def clonar_repositorio(directorio, url):
if os.path.exists(os.path.join('..', directorio)):
console.log(" Evitando clonar %s porque ya existe." % (directorio))
os.system('cd ..; git pull ')
else:
console.success("Clonando %s ..." % (directorio))
os.system('git clone ' + url + " " + directorio)
def clonar_repositorio(directorio, url):
if os.path.exists(os.path.join('..', directorio)):
console.log(" Evitando clonar %s porque ya existe." %(directorio))
os.system('cd ..; git pull ')
else:
console.success("Clonando %s ..." %(directorio))
os.system('cd ..; git clone ' + url + " " + directorio)
def SlopeReclass(bassin, zone, workdir, overwrite):
"""
Reclassification des pentes en 4 classes
"""
from qgis_helper import execute
from processing.tools.system import getTempDirInTempFolder
dem = os.path.join(workdir, bassin, zone, 'DEM5M.tif')
# slope = os.path.join(workdir, bassin, zone, 'SLOPE.tif')
output = os.path.join(workdir, bassin, zone, 'SLOPE_CLS.tif')
if os.path.exists(output) and not overwrite:
important('Output already exists : %s' % output)
return
info('Smooth DEM using 5x5 mean filter')
parameters = dict(input=dem,
bands=[1],
filter_type=0,
size=5,
output=os.path.join(getTempDirInTempFolder(),
'SMOOTHED.tif'))
result = execute("fct:simplerasterfilter", **parameters)
if 'OUTPUT' not in result:
warning('Error :(')
return
info('Calculate slope')
parameters = dict(input=result['OUTPUT'],
z_factor=1,
output=os.path.join(getTempDirInTempFolder(),
'SLOPE.tif'))
result = execute("qgis:slope", **parameters)
if 'OUTPUT' not in result:
warning('Error :(')
return
info('Reclass slopes')
parameters = dict(input_raster=result['OUTPUT'],
raster_band=1,
table=[0, 2, 1, 2, 6, 2, 6, 12, 3, 12, None, 4],
no_data=0,
range_boundaries=1,
nodata_for_missing=True,
data_type=0,
output=output)
result = execute('native:reclassifybytable', **parameters)
if 'OUTPUT' in result:
success('Saved to %s' % result['OUTPUT'])
def verify(args: argparse.Namespace):
con.pretty_printing = args.colors
try:
print("Validating IP Address ... ", end="")
ip = args.address.split(".")
# Check if IP has 4 decimal point
assert len(ip) == 4
# Check if any of them is empty
for ad in ip:
assert len(ad) != 0
assert network.ping(args.address)
con.success("OK")
# Verify if the path given is valid directory
print("Validating directory ... ", end="")
assert pathlib.Path(args.output).is_dir()
con.success("OK")
# Check if resume flag is enabled
if args.resume:
# Check if resume.json exists
print("Validating resume data ... ", end="")
assert pathlib.Path('resume.pyb').exists()
con.success("OK")
return args
except AssertionError:
con.error("FAILED")
quit(1)
def verify(args: argparse.Namespace):
con.pretty_printing = args.colors
try:
# Verify number of ports equal the number of servers
print("Validating server count ... ", end="")
assert args.number == len(args.ports)
con.success("OK")
print("Validating server ports ... ")
for port in args.ports:
print("\t{} ... ".format(port), end="")
assert network.check_sock(network.get_local_ip(), port)
con.success("OK")
# Verify a valid file was passed
print("Validating file ... ", end="")
assert pathlib.Path(args.file).is_file()
con.success("OK")
return args
except AssertionError:
con.error("FAILED")
quit(1)
#!/usr/bin/python
import os
import console
console.success("Bajando dependencias ...")
