ENH: Use arm-test-data repo for unit testing

act/tests/sample_files.py

@@ -6,68 +6,131 @@
 
 import os
 
-DATA_PATH = os.path.join(os.path.dirname(__file__), 'data')
+from arm_test_data import DATASETS
 
-EXAMPLE_MET1 = os.path.join(DATA_PATH, 'sgpmetE13.b1.20190101.000000.cdf')
-EXAMPLE_MET_SAIL = os.path.join(DATA_PATH, 'gucmetM1.b1.20230301.000000.cdf')
-EXAMPLE_MET_CSV = os.path.join(DATA_PATH, 'sgpmetE13.*csv')
-EXAMPLE_METE40 = os.path.join(DATA_PATH, 'sgpmetE40.b1.20190508.000000.cdf')
-EXAMPLE_CEIL1 = os.path.join(DATA_PATH, 'sgpceilC1.b1.20190101.000000.nc')
-EXAMPLE_SONDE1 = os.path.join(DATA_PATH, 'sgpsondewnpnC1.b1.20190101.053200.cdf')
-EXAMPLE_LCL1 = os.path.join(DATA_PATH, 'met_lcl.nc')
-EXAMPLE_SONDE_WILDCARD = os.path.join(DATA_PATH, 'sgpsondewnpn*.cdf')
-EXAMPLE_MET_WILDCARD = os.path.join(DATA_PATH, 'sgpmet*201901*.cdf')
-EXAMPLE_MET_CONTOUR = os.path.join(DATA_PATH, 'sgpmet*20190508*.cdf')
-EXAMPLE_CEIL_WILDCARD = os.path.join(DATA_PATH, 'sgpceil*.cdf')
-EXAMPLE_TWP_SONDE_WILDCARD = os.path.join(DATA_PATH, 'twpsondewnpn*.cdf')
-EXAMPLE_TWP_SONDE_20060121 = os.path.join(DATA_PATH, 'twpsondewnpn*20060121*.cdf')
-EXAMPLE_ANL_CSV = os.path.join(DATA_PATH, 'anltwr_mar19met.data')
-EXAMPLE_VISST = os.path.join(DATA_PATH, 'twpvisstgridirtemp.c1.20050705.002500.nc')
-EXAMPLE_MPL_1SAMPLE = os.path.join(DATA_PATH, 'sgpmplpolfsC1.b1.20190502.000000.cdf')
-EXAMPLE_IRT25m20s = os.path.join(DATA_PATH, 'sgpirt25m20sC1.a0.20190601.000000.cdf')
-EXAMPLE_NAV = os.path.join(DATA_PATH, 'marnavM1.a1.20180201.000000.nc')
-EXAMPLE_AOSMET = os.path.join(DATA_PATH, 'maraosmetM1.a1.20180201.000000.nc')
-EXAMPLE_DLPPI = os.path.join(DATA_PATH, 'sgpdlppiC1.b1.20191015.120023.cdf')
-EXAMPLE_DLPPI_MULTI = os.path.join(DATA_PATH, 'sgpdlppiC1.b1.20191015.*.cdf')
-EXAMPLE_BRS = os.path.join(DATA_PATH, 'sgpbrsC1.b1.20190705.000000.cdf')
-EXAMPLE_AERI = os.path.join(DATA_PATH, 'sgpaerich1C1.b1.20190501.000342.nc')
-EXAMPLE_IRTSST = os.path.join(DATA_PATH, 'marirtsstM1.b1.20190320.000000.nc')
-EXAMPLE_MFRSR = os.path.join(DATA_PATH, 'sgpmfrsr7nchE11.b1.20210329.070000.nc')
-EXAMPLE_SURFSPECALB1MLAWER = os.path.join(
-    DATA_PATH, 'nsasurfspecalb1mlawerC1.c1.20160609.080000.nc'
+# Single files
+EXAMPLE_MET1 = DATASETS.fetch('sgpmetE13.b1.20190101.000000.cdf')
+EXAMPLE_MET_SAIL = DATASETS.fetch('gucmetM1.b1.20230301.000000.cdf')
+EXAMPLE_MET_CSV = DATASETS.fetch('sgpmetE13.b1.20210401.000000.csv')
+EXAMPLE_METE40 = DATASETS.fetch('sgpmetE40.b1.20190508.000000.cdf')
+EXAMPLE_CEIL1 = DATASETS.fetch('sgpceilC1.b1.20190101.000000.nc')
+EXAMPLE_SONDE1 = DATASETS.fetch('sgpsondewnpnC1.b1.20190101.053200.cdf')
+EXAMPLE_LCL1 = DATASETS.fetch('met_lcl.nc')
