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"mkdocs-jupyter>=0.26.2", diff --git a/src/lazycogs/__init__.py b/src/lazycogs/__init__.py index c72b298..8deff77 100644 --- a/src/lazycogs/__init__.py +++ b/src/lazycogs/__init__.py @@ -20,6 +20,7 @@ MosaicMethodBase, StdevMethod, ) +from lazycogs._single import open_cog, open_cog_async from lazycogs._store import store_for __all__ = [ @@ -36,6 +37,8 @@ "StdevMethod", "align_bbox", "open", + "open_cog", + "open_cog_async", "read_chunk_async", "run_on_loop", "store_for", diff --git a/src/lazycogs/_single.py b/src/lazycogs/_single.py new file mode 100644 index 0000000..4f547fb --- /dev/null +++ b/src/lazycogs/_single.py @@ -0,0 +1,146 @@ +"""Open a single COG at its native grid as an xarray DataArray. + +Unlike :func:`lazycogs.open`, which mosaics a whole STAC/geoparquet +collection onto a caller-defined output grid, this module reads one +Cloud-Optimized GeoTIFF in place: native CRS, native resolution, native +shape, no reprojection. It is the obstore-backed analogue of +``rioxarray.open_rasterio`` for a single asset. +""" + +from __future__ import annotations + +from typing import TYPE_CHECKING + +import numpy as np +from async_geotiff import GeoTIFF +from pyproj import CRS +from rasterix import RasterIndex +from xarray import Coordinates, DataArray + +from lazycogs._core import _spatial_coords_with_eager_variables +from lazycogs._executor import run_on_loop +from lazycogs._store import resolve + +if TYPE_CHECKING: + from collections.abc import Callable + + from async_geotiff import Store + +__all__ = ["open_cog", "open_cog_async"] + + +def _build_cog_dataarray(geotiff: GeoTIFF, raster: object) -> DataArray: + """Wrap a native-resolution read in a rioxarray-compatible DataArray. + + Args: + geotiff: The opened GeoTIFF, used for ``scales``/``offsets``/``nodata``. + raster: The result of ``geotiff.read()`` with ``data`` (shape + ``(band, y, x)``), ``transform``, ``crs``, ``width``, ``height``. + + Returns: + DataArray with dims ``(band, y, x)`` at the COG's native grid. + + """ + data = raster.data + crs = CRS.from_user_input(raster.crs) + + index = RasterIndex.from_transform( + raster.transform, + width=raster.width, + height=raster.height, + x_dim="x", + y_dim="y", + crs=crs, + ) + spatial_coords = _spatial_coords_with_eager_variables(index) + + crs_wkt = crs.to_wkt() + spatial_ref = DataArray( + np.array(0), + attrs={ + "crs_wkt": crs_wkt, + "spatial_ref": crs_wkt, + "GeoTransform": " ".join(str(v) for v in raster.transform.to_gdal()), + }, + ) + + attrs: dict[str, object] = {"grid_mapping": "spatial_ref"} + if geotiff.nodata is not None: + attrs["_FillValue"] = geotiff.nodata + scale = geotiff.scales[0] if geotiff.scales else 1.0 + offset = geotiff.offsets[0] if geotiff.offsets else 0.0 + if scale != 1.0: + attrs["scale_factor"] = scale + if offset != 0.0: + attrs["add_offset"] = offset + + bands = list(range(1, data.shape[0] + 1)) + return DataArray( + data, + dims=("band", "y", "x"), + coords=Coordinates({"band": bands, "spatial_ref": spatial_ref}) + | spatial_coords, + attrs=attrs, + ) + + +async def open_cog_async( + href: str, + *, + store: Store | None = None, + path_from_href: Callable[[str], str] | None = None, +) -> DataArray: + """Open one COG at native resolution as an ``(band, y, x)`` DataArray. + + Async variant of :func:`open_cog` for use inside a running event loop. + + Args: + href: Asset URL or path. When ``store`` is ``None``, an obstore-backed + store is auto-resolved from the URL root; otherwise only the object + path is extracted from the HREF. + store: Pre-configured :class:`async_geotiff.Store` for all reads. + path_from_href: Optional callable ``(href) -> path`` overriding the + default ``urlparse`` extraction (see :func:`lazycogs.open`). + + Returns: + DataArray at the COG's native CRS, resolution, and shape — no + reprojection. Source ``nodata`` is set as ``_FillValue`` and any + ``scale``/``offset`` as ``scale_factor``/``add_offset`` so rioxarray's + ``mask_and_scale`` decoding applies them. + + """ + resolved_store, path = resolve(href, store=store, path_fn=path_from_href) + geotiff = await GeoTIFF.open(path, store=resolved_store) + raster = await geotiff.read() + return _build_cog_dataarray(geotiff, raster) + + +def open_cog( + href: str, + *, + store: Store | None = None, + path_from_href: Callable[[str], str] | None = None, +) -> DataArray: + """Open one COG at native resolution as an ``(band, y, x)`` DataArray. + + Reads a single Cloud-Optimized GeoTIFF in place — native CRS, resolution, + and shape, no reprojection or mosaicking. Use :func:`lazycogs.open` for a + reprojected mosaic across a STAC/geoparquet collection. + + Args: + href: Asset URL or path. When ``store`` is ``None``, an obstore-backed + store is auto-resolved from the URL root; otherwise only the object + path is extracted from the HREF. + store: Pre-configured :class:`async_geotiff.Store` for all reads. + path_from_href: Optional callable ``(href) -> path`` overriding the + default ``urlparse`` extraction (see :func:`lazycogs.open`). + + Returns: + DataArray at the COG's native CRS, resolution, and shape. Source + ``nodata`` is set as ``_FillValue`` and any ``scale``/``offset`` as + ``scale_factor``/``add_offset``. + + """ + return run_on_loop( + open_cog_async(href, store=store, path_from_href=path_from_href), + ) diff --git a/test.ipynb b/test.ipynb new file mode 100644 index 0000000..d52ab2d --- /dev/null +++ b/test.ipynb @@ -0,0 +1,727 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 6, + "id": "755b4e97", + "metadata": {}, + "outputs": [], + "source": [ + "import boto3\n", + "import lazycogs\n", + "from odc.geo.geobox import GeoBox\n", + "from affine import Affine\n", + "import rustac\n", + "from obstore.store import S3Store\n", + "\n", + "geobox = GeoBox(\n", + " shape=(10, 10),\n", + " affine=Affine(5000.0, 0.0, 690400.0, 0.0, -5000.0, 4660400.0),\n", + " crs=\"EPSG:32614\"\n", + ")\n", + "\n", + "# 1. Fetch the frozen credentials directly from boto3\n", + "session = boto3.Session(profile_name=\"cdse\")\n", + "creds = session.get_credentials().get_frozen_credentials()\n", + "\n", + "# # 2. Build the configuration dictionary for obstore\n", + "# obstore_config = {\n", + "# \"aws_access_key_id\": creds.access_key,\n", + "# \"aws_secret_access_key\": creds.secret_key,\n", + "# # \"aws_endpoint_url\": \"https://eodata.dataspace.copernicus.eu\",\n", + "# \"aws_virtual_hosted_style_request\": \"false\",\n", + "# \"aws_region\": session.region_name or \"default\",\n", + "# }\n", + "# # If your profile uses temporary STS credentials, pass the token too\n", + "# if creds.token:\n", + "# obstore_config[\"aws_session_token\"] = creds.token\n", + "\n", + "obstore_config = {\n", + " \"access_key_id\": creds.access_key,\n", + " \"secret_access_key\": creds.secret_key,\n", + " \"endpoint\": \"https://eodata.dataspace.copernicus.eu\", # Required for CDSE\n", + " \"virtual_hosted_style_request\": \"false\",\n", + " \"region\": session.region_name or \"default\",\n", + "}\n", + "\n", + "if creds.token:\n", + " obstore_config[\"token\"] = creds.token\n", + "\n", + "\n", + "\n", + "PARQUET = \"items.parquet\"\n", + "items = await rustac.search(\n", + " # PARQUET,\n", + " href=\"https://stac.dataspace.copernicus.eu/v1/\",\n", + " collections=[\"clms_lst_global_3km_hourly_v3_cog\"],\n", + " datetime=\"2021-03-27\",\n", + " bbox=list(geobox.boundingbox.to_crs(4326)),\n", + " limit=1,\n", + " )\n", + "\n", + "store = S3Store(\n", + " bucket=\"eodata\",\n", + " config=obstore_config,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "d51b197b", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " Size: 161MB\n", + "array([[[-9999, -9999, -9999, ..., -9999, -9999, -9999],\n", + " [-9999, -9999, -9999, ..., -9999, -9999, -9999],\n", + " [-9999, -9999, -9999, ..., -9999, -9999, -9999],\n", + " ...,\n", + " [-9999, -9999, -9999, ..., -9999, -9999, -9999],\n", + " [-9999, -9999, -9999, ..., -9999, -9999, -9999],\n", + " [-9999, -9999, -9999, ..., -9999, -9999, -9999]]],\n", + " shape=(1, 5601, 14400), dtype=int16)\n", + "Coordinates:\n", + " * band (band) int64 8B 1\n", + " * y (y) float64 45kB 70.0 69.97 69.95 69.92 ... -69.95 -69.98 -70.0\n", + " * x (x) float64 115kB -180.0 -180.0 -179.9 ... 179.9 180.0 180.0\n", + " spatial_ref int64 8B 0\n", + "Indexes:\n", + " ┌ x RasterIndex (crs=EPSG:4326)\n", + " └ y\n", + "Attributes:\n", + " grid_mapping: spatial_ref\n", + " _FillValue: -9999.0\n", + " scale_factor: 0.01\n", + " add_offset: 273.15" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from async_geotiff import GeoTIFF\n", + "from urllib.parse import urlparse\n", + "\n", + "def strip_bucket(href: str) -> str:\n", + " # href: https://data.lpdaac.earthdatacloud.nasa.gov/lp-prod-protected/path/to/file.tif\n", + " # store is rooted at the bucket, so the path is just path/to/file.tif\n", + " return urlparse(href).path.lstrip(\"/\").removeprefix(\"eodata/\")\n", + "\n", + "\n", + "\n", + "lazycogs.open_cog(strip_bucket(items[0][\"assets\"][\"lst_lst\"][\"href\"]), store=store)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "dde80bbe", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv (3.12.2.final.0)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.2" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/tests/test_single.py b/tests/test_single.py new file mode 100644 index 0000000..956e9fa --- /dev/null +++ b/tests/test_single.py @@ -0,0 +1,50 @@ +"""Tests for open_cog: single-COG reads at native resolution.""" + +from __future__ import annotations + +import numpy as np +import pytest +from obstore.store import LocalStore +from pyproj import CRS + +import lazycogs + + +@pytest.fixture +def native_da(synthetic_cog): + """Open the synthetic COG at native resolution via a local obstore store.""" + store = LocalStore() + return lazycogs.open_cog(synthetic_cog.as_uri(), store=store) + + +def test_native_shape_matches_source(native_da): + """No reprojection: output keeps the COG's 2048 x 2048 native shape.""" + assert native_da.dims == ("band", "y", "x") + assert native_da.sizes == {"band": 1, "y": 2048, "x": 2048} + + +def test_native_crs_preserved(native_da): + """The native UTM 32N CRS is preserved, not reprojected.""" + crs = CRS.from_wkt(native_da["spatial_ref"].attrs["crs_wkt"]) + assert crs.to_epsg() == 32632 + + +def test_native_resolution_preserved(native_da): + """Native 10 m pixel size is preserved on both axes.""" + x = native_da["x"].to_numpy() + y = native_da["y"].to_numpy() + assert np.isclose(abs(x[1] - x[0]), 10.0) + assert np.isclose(abs(y[1] - y[0]), 10.0) + + +def test_nodata_advertised_as_fillvalue(native_da): + """Source nodata of 0 is surfaced as _FillValue, grid_mapping is set.""" + assert native_da.attrs["_FillValue"] == 0 + assert native_da.attrs["grid_mapping"] == "spatial_ref" + + +def