NEW: Adding new example for working with CoURAGE data sources

examples/workflows/plot_courage_comparison.py

@@ -0,0 +1,120 @@
+"""
+Consolidation of CoURAGE Data Sources
+-------------------------------------
+
+This example shows how to use ACT to combine multiple
+datasets to support ARM's CoURAGE deployment in
+Baltimore, MD.  Example uses ARM, EPA, and ASOS data.
+
+"""
+
+import act
+from datetime import datetime
+import matplotlib.pyplot as plt
+import numpy as np
+import os
+
+# Get Surface Meteorology data
+lat = (39.04, 39.6)
+lon = (-77.10, -76.04)
+time_window = [datetime(2024, 12, 15), datetime(2024, 12, 20)]
+asos_dict = act.discovery.get_asos_data(time_window, lat_range=lat, lon_range=lon, regions='MD')
+asos_stations = asos_dict.keys()
+
+# Set up a dictionary to fill with data
+data_dict = {}
+
+# Fill the dictionary with ASOS data
+for s in asos_stations:
+    ds = asos_dict[s]
+    ds = ds.where(~np.isnan(ds.tmpf), drop=True)
+    ds['tmpf'].attrs['units'] = 'degF'
+    ds.utils.change_units(variables='tmpf', desired_unit='degC', verbose=True)
+    data_dict[s] = ds
+
+# You need an account and token from https://docs.airnowapi.org/ first
+# And then you can download EPA data
+airnow_token = os.getenv('AIRNOW_API')
+if airnow_token is not None and len(airnow_token) > 0:
+    latlon = '-76.905,39.185,-76.158,39.499'
+
+    ds_airnow = act.discovery.get_airnow_bounded_obs(
+        airnow_token, '2024-12-15T00', '2024-12-20T23', latlon, 'OZONE,PM25', data_type='B'
+    )
+    ds_airnow = act.utils.convert_2d_to_1d(ds_airnow, parse='sites')
+    sites = ds_airnow['sites'].values
+    data_dict['EPA'] = ds_airnow
+    airnow = True
+
+# Place your username and token here
+username = os.getenv('ARM_USERNAME')
+token = os.getenv('ARM_PASSWORD')
+
+# Download ARM data
+if username is not None and token is not None and len(username) > 1:
+    # Example to show how easy it is to download ARM data if a username/token are set
+    sdate = '2024-12-15'
+    edate = '2024-12-20'
+
+    # Download and read ARM MET data
+    results = act.discovery.download_arm_data(username, token, 'crgmetM1.b1', sdate, edate)
+    ds_arm = act.io.arm.read_arm_netcdf(results)
+    data_dict['ARM'] = ds_arm
+
+    # Download and read ARM Ozone data
+    results = act.discovery.download_arm_data(username, token, 'crgaoso3S2.a1', sdate, edate)
+    ds_o3 = act.io.arm.read_arm_netcdf(results, cleanup_qc=True)
+    ds_o3.qcfilter.datafilter('o3', rm_assessments=['Suspect', 'Bad'], del_qc_var=False)
+    data_dict['ARM_O3'] = ds_o3
+
+    # Download and read ARM SMPS data
+    results = act.discovery.download_arm_data(username, token, 'crgaossmpsS2.b1', sdate, edate)
+    ds_smps = act.io.arm.read_arm_netcdf(results)
+    data_dict['ARM_SMPS'] = ds_smps
+
+    # Set up plot and plot all surface temperature data
+    display = act.plotting.TimeSeriesDisplay(data_dict, figsize=(12, 10), subplot_shape=(3,))
+    for k in data_dict.keys():
+        if 'ARM' not in k and k != 'EPA':
+            display.plot('tmpf', dsname=k, label=k, subplot_index=(0,))
+        elif k == 'ARM':
+            display.plot('temp_mean', dsname=k, label=k, subplot_index=(0,))
+            display.day_night_background(dsname='ARM', subplot_index=(0,))
+
+    display.set_yrng([-5, 20], subplot_index=(0,))
+
+    # Plot up ozone data
+    title = 'Comparison of ARM and EPA Ozone Measurements'
+    display.plot('o3', dsname='ARM_O3', label='ARM', subplot_index=(1,))
+    if airnow:
+        display.plot(
+            'OZONE_sites_2',
+            dsname='EPA ',
+            label='EPA' + sites[2],
+            subplot_index=(1,),
+            set_title=title,
+        )
+    display.set_yrng([0, 60], subplot_index=(1,))
+    display.day_night_background(dsname='ARM', subplot_index=(1,))
+
+    # Plot SMPS data
+    title = 'ARM SMPS Concentrations and EPA PM2.5'
+    if airnow:
+        display.plot('PM2.5_sites_0', dsname='EPA', label='EPA ' + sites[0], subplot_index=(2,))
+        display.plot('PM2.5_sites_1', dsname='EPA', label='EPA ' + sites[1], subplot_index=(2,))
+        display.plot(
+            'PM2.5_sites_3',
+            dsname='EPA',
+            label='EPA ' + sites[3],
+            subplot_index=(2,),
+            set_title=title,
+        )
+
+    display.set_yrng([0, 30], subplot_index=(2,))
+    plt.legend(loc=2)
+    ax2 = display.axes[2].twinx()
+    ax2.plot(ds_smps['time'], ds_smps['total_N_conc'], color='purple')
+    ax2.set_ylabel('ARM SMPS (' + ds_smps['total_N_conc'].attrs['units'] + ')')
+    display.day_night_background(dsname='ARM', subplot_index=(2,))
+
+    plt.show()