def test_BasinClass01(self):
files = ["small25", "jebja30", "tunez"]
for file in files:
# Cargamos flow
flw_path = "{}/{}_fd.tif".format(infolder, file)
dem_path = "{}/{}.tif".format(infolder, file)
dem = DEM(dem_path)
fd = Flow(flw_path)
# Obtenemos cuencas
cuencas = fd.get_drainage_basins(min_area=0.0025)
# Mayor, menor, y random
bids, counts = np.unique(cuencas.read_array(), return_counts=True)
if 0 in bids:
bids = bids[1:]
counts = counts[1:]
idmax = bids[np.argmax(counts)]
idmin = bids[np.argmin(counts)]
idrdn = np.random.choice(bids)
idxs = [idmax, idmin, idrdn]
lbls = ["max", "min", "rdn"]
for n in range(3):
basin = Basin(dem, cuencas, idxs[n])
basin_path = "{}/{}_basin{}.tif".format(
outfolder, file, lbls[n])
basin.save(basin_path)
basin2 = Basin(basin_path)
computed = np.array_equal(basin.read_array(),
basin2.read_array())
self.assertEqual(computed, True)
def test_BNetwork_class04(self):
"""
Test que prueba cabeceras en cuenca 1 con small25 (sin utilizar id field)
474260.9;4114339.6;3
474856.9;4114711.1;2
"""
# Cargamos DEM, Flow, Network
fd = Flow("{}/{}_fd.tif".format(infolder, "small25"))
net = Network("{}/{}_net.dat".format(infolder, "small25"))
# Cargamos outlets, heads y generamos cuencas
outlets = np.loadtxt("{}/{}_bnet_outlets.txt".format(
infolder, "small25"),
delimiter=";")
heads = np.loadtxt("{}/{}_bnet_heads.txt".format(infolder, "small25"),
delimiter=";")
# Remove the id column
heads = heads[:, :-1]
outlets = net.snap_points(outlets)
cuencas = fd.get_drainage_basins(outlets)
bid = 1
bnet = BNetwork(net, cuencas, heads, bid)
self.assertEqual(np.array_equal(bnet._heads, np.array([16171, 13494])),
True)
def test_BNetwork_class01(self):
"""
Test00 Crea BNetwork para cuencas de prueba a partir de un objeto Basin
Sin utilizar cabeceras
"""
files = ["small25", "jebja30", "tunez"]
for file in files:
# Cargamos DEM, Flow, Network
fd = Flow("{}/{}_fd.tif".format(infolder, file))
dem = DEM("{}/{}.tif".format(infolder, file))
net = Network("{}/{}_net.dat".format(infolder, file))
# Cargamos outlets y generamos cuencas
outlets = np.loadtxt("{}/{}_bnet_outlets.txt".format(
infolder, file),
delimiter=";")
outlets = net.snap_points(outlets)
cuencas = fd.get_drainage_basins(outlets)
for bid in np.unique(cuencas.read_array()):
if bid == 0:
continue
basin = Basin(dem, cuencas, bid)
bnet = BNetwork(net, basin)
# Este test solo verifica que se realice sin fallos y que
# el objeto bnet tiene una única cabecera
bnet = BNetwork(net, cuencas, None, bid)
self.assertEqual(int(bnet._heads[0]), self.results[file][bid])
def test_drainage_basins_05(self):
# Test extracting all basins
files = ["small25", "morocco", "tunez", "jebja30"]
for file in files:
flw_path = infolder + "/{0}_fd.tif".format(file)
fd = Flow(flw_path)
# Extract all basin without min_area
basins = fd.get_drainage_basins(min_area=0)
basins.save(outfolder + "/all_basins{0}".format(file))
def test_drainage_basins_04(self):
# Test extracting all basins (min_area = 10%)
files = ["small25", "tunez", "jebja30"]
for file in files:
flw_path = infolder + "/{0}_fd.tif".format(file)
fd = Flow(flw_path)
# Extract all basin with min_area
basins = fd.get_drainage_basins()
basins.save(outfolder + "/all_basins-minarea_{0}.tif".format(file))
def test_drainage_basins_03(self):
# Test extracting the biggest basin and input as a list [x, y]
files = ["small25", "morocco", "tunez", "jebja30"]
for file in files:
flw_path = infolder + "/{0}_fd.tif".format(file)
fd = Flow(flw_path)
# Get coords of the highest flow accumulation
fac = fd.get_flow_accumulation()
maxval = fac.max()
rowpos, colpos = np.where(fac.read_array() == maxval)
xi, yi = fd.cell_2_xy(rowpos, colpos)
# Extract basin
outlets = np.array((xi, yi)).T
basins = fd.get_drainage_basins(outlets)
basins.save(outfolder + "/max_basin2_{0}".format(file))
def test_drainage_basins_01(self):
# Test 10 random basins
files = ["small25", "morocco", "tunez", "jebja30"]
for file in files:
flw_path = infolder + "/{0}_fd.tif".format(file)
fd = Flow(flw_path)
# Creamos 10 cuencas aleatorias
ri = np.random.randint(0, fd._dims[0], 10)
ci = np.random.randint(0, fd._dims[1], 10)
xi, yi = fd.cell_2_xy(ri, ci)
# Extract basins
outlets = np.array((xi, yi)).T
basins = fd.get_drainage_basins(outlets)
basins.save(outfolder + "/rnd_basins_{0}".format(file))
def test_BNetwork_class05(self):
