view.py: use a different colormap for sea, to distinguish it from lakes

view.py

@@ -11,10 +11,12 @@ try:
         import colorcet as cc
         cmap1 = cc.cm.CET_L11
         cmap2 = cc.cm.CET_L12
+        cmap3 = cc.cm.CET_L6.reversed()
     except ImportError: # No module colorcet
         import matplotlib.cm as cm
         cmap1 = cm.summer
-        cmap2 = cm.Blues
+        cmap2 = cm.ocean.reversed()
+        cmap3 = cm.Blues
 except ImportError: # No module matplotlib
     has_matplotlib = False
 
@@ -24,10 +26,12 @@ if has_matplotlib:
         water = np.maximum(lakes_sea - dem, 0)
         max_elev = dem.max()
         max_depth = water.max()
+        max_lake_depth = lakes.max()
 
         ls = mcl.LightSource(azdeg=315, altdeg=45)
         norm_ground = plt.Normalize(vmin=sea_level, vmax=max_elev)
         norm_sea = plt.Normalize(vmin=0, vmax=max_depth)
+        norm_lake = plt.Normalize(vmin=0, vmax=max_lake_depth)
         rgb = ls.shade(dem, cmap=cmap1, vert_exag=1/scale, blend_mode='soft', norm=norm_ground)
 
         (X, Y) = dem.shape
@@ -37,13 +41,23 @@ if has_matplotlib:
             extent = (-0.5*scale, (Y-0.5)*scale, -0.5*scale, (X-0.5)*scale)
         plt.imshow(np.flipud(rgb), extent=extent, interpolation='antialiased')
         alpha = (water > 0).astype('u1')
-        plt.imshow(np.flipud(water), alpha=np.flipud(alpha), cmap=cmap2, extent=extent, vmin=0, vmax=max_depth, interpolation='antialiased')
+        lakes_alpha = ((lakes_sea - np.maximum(dem,sea_level)) > 0).astype('u1')
+        # plt.imshow(np.flipud(water), alpha=np.flipud(alpha), cmap=cmap2, extent=extent, vmin=0, vmax=max_depth, interpolation='antialiased')
+        plt.imshow(np.flipud(water), alpha=np.flipud(alpha), cmap=cmap3, extent=extent, vmin=0, vmax=max_depth, interpolation='antialiased')
+        plt.imshow(np.flipud(water), alpha=np.flipud(lakes_alpha), cmap=cmap2, extent=extent, vmin=0, vmax=max_depth, interpolation='antialiased')
 
         sm1 = plt.cm.ScalarMappable(cmap=cmap1, norm=norm_ground)
         plt.colorbar(sm1).set_label('Elevation')
 
-        sm2 = plt.cm.ScalarMappable(cmap=cmap2, norm=norm_sea)
-        plt.colorbar(sm2).set_label('Water depth')
+        sm2 = plt.cm.ScalarMappable(cmap=cmap2, norm=norm_lake)
+        cb2 = plt.colorbar(sm2)
+        cb2.ax.invert_yaxis()
+        cb2.set_label('Lake Depth')
+
+        sm3 = plt.cm.ScalarMappable(cmap=cmap3, norm=norm_sea)
+        cb3 = plt.colorbar(sm3)
+        cb3.ax.invert_yaxis()
+        cb3.set_label('Ocean Depth')
 
         plt.xlabel('X')
         plt.ylabel('Z')
@@ -84,7 +98,8 @@ def stats(dem, lakes, scale=1):
     lake_surface = lake.sum()
 
     print('---   General    ---')
-    print('Grid size:    {:5d}x{:5d}'.format(dem.shape[0], dem.shape[1]))
+    print('Grid size (dem):     {:5d}x{:5d}'.format(dem.shape[0], dem.shape[1]))
+    print('Grid size (lakes):   {:5d}x{:5d}'.format(lakes.shape[0], lakes.shape[1]))
     if scale > 1:
         print('Map size:            {:5d}x{:5d}'.format(int(dem.shape[0]*scale), int(dem.shape[1]*scale)))
     print()
@@ -100,3 +115,5 @@ def stats(dem, lakes, scale=1):
     print('Mean continent elev: {:4.0f}'.format((dem*continent).sum()/continent_surface))
     print('Lowest elevation:    {:4.0f}'.format(dem.min()))
     print('Highest elevation:   {:4.0f}'.format(dem.max()))
+    print()
+