https://github.com/parro-it/netcdf4
NodeJS addon to read and write NetCDF4 files
https://github.com/parro-it/netcdf4
netcdf netcdf4 nodejs nodejs-addon
Last synced: 9 months ago
JSON representation
NodeJS addon to read and write NetCDF4 files
- Host: GitHub
- URL: https://github.com/parro-it/netcdf4
- Owner: parro-it
- License: isc
- Created: 2015-11-05T04:03:40.000Z (about 10 years ago)
- Default Branch: master
- Last Pushed: 2022-12-30T20:15:09.000Z (about 3 years ago)
- Last Synced: 2025-04-30T22:11:31.754Z (9 months ago)
- Topics: netcdf, netcdf4, nodejs, nodejs-addon
- Language: C++
- Size: 207 KB
- Stars: 42
- Watchers: 3
- Forks: 14
- Open Issues: 20
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# netcdf4-js
[](https://npmjs.org/package/netcdf4)
NodeJS addon for reading and writing the files in the
[Network Common Data Form (NetCDF)](https://www.unidata.ucar.edu/software/netcdf/)
version <= 4,
built upon the C-library for netcdf.
## Installation
`netcdf4-js` is built with `nodejs` >= 4.x
Install using `npm`:
```
$ npm install netcdf4
```
Prerequisites:
You will need `libnetcdf` >= 4.x installed.
### On Linux/Unix/OSX
* Install NetCDF4 using your package manager, e.g., on Ubuntu/Debian:
```
$ sudo apt-get install libnetcdf-dev
```
or download it [here](https://www.unidata.ucar.edu/downloads/netcdf/index.jsp)
* Make sure your system fulfills all the prerequisites of [node-gyp](https://github.com/nodejs/node-gyp#on-unix)
### On Windows:
* Install NetCDF4 from [here](https://www.unidata.ucar.edu/downloads/netcdf/index.jsp)
* Make sure to select at least "dependencies", "headers" and "libraries" to install in the NetCDF installation wizard
* Install the build tools as described [here](https://github.com/nodejs/node-gyp#on-windows)
* Set the environment variable `NETCDF_DIR` to your NetCDF installation, e.g.,
``` bash
C:\> set NETCDF_DIR=C:\Program Files\netCDF 4.6.1
```
## Usage
Open files with
```
var netcdf4 = require("netcdf4");
var file = new netcdf4.File("test/testrh.nc", "r");
```
File modes are `"r"` for "reading", `"w"` for "writing", `"c"` for
"creation", and `"c!"` for "overwriting".
Then you can read variables using `read` or `readSlice`. The following example reads values at positions 5 to 15:
```
console.log(file.root.variables['var1'].readSlice(5, 10));
```
### Classes
Properties marked *(r/w)* can be read and will be written to the file
when set.
#### File
Properties:
* `root` : Main `Group`-object in file
Methods:
* `close()` : Close file
* `sync()` : Sync (or "flush") file to disk
#### Group
Properties:
* `id` : ID used by C-library
* `name` : Name
* `fullname` : Full name (path in file)
* `variables` : Associative array of variables in group
* `dimensions` : Associative array of dimensions in group
* `unlimited` : Associative array of unlimited Dimensions in group
* `attribute` : Associative array of attributes of group
* `subgroups` : Associative array of subgroups of group
Methods:
* `addVariable(name, type, dimensions)` : Add a new variable in
group. `type` is one of `"byte", "char", "short", "int", "ubyte", "ushort",
"uint", "float", "double"`. `dimensions` is an array of ids of dimensions
for the new variable. Returns new variable.
* `addDimension(name, length)` : Add new dimension of length `length`
(can be `"unlimited"` for unlimited dimension). Returns new dimension.
* `addSubgroup(name)` : Add subgroup. Returns new subgroup.
* `addAttribute(name, type, value)` : Add and set new attribute. Returns new attribute.
### Dimension
Properties:
* `id` : ID used by C-library
* `name` : Name (r/w)
* `length` : Length or currently used length for unlimited dimensions
### Attribute
Properties:
* `id` : ID used by C-library
* `name` : Name (r/w)
* `value` : Value (r/w)
Methods:
* `delete()` : Delete attribute
### Variable
Properties:
* `id` : ID used by C-library
* `name` : Name (r/w)
* `type` : Type of variable
* `attributes` : Associative array of attributes
* `dimensions` : Array of dimensions used by variable
* `endianness` : Endianness: `"little"`, `"big"`, or `"native"` (r/w)
* `checksummode` : Checksum mode: `"none"`, or `"fletcher32"` (r/w)
* `chunkmode` : Chunk mode: `"contiguous"`, or `"chunked"` (r/w)
* `chunksizes` : Array of chunk sizes (one size per dimension) (r/w)
* `fillmode` : Boolean switch for fill mode (r/w)
* `fillvalue` : Fill value (r/w)
* `compressionshuffle` : Boolean switch for shuffle (r/w)
* `compressiondeflate` : Boolean switch for compression (r/w)
* `compressionlevel` : Compression level (1-9) (r/w)
Methods:
* `read(pos....)` : Reads and returns a single value at positions
given as for `write`.
* `readSlice(pos, size....)` : Reads and returns an array of values (cf.
["Specify a Hyperslab"](https://www.unidata.ucar.edu/software/netcdf/docs/programming_notes.html#specify_hyperslab))
at positions and sizes given for each dimension, `readSlice(pos1,
size1, pos2, size2, ...)` e.g. `readSlice(2, 3, 4, 2)` gives an
array of the values at position 2 for 3 steps along the first
dimension and position 4 for 2 steps along the second one.
* `readStridedSlice(pos, size, stride....)` : Similar to `readSlice()`, but it
adds a *stride* (interval between indices) parameter to each dimension. If stride is 4,
the function will take 1 value, discard 3, take 1 again, etc.
So for instance `readStridedSlice(2, 3, 2, 4, 2, 1)` gives an
array of the values at position 2 for 3 steps with stride 2 (i.e.
every other value) along the first dimension and position 4 for 2 steps
with stride 1 (i.e. with no dropping) along the second dimension.
* `write(pos..., value)` : Write `value` at positions given,
e.g. `write(2, 3, "a")` writes `"a"` at position 2 along the first
dimension and position 3 along the second one.
* `writeSlice(pos, size..., valuearray)` : Write values in `valuearray`
(must be a typed array) at positions and sizes given for each
dimension, e.g. `writeSlice(2, 3, 4, 2, new
Int32Array([0, 1, 2, 3, 4, 5]))` writes the array at position 2 for
3 steps along the first dimension and position 4 for 2 step along
the second one (cf.
["Specify a Hyperslab"](https://www.unidata.ucar.edu/software/netcdf/docs/programming_notes.html#specify_hyperslab)).
* `writeStridedSlice(pos, size, stride..., valuearray)` : Similar to
`writeSlice()`, but it adds a *stride* parameter to each dimension.
So for instance `writeStridedSlice(2, 3, 2, 4, 2, 1), new
Int32Array([0, 1, 2, 3, 4, 5])` writes the array
at position 2 for 3 steps with stride 2 (i.e.
every other value) along the first dimension and position 4 for 2 steps
with stride 1 (i.e. with no dropping) along the second dimension.
* `addAttribute(name, type, value)` : Adds and sets new attribute. Returns
new attribute.