def clonar_repositorio(directorio, url):
if os.path.exists(os.path.join('..', directorio)):
console.log(" Evitando clonar %s porque ya existe." %(directorio))
os.system('cd ..; git pull ')
else:
console.success("Clonando %s ..." %(directorio))
os.system('cd ..; git clone ' + url + " " + directorio)
clonar_repositorio('pilasweb', 'https://github.com/hugoruscitti/pilasweb.git')
clonar_repositorio('blockly', 'https://github.com/Program-AR/blockly.git')
clonar_repositorio('closure-library', 'https://github.com/google/closure-library.git')
clonar_repositorio('ejerciciosPilas', 'https://github.com/Program-AR/ejerciciosPilas.git')
def ExtractZoneHydro(bassin, zone, **options):
"""
Re-délimitation des zones hydrographiques BDC à la résolution du MNT
1. Rastérise le réseau hydro cartographié en utilisant le même algorithme que celui utilisé dans l'algorithme `StreamToRaster` de la FCT
2. Calcule le plan de drainage en utilisant la variante de l'algorithme Priority Flood de Lindsay
3. Réalise une analyse de bassin versant (Watershed Analysis)
4. Vectorize le polygone correspondant à la zone indiquée
"""
root = options.get('workdir', '.')
overwrite = options.get('overwrite', False)
basename = options.get('output', 'ZONEHYDRO5M.shp')
flowdir = options.get('flowdir', 'FLOW.tif')
epsg = options.get('epsg', 2154)
info('Processing zone %s' % zone)
info('Working Directory = %s' % root)
raster_template = os.path.join(root, bassin, zone, 'DEM5M.tif')
stream_network = os.path.join(root, bassin, zone, 'StreamNetwork.shp')
output = os.path.join(root, bassin, zone, basename)
if os.path.exists(output) and not overwrite:
important('Output already exists : %s' % output)
return
feedback = ta.ConsoleFeedback()
with rio.open(raster_template) as ds:
info('Rasterize Stream Network')
elevations = ds.read(1)
transform = ds.transform
cdzonecnt = itertools.count(1)
cdzones = defaultdict(lambda: next(cdzonecnt))
fill_value = 0
# burn_value = 1
junctions = np.zeros((ds.height, ds.width), dtype=np.uint8)
streams = RasterizeStream(elevations, ds.transform, ds.nodata,
stream_network, fill_value, cdzones,
junctions)
# filename = os.path.join(root, bassin, zone, 'STREAMS.tif')
# info('Write %s' % filename)
# profile = ds.profile.copy()
# profile.update(compress='deflate')
# with rio.open(filename, 'w', **profile) as dst:
# dst.write(streams, 1)
# filename = os.path.join(root, bassin, zone, 'JUNCTIONS.tif')
# info(' Write %s' % filename)
# profile.update(dtype=np.uint8, nodata=255, compress='deflate')
# with rio.open(filename, 'w', **profile) as dst:
# dst.write(junctions, 1)
flow_raster = os.path.join(root, bassin, zone, flowdir)
info('Read Flow Direction from %s' % flow_raster)
with rio.open(flow_raster) as src:
flow = src.read(1)
info('Calculate Watersheds')
watersheds = np.copy(streams)
ta.watershed(flow, watersheds, fill_value, feedback)
feedback.setProgress(100)
# filename = os.path.join(root, bassin, zone, 'WATERSHEDS.tif')
# info('Write %s' % filename)
# profile = ds.profile.copy()
# profile.update(dtype=np.int32, nodata=0, compress='deflate')
# with rio.open(filename, 'w', **profile) as dst:
# dst.write(np.int32(watersheds), 1)
info('Vectorize Polygons')
watersheds = sieve(np.int32(watersheds), 400)
schema = {'geometry': 'Polygon', 'properties': [('CdZoneHydr', 'str:4')]}
crs = fiona.crs.from_epsg(epsg)
CdToZones = {v: k for k, v in cdzones.items()}
polygons = shapes(watersheds, (watersheds == cdzones[zone]),
connectivity=8,
transform=transform)
options = dict(driver='ESRI Shapefile', crs=crs, schema=schema)
with fiona.open(output, 'w', **options) as dst:
for polygon, value in polygons:
if value > 0:
geom = asShape(polygon).buffer(0.0)
feature = {
'geometry': geom.__geo_interface__,
'properties': {
'CdZoneHydr': CdToZones[value]
}
}
dst.write(feature)
success('Everything Ok')
#!/usr/bin/python
import os
import console
console.success("Generando lista de imagenes ...")
