ADD: radar_freq param in hydroclass_semisupervised (#1573)

* reformated, tests working * warnings * docs string * docs changed * old Note changed to reflect new addition * more description added * MOD: ipynb to py script * Delete:ipynb * comments added as per sphinx * comments added * example file renamed * used open_radar_data --------- Co-authored-by: Zach Sherman <[email protected]>
ARM-DOE · Jun 20, 2024 · a5ebda1 · a5ebda1
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diff --git a/examples/retrieve/hydrometeor-class.ipynb b/examples/retrieve/hydrometeor-class.ipynb
diff --git a/examples/retrieve/plot_hydrometeor_class_x_band.py b/examples/retrieve/plot_hydrometeor_class_x_band.py
@@ -0,0 +1,227 @@
+"""
+Hydrometeor Classification with Custom Frequency Settings
+===========================================================
+
+ This script shows how to use hydrometeor classification for X-band radar data.
+ We are reading radar data, plotting some variables of interest and applying the
+ classification to identify types of precipitation.
+
+ .. note::
+    The script initially attempts hydrometeor classification without specific radar frequency information for band selection.
+"""
+
+import matplotlib.pyplot as plt
+import numpy as np
+from open_radar_data import DATASETS
+
+import pyart
+
+filename = DATASETS.fetch("gucxprecipradarcmacppiS2.c1.20220314.025840.nc")
+radar = pyart.io.read_cfradial(filename)
+
+figure = plt.figure(figsize=(15, 4))
+
+ax1 = plt.subplot(1, 3, 1)
+display = pyart.graph.RadarDisplay(radar)
+ax1 = display.plot("DBZ", vmin=0, vmax=50)  # DBZ corrected_reflectivity
+plt.xlim(-20, 20)
+plt.ylim(-20, 20)
+
+ax2 = plt.subplot(1, 3, 2)
+ax2 = display.plot("corrected_differential_reflectivity", cmap="pyart_Carbone42")  # ZDR
+plt.xlim(-20, 20)
+plt.ylim(-20, 20)
+
+ax3 = plt.subplot(1, 3, 3)
+ax3 = display.plot("corrected_specific_diff_phase", cmap="pyart_Carbone42")  # KDP
+plt.xlim(-20, 20)
+
+# ### When instrument parameters does not have radar frequency info.
+
+print(radar.instrument_parameters)
+
+
+# This shows an issue where radar frequency information is missing. Without this hydrometeor classification will default to C-band.
+
+# Get classification
+hydromet_class = pyart.retrieve.hydroclass_semisupervised(
+    radar,
+    refl_field="corrected_reflectivity",
+    zdr_field="corrected_differential_reflectivity",
+    kdp_field="filtered_corrected_specific_diff_phase",
+    rhv_field="RHOHV",
+    temp_field="sounding_temperature",
+)
+
+radar.add_field("hydro_classification", hydromet_class, replace_existing=True)
+
+
+# Use `radar_freq` parameters
+# To address this issue, radar frequency information can be supplied to the function with `radar_freq` parameter.
+
+
+# Get classification
+hydromet_class = pyart.retrieve.hydroclass_semisupervised(
+    radar,
+    refl_field="corrected_reflectivity",
+    zdr_field="corrected_differential_reflectivity",
+    kdp_field="filtered_corrected_specific_diff_phase",
+    rhv_field="RHOHV",
+    temp_field="sounding_temperature",
+    radar_freq=9.2e9,
+)
+
+radar.add_field("hydro_classification", hydromet_class, replace_existing=True)
+
+
+# Add radar frequency to the radar object
+# Incorporating radar frequency into the radar object enhances processing pipeline.
+
+# Add X-band frequency information to radar.instrument_parameters
+radar.instrument_parameters["frequency"] = {
+    "long_name": "Radar frequency",
+    "units": "Hz",
+    "data": [9.2e9],
+}
+
+radar.instrument_parameters
+
+
+# Let's run the classification again and the warning should change telling the radar frequency from instrument parameters is used.
