out_pos = (sum_arr == 0) & w
elif kind == 'confluences':
sum_arr = np.asarray(np.sum(sp_arr, 0)).ravel()
out_pos = sum_arr > 1
elif kind == 'outlets':
sum_arr = np.asarray(np.sum(sp_arr, 1)).ravel()
out_pos = (sum_arr == 0) & w
out_pos = out_pos.reshape(fd._dims)
row, col = np.where(out_pos)
return row, col
dem = DEM("../data/tunez.tif")
fd = Flow()
fd.load_gtiff("../data/tunez_fd.tif")
fig, ax = plt.subplots()
dem.plot(ax)
streams = fd.get_network(1000)
streams.plot(ax)
# Heads
row, col = get_stream_poi(fd, 1000, 'heads')
ax.plot(col, row, "ro")
#
# Confluences
row, col = get_stream_poi(fd, 1000, 'confluences')
ax.plot(col, row, "bs")
# -*- coding: utf-8 -*-
"""
Created on Fri Jan 26 17:53:42 2018
@author: vicen
"""
import sys
sys.path.append("../../")
from topopy import Flow, Grid
import numpy as np
from scipy.sparse import csc_matrix
import matplotlib.pyplot as plt
fd = Flow()
fd.load_gtiff("../data/in/fd_tunez.tif")
threshold = 1000
fac = fd.get_flow_accumulation(nodata=False, asgrid=False)
w = fac > threshold
w = w.ravel()
I = w[fd._ix]
ix = fd._ix[I]
ixc = fd._ixc[I]
ixcix = np.zeros(fd._ncells, np.int)
ixcix[fd._ix] = np.arange(len(fd._ix))
ixcix[ix] = np.arange(len(ix))
x = 507194.338