+EXAMPLE_ANL_CSV = DATASETS.fetch('anltwr_mar19met.data')
+EXAMPLE_VISST = DATASETS.fetch('twpvisstgridirtemp.c1.20050705.002500.nc')
+EXAMPLE_MPL_1SAMPLE = DATASETS.fetch('sgpmplpolfsC1.b1.20190502.000000.cdf')
+EXAMPLE_IRT25m20s = DATASETS.fetch('sgpirt25m20sC1.a0.20190601.000000.cdf')
+EXAMPLE_NAV = DATASETS.fetch('marnavM1.a1.20180201.000000.nc')
+EXAMPLE_AOSMET = DATASETS.fetch('maraosmetM1.a1.20180201.000000.nc')
+EXAMPLE_DLPPI = DATASETS.fetch('sgpdlppiC1.b1.20191015.120023.cdf')
+EXAMPLE_BRS = DATASETS.fetch('sgpbrsC1.b1.20190705.000000.cdf')
+EXAMPLE_AERI = DATASETS.fetch('sgpaerich1C1.b1.20190501.000342.nc')
+EXAMPLE_IRTSST = DATASETS.fetch('marirtsstM1.b1.20190320.000000.nc')
+EXAMPLE_MFRSR = DATASETS.fetch('sgpmfrsr7nchE11.b1.20210329.070000.nc')
+EXAMPLE_SURFSPECALB1MLAWER = DATASETS.fetch(
+    'nsasurfspecalb1mlawerC1.c1.20160609.080000.nc'
 )
-EXAMPLE_SIGMA_MPLV5 = os.path.join(DATA_PATH, '201509021500.bi')
-EXAMPLE_RL1 = os.path.join(DATA_PATH, 'sgprlC1.a0.20160131.000000.nc')
-EXAMPLE_CO2FLX4M = os.path.join(DATA_PATH, 'sgpco2flx4mC1.b1.20201007.001500.nc')
-EXAMPLE_SIRS = os.path.join(DATA_PATH, 'sgpsirsE13.b1.20190101.000000.cdf')
-EXAMPLE_GML_RADIATION = os.path.join(DATA_PATH, 'brw21001.dat')
-EXAMPLE_GML_MET = os.path.join(DATA_PATH, 'met_brw_insitu_1_obop_hour_2020.txt')
-EXAMPLE_GML_OZONE = os.path.join(DATA_PATH, 'brw_12_2020_hour.dat')
-EXAMPLE_GML_CO2 = os.path.join(DATA_PATH, 'co2_brw_surface-insitu_1_ccgg_MonthlyData.txt')
-EXAMPLE_GML_HALO = os.path.join(DATA_PATH, 'brw_CCl4_Day.dat')
-EXAMPLE_MET_TEST1 = os.path.join(DATA_PATH, 'sgpmet_no_time.nc')
-EXAMPLE_MET_TEST2 = os.path.join(DATA_PATH, 'sgpmet_test_time.nc')
-EXAMPLE_STAMP_WILDCARD = os.path.join(DATA_PATH, 'sgpstamp*202001*.nc')
-EXAMPLE_NOAA_PSL = os.path.join(DATA_PATH, 'ctd21125.15w')
-EXAMPLE_NOAA_PSL_TEMPERATURE = os.path.join(DATA_PATH, 'ctd22187.00t.txt')
-EXAMPLE_NOAA_PSL_SURFACEMET = [os.path.join(DATA_PATH, 'ayp22199.21m'), os.path.join(DATA_PATH, 'ayp22200.00m')]
-EXAMPLE_SP2B = os.path.join(DATA_PATH, 'mosaossp2M1.00.20191216.130601.raw.20191216x193.sp2b')
-EXAMPLE_INI = os.path.join(DATA_PATH, 'mosaossp2M1.00.20191216.000601.raw.20191216000000.ini')
-EXAMPLE_HK = os.path.join(DATA_PATH, 'mosaossp2auxM1.00.20191217.010801.raw.20191216000000.hk')
-EXAMPLE_MET_YAML = os.path.join(DATA_PATH, 'sgpmetE13.b1.yaml')
-EXAMPLE_CLOUDPHASE = os.path.join(DATA_PATH, 'nsacloudphaseC1.c1.20180601.000000.nc')
-EXAMPLE_AAF_ICARTT = os.path.join(DATA_PATH, 'AAFNAV_COR_20181104_R0.ict')
-EXAMPLE_MMCR = os.path.join(DATA_PATH, 'sgpmmcrC1.b1.*.cdf')
-EXAMPLE_NEON = os.path.join(DATA_PATH, 'NEON.D18.BARR.DP1.00002.001.000.010.001.SAAT_1min.2022-10.expanded.20221107T205629Z.csv')
