def proximity_raster(src_filename, dst_filename, values, compression):
src_ds = gdal.Open(src_filename)
srcband = src_ds.GetRasterBand(1)
dst_filename = dst_filename
drv = gdal.GetDriverByName('GTiff')
dst_ds = drv.Create(dst_filename,
src_ds.RasterXSize,
src_ds.RasterYSize,
1,
gdal.GetDataTypeByName('Float32'),
options=['COMPRESS={}'.format(compression)])
dst_ds.SetGeoTransform(src_ds.GetGeoTransform())
dst_ds.SetProjection(src_ds.GetProjectionRef())
dstband = dst_ds.GetRasterBand(1)
gdal.ComputeProximity(srcband, dstband, [
"VALUES={}".format(','.join([str(i) for i in values])), "DISTUNITS=GEO"
])
srcband = None
dstband = None
src_ds = None
dst_ds = None
def proximity_1():
drv = gdal.GetDriverByName('GTiff')
src_ds = gdal.Open('data/pat.tif')
src_band = src_ds.GetRasterBand(1)
dst_ds = drv.Create('tmp/proximity_1.tif', 25, 25, 1, gdal.GDT_Byte)
dst_band = dst_ds.GetRasterBand(1)
gdal.ComputeProximity(src_band, dst_band)
cs_expected = 1941
cs = dst_band.Checksum()
dst_band = None
dst_ds = None
if cs == cs_expected \
or gdal.GetConfigOption('CPL_DEBUG', 'OFF') != 'ON':
drv.Delete('tmp/proximity_1.tif')
if cs != cs_expected:
print('Got: ', cs)
gdaltest.post_reason('got wrong checksum')
return 'fail'
return 'success'
def _computeProximityArrArgsFunc(argVals):
"""
This function is used internally within calcDist2Classes for the multiprocessing Pool
"""
import rsgislib.imageutils
try:
import tqdm
pbar = tqdm.tqdm(total=100)
callback = lambda *args, **kw: pbar.update()
except:
callback = gdal.TermProgress
classImgDS = gdal.Open(argVals[0], gdal.GA_ReadOnly)
classImgBand = classImgDS.GetRasterBand(1)
rsgislib.imageutils.createCopyImage(argVals[0], argVals[1], 1, argVals[3],
argVals[4], rsgislib.TYPE_32FLOAT)
distImgDS = gdal.Open(argVals[1], gdal.GA_Update)
distImgBand = distImgDS.GetRasterBand(1)
gdal.ComputeProximity(classImgBand,
distImgBand,
argVals[2],
callback=callback)
distImgBand = None
distImgDS = None
classImgBand = None
classImgDS = None
def proximity_2():
drv = gdal.GetDriverByName('GTiff')
src_ds = gdal.Open('data/pat.tif')
src_band = src_ds.GetRasterBand(1)
dst_ds = drv.Create('tmp/proximity_2.tif', 25, 25, 1, gdal.GDT_Float32)
dst_band = dst_ds.GetRasterBand(1)
gdal.ComputeProximity(src_band,
dst_band,
options=[
'VALUES=65,64', 'MAXDIST=12', 'NODATA=-1',
'FIXED_BUF_VAL=255'
])
cs_expected = 3256
cs = dst_band.Checksum()
dst_band = None
dst_ds = None
if cs == cs_expected \
or gdal.GetConfigOption('CPL_DEBUG', 'OFF') != 'ON':
drv.Delete('tmp/proximity_2.tif')
if cs != cs_expected:
print('Got: ', cs)
gdaltest.post_reason('got wrong checksum')
return 'fail'
return 'success'
def proximity_3():
drv = gdal.GetDriverByName('GTiff')
src_ds = gdal.Open('data/pat.tif')
src_band = src_ds.GetRasterBand(1)
dst_ds = drv.Create('tmp/proximity_3.tif', 25, 25, 1, gdal.GDT_Byte)
dst_band = dst_ds.GetRasterBand(1)
gdal.ComputeProximity(src_band,
dst_band,
options=[
'VALUES=65,64', 'MAXDIST=12',
'USE_INPUT_NODATA=YES', 'NODATA=0'
])
cs_expected = 1465
cs = dst_band.Checksum()
dst_band = None
dst_ds = None
if cs == cs_expected \
or gdal.GetConfigOption( 'CPL_DEBUG', 'OFF' ) != 'ON':
drv.Delete('tmp/proximity_3.tif')
if cs != cs_expected:
print('Got: ', cs)
gdaltest.post_reason('got wrong checksum')
return 'fail'
else:
return 'success'
def get_distance_raster(self,
base_layer,
output_path=None,
create_raster=True):
if self.distance == 'proximity':
with rasterio.open(base_layer) as src:
bounds = src.bounds
width = src.width
height = src.height
crs = src.crs
transform = src.transform
data, meta = self.rasterize(value=1,
width=width,
height=height,
transform=transform)
drv = gdal.GetDriverByName('MEM')
src_ds = drv.Create('', width, height, 1,
gdal.GetDataTypeByName('Float32'))
src_ds.SetGeoTransform(transform.to_gdal())
src_ds.SetProjection(crs.wkt)
src_ds.WriteArray(data)
srcband = src_ds.GetRasterBand(1)
drv = gdal.GetDriverByName('MEM')
dst_ds = drv.Create('', width, height, 1,
gdal.GetDataTypeByName('Float32'))
dst_ds.SetGeoTransform(transform.to_gdal())
dst_ds.SetProjection(crs.wkt)
dstband = dst_ds.GetRasterBand(1)
gdal.ComputeProximity(srcband, dstband,
["VALUES=1", "DISTUNITS=GEO"])
data = dstband.ReadAsArray()
meta.update(nodata=np.nan, dtype='float32')
if create_raster:
self.distance_raster = RasterLayer(
self.category,
self.name + '_dist',
distance_limit=self.distance_limit,
inverse=self.inverse,
normalization=self.normalization)
self.distance_raster.layer = data
self.distance_raster.meta = meta
self.distance_raster.bounds = bounds
if output_path:
self.distance_raster.save(output_path)
else:
return data, meta
elif self.distance == 'travel_time':
self.travel_time(output_path)
def calculateProximity(src_filename, dst_filename):
src_ds = gdal.Open( src_filename)
srcband = src_ds.GetRasterBand(1)
target_ds = createRaster(src_filename, dst_filename,gdal.GDT_Int32 )
dstband = target_ds.GetRasterBand(1)
options = []
options.append( 'DISTUNITS=PIXEL' )
options.append( 'NODATA=noDataValue')
gdal.ComputeProximity( srcband, dstband, options)
target_ds = None
def proximity_rast_ds(ds_raster_in, val=1):
drv = gdal.GetDriverByName('MEM')
proxy_ds = drv.Create('', ds_raster_in.RasterXSize,
ds_raster_in.RasterYSize, 1,
gdal.GetDataTypeByName('Float32'))
gdal.ComputeProximity(ds_raster_in.GetRasterBand(1),
proxy_ds.GetRasterBand(1),
["VALUES=" + str(val), "DISTUNITS=GEO"])
return proxy_ds
def __getNearestNeighbors__(self):
'''
Find the nearest neighbors of particular component amongst other components.
