TST: Adding unit tests for whole echoclass module.

pyart/retrieve/tests/test_echo_class.py

@@ -1,6 +1,7 @@
 """ Unit Tests for Py-ART's retrieve/echo_class.py module. """
 
 import numpy as np
+from numpy.testing import assert_allclose
 import pytest
 
 import pyart
@@ -20,3 +21,181 @@ def test_steiner_conv_strat_modify_area(area_relation):
                                                area_relation=area_relation)
     assert eclass['data'].min() == 0
     assert eclass['data'].max() == 2
+
+
+def test_hydroclass_semisupervised():
+    radar = pyart.io.read(pyart.testing.NEXRAD_ARCHIVE_MSG31_FILE)
+    temp_dict = pyart.config.get_metadata('temperature')
+    temp = np.empty(radar.fields['reflectivity']['data'].shape)
+    temp[:] = -10.0
+    temp_dict['data'] = temp
+    radar.add_field('temperature', temp_dict, replace_existing=True)
+    radar.fields['specific_differential_phase'] = radar.fields.pop('differential_phase')
+    radar_small = radar.extract_sweeps([0])
+
+    mass_centers = pyart.retrieve.echo_class._get_mass_centers(10e9)
+
+    hydro_nofreq = pyart.retrieve.hydroclass_semisupervised(radar_small)
+    assert 'units' in hydro_nofreq.keys()
+    assert 'standard_name' in hydro_nofreq.keys()
+    assert 'long_name' in hydro_nofreq.keys()
+    assert 'coordinates' in hydro_nofreq.keys()
+
+    assert hydro_nofreq['data'].dtype == 'int64'
+    assert_allclose(
+        hydro_nofreq['data'][0][0:5],
+        [6, 6, 6, 6, 6])
+    assert_allclose(
+        hydro_nofreq['data'][0][-5:],
+        [2, 2, 2, 2, 2])
+
+    radar_small.instrument_parameters['frequency'] = {'data': np.array([5e9])}
+    hydro_freq = pyart.retrieve.hydroclass_semisupervised(radar_small)
+    assert_allclose(
+        hydro_freq['data'][0][0:5],
+        [6, 6, 6, 6, 6])
+    assert_allclose(
+        hydro_freq['data'][0][-5:],
+        [2, 2, 2, 2, 2])
+
+    hydro = pyart.retrieve.hydroclass_semisupervised(
+        radar_small, mass_centers=mass_centers)
+    assert_allclose(
+        hydro['data'][0][0:5],
+        [6, 6, 6, 6, 6])
+    assert_allclose(
+        hydro['data'][0][-5:],
+       [2, 2, 2, 2, 2])
+
+
+def test_data_limits_table():
+    dlimits_dict = pyart.retrieve.echo_class._data_limits_table()
+    test_dict = {'Zh': (60.0, -10.0),
+                 'ZDR': (5.0, -5.0),
+                 'KDP': (7.0, -10.0),
+                 'RhoHV': (-5.23, -50.0)}
+
+    assert type(dlimits_dict) == dict
+    assert dlimits_dict == test_dict
+
+
+def test_get_freq():
+    freq_band_s = pyart.retrieve.get_freq_band(3e9)
+    assert freq_band_s == 'S'
+
+    freq_band_c = pyart.retrieve.get_freq_band(6e9)
+    assert freq_band_c == 'C'
+
+    freq_band_x = pyart.retrieve.get_freq_band(10e9)
+    assert freq_band_x == 'X'
+
+    freq_band_bad = pyart.retrieve.get_freq_band(10)
+    assert freq_band_bad == None
+
+
+def test_mass_centers_dict():
+    mass_centers_dict =  pyart.retrieve.echo_class._mass_centers_table()
+
+    assert type(mass_centers_dict)
+    assert 'C' in mass_centers_dict.keys()
+    assert 'X' in mass_centers_dict.keys()
+
+    assert_allclose(
+        mass_centers_dict['C'][0],
+        [1.35829e+01,  4.06300e-01,  4.97000e-02,  9.86800e-01,
+         1.33030e+03], atol=1e-7)
+    assert_allclose(
+        mass_centers_dict['C'][8],
+        [5.06186e+01, -6.49000e-02,  9.46000e-02,  9.90400e-01,
