Merge pull request #3 from rcjackson/inital_repo

Initial repo

Author: rcjackson

examples/bnf_example.py

@@ -0,0 +1,42 @@
+import radclss
+import glob
+import xradar as xd
+import xarray as xr
+import matplotlib.pyplot as plt
+
+from dask.distributed import Client, LocalCluster
+
+def main():
+    date = '20250619'
+    radar_files = glob.glob(f'/Volumes/Untitled/bnf/bnfcsapr2cmacS3.c1/*{date}*.nc')
+    volumes = {'date': date,
+            'radar': radar_files[0:2],  # Limit to first 2 files for testing
+            'sonde': glob.glob(f'/Volumes/Untitled/bnf/in_situ/bnfsondewnpnM1.b1/*{date}*.cdf'),
+            'vd_M1': glob.glob(f'/Volumes/Untitled/bnf/in_situ/bnfvdisquantsM1.c1/*{date}*.nc'),
+            'met_M1': glob.glob(f'/Volumes/Untitled/bnf/in_situ/bnfmetM1.b1/*{date}*'),
+            'met_S20': glob.glob(f'/Volumes/Untitled/bnf/in_situ/bnfmetS20.b1/*{date}*'),
+            'met_S30': glob.glob(f'/Volumes/Untitled/bnf/in_situ/bnfmetS30.b1/*{date}*'),
+            'met_S40': glob.glob(f'/Volumes/Untitled/bnf/in_situ/bnfmetS40.b1/*{date}*'),
+            'wxt_S13': glob.glob(f'/Volumes/Untitled/bnf/in_situ/bnfmetwxtS13.b1/*{date}*.nc'),
+            'pluvio_M1': glob.glob(f'/Volumes/Untitled/bnf/in_situ/bnfwbpluvio2M1.a1/*{date}*.nc'),
+            'ld_M1': glob.glob(f'/Volumes/Untitled/bnf/in_situ/bnfldquantsM1.c1/*{date}*.nc'),
+            'ld_S30': glob.glob(f'/Volumes/Untitled/bnf/in_situ/bnfldquantsS30.c1/*{date}*.nc')}
+
+    input_site_dict = {'M1': (34.34525, -87.33842, 293),
+                    'S4': (34.46451, -87.23598, 197),
+                    'S20': (34.65401, -87.29264, 178),
+                    'S30': (34.38501, -86.92757, 183),
+                    'S40': (34.17932, -87.45349, 236),
+                    'S13': (34.343889, -87.350556, 286)}
+    with Client(LocalCluster(n_workers=2, threads_per_worker=1)) as client:
+        my_columns = radclss.core.radclss(volumes, input_site_dict, serial=False, verbose=True)
+    radclss.io.write_radclss_output(my_columns, 'radclss_example.nc', 'csapr2radclss.c2')
+
+    for vars in my_columns.data_vars:
+        print(vars, my_columns[vars].dtype)
+    fig, ax = radclss.vis.create_radclss_columns('radclss_example.nc')
+    print(fig)
+    plt.show()
+
+if __name__ == "__main__":
+    main()

radclss/core/radclss_core.py

@@ -11,7 +11,7 @@
 from dask.distributed import Client, as_completed
 
 def radclss(volumes, input_site_dict, serial=True, dod_version='', discard_var={}, verbose=False,
-            base_station="M1"):
+            base_station="M1", current_client=None):
     """
     Extracted Radar Columns and In-Situ Sensors
 
@@ -50,6 +50,9 @@ def radclss(volumes, input_site_dict, serial=True, dod_version='', discard_var={
         Option to print additional information during processing.
     base_station : str, Default = "M1"
         The base station name to use for time variables.
+    current_client : Dask Client, Default = None
+        Option to supply an existing Dask client for parallel processing.
+        Set to None to use the current active client.
 
     Returns
     -------
@@ -65,9 +68,11 @@ def radclss(volumes, input_site_dict, serial=True, dod_version='', discard_var={
     # Call Subset Points
     columns = []
     if serial == False:
-        current_client = Client.current()
         if current_client is None:
-            raise RuntimeError("No Dask client found. Please start a Dask client before running in parallel mode.")
+            try:
+                current_client = Client.current()
+            except ValueError:
+                raise RuntimeError("No Dask client found. Please start a Dask client before running in parallel mode.")
         results = current_client.map(subset_points, volumes["radar"], sonde=volumes["sonde"], input_site_dict=input_site_dict)
         for done_work in as_completed(results, with_results=False):
             try:
@@ -147,9 +152,7 @@ def radclss(volumes, input_site_dict, serial=True, dod_version='', discard_var={
     # Remove all the unused CMAC variables
     # Drop duplicate latitude and longitude
     del ds_concat       
-    #except ValueError as e:
-    #    print(f"Error concatenating columns: {e}")
-     #   ds = None
+    
 
     # Free up Memory
     del columns