test_values_loaded(native_da): + """Pixel values are read eagerly and finite.""" + data = native_da.to_numpy() + assert data.shape == (1, 2048, 2048) + assert data.max() > 0 From cbf7350949931306fafce14c13f05665067759dd Mon Sep 17 00:00:00 2001 From: Jonas Berhin Date: Mon, 13 Jul 2026 16:00:23 +0200 Subject: [PATCH 2/8] Refactor synthetic COG generation and enhance test coverage - Introduced a new helper function `_write_synthetic_cog` to streamline the creation of synthetic COGs with customizable parameters such as size, native resolution, and band count. - Updated the `synthetic_cog` fixture to utilize the new helper function, maintaining the original properties while allowing for more flexibility. - Introduction open_item - Undo lock and pyproject changes --- ARCHITECTURE.md | 1 + README.md | 29 + pyproject.toml | 5 +- src/lazycogs/__init__.py | 9 +- src/lazycogs/_core.py | 26 +- src/lazycogs/_single.py | 243 ++++-- test.ipynb | 1532 +++++++++++++++++++++++++++++++++++++- tests/conftest.py | 131 +++- tests/test_single.py | 87 +++ uv.lock | 2 +- 10 files changed, 1969 insertions(+), 96 deletions(-) diff --git a/ARCHITECTURE.md b/ARCHITECTURE.md index 709ca89..af1203f 100644 --- a/ARCHITECTURE.md +++ b/ARCHITECTURE.md @@ -14,6 +14,7 @@ src/lazycogs/ _grid.py output affine transform and grid dimensions _reproject.py warp-map computation and nearest-neighbor sampling _storage_ext.py STAC Storage Extension metadata parsing + _single.py open_cog()/open_item(): native-resolution single-COG and single-item reads _store.py HREF-to-store resolution and store_for() _temporal.py temporal grouping strategies and _TimeStep predicates _mosaic_methods.py pixel-selection strategies diff --git a/README.md b/README.md index 5c02cdc..08da4d9 100644 --- a/README.md +++ b/README.md @@ -83,6 +83,35 @@ da = lazycogs.open( ) ``` +### Single COG and single item reads + +Sometimes you don't want a reprojected mosaic — you want to read one asset (or +a few bands of one item) exactly as stored. `lazycogs.open_cog` and +`lazycogs.open_item` read COGs **at their native grid** (native CRS, resolution, +and shape, no reprojection), returning eagerly-loaded `(band, y, x)` DataArrays +with the same rioxarray-compatible metadata as `lazycogs.open`. + +```python +import lazycogs + +# One COG → (band, y, x) at native resolution, band labelled 1..N. +da = lazycogs.open_cog("s3://bucket/scene/B04.tif") + +# Several same-grid assets of one STAC item, stacked and labelled by asset key. +# `item` is a STAC item dict (e.g. a rustac search result) or a pystac Item. +da = lazycogs.open_item(item, bands=["B04", "B08"]) +# da.dims == ("band", "y", "x"); da["band"] == ["B04", "B08"] +``` + +`open_item` requires every selected asset to be a single-band COG sharing the +same native grid (CRS, resolution, extent); it raises a `ValueError` otherwise. +`nodata`/`scale`/`offset` are read from each asset file and surfaced as scalar +CF attributes (`_FillValue`/`scale_factor`/`add_offset`) only when all selected +bands agree. For assets at differing resolutions, or to mosaic across a whole +collection, use `lazycogs.open` instead. Both functions accept the same +`store=`/`path_from_href=` arguments as `lazycogs.open`, and each has an +`await`-able `_async` variant (`open_cog_async`, `open_item_async`). + ### Temporal grouping By default, `lazycogs.open()` groups items into one time step per calendar day (`time_period="P1D"`). You can also request coarser composites with `"PnD"`, `"P1W"`, `"P1M"`, or `"P1Y"`. diff --git a/pyproject.toml b/pyproject.toml index c548e24..43b2756 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -58,9 +58,6 @@ dev = [ "pre-commit>=4.6.0", "ruff>=0.15.12", "rioxarray>=0.22.0", - "odc-geo>=0.5.1", - "boto3>=1.43.36", - "rustac>=0.9.13", ] docs = [ "mkdocs-jupyter>=0.26.2", @@ -118,4 +115,4 @@ addopts = "-vv --benchmark-disable --ignore=tests/benchmarks" python_files = ["test_*.py", "bench_*.py"] markers = [ "benchmark: performance benchmarks (run with --benchmark-enable)", -] +] \ No newline at end of file diff --git a/src/lazycogs/__init__.py b/src/lazycogs/__init__.py index a875ff1..9625206 100644 --- a/src/lazycogs/__init__.py +++ b/src/lazycogs/__init__.py @@ -20,7 +20,12 @@ MosaicMethodBase, StdevMethod, ) -from lazycogs._single import open_cog, open_cog_async +from lazycogs._single import ( + open_cog, + open_cog_async, + open_item, + open_item_async, +) from lazycogs._store import store_for __all__ = [ @@ -40,6 +45,8 @@ "open", "open_cog", "open_cog_async", + "open_item", + "open_item_async", "read_chunk_async", "run_on_loop", "store_for", diff --git a/src/lazycogs/_core.py b/src/lazycogs/_core.py index e6432de..dcaabcc 100644 --- a/src/lazycogs/_core.py +++ b/src/lazycogs/_core.py @@ -27,6 +27,7 @@ if TYPE_CHECKING: from collections.abc import Callable + from affine import Affine from arro3.core import Table from async_geotiff import Store @@ -367,6 +368,19 @@ def _spatial_coords_with_eager_variables(index: RasterIndex) -> Coordinates: ) +def _spatial_ref_dataarray(crs: CRS, transform: Affine) -> DataArray: + """Return the scalar ``spatial_ref`` grid-mapping variable for a grid.""" + crs_wkt = crs.to_wkt() + return DataArray( + np.array(0), + attrs={ + "crs_wkt": crs_wkt, + "spatial_ref": crs_wkt, + "GeoTransform": " ".join(str(v) for v in transform.to_gdal()), + }, + ) + + def _build_dataarray( *, parquet_path: str, @@ -454,17 +468,7 @@ def _build_dataarray( dst_affine.e, dst_affine.f, ] - gdal_transform = dst_affine.to_gdal() - crs_wkt = dst_crs.to_wkt() - - spatial_ref = DataArray( - np.array(0), - attrs={ - "crs_wkt": crs_wkt, - "spatial_ref": crs_wkt, - "GeoTransform": " ".join(str(v) for v in gdal_transform), - }, - ) + spatial_ref = _spatial_ref_dataarray(dst_crs, dst_affine) attributes = { "grid_mapping": "spatial_ref", diff --git a/src/lazycogs/_single.py b/src/lazycogs/_single.py index 4f547fb..16ddcda 100644 --- a/src/lazycogs/_single.py +++ b/src/lazycogs/_single.py @@ -1,45 +1,66 @@ -"""Open a single COG at its native grid as an xarray DataArray. +"""Open a single COG or STAC item at native grid as an xarray DataArray. Unlike :func:`lazycogs.open`, which mosaics a whole STAC/geoparquet -collection onto a caller-defined output grid, this module reads one -Cloud-Optimized GeoTIFF in place: native CRS, native resolution, native -shape, no reprojection. It is the obstore-backed analogue of -``rioxarray.open_rasterio`` for a single asset. +collection onto a caller-defined output grid, this module reads assets in +place: native CRS, native resolution, native shape, no reprojection. + +- :func:`open_cog` reads one Cloud-Optimized GeoTIFF — the obstore-backed + analogue of ``rioxarray.open_rasterio`` for a single asset. +- :func:`open_item` reads several assets of a single STAC item that share the + same native grid and stacks them into one ``(band, y, x)`` DataArray whose + ``band`` coordinate is labelled by asset key. """ from __future__ import annotations -from typing import TYPE_CHECKING +import asyncio +from typing import TYPE_CHECKING, Any -import numpy as np from async_geotiff import GeoTIFF from pyproj import CRS from rasterix import RasterIndex -from xarray import Coordinates, DataArray +from xarray import Coordinates, DataArray, concat -from lazycogs._core import _spatial_coords_with_eager_variables +from lazycogs._core import ( + _ordered_bands, + _spatial_coords_with_eager_variables, + _spatial_ref_dataarray, +) from lazycogs._executor import run_on_loop from lazycogs._store import resolve if TYPE_CHECKING: from collections.abc import Callable - from async_geotiff import Store + from async_geotiff import RasterArray, Store -__all__ = ["open_cog", "open_cog_async"] +__all__ = ["open_cog", "open_cog_async", "open_item", "open_item_async"] -def _build_cog_dataarray(geotiff: GeoTIFF, raster: object) -> DataArray: - """Wrap a native-resolution read in a rioxarray-compatible DataArray. +def _cf_attrs(geotiff: GeoTIFF) -> dict[str, object]: + """Return CF/rioxarray attrs, attaching only ones that carry meaning.""" + attrs: dict[str, object] = {"grid_mapping": "spatial_ref"} + if geotiff.nodata is not None: + attrs["_FillValue"] = geotiff.nodata + scale = geotiff.scales[0] if geotiff.scales else 1.0 + offset = geotiff.offsets[0] if geotiff.offsets else 0.0 + if scale != 1.0: + attrs["scale_factor"] = scale + if offset != 0.0: + attrs["add_offset"] = offset + return attrs - Args: - geotiff: The opened GeoTIFF, used for ``scales``/``offsets``/``nodata``. - raster: The result of ``geotiff.read()`` with ``data`` (shape - ``(band, y, x)``), ``transform``, ``crs``, ``width``, ``height``. - Returns: - DataArray with dims ``(band, y, x)`` at the COG's native grid. +def _build_cog_dataarray( + geotiff: GeoTIFF, + raster: RasterArray, + *, + band_coord: list[int | str] | None = None, +) -> DataArray: + """Wrap a native-resolution read in a rioxarray-compatible DataArray. + ``band_coord`` labels the band dimension; it defaults to 1-based integer + band indices and is set to the asset key when stacking a STAC item. """ data = raster.data crs = CRS.from_user_input(raster.crs) @@ -53,37 +74,33 @@ def _build_cog_dataarray(geotiff: GeoTIFF, raster: object) -> DataArray: crs=crs, ) spatial_coords = _spatial_coords_with_eager_variables(index) + spatial_ref = _spatial_ref_dataarray(crs, raster.transform) - crs_wkt = crs.to_wkt() - spatial_ref = DataArray( - np.array(0), - attrs={ - "crs_wkt": crs_wkt, - "spatial_ref": crs_wkt, - "GeoTransform": " ".join(str(v) for v in raster.transform.to_gdal()), - }, - ) - - attrs: dict[str, object] = {"grid_mapping": "spatial_ref"} - if geotiff.nodata is not None: - attrs["_FillValue"] = geotiff.nodata - scale = geotiff.scales[0] if geotiff.scales else 1.0 - offset = geotiff.offsets[0] if geotiff.offsets else 0.0 - if scale != 1.0: - attrs["scale_factor"] = scale - if offset != 0.0: - attrs["add_offset"] = offset - - bands = list(range(1, data.shape[0] + 1)) + bands = band_coord if band_coord is not None else list(range(1, data.shape[0] + 1)) return DataArray( data, dims=("band", "y", "x"), coords=Coordinates({"band": bands, "spatial_ref": spatial_ref}) | spatial_coords, - attrs=attrs, + attrs=_cf_attrs(geotiff), ) +async def _open_asset( + assets: dict[str, Any], + band: str, + *, + store: Store | None, + path_from_href: Callable[[str], str] | None, +) -> GeoTIFF: + """Open the COG backing one asset key of a STAC item.""" + href = assets[band].get("href", "") + if not href: + raise ValueError(f"Asset {band!r} does not have an href.") + resolved_store, path = resolve(href, store=store, path_fn=path_from_href) + return await GeoTIFF.open(path, store=resolved_store) + + async def open_cog_async( href: str, *, @@ -125,7 +142,8 @@ def open_cog( Reads a single Cloud-Optimized GeoTIFF in place — native CRS, resolution, and shape, no reprojection or