Refactored a bit.

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

168
ndvi.py
View file

@ -5,12 +5,14 @@ from rasterio.warp import transform as transform_coords
from pathlib import Path
from datetime import datetime
RED_BAND = 3
NIR_BAND = 4
def _calculate_and_write_ndvi(input_file, output_file):
"""Calculate NDVI from red and NIR bands and write to output file."""
with rasterio.open(input_file) as src:
red = src.read(3).astype(np.float32)
nir = src.read(4).astype(np.float32)
red = src.read(RED_BAND).astype(np.float32)
nir = src.read(NIR_BAND).astype(np.float32)
mask = (red > 0) & (nir > 0)
ndvi = np.zeros_like(red, dtype=np.float32)
@ -31,13 +33,26 @@ def _calculate_and_write_ndvi(input_file, output_file):
dst.set_band_description(1, "NDVI")
def _get_ndvi_value(ndvi_file, site_position):
try:
with rasterio.open(ndvi_file) as src:
lon, lat = site_position[1], site_position[0]
x, y = transform_coords("EPSG:4326", src.crs, [lon], [lat])
samples = list(src.sample([(x[0], y[0])]))
if samples:
value = float(samples[0][0])
if value != 0 and not np.isnan(value):
return value
except Exception:
pass
return None
def _create_timeseries_for_dir(output_dir, site_position, source_name):
"""Create timeseries.json for NDVI files in the given directory."""
print(f"[NDVI-{source_name}] Creating timeseries.json...")
timeseries = []
ndvi_files = sorted(output_dir.glob("*.geotiff"))
for ndvi_file in ndvi_files:
for ndvi_file in sorted(output_dir.glob("*.geotiff")):
filename = ndvi_file.name
date_str = filename.split("_")[0]
try:
@ -45,18 +60,9 @@ def _create_timeseries_for_dir(output_dir, site_position, source_name):
except ValueError:
date = date_str
ndvi_value = None
try:
with rasterio.open(ndvi_file) as src:
lon, lat = site_position[1], site_position[0]
x, y = transform_coords("EPSG:4326", src.crs, [lon], [lat])
samples = list(src.sample([(x[0], y[0])]))
if samples:
value = float(samples[0][0])
if value != 0 and not np.isnan(value):
ndvi_value = value
except Exception as e:
print(f"[NDVI-{source_name}] Warning: Could not sample {filename}: {e}")
ndvi_value = _get_ndvi_value(ndvi_file, site_position)
if ndvi_value is None:
print(f"[NDVI-{source_name}] Warning: Could not sample {filename}")
timeseries.append({"date": date, "filename": filename, "ndvi": ndvi_value})
@ -68,30 +74,35 @@ def _create_timeseries_for_dir(output_dir, site_position, source_name):
print(f"[NDVI-{source_name}] Saved: {timeseries_file} ({len(timeseries)} entries)")
def _process_ndvi_files(
input_dir, output_dir, source_name, pattern="*.geotiff", output_namer=None
):
output_dir.mkdir(parents=True, exist_ok=True)
print(f"[NDVI-{source_name}] Processing {input_dir}...")
geotiff_files = sorted(input_dir.glob(pattern))
if not geotiff_files:
print(f"[NDVI-{source_name}] No files found")
return
for geotiff_file in geotiff_files:
output_file = output_dir / (
output_namer(geotiff_file) if output_namer else geotiff_file.name
)
if output_file.exists():
print(f"[NDVI-{source_name}] Skipping {geotiff_file.name} (exists)")
continue
_calculate_and_write_ndvi(geotiff_file, output_file)
print(f"[NDVI-{source_name}] Saved: {output_file}")
def generate_ndvi_raw(season, site_position, site_name):
for source in ["s2", "s3"]:
input_dir = Path(f"data/{site_name}/{season}/raw/{source}/")
output_dir = Path(f"data/{site_name}/{season}/raw/ndvi/{source}/")
output_dir.mkdir(parents=True, exist_ok=True)
print(f"[NDVI-{source.upper()}] Processing {input_dir}...")
geotiff_files = sorted(input_dir.glob("*.geotiff"))
if not geotiff_files:
print(f"[NDVI-{source.upper()}] No files found")
