hipims_io
--------
Python code to process input and output files of [HiPIMS flood model](https://www.hemlab.org/models/). This code follows [Google Python Style Guide](http://google.github.io/styleguide/pyguide.html).
Python version: >=3.6. The main content of this package is also included in a [Python API of HiPIMS](https://pypims.readthedocs.io/en/latest/).
To install hipims_io from command window/terminal:
```
pip install hipims_io
```
To install using github repo:
```
git clone https://github.com/mingxiaodong/hipims_io_python.git
cd hipims_io_python
pip install .
```
A quick demonstration to setup a HiPIMS input object with a sample DEM:
```
import hipims_io as hp
obj_in = hp.demo_input() # create an input object and show domain map
```
A quick demonstration to setup a HiPIMS input object with a data path contaning the following files:
- DEM.gz/.asc/.tif (essential file, in projected crs)
- rain_mask.gz/.asc/.tif (optional file for setting rainfall, having the same crs with DEM)
- rain_source.csv (optional file for setting rainfall rate in timeseries]
- landcover.gz/.asc/.tif (optional file for setting landcover-based parameters, having the same crs with DEM)
```
import os
import hipims_io as hp
from hipims_io.demo_functions import get_sample_data
dem_path, _ = get_sample_data(return_path=True) # get the path of sample data
data_path = os.path.dirname(dem_path)
case_folder = os.path.join(os.getcwd(), 'hipims_case') # define a case folder in the current directory
obj_in = hp.InputHipims(case_folder=case_folder, num_of_sections=1,
data_path=data_path) # create input object
obj_in.domain_show() # show domain map
print(obj_in) # show case information
```
A step-by-step tutorial to setup a HiPIMS input object with sample data:
```
import os
import numpy as np
import hipims_io as hp
dem_file, model_data, _ = hp.get_sample_data() # get sample data
case_folder = os.path.join(os.getcwd(), 'hipims_case') # define a case folder in the current directory
# create a single-gpu input object
obj_in = hp.InputHipims(dem_data=dem_file, num_of_sections=1, case_folder=case_folder)
# set a initial water depth of 0.5 m
obj_in.set_initial_condition('h0', 0.5)
# set boundary condition
bound_list = model_data['boundary_condition'] # with boundary information
obj_in.set_boundary_condition(bound_list, outline_boundary='fall')
# set rainfall mask and source
rain_source = model_data['rain_source']
obj_in.set_rainfall(rain_mask=0, rain_source=rain_source)
# set manning parameter
manning_array = np.zeros(obj_in.DEM.shape)+0.03 # create an array with the same shape of the DEM array
obj_in.set_grid_parameter(manning=manning_array)
# set monitor positions
gauges_pos = model_data['gauges_pos']
obj_in.set_gauges_position(gauges_pos)
# display model information
obj_in.domain_show() # show domain map
print(obj_in) # print model summary
# write all input files for HiPIMS to the case folder
obj_in.write_input_files()
```
The domain map will be shown like this:
Raw data
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"description": "hipims_io\n--------\nPython code to process input and output files of [HiPIMS flood model](https://www.hemlab.org/models/). This code follows [Google Python Style Guide](http://google.github.io/styleguide/pyguide.html).\n\nPython version: >=3.6. The main content of this package is also included in a [Python API of HiPIMS](https://pypims.readthedocs.io/en/latest/).\n\nTo install hipims_io from command window/terminal:\n```\npip install hipims_io\n```\nTo install using github repo:\n```\ngit clone https://github.com/mingxiaodong/hipims_io_python.git\ncd hipims_io_python\npip install .\n```\n\nA quick demonstration to setup a HiPIMS input object with a sample DEM:\n```\nimport hipims_io as hp\nobj_in = hp.demo_input() # create an input object and show domain map\n```\nA quick demonstration to setup a HiPIMS input object with a data path contaning the following files:\n- DEM.gz/.asc/.tif (essential file, in projected crs)\n- rain_mask.gz/.asc/.tif (optional file for setting rainfall, having the same crs with DEM)\n- rain_source.csv (optional file for setting rainfall rate in timeseries]\n- landcover.gz/.asc/.tif (optional file for setting landcover-based parameters, having the same crs with DEM)\n\n```\nimport os\nimport hipims_io as hp\nfrom hipims_io.demo_functions import get_sample_data\ndem_path, _ = get_sample_data(return_path=True) # get the path of sample data\ndata_path = os.path.dirname(dem_path)\ncase_folder = os.path.join(os.getcwd(), 'hipims_case') # define a case folder in the current directory\nobj_in = hp.InputHipims(case_folder=case_folder, num_of_sections=1, \n data_path=data_path) # create input object\nobj_in.domain_show() # show domain map\nprint(obj_in) # show case information\n```\n\nA step-by-step tutorial to setup a HiPIMS input object with sample data:\n\n\n```\nimport os\nimport numpy as np\nimport hipims_io as hp\n\ndem_file, model_data, _ = hp.get_sample_data() # get sample data\ncase_folder = os.path.join(os.getcwd(), 'hipims_case') # define a case folder in the current directory\n# create a single-gpu input object\nobj_in = hp.InputHipims(dem_data=dem_file, num_of_sections=1, case_folder=case_folder)\n\n# set a initial water depth of 0.5 m\nobj_in.set_initial_condition('h0', 0.5)\n\n# set boundary condition\nbound_list = model_data['boundary_condition'] # with boundary information\nobj_in.set_boundary_condition(bound_list, outline_boundary='fall')\n\n# set rainfall mask and source\nrain_source = model_data['rain_source']\nobj_in.set_rainfall(rain_mask=0, rain_source=rain_source)\n\n# set manning parameter\nmanning_array = np.zeros(obj_in.DEM.shape)+0.03 # create an array with the same shape of the DEM array\nobj_in.set_grid_parameter(manning=manning_array)\n\n# set monitor positions\ngauges_pos = model_data['gauges_pos']\nobj_in.set_gauges_position(gauges_pos) \n\n# display model information\nobj_in.domain_show() # show domain map\nprint(obj_in) # print model summary\n\n# write all input files for HiPIMS to the case folder\nobj_in.write_input_files() \n\n```\n\nThe domain map will be shown like this:\n\n\n\n\n",
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