-EXAMPLE_NEON_VARIABLE = os.path.join(DATA_PATH, 'NEON.D18.BARR.DP1.00002.001.variables.20221201T110553Z.csv')
-EXAMPLE_NEON_POSITION = os.path.join(DATA_PATH, 'NEON.D18.BARR.DP1.00002.001.sensor_positions.20221107T205629Z.csv')
-EXAMPLE_DOD = os.path.join(DATA_PATH, 'vdis.b1')
-EXAMPLE_EBBR1 = os.path.join(DATA_PATH, 'sgp30ebbrE32.b1.20191125.000000.nc')
-EXAMPLE_EBBR2 = os.path.join(DATA_PATH, 'sgp30ebbrE32.b1.20191130.000000.nc')
-EXAMPLE_EBBR3 = os.path.join(DATA_PATH, 'sgp30ebbrE13.b1.20190601.000000.nc')
-EXAMPLE_ECOR = os.path.join(DATA_PATH, 'sgp30ecorE14.b1.20190601.000000.cdf')
-EXAMPLE_SEBS = os.path.join(DATA_PATH, 'sgpsebsE14.b1.20190601.000000.cdf')
-EXAMPLE_MFAS_SODAR = os.path.join(DATA_PATH, 'sodar.20230404.mnd')
-EXAMPLE_ENA_MET = os.path.join(DATA_PATH, 'enametC1.b1.20221109.000000.cdf')
-EXAMPLE_CCN = os.path.join(DATA_PATH, 'sgpaosccn2colaE13.b1.20170903.000000.nc')
-EXAMPLE_OLD_QC = os.path.join(DATA_PATH, 'sgp30ecorE6.b1.20040705.000000.cdf')
+EXAMPLE_SIGMA_MPLV5 = DATASETS.fetch('201509021500.bi')
+EXAMPLE_RL1 = DATASETS.fetch('sgprlC1.a0.20160131.000000.nc')
+EXAMPLE_CO2FLX4M = DATASETS.fetch('sgpco2flx4mC1.b1.20201007.001500.nc')
+EXAMPLE_SIRS = DATASETS.fetch('sgpsirsE13.b1.20190101.000000.cdf')
+EXAMPLE_GML_RADIATION = DATASETS.fetch('brw21001.dat')
+EXAMPLE_GML_MET = DATASETS.fetch('met_brw_insitu_1_obop_hour_2020.txt')
+EXAMPLE_GML_OZONE = DATASETS.fetch('brw_12_2020_hour.dat')
+EXAMPLE_GML_CO2 = DATASETS.fetch('co2_brw_surface-insitu_1_ccgg_MonthlyData.txt')
+EXAMPLE_GML_HALO = DATASETS.fetch('brw_CCl4_Day.dat')
+EXAMPLE_MET_TEST1 = DATASETS.fetch('sgpmet_no_time.nc')
+EXAMPLE_MET_TEST2 = DATASETS.fetch('sgpmet_test_time.nc')
+EXAMPLE_NOAA_PSL = DATASETS.fetch('ctd21125.15w')
+EXAMPLE_NOAA_PSL_TEMPERATURE = DATASETS.fetch('ctd22187.00t.txt')
+EXAMPLE_SP2B = DATASETS.fetch('mosaossp2M1.00.20191216.130601.raw.20191216x193.sp2b')
+EXAMPLE_INI = DATASETS.fetch('mosaossp2M1.00.20191216.000601.raw.20191216000000.ini')
+EXAMPLE_HK = DATASETS.fetch('mosaossp2auxM1.00.20191217.010801.raw.20191216000000.hk')
+EXAMPLE_MET_YAML = DATASETS.fetch('sgpmetE13.b1.yaml')
+EXAMPLE_CLOUDPHASE = DATASETS.fetch('nsacloudphaseC1.c1.20180601.000000.nc')
+EXAMPLE_AAF_ICARTT = DATASETS.fetch('AAFNAV_COR_20181104_R0.ict')
+EXAMPLE_NEON = DATASETS.fetch('NEON.D18.BARR.DP1.00002.001.000.010.001.SAAT_1min.2022-10.expanded.20221107T205629Z.csv')
+EXAMPLE_NEON_VARIABLE = DATASETS.fetch('NEON.D18.BARR.DP1.00002.001.variables.20221201T110553Z.csv')
+EXAMPLE_NEON_POSITION = DATASETS.fetch('NEON.D18.BARR.DP1.00002.001.sensor_positions.20221107T205629Z.csv')
+EXAMPLE_DOD = DATASETS.fetch('vdis.b1')
