ElEgEv/EvaluationEfficiencyOptimizationWind
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prediction #10

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shadowik merged 2 commits from prediction into front-2-fix-gen 2024-12-01 18:53:33 +04:00
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1 changed files with 22 additions and 18 deletions
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davisAPI/prediction.py
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@ -103,7 +103,7 @@ def create_batch(date, levels, downloads, download_path):
return batch.regrid(res=0.1) return batch.regrid(res=0.1)
def create_batch_random(levels: tuple[int], date: datetime): def create_batch_random(levels: tuple[int], date: tuple):
"""Создает объект Batch с рандомными данными для модели.""" """Создает объект Batch с рандомными данными для модели."""
return Batch( return Batch(
surf_vars={k: torch.randn(1, 2, 17, 32) for k in ("2t", "10u", "10v", "msl")}, surf_vars={k: torch.randn(1, 2, 17, 32) for k in ("2t", "10u", "10v", "msl")},
@ -112,7 +112,7 @@ def create_batch_random(levels: tuple[int], date: datetime):
metadata=Metadata( metadata=Metadata(
lat=torch.linspace(90, -90, 17), lat=torch.linspace(90, -90, 17),
lon=torch.linspace(0, 360, 32 + 1)[:-1], lon=torch.linspace(0, 360, 32 + 1)[:-1],
time=(date,), time=date,
atmos_levels=levels, atmos_levels=levels,
), ),
) )
@ -138,24 +138,26 @@ def get_wind_speed_and_direction(prediction, batch: Batch, lat: float, lon: floa
u_values = prediction.atmos_vars["u"][:, :, :, lat_idx, lon_idx] u_values = prediction.atmos_vars["u"][:, :, :, lat_idx, lon_idx]
v_values = prediction.atmos_vars["v"][:, :, :, lat_idx, lon_idx] v_values = prediction.atmos_vars["v"][:, :, :, lat_idx, lon_idx]
wind_speeds=[]
wind_directions=[]
for i in range(u_values.numel()):
u_scalar = u_values.view(-1)[i].item() # Разворачиваем тензор в одномерный и берем элемент
v_scalar = v_values.view(-1)[i].item()
u_scalar = u_values.item() print("u value:", u_scalar)
v_scalar = v_values.item() print("v value:", v_scalar)
print("u value:", u_scalar) u_with_units = u_scalar * units("m/s")
print("v value:", v_scalar) v_with_units = v_scalar * units("m/s")
u_with_units = u_scalar * units("m/s")
v_with_units = v_scalar * units("m/s")
# Рассчитайте направление и скорость ветра # Рассчитайте направление и скорость ветра
wind_dir = metpy.calc.wind_direction(u_with_units, v_with_units) wind_dir = metpy.calc.wind_direction(u_with_units, v_with_units)
wind_speed = metpy.calc.wind_speed(u_with_units, v_with_units) wind_speed = metpy.calc.wind_speed(u_with_units, v_with_units)
wind_dir_text = wind_direction_to_text(wind_dir.magnitude) wind_speeds.append(wind_speed.magnitude.item())
# Вывод результата wind_directions.append(wind_dir.magnitude.item())
print(f"Направление ветра: {wind_dir_text} ({wind_dir:.2f}°)")
print(f"Скорость ветра: {wind_speed:.2f} м/с") return wind_speeds,wind_directions
return wind_dir.magnitude.item(), wind_speed.magnitude.item()
def wind_direction_to_text(wind_dir_deg): def wind_direction_to_text(wind_dir_deg):
@ -169,12 +171,14 @@ def wind_direction_to_text(wind_dir_deg):
def main(): def main():
levels = (100,) levels = (100,)
date = datetime(2024, 11, 5, 12)
date1 = datetime(2024, 11, 27, 12)
date2 = datetime(2024, 11, 28, 12)
date_tuple = (date1, date2,)
# downloads, download_path = get_download_paths(date) # downloads, download_path = get_download_paths(date)
# download_data(downloads) # Скачиваем данные, если их нет # download_data(downloads) # Скачиваем данные, если их нет
# batch_actual = create_batch(date, levels, downloads, download_path) # batch_actual = create_batch(date, levels, downloads, download_path)
batch_actual = create_batch_random(levels, date) batch_actual = create_batch_random(levels, date_tuple)
prediction_actual = run_model(batch_actual) prediction_actual = run_model(batch_actual)
wind_speed_and_direction = get_wind_speed_and_direction(prediction_actual, batch_actual, 50, 20) wind_speed_and_direction = get_wind_speed_and_direction(prediction_actual, batch_actual, 50, 20)
return wind_speed_and_direction return wind_speed_and_direction