def compute_mask(self):
import matplotlib.nxutils as nx
if self.pts is not None:
def correct_mask(mask, x, y, pts):
for j in range(y.size):
for i in range(x.size):
if mask[j,i] > 0:
if nx.pnpoly(x[i], y[j], pts):
mask[j,i] = 2
else:
mask[j,i] = 1
correct_mask(self.mask, self.x, self.y, self.pts)
dbg.upslope_area(self.x, self.y, self.z, self.mask)
print "Drainage basin computation: done"
self.mask_computed = True
plt.figure(1)
plt.pcolormesh(self.x, self.y, self.mask)
plt.contour(self.x, self.y, self.z, colors='black')
plt.axis('tight')
plt.axes().set_aspect('equal')
plt.show()
pts = get_terminus()
import matplotlib.nxutils as nx
def correct_mask(pts):
for j in range(y.size):
for i in range(x.size):
if mask[j,i] > 0:
if nx.pnpoly(x[i], y[j], pts):
mask[j,i] = 2
else:
mask[j,i] = 1
correct_mask(pts)
dbg.upslope_area(x, y, z, mask)
print "Drainage basin computation: done"
plt.figure(1)
plt.pcolormesh(x, y, mask)
plt.contour(x, y, z, colors='black')
plt.axis('tight')
plt.axes().set_aspect('equal')
plt.title("upslope areas")
# mask2 = np.zeros(thk.shape, dtype=np.float64) - 1
# mask2[thk > 5] = 0
# mask2[mask != 2] = -1
# dbg.accumulated_flow(x, y, z, mask2, n_samples = 4)
