| Name | gridit JSON |
| Version |
0.5
JSON |
| download |
| home_page | |
| Summary | Spatial tools to translate raster or vector geometry data to regular grids |
| upload_time | 2023-12-06 22:34:52 |
| maintainer | |
| docs_url | None |
| author | |
| requires_python | >=3.8 |
| license | BSD 3-Clause |
| keywords |
rasterize
grid
regular grid
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# Gridit
[](https://github.com/mwtoews/gridit/actions/workflows/tests.yml)
[](https://codecov.io/gh/mwtoews/gridit)
[](https://zenodo.org/badge/latestdoi/530041277)
## Description
Gridit provides spatial tools to translate raster or vector geometry data to regular grids.
## Installation
This package primarily depends on NumPy and SciPy, and has several optional dependencies.
Pip can be used to install all optional dependencies:
```bash
$ pip install gridit[optional]
```
Or from a clone of this repository, create an "editable" install:
```bash
$ pip install -e .[optional]
```
### Testing
Run `pytest -v`.
## Examples
### Python
```python
>>> import matplotlib.pyplot as plt # optional
>>> from gridit import Grid
>>> grid = Grid.from_vector("tests/data/Mana_polygons.shp", 100)
>>> print(grid)
<Grid: resolution=100.0, shape=(24, 18), top_left=(1748600.0, 5451200.0) />
>>> ar_vec = grid.array_from_vector("tests/data/Mana_polygons.shp", "K_m_d")
>>> plt.imshow(ar_vec)
<matplotlib.image.AxesImage at 0x7fb6c7dacf10>
>>> ar_rast = grid.array_from_raster("tests/data/Mana.tif")
>>> plt.imshow(ar_rast)
<matplotlib.image.AxesImage at 0x7fb6bc4ad6d0>
```
### Command line
Grid and array from vector, write PNG image and shapefile grid:
```bash
$ gridit --grid-from-vector tests/data/Mana_polygons.shp --resolution 100 \
--array-from-vector tests/data/Mana_polygons.shp \
--array-from-vector-attribute=K_m_d \
--write-image /tmp/Mana_Kmd.png \
--write-vector /tmp/Mana_Kmd.shp
```
Grid from bounding box, array from raster, write GeoTIFF raster:
```bash
$ gridit --grid-from-bbox 1748600 5448800 1750400 5451200 --resolution 100 \
--array-from-raster tests/data/Mana.tif \
--write-raster /tmp/Mana_100m.tif
```
Grid from vector, array from netCDF, write text array file for each time stat:
```bash
$ gridit --grid-from-vector tests/data/waitaku2.shp --resolution 250 \
--array-from-vector tests/data/waitaku2.shp \
--array-from-vector-attribute rid \
--array-from-netcdf tests/data/waitaku2.nc:rid:myvar:0 \
--time-stats "quantile(0.75),max" \
--write-text /tmp/waitaku2_cat.ref
```
Grid from MODFLOW, array from vector, write text array file:
```bash
$ gridit --grid-from-modflow tests/data/modflow/mfsim.nam:h6 \
--array-from-vector tests/data/waitaku2.shp \
--array-from-vector-attribute rid \
--write-text /tmp/waitaku2_rid.txt
```
See other options with:
```bash
$ gridit -h
```
## Funding
Funding for the development of gridit has been provided by New Zealand Strategic Science Investment Fund as part of GNS Science’s (https://www.gns.cri.nz/) Groundwater Research Programme.
Raw data
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