+EXAMPLE_EBBR1 = DATASETS.fetch('sgp30ebbrE32.b1.20191125.000000.nc')
+EXAMPLE_EBBR2 = DATASETS.fetch('sgp30ebbrE32.b1.20191130.000000.nc')
+EXAMPLE_EBBR3 = DATASETS.fetch('sgp30ebbrE13.b1.20190601.000000.nc')
+EXAMPLE_ECOR = DATASETS.fetch('sgp30ecorE14.b1.20190601.000000.cdf')
+EXAMPLE_SEBS = DATASETS.fetch('sgpsebsE14.b1.20190601.000000.cdf')
+EXAMPLE_MFAS_SODAR = DATASETS.fetch('sodar.20230404.mnd')
+EXAMPLE_ENA_MET = DATASETS.fetch('enametC1.b1.20221109.000000.cdf')
+EXAMPLE_CCN = DATASETS.fetch('sgpaosccn2colaE13.b1.20170903.000000.nc')
+EXAMPLE_OLD_QC = DATASETS.fetch('sgp30ecorE6.b1.20040705.000000.cdf')
+EXAMPLE_SONDE_WILDCARD = DATASETS.fetch('sgpsondewnpnC1.b1.20190101.053200.cdf')
+EXAMPLE_CEIL_WILDCARD = DATASETS.fetch('sgpceilC1.b1.20190101.000000.nc')
+
+# Multiple files in a list
+dlppi_multi_list = ['sgpdlppiC1.b1.20191015.120023.cdf',
+                    'sgpdlppiC1.b1.20191015.121506.cdf']
+EXAMPLE_DLPPI_MULTI = [DATASETS.fetch(file) for file in dlppi_multi_list]
+noaa_psl_list = ['ayp22199.21m',
+                 'ayp22200.00m']
+EXAMPLE_NOAA_PSL_SURFACEMET = [DATASETS.fetch(file) for file in noaa_psl_list]
+met_wildcard_list = ['sgpmetE13.b1.20190101.000000.cdf',
+                     'sgpmetE13.b1.20190102.000000.cdf',
+                     'sgpmetE13.b1.20190103.000000.cdf',
+                     'sgpmetE13.b1.20190104.000000.cdf',
+                     'sgpmetE13.b1.20190105.000000.cdf',
+                     'sgpmetE13.b1.20190106.000000.cdf',
+                     'sgpmetE13.b1.20190107.000000.cdf']
+EXAMPLE_MET_WILDCARD = [DATASETS.fetch(file) for file in met_wildcard_list]
+met_contour_list = ['sgpmetE15.b1.20190508.000000.cdf',
+                    'sgpmetE31.b1.20190508.000000.cdf',
+                    'sgpmetE32.b1.20190508.000000.cdf',
+                    'sgpmetE33.b1.20190508.000000.cdf',
+                    'sgpmetE34.b1.20190508.000000.cdf',
+                    'sgpmetE35.b1.20190508.000000.cdf',
+                    'sgpmetE36.b1.20190508.000000.cdf',
+                    'sgpmetE37.b1.20190508.000000.cdf',
+                    'sgpmetE38.b1.20190508.000000.cdf',
+                    'sgpmetE39.b1.20190508.000000.cdf',
+                    'sgpmetE40.b1.20190508.000000.cdf',
+                    'sgpmetE9.b1.20190508.000000.cdf',
+                    'sgpmetE13.b1.20190508.000000.cdf']
+EXAMPLE_MET_CONTOUR = [DATASETS.fetch(file) for file in met_contour_list]
+twp_sonde_wildcard_list = ['twpsondewnpnC3.b1.20060119.050300.custom.cdf',
+                           'twpsondewnpnC3.b1.20060119.112000.custom.cdf',
+                           'twpsondewnpnC3.b1.20060119.163300.custom.cdf',
