File size: 2,701 Bytes
5154c4e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 | #!/usr/bin/env python3
import math
from pathlib import Path
import floris
from floris import FlorisModel
import numpy as np
import yaml
from eval_utils import (
desktop_root,
parse_floats,
print_result,
read_numeric_csv,
require_calls,
require_source_tokens,
run_submission,
)
def reference_results():
path = Path(floris.__file__).resolve().with_name("default_inputs.yaml")
config = yaml.safe_load(path.read_text(encoding="utf-8"))
config["logging"]["console"]["level"] = "ERROR"
coordinates = [0.0, 882.0, 1764.0]
config["farm"]["layout_x"] = [x for y in coordinates for x in coordinates]
config["farm"]["layout_y"] = [y for y in coordinates for x in coordinates]
config["farm"]["turbine_type"] = ["nrel_5MW"] * 9
model = FlorisModel(config)
directions = np.arange(0.0, 360.0, 30.0)
model.set(
wind_directions=directions,
wind_speeds=np.full(12, 8.0),
turbulence_intensities=np.full(12, 0.06),
)
model.run()
matrix_kw = model.get_turbine_powers() / 1000.0
totals = matrix_kw.sum(axis=1)
model.set(wind_directions=[270.0], wind_speeds=[8.0], turbulence_intensities=[0.06])
model.run_no_wake()
no_wake_kw = float(model.get_turbine_powers().sum() / 1000.0)
summary = [
float(totals.max()),
float(totals.min()),
float((no_wake_kw - totals.min()) / no_wake_kw * 100.0),
]
return matrix_kw, summary
def check() -> bool:
root = desktop_root()
tree = run_submission(root, "wind_sector.py", ["power_matrix.csv", "summary.txt"])
require_calls(tree, {"FlorisModel": 1, "set": 2, "run": 1, "run_no_wake": 1, "get_turbine_powers": 2})
require_source_tokens(root / "wind_sector.py", ["30.0", "360.0", "126.0", "7.0", "nrel_5MW"])
actual_matrix = np.asarray(read_numeric_csv(root / "power_matrix.csv", 12, 9), dtype=float)
actual_summary = parse_floats(root / "summary.txt", 3)
expected_matrix, expected_summary = reference_results()
if not np.allclose(actual_matrix, expected_matrix, rtol=5e-3, atol=1e-2):
return False
if not all(
math.isclose(a, e, rel_tol=5e-3, abs_tol=1e-2)
for a, e in zip(actual_summary, expected_summary)
):
return False
totals = actual_matrix.sum(axis=1)
return (
math.isclose(actual_summary[0], float(totals.max()), rel_tol=1e-6, abs_tol=1e-3)
and math.isclose(actual_summary[1], float(totals.min()), rel_tol=1e-6, abs_tol=1e-3)
and 0.0 < actual_summary[2] < 100.0
)
if __name__ == "__main__":
try:
result = check()
except Exception:
result = False
raise SystemExit(print_result(result))
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