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4 changes: 4 additions & 0 deletions CHANGES.md
Original file line number Diff line number Diff line change
@@ -1,3 +1,7 @@
## Changes in 0.0.2 (in development)

- Handle unpacked data directories (#3)

## Changes in 0.0.1

Initial release
1 change: 1 addition & 0 deletions environment.yml
Original file line number Diff line number Diff line change
Expand Up @@ -3,6 +3,7 @@ channels:
- conda-forge
dependencies:
- python >=3.11
- fsspec
- rioxarray
- shapely
- xarray
1 change: 1 addition & 0 deletions pyproject.toml
Original file line number Diff line number Diff line change
Expand Up @@ -21,6 +21,7 @@ license = "MIT"
license-files = ["LICEN[CS]E*"]
requires-python = ">=3.11"
dependencies = [
"fsspec",
"rioxarray",
"shapely",
"xarray",
Expand Down
2 changes: 1 addition & 1 deletion xarray_enmap/__init__.py
Original file line number Diff line number Diff line change
@@ -1 +1 @@
__version__ = "0.0.1"
__version__ = "0.0.2.dev0"
85 changes: 60 additions & 25 deletions xarray_enmap/xarray_enmap.py
Original file line number Diff line number Diff line change
@@ -1,7 +1,7 @@
# Copyright (c) 2025 by Brockmann Consult GmbH
# Permissions are hereby granted under the terms of the MIT License:
# https://opensource.org/licenses/MIT.

import re
from collections.abc import Iterable
import logging
import os
Expand All @@ -10,7 +10,7 @@
import shutil
import tarfile
import tempfile
from typing import Any
from typing import Any, Mapping
import xml.etree
import zipfile

Expand Down Expand Up @@ -49,9 +49,9 @@ def open_dataset(
if path.is_file():
ds = read_dataset_from_archive(filename_or_obj, self.temp_dir)
elif path.is_dir():
ds = read_dataset_from_directory(path)
ds = read_dataset_from_unknown_directory(path, self.temp_dir)
elif filename_or_obj.startswith("s3://"):
ds = read_dataset_from_directory(filename_or_obj)
ds = read_dataset_from_inner_directory(filename_or_obj)
else:
raise ValueError(
f"{filename_or_obj} is neither a path nor a directory."
Expand All @@ -65,38 +65,67 @@ def close(self):


def read_dataset_from_archive(
input_filename: str, temp_dir: str
input_filename: str | os.PathLike[Any], temp_dir: str
) -> xr.Dataset:
data_dirs = list(extract_archives(input_filename, temp_dir))
if len(data_dirs) > 1:
LOGGER.warning("Multiple data archives found; reading the first.")
return read_dataset_from_directory(data_dirs[0])
return read_dataset_from_inner_directory(data_dirs[0])


def read_dataset_from_unknown_directory(
data_dir: str | os.PathLike[Any], temp_dir: str
):
data_path = pathlib.Path(data_dir)
metadata_files = list(data_path.glob("*METADATA.XML"))
match len(metadata_files):
case 0:
# assume outer directory
return read_dataset_from_archive(data_path, temp_dir)
case 1:
# assume inner directory
return read_dataset_from_inner_directory(data_path)
case _:
raise RuntimeError("Too many METADATA.XML files")


def read_dataset_from_directory(data_dir):
LOGGER.info(f"Processing {data_dir}")
def read_dataset_from_inner_directory(data_dir: str | os.PathLike[Any]):
data_path = pathlib.Path(data_dir)
LOGGER.info(f"Processing {data_path}")
arrays = {
name: rioxarray.open_rasterio(
str(data_dir) + "/" + (filename + ".TIF")
).squeeze()
for name, filename in VAR_MAP.items()
name: rioxarray.open_rasterio(filename).squeeze()
for name, filename in find_datafiles(data_path).items()
}
ds = xr.Dataset(arrays)
add_metadata(ds, data_dir)
add_metadata(ds, data_path)
return ds


def find_datafiles(data_path: pathlib.Path) -> Mapping[str, pathlib.Path]:
assert data_path.is_dir()
tiffs = list(data_path.glob("*.TIF"))
result = {}
for name, basename in VAR_MAP.items():
pattern = f"(ENMAP.*)?{basename}.TIF"
matches = [tiff for tiff in tiffs if re.match(pattern, tiff.name)]
assert len(matches) > 0, f"Can't find TIFF for {name}"
assert len(matches) < 2, f"Too many TIFFs for {name}"
result[name] = matches[0]
return result


def add_metadata(ds: xr.Dataset, data_dir: pathlib.Path):
metadata_paths = list(data_dir.glob("*METADATA.XML"))
assert len(metadata_paths) == 1
metadata_path = metadata_paths[0]
if str(data_dir).startswith("s3://"):
import fsspec

fs = fsspec.filesystem("s3")
with fs.open(str(data_dir) + "/" + "METADATA.XML") as fh:
with fs.open(metadata_path) as fh:
root = xml.etree.ElementTree.parse(fh).getroot()
else:
root = xml.etree.ElementTree.parse(
str(data_dir) + "/" + "METADATA.XML"
).getroot()
root = xml.etree.ElementTree.parse(metadata_path).getroot()
points = root.findall("base/spatialCoverage/boundingPolygon/point")
bounds = shapely.Polygon(
[float(p.find("longitude").text), p.find("latitude").text]
Expand Down Expand Up @@ -190,13 +219,16 @@ def extract_archives(
final_path = dest_path / "data"
os.mkdir(final_path)
archive_path = pathlib.Path(archive_path)
if archive_path.name.endswith(".tar.gz"):
# An EnMAP tgz usually contains one or more zip archives containing
# the actual data files.
outer_path = dest_path / "outer-archive"
LOGGER.info(f"Extracting {archive_path.name}")
with tarfile.open(archive_path) as tgz_file:
tgz_file.extractall(path=outer_path, filter="data")
if archive_path.name.endswith(".tar.gz") or archive_path.is_dir():
if archive_path.is_dir():
outer_path = archive_path
else:
# An EnMAP tgz usually contains one or more zip archives containing
# the actual data files.
outer_path = dest_path / "outer-archive"
LOGGER.info(f"Extracting {archive_path.name}")
with tarfile.open(archive_path) as tgz_file:
tgz_file.extractall(path=outer_path, filter="data")
data_paths = []
for index, path_to_zip_file in enumerate(find_zips(outer_path)):
data_paths.append(
Expand All @@ -206,7 +238,7 @@ def extract_archives(
else:
# Assume it's a zip and skip the outer archive extraction step.
LOGGER.info(f"Assuming {archive_path} is an inner zipfile")
return [(extract_zip(final_path, 0, inner_path, archive_path))]
return [extract_zip(final_path, 0, inner_path, archive_path)]


def find_zips(root: os.PathLike):
Expand All @@ -232,6 +264,9 @@ def extract_zip(
output_data_path = final_path / input_data_dir
prefix_length = len(input_data_path.name) + 1
os.mkdir(output_data_path)
# Strip the long, redundant prefix from the filenames. Not visible anyway
# via the xarray plugin, but convenient if using this function as a
# standalone archive extractor.
for filepath in input_data_path.iterdir():
os.rename(filepath, output_data_path / filepath.name[prefix_length:])
return output_data_path