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_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 processAlgorithm(self, parameters, context, feedback):
dem_raster = self.parameterAsRasterLayer(parameters, self.INPUT_DEM,
context)
fac_raster = self.parameterAsOutputLayer(parameters, self.OUTPUT_FAC,
context)
fd_raster = self.parameterAsOutputLayer(parameters, self.OUTPUT_FD,
context)
verbose = self.parameterAsBool(parameters, self.VERBOSE, context)
filled = self.parameterAsBool(parameters, self.FILLED, context)
auxtopo = self.parameterAsBool(parameters, self.AUXTOPO, context)
dem = DEM(dem_raster.source())
fd = Flow(dem,
auxtopo=auxtopo,
filled=filled,
verbose=verbose,
verb_func=feedback.setProgressText)
fac = fd.get_flow_accumulation()
fd.save_gtiff(fd_raster)
fac.save(fac_raster)
results = {}
results[self.OUTPUT_FD] = fd_raster
results[self.OUTPUT_FAC] = fac_raster
return results
# -*- coding: utf-8 -*-
from topopy import DEM, Flow
import numpy as np
import ogr, gdal
import matplotlib.pyplot as plt
# Get DEM, Flow Direction and Flow Accumulation
dem = DEM("../data/in/jebja30.tif")
fd = Flow(dem)
thr = 1000
fac = fd.get_flow_accumulation()
row, col = np.where(
np.logical_and(fac.read_array() > thr,
fac.read_array() != fac.get_nodata()))
x, y = fd.cell_2_xy(row, col)
coords = np.array((x, y)).T
geot = fac.get_geotransform()
xmin = geot[0]
xmax = geot[0] + fac.get_size()[0] * geot[1]
ymax = geot[3]
ymin = geot[3] + fac.get_size()[1] * geot[5]
extent = (xmin, ymin, xmax, ymax)
fig, ax = plt.subplots()
ax.plot(x, y, "ro")
class MyApp():
@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
y = 4060151.087
row, col = fd.xy_2_cell(x, y)