'''
#Initialize list of vertices
vertices = []
mem_drv = gdal.GetDriverByName('MEM')
for compNumber in range(1, self.nComponents + 1):
options = []
options.append('NODATA=0')
options.append('VALUES=%d' % (compNumber))
dst_ds = mem_drv.Create('', self.cc_ds.RasterXSize,
self.cc_ds.RasterYSize, 1, gdal.GDT_Int16)
dst_ds.SetGeoTransform(self.cc_ds.GetGeoTransform())
dst_ds.SetProjection(self.cc_ds.GetProjectionRef())
dstband = dst_ds.GetRasterBand(1)
print('Estimating neighbors of component : %d' % (compNumber))
gdal.ComputeProximity(self.ccband,
dstband,
options,
callback=gdal.TermProgress)
width = self.cc_ds.RasterXSize
dist = dstband.ReadAsArray()
#For each components, find the closest neighbor
#from the other components
ptList = []
for comp in range(1, self.nComponents + 1):
if comp != compNumber:
marr = np.ma.array(
dist, mask=(self.conncompAcc != comp)).argmin()
point = Vertex()
point.y, point.x = np.unravel_index(
marr, self.conncompAcc.shape)
point.compNumber = comp
point.source = compNumber
point.dist = dist[point.y, point.x]
ptList.append(point)
vertices += ptList
# Emptying dst_ds
dst_ds = None
# Emptying src_ds
src_ds = None
uniqVertices = self.__getUniqueVertices__(vertices)
return uniqVertices
def generateMask(self):
resol = self.resol
pointRaster = self.pointRaster
pointBand = pointRaster.GetRasterBand(1)
array = pointBand.ReadAsArray()
#plt.imshow(array)
#plt.show()
cols = pointRaster.RasterXSize
rows = pointRaster.RasterYSize
geoTrans = pointRaster.GetGeoTransform()
geoTrans = list(geoTrans)
x_min = geoTrans[0]
pixelWidth = geoTrans[1]
y_max = geoTrans[3]
pixelHeight = geoTrans[5]
#Generate distance layer
#-----------------------
driver = gdal.GetDriverByName('MEM')
distRaster = driver.Create('memory', cols, rows, 1, gdal.GDT_UInt16)
distRaster.SetGeoTransform(
(x_min, pixelWidth, 0, y_max, 0, pixelHeight))
outband = distRaster.GetRasterBand(1)
#outband.WriteArray(boolMat)
outRasterSRS = osr.SpatialReference()
outRasterSRS.ImportFromEPSG(self.epsg)
distRaster.SetProjection(outRasterSRS.ExportToWkt())
outband.FlushCache()
gdal.ComputeProximity(pointRaster.GetRasterBand(1), outband)
distBand = distRaster.GetRasterBand(1)
array = distBand.ReadAsArray()
#plt.imshow(array)
#plt.show()
idDel = np.nonzero(array >= resol)
mask = np.zeros(array.shape)
mask[idDel] = 1
#plt.imshow(mask)
#plt.show()
self.mask = mask
def distRasters(rst, outnme):
ref = gdal.Open(rst, GA_ReadOnly)
band = ref.GetRasterBand(1)
proj = ref.GetProjection()
geotransform = ref.GetGeoTransform()
xsize = band.XSize
ysize = band.YSize
gtiff = gdal.GetDriverByName('GTiff')
DataSet = gtiff.Create(outnme, xsize, ysize, 1, gdal.GDT_UInt16)
DataSet.SetGeoTransform(geotransform)
DataSet.SetProjection(proj)
options = []
gdal.ComputeProximity(band, DataSet.GetRasterBand(1), options, callback = None)
def proximity_raster(src_raster_path: str,
out_raster_path: str,
dist_units="PIXEL",
preserve_nodata=True):
"""Create a proximity raster
Args:
src_raster_path ([type]): [description]
out_raster_path ([type]): [description]
dist_units (str, optional): set to "GEO" for distance in length . Defaults to "PIXEL".
