Merge branch 'master' of https://github.com/NCAR/ldcpy

ldcpy/plot.py

@@ -45,6 +45,7 @@ def __init__(
         quantile=None,
         calc_ssim=False,
         contour_levs=24,
+        vert_plot=False,
     ):
 
         self._ds = ds
@@ -71,6 +72,7 @@ def __init__(
         self._quantile = None
         self._calc_ssim = calc_ssim
         self._contour_levs = contour_levs
+        self.vert_plot = vert_plot
 
     def verify_plot_parameters(self):
         if len(self._sets) < 2 and self._metric_type in [
@@ -223,7 +225,10 @@ def update_label(event_axes):
         return
 
     def spatial_plot(self, da_sets, titles):
-        nrows = int((da_sets.sets.size + 1) / 2)
+        if self.vert_plot:
+            nrows = int((da_sets.sets.size))
+        else:
+            nrows = int((da_sets.sets.size + 1) / 2)
         if len(da_sets) == 1:
             ncols = 1
         else:
@@ -238,7 +243,10 @@ def spatial_plot(self, da_sets, titles):
         for i in range(da_sets.sets.size):
             cy_datas[i], lon_sets[i] = add_cyclic_point(da_sets[i], coord=da_sets[i]['lon'])
 
-        fig = plt.figure(dpi=300, figsize=(9, 2.5 * nrows))
+        if self.vert_plot:
+            fig = plt.figure(dpi=300, figsize=(4.5, 2.5 * nrows))
+        else:
+            fig = plt.figure(dpi=300, figsize=(9, 2.5 * nrows))
 
         mymap = copy.copy(mpl.cm.get_cmap(f'{self._color}'))
         mymap.set_under(color='black')
@@ -248,9 +256,14 @@ def spatial_plot(self, da_sets, titles):
         axs = {}
         psets = {}
         for i in range(da_sets.sets.size):
-            axs[i] = plt.subplot(
-                nrows, ncols, i + 1, projection=ccrs.Robinson(central_longitude=0.0)
-            )
+            if self.vert_plot:
+                axs[i] = plt.subplot(
+                    nrows, 1, i + 1, projection=ccrs.Robinson(central_longitude=0.0)
+                )
+            else:
+                axs[i] = plt.subplot(
+                    nrows, ncols, i + 1, projection=ccrs.Robinson(central_longitude=0.0)
+                )
 
             axs[i].set_facecolor('#39ff14')
 
@@ -292,7 +305,8 @@ def spatial_plot(self, da_sets, titles):
             axs[i].set_title(titles[i])
 
         # add colorbar
-        fig.subplots_adjust(left=0.1, right=0.9, bottom=0.2, top=0.95)
+        if self.vert_plot is False:
+            fig.subplots_adjust(left=0.1, right=0.9, bottom=0.2, top=0.95)
 
         cbs = []
         if not all([np.isnan(cy_datas[i]).all() for i in range(len(cy_datas))]):
@@ -346,7 +360,12 @@ def hist_plot(self, plot_data, title):
         else:
             mpl.pyplot.xlabel(f'{self._metric}')
         mpl.pyplot.title(f'time-series histogram: {title[0]}')
-        plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', borderaxespad=0.0)
+        if self.vert_plot:
+            plt.legend(loc='upper right', borderaxespad=1.0)
+            plt.rcParams.update({'font.size': 16})
+        else:
+            plt.rcParams.update({'font.size': 10})
+            plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', borderaxespad=0.0)
 
     def periodogram_plot(self, plot_data, title):
         plt.figure()
@@ -361,7 +380,13 @@ def periodogram_plot(self, plot_data, title):
             freqs = np.array(range(1, int(dat.size / 2))) / dat.size
 
             mpl.pyplot.plot(freqs, i, label=plot_data[j].sets.data)
-        plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', borderaxespad=0.0)
+        if self.vert_plot:
+            plt.legend(loc='upper right', borderaxespad=1.0)
+            plt.rcParams.update({'font.size': 16})
+        else:
+            plt.rcParams.update({'font.size': 10})
+            plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', borderaxespad=0.0)
+
         mpl.pyplot.title(f'periodogram: {title[0]}')
         mpl.pyplot.ylabel('Spectrum')
         mpl.pyplot.xlabel('Frequency')
@@ -415,6 +440,11 @@ def time_series_plot(
         mpl.style.use('default')
 
         plt.figure()
+        if self.vert_plot:
+            plt.rcParams.update({'font.size': 16})
+        else:
+            plt.rcParams.update({'font.size': 10})
+
         for i in range(da_sets.sets.size):
             if self._group_by is not None:
                 plt.plot(
@@ -438,7 +468,11 @@ def time_series_plot(
                 mpl.pyplot.plot(c_d_time, da_sets[i], f'C{i}', label=f'{da_sets.sets.data[i]}')
                 ax = plt.gca()
 
-        plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', borderaxespad=0.0)
+        if self.vert_plot:
+            plt.legend(loc='upper right', borderaxespad=1.0)
+        else:
+            plt.rcParams.update({'font.size': 10})
+            plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', borderaxespad=0.0)
         mpl.pyplot.ylabel(plot_ylabel)
         mpl.pyplot.yscale(self._scale)
         self._label_offset(ax)
@@ -455,7 +489,7 @@ def time_series_plot(
                 ]
                 unique_month_labels = list(dict.fromkeys(month_labels))
                 plt.gca().set_xticklabels(unique_month_labels)
-                plt.xticks(rotation=45)
+                plt.xticks(rotation=90)
         # else:
         #    mpl.pyplot.xticks(
         #        pd.date_range(
@@ -510,6 +544,7 @@ def plot(
     start=None,
     end=None,
     calc_ssim=False,
+    vert_plot=False,
 ):
     """
     Plots the data given an xarray dataset
@@ -639,6 +674,7 @@ class in ldcpy.plot, for more information about the available metrics see ldcpy.
         standardized_err,
         quantile,
         calc_ssim,
+        vert_plot=vert_plot,
     )
 
     mp.verify_plot_parameters()