def test_snap_poi_02(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)
thr = int(fd.get_ncells() * 0.01)
# Obtenemos 20 puntos aleatorios
x1, x2, y1, y2 = fd.get_extent()
xi = (x2 - x1) * np.random.random(25) + x1
yi = (y2 - y1) * np.random.random(25) + y1
puntos = np.array((xi, yi)).T
# Obtenemos lista con Flow Accumulations cells
fac = fd.get_flow_accumulation(nodata=False, asgrid=False)
ch_cells = np.where(fac.ravel() >= thr)[0]
# Hacemos snap a celdas de canal
snap_pp = fd.snap_points(puntos, thr, kind="channel")
row, col = fd.xy_2_cell(snap_pp[:, 0], snap_pp[:, 1])
inds = fd.cell_2_ind(row, col)
# Comprobamos que punto esta entre los POI
for ind in inds:
res = ind in ch_cells
self.assertEqual(res, True)
def test_snap_poi_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)
thr = int(fd.get_ncells() * 0.01)
# Obtenemos 20 puntos aleatorios
x1, x2, y1, y2 = fd.get_extent()
xi = (x2 - x1) * np.random.random(25) + x1
yi = (y2 - y1) * np.random.random(25) + y1
puntos = np.array((xi, yi)).T
# Hacemos snap a los stream poi
for kind in ["heads", "confluences", "outlets"]:
poi = fd.get_stream_poi(thr, kind, "XY")
snap_pp = fd.snap_points(puntos, thr, kind)
# Comprobamos que punto esta entre los POI
for row in snap_pp:
res = row in poi
self.assertEqual(res, True)
# Remove duplicates
if remove_duplicates:
idx = np.unique(out_p[:, -1], return_index=True)[1]
out_p = out_p[idx, :-1]
return out_p
kind = "confluences"
fd = Flow("../data/in/small25_fd.tif")
poi = fd.get_stream_poi(500, kind, "XY")
# Generate 10 random points
xmin, xmax, ymin, ymax = fd.get_extent()
np.random.seed(1234)
rnd_x = (xmax - xmin) * np.random.random(10) + xmin
rnd_y = (ymax - ymin) * np.random.random(10) + ymin
plt.scatter(rnd_x, rnd_y, c="r", s=10)
plt.scatter(poi[:, 0], poi[:, 1], c="b", marker="s", s=20)
input_points = np.array((rnd_x, rnd_y, np.arange(0, 1000, 100))).T
for n in range(10):
plt.annotate(str(input_points[n, 2]),
(input_points[n, 0], input_points[n, 1]))
out_p = snap_points(fd, input_points, 500, kind, remove_duplicates=True)