"""
log = Logger('proximity_raster')
tmr = Timer()
src_ds = gdal.Open(src_raster_path)
srcband = src_ds.GetRasterBand(1)
drv = gdal.GetDriverByName('GTiff')
with TempRaster('vbet_proximity_raster') as tempfile:
dst_ds = drv.Create(tempfile.filepath, src_ds.RasterXSize,
src_ds.RasterYSize, 1,
gdal.GetDataTypeByName('Float32'))
dst_ds.SetGeoTransform(src_ds.GetGeoTransform())
dst_ds.SetProjection(src_ds.GetProjectionRef())
dstband = dst_ds.GetRasterBand(1)
log.info('Creating proximity raster')
gdal.ComputeProximity(
srcband, dstband,
["VALUES=1", f"DISTUNITS={dist_units}", "COMPRESS=DEFLATE"])
srcband = None
dstband = None
src_ds = None
dst_ds = None
# Preserve the nodata from the source
if preserve_nodata:
mask_rasters_nodata(tempfile.filepath, src_raster_path,
out_raster_path)
else:
shutil.copyfile(tempfile.filepath, out_raster_path)
log.info('completed in {}'.format(tmr.toString()))
def createDistanceTransform(rasterSrc,
vectorSrc,
npDistFileName='',
units='pixels'):
## open source vector file that truth data
source_ds = ogr.Open(vectorSrc)
source_layer = source_ds.GetLayer()
## extract data from src Raster File to be emulated
## open raster file that is to be emulated
srcRas_ds = gdal.Open(rasterSrc)
cols = srcRas_ds.RasterXSize
rows = srcRas_ds.RasterYSize
noDataValue = 0
if units == 'meters':
geoTrans, poly, ulX, ulY, lrX, lrY = gT.getRasterExtent(srcRas_ds)
transform_WGS84_To_UTM, transform_UTM_To_WGS84, utm_cs = gT.createUTMTransform(
poly)
line = ogr.Geometry(ogr.wkbLineString)
line.AddPoint(geoTrans[0], geoTrans[3])
line.AddPoint(geoTrans[0] + geoTrans[1], geoTrans[3])
line.Transform(transform_WGS84_To_UTM)
metersIndex = line.Length()
else:
metersIndex = 1
## create First raster memory layer
memdrv = gdal.GetDriverByName('MEM')
dst_ds = memdrv.Create('', cols, rows, 1, gdal.GDT_Byte)
dst_ds.SetGeoTransform(srcRas_ds.GetGeoTransform())
dst_ds.SetProjection(srcRas_ds.GetProjection())
band = dst_ds.GetRasterBand(1)
band.SetNoDataValue(noDataValue)
gdal.RasterizeLayer(dst_ds, [1], source_layer, burn_values=[255])
srcBand = dst_ds.GetRasterBand(1)
memdrv2 = gdal.GetDriverByName('MEM')
prox_ds = memdrv2.Create('', cols, rows, 1, gdal.GDT_Int16)
prox_ds.SetGeoTransform(srcRas_ds.GetGeoTransform())
prox_ds.SetProjection(srcRas_ds.GetProjection())
proxBand = prox_ds.GetRasterBand(1)
proxBand.SetNoDataValue(noDataValue)
options = ['NODATA=0']
##compute distance to non-zero pixel values and scrBand and store in proxBand
gdal.ComputeProximity(srcBand, proxBand, options)
memdrv3 = gdal.GetDriverByName('MEM')
proxIn_ds = memdrv3.Create('', cols, rows, 1, gdal.GDT_Int16)
proxIn_ds.SetGeoTransform(srcRas_ds.GetGeoTransform())
proxIn_ds.SetProjection(srcRas_ds.GetProjection())
proxInBand = proxIn_ds.GetRasterBand(1)
proxInBand.SetNoDataValue(noDataValue)
options = ['NODATA=0', 'VALUES=0']
##compute distance to zero pixel values and scrBand and store in proxInBand
gdal.ComputeProximity(srcBand, proxInBand, options)
proxIn = gdalnumeric.BandReadAsArray(proxInBand)
proxOut = gdalnumeric.BandReadAsArray(proxBand)
##distance tranform is the distance to zero pixel values minus distance to non-zero pixel values
proxTotal = proxIn.astype(float) - proxOut.astype(float)
proxTotal = proxTotal * metersIndex
if npDistFileName != '':
np.save(npDistFileName, proxTotal)
return proxTotal
def createDistanceTransformByFeatureIndex(feature_index,
rasterSrc,
vectorSrc,
npDistFileName='',
units='pixels'):
## open source vector file that truth data
source_ds = ogr.Open(vectorSrc)
source_layer = source_ds.GetLayer()
#Define feature
my_feature = source_layer[feature_index]
#Spatial Reference
srs = source_layer.GetSpatialRef()
#Create feature Layer
outDriver = ogr.GetDriverByName('MEMORY')
outDataSource = outDriver.CreateDataSource('memData')
Feature_Layer = outDataSource.CreateLayer("this_feature",
srs,
geom_type=ogr.wkbPolygon)
#Add feature to layer
Feature_Layer.CreateFeature(my_feature)
## extract data from src Raster File to be emulated
## open raster file that is to be emulated
srcRas_ds = gdal.Open(rasterSrc)
cols = srcRas_ds.RasterXSize