mosaicking. Use :func:`lazycogs.open` for a - reprojected mosaic across a STAC/geoparquet collection. + reprojected mosaic across a STAC/geoparquet collection, or + :func:`open_item` to stack several same-grid assets of one STAC item. Args: href: Asset URL or path. When ``store`` is ``None``, an obstore-backed @@ -144,3 +162,144 @@ def open_cog( return run_on_loop( open_cog_async(href, store=store, path_from_href=path_from_href), ) + + +def _assets_from_item(item: dict[str, Any]) -> dict[str, Any]: + """Return the ``assets`` mapping from a STAC item dict or pystac Item.""" + if hasattr(item, "to_dict"): + item = item.to_dict() + assets: dict[str, Any] = item.get("assets", {}) + if not assets: + raise ValueError("STAC item has no assets to open.") + return assets + + +async def _read_asset_band( + assets: dict[str, Any], + band: str, + *, + store: Store | None, + path_from_href: Callable[[str], str] | None, +) -> DataArray: + """Open and read one single-band asset as a ``(band, y, x)`` DataArray.""" + geotiff = await _open_asset( + assets, + band, + store=store, + path_from_href=path_from_href, + ) + if geotiff.count != 1: + raise ValueError( + f"Asset {band!r} is a {geotiff.count}-band COG; open_item stacks " + "single-band assets. Use lazycogs.open_cog to read a multi-band COG.", + ) + raster = await geotiff.read() + return _build_cog_dataarray(geotiff, raster, band_coord=[band]) + + +async def open_item_async( + item: dict[str, Any], + bands: list[str] | None = None, + *, + store: Store | None = None, + path_from_href: Callable[[str], str] | None = None, +) -> DataArray: + """Open several same-grid assets of one STAC item as ``(band, y, x)``. + + Async variant of :func:`open_item` for use inside a running event loop. + + Args: + item: A STAC item as a dict (e.g. a ``rustac`` search result) or a + pystac-like object exposing ``to_dict()``. + bands: Asset keys to include, in output order. When ``None``, the + item's preferred data assets are used (role ``"data"`` or media + type ``image/tiff``), matching :func:`lazycogs.open`. + store: Pre-configured :class:`async_geotiff.Store` for all reads. + path_from_href: Optional callable ``(href) -> path`` overriding the + default ``urlparse`` extraction (see :func:`lazycogs.open`). + + Returns: + DataArray at the assets' shared native CRS, resolution, and shape, with + the ``band`` coordinate labelled by asset key. ``nodata``/``scale``/ + ``offset`` are read from each asset file and surfaced as scalar CF + attrs only when all selected bands agree. + + Raises: + ValueError: If the item has no assets, a requested band is missing or + lacks an href, an asset is multi-band, or the selected assets do + not share one native grid. + + """ + assets = _assets_from_item(item) + resolved_bands = _ordered_bands(assets, bands=bands) + if not resolved_bands: + raise ValueError("No assets available to open from the STAC item.") + + arrays = await asyncio.gather( + *[ + _read_asset_band( + assets, + band, + store=store, + path_from_href=path_from_href, + ) + for band in resolved_bands + ], + ) + + # join="exact" rejects assets that are not on one native grid; drop_conflicts + # keeps _FillValue/scale_factor/add_offset only when every band agrees. + try: + return concat(arrays, dim="band", join="exact", combine_attrs="drop_conflicts") + except ValueError as exc: + raise ValueError( + "open_item requires every asset to share one native grid (CRS, " + "resolution, and extent). Use lazycogs.open to mosaic assets that " + "differ.", + ) from exc + + +def open_item( + item: dict[str, Any], + bands: list[str] | None = None, + *, + store: Store | None = None, + path_from_href: Callable[[str], str] | None = None, +) -> DataArray: + """Open several same-grid assets of one STAC item as ``(band, y, x)``. + + Reads the requested single-band assets of one STAC item at their native + grid — no reprojection or mosaicking — and stacks them into a single + DataArray whose ``band`` coordinate is labelled by asset key. All selected + assets must share the same native CRS, resolution, and shape. This is the + multi-band complement to :func:`open_cog`; use :func:`lazycogs.open` for a + reprojected mosaic across a whole collection. + + Args: + item: A STAC item as a dict (e.g. a ``rustac`` search result) or a + pystac-like object exposing ``to_dict()``. + bands: Asset keys to include, in output order. When ``None``, the + item's preferred data assets are used (role ``"data"`` or media + type ``image/tiff``), matching :func:`lazycogs.open`. + store: Pre-configured :class:`async_geotiff.Store` for all reads. + path_from_href: Optional callable ``(href) -> path`` overriding the + default ``urlparse`` extraction (see :func:`lazycogs.open`). + + Returns: + DataArray at the assets' shared native CRS, resolution, and shape, with + the ``band`` coordinate labelled by asset key. + + Raises: + ValueError: If the item has no assets, a requested band is missing or + lacks an href, an asset is multi-band, or the selected assets do + not share one native grid. + + """ + return run_on_loop( + open_item_async( + item, + bands, + store=store, + path_from_href=path_from_href, + ), + ) diff --git a/test.ipynb b/test.ipynb index d52ab2d..2ae0636 100644 --- a/test.ipynb +++ b/test.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 6, + "execution_count": 14, "id": "755b4e97", "metadata": {}, "outputs": [], @@ -14,6 +14,10 @@ "import rustac\n", "from obstore.store import S3Store\n", "\n", + "import os\n", + "\n", + "os.environ[\"AWS_PROFILE\"] = \"cdse\"\n", + "\n", "geobox = GeoBox(\n", " shape=(10, 10),\n", " affine=Affine(5000.0, 0.0, 690400.0, 0.0, -5000.0, 4660400.0),\n", @@ -67,7 +71,23 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, + "id": "088c1426", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4719d475", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, "id": "d51b197b", "metadata": {}, "outputs": [ @@ -637,18 +657,18 @@ " grid_mapping: spatial_ref\n", " _FillValue: -9999.0\n", " scale_factor: 0.01\n", - " add_offset: 273.15
  • grid_mapping :
    spatial_ref
    _FillValue :
    -9999.0
    scale_factor :
    0.01
    add_offset :
    273.15
    • " ], "text/plain": [ " Size: 161MB\n", @@ -675,7 +695,7 @@ " add_offset: 273.15" ] }, - "execution_count": 7, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } @@ -691,21 +711,1511 @@ "\n", "\n", "\n", - "lazycogs.open_cog(strip_bucket(items[0][\"assets\"][\"lst_lst\"][\"href\"]), store=store)" + "await lazycogs.open_cog(strip_bucket(items[0][\"assets\"][\"lst_lst\"][\"href\"]), store=store)" ] }, { "cell_type": "code", "execution_count": null, + "id": "9f557dd2", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fdb9e57b", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0da22527", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6de3087e", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "8b1be7a4", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'Product': {'href': 'https://download.dataspace.copernicus.eu/odata/v1/Products(db6d312c-12bf-49f8-9fec-424bf08a4ffb)/$value',\n", + " 'file:size': 25720143,\n", + " 'file:checksum': 'd50110dcddac5dc58d26bddaa50e251a6f5d1c',\n", + " 'file:local_path': 'c_gls_LST_202103272300_GLOBE_GEO_V3.0.1_cog.zip',\n", + " 'type': 'application/zip',\n", + " 'roles': ['data', 'metadata', 'archive'],\n", + " 'title': 'Zipped product',\n", + " 'auth:refs': ['oidc']},\n", + " 'lst_lst': {'href': 's3://eodata/CLMS/bio-geophysical/land_surface_temperature/lst_global_3km_hourly_v3/2021/03/27/c_gls_LST_202103272300_GLOBE_GEO_V3.0.1_cog/c_gls_LST-LST_202103272300_GLOBE_GEO_V3.0.1.tiff',\n", + " 'alternate': {'https': {'href': 'https://download.dataspace.copernicus.eu/odata/v1/Products(db6d312c-12bf-49f8-9fec-424bf08a4ffb)/Nodes(c_gls_LST_202103272300_GLOBE_GEO_V3.0.1_cog)/Nodes(c_gls_LST-LST_202103272300_GLOBE_GEO_V3.0.1.tiff)/$value',\n", + " 'auth:refs': ['oidc'],\n", + " 'storage:refs': [],\n", + " 'alternate:name': 'HTTPS'}},\n", + " 'file:size': 14369966,\n", + " 'proj:shape': [5601, 14400],\n", + " 'file:checksum': 'd5011030da76f45348000f8c1ed5d4f3943b99',\n", + " 'proj:transform': [0.025, 0.0, -180.01250000000002, 0.0, -0.025, 70.0125],\n", + " 'file:local_path': 'c_gls_LST_202103272300_GLOBE_GEO_V3.0.1_cog/c_gls_LST-LST_202103272300_GLOBE_GEO_V3.0.1.tiff',\n", + " 'type': 'image/tiff; application=geotiff; profile=cloud-optimized',\n", + " 'bands': [{'name': 'lst', 'description': 'Land Surface Temperature'}],\n", + " 'roles': ['data'],\n", + " 'title': 'Land Surface Temperature',\n", + " 'nodata': -9999,\n", + " 'auth:refs': ['s3'],\n", + " 'data_type': 'int16',\n", + " 'raster:scale': 0.01,\n", + " 'storage:refs': ['cdse-s3', 'creodias-s3'],\n", + " 'raster:offset': 273.15,\n", + " 'alternate:name': 'S3'},\n", + " 'lst_qflag': {'href': 's3://eodata/CLMS/bio-geophysical/land_surface_temperature/lst_global_3km_hourly_v3/2021/03/27/c_gls_LST_202103272300_GLOBE_GEO_V3.0.1_cog/c_gls_LST-QFLAG_202103272300_GLOBE_GEO_V3.0.1.tiff',\n", + " 'bands': [{'name': 'qflag',\n", + " 'description': 'Quality Flag on Land Surface Temperature'}],\n", + " 'alternate': {'https': {'href': 'https://download.dataspace.copernicus.eu/odata/v1/Products(db6d312c-12bf-49f8-9fec-424bf08a4ffb)/Nodes(c_gls_LST_202103272300_GLOBE_GEO_V3.0.1_cog)/Nodes(c_gls_LST-QFLAG_202103272300_GLOBE_GEO_V3.0.1.tiff)/$value',\n", + " 'auth:refs': ['oidc'],\n", + " 'storage:refs': [],\n", + " 'alternate:name': 'HTTPS'}},\n", + " 'file:size': 1602881,\n", + " 'proj:shape': [5601, 14400],\n", + " 'file:checksum': 'd501101f71f56f35eae37caa15cd474e1de39d',\n", + " 'proj:transform': [0.025, 0.0, -180.01250000000002, 0.0, -0.025, 70.0125],\n", + " 'file:local_path': 'c_gls_LST_202103272300_GLOBE_GEO_V3.0.1_cog/c_gls_LST-QFLAG_202103272300_GLOBE_GEO_V3.0.1.tiff',\n", + " 'type': 'image/tiff; application=geotiff; profile=cloud-optimized',\n", + " 'roles': ['data'],\n", + " 'title': 'Quality Flag on Land Surface Temperature',\n", + " 'nodata': -9999,\n", + " 'auth:refs': ['s3'],\n", + " 'data_type': 'int16',\n", + " 'storage:refs': ['cdse-s3', 'creodias-s3'],\n", + " 'alternate:name': 'S3'},\n", + " 'lst_tdelta': {'href': 's3://eodata/CLMS/bio-geophysical/land_surface_temperature/lst_global_3km_hourly_v3/2021/03/27/c_gls_LST_202103272300_GLOBE_GEO_V3.0.1_cog/c_gls_LST-TDELTA_202103272300_GLOBE_GEO_V3.0.1.tiff',\n", + " 'alternate': {'https': {'href': 'https://download.dataspace.copernicus.eu/odata/v1/Products(db6d312c-12bf-49f8-9fec-424bf08a4ffb)/Nodes(c_gls_LST_202103272300_GLOBE_GEO_V3.0.1_cog)/Nodes(c_gls_LST-TDELTA_202103272300_GLOBE_GEO_V3.0.1.tiff)/$value',\n", + " 'auth:refs': ['oidc'],\n", + " 'storage:refs': [],\n", + " 'alternate:name': 'HTTPS'}},\n", + " 'file:size': 1212769,\n", + " 'proj:shape': [5601, 14400],\n", + " 'file:checksum': 'd5011092cf24980c8e71190b7aeb2f024ddd36',\n", + " 'proj:transform': [0.025, 