Improve proxy visualization funcs

cfr/proxy.py

@@ -621,7 +621,7 @@ def plotly(self, **kwargs):
         return fig
 
     def plot(self, figsize=[12, 4], legend=False, ms=200, stock_img=True, edge_clr='w',
-        wspace=0.1, hspace=0.1, plot_map=True, **kwargs):
+        wspace=0.1, hspace=0.1, plot_map=True, p=visual.STYLE, **kwargs):
         ''' Visualize the ProxyRecord
 
         Args:
@@ -635,7 +635,10 @@ def plot(self, figsize=[12, 4], legend=False, ms=200, stock_img=True, edge_clr='
             plot_map (bool): if True, plot the record on a map. Defaults to True.
         '''
         if 'color' not in kwargs and 'c' not in kwargs:
-            kwargs['color'] = visual.STYLE.colors_dict[self.ptype]
+            if self.ptype in p.colors_dict:
+                kwargs['color'] = p.colors_dict[self.ptype]
+            else:
+                kwargs['color'] = 'tab:blue'
 
         fig = plt.figure(figsize=figsize)
 
@@ -671,9 +674,13 @@ def plot(self, figsize=[12, 4], legend=False, ms=200, stock_img=True, edge_clr='
             if stock_img:
                 ax['map'].stock_img()
 
+            if self.ptype in p.markers_dict:
+                marker = p.markers_dict[self.ptype]
+            else:
+                marker = 'o'
             transform=ccrs.PlateCarree()
             ax['map'].scatter(
-                self.lon, self.lat, marker=visual.STYLE.markers_dict[self.ptype],
+                self.lon, self.lat, marker=marker,
                 s=ms, c=kwargs['color'], edgecolor=edge_clr, transform=transform,
             )
 

cfr/utils.py

@@ -611,6 +611,10 @@ def colored_noise_2regimes(alpha1, alpha2, f_break, t, f0=None, m=None, seed=Non
 
     return y
 
+def arr_str2np(arr):
+    arr =  np.array([float(s) for s in arr[1:-1].split(',')])
+    return arr
+
 def is_numeric(obj):
     attrs = ['__add__', '__sub__', '__mul__', '__truediv__', '__pow__']
     return all(hasattr(obj, attr) for attr in attrs)

cfr/visual.py

@@ -555,10 +555,17 @@ def plot_proxies(df, year=np.arange(2001), lon_col='lon', lat_col='lat', type_co
         type_names.append(f'{ptype} (n={max_count[-1]})')
         lons = list(df[selector][lon_col])
         lats = list(df[selector][lat_col])
+        if ptype in markers_dict:
+            marker = markers_dict[ptype]
+            color = colors_dict[ptype]
+        else:
+            marker = 'o'
+            color = 'tab:blue'
+
         s_plots.append(
             ax['map'].scatter(
-                lons, lats, marker=markers_dict[ptype],
-                c=colors_dict[ptype], edgecolor='k', s=markersize, transform=ccrs.PlateCarree()
+                lons, lats, marker=marker, c=color,
+                edgecolor='k', s=markersize, transform=ccrs.PlateCarree()
             )
         )