rows = srcRas_ds.RasterYSize
noDataValue = 0
metersIndex = 1
## create First raster memory layer
memdrv = gdal.GetDriverByName('MEM')
dst_ds = memdrv.Create('', cols, rows, 1, gdal.GDT_Byte)
dst_ds.SetGeoTransform(srcRas_ds.GetGeoTransform())
dst_ds.SetProjection(srcRas_ds.GetProjection())
band = dst_ds.GetRasterBand(1)
band.SetNoDataValue(noDataValue)
gdal.RasterizeLayer(dst_ds, [1], Feature_Layer, burn_values=[255])
srcBand = dst_ds.GetRasterBand(1)
memdrv2 = gdal.GetDriverByName('MEM')
prox_ds = memdrv2.Create('', cols, rows, 1, gdal.GDT_Int16)
prox_ds.SetGeoTransform(srcRas_ds.GetGeoTransform())
prox_ds.SetProjection(srcRas_ds.GetProjection())
proxBand = prox_ds.GetRasterBand(1)
proxBand.SetNoDataValue(noDataValue)
options = ['NODATA=0']
gdal.ComputeProximity(srcBand, proxBand, options)
memdrv3 = gdal.GetDriverByName('MEM')
proxIn_ds = memdrv3.Create('', cols, rows, 1, gdal.GDT_Int16)
proxIn_ds.SetGeoTransform(srcRas_ds.GetGeoTransform())
proxIn_ds.SetProjection(srcRas_ds.GetProjection())
proxInBand = proxIn_ds.GetRasterBand(1)
proxInBand.SetNoDataValue(noDataValue)
options = ['NODATA=0', 'VALUES=0']
gdal.ComputeProximity(srcBand, proxInBand, options)
proxIn = gdalnumeric.BandReadAsArray(proxInBand)
proxOut = gdalnumeric.BandReadAsArray(proxBand)
proxTotal = proxIn.astype(float) - proxOut.astype(float)
proxTotal = proxTotal * metersIndex
if npDistFileName != '':
np.save(npDistFileName, proxTotal)
return proxTotal
def main(argv):
frmt = None
creation_options = []
options = []
src_filename = None
src_band_n = 1
dst_filename = None
dst_band_n = 1
creation_type = 'Float32'
quiet_flag = 0
gdal.AllRegister()
argv = gdal.GeneralCmdLineProcessor(argv)
if argv is None:
sys.exit(0)
# Parse command line arguments.
i = 1
while i < len(argv):
arg = argv[i]
if arg == '-of' or arg == '-f':
i = i + 1
frmt = argv[i]
elif arg == '-co':
i = i + 1
creation_options.append(argv[i])
elif arg == '-ot':
i = i + 1
creation_type = argv[i]
elif arg == '-maxdist':
i = i + 1
options.append('MAXDIST=' + argv[i])
elif arg == '-values':
i = i + 1
options.append('VALUES=' + argv[i])
elif arg == '-distunits':
i = i + 1
options.append('DISTUNITS=' + argv[i])
elif arg == '-nodata':
i = i + 1
options.append('NODATA=' + argv[i])
elif arg == '-use_input_nodata':
i = i + 1
options.append('USE_INPUT_NODATA=' + argv[i])
elif arg == '-fixed-buf-val':
i = i + 1
options.append('FIXED_BUF_VAL=' + argv[i])
elif arg == '-srcband':
i = i + 1
src_band_n = int(argv[i])
elif arg == '-dstband':
i = i + 1
dst_band_n = int(argv[i])
elif arg == '-q' or arg == '-quiet':
quiet_flag = 1
elif src_filename is None:
src_filename = argv[i]
elif dst_filename is None:
dst_filename = argv[i]
else:
Usage()
i = i + 1
if src_filename is None or dst_filename is None:
Usage()
# =============================================================================
# Open source file
# =============================================================================
src_ds = gdal.Open(src_filename)
if src_ds is None:
print('Unable to open %s' % src_filename)
sys.exit(1)
srcband = src_ds.GetRasterBand(src_band_n)
# =============================================================================
# Try opening the destination file as an existing file.
# =============================================================================
try:
driver = gdal.IdentifyDriver(dst_filename)
if driver is not None:
dst_ds = gdal.Open(dst_filename, gdal.GA_Update)
dstband = dst_ds.GetRasterBand(dst_band_n)
else:
dst_ds = None
except:
dst_ds = None
# =============================================================================
# Create output file.
# =============================================================================
if dst_ds is None:
if frmt is None:
frmt = GetOutputDriverFor(dst_filename)
drv = gdal.GetDriverByName(frmt)
dst_ds = drv.Create(dst_filename, src_ds.RasterXSize,
src_ds.RasterYSize, 1,
gdal.GetDataTypeByName(creation_type),
creation_options)
dst_ds.SetGeoTransform(src_ds.GetGeoTransform())
dst_ds.SetProjection(src_ds.GetProjectionRef())
dstband = dst_ds.GetRasterBand(1)
