Merge pull request ARM-Development#59 from zssherman/open_radar

ENH: Add open_radar_data for testing and examples.

continuous_integration/environment_actions.yml

@@ -18,3 +18,5 @@ dependencies:
   - coveralls
   - pre-commit
   - pip
+  - pip:
+      - git+https://github.com/openradar/open-radar-data

continuous_integration/environment_documentation.yml

@@ -23,3 +23,5 @@ dependencies:
   - sphinx-gallery
   - sphinx-rtd-theme
   - urllib3
+  - pip:
+      - git+https://github.com/openradar/open-radar-data

examples/plot_cfad.py

@@ -8,11 +8,13 @@
 
 import matplotlib.pyplot as plt
 from act.io.armfiles import read_netcdf
+from open_radar_data import DATASETS
 
 import radtraq
 
 # Read in example data
-ds = read_netcdf(radtraq.tests.sample_files.EXAMPLE_KAZR)
+filename = DATASETS.fetch('sgpkazrgeC1.a1.20190529.000002.cdf')
+ds = read_netcdf(filename)
 
 # Calculate CFAD histogram
 data_array = radtraq.plotting.cfad.calc_cfad(ds, 'reflectivity_copol')

examples/plot_cloud_mask.py

@@ -9,11 +9,13 @@
 
 import act
 import matplotlib.pyplot as plt
+from open_radar_data import DATASETS
 
 import radtraq
 
 # Read in sample data using ACT
-ds = act.io.armfiles.read_netcdf(radtraq.tests.sample_files.EXAMPLE_KAZR)
+filename = DATASETS.fetch('sgpkazrgeC1.a1.20190529.000002.cdf')
+ds = act.io.armfiles.read_netcdf(filename)
 
 # Resample data for ease of processing
 ds = ds.resample(time='1min').nearest()

examples/plot_corner_reflector_raster.py

@@ -8,14 +8,15 @@
 
 """
 
-
 import matplotlib.pyplot as plt
 from act.io.armfiles import read_netcdf
+from open_radar_data import DATASETS
 
 import radtraq
 
 # Read in sample data using ACT
-ds = read_netcdf(radtraq.tests.sample_files.EXAMPLE_RASTER)
+filename = DATASETS.fetch('sgpkasacrcrrasterC1.a1.20130419.012153.nc')
+ds = read_netcdf(filename)
 
 # Process and plot raster file
 data = radtraq.plotting.corner_reflector.plot_cr_raster(

examples/plot_mask_vpt.py

@@ -11,17 +11,19 @@
 import matplotlib.pyplot as plt
 import numpy as np
 from act.io.armfiles import read_netcdf
+from open_radar_data import DATASETS
 
 import radtraq
 
 # Read in Example KAZR File using ACT
-obj = read_netcdf(radtraq.tests.sample_files.EXAMPLE_KAZR)
+filename = DATASETS.fetch('sgpkazrgeC1.a1.20190529.000002.cdf')
+ds = read_netcdf(filename)
 
 # Resample to 1-minute to simplify processing
-obj = obj.resample(time='1min').nearest()
+ds = ds.resample(time='1min').nearest()
 
 # Process cloud mask in order to properly produce average VPT profiles through cloud
-obj = radtraq.proc.cloud_mask.calc_cloud_mask(obj, 'reflectivity_copol')
+ds = radtraq.proc.cloud_mask.calc_cloud_mask(ds, 'reflectivity_copol')
 
 # Variables to calculate average profiles
 variable = ['reflectivity_copol', 'mean_doppler_velocity_copol', 'reflectivity_xpol']
@@ -31,17 +33,17 @@
 ygrid = np.arange(first_height, 15000, 50)
 
 # Calculate average profiles
-obj = radtraq.proc.profile.calc_avg_profile(
-    obj, variable=variable, first_height=first_height, ygrid=ygrid
+ds = radtraq.proc.profile.calc_avg_profile(
+    ds, variable=variable, first_height=first_height, ygrid=ygrid
 )
 
 # Showing how to do this for multiple radars
 # Set up dictionary for profile comparison plotting
 rad_dict = {
-    'sgpkazrgeC1.b1': {'object': obj, 'variable': variable[0]},
-    'sgpkazrge2C1.b1': {'object': obj, 'variable': variable[0]},
-    'sgpkazrmdC1.b1': {'object': obj, 'variable': 'reflectivity_xpol'},
-    'sgpkazrmd2C1.b1': {'object': obj, 'variable': 'reflectivity_xpol'},
+    'sgpkazrgeC1.b1': {'object': ds, 'variable': variable[0]},
+    'sgpkazrge2C1.b1': {'object': ds, 'variable': variable[0]},
+    'sgpkazrmdC1.b1': {'object': ds, 'variable': 'reflectivity_xpol'},
+    'sgpkazrmd2C1.b1': {'object': ds, 'variable': 'reflectivity_xpol'},
 }
 
 # Plot up profiles and perform comparisons from data in dictionary
@@ -51,4 +53,4 @@
 plt.show()
 
 # Close out object
-obj.close()
+ds.close()

examples/plot_self_consistency.py

@@ -8,11 +8,13 @@
 
 import matplotlib.pyplot as plt
 from act.io.armfiles import read_netcdf
+from open_radar_data import DATASETS
 
 import radtraq
 
 # Read in example data
-ds = read_netcdf(radtraq.tests.sample_files.EXAMPLE_CSAPR)
+filename = DATASETS.fetch('csapr.nc')
+ds = read_netcdf(filename)
 
