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Updated Documentation for retrieve/hydroclass_semisupervised function #1616

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32 changes: 28 additions & 4 deletions pyart/retrieve/echo_class.py
Original file line number Diff line number Diff line change
Expand Up @@ -612,8 +612,10 @@ def hydroclass_semisupervised(
radar_freq=None,
):
"""
Classifies precipitation echoes following the approach by Besic et al
(2016).
Classifies precipitation echoes into hydrometeor types.

The `hydroclass_semisupervised` function classifies precipitation echoes in the polarimetric radar data
into 9 hydrometeor types using a semi-supervised approach (Besic et al., 2016).

Parameters
----------
Expand Down Expand Up @@ -642,7 +644,17 @@ def hydroclass_semisupervised(
Returns
-------
hydro : dict
Hydrometeor classification field.
Hydrometeor classification.
- 0: Not classified
- 1: Aggregates
- 2: Ice crystals
- 3: Light rain
- 4: Rimed particles
- 5: Rain
- 6: Vertically oriented ice
- 7: Wet snow
- 8: Melting hail
- 9: Dry hail or high-density graupel

References
----------
Expand All @@ -651,6 +663,18 @@ def hydroclass_semisupervised(
of polarimetric radar measurements: a semi-supervised approach,
Atmos. Meas. Tech., 9, 4425-4445, doi:10.5194/amt-9-4425-2016, 2016

Usage
-----
.. code-block:: python
hydro_class = pyart.retrieve.hydroclass_semisupervised(
radar,
refl_field="corrected_reflectivity",
zdr_field="corrected_differential_reflectivity",
kdp_field="specific_differential_phase",
rhv_field="uncorrected_cross_correlation_ratio",
temp_field="temperature",
)

Notes
-----
The default hydrometeor classification is valid for C-band radars. For X-band radars,
Expand All @@ -660,8 +684,8 @@ def hydroclass_semisupervised(

If the radar frequency information is missing from the radar object, you can add it in
`radar.instrument_parameters`, as follows:
.. code-block:: python

.. code-block:: python
radar.instrument_parameters["frequency"] = {
"long_name": "Radar frequency",
"units": "Hz",
Expand Down