Create Basic OmF/OmA Maps

LAMDA/map_departures.py

@@ -0,0 +1,120 @@
+import numpy as np
+import yaml
+import os
+from pathlib import Path
+import matplotlib.pyplot as plt
+import LAMDA.plot_features as features
+from LAMDA.no_data_plots import no_data_map
+from emcpy.plots.map_plots import MapScatter
+from emcpy.plots import CreateMap
+from emcpy.plots.map_tools import Domain, MapProjection
+from pyGSI.diags import Conventional, Radiance, Ozone
+
+
+def _create_map_departures(df, domain, projection,
+                           metadata, outdir):
+    """
+    Create the map figure and plot data.
+    """
+    # this for now puts all O-F/O-A together, might want to split by
+    # monitored/rejected/assim later
+    # grab variables for plotting
+    lats = df['latitude'].to_numpy()
+    lons = df['longitude'].to_numpy()
+    omf = df['omf_adjusted'].to_numpy()
+
+    plot_objects = []
+
+    # Create map object
+    mymap = CreateMap(figsize=(12, 8),
+                      domain=Domain(domain),
+                      proj_obj=MapProjection(projection))
+    # Add coastlines and states
+    mymap.add_features(['coastlines', 'states'])
+
+    # determine vmin/vmax for colorbar and must be symmetric
+    if len(lats) > 0:
+        omfscatter = MapScatter(latitude=lats,
+                                longitude=lons,
+                                data=omf)
+        omfscatter.markersize = 2
+        omfscatter.cmap = 'coolwarm'
+        # determine min/max of values
+        maxval = np.nanmax(omf)
+        minval = np.nanmin(omf)
+        vmax = max(abs(minval), maxval)
+        omfscatter.vmin = vmax * -1
+        omfscatter.vmax = vmax
+        # add data to plot objects
+        plot_objects.append(omfscatter)
+        # labels and annotations
+        labels = features.get_labels(metadata)
+        # draw data
+        mymap.draw_data(plot_objects)
+        # add labels
+        mymap.add_colorbar(label=metadata['Diag Type'],
+                           label_fontsize=12, extend='neither')
+        mymap.add_title(labels['title'], loc='left', fontsize=12)
+        mymap.add_title(labels['date title'], loc='right', fontsize=12,
+                        fontweight='semibold')
+        mymap.add_xlabel("Longitude", fontsize=12)
+        mymap.add_ylabel("Latitude", fontsize=12)
+        # add stats to figure
+        stats_dict = {
+            'nobs': len(lats),
+            'min': str(np.round(minval, 4)),
+            'max': str(np.round(maxval, 4)),
+        }
+        mymap.add_stats_dict(stats_dict=stats_dict)
+        # save figure
+        fig = mymap.return_figure()
+        str_domain = domain.replace(" ", "_")
+        plt.savefig(outdir + f"{labels['save file']}_{str_domain}.png",
+                    bbox_inches='tight', pad_inches=0.1)
+        plt.close('all')
+
+    else:
+        # no data to plot
+        fig = no_data_map(mymap, Domain(domain), metadata)
+
+
+def map_departures(config):
+    """
+    Create map of departures (O-F and O-A)
+
+    Args:
+        config : (dict) configuration file that includes the
+                 appropriate inputs based on file type (i.e.
+                 conventional or radiance data)
+    """
+
+    # Get filename to determing what the file type is
+    filename = os.path.splitext(Path(config['diag file']).stem)[0]
+    filetype = filename.split('_')[1]
+
+    if filetype == 'conv':
+        diag = Conventional(config['diag file'])
+        df = diag.get_data(obsid=[config['observation id']],
+                           subtype=[config['observation subtype']],
+                           analysis_use=config['analysis use'])
+        metadata = diag.metadata
+        metadata['ObsID Name'] = features.get_obs_type([config['observation id']])
+
+    else:
+        diag = Radiance(config['diag file'])
+        df = diag.get_data(channel=[config['channel']],
+                           analysis_use=config['analysis use'])
+        metadata = diag.metadata
+
+    metadata['Diag Type'] = config['data type']
+
+    anl_use = config['analysis use']
+    if anl_use:
+        for anl_type in df.keys():
+            metadata['Anl Use Type'] = anl_type
+            _create_map_departures(df[anl_type], config['domain'], config['projection'],
+                                   metadata, config['outdir'])
+    else:
+        metadata['Anl Use Type'] = None
+        _create_map_departures(df, config['domain'], config['projection'],
+                               metadata, config['outdir'])

LAMDA/scripts/LAMDA_mapping_workflow.py

@@ -5,6 +5,7 @@
 import itertools
 import argparse
 from LAMDA.map_qc_flags import map_qc_flags
+from LAMDA.map_departures import map_departures
 
 
 def create_mp_work_list(diag_inputs, plotting_config):
@@ -40,6 +41,7 @@ def plotting_func(config, diag_file, data_type='omf',
 
     plot_dict = {
         'qcflags': map_qc_flags,
+        'map departures': map_departures,
     }
 
     plot_dict[config['plot type']](config)