mtcontrib/mapgen_rivers
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Use iterative finite differences for diffusion, instead of gaussian blur

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Allows variable diffusion coefficients
This commit is contained in:
Gael-de-Sailly 2020-12-27 13:46:25 +01:00
parent 1b96f52e47
commit 462942cc22
2 changed files with 31 additions and 7 deletions
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2
generate.py
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@ -172,7 +172,7 @@ K_map = noisemap(mapsize+1, mapsize+1, **params_K).get2d()
### COMPUTE LANDSCAPE EVOLUTION ### COMPUTE LANDSCAPE EVOLUTION
# Initialize landscape evolution model # Initialize landscape evolution model
print('Initializing model') print('Initializing model')
model = terrainlib.EvolutionModel(n, K=K_map, m=m_map, d=d, sea_level=sea_level, flex_radius=flex_radius, flow_method=flow_method) model = terrainlib.EvolutionModel(n, K=K_map, m=m_map, d=K_map, sea_level=sea_level, flex_radius=flex_radius, flow_method=flow_method)
terrainlib.update(model.dem, model.lakes, t=5, sea_level=model.sea_level, title='Initializing...') terrainlib.update(model.dem, model.lakes, t=5, sea_level=model.sea_level, title='Initializing...')
dt = time/niter dt = time/niter

36
terrainlib/erosion.py
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@ -1,5 +1,6 @@
import numpy as np import numpy as np
import scipy.ndimage as im import scipy.ndimage as im
import scipy.signal as si
from .rivermapper import flow from .rivermapper import flow
def advection(dem, dirs, rivers, time, K=1, m=0.5, sea_level=0): def advection(dem, dirs, rivers, time, K=1, m=0.5, sea_level=0):
@ -47,11 +48,31 @@ def advection(dem, dirs, rivers, time, K=1, m=0.5, sea_level=0):
return dem_new return dem_new
def diffusion(dem, time, d=1): second_derivative_matrix = np.array([
radius = d * time**.5 [0., 0.25, 0.],
if radius == 0: [0.25,-1., 0.25],
return dem [0., 0.25, 0.],
return im.gaussian_filter(dem, radius, mode='reflect') # Diffusive erosion is a simple Gaussian blur ])
diff_max = 1.0
def diffusion(dem, time, d=1.0):
if isinstance(d, np.ndarray):
dmax = d.max()
else:
dmax = d
diff = time * dmax
print(diff)
niter = int(diff//diff_max) + 1
ddiff = d * (time / niter)
#print('{:d} iterations'.format(niter))
for i in range(niter):
dem[1:-1,1:-1] += si.convolve2d(dem, second_derivative_matrix, mode='valid') * ddiff
#print('iteration {:d}'.format(i+1))
return dem
#return im.gaussian_filter(dem, radius, mode='reflect') # Diffusive erosion is a simple Gaussian blur
class EvolutionModel: class EvolutionModel:
def __init__(self, dem, K=1, m=0.5, d=1, sea_level=0, flow=False, flex_radius=100, flow_method='semirandom'): def __init__(self, dem, K=1, m=0.5, d=1, sea_level=0, flow=False, flex_radius=100, flow_method='semirandom'):
@ -59,7 +80,10 @@ class EvolutionModel:
#self.bedrock = dem #self.bedrock = dem
self.K = K self.K = K
self.m = m self.m = m
self.d = d if isinstance(d, np.ndarray):
self.d = d[1:-1,1:-1]
else:
self.d = d
self.sea_level = sea_level self.sea_level = sea_level
self.flex_radius = flex_radius self.flex_radius = flex_radius
self.define_isostasy() self.define_isostasy()