# =============================================================================
# Invoke algorithm.
# =============================================================================
if quiet_flag:
prog_func = None
else:
prog_func = gdal.TermProgress_nocb
gdal.ComputeProximity(srcband, dstband, options, callback=prog_func)
srcband = None
dstband = None
src_ds = None
dst_ds = None
rasterizedDS.GetRasterBand(1).SetNoDataValue(nodata)
rasterizedDS.SetGeoTransform(transform)
rasterizedDS.SetProjection(srs.ExportToWkt())
rasterizedDS.GetRasterBand(1).Fill(nodata)
gdal.RasterizeLayer(rasterizedDS, [1], ogr_vector_layer, burn_values=[1])
# =============================================================================
# 4. compute proximity from rasterized dataset
# =============================================================================
options = []
if Max_Distance > 0:
options.append('MAXDIST=' + str(Max_Distance))
proximityDs = driver.Create(Output, raster_width, raster_height, 1,
gdal.GetDataTypeByName(TYPES[Raster_Type]))
proximityDs.GetRasterBand(1).SetNoDataValue(nodata)
proximityDs.SetGeoTransform(transform)
proximityDs.SetProjection(srs.ExportToWkt())
proximityDs.GetRasterBand(1).Fill(nodata)
gdal.ComputeProximity(rasterizedDS.GetRasterBand(1),
proximityDs.GetRasterBand(1),
options,
callback=None)
# =============================================================================
# 5. cleanup
# =============================================================================
rasterizedDS = None
proximityDs = None
ogr_vector_datasource = None
# Create an empty raster to hold the rasterized roads.
road_ds = tif_driver.Create(road_raster_fn, cols, rows)
road_ds.SetProjection(road_lyr.GetSpatialRef().ExportToWkt())
road_ds.SetGeoTransform((minx, cellsize, 0, maxy, 0, -cellsize))
# Burn the roads into the raster.
gdal.RasterizeLayer(road_ds, [1],
road_lyr,
burn_values=[1],
callback=gdal.TermProgress)
# Burn proximity to roads into a new raster.
prox_ds = tif_driver.Create(proximity_fn, cols, rows, 1, gdal.GDT_Int32)
prox_ds.SetProjection(road_ds.GetProjection())
prox_ds.SetGeoTransform(road_ds.GetGeoTransform())
gdal.ComputeProximity(road_ds.GetRasterBand(1), prox_ds.GetRasterBand(1),
['DISTUNITS=GEO'], gdal.TermProgress)
# Burn the wilderness area into a temporary raster.
wild_ds = gdal.GetDriverByName('MEM').Create('tmp', cols, rows)
wild_ds.SetProjection(prox_ds.GetProjection())
wild_ds.SetGeoTransform(prox_ds.GetGeoTransform())
gdal.RasterizeLayer(wild_ds, [1],
wild_lyr,
burn_values=[1],
callback=gdal.TermProgress)
# Use the temporary wilderness raster to set the proximity one
# to NoData everywhere that is outside the wilderness area.
wild_data = wild_ds.ReadAsArray()
prox_data = prox_ds.ReadAsArray()
prox_data[wild_data == 0] = -99
def gdal_proximity(
src_filename: Optional[str] = None,
src_band_n: int = 1,
dst_filename: Optional[str] = None,
dst_band_n: int = 1,
driver_name: Optional[str] = None,
creation_type: str = 'Float32',
creation_options: Optional[Sequence[str]] = None,
alg_options: Optional[Sequence[str]] = None,
quiet: bool = False):
# =============================================================================
# Open source file
# =============================================================================
creation_options = creation_options or []
alg_options = alg_options or []
src_ds = gdal.Open(src_filename)
if src_ds is None:
print('Unable to open %s' % src_filename)
return 1
srcband = src_ds.GetRasterBand(src_band_n)
# =============================================================================
# Try opening the destination file as an existing file.
# =============================================================================
try:
driver_name = gdal.IdentifyDriver(dst_filename)
if driver_name is not None:
dst_ds = gdal.Open(dst_filename, gdal.GA_Update)
dstband = dst_ds.GetRasterBand(dst_band_n)
else:
dst_ds = None
except:
dst_ds = None
# =============================================================================
# Create output file.
# =============================================================================
if dst_ds is None:
if driver_name is None:
driver_name = GetOutputDriverFor(dst_filename)
drv = gdal.GetDriverByName(driver_name)
dst_ds = drv.Create(dst_filename,
src_ds.RasterXSize, src_ds.RasterYSize, 1,
gdal.GetDataTypeByName(creation_type), creation_options)
dst_ds.SetGeoTransform(src_ds.GetGeoTransform())
dst_ds.SetProjection(src_ds.GetProjectionRef())
dstband = dst_ds.GetRasterBand(1)
