dask-rasterio provides some methods for reading and writing rasters in
parallel using Rasterio and
Dask arrays.
>>> from dask_rasterio import read_raster
>>> array = read_raster('tests/data/RGB.byte.tif')
>>> array
dask.array<stack, shape=(3, 718, 791), dtype=uint8, chunksize=(1, 3, 791)>
>>> array.mean()
dask.array<mean_agg-aggregate, shape=(), dtype=float64, chunksize=()>
>>> array.mean().compute()
40.858976977533935>>> from dask_rasterio import read_raster
>>> array = read_raster('tests/data/RGB.byte.tif', band=3)
>>> array
dask.array<raster, shape=(718, 791), dtype=uint8, chunksize=(3, 791)>>>> from dask_rasterio import read_raster, write_raster
>>> array = read_raster('tests/data/RGB.byte.tif')
>>> new_array = array & (array > 100)
>>> new_array
dask.array<and_, shape=(3, 718, 791), dtype=uint8, chunksize=(1, 3, 791)>
>>> prof = ... # reuse profile from tests/data/RGB.byte.tif...
>>> write_raster('processed_image.tif', new_array, **prof)Both read_raster and write_raster accept a block_size argument that
acts as a multiplier to the block size of rasters. The default value is 1,
which means the dask array chunk size will be the same as the block size of
the raster file. You will have to adjust this value depending on the
specification of your machine (how much memory do you have, and the block
size of the raster).
Install with pip:
pip install dask-rasterio
This project is managed by Poetry. If you do not have it installed, please refer to Poetry instructions.
Now, clone the repository and run poetry install. This will create a virtual
environment and install all required packages there.
Run poetry run pytest to run all tests.
Run poetry build to build package on dist/.
Please report any bugs and enhancement ideas using the GitHub issue tracker:
https://github.com/dymaxionlabs/dask-rasterio/issues
Feel free to also ask questions on our Gitter channel, or by email.
Any help in testing, development, documentation and other tasks is highly appreciated and useful to the project.
For more details, see the file CONTRIBUTING.md.
Source code is released under a BSD-2 license. Please refer to LICENSE.md for more information.