+         1.17990e+03], atol=1e-7)
+
+    assert_allclose(
+        mass_centers_dict['X'][0],
+        [1.9077e+01, 4.1390e-01, 9.9000e-03, 9.8410e-01,
+         1.0617e+03], atol=1e-7)
+
+    assert_allclose(
+        mass_centers_dict['X'][8],
+        [4.42216e+01, -3.41900e-01,  6.87000e-02,  9.68300e-01,
+         1.27270e+03], atol=1e-7)
+
+
+def test_mass_centers():
+    mass_centers_good_freq = pyart.retrieve.echo_class._get_mass_centers(10e9)
+    assert_allclose(
+        mass_centers_good_freq[0],
+        [1.90770e+01,  4.13900e-01,  9.90000e-03,  9.84100e-01,
+         1.06170e+03], atol=1e-7)
+
+    low_bad_freq = pyart.retrieve.echo_class._get_mass_centers(3e9)
+    assert_allclose(
+        low_bad_freq[0],
+        [1.35829e+01,  4.06300e-01,  4.97000e-02,  9.86800e-01,
+         1.33030e+03], atol=1e-7)
+
+    high_bad_freq = pyart.retrieve.echo_class._get_mass_centers(13e9)
+    assert_allclose(
+        high_bad_freq[0],
+        [1.90770e+01,  4.13900e-01,  9.90000e-03,  9.84100e-01,
+         1.06170e+03], atol=1e-7)
+
+
+def test_assign_to_class():
+    rhohv = np.array(([0.2, 0.2, 0.2, 0.2, 0.2],
+                      [0.2, 0.2, 0.2, 0.2, 0.2]))
+    zdr = np.array(([-7.8, -7.8, -7.8, -7.8, -7.8],
+                    [-7.8, -7.8, -7.8, -7.8, -7.8]))
+    kdp = np.array(([180.5, 180.5, 180.5, 180.5, 180.5],
+                    [180.5, 180.5, 180.5, 180.5, 180.5]))
+    relh = np.array(([10.0, 10.0, 10.0, 10.0, 10.0],
+                     [10.0, 10.0, 10.0, 10.0, 10.0]))
+    zh = np.array(([-32.0, -32.0, -32.0, -32.0, -32.0],
+                   [-32.0, -32.0, -32.0, -32.0, -32.0]))
+
+    mass_centers = pyart.retrieve.echo_class._get_mass_centers(10e9)
+    hydroclass, min_dist = pyart.retrieve.echo_class._assign_to_class(
+        zh, zdr, kdp, rhohv, relh, mass_centers)
+
+    assert_allclose(hydroclass[0], [7, 7, 7, 7, 7], atol=1e-7)
+    assert_allclose(
+        min_dist[0],
+        [227.0343910, 227.0343910, 227.0343910,
+         227.0343910, 227.0343910], atol=1e-7)
+
+
+def test_standardize():
+    kdp = np.array(([180.5, 180.5, 180.5, 180.5, 180.5],
+                    [180.5, 180.5, 180.5, 180.5, 180.5]))
+    field_std_kdp = pyart.retrieve.echo_class._standardize(
+        kdp, 'KDP', mx=180.0, mn=181.0)
+    assert_allclose(field_std_kdp[0],
+                    [-1.0, -1.0, -1.0, -1.0, -1.0],
+                    atol=1e-6)
+
+    relh = np.array(([10.0, 10.0, 10.0, 10.0, 10.0],
+                     [10.0, 10.0, 10.0, 10.0, 10.0]))
+    field_std_relh = pyart.retrieve.echo_class._standardize(
+        relh, 'relH', mx=9.0, mn=5.0)
+    assert_allclose(
+        field_std_relh[0],
+        [0.024994, 0.024994, 0.024994, 0.024994, 0.024994],
+        atol=1e-6)
+
+    rhohv = np.array(([0.2, 0.2, 0.2, 0.2, 0.2],
+                      [0.2, 0.2, 0.2, 0.2, 0.2]))
+    field_std_rhohv = pyart.retrieve.echo_class._standardize(
+        rhohv, 'RhoHV', mx=0.1, mn=1.0)
+    assert_allclose(
+        field_std_rhohv[0],
+        [-1.0, -1.0, -1.0, -1.0, -1.0],
+        atol=1e-6)
+
+    field_std_no_limits = pyart.retrieve.echo_class._standardize(
+        rhohv, 'RhoHV', mx=None, mn=None)
+    assert_allclose(
+        field_std_no_limits[0],
+        [1.0, 1.0, 1.0, 1.0, 1.0],
+        atol=1e-6)
+
+    pytest.raises(
+        ValueError, pyart.retrieve.echo_class._standardize, rhohv, 'foo')