+                           'twpsondewnpnC3.b1.20060119.231600.custom.cdf',
+                           'twpsondewnpnC3.b1.20060120.043800.custom.cdf',
+                           'twpsondewnpnC3.b1.20060120.111900.custom.cdf',
+                           'twpsondewnpnC3.b1.20060120.170800.custom.cdf',
+                           'twpsondewnpnC3.b1.20060120.231500.custom.cdf',
+                           'twpsondewnpnC3.b1.20060121.051500.custom.cdf',
+                           'twpsondewnpnC3.b1.20060121.111600.custom.cdf',
+                           'twpsondewnpnC3.b1.20060121.171600.custom.cdf',
+                           'twpsondewnpnC3.b1.20060121.231600.custom.cdf',
+                           'twpsondewnpnC3.b1.20060122.052600.custom.cdf',
+                           'twpsondewnpnC3.b1.20060122.111500.custom.cdf',
+                           'twpsondewnpnC3.b1.20060122.171800.custom.cdf',
+                           'twpsondewnpnC3.b1.20060122.232600.custom.cdf',
+                           'twpsondewnpnC3.b1.20060123.052500.custom.cdf',
+                           'twpsondewnpnC3.b1.20060123.111700.custom.cdf',
+                           'twpsondewnpnC3.b1.20060123.171600.custom.cdf',
+                           'twpsondewnpnC3.b1.20060123.231500.custom.cdf',
+                           'twpsondewnpnC3.b1.20060124.051500.custom.cdf',
+                           'twpsondewnpnC3.b1.20060124.111800.custom.cdf',
+                           'twpsondewnpnC3.b1.20060124.171700.custom.cdf',
+                           'twpsondewnpnC3.b1.20060124.231500.custom.cdf']
+EXAMPLE_TWP_SONDE_WILDCARD = [DATASETS.fetch(file) for file in twp_sonde_wildcard_list]
+twp_sonde_20060121_list = ['twpsondewnpnC3.b1.20060121.051500.custom.cdf',
+                           'twpsondewnpnC3.b1.20060121.111600.custom.cdf',
+                           'twpsondewnpnC3.b1.20060121.171600.custom.cdf',
+                           'twpsondewnpnC3.b1.20060121.231600.custom.cdf']
+EXAMPLE_TWP_SONDE_20060121 = [DATASETS.fetch(file) for file in twp_sonde_20060121_list]
+stamp_wildcard_list = ['sgpstampE13.b1.20200101.000000.nc',
+                       'sgpstampE31.b1.20200101.000000.nc',
+                       'sgpstampE32.b1.20200101.000000.nc',
+                       'sgpstampE33.b1.20200101.000000.nc',
+                       'sgpstampE34.b1.20200101.000000.nc',
+                       'sgpstampE9.b1.20200101.000000.nc']
+EXAMPLE_STAMP_WILDCARD = [DATASETS.fetch(file) for file in stamp_wildcard_list]
+mmcr_list = ['sgpmmcrC1.b1.1.cdf',
+             'sgpmmcrC1.b1.2.cdf']
+EXAMPLE_MMCR = [DATASETS.fetch(file) for file in mmcr_list]