0.0, -180.01250000000002, 0.0, -0.025, 70.0125],\n", + " 'file:local_path': 'c_gls_LST_202103272300_GLOBE_GEO_V3.0.1_cog/c_gls_LST-TDELTA_202103272300_GLOBE_GEO_V3.0.1.tiff',\n", + " 'type': 'image/tiff; application=geotiff; profile=cloud-optimized',\n", + " 'bands': [{'name': 'tdelta',\n", + " 'description': 'Time delta between observation and reference time on Land Surface Temperature'}],\n", + " 'roles': ['data'],\n", + " 'title': 'Time delta between observation and reference time on Land Surface Temperature',\n", + " 'nodata': -9999,\n", + " 'auth:refs': ['s3'],\n", + " 'data_type': 'int16',\n", + " 'storage:refs': ['cdse-s3', 'creodias-s3'],\n", + " 'alternate:name': 'S3'},\n", + " 'lst_errorbar': {'href': 's3://eodata/CLMS/bio-geophysical/land_surface_temperature/lst_global_3km_hourly_v3/2021/03/27/c_gls_LST_202103272300_GLOBE_GEO_V3.0.1_cog/c_gls_LST-ERRORBAR_202103272300_GLOBE_GEO_V3.0.1.tiff',\n", + " 'alternate': {'https': {'href': 'https://download.dataspace.copernicus.eu/odata/v1/Products(db6d312c-12bf-49f8-9fec-424bf08a4ffb)/Nodes(c_gls_LST_202103272300_GLOBE_GEO_V3.0.1_cog)/Nodes(c_gls_LST-ERRORBAR_202103272300_GLOBE_GEO_V3.0.1.tiff)/$value',\n", + " 'auth:refs': ['oidc'],\n", + " 'storage:refs': [],\n", + " 'alternate:name': 'HTTPS'}},\n", + " 'file:size': 8533381,\n", + " 'proj:shape': [5601, 14400],\n", + " 'file:checksum': 'd50110df1a561b607ae0c69ad7915c21dbb17a',\n", + " 'proj:transform': [0.025, 0.0, -180.01250000000002, 0.0, -0.025, 70.0125],\n", + " 'file:local_path': 'c_gls_LST_202103272300_GLOBE_GEO_V3.0.1_cog/c_gls_LST-ERRORBAR_202103272300_GLOBE_GEO_V3.0.1.tiff',\n", + " 'type': 'image/tiff; application=geotiff; profile=cloud-optimized',\n", + " 'bands': [{'name': 'errorbar',\n", + " 'description': 'Standard error on Land Surface Temperature'}],\n", + " 'roles': ['data'],\n", + " 'title': 'Standard error on Land Surface Temperature',\n", + " 'nodata': -9999,\n", + " 'auth:refs': ['s3'],\n", + " 'data_type': 'int16',\n", + " 'raster:scale': 0.01,\n", + " 'storage:refs': ['cdse-s3', 'creodias-s3'],\n", + " 'alternate:name': 'S3'}}" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "items[0][\"assets\"]" + ] + }, + { + "cell_type": "code", + "execution_count": 8, "id": "dde80bbe", "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
    \n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "
    <xarray.DataArray (band: 2, y: 5601, x: 14400)> Size: 323MB\n",
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    " + ], + "text/plain": [ + " Size: 323MB\n", + "array([[[-9999, -9999, -9999, ..., -9999, -9999, -9999],\n", + " [-9999, -9999, -9999, ..., -9999, -9999, -9999],\n", + " [-9999, -9999, -9999, ..., -9999, -9999, -9999],\n", + " ...,\n", + " [-9999, -9999, -9999, ..., -9999, -9999, -9999],\n", + " [-9999, -9999, -9999, ..., -9999, -9999, -9999],\n", + " [-9999, -9999, -9999, ..., -9999, -9999, -9999]],\n", + "\n", + " [[ 0, 0, 0, ..., 0, 0, 0],\n", + " [ 0, 0, 0, ..., 0, 0, 0],\n", + " [ 0, 0, 0, ..., 0, 0, 0],\n", + " ...,\n", + " [ 0, 0, 0, ..., 0, 0, 0],\n", + " [ 0, 0, 0, ..., 0, 0, 0],\n", + " [ 0, 0, 0, ..., 0, 0, 0]]],\n", + " shape=(2, 5601, 14400), dtype=int16)\n", + "Coordinates:\n", + " * band (band) \u001b[39m\u001b[32m17\u001b[39m da = lazycogs.open_item(items[\u001b[32m0\u001b[39m], bands=[\u001b[33m\"red\"\u001b[39m, \u001b[33m\"green\"\u001b[39m, \u001b[33m\"blue\"\u001b[39m, \u001b[33m\"nir\"\u001b[39m])\n\u001b[32m 18\u001b[39m \n\u001b[32m 19\u001b[39m print(da.dims, dict(da.sizes)) \u001b[38;5;66;03m# ('band', 'y', 'x') {'band': 4, 'y': 10980, 'x': 10980}\u001b[39;00m\n\u001b[32m 20\u001b[39m print(da[\u001b[33m\"band\"\u001b[39m].values) \u001b[38;5;66;03m# ['red' 'green' 'blue' 'nir']\u001b[39;00m\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/lazycogs/src/lazycogs/_single.py:298\u001b[39m, in \u001b[36mopen_item\u001b[39m\u001b[34m(item, bands, store, path_from_href)\u001b[39m\n\u001b[32m 262\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34mopen_item\u001b[39m(\n\u001b[32m 263\u001b[39m item: \u001b[38;5;28mdict\u001b[39m[\u001b[38;5;28mstr\u001b[39m, Any],\n\u001b[32m 264\u001b[39m bands: \u001b[38;5;28mlist\u001b[39m[\u001b[38;5;28mstr\u001b[39m] | \u001b[38;5;28;01mNone\u001b[39;00m = \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[32m (...)\u001b[39m\u001b[32m 267\u001b[39m path_from_href: Callable[[\u001b[38;5;28mstr\u001b[39m], \u001b[38;5;28mstr\u001b[39m] | \u001b[38;5;28;01mNone\u001b[39;00m = \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[32m 268\u001b[39m ) -> DataArray:\n\u001b[32m 269\u001b[39m \u001b[38;5;250m \u001b[39m\u001b[33;03m\"\"\"Open several same-grid assets of one STAC item as ``(band, y, x)``.\u001b[39;00m\n\u001b[32m 270\u001b[39m \n\u001b[32m 271\u001b[39m \u001b[33;03m Reads the requested single-band assets of one STAC item at their native\u001b[39;00m\n\u001b[32m (...)\u001b[39m\u001b[32m 296\u001b[39m \n\u001b[32m 297\u001b[39m \u001b[33;03m \"\"\"\u001b[39;00m\n\u001b[32m--> \u001b[39m\u001b[32m298\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[30;43mrun_on_loop\u001b[39;49m\u001b[30;43m(\u001b[39;49m\n\u001b[32m 299\u001b[39m \u001b[30;43m \u001b[39;49m\u001b[30;43mopen_item_async\u001b[39;49m\u001b[30;43m(\u001b[39;49m\n\u001b[32m 300\u001b[39m \u001b[30;43m \u001b[39;49m\u001b[30;43mitem\u001b[39;49m\u001b[30;43m,\u001b[39;49m\n\u001b[32m 301\u001b[39m \u001b[30;43m \u001b[39;49m\u001b[30;43mbands\u001b[39;49m\u001b[30;43m,\u001b[39;49m\n\u001b[32m 302\u001b[39m \u001b[30;43m \u001b[39;49m\u001b[30;43mstore\u001b[39;49m\u001b[30;43m=\u001b[39;49m\u001b[30;43mstore\u001b[39;49m\u001b[30;43m,\u001b[39;49m\n\u001b[32m 303\u001b[39m \u001b[30;43m \u001b[39;49m\u001b[30;43mpath_from_href\u001b[39;49m\u001b[30;43m=\u001b[39;49m\u001b[30;43mpath_from_href\u001b[39;49m\u001b[30;43m,\u001b[39;49m\n\u001b[32m 304\u001b[39m \u001b[30;43m \u001b[39;49m\u001b[30;43m)\u001b[39;49m\u001b[30;43m,\u001b[39;49m\n\u001b[32m 305\u001b[39m \u001b[30;43m \u001b[39;49m\u001b[30;43m)\u001b[39;49m\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/lazycogs/src/lazycogs/_executor.py:174\u001b[39m, in \u001b[36mrun_on_loop\u001b[39m\u001b[34m(coro)\u001b[39m\n\u001b[32m 167\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34mrun_on_loop\u001b[39m[T](coro: Coroutine[\u001b[38;5;28mobject\u001b[39m, \u001b[38;5;28mobject\u001b[39m, T]) -> T:\n\u001b[32m 168\u001b[39m \u001b[38;5;250m \u001b[39m\u001b[33;03m\"\"\"Run ``coro`` on the shared lazycogs event loop and return its result.\u001b[39;00m\n\u001b[32m 169\u001b[39m \n\u001b[32m 170\u001b[39m \u001b[33;03m This is the supported helper for sync code that must execute a coroutine on\u001b[39;00m\n\u001b[32m 171\u001b[39m \u001b[33;03m the lazycogs background loop, including callers that need to construct\u001b[39;00m\n\u001b[32m 172\u001b[39m \u001b[33;03m loop-bound resources on that loop.\u001b[39;00m\n\u001b[32m 173\u001b[39m \u001b[33;03m \"\"\"\u001b[39;00m\n\u001b[32m--> \u001b[39m\u001b[32m174\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[30;43m_submit_to_loop\u001b[39;49m\u001b[30;43m(\u001b[39;49m\u001b[30;43mcoro\u001b[39;49m\u001b[30;43m)\u001b[39;49m\u001b[30;43m.\u001b[39;49m\u001b[30;43mresult\u001b[39;49m\u001b[30;43m(\u001b[39;49m\u001b[30;43m)\u001b[39;49m\n", + "\u001b[36mFile \u001b[39m\u001b[32m/opt/homebrew/Cellar/python@3.13/3.13.3/Frameworks/Python.framework/Versions/3.13/lib/python3.13/concurrent/futures/_base.py:456\u001b[39m, in \u001b[36mFuture.result\u001b[39m\u001b[34m(self, timeout)\u001b[39m\n\u001b[32m 454\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m CancelledError()\n\u001b[32m 455\u001b[39m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28mself\u001b[39m._state == FINISHED:\n\u001b[32m--> \u001b[39m\u001b[32m456\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[30;43mself\u001b[39;49m\u001b[30;43m.\u001b[39;49m\u001b[30;43m__get_result\u001b[39;49m\u001b[30;43m(\u001b[39;49m\u001b[30;43m)\u001b[39;49m\n\u001b[32m 457\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m 458\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTimeoutError\u001b[39;00m()\n", + "\u001b[36mFile \u001b[39m\u001b[32m/opt/homebrew/Cellar/python@3.13/3.13.3/Frameworks/Python.framework/Versions/3.13/lib/python3.13/concurrent/futures/_base.py:401\u001b[39m, in \u001b[36mFuture.__get_result\u001b[39m\u001b[34m(self)\u001b[39m\n\u001b[32m 399\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m._exception:\n\u001b[32m 400\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m401\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;28mself\u001b[39m._exception\n\u001b[32m 402\u001b[39m \u001b[38;5;28;01mfinally\u001b[39;00m:\n\u001b[32m 403\u001b[39m \u001b[38;5;66;03m# Break a reference cycle with the exception in self._exception\u001b[39;00m\n\u001b[32m 404\u001b[39m \u001b[38;5;28mself\u001b[39m = \u001b[38;5;28;01mNone\u001b[39;00m\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/lazycogs/src/lazycogs/_single.py:238\u001b[39m, in \u001b[36mopen_item_async\u001b[39m\u001b[34m(item, bands, store, path_from_href)\u001b[39m\n\u001b[32m 235\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m resolved_bands:\n\u001b[32m 236\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[33m\"\u001b[39m\u001b[33mNo assets available to open from the STAC item.\u001b[39m\u001b[33m\"\u001b[39m)\n\u001b[32m--> \u001b[39m\u001b[32m238\u001b[39m arrays = \u001b[38;5;28;01mawait\u001b[39;00m asyncio.gather(\n\u001b[32m 239\u001b[39m *[\n\u001b[32m 240\u001b[39m _read_asset_band(\n\u001b[32m 241\u001b[39m assets,\n\u001b[32m 242\u001b[39m band,\n\u001b[32m 243\u001b[39m store=store,\n\u001b[32m 244\u001b[39m path_from_href=path_from_href,\n\u001b[32m 245\u001b[39m )\n\u001b[32m 246\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m band \u001b[38;5;129;01min\u001b[39;00m resolved_bands\n\u001b[32m 247\u001b[39m ],\n\u001b[32m 248\u001b[39m )\n\u001b[32m 250\u001b[39m \u001b[38;5;66;03m# join=\"exact\" rejects assets that are not on one native grid; drop_conflicts\u001b[39;00m\n\u001b[32m 251\u001b[39m \u001b[38;5;66;03m# keeps _FillValue/scale_factor/add_offset only when every band agrees.\u001b[39;00m\n\u001b[32m 252\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/lazycogs/src/lazycogs/_single.py:185\u001b[39m, in \u001b[36m_read_asset_band\u001b[39m\u001b[34m(assets, band, store, path_from_href)\u001b[39m\n\u001b[32m 177\u001b[39m \u001b[38;5;28;01masync\u001b[39;00m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34m_read_asset_band\u001b[39m(\n\u001b[32m 178\u001b[39m assets: \u001b[38;5;28mdict\u001b[39m[\u001b[38;5;28mstr\u001b[39m, Any],\n\u001b[32m 179\u001b[39m band: \u001b[38;5;28mstr\u001b[39m,\n\u001b[32m (...)