def decompose_plant_data_frame_into_areas(df, areas, grid):
"""Take a plant-column data frame and decompose it into plant-column data frames
for areas.
:param pandas.DataFrame df: data frame, columns are plant id in grid.
:param dict areas: areas to use for decomposition. Keys are area types
('*loadzone*', '*state*', or '*interconnect*'), values are
str/list/tuple/set of areas.
:param powersimdata.input.grid.Grid grid: Grid instance.
:return: (*dict*) -- keys are areas, values are plant-column data frames.
"""
_check_data_frame(df, "PG")
plant_id = set(df.columns)
_check_plants_are_in_grid(plant_id, grid)
areas = _check_areas_are_in_grid_and_format(areas, grid)
df_areas = {}
for k, v in areas.items():
if k == "interconnect":
for i in v:
name = "%s interconnect" % " - ".join(i.split("_"))
df_areas[name] = df[get_plant_id_in_interconnects(i, grid)
& plant_id]
elif k == "state":
for s in v:
df_areas[s] = df[get_plant_id_in_states(s, grid) & plant_id]
elif k == "loadzone":
for l in v:
df_areas[l] = df[get_plant_id_in_loadzones(l, grid) & plant_id]
return df_areas
def test_check_plants_are_in_grid_argument_type(mock_grid):
arg = (
(str(mock_grid.plant.index[1]), mock_grid),
(mock_grid.plant.index[:3], mock_grid),
(mock_grid.plant.index[0], mock_grid.plant),
)
for a in arg:
with pytest.raises(TypeError):
_check_plants_are_in_grid(a[0], a[1])
def summarize_plant_to_location(df, grid):
"""Take a plant-column data frame and sum to a location-column data frame.
:param pandas.DataFrame df: dataframe, columns are plant id in grid.
:param powersimdata.input.grid.Grid grid: Grid instance.
:return: (*pandas.DataFrame*) -- index: df index, columns: location tuples.
"""
_check_data_frame(df, "PG")
_check_grid_type(grid)
_check_plants_are_in_grid(df.columns.to_list(), grid)
all_locations = grid.plant[["lat", "lon"]]
locations_in_df = all_locations.loc[df.columns].to_records(index=False)
location_data = df.groupby(locations_in_df, axis=1).sum()
return location_data
def decompose_plant_data_frame_into_resources(df, resources, grid):
"""Take a plant-column data frame and decompose it into plant-column data frames
for each resource.
:param pandas.DataFrame df: data frame, columns are plant id in grid.
:param str/list/tuple/set resources: resource(s) to use for decomposition.
:param powersimdata.input.grid.Grid grid: Grid instance.
:return: (*dict*) -- keys are resources, values are plant-column data frames.
"""
_check_data_frame(df, "PG")
plant_id = set(df.columns)
_check_plants_are_in_grid(plant_id, grid)
resources = _check_resources_are_in_grid_and_format(resources, grid)
df_resources = {
r: df[get_plant_id_for_resources(r, grid) & plant_id].sort_index(axis=1)
for r in resources
}
return df_resources
def summarize_plant_to_bus(df, grid, all_buses=False):
"""Take a plant-column data frame and sum to a bus-column data frame.
:param pandas.DataFrame df: dataframe, columns are plant id in grid.
:param powersimdata.input.grid.Grid grid: Grid instance.
:param boolean all_buses: return all buses in grid, not just plant buses.
:return: (*pandas.DataFrame*) -- index as df input, columns are buses.
"""
_check_data_frame(df, "PG")
_check_grid_type(grid)
_check_plants_are_in_grid(df.columns.to_list(), grid)
all_buses_in_grid = grid.plant["bus_id"]
buses_in_df = all_buses_in_grid.loc[df.columns]
bus_data = df.T.groupby(buses_in_df).sum().T
if all_buses:
bus_data = pd.DataFrame(bus_data,
columns=grid.bus.index,
index=df.index).fillna(0.0)
return bus_data
def test_check_plants_are_in_grid(mock_grid):
_check_plants_are_in_grid([p for p in mock_grid.plant.index[:5]], mock_grid)
_check_plants_are_in_grid([str(p) for p in mock_grid.plant.index[:5]], mock_grid)
_check_plants_are_in_grid(set([p for p in mock_grid.plant.index[:5]]), mock_grid)
_check_plants_are_in_grid(tuple([p for p in mock_grid.plant.index[:5]]), mock_grid)
def test_check_plants_are_in_grid_argument_value(mock_grid):
with pytest.raises(ValueError):
_check_plants_are_in_grid(
[p + 100 for p in mock_grid.plant.index[-5:]], mock_grid
)