# =============================================================================
# Invoke algorithm.
# =============================================================================
if quiet:
prog_func = None
else:
prog_func = gdal.TermProgress_nocb
gdal.ComputeProximity(srcband, dstband, alg_options,
callback=prog_func)
srcband = None
dstband = None
src_ds = None
dst_ds = None
transform=out.transform)
out.write_band(1, burned)
# Proximité (distance raster) depuis les équipements rastérisés
if not equip_zone.empty:
src_ds = gdal.Open('structure_zone_r.tif')
srcband = src_ds.GetRasterBand(1)
dst_filename = 'prox_r.tif'
drv = gdal.GetDriverByName('GTiff')
dst_ds = drv.Create(dst_filename, src_ds.RasterXSize, src_ds.RasterYSize,
1, gdal.GetDataTypeByName('Float32'))
dst_ds.SetGeoTransform(src_ds.GetGeoTransform())
dst_ds.SetProjection(src_ds.GetProjectionRef())
dstband = dst_ds.GetRasterBand(1)
gdal.ComputeProximity(
srcband, dstband,
["DISTUNITS=GEO"]) #Algo de proximité (distance géo et non en pixels)
# Note intéressante : le fichier ne s'écrit totalement QUE quand le traitement est relancé, c'est pourquoi
# Je recopie le MÊME CODE deux fois pour écrire un .tif pourri qui ne servira à rien
if not equip_zone.empty:
src_ds = gdal.Open('structure_zone_r.tif')
srcband = src_ds.GetRasterBand(1)
dst_filename = 'prox_r_useless.tif'
drv = gdal.GetDriverByName('GTiff')
dst_ds = drv.Create(dst_filename, src_ds.RasterXSize, src_ds.RasterYSize,
1, gdal.GetDataTypeByName('Float32'))
dst_ds.SetGeoTransform(src_ds.GetGeoTransform())
dst_ds.SetProjection(src_ds.GetProjectionRef())
dstband = dst_ds.GetRasterBand(1)
gdal.ComputeProximity(
def main(args):
# --------------------------------------------------------------------------- #
# Parse arguments
# --------------------------------------------------------------------------- #
parser = argparse.ArgumentParser(prog=__program_name__, )
# Help arguments
parser.add_argument('--help-info',
dest='help_info',
action='store_true',
help='Display more detailed help information')
# Output options
parser.add_argument('-of',
'--output-format',
dest='driver_name',
type=str,
action='store',
default='GTiff',
metavar='driver',
help='Output raster driver name')
parser.add_argument('-tr',
'--target-res',
required=True,
dest='target_resolution',
type=int,
nargs=2,
action='store',
metavar=('xres', 'yres'),
help='Target pixel resolution in georeferenced units')
parser.add_argument(
'-at',
'--all-touched',
dest='all_touched',
action='store_true',
default=False,
help=
"Rasterizes features into all touched pixels instead of just those on the line render path or whose center point is within the polygon"
)
parser.add_argument('-nd',
'--nodata',
dest='nodata',
default=0,
type=int,
action='store',
help='Destination nodata value')
parser.add_argument(
'-md',
'--max-distance',
dest='max_distance',
type=int,
action='append',
help=
'Maximum search distance for non-nodata pixels when computing distance'
)
parser.add_argument(
'-du',
'-dist-units',
dest='distance_units',
choices=('GEO', 'PIXEL'),
default='GEO',
type=str,
action='store',
help=
'Values to write when computing distance - num pixels or georeferenced units'
)
parser.add_argument(
'-fbv',
'--fixed-buff-val',
dest='fixed_buffer_val',
type=int,
action='store',
help=
'Write this value instead of distance for all pixels that are within the max distance'
)
parser.add_argument('-l',
'--layers',
dest='layers_to_process',
type=str,
nargs='+',
action='append',
help='Layers to process')
parser.add_argument('-co',
'--creation-option',
dest='creation_options',
type=str,
default=[],
action='append',
metavar='OPTION=VAL',
help='Output format supported creation option')
parser.add_argument('-ovr',
'--overview',
dest='overviews',
type=int,
nargs='+',
metavar='level',
help='Overview levels')
parser.add_argument('-or',
'--ovr-resampling',
dest='overview_resampling',
choices=('nearest', 'average', 'gauss', 'cubic',
'average_mp', 'average_magphase', 'mode'),
default='nearest',
help='Overview resampling method')
parser.add_argument('--overwrite',
dest='overwrite_mode',
action='store_true',
default=False,
help='Blindly overwrite the output file if it exists')
# Positional arguments and errors
parser.add_argument('input_vector',
metavar='src_vector',
type=str,
action='store',
help='Vector to calculate distance against')
parser.add_argument('output_raster',
metavar='dst_raster',
type=str,
action='store',
help='Output raster containing distance values')
pargs = parser.parse_args(args=args)
# --------------------------------------------------------------------------- #
# Adjust and validate parameters
# --------------------------------------------------------------------------- #
# Force cell sizes to be positive
pargs.target_resolution = [abs(i) for i in pargs.target_resolution]
bail = False
# Check input vector
try:
ds = ogr.Open(pargs.input_vector, 0)
if ds is None:
del ds
bail = True
print("ERROR: Can't access input vector: %s" % pargs.input_vector)
except RuntimeError:
pass
# Check output raster
try:
ds = gdal.Open(pargs.output_raster, 0)
if ds is not None and not pargs.overwrite_mode:
ds = None
bail = True
print("ERROR: Overwrite=%s and output raster exists: %s" %
(pargs.overwrite_mode, pargs.output_raster))
except RuntimeError:
pass
if bail:
return 1
# --------------------------------------------------------------------------- #
# Prep workspace
# --------------------------------------------------------------------------- #
vds = ogr.Open(pargs.input_vector)
# Get full extent of all vector layers being processed and make sure all layers are in the same spatial reference
print("Computing input vector extent ...")
vds_srs = None
vds_extent = []
for layer in vds:
if pargs.layers_to_process is None or layer.GetName(
) in pargs.layers_to_process:
# Check SRS
if vds_srs is None:
vds_srs = layer.GetSpatialRef()
elif not vds_srs.IsSame(layer.GetSpatialRef()):
vds = None
print(
"ERROR: One or more input layers do not have the same SRS")
return 1
# Update extent
min_x, max_x, min_y, max_y = layer.GetExtent()
if len(vds_extent) is 0:
vds_extent = [min_x, min_y, max_x, max_y]
else:
if min_x < vds_extent[0]:
vds_extent[0] = min_x
if min_y < vds_extent[1]:
vds_extent[1] = min_y
if max_x > vds_extent[2]:
vds_extent[2] = max_x
if max_y > vds_extent[3]:
vds_extent[3] = max_y
# Construct an in-memory raster that will store the rasterized vectors
print("Building an in-memory raster for rasterization ...")
