Coloured slope for e4MSTP

4th layer is coloured slope, it can be calculated directly in layer, so far it had a separate function. The function is now removed from tiled_multiprocessing as well.

Author: NejcCoz

examples/tiled_processing/tiled_multiprocess.py

@@ -1018,8 +1018,6 @@ def blend_e3mstp(dict_arrays, save_path, save_float=False):
 
 
 def blend_e4mstp(dict_arrays, save_path, save_float=False):
-    # Get Coloured Slope
-    dict_arrays['cs'] = blend_coloured_slope(dict_arrays)
     # Get SVF combined
     dict_arrays['svf_combined'] = blend_svf_combined(dict_arrays)
     # Get Openness + LD
@@ -1045,10 +1043,11 @@ def blend_e4mstp(dict_arrays, save_path, save_float=False):
         image=dict_arrays['opns_ld']
     )
     comb_nv.create_layer(
-        vis_method="coloured slope",
-        normalization="value", minimum=0, maximum=1,
+        vis_method="Slope gradient",
+        normalization="value", minimum=0, maximum=55,
         blend_mode="normal", opacity=100,
-        image=dict_arrays['cs']
+        colormap="Reds_r", min_colormap_cut=0, max_colormap_cut=1,
+        image=dict_arrays['slp_1'].squeeze()
     )
     out_e4mstp = comb_nv.render_all_images(
         save_visualizations=False,
@@ -1089,35 +1088,6 @@ def blend_e4mstp(dict_arrays, save_path, save_float=False):
     return out_e4mstp
 
 
-def blend_coloured_slope(dict_arrays, save_path=None):
-    # Coloured slope
-    comb_cs = rvt.blend.BlenderCombination()
-    comb_cs.create_layer(
-        vis_method="Slope gradient", normalization="Value",
-        minimum=0, maximum=55,
-        blend_mode="normal", opacity=100,
-        colormap="Reds_r", min_colormap_cut=0, max_colormap_cut=1,
-        image=dict_arrays['slp_1'].squeeze()
-    )
-    coloured_slope = comb_cs.render_all_images(
-        save_visualizations=False,
-        save_render_path=None,
-        no_data=np.nan
-    )
-    coloured_slope = coloured_slope.astype("float32")
-
-    if save_path:
-        # Save GeoTIF
-        rasterio_save(
-            coloured_slope,
-            dict_arrays['profile'],
-            save_path=save_path,
-            nodata=np.nan
-        )
-
-    return coloured_slope
-
-
 def blend_opns_ld(dict_arrays, save_path=None):
     """Required dict_arrays:
     - opns

rvt/blend.py

@@ -1408,7 +1408,7 @@ def e4mstp(dem, resolution, default: rvt.default.DefaultValues = rvt.default.Def
     svf_arr = svf_temp["svf"].squeeze()
     neg_opns_arr = default.get_neg_opns(dem, resolution).squeeze()
 
-    # For SVF 2 (FLAT)
+    # For SVF 2 (FLAT) # TODO: svf_r_max is in pixels, take into account the resolution
     default_2 = rvt.default.DefaultValues()
     default_2.svf_r_max = 20
     default_2.svf_noise = 3
@@ -1437,14 +1437,14 @@ def e4mstp(dem, resolution, default: rvt.default.DefaultValues = rvt.default.Def
     # 3) Comb openness LD
     comb_ol = rvt.blend.BlenderCombination()
     comb_ol.create_layer(
-        vis_method="Openness difference", normalization="Value",
-        minimum=-15, maximum=15,
+        vis_method="Openness difference",
+        normalization="Value", minimum=-15, maximum=15,
         blend_mode="normal", opacity=50,
         image=(opns_arr - neg_opns_arr)
     )
     comb_ol.create_layer(
-        vis_method="Local dominance", normalization="Value",
-        minimum=0.5, maximum=1.8,
+        vis_method="Local dominance",
+        normalization="Value", minimum=0.5, maximum=1.8,
         blend_mode="normal", opacity=100,
         image=ld_arr
     )
@@ -1456,11 +1456,7 @@ def e4mstp(dem, resolution, default: rvt.default.DefaultValues = rvt.default.Def
     comb_opns_ld_arr = comb_opns_ld_arr.astype("float32")
 
     # 4) Coloured slope
-    slope_arr = rvt.vis.slope_aspect(
-        dem=dem,
-        resolution_x=resolution,
-        resolution_y=resolution,
-    )["slope"]
+    slope_arr = rvt.vis.slope_aspect(dem=dem, resolution_x=resolution, resolution_y=resolution)["slope"]
     # ------------------------------------------------------------------------------------------------------------------
 
     # Prepare layers for blending
@@ -1484,8 +1480,8 @@ def e4mstp(dem, resolution, default: rvt.default.DefaultValues = rvt.default.Def
         image=comb_opns_ld_arr
     )
     blend_combination.create_layer(
-        vis_method="coloured slope",
-        normalization="value", minimum=0, maximum=1,
+        vis_method="Slope gradient",
+        normalization="value", minimum=0, maximum=55,
         blend_mode="normal", opacity=100,
         colormap="Reds_r", min_colormap_cut=0, max_colormap_cut=1,
         image=slope_arr