pantierra/efast-phenocam-validation
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Refactored a bit.

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This commit is contained in:
Felix Delattre 2025-12-27 10:25:17 +01:00
parent 290c8f8c57
commit 6bbaa4b3eb
8 changed files with 323 additions and 331 deletions
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121
download_s3.py
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@ -11,6 +11,66 @@ from rasterio.transform import from_bounds
load_dotenv()
BBOX_SIZE = 0.011
def _get_bbox(lon, lat):
half = BBOX_SIZE / 2
return [lon - half, lat - half, lon + half, lat + half]
def _process_netcdf(nc_file, output_dir, bands, openeo_bands):
with netCDF4.Dataset(str(nc_file), "r") as nc:
times = netCDF4.num2date(nc.variables["t"][:], nc.variables["t"].units)
x_coords = nc.variables["x"][:]
y_coords = nc.variables["y"][:]
band_vars = sorted(
[v for v in nc.variables.keys() if v.startswith("B") and v[1:].isdigit()]
)
band_names = [list(bands.keys())[openeo_bands.index(b)] for b in band_vars]
transform = from_bounds(
float(x_coords.min()),
float(y_coords.min()),
float(x_coords.max()),
float(y_coords.max()),
len(x_coords),
len(y_coords),
)
print(f"[S3] Found {len(times)} time steps")
date_counts = {}
for t_idx, time_val in enumerate(times):
dt = (
time_val
if isinstance(time_val, datetime)
else netCDF4.num2date(nc.variables["t"][t_idx], nc.variables["t"].units)
)
date_str = dt.strftime("%Y%m%d")
increment = date_counts.get(date_str, 0)
date_counts[date_str] = increment + 1
band_data = [nc.variables[b][t_idx, :, :] for b in band_vars]
stacked = np.stack(band_data, axis=0)
output_path = output_dir / f"{date_str}_{increment}.geotiff"
with rasterio.open(
output_path,
"w",
driver="GTiff",
height=len(y_coords),
width=len(x_coords),
count=len(band_data),
dtype=stacked.dtype,
crs="EPSG:32632",
transform=transform,
compress="lzw",
) as dst:
dst.write(stacked)
for i, band_name in enumerate(band_names, 1):
dst.set_band_description(i, band_name)
print(f"[S3] Saved: {output_path}")
def download_s3(season, site_position, site_name, date_range=None):
lat, lon = site_position
@ -19,13 +79,7 @@ def download_s3(season, site_position, site_name, date_range=None):
print(f"[S3] Starting download: {site_name} ({lat:.6f}, {lon:.6f}), {season}")
bbox_size = 0.011
bbox = [
lon - bbox_size / 2,
lat - bbox_size / 2,
lon + bbox_size / 2,
lat + bbox_size / 2,
]
bbox = _get_bbox(lon, lat)
bands = {
"SDR_Oa04": "blue",
"SDR_Oa06": "green",
@ -81,57 +135,6 @@ def download_s3(season, site_position, site_name, date_range=None):
datacube.download(str(output_file), format="NetCDF")
print("[S3] Processing NetCDF...")
nc = netCDF4.Dataset(str(output_file), "r")
times = netCDF4.num2date(nc.variables["t"][:], nc.variables["t"].units)
x_coords = nc.variables["x"][:]
y_coords = nc.variables["y"][:]
band_vars = sorted(
[v for v in nc.variables.keys() if v.startswith("B") and v[1:].isdigit()]
)
band_names = [list(bands.keys())[openeo_bands.index(b)] for b in band_vars]
transform = from_bounds(
float(x_coords.min()),
float(y_coords.min()),
float(x_coords.max()),
float(y_coords.max()),
len(x_coords),
len(y_coords),
)
print(f"[S3] Found {len(times)} time steps")
date_counts = {}
for t_idx, time_val in enumerate(times):
dt = (
time_val
if isinstance(time_val, datetime)
else netCDF4.num2date(nc.variables["t"][t_idx], nc.variables["t"].units)
)
date_str = dt.strftime("%Y%m%d")
increment = date_counts.get(date_str, 0)
date_counts[date_str] = increment + 1
band_data = [nc.variables[b][t_idx, :, :] for b in band_vars]
stacked = np.stack(band_data, axis=0)
output_path = output_dir / f"{date_str}_{increment}.geotiff"
with rasterio.open(
output_path,
"w",
driver="GTiff",
height=len(y_coords),
width=len(x_coords),
count=len(band_data),
dtype=stacked.dtype,
crs="EPSG:32632",
transform=transform,
compress="lzw",
) as dst:
dst.write(stacked)
for i, band_name in enumerate(band_names, 1):
dst.set_band_description(i, band_name)
print(f"[S3] Saved: {output_path}")
nc.close()
_process_netcdf(output_file, output_dir, bands, openeo_bands)
os.remove(output_file)
print("[S3] Completed")