\u001b[39m\u001b[32m 182\u001b[39m path_from_href: Callable[[\u001b[38;5;28mstr\u001b[39m], \u001b[38;5;28mstr\u001b[39m] | \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[32m 183\u001b[39m ) -> DataArray:\n\u001b[32m 184\u001b[39m \u001b[38;5;250m \u001b[39m\u001b[33;03m\"\"\"Open and read one single-band asset as a ``(band, y, x)`` DataArray.\"\"\"\u001b[39;00m\n\u001b[32m--> \u001b[39m\u001b[32m185\u001b[39m geotiff = \u001b[38;5;28;01mawait\u001b[39;00m _open_asset(\n\u001b[32m 186\u001b[39m assets,\n\u001b[32m 187\u001b[39m band,\n\u001b[32m 188\u001b[39m store=store,\n\u001b[32m 189\u001b[39m path_from_href=path_from_href,\n\u001b[32m 190\u001b[39m )\n\u001b[32m 191\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m geotiff.count != \u001b[32m1\u001b[39m:\n\u001b[32m 192\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[32m 193\u001b[39m \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mAsset \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mband\u001b[38;5;132;01m!r}\u001b[39;00m\u001b[33m is a \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mgeotiff.count\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m-band COG; open_item stacks \u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 194\u001b[39m \u001b[33m\"\u001b[39m\u001b[33msingle-band assets. Use lazycogs.open_cog to read a multi-band COG.\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m 195\u001b[39m )\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/lazycogs/src/lazycogs/_single.py:101\u001b[39m, in \u001b[36m_open_asset\u001b[39m\u001b[34m(assets, band, store, path_from_href)\u001b[39m\n\u001b[32m 99\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mAsset \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mband\u001b[38;5;132;01m!r}\u001b[39;00m\u001b[33m does not have an href.\u001b[39m\u001b[33m\"\u001b[39m)\n\u001b[32m 100\u001b[39m resolved_store, path = resolve(href, store=store, path_fn=path_from_href)\n\u001b[32m--> \u001b[39m\u001b[32m101\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mawait\u001b[39;00m GeoTIFF.open(path, store=resolved_store)\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/lazycogs/.venv/lib/python3.13/site-packages/async_geotiff/_geotiff.py:236\u001b[39m, in \u001b[36mGeoTIFF.open\u001b[39m\u001b[34m(cls, path, store, prefetch, multiplier)\u001b[39m\n\u001b[32m 206\u001b[39m \u001b[38;5;129m@classmethod\u001b[39m\n\u001b[32m 207\u001b[39m \u001b[38;5;28;01masync\u001b[39;00m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34mopen\u001b[39m(\n\u001b[32m 208\u001b[39m \u001b[38;5;28mcls\u001b[39m,\n\u001b[32m (...)\u001b[39m\u001b[32m 213\u001b[39m multiplier: \u001b[38;5;28mfloat\u001b[39m = \u001b[32m2.0\u001b[39m,\n\u001b[32m 214\u001b[39m ) -> Self:\n\u001b[32m 215\u001b[39m \u001b[38;5;250m \u001b[39m\u001b[33;03m\"\"\"Open a new GeoTIFF.\u001b[39;00m\n\u001b[32m 216\u001b[39m \n\u001b[32m 217\u001b[39m \u001b[33;03m Args:\u001b[39;00m\n\u001b[32m (...)\u001b[39m\u001b[32m 234\u001b[39m \n\u001b[32m 235\u001b[39m \u001b[33;03m \"\"\"\u001b[39;00m\n\u001b[32m--> \u001b[39m\u001b[32m236\u001b[39m tiff = \u001b[38;5;28;01mawait\u001b[39;00m TIFF.open(\n\u001b[32m 237\u001b[39m path=path,\n\u001b[32m 238\u001b[39m store=store,\n\u001b[32m 239\u001b[39m prefetch=prefetch,\n\u001b[32m 240\u001b[39m multiplier=multiplier,\n\u001b[32m 241\u001b[39m )\n\u001b[32m 242\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mcls\u001b[39m(tiff)\n", + "\u001b[31mAsyncTiffException\u001b[39m: GenericError: Generic S3 error: Error performing PUT http://169.254.169.254/latest/api/token in 15.25687525s, after 10 retries, max_retries: 10, retry_timeout: 180s - HTTP error: error sending request\n\nDebug source:\nGeneric {\n store: \"S3\",\n source: RetryError(\n RetryErrorImpl {\n method: PUT,\n uri: Some(\n http://169.254.169.254/latest/api/token,\n ),\n retries: 10,\n max_retries: 10,\n elapsed: 15.25687525s,\n retry_timeout: 180s,\n inner: Http(\n HttpError {\n kind: Connect,\n source: reqwest::Error {\n kind: Request,\n source: hyper_util::client::legacy::Error(\n Connect,\n ConnectError(\n \"tcp connect error\",\n 169.254.169.254:80,\n Os {\n code: 64,\n kind: Uncategorized,\n message: \"Host is down\",\n },\n ),\n ),\n },\n },\n ),\n },\n ),\n}" + ] + } + ], + "source": [ + "import rustac\n", + "import lazycogs\n", + "\n", + "# 1. Find one low-cloud Sentinel-2 scene (public STAC API, no credentials).\n", + "items = await rustac.search(\n", + " href=\"https://earth-search.aws.element84.com/v1\",\n", + " collections=[\"sentinel-2-l2a\"],\n", + " bbox=[4.8, 52.3, 5.0, 52.5], # Amsterdam\n", + " datetime=\"2023-06-01/2023-06-30\",\n", + " query={\"eo:cloud_cover\": {\"lt\": 10}},\n", + " limit=1,\n", + ")\n", + "\n", + "# 2. Stack the 10 m bands at native resolution → one (band, y, x) DataArray,\n", + "# band labelled by asset key. The asset hrefs point at the public\n", + "# sentinel-cogs bucket over https, so no store= is needed.\n", + "da = lazycogs.open_item(items[0], bands=[\"red\", \"green\", \"blue\", \"nir\"])\n", + "\n", + "print(da.dims, dict(da.sizes)) # ('band', 'y', 'x') {'band': 4, 'y': 10980, 'x': 10980}\n", + "print(da[\"band\"].values) # ['red' 'green' 'blue' 'nir']\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9cb200ef", + "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { - "display_name": ".venv (3.12.2.final.0)", + "display_name": "lazycogs (3.13.3)", "language": "python", "name": "python3" }, @@ -719,7 +2229,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.2" + "version": "3.13.3" } }, "nbformat": 4, diff --git a/tests/conftest.py b/tests/conftest.py index 21e1853..aae2a36 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -104,33 +104,52 @@ async def fake_open(path: str, *, store): ) -@pytest.fixture(scope="session") -def synthetic_cog(tmp_path_factory) -> Path: - """Write a small synthetic COG with four overview levels to a temp file. - - Properties: - - Native resolution: 10 m, 320 x 320 pixels - - CRS: UTM zone 32N (EPSG:32632) - - Origin: 500 000 E, 5 600 000 N - - Overview shrink factors: [2, 4, 8, 16] → resolutions 20, 40, 80, 160 m - - Pixel values: unique uint16 per pixel (col + row * width), so every - sampling position returns a deterministic, distinct value that lets - tests distinguish which source pixel was sampled. - - Nodata: 0 (pixels shifted by 1 to avoid accidental nodata) - - The file is written using the standard two-step COG recipe so that both - the full-resolution IFD and all overview IFDs are tiled (required by - async_geotiff). +def _write_synthetic_cog( + cog_path: Path, + *, + size: int = 2048, + native_res: float = 10.0, + minx: float = 500_000.0, + maxy: float = 5_600_000.0, + epsg: int = 32632, + count: int = 1, + nodata: float | None = 0, + seed: int = 0, +) -> Path: + """Write a tiled synthetic COG with four overview levels. + + Pixel values are unique per pixel (``col + row * size`` plus a per-band and + per-``seed`` offset) so tests can tell which source pixel and band was + sampled. The two-step recipe keeps both the full-resolution IFD and every + overview IFD tiled, which async_geotiff requires. + + Args: + cog_path: Destination path for the COG. + size: Width and height in pixels. + native_res: Pixel size in CRS units. + minx: Left edge (origin easting). + maxy: Top edge (origin northing). + epsg: CRS EPSG code. + count: Number of bands. + nodata: Nodata value, or ``None`` for no nodata. + seed: Offset added to pixel values so distinct COGs differ. + + Returns: + ``cog_path``. """ - cog_path = tmp_path_factory.mktemp("cog") / "synthetic.tif" - native_res = 10.0 - size = 2048 - minx, maxy = 500_000.0, 5_600_000.0 transform = Affine(native_res, 0.0, minx, 0.0, -native_res, maxy) - crs_wkt = CRS.from_epsg(32632).to_wkt() + crs_wkt = CRS.from_epsg(epsg).to_wkt() rows, cols = np.meshgrid(np.arange(size), np.arange(size), indexing="ij") - data = ((cols + rows * size) % 65535 + 1).astype(np.uint16) + linear = cols + rows * size + seed + # count=1, seed=0 reproduces the original single-band fixture exactly: + # ((cols + rows * size) % 65535 + 1). + data = np.stack( + [ + ((linear + band * 100) % 65535 + 1).astype(np.uint16) + for band in range(count) + ], + ) # Step 1: write to a temporary stripped GeoTIFF and build overviews. with tempfile.NamedTemporaryFile(suffix=".tif", delete=False) as tmp: @@ -142,13 +161,13 @@ def synthetic_cog(tmp_path_factory) -> Path: driver="GTiff", height=size, width=size, - count=1, + count=count, dtype="uint16", crs=crs_wkt, transform=transform, - nodata=0, + nodata=nodata, ) as dst: - dst.write(data[np.newaxis]) + dst.write(data) with rasterio.open(tmp_path, "r+") as dst: dst.build_overviews([2, 4, 8, 16], rasterio.enums.Resampling.nearest) @@ -167,3 +186,63 @@ def synthetic_cog(tmp_path_factory) -> Path: tmp_path.unlink() return cog_path + + +@pytest.fixture(scope="session") +def synthetic_cog(tmp_path_factory) -> Path: + """Write a small synthetic COG with four overview levels to a temp file. + + Properties: + - Native resolution: 10 m, 2048 x 2048 pixels + - CRS: UTM zone 32N (EPSG:32632) + - Origin: 500 000 E, 5 600 000 N + - Overview shrink factors: [2, 4, 8, 16] → resolutions 20, 40, 80, 160 m + - Pixel values: unique uint16 per pixel (col + row * width), so every + sampling position returns a deterministic, distinct value that lets + tests distinguish which source pixel was sampled. + - Nodata: 0 (pixels shifted by 1 to avoid accidental nodata) + + The file is written using the standard two-step COG recipe so that both + the full-resolution IFD and all overview IFDs are tiled (required by + async_geotiff). + """ + return _write_synthetic_cog(tmp_path_factory.mktemp("cog") / "synthetic.tif") + + +@pytest.fixture(scope="session") +def synthetic_cog_b(tmp_path_factory) -> Path: + """A second single-band COG on the same grid as ``synthetic_cog``. + + Different pixel values (``seed``) so a stacked ``open_item`` result carries + distinct data per band. + """ + return _write_synthetic_cog( + tmp_path_factory.mktemp("cog_b") / "synthetic_b.tif", + seed=1000, + ) + + +@pytest.fixture(scope="session") +def synthetic_cog_offgrid(tmp_path_factory) -> Path: + """A single-band COG on a different grid (20 m, shifted origin). + + Used to check that ``open_item`` rejects assets that do not share one + native grid. + """ + return _write_synthetic_cog( + tmp_path_factory.mktemp("cog_offgrid") / "synthetic_offgrid.tif", + native_res=20.0, + minx=600_000.0, + ) + + +@pytest.fixture(scope="session") +def synthetic_cog_multiband(tmp_path_factory) -> Path: + """A two-band COG on the ``synthetic_cog`` grid. + + Used to check that ``open_item`` rejects multi-band assets. + """ + return _write_synthetic_cog( + tmp_path_factory.mktemp("cog_mb") / "synthetic_mb.tif", + count=2, + ) diff --git a/tests/test_single.py b/tests/test_single.py index 956e9fa..115c2d7 100644 --- a/tests/test_single.py +++ b/tests/test_single.py @@ -48,3 +48,90 @@ def