Metadata-Version: 2.1
Name: hydro-raster
Version: 0.0.11
Summary: To process raster data for hydrological/hydrodynamic modelling
Home-page: https://github.com/mingxiaodong/hydro-raster
Author: Xiaodong Ming
Author-email: xiaodong.ming@outlook.com
License: LICENSE.txt
Keywords: Raster Hydrological Hydrodynamic
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: rasterio
Requires-Dist: scipy
Requires-Dist: shapely
Requires-Dist: pyshp
Requires-Dist: matplotlib
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: imageio
Requires-Dist: geopandas

hydro_raster
--------
Python code to process raster data for hydrological or hydrodynamic modelling, 
e.g., [SynxFlow](https://github.com/SynxFlow/SynxFlow) or [HiPIMS-CUDA](https://github.com/HEMLab/hipims). The style of this package follows the [Google Python Style Guide](http://google.github.io/styleguide/pyguide.html).

Full documentation about how to install and use is [here](https://hydro-raster.readthedocs.io/en/latest/index.html).

Python version: >=3.6. To use the full function of this package for processing 
raster and feature files, *rasterio* and *pyshp* are required.

**The CRS of both DEM and Shapfiles must be projected crs whose map unit is meter.**

Functions included in this package:

1. merge raster files
2. edit raster cell values based on shapefile
3. convert cross-section lines to river bathymetry raster
4. remove overhead buildings/bridges on raster 
5. read, write, and visualise raster file

To install hydro_raster from command window/terminal:
```
pip install hydro_raster
```
To install using github repo:
```
git clone https://github.com/mingxiaodong/hydro-raster
cd hydro-raster
pip install .
```

Tutorial

A [jupyter-notebook file](https://github.com/mingxiaodong/hydro-raster/blob/main/demo/tutorial_edit_DEM.ipynb) is available to show a more detailed tutorial with outputs/plots of its codes.

1. Read a raster file
```
from hydro_raster.Raster import Raster
from hydro_raster import get_sample_data
tif_file_name = get_sample_data('tif')
ras_obj = Raster(tif_file_name)
```
2. Visualize a raster file
```
ras_obj.mapshow()
ras_obj.rankshow(breaks=[0, 10, 20, 30, 40, 50])
```
3. Clip raster file
```
clip_extent = (340761, 341528, 554668, 555682) # left, right, bottom, top
ras_obj_cut = ras_obj.rect_clip(clip_extent) # raster can aslo be cut by a shapfile using 'clip' function
ras_obj_cut.mapshow()
```
3. Rasterize polygons on a raster and return an index array with the same dimension of the raster array
```
shp_file_name = get_sample_data('shp')
index_array = ras_obj_cut.rasterize(shp_file_name)
index_array = index_array>=0
```
4. Change raster cell values within the polygons by adding a fixed value
```
ras_obj_new = ras_obj_cut.duplicate()
ras_obj_new.array[index_array] = ras_obj_cut.array[index_array]+20
```
5. Show the edited raster with the shapefile polygons
```
import matplotlib.pyplot as plt
from hydro_raster.grid_show import plot_shape_file
fig, ax = plt.subplots(1, 2)
ras_obj_cut.mapshow(ax=ax[0])
plot_shape_file(shp_file_name, ax=ax[0], linewidth=1)
ras_obj_new.mapshow(ax=ax[1])
plot_shape_file(shp_file_name, ax=ax[1], linewidth=1)
# values can also be changed based on the attributes of each shapefile features
```


