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)
class FlowValueTest(unittest.TestCase):
def setUp(self):
# Load test data
self.ids = np.load(infolder + "/np_files/small25_100rnd_id.npy")
self.rows = np.load(infolder + "/np_files/small25_100rnd_row.npy")
self.cols = np.load(infolder + "/np_files/small25_100rnd_col.npy")
self.xi = np.load(infolder + "/np_files/small25_100rnd_X.npy")
self.yi = np.load(infolder + "/np_files/small25_100rnd_Y.npy")
self.zi = np.load(infolder + "/np_files/small25_100rnd_Z.npy")
# Load Flow object
self.fd = Flow(infolder + "/small25_fd.tif")
def test_xy_2_cell_01(self):
xi = self.xi
yi = self.yi
rows = self.rows
cols = self.cols
expected = (rows, cols)
computed = self.fd.xy_2_cell(xi, yi)
comparison = (computed[0] == expected[0]).all() and (computed[1] == expected[1]).all()
self.assertEqual(comparison, True)
def test_xy_2_cell_02(self):
ind = np.random.randint(0, 100)
x = self.xi[ind]
y = self.yi[ind]
row = self.rows[ind]
col = self.cols[ind]
expected = (row, col)
computed = self.fd.xy_2_cell(x, y)
self.assertEqual(computed, expected)
def test_xy_2_cell_03(self):
xi = self.xi.tolist()
yi = self.yi.tolist()
rows = self.rows
cols = self.cols
crows, ccols = self.fd.xy_2_cell(xi, yi)
computed = (np.array_equal(rows, crows), np.array_equal(cols, ccols))
self.assertEqual(computed, (True, True))
def test_ind_2_cell_01(self):
idx = np.random.randint(0, 100)
ind = self.ids[idx]
row = self.rows[idx]
col = self.cols[idx]
expected = (row, col)
computed = self.fd.ind_2_cell(ind)
self.assertEqual(computed, expected)
def test_ind_2_cell_02(self):
ind = self.ids
row = self.rows
col = self.cols
crow, ccol = self.fd.ind_2_cell(ind)
computed = (np.array_equal(row, crow), np.array_equal(col, ccol))
self.assertEqual(computed, (True, True))
def test_ind_2_cell_03(self):
ind = self.ids
row = self.rows
col = self.cols
expected = (row, col)
computed = self.fd.ind_2_cell(ind)
comparison = (computed[0] == expected[0]).all() and (computed[1] == expected[1]).all()
self.assertEqual(comparison, True)
def test_cell_2_ind_01(self):
idx = np.random.randint(0, 100)
ind = self.ids[idx]
row = self.rows[idx]
col = self.cols[idx]
expected = ind
computed = self.fd.cell_2_ind(row, col)
self.assertEqual(computed, expected)
def test_cell_2_ind_02(self):
ind = self.ids
row = self.rows
col = self.cols
expected = ind
computed = self.fd.cell_2_ind(row, col)
res = np.array_equal(expected, computed)
self.assertEqual(res, True)
def test_cell_2_ind_03(self):
ind = self.ids
row = self.rows
col = self.cols
expected = ind
computed = self.fd.cell_2_ind(row, col)
comparison = (computed == expected).all()
self.assertEqual(comparison, True)
def test_cell_2_xy_01(self):
xi = self.xi
yi = self.yi
rows = self.rows
cols = self.cols
expected = (xi, yi)
computed = self.fd.cell_2_xy(rows, cols)
res = (np.array_equal(expected[0], computed[0]), np.array_equal(expected[1], computed[1]))
self.assertEqual(res, (True, True))
def test_cell_2_xy_02(self):
ind = np.random.randint(0, 100)
xi = self.xi[ind]
yi = self.yi[ind]
rows = self.rows[ind]
cols = self.cols[ind]
expected = (xi, yi)
computed = self.fd.cell_2_xy(rows, cols)
res = (np.array_equal(expected[0], computed[0]), np.array_equal(expected[1], computed[1]))
self.assertEqual(res, (True, True))
def test_cell_2_xy_03(self):
xi = self.xi.tolist()
yi = self.yi.tolist()
rows = self.rows
cols = self.cols
expected = (xi, yi)
computed = self.fd.cell_2_xy(rows, cols)
res = (np.array_equal(expected[0], computed[0]), np.array_equal(expected[1], computed[1]))
self.assertEqual(res, (True, True))
"""
from topopy import Flow, Network, DEM
import numpy as np
import matplotlib.pyplot as plt
# Get DEM, Flow and Network
dem = DEM("../data/in/jebja30.tif")
fd = Flow(dem)
net = Network(dem, fd, 1000)
# Head
x = 577413
y = 496519
row, col = fd.xy_2_cell(x, y)
ix = fd.cell_2_ind(row, col)
def get_channel(fd, ix):
ixcix = np.zeros(fd._ncells, np.int)
ixcix[fd._ix] = np.arange(len(fd._ix))
channel_points = [ix]
new_ind = ix
while ixcix[new_ind] != 0:
new_ind = fd._ixc[ixcix[new_ind]]
channel_points.append(new_ind)
return channel_points
def get_channel2(net, ix):
channel = [ix]
while ix.size > 0:
idx = np.where(net._ix == ix)
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 y = 4060151.087 row, col = fd.xy_2_cell(x, y) channel_ix = fd.cell_2_ind(row, col) #channel_points = [channel_ix] # #new_ind = channel_ix #while ixcix[new_ind] != 0: # new_ind = fd._ixc[ixcix[new_ind]] # channel_points.append(new_ind) # ##while ixcix[channel_points[-1]] != 0: ## channel_points.append(fd._ixc[ixcix[channel_points[-1]]]) # #marr = np.zeros(fd._ncells, np.int) #marr[channel_points] = 1 #marr = marr.reshape(fd._dims) #plt.imshow(marr)