test_values_loaded(native_da): data = native_da.to_numpy() assert data.shape == (1, 2048, 2048) assert data.max() > 0 + + +def _item(**assets) -> dict: + """Build a minimal STAC item dict from ``key=cog_path`` pairs.""" + return { + "assets": { + key: { + "href": path.as_uri(), + "roles": ["data"], + "type": "image/tiff; application=geotiff; profile=cloud-optimized", + } + for key, path in assets.items() + }, + } + + +@pytest.fixture +def two_band_item(synthetic_cog, synthetic_cog_b): + """A STAC item with two same-grid single-band assets.""" + return _item(b04=synthetic_cog, b08=synthetic_cog_b) + + +def test_open_item_stacks_bands_by_asset_key(two_band_item): + """Selected assets stack into (band, y, x) labelled by asset key.""" + store = LocalStore() + da = lazycogs.open_item(two_band_item, bands=["b04", "b08"], store=store) + + assert da.dims == ("band", "y", "x") + assert da.sizes == {"band": 2, "y": 2048, "x": 2048} + assert list(da["band"].to_numpy()) == ["b04", "b08"] + # Distinct source COGs → distinct band data. + assert not np.array_equal(da.isel(band=0).to_numpy(), da.isel(band=1).to_numpy()) + + +def test_open_item_defaults_to_preferred_data_assets(two_band_item): + """Omitting bands uses the item's preferred data assets.""" + store = LocalStore() + da = lazycogs.open_item(two_band_item, store=store) + assert set(da["band"].to_numpy()) == {"b04", "b08"} + + +def test_open_item_preserves_native_crs_and_resolution(two_band_item): + """open_item keeps the native grid; no reprojection.""" + store = LocalStore() + da = lazycogs.open_item(two_band_item, bands=["b04", "b08"], store=store) + + crs = CRS.from_wkt(da["spatial_ref"].attrs["crs_wkt"]) + assert crs.to_epsg() == 32632 + x = da["x"].to_numpy() + assert np.isclose(abs(x[1] - x[0]), 10.0) + + +def test_open_item_surfaces_shared_nodata(two_band_item): + """A nodata value shared by all bands is advertised as _FillValue.""" + store = LocalStore() + da = lazycogs.open_item(two_band_item, bands=["b04", "b08"], store=store) + assert da.attrs["_FillValue"] == 0 + assert da.attrs["grid_mapping"] == "spatial_ref" + + +def test_open_item_rejects_grid_mismatch(synthetic_cog, synthetic_cog_offgrid): + """Assets on different native grids raise a ValueError.""" + item = _item(b04=synthetic_cog, off=synthetic_cog_offgrid) + store = LocalStore() + with pytest.raises(ValueError, match="native grid"): + lazycogs.open_item(item, bands=["b04", "off"], store=store) + + +def test_open_item_rejects_multiband_asset(synthetic_cog, synthetic_cog_multiband): + """A multi-band asset raises and points to open_cog.""" + item = _item(b04=synthetic_cog, mb=synthetic_cog_multiband) + store = LocalStore() + with pytest.raises(ValueError, match="single-band"): + lazycogs.open_item(item, bands=["b04", "mb"], store=store) + + +def test_open_item_rejects_unknown_band(two_band_item): + """Requesting a band absent from the item raises a ValueError.""" + store = LocalStore() + with pytest.raises(ValueError, match="not present"): + lazycogs.open_item(two_band_item, bands=["b04", "missing"], store=store) + + +def test_open_item_rejects_item_without_assets(): + """An item with no assets raises a ValueError.""" + with pytest.raises(ValueError, match="no assets"): + lazycogs.open_item({"assets": {}}) diff --git a/uv.lock b/uv.lock index 1e12a98..ff515af 100644 --- a/uv.lock +++ b/uv.lock @@ -3098,4 +3098,4 @@ dependencies = [ sdist = { url = "https://files.pythonhosted.org/packages/48/33/8c2bcceedfa13122916b6a582eedf9581682dbee329d95bcfb4c69542ade/xproj-0.2.1.tar.gz", hash = "sha256:d520c7a0df402f6a5922108ed614c8ea0ce6b04bec12c91aceb75fe3c1d3c5c3", size = 31781, upload-time = "2025-07-07T09:05:48.022Z" } wheels = [ { url = "https://files.pythonhosted.org/packages/05/b9/b6a9cf72aef69c3e6db869dcc130e19452a658366dac9377f9cd32a76b80/xproj-0.2.1-py3-none-any.whl", hash = "sha256:d762c540c1bc4abc5955b4034b409b9b2f7733c3e49285f3aeb71f9a2dd6bf34", size = 23837, upload-time = "2025-07-07T09:05:46.889Z" }, -] +] \ No newline at end of file From d517908cfbd50184ceacab12c443b6ea0f59c0d2 Mon Sep 17 00:00:00 2001 From: Jonas Berhin Date: Mon, 13 Jul 2026 17:07:38 +0200 Subject: [PATCH 3/8] Refactor code structure for improved readability and maintainability --- docs/notebooks/single-item.ipynb | 1354 ++++++++++++++++++ test.ipynb | 2237 ------------------------------ 2 files changed, 1354 insertions(+), 2237 deletions(-) create mode 100644 docs/notebooks/single-item.ipynb delete mode 100644 test.ipynb diff --git a/docs/notebooks/single-item.ipynb b/docs/notebooks/single-item.ipynb new file mode 100644 index 0000000..b5cee0a --- /dev/null +++ b/docs/notebooks/single-item.ipynb @@ -0,0 +1,1354 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "633084e9", + "metadata": {}, + "source": [ + "# Single STAC Item: `open_item` and `open_cog`\n", + "\n", + "Two single-item helpers in `lazycogs`, both lazy and read at the asset's native grid:\n", + "\n", + "- `lazycogs.open_item` — stack several same-grid bands of one STAC item into a `(band, y, x)` DataArray.\n", + "- `lazycogs.open_cog` — read one Cloud-Optimized GeoTIFF at its native CRS, resolution, and shape.\n", + "\n", + "First, find one low-cloud Sentinel-2 scene and configure a store for the public bucket (no credentials needed)." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "5b3e1557", + "metadata": {}, + "outputs": [], + "source": [ + "import rustac\n", + "from obstore.store import S3Store\n", + "\n", + "import lazycogs\n", + "\n", + "items = await rustac.search(\n", + " href=\"https://earth-search.aws.element84.com/v1\",\n", + " collections=[\"sentinel-2-c1-l2a\"],\n", + " bbox=[4.8, 52.3, 5.0, 52.5], # Amsterdam\n", + " datetime=\"2023-06-01/2023-06-30\",\n", + " query={\"eo:cloud_cover\": {\"lt\": 10}},\n", + " limit=1,\n", + ")\n", + "item = items[0]\n", + "\n", + "store = S3Store(\n", + " bucket=\"e84-earth-search-sentinel-data\",\n", + " region=\"us-west-2\",\n", + " skip_signature=True,\n", + " virtual_hosted_style_request=True,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "62a2cb1a", + "metadata": {}, + "source": [ + "## Open a Multi-Band Item with `open_item`\n", + "\n", + "`lazycogs.open_item` stacks several single-band assets of one STAC item into a `(band, y, x)` DataArray at their shared native grid. Here we request the `red` and `green` bands. Notice that both of these assets have the same grid. If we were to pick bands with different grids, `lazycogs.open_item` would raise an error, `lazycogs.open` would then be the correct function to use." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "3ab37ec3", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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    " - ], - "text/plain": [ - " Size: 161MB\n", - "array([[[-9999, -9999, -9999, ..., -9999, -9999, -9999],\n", - " [-9999, -9999, -9999, ..., -9999, -9999, -9999],\n", - " [-9999, -9999, -9999, ..., -9999, -9999, -9999],\n", - " ...,\n", - " [-9999, -9999, -9999, ..., -9999, -9999, -9999],\n", - " [-9999, -9999, -9999, ..., -9999, -9999, -9999],\n", - " [-9999, -9999, -9999, ..., -9999, -9999, -9999]]],\n", - " shape=(1, 5601, 14400), dtype=int16)\n", - "Coordinates:\n", - " * band (band) int64 8B 1\n", - " * y (y) float64 45kB 70.0 69.97 69.95 69.92 ... -69.95 -69.98 -70.0\n", - " * x (x) float64 115kB -180.0 -180.0 -179.9 ... 179.9 180.0 180.0\n", - " spatial_ref int64 8B 0\n", - "Indexes:\n", - " ┌ x RasterIndex (crs=EPSG:4326)\n", - " └ y\n", - "Attributes:\n", - " grid_mapping: spatial_ref\n", - " _FillValue: -9999.0\n", - " scale_factor: 0.01\n", - " add_offset: 273.15" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from async_geotiff import GeoTIFF\n", - "from urllib.parse import urlparse\n", - "\n", - "def strip_bucket(href: str) -> str:\n", - " # href: https://data.lpdaac.earthdatacloud.nasa.gov/lp-prod-protected/path/to/file.tif\n", - " # store is rooted at the bucket, so the path is just path/to/file.tif\n", - " return urlparse(href).path.lstrip(\"/\").removeprefix(\"eodata/\")\n", - "\n", - "\n", - "\n", - "await lazycogs.open_cog(strip_bucket(items[0][\"assets\"][\"lst_lst\"][\"href\"]), store=store)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "9f557dd2", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "fdb9e57b", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "0da22527", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "6de3087e", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "8b1be7a4", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'Product': {'href': 'https://download.dataspace.copernicus.eu/odata/v1/Products(db6d312c-12bf-49f8-9fec-424bf08a4ffb)/$value',\n", - " 'file:size': 25720143,\n", - " 'file:checksum': 'd50110dcddac5dc58d26bddaa50e251a6f5d1c',\n", - " 'file:local_path': 'c_gls_LST_202103272300_GLOBE_GEO_V3.0.1_cog.zip',\n", - " 'type': 'application/zip',\n", - " 'roles': ['data', 'metadata', 'archive'],\n", - " 'title': 'Zipped product',\n", - " 'auth:refs': ['oidc']},\n", - " 'lst_lst': {'href': 's3://eodata/CLMS/bio-geophysical/land_surface_temperature/lst_global_3km_hourly_v3/2021/03/27/c_gls_LST_202103272300_GLOBE_GEO_V3.0.1_cog/c_gls_LST-LST_202103272300_GLOBE_GEO_V3.0.1.tiff',\n", - " 'alternate': {'https': {'href': 'https://download.dataspace.copernicus.eu/odata/v1/Products(db6d312c-12bf-49f8-9fec-424bf08a4ffb)/Nodes(c_gls_LST_202103272300_GLOBE_GEO_V3.0.1_cog)/Nodes(c_gls_LST-LST_202103272300_GLOBE_GEO_V3.0.1.tiff)/$value',\n", - " 'auth:refs': ['oidc'],\n", - " 'storage:refs': [],\n", - " 'alternate:name': 'HTTPS'}},\n", - " 'file:size': 14369966,\n", - " 'proj:shape': [5601, 14400],\n", - " 'file:checksum': 'd5011030da76f45348000f8c1ed5d4f3943b99',\n", - " 'proj:transform': [0.025, 0.0, -180.01250000000002, 0.0, -0.025, 70.0125],\n", - " 'file:local_path': 'c_gls_LST_202103272300_GLOBE_GEO_V3.0.1_cog/c_gls_LST-LST_202103272300_GLOBE_GEO_V3.0.1.tiff',\n", - " 'type': 'image/tiff; application=geotiff; profile=cloud-optimized',\n", - " 'bands': [{'name': 'lst', 'description': 'Land Surface Temperature'}],\n", - " 'roles': ['data'],\n", - " 'title': 'Land Surface Temperature',\n", - " 'nodata': -9999,\n", - " 'auth:refs': ['s3'],\n", - " 'data_type': 'int16',\n", - " 'raster:scale': 0.01,\n", - " 'storage:refs': ['cdse-s3', 'creodias-s3'],\n", - " 'raster:offset': 273.15,\n", - " 'alternate:name': 'S3'},\n", - " 'lst_qflag': {'href': 's3://eodata/CLMS/bio-geophysical/land_surface_temperature/lst_global_3km_hourly_v3/2021/03/27/c_gls_LST_202103272300_GLOBE_GEO_V3.0.1_cog/c_gls_LST-QFLAG_202103272300_GLOBE_GEO_V3.0.1.tiff',\n", - " 'bands': [{'name': 'qflag',\n", - " 'description': 'Quality Flag on Land Surface Temperature'}],\n", - " 'alternate': {'https': {'href': 'https://download.dataspace.copernicus.eu/odata/v1/Products(db6d312c-12bf-49f8-9fec-424bf08a4ffb)/Nodes(c_gls_LST_202103272300_GLOBE_GEO_V3.0.1_cog)/Nodes(c_gls_LST-QFLAG_202103272300_GLOBE_GEO_V3.0.1.tiff)/$value',\n", - " 