import datetime
import numpy as np
import pandas as pd
import pytest
from powersimdata import Grid
from powersimdata.input.check import (
_check_areas_and_format,
_check_areas_are_in_grid_and_format,
_check_data_frame,
_check_date,
_check_date_range_in_scenario,
_check_date_range_in_time_series,
_check_epsilon,
_check_gencost,
_check_grid_models_match,
_check_grid_type,
_check_number_hours_to_analyze,
_check_plants_are_in_grid,
_check_resources_and_format,
_check_resources_are_in_grid_and_format,
_check_resources_are_renewable_and_format,
_check_time_series,
check_grid,
)
from powersimdata.network.europe_tub.model import TUB
from powersimdata.tests.mock_scenario import MockScenario
[docs]@pytest.fixture
def europe():
tub = TUB("Europe", reduction=128)
tub.build()
return tub
[docs]@pytest.fixture
def mock_plant():
return {
"plant_id": range(15),
"type": [
"solar",
"nuclear",
"wind",
"wind_offshore",
"coal",
"ng",
"coal",
"coal",
"geothermal",
"wind",
"solar",
"hydro",
"coal",
"ng",
"solar",
],
"interconnect": ["Western"] * 3 + ["Texas"] * 8 + ["Eastern"] * 4,
"zone_name": [
"Washington",
"El Paso",
"Bay Area",
]
+ [
"Far West",
"North",
"West",
"South",
"North Central",
"South Central",
"Coast",
"East",
]
+ ["Kentucky", "Nebraska", "East Texas", "Texas Panhandle"],
}
[docs]@pytest.fixture
def mock_gencost():
return {
"plant_id": range(15),
"type": [2] * 15,
"startup": [0] * 15,
"shutdown": [0] * 15,
"n": [3] * 15,
"c2": [
0,
0.00021,
0,
0,
0.00125,
0.0015,
0.00085,
0.0009,
0,
0,
0,
0,
0.0013,
0.0011,
0,
],
"c1": [0, 20, 0, 0, 25, 32, 18, 29, 0, 0, 0, 0, 35, 27, 0],
"c0": [0, 888, 0, 0, 750, 633, 599, 933, 0, 0, 0, 0, 1247, 1111, 0],
"interconnect": ["Western"] * 15,
}
[docs]@pytest.fixture
def mock_scenario(mock_plant, mock_gencost):
mock_scenario = MockScenario({"plant": mock_plant, "gencost_after": mock_gencost})
mock_scenario.info["start_date"] = "2016-01-01 00:00:00"
mock_scenario.info["end_date"] = "2016-01-10 23:00:00"
return mock_scenario
[docs]@pytest.fixture
def mock_grid(mock_scenario):
return mock_scenario.get_grid()
[docs]def test_error_handling():
grid = Grid("Western")
del grid.dcline
with pytest.raises(ValueError):
check_grid(grid)
[docs]@pytest.mark.parametrize(
"interconnect", ["Eastern", "Western", "Texas", ["Western", "Texas"], "USA"]
)
def test_check_grid(interconnect):
grid = Grid(interconnect)
check_grid(grid)
[docs]def check_grid_models_match_success():
_check_grid_models_match(Grid("Western"), Grid("Texas"))
[docs]def check_grid_models_match_failure():
grid1 = Grid("Western")
grid2 = Grid("Texas")
grid2.grid_model == "foo"
with pytest.raises(ValueError):
_check_grid_models_match(grid1, grid2)
[docs]def test_check_data_frame_argument_type():
arg = (
(1, "int"),
("homer", "str"),
({"homer", "marge", "bart", "lida"}, "set"),
(pd.DataFrame({"California": [1, 2, 3], "Texas": [4, 5, 6]}), 123456),
)
for a in arg:
with pytest.raises(TypeError):
_check_data_frame(a[0], a[1])
[docs]def test_check_data_frame_argument_value():
arg = (
(pd.DataFrame({"California": [], "Texas": []}), "row"),
(pd.DataFrame({}), "col"),
)
for a in arg:
with pytest.raises(ValueError):
_check_data_frame(a[0], a[1])
[docs]def test_check_data_frame():
_check_data_frame(
pd.DataFrame({"California": [1, 2, 3], "Texas": [4, 5, 6]}), "pandas.DataFrame"
)
[docs]def test_check_time_series_argument_value():
ts = pd.DataFrame({"demand": [200, 100, 10, 75, 150]})
with pytest.raises(ValueError):
_check_time_series(ts, "demand")
[docs]def test_check_time_series():
ts = pd.DataFrame(
{"demand": [200, 100, 10, 75, 150]},
index=pd.date_range("2018-01-01", periods=5, freq="H"),