"""
Test de creado masivo de cuencas con cabeceras aleatorias
"""
files = ["small25", "jebja30", "tunez"]
for file in files:
# Cargamos DEM, Flow, Network
fd = Flow("{}/{}_fd.tif".format(infolder, file))
net = Network("{}/{}_net.dat".format(infolder, file))
dem = DEM("{}/{}.tif".format(infolder, file))
# Generamos todas las cuencas
cuencas = fd.get_drainage_basins(min_area=0.0025)
# Generamos 50 puntos aleatorios dentro de la extensión del objeto Network
# Estos 50 puntos se usaran como cabeceras
xmin, xmax, ymin, ymax = net.get_extent()
xi = np.random.randint(xmin, xmax, 50)
yi = np.random.randint(ymin, ymax, 50)
heads = np.array((xi, yi)).T
# Cogemos 5 cuencas aleatorias
bids = np.random.choice(np.unique(cuencas.read_array())[1:], 5)
for bid in bids:
try:
if np.random.randint(100) < 70:
bnet = BNetwork(net, cuencas, heads, bid)
else:
basin = Basin(dem, cuencas, bid)
bnet = BNetwork(net, basin, heads)
except NetworkError:
print(
"Network of {} file inside the basin {} has not enough pixels"
.format(file, bid))
continue
# Salvamos BNetwork y volvemos a cargar para comprobar que se cargan-guardan bien
bnet_path = "{}/{}_{}_bnet.dat".format(outfolder, file, bid)
bnet.save(bnet_path)
bnet2 = BNetwork(bnet_path)
computed = np.array_equal(bnet._ix, bnet2._ix)
self.assertEqual(computed, True)
# borramos archivo
os.remove(bnet_path)
def test_drainage_basins_00(self):
# Test 10 random basins
files = ["small25", "tunez", "jebja30"]
for file in files:
flw_path = infolder + "/{0}_fd.tif".format(file)
fd = Flow(flw_path)
# Creamos 10 cuencas aleatorias
ri = np.random.randint(0, fd.get_dims()[0], 10)
ci = np.random.randint(0, fd.get_dims()[1], 10)
rdn_ids = np.random.randint(100, 700, 10)
xi, yi = fd.cell_2_xy(ri, ci)
# Extract basins
outlets = np.array((xi, yi, rdn_ids)).T
threshold = int(fd.get_ncells() * 0.05)
snap_outlets = fd.snap_points(outlets, threshold, kind="channel")
snap = np.append(snap_outlets, rdn_ids.reshape(rdn_ids.size, 1), 1)
basins = fd.get_drainage_basins(snap)
basins.save(outfolder + "/rnd_snap_basins_{0}.tif".format(file))
def test_BNetwork_class00(self):
"""
Test00 Crea BNetwork para cuencas de prueba a partir de un Grid de cuencas
Sin utilizar cabeceras
"""
files = ["small25", "jebja30", "tunez"]
for file in files:
# Cargamos DEM, Flow, Network
fd = Flow("{}/{}_fd.tif".format(infolder, file))
net = Network("{}/{}_net.dat".format(infolder, file))
# Cargamos outlets y generamos cuencas
outlets = np.loadtxt("{}/{}_bnet_outlets.txt".format(
infolder, file),
delimiter=";")
outlets = net.snap_points(outlets)
cuencas = fd.get_drainage_basins(outlets)
for bid in np.unique(cuencas.read_array()):
if bid == 0:
continue
bnet = BNetwork(net, cuencas, None, bid)
self.assertEqual(int(bnet._heads[0]), self.results[file][bid])
from topopy import Network, DEM, Flow, Grid import matplotlib.pyplot as plt import numpy as np infolder = "../data/in" outfolder = "../data/out" dem = DEM(infolder + "/morocco.tif") fd = Flow(dem) net = Network(dem, fd, 1500) streams = net.get_streams() streams.save(outfolder + "/canales_orig.tif") outlet = np.array([579213, 504282]).reshape(1, 2) basin = fd.get_drainage_basins(net.snap_points(outlet), asgrid=False) c1 = basin.max(axis=0).argmax() r1 = basin.max(axis=1).argmax() c2 = basin.shape[1] - np.fliplr(basin).max(axis=0).argmax() r2 = basin.shape[0] - np.flipud(basin).max(axis=1).argmax() basin_cl = basin[r1:r2, c1:c2] nrow = basin_cl.shape[0] ncol = basin_cl.shape[1] outgrid = Grid() outgrid._size = (ncol, nrow) outgrid._dims = (nrow, ncol) geot = net._geot ULx = geot[0] + geot[1] * c1 ULy = geot[3] + geot[5] * r1
# -*- coding: utf-8 -*-
"""
Editor de Spyder
Este es un archivo temporal
"""
from topopy import Network, Channel, Flow, BNetwork
import ogr
import numpy as np
import matplotlib.pyplot as plt
fd = Flow("../data/in/jebja30_fd.tif")
net = Network("../data/in/jebja30_net.dat")
cuencas = fd.get_drainage_basins()
bnet1 = BNetwork(net, cuencas, None, 3)
bnet2 = BNetwork(net, cuencas, None, 10)
shp_path = "../data/out/canales_basin.shp"
bnet1.export_to_shp(shp_path, True)
dataset = ogr.Open(shp_path)
layer = dataset.GetLayer(0)
canales = []
for n in range(layer.GetFeatureCount()):
feat = layer.GetFeature(n)
geom = feat.GetGeometryRef()
head = geom.GetPoint(0)
mouth = geom.GetPoint(geom.GetPointCount() - 1)
