pymt_nwm converts nwm into a reusable, plug-and-play data component for PyMT modeling framework. pymt_nwm allows the National Water Model datasets to be easily coupled with other datasets or models that expose a Basic Model Interface.

Please note that pymt_nwm package is deprecated. This package now only serves as an example to demonstrate how to create CSDMS Data Component for research datasets.

Installation

Install the pymt in a new environment:

$ conda config --add channels conda-forge
$ conda create -n pymt -c conda-forge python=3 pymt
$ conda activate pymt

Install the pymt_nwm using pip:

$ pip install pymt_nwm

Coding Example

import matplotlib.pyplot as plt
import numpy as np
import cftime

from pymt.models import Nwm

# initiate a data component
data_comp = Nwm()
data_comp.initialize('config_file.yaml')

# get variable info
var_name = data_comp.output_var_names[0]
var_unit = data_comp.var_units(var_name)
var_location = data_comp.var_location(var_name)
var_type = data_comp.var_type(var_name)
var_grid = data_comp.var_grid(var_name)

print('variable_name: {} \nvar_unit: {} \nvar_location: {} \nvar_type: {} \nvar_grid: {}'.format(
    var_name, var_unit, var_location, var_type, var_grid))

# get time info
start_time = data_comp.start_time
end_time = data_comp.end_time
time_step = data_comp.time_step
time_units = data_comp.time_units
time_steps = int((end_time - start_time)/time_step) + 1

print('start_time: {} \nend_time: {} \ntime_step: {} \ntime_units: {} \ntime_steps: {}'.format(
    start_time, end_time, time_step, time_units, time_steps))

# get variable data
stream_array = np.empty(time_steps)
cftime_array = np.empty(time_steps)

for i in range(0, time_steps):
    stream_array[i] = data_comp.get_value(var_name)
    cftime_array[i] = data_comp.time
    data_comp.update()

time_array = cftime.num2date(cftime_array, time_units, only_use_cftime_datetimes=False, only_use_python_datetimes=True )


# plot data
plt.figure(figsize=(9,5))
plt.plot(time_array, stream_array)
plt.xlabel('Year 2017')
plt.ylabel('{} ({})'.format(var_name, var_unit))
plt.title('Short range streamflow forecast for Channel 5781915 during Harvey Hurricane Event')

# complete the example by finalizing the component
data_comp.finalize()