hipims-io

hipims_io

Python code to process input and output files of HiPIMS flood model. This code follows Google Python Style Guide.

Python version: >=3.6. The main content of this package is also included in a Python API of HiPIMS.

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: