Prepare data to run the LOONE model.
Project description
LOONE_DATA_PREP
LOONE_DATA_PREP
Prepare data for the LOONE water quality model.
Line to the LOONE model: https://pypi.org/project/loone Link to LOONE model repository: https://github.com/Aquaveo/LOONE
Prerequisites:
- R (https://www.r-project.org/)
- R packages: dbhydroR, rio, dplyr
Installation:
pip install loone_data_prep
Development Installation:
cd /path/to/loone_data_prep/repo
pip install -e .
Examples
From the command line:
# Get flow data
python -m loone_data_prep.flow_data.get_inflows /path/to/workspace/
python -m loone_data_prep.flow_data.get_outflows /path/to/workspace/
python -m loone_data_prep.flow_data.S65E_total /path/to/workspace/
# Get water quality data
python -m loone_data_prep.water_quality_data.get_inflows /path/to/workspace/
python -m loone_data_prep.water_quality_data.get_lake_wq /path/to/workspace/
# Get weather data
python -m loone_data_prep.weather_data.get_all /path/to/workspace/
# Get water level
python -m loone_data_prep.water_level_data.get_all /path/to/workspace/
# Interpolate data
python -m loone_data_prep.utils interp_all /path/to/workspace/
# Prepare data for LOONE
python -m loone_data_prep.LOONE_DATA_PREP /path/to/workspace/ /path/to/output/directory/
From Python:
from loone_data_prep.utils import get_dbkeys
from loone_data_prep.water_level_data import hydro
from loone_data_prep import LOONE_DATA_PREP
input_dir = '/path/to/workspace/'
output_dir = '/path/to/output/directory/'
# Get dbkeys for water level data
dbkeys = get_dbkeys(
station_ids=["L001", "L005", "L006", "LZ40"],
category="SW",
param="STG",
stat="MEAN",
recorder="CR10",
freq="DA",
detail_level="dbkey"
)
# Get water level data
hydro.get(
workspace=input_dir,
name="lo_stage",
dbkeys=dbkeys,
date_min="1950-01-01",
date_max="2023-03-31"
)
# Prepare data for LOONE
LOONE_DATA_PREP(input_dir, output_dir)
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