ADD: New example showing how to use ACT to work with ARM and Satellit…

…e data

act/plotting/xsectiondisplay.py

@@ -146,13 +146,14 @@ def set_yrng(self, yrng, subplot_index=(0,)):
 
     def plot_xsection(
         self,
-        dsname,
-        varname,
+        field,
+        dsname=None,
         x=None,
         y=None,
         subplot_index=(0,),
         sel_kwargs=None,
         isel_kwargs=None,
+        set_title=None,
         **kwargs,
     ):
         """
@@ -162,11 +163,10 @@ def plot_xsection(
 
         Parameters
         ----------
-        dsname : str or None
-            The name of the datastream to plot from. Set to None to have
-            ACT attempt to automatically detect this.
-        varname : str
+        field : str
             The name of the variable to plot.
+        dsname : str or None
+            The name of the datastream to plot from.
         x : str or None
             The name of the x coordinate variable.
         y : str or None
@@ -181,6 +181,8 @@ def plot_xsection(
             to slice datasets, see the documentation on :func:`xarray.DataArray.sel`.
         isel_kwargs : dict
             The keyword arguments to pass into :py:func:`xarray.DataArray.sel`
+        set_title : str
+            Title for the plot
         **kwargs : keyword arguments
             Additional keyword arguments will be passed into
             :func:`xarray.DataArray.plot`.
@@ -220,9 +222,9 @@ def plot_xsection(
             y_coord_dim = temp_ds[y].dims[0]
             coord_list[y] = y_coord_dim
             new_ds = data_utils.assign_coordinates(temp_ds, coord_list)
-            my_dataarray = new_ds[varname]
+            my_dataarray = new_ds[field]
         else:
-            my_dataarray = temp_ds[varname]
+            my_dataarray = temp_ds[field]
 
         coord_keys = [key for key in my_dataarray.coords.keys()]
         # X-array will sometimes shorten latitude and longitude variables
@@ -255,28 +257,42 @@ def plot_xsection(
         self.set_xrng(xrng, subplot_index)
         yrng = self.axes[subplot_index].get_ylim()
         self.set_yrng(yrng, subplot_index)
+
+        if set_title is None:
+            if 'long_name' in self._ds[dsname][field].attrs:
+                set_title = self._ds[dsname][field].attrs['long_name']
+        plt.title(set_title)
+
         del temp_ds
         return self.axes[subplot_index]
 
     def plot_xsection_map(
-        self, dsname, varname, subplot_index=(0,), coastlines=True, background=False, **kwargs
+        self,
+        field,
+        dsname=None,
+        subplot_index=(0,),
+        coastlines=True,
+        background=False,
+        set_title=None,
+        **kwargs,
     ):
         """
         Plots a cross section of 2D data on a geographical map.
 
         Parameters
         ----------
-        dsname : str or None
-            The name of the datastream to plot from. Set to None
-            to have ACT attempt to automatically detect this.
-        varname : str
+        field : str
             The name of the variable to plot.
+        dsname : str or None
+            The name of the datastream to plot from.
         subplot_index : tuple
             The index of the subplot to plot inside.
         coastlines : bool
             Set to True to plot the coastlines.
         background : bool
             Set to True to plot a stock image background.
+        set_title : str
+            Title for the plot
         **kwargs : keyword arguments
             Additional keyword arguments will be passed into
             :func:`act.plotting.XSectionDisplay.plot_xsection`
@@ -292,7 +308,9 @@ def plot_xsection_map(
                 'Cartopy needs to be installed in order to plot ' + 'cross sections on maps!'
             )
         self.set_subplot_to_map(subplot_index)
-        self.plot_xsection(dsname, varname, subplot_index=subplot_index, **kwargs)
+        self.plot_xsection(
+            field, dsname=dsname, subplot_index=subplot_index, set_title=set_title, **kwargs
+        )
         xlims = self.xrng[subplot_index].flatten()
         ylims = self.yrng[subplot_index].flatten()
         self.axes[subplot_index].set_xticks(np.linspace(round(xlims[0], 0), round(xlims[1], 0), 10))

examples/plotting/plot_satellite.py

@@ -0,0 +1,52 @@
+"""
+Using ACT for Satellite data
+----------------------------
+
+Simple example for working with satellite data.
+It is recommended that users explore other
+satellite specific libraries suchas SatPy.
+
+Author: Adam Theisen
+"""
+
+import act
+import matplotlib.pyplot as plt
+import numpy as np
+from arm_test_data import DATASETS
+
+# Read in VISST Data
+files = DATASETS.fetch('enavisstgridm11minnisX1.c1.20230307.000000.cdf')
+ds = act.io.read_arm_netcdf(files)
+
+# Plot up the VISST cloud percentage using XSectionDisplay
+display = act.plotting.XSectionDisplay(ds, figsize=(10, 8))
+display.plot_xsection_map(
+    'cloud_percentage', x='longitude', y='latitude', isel_kwargs={'time': 0, 'cld_type': 0}
+)
+plt.show()
+
+# Download ARM TSI Data
+files = DATASETS.fetch('enatsiskycoverC1.b1.20230307.082100.cdf')
+ds_tsi = act.io.read_arm_netcdf(files)
+ds_tsi = ds_tsi.where(ds_tsi.percent_opaque > 0)
+
+# Set coordinates to extra data for ENA
+ena_lat = 39.091600
+ena_lon = 28.025700
+
+lat = ds['lat'].values
+lon = ds['lon'].values
+
+# Find the nearest pixel for the satellite data and extract it
+lat_ind = np.argmin(np.abs(lat - ena_lat))
+lon_ind = np.argmin(np.abs(lon - ena_lon))
+
+ds_new = ds.isel(lat=lat_ind, lon=lon_ind, cld_type=0)
+
+# Plot the comparison using TimeSeriesDisplay
+display = act.plotting.TimeSeriesDisplay({'Satellite': ds_new, 'ARM': ds_tsi}, figsize=(15, 8))
+display.plot('cloud_percentage', dsname='Satellite', label='VISST Cloud Percentage')
+display.plot('percent_opaque', dsname='ARM', label='ARM TSI Percent Opaque')
+display.day_night_background(dsname='ARM')
+plt.legend()
+plt.show()