act/tests/test_io.py

@@ -108,8 +108,7 @@ def test_keep_variables():
     assert list(ds.data_vars).sort() == var_names.sort()
     del ds
 
-    filenames = Path(act.tests.EXAMPLE_MET_WILDCARD).parent
-    filenames = list(filenames.glob(Path(act.tests.EXAMPLE_MET_WILDCARD).name))
+    filenames = list(Path(file) for file in act.tests.EXAMPLE_MET_WILDCARD)
     var_names = ['temp_mean', 'qc_temp_mean', 'alt', 'lat', 'lon']
     ds = act.io.arm.read_arm_netcdf(filenames, keep_variables=var_names)
     assert list(ds.data_vars).sort() == var_names.sort()
@@ -794,8 +793,7 @@ def test_gunzip():
 def test_read_netcdf_tarfiles():
 
     with tempfile.TemporaryDirectory() as tmpdirname:
-        met_files = Path(act.tests.EXAMPLE_MET_WILDCARD)
-        met_files = list(Path(met_files.parent).glob(met_files.name))
+        met_files = list(Path(file) for file in act.tests.EXAMPLE_MET_WILDCARD)
         filename = act.utils.io_utils.pack_tar(met_files, write_directory=tmpdirname)
         ds = act.io.arm.read_arm_netcdf(filename)
         ds.clean.cleanup()
@@ -805,8 +803,7 @@ def test_read_netcdf_tarfiles():
 
 def test_read_netcdf_gztarfiles():
     with tempfile.TemporaryDirectory() as tmpdirname:
-        met_files = Path(act.tests.EXAMPLE_MET_WILDCARD)
-        met_files = list(Path(met_files.parent).glob(met_files.name))
+        met_files = list(Path(file) for file in act.tests.EXAMPLE_MET_WILDCARD)
         filename = act.utils.io_utils.pack_tar(met_files, write_directory=tmpdirname)
         filename = act.utils.io_utils.pack_gzip(filename, write_directory=tmpdirname, remove=True)
         ds = act.io.arm.read_arm_netcdf(filename)
@@ -824,7 +821,7 @@ def test_read_netcdf_gztarfiles():
 
 
 def test_read_mmcr():
-    results = glob.glob(act.tests.EXAMPLE_MMCR)
+    results = act.tests.EXAMPLE_MMCR
     ds = act.io.arm.read_arm_mmcr(results)
     assert 'MeanDopplerVelocity_PR' in ds
     assert 'SpectralWidth_BL' in ds

act/tests/test_plotting.py

@@ -334,7 +334,7 @@ def test_skewt_plot_spd_dir():
 
 @pytest.mark.mpl_image_compare(tolerance=81)
 def test_multi_skewt_plot():
-    files = glob.glob(sample_files.EXAMPLE_TWP_SONDE_20060121)
+    files = sample_files.EXAMPLE_TWP_SONDE_20060121
     test = {}
     for f in files:
         time = f.split('.')[-3]
@@ -603,7 +603,7 @@ def test_size_distribution():
 
 @pytest.mark.mpl_image_compare(tolerance=30)
 def test_contour():
-    files = glob.glob(sample_files.EXAMPLE_MET_CONTOUR)
+    files = sample_files.EXAMPLE_MET_CONTOUR
     time = '2019-05-08T04:00:00.000000000'
     data = {}
     fields = {}
@@ -631,7 +631,7 @@ def test_contour():
 
 @pytest.mark.mpl_image_compare(tolerance=30)
 def test_contour_stamp():
-    files = glob.glob(sample_files.EXAMPLE_STAMP_WILDCARD)
+    files = sample_files.EXAMPLE_STAMP_WILDCARD
     test = {}
     stamp_fields = {}
     time = '2020-01-01T00:00:00.000000000'
@@ -653,7 +653,7 @@ def test_contour_stamp():
 
 @pytest.mark.mpl_image_compare(tolerance=30)
 def test_contour2():
-    files = glob.glob(sample_files.EXAMPLE_MET_CONTOUR)
+    files = sample_files.EXAMPLE_MET_CONTOUR
     time = '2019-05-08T04:00:00.000000000'
     data = {}
     fields = {}
@@ -681,7 +681,7 @@ def test_contour2():
 
 @pytest.mark.mpl_image_compare(tolerance=30)
 def test_contourf():
-    files = glob.glob(sample_files.EXAMPLE_MET_CONTOUR)
+    files = sample_files.EXAMPLE_MET_CONTOUR
     time = '2019-05-08T04:00:00.000000000'
     data = {}
     fields = {}
@@ -721,7 +721,7 @@ def test_contourf():
 