)
_check_time_series(ts, "demand")
ts = pd.Series(
[200, 100, 10, 75, 150],
index=pd.date_range("2018-01-01", periods=5, freq="H"),
)
_check_time_series(ts, "demand")
[docs]def test_check_grid_type_failure():
arg = (1, pd.DataFrame({"California": [1, 2, 3], "Texas": [4, 5, 6]}))
for a in arg:
with pytest.raises(TypeError):
_check_grid_type(a)
[docs]def test_check_grid_type_success(mock_grid):
_check_grid_type(mock_grid)
[docs]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])
[docs]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
)
[docs]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)
[docs]def test_check_number_hours_to_analyze_argument_type(mock_scenario):
arg = ((mock_scenario, "100"), (mock_scenario, [100]), (mock_scenario, {100, 50}))
for a in arg:
with pytest.raises(TypeError):
_check_number_hours_to_analyze(a[0], a[1])
[docs]def test_check_number_hours_to_analyze_argument_value(mock_scenario):
arg = ((mock_scenario, -10), (mock_scenario, 15 * 24))
for a in arg:
with pytest.raises(ValueError):
_check_number_hours_to_analyze(a[0], a[1])
[docs]def test_check_number_hours_to_analyze(mock_scenario):
_check_number_hours_to_analyze(mock_scenario, 24)
[docs]def test_check_date_argument_type():
with pytest.raises(TypeError):
_check_date("2016-02-01 00:00:00")
[docs]def test_check_date():
_check_date(datetime.datetime(2020, 9, 9))
_check_date(np.datetime64("1981-06-21"))
_check_date(pd.Timestamp(2016, 2, 1))
[docs]def test_check_date_range_in_scenario_argument_value(mock_scenario):
arg = (
(mock_scenario, pd.Timestamp(2016, 1, 5), pd.Timestamp(2016, 1, 2)),
(mock_scenario, pd.Timestamp(2015, 12, 1), pd.Timestamp(2016, 1, 8)),
(mock_scenario, pd.Timestamp(2016, 1, 2), pd.Timestamp(2016, 2, 15)),
)
for a in arg:
with pytest.raises(ValueError):
_check_date_range_in_scenario(a[0], a[1], a[2])
[docs]def test_check_date_range_in_scenario(mock_scenario):
_check_date_range_in_scenario(
mock_scenario, pd.Timestamp(2016, 1, 2), pd.Timestamp(2016, 1, 7)
)
[docs]def test_check_date_range_in_time_series_argument_value():
data = {
"A": np.random.randint(0, high=1000, size=366 * 24),
"B": np.random.randn(366 * 24),
}
ts = pd.DataFrame(
data, index=pd.date_range("2016-01-01", periods=366 * 24, freq="H")
)
arg = (
(ts, pd.Timestamp(2016, 5, 5), pd.Timestamp(2016, 3, 28)),
(ts, pd.Timestamp(2015, 12, 1), pd.Timestamp(2016, 8, 8)),
(ts, pd.Timestamp(2016, 3, 2), pd.Timestamp(2017, 2, 15)),
)
for a in arg:
with pytest.raises(ValueError):
_check_date_range_in_time_series(a[0], a[1], a[2])
[docs]def test_check_epsilon_argument_type():
arg = ("1e-3", [0.0001])
for a in arg:
with pytest.raises(TypeError):
_check_epsilon(a)
[docs]def test_check_epsilon_argument_value():
with pytest.raises(ValueError):
_check_epsilon(-0.00001)
[docs]def test_check_epsilon():
_check_epsilon(1e-2)
_check_epsilon(0.001)
[docs]def test_check_gencost_argument_type(mock_grid):
gencost_n = mock_grid.gencost["after"].copy()
gencost_n.n = gencost_n.n.astype(float)
arg = (1, gencost_n)
for a in arg:
with pytest.raises(TypeError):
_check_gencost(a)
[docs]def test_check_gencost_argument_value(mock_grid):
gencost = mock_grid.gencost["after"]
gencost_n = mock_grid.gencost["after"].copy()
gencost_n.loc[0, "n"] = 10
gencost_type = mock_grid.gencost["after"].copy()
gencost_type.loc[3, "type"] = 3
arg = (
gencost.drop(columns=["type"]),
gencost.drop(columns=["n"]),
gencost_type,
gencost_n,
)
for a in arg:
with pytest.raises(ValueError):
_check_gencost(a)
[docs]def test_check_gencost(mock_grid):
gencost = mock_grid.gencost["after"]
_check_gencost(gencost)