continue
for geotiff_file in geotiff_files:
output_file = output_dir / geotiff_file.name
if output_file.exists():
print(f"[NDVI-{source.upper()}] Skipping {geotiff_file.name} (exists)")
continue
_calculate_and_write_ndvi(geotiff_file, output_file)
print(f"[NDVI-{source.upper()}] Saved: {output_file}")
print(f"[NDVI-{source.upper()}] Completed")
_process_ndvi_files(input_dir, output_dir, source.upper())
def create_ndvi_timeseries_raw(season, site_position, site_name):
@ -100,67 +111,50 @@ def create_ndvi_timeseries_raw(season, site_position, site_name):
_create_timeseries_for_dir(output_dir, site_position, source.upper())
def _get_output_name_prepared(geotiff_file):
if geotiff_file.suffix == ".tif":
if "REFL" in geotiff_file.stem:
date_str = geotiff_file.stem.split("_")[1]
return f"{date_str}_ndvi.geotiff"
return geotiff_file.name.replace(".tif", ".geotiff")
return geotiff_file.name
def _fusion_namer(f):
date_str = f.stem.split("_")[1]
return f"{date_str}_ndvi.geotiff"
def generate_ndvi_prepared(season, site_position, site_name):
for source in ["s2", "s3"]:
input_dir = Path(f"data/{site_name}/{season}/prepared/{source}/")
output_dir = Path(f"data/{site_name}/{season}/prepared/ndvi/{source}/")
output_dir.mkdir(parents=True, exist_ok=True)
print(f"[NDVI-PREPARED-{source.upper()}] Processing {input_dir}...")
geotiff_files = sorted(input_dir.glob("*.geotiff")) + sorted(input_dir.glob("*.tif"))
if not geotiff_files:
print(f"[NDVI-PREPARED-{source.upper()}] No files found")
continue
for geotiff_file in geotiff_files:
if geotiff_file.suffix == ".tif":
if "REFL" in geotiff_file.stem:
date_str = geotiff_file.stem.split("_")[1]
output_file = output_dir / f"{date_str}_ndvi.geotiff"
else:
output_file = output_dir / geotiff_file.name.replace(".tif", ".geotiff")
else:
output_file = output_dir / geotiff_file.name
if output_file.exists():
print(f"[NDVI-PREPARED-{source.upper()}] Skipping {geotiff_file.name} (exists)")
continue
_calculate_and_write_ndvi(geotiff_file, output_file)
print(f"[NDVI-PREPARED-{source.upper()}] Saved: {output_file}")
print(f"[NDVI-PREPARED-{source.upper()}] Completed")
for pattern in ["*.geotiff", "*.tif"]:
_process_ndvi_files(
input_dir,
output_dir,
f"PREPARED-{source.upper()}",
pattern=pattern,
output_namer=_get_output_name_prepared,
)
input_dir = Path(f"data/{site_name}/{season}/prepared/fusion/")
output_dir = Path(f"data/{site_name}/{season}/prepared/ndvi/fusion/")
output_dir.mkdir(parents=True, exist_ok=True)
print(f"[NDVI-FUSION] Processing {input_dir}...")
geotiff_files = sorted(input_dir.glob("REFL_*.tif"))
if not geotiff_files:
print(f"[NDVI-FUSION] No files found")
return
for geotiff_file in geotiff_files:
date_str = geotiff_file.stem.split("_")[1]
output_file = output_dir / f"{date_str}_ndvi.geotiff"
if output_file.exists():
print(f"[NDVI-FUSION] Skipping {geotiff_file.name} (exists)")
continue
_calculate_and_write_ndvi(geotiff_file, output_file)
print(f"[NDVI-FUSION] Saved: {output_file}")
print(f"[NDVI-FUSION] Completed")
_process_ndvi_files(
input_dir,
output_dir,
"FUSION",
pattern="REFL_*.tif",
output_namer=_fusion_namer,
)
def create_ndvi_timeseries_prepared(season, site_position, site_name):
for source in ["s2", "s3"]:
output_dir = Path(f"data/{site_name}/{season}/prepared/ndvi/{source}/")
_create_timeseries_for_dir(output_dir, site_position, f"PREPARED-{source.upper()}")
_create_timeseries_for_dir(
output_dir, site_position, f"PREPARED-{source.upper()}"
)
output_dir = Path(f"data/{site_name}/{season}/prepared/ndvi/fusion/")
_create_timeseries_for_dir(output_dir, site_position, "FUSION")