 # Set thresholds of RhoHv > 0.99
 thresh = {'copol_correlation_coeff': 0.99}

examples/plot_zdr_check.py

@@ -8,11 +8,13 @@
 
 import matplotlib.pyplot as plt
 from act.io.armfiles import read_netcdf
+from open_radar_data import DATASETS
 
 import radtraq
 
 # Read in example data
-ds = read_netcdf(radtraq.tests.sample_files.EXAMPLE_XSAPR)
+filename = DATASETS.fetch('sgpxsaprcfrvptI4.a1.20200205.100827.nc')
+ds = read_netcdf(filename)
 thresh = {'cross_correlation_ratio_hv': [0.995, 1], 'reflectivity': [10, 30], 'range': [1000, 3000]}
 # Call RadTraQ function
 results = radtraq.proc.calc_zdr_offset(ds, zdr_var='differential_reflectivity', thresh=thresh)

radtraq/tests/sample_files.py

@@ -9,14 +9,18 @@
     :toctree: generated/
 
     EXAMPLE_KAZR
-"""
-import os
+    EXAMPLE_RASTER
+    EXAMPLE_PPI
+    EXAMPLE_RHI
+    EXAMPLE_XSAPR
+    EXAMPLE_CSAPR
 
-DATA_PATH = os.path.join(os.path.dirname(__file__), 'data')
+"""
+from open_radar_data import DATASETS
 
-EXAMPLE_KAZR = os.path.join(DATA_PATH, 'sgpkazrgeC1.a1.20190529.000002.cdf')
-EXAMPLE_RASTER = os.path.join(DATA_PATH, 'sgpkasacrcrrasterC1.a1.20130419.012153.nc')
-EXAMPLE_PPI = os.path.join(DATA_PATH, 'houkasacrcfrM1.a1.20210922.150006.nc')
-EXAMPLE_RHI = os.path.join(DATA_PATH, 'houkasacrcfrM1.a1.20211122.164124.nc')
-EXAMPLE_XSAPR = os.path.join(DATA_PATH, 'sgpxsaprcfrvptI4.a1.20200205.100827.nc')
-EXAMPLE_CSAPR = os.path.join(DATA_PATH, 'csapr.nc')
+EXAMPLE_KAZR = DATASETS.fetch('sgpkazrgeC1.a1.20190529.000002.cdf')
+EXAMPLE_RASTER = DATASETS.fetch('sgpkasacrcrrasterC1.a1.20130419.012153.nc')
+EXAMPLE_PPI = DATASETS.fetch('houkasacrcfrM1.a1.20210922.150006.nc')
+EXAMPLE_RHI = DATASETS.fetch('houkasacrcfrM1.a1.20211122.164124.nc')
+EXAMPLE_XSAPR = DATASETS.fetch('sgpxsaprcfrvptI4.a1.20200205.100827.nc')
+EXAMPLE_CSAPR = DATASETS.fetch('csapr.nc')

radtraq/tests/test_plotting.py

@@ -4,15 +4,15 @@
 from act.io.armfiles import read_netcdf
 from matplotlib.figure import Figure
 
+import radtraq
 from radtraq.plotting.cfad import calc_cfad, plot_cfad
 from radtraq.plotting.corner_reflector import plot_cr_raster
 from radtraq.plotting.self_consistency import plot_self_consistency
-from radtraq.tests.sample_files import EXAMPLE_CSAPR, EXAMPLE_KAZR, EXAMPLE_RASTER
 
 
 @pytest.mark.mpl_image_compare(tolerance=10)
 def test_plotting():
-    obj = read_netcdf(EXAMPLE_KAZR)
+    obj = read_netcdf(radtraq.tests.sample_files.EXAMPLE_KAZR)
 
     np.seterr(divide='ignore')
     data_array = calc_cfad(obj, 'reflectivity_copol')
@@ -23,7 +23,7 @@ def test_plotting():
 
 @pytest.mark.mpl_image_compare(tolerance=10)
 def test_corner_reflector():
-    obj = read_netcdf(EXAMPLE_RASTER)
+    obj = read_netcdf(radtraq.tests.sample_files.EXAMPLE_RASTER)
     data = plot_cr_raster(obj, target_range=478.0, el_limits=[-0.5, 2.5], noplot=False)
 
     np.testing.assert_almost_equal(data['max'], 12.09, decimal=2)
@@ -41,7 +41,7 @@ def test_corner_reflector():
 
 @pytest.mark.mpl_image_compare(tolerance=10)
 def test_self_consistency():
-    obj = read_netcdf(EXAMPLE_CSAPR)
+    obj = read_netcdf(radtraq.tests.sample_files.EXAMPLE_CSAPR)
     thresh = {'copol_correlation_coeff': 0.99}
     # Set up dictionary of variables to plot
     var_dict = {

requirements.txt

@@ -7,3 +7,4 @@ xarray
 matplotlib
 netcdf4
 pint
+open_radar_data