import new_import_ODC
importlib = __import__('importlib')
importlib.reload(new_import_ODC)
from new_import_ODC import *
import numpy as np

date_range = ("2022-09-01", "2022-10-01")
longtitude_range = (105.86, 105.94)
latitude_range = (9.65, 9.69)
coordinates = (longtitude_range, latitude_range)

print("Loading S2...")
data = load_data(None, date_range, longtitude_range, latitude_range)
result = mask_clean(data)
ds1 = calculate_indices(result, index="NDVI", satellite_mission="s2")
ndvi = ds1["NDVI"]
time_split = [
    slice("2022-09-01", "2023-01-01"),
    slice("2023-01-01", "2023-05-01"),
    slice("2023-05-01", "2023-07-01"),
    slice("2023-07-01", "2022-10-01"),
]
fill_nan_ndvi = fill_nan(ndvi, time_split)
average_ndvi = fill_nan_ndvi.resample(time="1M").mean().compute()

print("Loading S1...")
dsvh, dsvv = load_data_sen1(None, date_range, coordinates)
average_vv = calculate_average(dsvv, time_pattern='1M')
average_vh = calculate_average(dsvh, time_pattern='1M')

train = load_train_data("train/ST_training_data_updated_1130points_new.shp")
point = train.iloc[0]

ndvi_val = average_ndvi.sel(x=point.geometry.x, y=point.geometry.y, method='nearest').values
vh_val = average_vh.sel(x=point.geometry.x, y=point.geometry.y, method='nearest').values
vv_val = average_vv.sel(x=point.geometry.x, y=point.geometry.y, method='nearest').values

print("NDVI shape:", ndvi_val.shape, "ndim:", ndvi_val.ndim)
print("VH shape:", vh_val.shape, "ndim:", vh_val.ndim)
print("VV shape:", vv_val.shape, "ndim:", vv_val.ndim)