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BMI prototype for Hyfeature network #598

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A prototype of wrapping BMI around t-route with Hyfeature networks is produced here. So far, BMI around initialize and set_value functions were successfully made. The initialize function prepares channel network connectivity and config file parameter values. Also, it prepares sets of forcing files and sets of TimeSlice files for each time loop and sets of CHRTOUT files against which to compare t-route flows. Finally, it coverts lateral flow dataframe into one element of BMI dictionary data.

** This is only a prototype (not to be merged yet) and more updates yet to come.

Additions

Removals

Changes

Testing

  1. In t-route/test/unit_test_hyfeature/
    python3 run-troute-with-bmi.py

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Notes

Todos

Checklist

  • PR has an informative and human-readable title
  • Changes are limited to a single goal (no scope creep)
  • Code can be automatically merged (no conflicts)
  • Code follows project standards (link if applicable)
  • Passes all existing automated tests
  • Any change in functionality is tested
  • New functions are documented (with a description, list of inputs, and expected output)
  • Placeholder code is flagged / future todos are captured in comments
  • Visually tested in supported browsers and devices (see checklist below 👇)
  • Project documentation has been updated (including the "Unreleased" section of the CHANGELOG)
  • Reviewers requested with the Reviewers tool ➡️

Testing checklist

Target Environment support

  • Windows
  • Linux
  • Browser

Accessibility

  • Keyboard friendly
  • Screen reader friendly

Other

  • Is useable without CSS
  • Is useable without JS
  • Flexible from small to large screens
  • No linting errors or warnings
  • JavaScript tests are passing
  • [ ]


# -------------- Initalize all the variables --------------------------#
# -------------- so that they'll be picked up with the get functions --#
for var_name in list(self._var_name_units_map.keys()):
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Creating a list here is unnecessary. The keys can be iterated thru directly.
for var_name in self._var_nname_units_map:

int
Rank of grid.
"""
return len(self._model.shape)
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@groutr groutr Dec 9, 2022

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If self._model is a numpy array, we can simply return self._model.ndim

int
Size of grid.
"""
return int(np.prod(self._model.shape))
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If self._model is a numpy array, we can return self._model.size

return self._name

def get_input_item_count(self):
"""Get names of input variables."""
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Docstring doesn't make sense here.

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