Spatial tools to translate raster or vector polygon data to regular grids
Project description
Gridit
Description
Gridit provides spatial tools to translate raster or vector polygon 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:
$ pip install .[optional]
Testing
Run pytest -v
.
Example
>>> import matplotlib.pyplot as plt # optional
>>> from gridit import Grid
>>> grid = Grid.from_vector("tests/data/Mana_polygons.shp", 10)
>>> print(grid)
<Grid: resolution=10.0, shape=(224, 172), top_left=(1748660.0, 5451110.0) />
>>> 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>
Array from vector:
$ gridit --grid-from-vector tests/data/Mana_polygons.shp --resolution 10 --array-from-vector tests/data/Mana_polygons.shp --array-from-vector-attribute=K_m_d
Array from raster:
$ gridit --grid-from-vector tests/data/Mana_polygons.shp --resolution 10 --array-from-raster tests/data/Mana.tif
See other options with:
$ 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.
Project details
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gridit-0.1-py3-none-any.whl
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