mirror of
https://gitlab.com/gaelysam/mapgen_rivers.git
synced 2024-11-16 07:40:20 +01:00
103 lines
3.5 KiB
Python
103 lines
3.5 KiB
Python
#!/usr/bin/env python3
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import numpy as np
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import sys, traceback
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has_matplotlib = True
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try:
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import matplotlib.colors as mcl
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import matplotlib.pyplot as plt
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try:
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import colorcet as cc
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cmap1 = cc.cm.CET_L11
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cmap2 = cc.cm.CET_L12
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except ImportError: # No module colorcet
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import matplotlib.cm as cm
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cmap1 = cm.summer
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cmap2 = cm.Blues
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except ImportError: # No module matplotlib
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has_matplotlib = False
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if has_matplotlib:
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def view_map(dem, lakes, scale=1, center=False, sea_level=0.0, title=None):
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lakes_sea = np.maximum(lakes, sea_level)
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water = np.maximum(lakes_sea - dem, 0)
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max_elev = dem.max()
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max_depth = water.max()
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ls = mcl.LightSource(azdeg=315, altdeg=45)
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norm_ground = plt.Normalize(vmin=sea_level, vmax=max_elev)
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norm_sea = plt.Normalize(vmin=0, vmax=max_depth)
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rgb = ls.shade(dem, cmap=cmap1, vert_exag=1/scale, blend_mode='soft', norm=norm_ground)
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(X, Y) = dem.shape
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if center:
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extent = (-(Y+1)*scale/2, (Y-1)*scale/2, -(X+1)*scale/2, (X-1)*scale/2)
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else:
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extent = (-0.5*scale, (Y-0.5)*scale, -0.5*scale, (X-0.5)*scale)
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plt.imshow(np.flipud(rgb), extent=extent, interpolation='antialiased')
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alpha = (water > 0).astype('u1')
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plt.imshow(np.flipud(water), alpha=np.flipud(alpha), cmap=cmap2, extent=extent, vmin=0, vmax=max_depth, interpolation='antialiased')
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sm1 = plt.cm.ScalarMappable(cmap=cmap1, norm=norm_ground)
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plt.colorbar(sm1).set_label('Elevation')
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sm2 = plt.cm.ScalarMappable(cmap=cmap2, norm=norm_sea)
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plt.colorbar(sm2).set_label('Water depth')
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plt.xlabel('X')
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plt.ylabel('Z')
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if title is not None:
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plt.title(title, fontweight='bold')
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def update(*args, t=0.01, **kwargs):
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try:
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plt.clf()
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view_map(*args, **kwargs)
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plt.pause(t)
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except:
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traceback.print_exception(*sys.exc_info())
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def plot(*args, **kwargs):
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try:
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plt.clf()
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view_map(*args, **kwargs)
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plt.pause(0.01)
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plt.show()
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except Exception as e:
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traceback.print_exception(*sys.exc_info())
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else:
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def update(*args, **kwargs):
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pass
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def plot(*args, **kwargs):
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pass
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def stats(dem, lakes, scale=1):
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surface = dem.size
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continent = np.maximum(dem, lakes) >= 0
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continent_surface = continent.sum()
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lake = continent & (lakes>dem)
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lake_surface = lake.sum()
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print('--- General ---')
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print('Grid size: {:5d}x{:5d}'.format(dem.shape[0], dem.shape[1]))
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if scale > 1:
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print('Map size: {:5d}x{:5d}'.format(int(dem.shape[0]*scale), int(dem.shape[1]*scale)))
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print()
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print('--- Surfaces ---')
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print('Continents: {:6.2%}'.format(continent_surface/surface))
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print('-> Ground: {:6.2%}'.format((continent_surface-lake_surface)/surface))
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print('-> Lakes: {:6.2%}'.format(lake_surface/surface))
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print('Oceans: {:6.2%}'.format(1-continent_surface/surface))
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print()
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print('--- Elevations ---')
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print('Mean elevation: {:4.0f}'.format(dem.mean()))
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print('Mean ocean depth: {:4.0f}'.format((dem*~continent).sum()/(surface-continent_surface)))
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print('Mean continent elev: {:4.0f}'.format((dem*continent).sum()/continent_surface))
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print('Lowest elevation: {:4.0f}'.format(dem.min()))
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print('Highest elevation: {:4.0f}'.format(dem.max()))
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