.0
def test_segment_time_series_invalid_type(index_8760):
with pytest.raises(ValueError):
segment_time_series(index_8760, segment_type="unknown")
def segmentation(dataset):
return segment_time_series(dataset.index, segment_type="one_month")
