mtcontrib/mapgen_rivers
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Enhanced visualization code to display colormaps, and reuse the same code for initial and further viewing, in view_map.py

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Gael-de-Sailly 2020-04-26 18:30:29 +02:00
parent 206c68813e
commit cd90a21df4
2 changed files with 34 additions and 55 deletions
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29
terrain_rivers.py
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@ -91,32 +91,7 @@ with open('size', 'w') as sfile:
# Display the map if matplotlib is found
try:
import matplotlib.pyplot as plt
plt.subplot(2,2,1)
plt.pcolormesh(nn, cmap='viridis')
plt.gca().set_aspect('equal', 'box')
#plt.colorbar(orientation='horizontal')
plt.title('Raw elevation')
plt.subplot(2,2,2)
plt.pcolormesh(model.lakes, cmap='viridis')
plt.gca().set_aspect('equal', 'box')
#plt.colorbar(orientation='horizontal')
plt.title('Lake surface elevation')
plt.subplot(2,2,3)
plt.pcolormesh(model.dem, cmap='viridis')
plt.gca().set_aspect('equal', 'box')
#plt.colorbar(orientation='horizontal')
plt.title('Elevation after advection')
plt.subplot(2,2,4)
plt.pcolormesh(model.rivers, vmin=0, vmax=mapsize**2/25, cmap='Blues')
plt.gca().set_aspect('equal', 'box')
#plt.colorbar(orientation='horizontal')
plt.title('Rivers flux')
plt.show()
from view_map import view_map
view_map(model.dem, model.lakes, model.rivers)
except:
pass

60
view_map.py
View File

@ -2,38 +2,42 @@
import numpy as np
import zlib
import matplotlib.colors as mcol
import matplotlib.pyplot as plt
def load_map(name, dtype, shape):
dtype = np.dtype(dtype)
with open(name, 'rb') as f:
data = f.read()
if len(data) < shape[0]*shape[1]*dtype.itemsize:
data = zlib.decompress(data)
return np.frombuffer(data, dtype=dtype).reshape(shape)
def view_map(dem, lakes, rivers):
plt.subplot(1,3,1)
plt.pcolormesh(dem, cmap='viridis')
plt.gca().set_aspect('equal', 'box')
plt.colorbar(orientation='horizontal')
plt.title('Raw elevation')
shape = np.loadtxt('size', dtype='u4')
n = shape[0] * shape[1]
dem = load_map('dem', '>i2', shape)
lakes = load_map('lakes', '>i2', shape)
rivers = load_map('rivers', '>u4', shape)
plt.subplot(1,3,2)
plt.pcolormesh(lakes, cmap='viridis')
plt.gca().set_aspect('equal', 'box')
plt.colorbar(orientation='horizontal')
plt.title('Lake surface elevation')
plt.subplot(1,3,1)
plt.pcolormesh(dem, cmap='viridis')
plt.gca().set_aspect('equal', 'box')
#plt.colorbar(orientation='horizontal')
plt.title('Raw elevation')
plt.subplot(1,3,3)
plt.pcolormesh(rivers, cmap='Blues', norm=mcol.LogNorm())
plt.gca().set_aspect('equal', 'box')
plt.colorbar(orientation='horizontal')
plt.title('Rivers flux')
plt.subplot(1,3,2)
plt.pcolormesh(lakes, cmap='viridis')
plt.gca().set_aspect('equal', 'box')
#plt.colorbar(orientation='horizontal')
plt.title('Lake surface elevation')
plt.show()
plt.subplot(1,3,3)
plt.pcolormesh(np.log(rivers), vmin=0, vmax=np.log(n/25), cmap='Blues')
plt.gca().set_aspect('equal', 'box')
#plt.colorbar(orientation='horizontal')
plt.title('Rivers flux')
if __name__ == "__main__":
def load_map(name, dtype, shape):
dtype = np.dtype(dtype)
with open(name, 'rb') as f:
data = f.read()
if len(data) < shape[0]*shape[1]*dtype.itemsize:
data = zlib.decompress(data)
return np.frombuffer(data, dtype=dtype).reshape(shape)
plt.show()
shape = np.loadtxt('size', dtype='u4')
dem = load_map('dem', '>i2', shape)
lakes = load_map('lakes', '>i2', shape)
rivers = load_map('rivers', '>u4', shape)
view_map(dem, lakes, rivers)