'auth:refs': ['oidc'],\n", - " 'storage:refs': [],\n", - " 'alternate:name': 'HTTPS'}},\n", - " 'file:size': 1602881,\n", - " 'proj:shape': [5601, 14400],\n", - " 'file:checksum': 'd501101f71f56f35eae37caa15cd474e1de39d',\n", - " 'proj:transform': [0.025, 0.0, -180.01250000000002, 0.0, -0.025, 70.0125],\n", - " 'file:local_path': 'c_gls_LST_202103272300_GLOBE_GEO_V3.0.1_cog/c_gls_LST-QFLAG_202103272300_GLOBE_GEO_V3.0.1.tiff',\n", - " 'type': 'image/tiff; application=geotiff; profile=cloud-optimized',\n", - " 'roles': ['data'],\n", - " 'title': 'Quality Flag on Land Surface Temperature',\n", - " 'nodata': -9999,\n", - " 'auth:refs': ['s3'],\n", - " 'data_type': 'int16',\n", - " 'storage:refs': ['cdse-s3', 'creodias-s3'],\n", - " 'alternate:name': 'S3'},\n", - " 'lst_tdelta': {'href': 's3://eodata/CLMS/bio-geophysical/land_surface_temperature/lst_global_3km_hourly_v3/2021/03/27/c_gls_LST_202103272300_GLOBE_GEO_V3.0.1_cog/c_gls_LST-TDELTA_202103272300_GLOBE_GEO_V3.0.1.tiff',\n", - " 'alternate': {'https': {'href': 'https://download.dataspace.copernicus.eu/odata/v1/Products(db6d312c-12bf-49f8-9fec-424bf08a4ffb)/Nodes(c_gls_LST_202103272300_GLOBE_GEO_V3.0.1_cog)/Nodes(c_gls_LST-TDELTA_202103272300_GLOBE_GEO_V3.0.1.tiff)/$value',\n", - " 'auth:refs': ['oidc'],\n", - " 'storage:refs': [],\n", - " 'alternate:name': 'HTTPS'}},\n", - " 'file:size': 1212769,\n", - " 'proj:shape': [5601, 14400],\n", - " 'file:checksum': 'd5011092cf24980c8e71190b7aeb2f024ddd36',\n", - " 'proj:transform': [0.025, 0.0, -180.01250000000002, 0.0, -0.025, 70.0125],\n", - " 'file:local_path': 'c_gls_LST_202103272300_GLOBE_GEO_V3.0.1_cog/c_gls_LST-TDELTA_202103272300_GLOBE_GEO_V3.0.1.tiff',\n", - " 'type': 'image/tiff; application=geotiff; profile=cloud-optimized',\n", - " 'bands': [{'name': 'tdelta',\n", - " 'description': 'Time delta between observation and reference time on Land Surface Temperature'}],\n", - " 'roles': ['data'],\n", - " 'title': 'Time delta between observation and reference time on Land Surface Temperature',\n", - " 'nodata': -9999,\n", - " 'auth:refs': ['s3'],\n", - " 'data_type': 'int16',\n", - " 'storage:refs': ['cdse-s3', 'creodias-s3'],\n", - " 'alternate:name': 'S3'},\n", - " 'lst_errorbar': {'href': 's3://eodata/CLMS/bio-geophysical/land_surface_temperature/lst_global_3km_hourly_v3/2021/03/27/c_gls_LST_202103272300_GLOBE_GEO_V3.0.1_cog/c_gls_LST-ERRORBAR_202103272300_GLOBE_GEO_V3.0.1.tiff',\n", - " 'alternate': {'https': {'href': 'https://download.dataspace.copernicus.eu/odata/v1/Products(db6d312c-12bf-49f8-9fec-424bf08a4ffb)/Nodes(c_gls_LST_202103272300_GLOBE_GEO_V3.0.1_cog)/Nodes(c_gls_LST-ERRORBAR_202103272300_GLOBE_GEO_V3.0.1.tiff)/$value',\n", - " 'auth:refs': ['oidc'],\n", - " 'storage:refs': [],\n", - " 'alternate:name': 'HTTPS'}},\n", - " 'file:size': 8533381,\n", - " 'proj:shape': [5601, 14400],\n", - " 'file:checksum': 'd50110df1a561b607ae0c69ad7915c21dbb17a',\n", - " 'proj:transform': [0.025, 0.0, -180.01250000000002, 0.0, -0.025, 70.0125],\n", - " 'file:local_path': 'c_gls_LST_202103272300_GLOBE_GEO_V3.0.1_cog/c_gls_LST-ERRORBAR_202103272300_GLOBE_GEO_V3.0.1.tiff',\n", - " 'type': 'image/tiff; application=geotiff; profile=cloud-optimized',\n", - " 'bands': [{'name': 'errorbar',\n", - " 'description': 'Standard error on Land Surface Temperature'}],\n", - " 'roles': ['data'],\n", - " 'title': 'Standard error on Land Surface Temperature',\n", - " 'nodata': -9999,\n", - " 'auth:refs': ['s3'],\n", - " 'data_type': 'int16',\n", - " 'raster:scale': 0.01,\n", - " 'storage:refs': ['cdse-s3', 'creodias-s3'],\n", - " 'alternate:name': 'S3'}}" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "items[0][\"assets\"]" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "dde80bbe", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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-       "array([[[-9999, -9999, -9999, ..., -9999, -9999, -9999],\n",
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    " - ], - "text/plain": [ - " Size: 323MB\n", - "array([[[-9999, -9999, -9999, ..., -9999, -9999, -9999],\n", - " [-9999, -9999, -9999, ..., -9999, -9999, -9999],\n", - " [-9999, -9999, -9999, ..., -9999, -9999, -9999],\n", - " ...,\n", - " [-9999, -9999, -9999, ..., -9999, -9999, -9999],\n", - " [-9999, -9999, -9999, ..., -9999, -9999, -9999],\n", - " [-9999, -9999, -9999, ..., -9999, -9999, -9999]],\n", - "\n", - " [[ 0, 0, 0, ..., 0, 0, 0],\n", - " [ 0, 0, 0, ..., 0, 0, 0],\n", - " [ 0, 0, 0, ..., 0, 0, 0],\n", - " ...,\n", - " [ 0, 0, 0, ..., 0, 0, 0],\n", - " [ 0, 0, 0, ..., 0, 0, 0],\n", - " [ 0, 0, 0, ..., 0, 0, 0]]],\n", - " shape=(2, 5601, 14400), dtype=int16)\n", - "Coordinates:\n", - " * band (band) \u001b[39m\u001b[32m17\u001b[39m da = lazycogs.open_item(items[\u001b[32m0\u001b[39m], bands=[\u001b[33m\"red\"\u001b[39m, \u001b[33m\"green\"\u001b[39m, \u001b[33m\"blue\"\u001b[39m, \u001b[33m\"nir\"\u001b[39m])\n\u001b[32m 18\u001b[39m \n\u001b[32m 19\u001b[39m print(da.dims, dict(da.sizes)) \u001b[38;5;66;03m# ('band', 'y', 'x') {'band': 4, 'y': 10980, 'x': 10980}\u001b[39;00m\n\u001b[32m 20\u001b[39m print(da[\u001b[33m\"band\"\u001b[39m].values) \u001b[38;5;66;03m# ['red' 'green' 'blue' 'nir']\u001b[39;00m\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/lazycogs/src/lazycogs/_single.py:298\u001b[39m, in \u001b[36mopen_item\u001b[39m\u001b[34m(item, bands, store, path_from_href)\u001b[39m\n\u001b[32m 262\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34mopen_item\u001b[39m(\n\u001b[32m 263\u001b[39m item: \u001b[38;5;28mdict\u001b[39m[\u001b[38;5;28mstr\u001b[39m, Any],\n\u001b[32m 264\u001b[39m bands: \u001b[38;5;28mlist\u001b[39m[\u001b[38;5;28mstr\u001b[39m] | \u001b[38;5;28;01mNone\u001b[39;00m = \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[32m (...)\u001b[39m\u001b[32m 267\u001b[39m path_from_href: Callable[[\u001b[38;5;28mstr\u001b[39m], \u001b[38;5;28mstr\u001b[39m] | \u001b[38;5;28;01mNone\u001b[39;00m = \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[32m 268\u001b[39m ) -> DataArray:\n\u001b[32m 269\u001b[39m \u001b[38;5;250m \u001b[39m\u001b[33;03m\"\"\"Open several same-grid assets of one STAC item as ``(band, y, x)``.\u001b[39;00m\n\u001b[32m 270\u001b[39m \n\u001b[32m 271\u001b[39m \u001b[33;03m Reads the requested single-band assets of one STAC item at their native\u001b[39;00m\n\u001b[32m (...)\u001b[39m\u001b[32m 296\u001b[39m \n\u001b[32m 297\u001b[39m \u001b[33;03m \"\"\"\u001b[39;00m\n\u001b[32m--> \u001b[39m\u001b[32m298\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[30;43mrun_on_loop\u001b[39;49m\u001b[30;43m(\u001b[39;49m\n\u001b[32m 299\u001b[39m \u001b[30;43m \u001b[39;49m\u001b[30;43mopen_item_async\u001b[39;49m\u001b[30;43m(\u001b[39;49m\n\u001b[32m 300\u001b[39m \u001b[30;43m \u001b[39;49m\u001b[30;43mitem\u001b[39;49m\u001b[30;43m,\u001b[39;49m\n\u001b[32m 301\u001b[39m \u001b[30;43m \u001b[39;49m\u001b[30;43mbands\u001b[39;49m\u001b[30;43m,\u001b[39;49m\n\u001b[32m 302\u001b[39m \u001b[30;43m \u001b[39;49m\u001b[30;43mstore\u001b[39;49m\u001b[30;43m=\u001b[39;49m\u001b[30;43mstore\u001b[39;49m\u001b[30;43m,\u001b[39;49m\n\u001b[32m 303\u001b[39m \u001b[30;43m \u001b[39;49m\u001b[30;43mpath_from_href\u001b[39;49m\u001b[30;43m=\u001b[39;49m\u001b[30;43mpath_from_href\u001b[39;49m\u001b[30;43m,\u001b[39;49m\n\u001b[32m 304\u001b[39m \u001b[30;43m \u001b[39;49m\u001b[30;43m)\u001b[39;49m\u001b[30;43m,\u001b[39;49m\n\u001b[32m 305\u001b[39m \u001b[30;43m \u001b[39;49m\u001b[30;43m)\u001b[39;49m\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/lazycogs/src/lazycogs/_executor.py:174\u001b[39m, in \u001b[36mrun_on_loop\u001b[39m\u001b[34m(coro)\u001b[39m\n\u001b[32m 167\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34mrun_on_loop\u001b[39m[T](coro: Coroutine[\u001b[38;5;28mobject\u001b[39m, \u001b[38;5;28mobject\u001b[39m, T]) -> T:\n\u001b[32m 168\u001b[39m \u001b[38;5;250m \u001b[39m\u001b[33;03m\"\"\"Run ``coro`` on the shared lazycogs event loop and return its result.\u001b[39;00m\n\u001b[32m 169\u001b[39m \n\u001b[32m 170\u001b[39m \u001b[33;03m This is the supported helper for sync code that must execute a coroutine on\u001b[39;00m\n\u001b[32m 171\u001b[39m \u001b[33;03m the lazycogs background loop, including callers that need to construct\u001b[39;00m\n\u001b[32m 172\u001b[39m \u001b[33;03m loop-bound resources on that loop.\u001b[39;00m\n\u001b[32m 173\u001b[39m \u001b[33;03m \"\"\"\u001b[39;00m\n\u001b[32m--> \u001b[39m\u001b[32m174\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[30;43m_submit_to_loop\u001b[39;49m\u001b[30;43m(\u001b[39;49m\u001b[30;43mcoro\u001b[39;49m\u001b[30;43m)\u001b[39;49m\u001b[30;43m.\u001b[39;49m\u001b[30;43mresult\u001b[39;49m\u001b[30;43m(\u001b[39;49m\u001b[30;43m)\u001b[39;49m\n", - "\u001b[36mFile \u001b[39m\u001b[32m/opt/homebrew/Cellar/python@3.13/3.13.3/Frameworks/Python.framework/Versions/3.13/lib/python3.13/concurrent/futures/_base.py:456\u001b[39m, in \u001b[36mFuture.result\u001b[39m\u001b[34m(self, timeout)\u001b[39m\n\u001b[32m 454\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m CancelledError()\n\u001b[32m 455\u001b[39m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28mself\u001b[39m._state == FINISHED:\n\u001b[32m--> \u001b[39m\u001b[32m456\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[30;43mself\u001b[39;49m\u001b[30;43m.\u001b[39;49m\u001b[30;43m__get_result\u001b[39;49m\u001b[30;43m(\u001b[39;49m\u001b[30;43m)\u001b[39;49m\n\u001b[32m 457\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m 458\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTimeoutError\u001b[39;00m()\n", - "\u001b[36mFile \u001b[39m\u001b[32m/opt/homebrew/Cellar/python@3.13/3.13.3/Frameworks/Python.framework/Versions/3.13/lib/python3.13/concurrent/futures/_base.py:401\u001b[39m, in \u001b[36mFuture.__get_result\u001b[39m\u001b[34m(self)\u001b[39m\n\u001b[32m 399\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m._exception:\n\u001b[32m 400\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m401\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;28mself\u001b[39m._exception\n\u001b[32m 402\u001b[39m \u001b[38;5;28;01mfinally\u001b[39;00m:\n\u001b[32m 403\u001b[39m \u001b[38;5;66;03m# Break a reference cycle with the exception in self._exception\u001b[39;00m\n\u001b[32m 404\u001b[39m \u001b[38;5;28mself\u001b[39m = \u001b[38;5;28;01mNone\u001b[39;00m\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/lazycogs/src/lazycogs/_single.py:238\u001b[39m, in \u001b[36mopen_item_async\u001b[39m\u001b[34m(item, bands, store, path_from_href)\u001b[39m\n\u001b[32m 235\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m resolved_bands:\n\u001b[32m 236\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[33m\"\u001b[39m\u001b[33mNo assets available to open from the STAC item.