src/esdac/glosem/process.py

import os
from pathlib import Path

import rasterio
from rasterio.transform import from_bounds

from src.process.io import prepare_dirs, unzip, upload
from src.process.processor import process_tif

# === Step 1: Set up local and drive directories ===
local_processed_dir, drive_download_dir, drive_processed_dir = (
    prepare_dirs("esdac", Path(__file__).parent.stem)
)

# === Step 2: Unzip all ZIP files from drive/download to local/processed ===
unzip(local_processed_dir, drive_download_dir, zip_files=None)
os.system("mv src/esdac/glosem/processed/Data2_SOIL_DISPLACEMENT_ESTIMATE_2019_1/"
          "Data2_SOIL_DISPLACEMENT_ESTIMATE_2019_1/SOIL_DISPLACEMENT_ESTIMATE_2019.tif.ovr "
          "src/esdac/glosem/processed/Data2_SOIL_DISPLACEMENT_ESTIMATE_2019_1/"
          "Data2_SOIL_DISPLACEMENT_ESTIMATE_2019_1/SOIL_DISPLACEMENT_ESTIMATE_2019.tif")

# === Step 3: Process all TIFF files under local/processed ===
move_list = []
for tif_path in sorted(local_processed_dir.rglob("*.tif")):
    move_list = process_tif(tif_path, move_list)

f = local_processed_dir / "Data2_SOIL_DISPLACEMENT_ESTIMATE_2019_1" / \
    "Data2_SOIL_DISPLACEMENT_ESTIMATE_2019_1" / "SOIL_DISPLACEMENT_ESTIMATE_2019.standardized.tif"

with rasterio.open(f, "r+") as ds:
    ds.crs = "EPSG:4326"
    ds.transform = from_bounds(-180, -90, 180, 90, ds.width, ds.height)
print("✅ CRS and transform fixed:", f)

# === Step 4: Upload processed files to drive/processed and clean up local ===
upload(local_processed_dir, drive_processed_dir, move_list)