loone-data-prep 0.1.7

Prepare data to run the LOONE model.

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)