Added a second method for local flow calculation. It is possible to switch between them using the 'flow_method' parameter.

terrainlib/erosion.py

@@ -54,7 +54,7 @@ def diffusion(dem, time, d=1):
     return im.gaussian_filter(dem, radius, mode='reflect') # Diffusive erosion is a simple Gaussian blur
 
 class EvolutionModel:
-    def __init__(self, dem, K=1, m=0.5, d=1, sea_level=0, flow=False, flex_radius=100):
+    def __init__(self, dem, K=1, m=0.5, d=1, sea_level=0, flow=False, flex_radius=100, flow_method='semirandom'):
         self.dem = dem
         #self.bedrock = dem
         self.K = K
@@ -63,6 +63,8 @@ class EvolutionModel:
         self.sea_level = sea_level
         self.flex_radius = flex_radius
         self.define_isostasy()
+        self.flow_method = flow_method
+        #set_flow_method(flow_method)
         if flow:
             self.calculate_flow()
         else:
@@ -72,7 +74,7 @@ class EvolutionModel:
             self.flow_uptodate = False
 
     def calculate_flow(self):
-        self.dirs, self.lakes, self.rivers = flow(self.dem)
+        self.dirs, self.lakes, self.rivers = flow(self.dem, method=self.flow_method)
         self.flow_uptodate = True
 
     def advection(self, time):

terrainlib/rivermapper.py

@@ -12,7 +12,19 @@ from collections import defaultdict
 # The algorithm here makes use of most of the paper's concepts, including the Planar Boruvka algorithm.
 # Only flow_local and accumulate_flow are custom algorithms.
 
-def flow_local(plist):
+# Define two different method for local flow routing
+def flow_local_steepest(plist):
+    vmax = 0.0
+    imax = 0.0
+    for i, p in enumerate(plist):
+        if p > vmax:
+            vmax = p
+            imax = i
+    if vmax > 0.0:
+        return imax+1
+    return 0
+
+def flow_local_semirandom(plist):
     """
     Determines a flow direction based on denivellation for every neighbouring node.
     Denivellation must be positive for downward and zero for flat or upward:
@@ -27,7 +39,16 @@ def flow_local(plist):
             return i+1
         r -= p
 
-def flow(dem):
+flow_local_methods = {
+    'steepest' : flow_local_steepest,
+    'semirandom' : flow_local_semirandom,
+}
+
+def flow(dem, method='semirandom'):
+    if method in flow_local_methods:
+        flow_local = flow_local_methods[method]
+    else:
+        raise KeyError('Flow method \'{}\' does not exist'.format(method))
 
     # Flow locally
     dirs1 = np.zeros(dem.shape, dtype=int)