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
```
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"description": "hydro_raster\n--------\nPython code to process raster data for hydrological or hydrodynamic modelling, \ne.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).\n\nFull documentation about how to install and use is [here](https://hydro-raster.readthedocs.io/en/latest/index.html).\n\nPython version: >=3.6. To use the full function of this package for processing \nraster and feature files, *rasterio* and *pyshp* are required.\n\n**The CRS of both DEM and Shapfiles must be projected crs whose map unit is meter.**\n\nFunctions included in this package:\n\n1. merge raster files\n2. edit raster cell values based on shapefile\n3. convert cross-section lines to river bathymetry raster\n4. remove overhead buildings/bridges on raster \n5. read, write, and visualise raster file\n\nTo install hydro_raster from command window/terminal:\n```\npip install hydro_raster\n```\nTo install using github repo:\n```\ngit clone https://github.com/mingxiaodong/hydro-raster\ncd hydro-raster\npip install .\n```\n\nTutorial\n\nA [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.\n\n1. Read a raster file\n```\nfrom hydro_raster.Raster import Raster\nfrom hydro_raster import get_sample_data\ntif_file_name = get_sample_data('tif')\nras_obj = Raster(tif_file_name)\n```\n2. Visualize a raster file\n```\nras_obj.mapshow()\nras_obj.rankshow(breaks=[0, 10, 20, 30, 40, 50])\n```\n3. Clip raster file\n```\nclip_extent = (340761, 341528, 554668, 555682) # left, right, bottom, top\nras_obj_cut = ras_obj.rect_clip(clip_extent) # raster can aslo be cut by a shapfile using 'clip' function\nras_obj_cut.mapshow()\n```\n3. Rasterize polygons on a raster and return an index array with the same dimension of the raster array\n```\nshp_file_name = get_sample_data('shp')\nindex_array = ras_obj_cut.rasterize(shp_file_name)\nindex_array = index_array>=0\n```\n4. Change raster cell values within the polygons by adding a fixed value\n```\nras_obj_new = ras_obj_cut.duplicate()\nras_obj_new.array[index_array] = ras_obj_cut.array[index_array]+20\n```\n5. Show the edited raster with the shapefile polygons\n```\nimport matplotlib.pyplot as plt\nfrom hydro_raster.grid_show import plot_shape_file\nfig, ax = plt.subplots(1, 2)\nras_obj_cut.mapshow(ax=ax[0])\nplot_shape_file(shp_file_name, ax=ax[0], linewidth=1)\nras_obj_new.mapshow(ax=ax[1])\nplot_shape_file(shp_file_name, ax=ax[1], linewidth=1)\n# values can also be changed based on the attributes of each shapefile features\n```\n\n\n",
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