\u001b[39m\u001b[33m\"\u001b[39m)\n\u001b[32m--> \u001b[39m\u001b[32m238\u001b[39m arrays = \u001b[38;5;28;01mawait\u001b[39;00m asyncio.gather(\n\u001b[32m 239\u001b[39m *[\n\u001b[32m 240\u001b[39m _read_asset_band(\n\u001b[32m 241\u001b[39m assets,\n\u001b[32m 242\u001b[39m band,\n\u001b[32m 243\u001b[39m store=store,\n\u001b[32m 244\u001b[39m path_from_href=path_from_href,\n\u001b[32m 245\u001b[39m )\n\u001b[32m 246\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m band \u001b[38;5;129;01min\u001b[39;00m resolved_bands\n\u001b[32m 247\u001b[39m ],\n\u001b[32m 248\u001b[39m )\n\u001b[32m 250\u001b[39m \u001b[38;5;66;03m# join=\"exact\" rejects assets that are not on one native grid; drop_conflicts\u001b[39;00m\n\u001b[32m 251\u001b[39m \u001b[38;5;66;03m# keeps _FillValue/scale_factor/add_offset only when every band agrees.\u001b[39;00m\n\u001b[32m 252\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/lazycogs/src/lazycogs/_single.py:185\u001b[39m, in \u001b[36m_read_asset_band\u001b[39m\u001b[34m(assets, band, store, path_from_href)\u001b[39m\n\u001b[32m 177\u001b[39m \u001b[38;5;28;01masync\u001b[39;00m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34m_read_asset_band\u001b[39m(\n\u001b[32m 178\u001b[39m assets: \u001b[38;5;28mdict\u001b[39m[\u001b[38;5;28mstr\u001b[39m, Any],\n\u001b[32m 179\u001b[39m band: \u001b[38;5;28mstr\u001b[39m,\n\u001b[32m (...)\u001b[39m\u001b[32m 182\u001b[39m path_from_href: Callable[[\u001b[38;5;28mstr\u001b[39m], \u001b[38;5;28mstr\u001b[39m] | \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[32m 183\u001b[39m ) -> DataArray:\n\u001b[32m 184\u001b[39m \u001b[38;5;250m \u001b[39m\u001b[33;03m\"\"\"Open and read one single-band asset as a ``(band, y, x)`` DataArray.\"\"\"\u001b[39;00m\n\u001b[32m--> \u001b[39m\u001b[32m185\u001b[39m geotiff = \u001b[38;5;28;01mawait\u001b[39;00m _open_asset(\n\u001b[32m 186\u001b[39m assets,\n\u001b[32m 187\u001b[39m band,\n\u001b[32m 188\u001b[39m store=store,\n\u001b[32m 189\u001b[39m path_from_href=path_from_href,\n\u001b[32m 190\u001b[39m )\n\u001b[32m 191\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m geotiff.count != \u001b[32m1\u001b[39m:\n\u001b[32m 192\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[32m 193\u001b[39m \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mAsset \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mband\u001b[38;5;132;01m!r}\u001b[39;00m\u001b[33m is a \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mgeotiff.count\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m-band COG; open_item stacks \u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 194\u001b[39m \u001b[33m\"\u001b[39m\u001b[33msingle-band assets. Use lazycogs.open_cog to read a multi-band COG.\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m 195\u001b[39m )\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/lazycogs/src/lazycogs/_single.py:101\u001b[39m, in \u001b[36m_open_asset\u001b[39m\u001b[34m(assets, band, store, path_from_href)\u001b[39m\n\u001b[32m 99\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mAsset \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mband\u001b[38;5;132;01m!r}\u001b[39;00m\u001b[33m does not have an href.\u001b[39m\u001b[33m\"\u001b[39m)\n\u001b[32m 100\u001b[39m resolved_store, path = resolve(href, store=store, path_fn=path_from_href)\n\u001b[32m--> \u001b[39m\u001b[32m101\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mawait\u001b[39;00m GeoTIFF.open(path, store=resolved_store)\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/lazycogs/.venv/lib/python3.13/site-packages/async_geotiff/_geotiff.py:236\u001b[39m, in \u001b[36mGeoTIFF.open\u001b[39m\u001b[34m(cls, path, store, prefetch, multiplier)\u001b[39m\n\u001b[32m 206\u001b[39m \u001b[38;5;129m@classmethod\u001b[39m\n\u001b[32m 207\u001b[39m \u001b[38;5;28;01masync\u001b[39;00m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34mopen\u001b[39m(\n\u001b[32m 208\u001b[39m \u001b[38;5;28mcls\u001b[39m,\n\u001b[32m (...)\u001b[39m\u001b[32m 213\u001b[39m multiplier: \u001b[38;5;28mfloat\u001b[39m = \u001b[32m2.0\u001b[39m,\n\u001b[32m 214\u001b[39m ) -> Self:\n\u001b[32m 215\u001b[39m \u001b[38;5;250m \u001b[39m\u001b[33;03m\"\"\"Open a new GeoTIFF.\u001b[39;00m\n\u001b[32m 216\u001b[39m \n\u001b[32m 217\u001b[39m \u001b[33;03m Args:\u001b[39;00m\n\u001b[32m (...)\u001b[39m\u001b[32m 234\u001b[39m \n\u001b[32m 235\u001b[39m \u001b[33;03m \"\"\"\u001b[39;00m\n\u001b[32m--> \u001b[39m\u001b[32m236\u001b[39m tiff = \u001b[38;5;28;01mawait\u001b[39;00m TIFF.open(\n\u001b[32m 237\u001b[39m path=path,\n\u001b[32m 238\u001b[39m store=store,\n\u001b[32m 239\u001b[39m prefetch=prefetch,\n\u001b[32m 240\u001b[39m multiplier=multiplier,\n\u001b[32m 241\u001b[39m )\n\u001b[32m 242\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mcls\u001b[39m(tiff)\n", - "\u001b[31mAsyncTiffException\u001b[39m: GenericError: Generic S3 error: Error performing PUT http://169.254.169.254/latest/api/token in 15.25687525s, after 10 retries, max_retries: 10, retry_timeout: 180s - HTTP error: error sending request\n\nDebug source:\nGeneric {\n store: \"S3\",\n source: RetryError(\n RetryErrorImpl {\n method: PUT,\n uri: Some(\n http://169.254.169.254/latest/api/token,\n ),\n retries: 10,\n max_retries: 10,\n elapsed: 15.25687525s,\n retry_timeout: 180s,\n inner: Http(\n HttpError {\n kind: Connect,\n source: reqwest::Error {\n kind: Request,\n source: hyper_util::client::legacy::Error(\n Connect,\n ConnectError(\n \"tcp connect error\",\n 169.254.169.254:80,\n Os {\n code: 64,\n kind: Uncategorized,\n message: \"Host is down\",\n },\n ),\n ),\n },\n },\n ),\n },\n ),\n}" - ] - } - ], - "source": [ - "import rustac\n", - "import lazycogs\n", - "\n", - "# 1. Find one low-cloud Sentinel-2 scene (public STAC API, no credentials).\n", - "items = await rustac.search(\n", - " href=\"https://earth-search.aws.element84.com/v1\",\n", - " collections=[\"sentinel-2-l2a\"],\n", - " bbox=[4.8, 52.3, 5.0, 52.5], # Amsterdam\n", - " datetime=\"2023-06-01/2023-06-30\",\n", - " query={\"eo:cloud_cover\": {\"lt\": 10}},\n", - " limit=1,\n", - ")\n", - "\n", - "# 2. Stack the 10 m bands at native resolution → one (band, y, x) DataArray,\n", - "# band labelled by asset key. The asset hrefs point at the public\n", - "# sentinel-cogs bucket over https, so no store= is needed.\n", - "da = lazycogs.open_item(items[0], bands=[\"red\", \"green\", \"blue\", \"nir\"])\n", - "\n", - "print(da.dims, dict(da.sizes)) # ('band', 'y', 'x') {'band': 4, 'y': 10980, 'x': 10980}\n", - "print(da[\"band\"].values) # ['red' 'green' 'blue' 'nir']\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "9cb200ef", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "lazycogs (3.13.3)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.13.3" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} From 898667935ceac034099355ba289d7e53eecc5e09 Mon Sep 17 00:00:00 2001 From: Jonas Berhin Date: Tue, 14 Jul 2026 09:55:05 +0200 Subject: [PATCH 4/8] Add link to loading single item on native grid in navigation --- mkdocs.yml | 1 + 1 file changed, 1 insertion(+) diff --git a/mkdocs.yml b/mkdocs.yml index 4e917e8..cfacf2a 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -39,6 +39,7 @@ nav: - Experimental async workflow: notebooks/async-workflow.ipynb - rioxarray interoperability: notebooks/rioxarray.ipynb - lazycogs vs odc-stac: notebooks/lazycogs-odc-stac.ipynb + - Loading single item on native grid: notebooks/single-item.ipynb - Performance: performance.md - API Reference: - open / open_async: api/open.md From b7c96d8f4d6154c91cf91481a1aee52932cc795c Mon Sep 17 00:00:00 2001 From: Jonas Berhin Date: Tue, 14 Jul 2026 10:27:32 +0200 Subject: [PATCH 5/8] restoring files --- pdm.lock | 3580 ------------------------------------------------ pyproject.toml | 4 +- uv.lock | 4 +- 3 files changed, 4 insertions(+), 3584 deletions(-) delete mode 100644 pdm.lock diff --git a/pdm.lock b/pdm.lock deleted file mode 100644 index 06b66bd..0000000 --- a/pdm.lock +++ /dev/null @@ -1,3580 +0,0 @@ -# This file is @generated by PDM. -# It is not intended for manual editing. - -[metadata] -groups = ["default", "dask", "dev", "docs"] -strategy = ["inherit_metadata"] -lock_version = "4.5.0" -content_hash = "sha256:66e7c03bb6ac385c33fb00238b2df832b4ea7e72d95eefc0fbdb988e348839d5" - 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"""Return the ``assets`` mapping from a STAC item dict or pystac Item.""" + """Return the ``assets`` mapping from a STAC item dict.""" if hasattr(item, "to_dict"): item = item.to_dict() assets: dict[str, Any] = item.get("assets", {}) @@ -209,8 +209,7 @@ async def open_item_async( Async variant of :func:`open_item` for use inside a running event loop. Args: - item: A STAC item as a dict (e.g. a ``rustac`` search result) or a - pystac-like object exposing ``to_dict()``. + item: A STAC item as a dict (e.g. a ``rustac`` search result). bands: Asset keys to include, in output order. When ``None``, the item's preferred data assets are used (role ``"data"`` or media type ``image/tiff``), matching :func:`lazycogs.open`. @@ -276,8 +275,7 @@ def open_item( reprojected mosaic across a whole collection. Args: - item: A STAC item as a dict (e.g. a ``rustac`` search result) or a - pystac-like object exposing ``to_dict()``. + item: A STAC item as a dict (e.g. a ``rustac`` search result). bands: Asset keys to include, in output order. When ``None``, the item's preferred data assets are used (role ``"data"`` or media type ``image/tiff``), matching :func:`lazycogs.open`. From ff117bf05b1b839a1d371f2b41317ca109b2b135 Mon Sep 17 00:00:00 2001 From: Jonas Berhin Date: Thu, 16 Jul 2026 10:45:49 +0200 Subject: [PATCH 8/8] Add documentation for Single COG / item and update navigation --- docs/api/single.md | 17 +++++++++++++++++ mkdocs.yml | 1 + 2 files changed, 18 insertions(+) create mode 100644 docs/api/single.md diff --git a/docs/api/single.md b/docs/api/single.md new file mode 100644 index 0000000..fc6cd7e --- /dev/null +++ b/docs/api/single.md @@ -0,0 +1,17 @@ +# Single COG / item + +Read a single Cloud-Optimized GeoTIFF or the assets of one STAC item at their +native grid — no reprojection or mosaicking. Use `lazycogs.open` for a +reprojected mosaic across a whole collection. + +!!! tip "See also" + [Loading single item on native grid](../notebooks/single-item.ipynb) + +::: lazycogs.open_cog + +::: lazycogs.open_item + +::: lazycogs.open_cog_async + +::: lazycogs.open_item_async + diff --git a/mkdocs.yml b/mkdocs.yml index cfacf2a..fe2da00 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -43,6 +43,7 @@ nav: - Performance: performance.md - API Reference: - open / open_async: api/open.md + - Single COG / item: api/single.md - Mosaic methods: api/mosaic.md - Utilities: api/utils.md - Architecture: architecture.md