 @pytest.mark.mpl_image_compare(tolerance=30)
 def test_contourf2():
-    files = glob.glob(sample_files.EXAMPLE_MET_CONTOUR)
+    files = sample_files.EXAMPLE_MET_CONTOUR
     time = '2019-05-08T04:00:00.000000000'
     data = {}
     fields = {}
@@ -1031,7 +1031,7 @@ def test_colorbar_labels():
 
 @pytest.mark.mpl_image_compare(tolerance=30)
 def test_plot_datarose():
-    files = glob.glob(sample_files.EXAMPLE_MET_WILDCARD)
+    files = sample_files.EXAMPLE_MET_WILDCARD
     ds = act.io.arm.read_arm_netcdf(files)
     display = act.plotting.WindRoseDisplay(ds, subplot_shape=(2, 3), figsize=(16, 10))
     display.plot_data(
@@ -1208,7 +1208,7 @@ def test_groupby_plot():
 
 @pytest.mark.mpl_image_compare(tolerance=30)
 def test_match_ylimits_plot():
-    files = glob.glob(sample_files.EXAMPLE_MET_WILDCARD)
+    files = sample_files.EXAMPLE_MET_WILDCARD
     ds = act.io.arm.read_arm_netcdf(files)
     display = act.plotting.TimeSeriesDisplay(ds, figsize=(10, 8), subplot_shape=(2, 2))
     groupby = display.group_by('day')

act/tests/test_retrievals.py

@@ -178,9 +178,9 @@ def test_calculate_sirs_variable():
 
 
 def test_calculate_pbl_liu_liang():
-    files = glob.glob(act.tests.sample_files.EXAMPLE_TWP_SONDE_20060121)
-    files2 = glob.glob(act.tests.sample_files.EXAMPLE_SONDE1)
-    files += files2
+    files = act.tests.sample_files.EXAMPLE_TWP_SONDE_20060121.copy()
+    files2 = act.tests.sample_files.EXAMPLE_SONDE1
+    files.append(files2)
     files.sort()
 
     pblht = []
@@ -237,7 +237,8 @@ def test_calculate_pbl_liu_liang():
 
 
 def test_calculate_heffter_pbl():
-    files = sorted(glob.glob(act.tests.sample_files.EXAMPLE_TWP_SONDE_20060121))
+    files = act.tests.sample_files.EXAMPLE_TWP_SONDE_20060121.copy()
+    files.sort()
     ds = act.io.arm.read_arm_netcdf(files[2])
     ds['tdry'].attrs['units'] = 'degree_Celsius'
     ds = act.retrievals.sonde.calculate_pbl_heffter(ds)

continuous_integration/environment_actions.yml

@@ -27,6 +27,7 @@ dependencies:
   - pip
   - lazy_loader
   - cmweather
+  - arm-test-data
   - pip:
     - mpl2nc
     - metpy

docs/environment_docs.yml

@@ -18,6 +18,7 @@ dependencies:
   - scikit-posthocs
   - pip
   - shapely<1.8.3
+  - arm-test-data
   - pip:
     - mpl2nc
     - lazy_loader

examples/plotting/plot_contour.py

@@ -15,7 +15,7 @@
 
 import act
 
-files = glob.glob(act.tests.sample_files.EXAMPLE_MET_CONTOUR)
+files = act.tests.sample_files.EXAMPLE_MET_CONTOUR
 time = '2019-05-08T04:00:00.000000000'
 data = {}
 fields = {}

examples/plotting/plot_skewt_with_text.py

@@ -22,7 +22,7 @@
 xr.set_options(keep_attrs=True)
 
 # Read data
-file = sorted(glob.glob(act.tests.sample_files.EXAMPLE_TWP_SONDE_20060121))[-1]
+file = sorted(act.tests.sample_files.EXAMPLE_TWP_SONDE_20060121)[-1]
 sonde_ds = act.io.arm.read_arm_netcdf(file)
 
 

examples/utils/plot_tar.py

@@ -27,8 +27,7 @@
 # TAR file into read_arm_netcdf() to be unpacked and read.
 
 # Here we get a list of MET data files to pack into a TAR bundle
-met_files = Path(EXAMPLE_MET_WILDCARD)
-met_files = list(Path(met_files.parent).glob(met_files.name))
+met_files = list(Path(file) for file in EXAMPLE_MET_WILDCARD)
 
 # We can pass the list of netCDF data files to the pack_tar() function.
 # Notice that the new_dir directory does not exist. The directory will