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.