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ocssw
V2022
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MDN.benchmarks Namespace Reference
Namespaces | |
| _template | |
| meta | |
| utils | |
Functions | |
| def | get_models (wavelengths, sensor, product, debug=False, allow_opt=False, method=None, **kwargs) |
| def | run_benchmarks (sensor, x_test, y_test=None, x_train=None, y_train=None, slices=None, args=None, *product='chl', bands=None, verbose=False, return_rs=True, return_ml=False, return_opt=False, kwargs_rs={}, kwargs_ml={}, kwargs_opt={}) |
Function Documentation
◆ get_models()
| def MDN.benchmarks.get_models | ( | wavelengths, | |
| sensor, | |||
| product, | |||
debug = False, |
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allow_opt = False, |
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method = None, |
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| ** | kwargs | ||
| ) |
Retrieve all benchmark functions from the appropriate product
directory. Import each function with "model" in the function
name, ensure any necessary parameters have a default value
available, and test whether the function can be run with the
given wavelengths. A template folder for new algorithms is
available in the Benchmarks directory.
Definition at line 14 of file __init__.py.
◆ run_benchmarks()
| def MDN.benchmarks.run_benchmarks | ( | sensor, | |
| x_test, | |||
y_test = None, |
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x_train = None, |
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y_train = None, |
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slices = None, |
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args = None, |
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| * | product = 'chl', |
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bands = None, |
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verbose = False, |
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return_rs = True, |
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return_ml = False, |
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return_opt = False, |
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kwargs_rs = {}, |
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kwargs_ml = {}, |
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kwargs_opt = {} |
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| ) |
Definition at line 51 of file __init__.py.