+
+
+hydromet_class = pyart.retrieve.hydroclass_semisupervised(
+    radar,
+    refl_field="corrected_reflectivity",
+    zdr_field="corrected_differential_reflectivity",
+    kdp_field="filtered_corrected_specific_diff_phase",
+    rhv_field="RHOHV",
+    temp_field="sounding_temperature",
+    radar_freq=9.2e9,
+)
+
+radar.add_field("hydro_classification", hydromet_class, replace_existing=True)
+
+
+# Note that the frequency used here is from the radar object, not the user supplied.
+
+
+# plotting
+
+import matplotlib.colors as colors
+
+hid_colors = [
+    "White",
+    "LightBlue",
+    "MediumBlue",
+    "DarkOrange",
+    "LightPink",
+    "Cyan",
+    "DarkGray",
+    "Lime",
+    "Yellow",
+    "Red",
+    "Fuchsia",
+]
+cmaphid = colors.ListedColormap(hid_colors)
+cmapmeth = colors.ListedColormap(hid_colors[0:6])
+cmapmeth_trop = colors.ListedColormap(hid_colors[0:7])
+
+
+def adjust_fhc_colorbar_for_pyart(cb):
+    cb.set_ticks(np.arange(1.4, 10, 0.9))
+    cb.ax.set_yticklabels(
+        [
+            "Drizzle",
+            "Rain",
+            "Ice Crystals",
+            "Aggregates",
+            "Wet Snow",
+            "Vertical Ice",
+            "LD Graupel",
+            "HD Graupel",
+            "Hail",
+            "Big Drops",
+        ]
+    )
+    cb.ax.set_ylabel("")
+    cb.ax.tick_params(length=0)
+    return cb
+
+
+def adjust_meth_colorbar_for_pyart(cb, tropical=False):
+    if not tropical:
+        cb.set_ticks(np.arange(1.25, 5, 0.833))
+        cb.ax.set_yticklabels(
+            ["R(Kdp, Zdr)", "R(Kdp)", "R(Z, Zdr)", "R(Z)", "R(Zrain)"]
+        )
+    else:
+        cb.set_ticks(np.arange(1.3, 6, 0.85))
+        cb.ax.set_yticklabels(
+            ["R(Kdp, Zdr)", "R(Kdp)", "R(Z, Zdr)", "R(Z_all)", "R(Z_c)", "R(Z_s)"]
+        )
+    cb.ax.set_ylabel("")
+    cb.ax.tick_params(length=0)
+    return cb
+
+
+def two_panel_plot(
+    radar,
+    sweep=0,
+    var1="corrected_reflectivity",
+    vmin1=0,
+    vmax1=65,
+    cmap1="RdYlBu_r",
+    units1="dBZ",
+    var2="corrected_differential_reflectivity",
+    vmin2=-5,
+    vmax2=5,
+    cmap2="RdYlBu_r",
+    units2="dB",
+    return_flag=False,
+    xlim=[-150, 150],
+    ylim=[-150, 150],
+):
+    display = pyart.graph.RadarDisplay(radar)
+    fig = plt.figure(figsize=(13, 5))
+    ax1 = fig.add_subplot(121)
+    display.plot_ppi(
+        var1,
+        sweep=sweep,
+        vmin=vmin1,
+        vmax=vmax1,
+        cmap=cmap1,
+        colorbar_label=units1,
+        mask_outside=True,
+    )
+    display.set_limits(xlim=xlim, ylim=ylim)
+    ax2 = fig.add_subplot(122)
+    display.plot_ppi(
+        var2,
+        sweep=sweep,
+        vmin=vmin2,
+        vmax=vmax2,
+        cmap=cmap2,
+        colorbar_label=units2,
+        mask_outside=True,
+    )
+    display.set_limits(xlim=xlim, ylim=ylim)
+    if return_flag:
+        return fig, ax1, ax2, display
+
+
+lim = [-20, 20]
+fig, ax1, ax2, display = two_panel_plot(
+    radar,
+    sweep=0,
+    var1="corrected_reflectivity",
+    var2="hydro_classification",
+    vmin2=0,
+    vmax2=10,
+    cmap2=cmaphid,
+    units2="",
+    return_flag=True,
+    xlim=lim,
+    ylim=lim,
+)
+display.cbs[1] = adjust_fhc_colorbar_for_pyart(display.cbs[1])