vds_geotransform = (vds_extent[0], pargs.target_resolution[0], 0,
vds_extent[3], 0, -pargs.target_resolution[1])
x_res = int((vds_extent[2] - vds_extent[0]) / pargs.target_resolution[0])
y_res = int((vds_extent[3] - vds_extent[1]) / pargs.target_resolution[1])
rize_ds = gdal.GetDriverByName(str('MEM')).Create(
str('rasterization_memory_ds'), x_res, y_res, 1, gdal.GDT_Byte)
rize_ds.SetGeoTransform(vds_geotransform)
rize_ds.SetProjection(vds_srs.ExportToWkt())
band = rize_ds.GetRasterBand(1)
band.SetNoDataValue(pargs.nodata)
band = None
# Create output datasource
rdriver = gdal.GetDriverByName(str(pargs.driver_name))
if rdriver is None:
vds = None
rize_ds = None
print("ERROR: Invalid driver: '%s'" % pargs.driver_name)
return 1
rds = rdriver.Create(str(pargs.output_raster),
rize_ds.RasterXSize,
rize_ds.RasterYSize,
1,
gdal.GDT_Float32,
options=pargs.creation_options)
if rds is None:
vds = None
rize_ds = None
print("ERROR: Could not create output raster: %s" %
pargs.output_raster)
return 1
rdriver = None
rds.SetGeoTransform(vds_geotransform)
rds.SetProjection(vds_srs.ExportToWkt())
# --------------------------------------------------------------------------- #
# Rasterize input layers
# --------------------------------------------------------------------------- #
if pargs.all_touched:
rize_options = ['ALL_TOUCHED=TRUE']
else:
rize_options = []
rize_options.append('MERGE_ALG=REPLACE')
rize_options = [str(opt) for opt in rize_options]
for layer in vds:
if pargs.layers_to_process is None or layer.GetName(
) in pargs.layers_to_process:
print("Rasterizing layer '%s' ..." % layer.GetName())
gdal.RasterizeLayer(rize_ds, [1],
layer,
options=rize_options,
burn_values=[1],
callback=gdal.TermProgress)
# --------------------------------------------------------------------------- #
# Compute proximity
# --------------------------------------------------------------------------- #
# Assemble options for proximity calculation
proximity_options = []
if pargs.max_distance:
proximity_options.append('MAXDIST=%s' % pargs.max_distance)
if pargs.distance_units:
proximity_options.append('DISTUNITS=%s' % pargs.distance_units)
if pargs.fixed_buffer_val:
proximity_options.append('FIXED_BUF_VAL=%s' % pargs.fixed_buffer_val)
proximity_options.append('VALUES=1')
proximity_options.append('NODATA=0')
proximity_options = [str(opt) for opt in proximity_options]
# Compute proximity
print("Computing proximity ...")
output_band = rds.GetRasterBand(1)
output_band.SetNoDataValue(pargs.nodata)
gdal.ComputeProximity(rize_ds.GetRasterBand(1),
output_band,
options=proximity_options,
callback=gdal.TermProgress)
# --------------------------------------------------------------------------- #
# Generate overviews
# --------------------------------------------------------------------------- #
if pargs.overviews:
print("Generating overview: %s" %
', '.join([str(o) for o in pargs.overviews]))
rds.BuildOverviews(resampling=str(pargs.overview_resampling),
overviewlist=pargs.overviews,
callback=gdal.TermProgress)
# Cleanup
band = None
output_band = None
vds_srs = None
vds = None
layer = None
rize_ds = None
rds = None
return 0
target_ds.SetGeoTransform((x_min, pixel_size, 0, y_max, 0, -pixel_size))
band = target_ds.GetRasterBand(1)
band.SetNoDataValue(NoData_value)
##
### Rasterize
gdal.RasterizeLayer(target_ds, [1], source_layer, burn_values=[1])
##
###Find Distance
target2_ds = gdal.GetDriverByName('GTiff').Create(raster2_fn, x_res, y_res,
2, gdal.GDT_Int16)
target2_ds.SetGeoTransform((x_min, pixel_size, 0, y_max, 0, -pixel_size))
##
srcband = target_ds.GetRasterBand(1)
dstband = target2_ds.GetRasterBand(1)
gdal.ComputeProximity(srcband, dstband)
##
###Convert to Array
myarray = np.array(target2_ds.GetRasterBand(1).ReadAsArray())
newarray = 500 - myarray
outputar = np.where(newarray < 0, 0, newarray)
arraylist.append(outputar[:])
print np.max(outputar)
outBand = target2_ds.GetRasterBand(2)
outBand.WriteArray(outputar)
totalarray = arraylist[0] * 0
def processAlgorithm(self, parameters, context, feedback):
source = self.parameterAsVectorLayer(parameters, self.INPUT, context)
if source is None:
raise QgsProcessingException(
self.invalidSourceError(parameters, self.INPUT))
max_distance = self.parameterAsDouble(parameters, self.MAX_DISTANCE,
context)
raster_type = self.RASTER_TYPES[self.parameterAsEnum(
parameters, self.RASTER_TYPE, context)]
extent = self.parameterAsExtent(parameters, self.EXTENT, context,
source.sourceCrs())
if extent is None or extent.width() == 0 or extent.height() == 0:
extent = source.sourceExtent()
cell_size = self.parameterAsDouble(parameters, self.CELL_SIZE, context)
if cell_size <= 0:
cell_size = int(min(extent.width(), extent.height()) / 250.0)
output_raster = self.parameterAsOutputLayer(parameters, self.OUTPUT,
context)
# open ogr vector layer from qgs map layer
ogrLayer, layerName = self.getOgrCompatibleSource(
self.INPUT, parameters, context, feedback, True)
if ogrLayer is None:
raise QgsProcessingException('Cannot connect OGR driver!')
