Plugin for gdal-async
allowing zero-copy I/O from and to scijs/ndarray
and @stdlib/ndarray
.
This module requires at least [email protected]
.
For scijs/ndarray
:
npm install --save gdal-async ndarray ndarray-gdal
For @stdlib/ndarray
:
npm install --save gdal-async @stdlib/ndarray ndarray-gdal
(beware, @stdlib/ndarray
causes npm@6
to hang, you need at least npm@7
)
const gdal = require('gdal-async');
const ndarray = require('ndarray');
require('ndarray-gdal');
const ds = gdal.open('test/sample.tif');
const band = ds.bands.get(1);
// Creating a new ndarray
const nd1 = band.pixels.readArray({ width: ds.rasterSize.x, height: ds.rasterSize.y });
// Reading into existing ndarray with a non-default stride
const nd2 = ndarray(new Uint8Array(ds.rasterSize.x * ds.rasterSize.y),
[ ds.rasterSize.y, ds.rasterSize.x ], [ ds.rasterSize.x, -1 ]);
// read the whole raster band fitting it in the array, resampling if needed
band.pixels.readArray({ data: nd2 });
// Writing from an ndarray (size can be deduced from the array)
band.pixels.writeArray({ data: nd2 });
I/O from and to all strides is supported without copying/rotation, but positive/positive row-major stride will be the fastest as this is usually the ordering that matches the file format. Interleaving is provided by the GDAL C++ implementation which uses SIMD instructions on CPUs that support it.
(x, y)
, while ndarray uses (y, x)
When used with GDAL >= 3.1, ndarray-gdal
supports the new Multidimensional Raster Data Model.
const gdal_array = gdal.open('gfs.t00z.alnsf.nc', 'mr').root.arrays.get('alnsf');
// Into existing ndarray keeping its stride
const nd1 = ndarray(new Float32Array(array.length),
gdal_array.dimensions.map((dim) => dim.size));
gdal_array.readArray({ data: nd });
// Into a new ndarray
const nd2 = gdal_array.readArray();
// Async
const nd3 = await gdal_array.readArrayAsync();
Multidimensional arrays are currently read-only.
TypeScript is supported via a module augmentation definition file.
npm install --save-dev @types/ndarray @stdlib/types
import * as gdal from 'gdal-async';
import ndarray from 'ndarray';
import 'ndarray-gdal';
const ds: gdal.Dataset = gdal.open('test/sample.tif');
const nd: ndarray.NdArray = ds.bands.get(1).pixels.readArray({
width: ds.rasterSize.x,
height: ds.rasterSize.y });
Same rules for asynchronous I/O as gdal-async
apply, you should refer to its documentation.
const nd = await gdal.openAsync('test/sample.tif')
.then((ds) => ds.bands.getAsync(1))
.then((band) => band.pixels.readArrayAsync())
.catch((e) => console.error(`bad things happened ${e}`));
Copyright © 2021 Momtchil Momtchev, @mmomtchev
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at: http:https://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.