current_path = os.path.dirname(os.path.realpath(__file__))
image_path = os.path.join(current_path, '..', 'node_modules', 'pilas-bloques-exercises','dist', 'data')
output_path = os.path.join(current_path, '..', 'app', 'components', 'listaImagenes.js')
image_names = [x for x in os.listdir(image_path) if x.endswith('.png')]
content = [
'// Autogenerado por scripts/generarListaImagenes.py',
'// Todo cambio se sobreescribira.',
'export default [',
]
for name in sorted(image_names):
content.append(' "%s",' %(name))
content.append('];');
jsFile = open(output_path, "w+")
jsFile.write('\n'.join(content))
jsFile.close()
console.success("Se encontraron %d imagenes" %(len(image_names)))
def SlopeContinuity(bassin, zone, workdir, overwrite):
"""
DCOME
"""
from rasterio.features import sieve
basename = 'SLOPE_CLS_CONTINUOUS.tif'
flow_raster = os.path.join(workdir, bassin, zone, 'FLOW.tif')
slope_raster = os.path.join(workdir, bassin, zone, 'SLOPE_CLS.tif')
stream_network = os.path.join(workdir, bassin, zone, 'StreamNetwork.shp')
output = os.path.join(workdir, bassin, zone, basename)
if os.path.exists(output) and not overwrite:
important('Output already exists : %s' % output)
return
with rio.open(slope_raster) as ds:
slopes = sieve(ds.read(1), 800)
streams = RasterizeStream(slopes, ds.transform, ds.nodata,
stream_network, 0)
# data = np.float32(slopes) + 1
# data[slopes == ds.nodata] = ds.nodata
# data[streams == 1] = 0
# feedback = ta.ConsoleFeedback()
# distance = np.float32(ta.shortest_distance(data, ds.nodata, 0, feedback=feedback))
# out = np.zeros_like(slopes, dtype=np.float32)
# data[distance < 100] = 1
# data[streams == 1] = 0
# feedback = ta.ConsoleFeedback()
# ta.shortest_max(data, ds.nodata, 0, out=out, feedback=feedback)
# out = np.uint8(out) - 1
# out[distance < 100] = slopes[distance < 100]
# out[slopes == ds.nodata] = ds.nodata
out = np.zeros_like(slopes, dtype=np.float32)
out[streams == 1] = 1
with rio.open(flow_raster) as ds2:
flow = ds2.read(1)
feedback = ta.ConsoleFeedback()
ta.watershed_max(flow,
out,
np.float32(slopes),
fill_value=0,
feedback=feedback)
out = np.uint8(out)
# out[streams == 1] = slopes[streams == 1]
out[slopes == ds.nodata] = ds.nodata
profile = ds.profile.copy()
profile.update(compress='deflate')
with rio.open(output, 'w', **profile) as dst:
dst.write(out, 1)
success('Saved result to %s' % output)
#!/usr/bin/python
import os
import console
console.success("Generating Image List ...")
current_path = os.path.dirname(os.path.realpath(__file__))
image_path = os.path.join(current_path, '..', 'src', 'assets')
output_path = os.path.join(current_path, '..', 'dist', 'imageList.js')
image_names = [x for x in os.listdir(image_path) if x.endswith('.png')]
content = [
'// Autogenerated by %s' % (os.path.basename(__file__)),
'// Changes to this file will be overwritten',
'export let imageList = [',
]
for name in sorted(image_names):
content.append(' "%s",' % (name))
content.append('];')
jsFile = open(output_path, "w+")
jsFile.write('\n'.join(content))
jsFile.close()
console.success("Found %d images" % (len(image_names)))
#!/usr/bin/python
import os
import console
console.success("Bajando dependencias ...")
def clonar_repositorio(directorio, url):
if os.path.exists(os.path.join('..', directorio)):
console.log(" Evitando clonar %s porque ya existe." % (directorio))
os.system('cd ..; git pull ')
else:
console.success("Clonando %s ..." % (directorio))
os.system('git clone ' + url + " " + directorio)
clonar_repositorio('blockly', 'https://github.com/Program-AR/blockly.git')
clonar_repositorio('closure-library',
'https://github.com/google/closure-library.git')