ogr_vector_datasource = ogr.Open(ogrLayer)
ogr_vector_layer = ogr_vector_datasource.GetLayer(layerName)
feedback.pushInfo('Raster Type = {0}'.format(raster_type))
feedback.pushInfo('Cell Size = {0}'.format(cell_size))
feedback.pushInfo('Extent = {0}'.format(extent))
nodata = -9999
srs = osr.SpatialReference()
srs.ImportFromWkt(source.crs().toWkt())
transform = [
extent.xMinimum(), cell_size, 0.0,
extent.yMaximum(), 0.0, -cell_size
]
raster_width = int(
math.ceil(abs(extent.xMaximum() - extent.xMinimum()) / cell_size))
raster_height = int(
math.ceil(abs(extent.yMaximum() - extent.yMinimum()) / cell_size))
# rasterize temporary raterdataset from vector layer, extent, cellsize
temporary_path = os.path.join(
QgsProcessingUtils.tempFolder(),
'euc_distance_{}.tif'.format(uuid.uuid4().hex))
feedback.pushInfo('Temporary path = {0}'.format(temporary_path))
driver = gdal.GetDriverByName('GTiff')
rasterizedDS = driver.Create(temporary_path, raster_width,
raster_height, 1, gdal.GDT_Byte)
rasterizedDS.GetRasterBand(1).SetNoDataValue(nodata)
rasterizedDS.SetGeoTransform(transform)
rasterizedDS.SetProjection(srs.ExportToWkt())
rasterizedDS.GetRasterBand(1).Fill(nodata)
gdal.RasterizeLayer(rasterizedDS, [1],
ogr_vector_layer,
burn_values=[1])
# compute proximity from rasterized dataset
options = ['DISTUNITS=GEO']
if max_distance > 0:
options.append('MAXDIST=' + str(max_distance))
proximityDs = driver.Create(output_raster, raster_width, raster_height,
1, gdal.GetDataTypeByName(raster_type))
proximityDs.GetRasterBand(1).SetNoDataValue(nodata)
proximityDs.SetGeoTransform(transform)
proximityDs.SetProjection(srs.ExportToWkt())
proximityDs.GetRasterBand(1).Fill(nodata)
gdal.ComputeProximity(rasterizedDS.GetRasterBand(1),
proximityDs.GetRasterBand(1),
options,
callback=None)
# cleanup
rasterizedDS = None
proximityDs = None
ogr_vector_datasource = None
return {self.OUTPUT: output_raster}
def calc_proximity(
input_rasters,
target_value=1,
out_path=None,
max_dist=1000,
add_border=False,
weighted=False,
invert=False,
return_array=False,
postfix="_proximity",
uuid=False,
overwrite=True,
skip_existing=False,
):
"""
Calculate the proximity of input_raster to values
"""
raster_list, path_list = ready_io_raster(input_rasters,
out_path,
overwrite,
postfix=postfix,
uuid=uuid)
output = []
for index, input_raster in enumerate(raster_list):
out_path = path_list[index]
if skip_existing and os.path.exists(out_path):
output.append(out_path)
continue
in_arr = raster_to_array(input_raster, filled=True)
bin_arr = (in_arr != target_value).astype("uint8")
bin_raster = array_to_raster(bin_arr, reference=input_raster)
in_raster = open_raster(bin_raster)
in_raster_path = bin_raster
if add_border:
border_size = 1
border_raster = add_border_to_raster(
in_raster,
border_size=border_size,
border_value=0,
overwrite=True,
)
in_raster = open_raster(border_raster)
gdal.Unlink(in_raster_path)
in_raster_path = border_raster
src_band = in_raster.GetRasterBand(1)
driver_name = "GTiff" if out_path is None else path_to_driver_raster(
out_path)
if driver_name is None:
raise ValueError(f"Unable to parse filetype from path: {out_path}")
driver = gdal.GetDriverByName(driver_name)
if driver is None:
raise ValueError(
f"Error while creating driver from extension: {out_path}")
mem_path = f"/vsimem/raster_proximity_tmp_{uuid4().int}.tif"
dest_raster = driver.Create(
mem_path,
in_raster.RasterXSize,
in_raster.RasterYSize,
1,
gdal.GetDataTypeByName("Float32"),
)
dest_raster.SetGeoTransform(in_raster.GetGeoTransform())
dest_raster.SetProjection(in_raster.GetProjectionRef())
dst_band = dest_raster.GetRasterBand(1)
gdal.ComputeProximity(
src_band,
dst_band,
[
f"VALUES='1'",
"DISTUNITS=GEO",
f"MAXDIST={max_dist}",
],
)
dst_arr = dst_band.ReadAsArray()
gdal.Unlink(mem_path)
gdal.Unlink(in_raster_path)
dst_arr = np.where(dst_arr > max_dist, max_dist, dst_arr)
if invert:
dst_arr = max_dist - dst_arr
if weighted:
dst_arr = dst_arr / max_dist
if add_border:
dst_arr = dst_arr[border_size:-border_size,
border_size:-border_size]
src_band = None
dst_band = None
in_raster = None
dest_raster = None
if return_array:
output.append(dst_arr)
else:
array_to_raster(dst_arr, reference=input_raster, out_path=out_path)
output.append(out_path)
dst_arr = None
if isinstance(input_rasters, list):
return output
return output[0]
def create_dist_map(rasterSrc, vectorSrc, npDistFileName='',
noDataValue=0, burn_values=255,
dist_mult=1, vmax_dist=64):
source_ds = ogr.Open(vectorSrc)
source_layer = source_ds.GetLayer()
srcRas_ds = gdal.Open(rasterSrc)
cols = srcRas_ds.RasterXSize
rows = srcRas_ds.RasterYSize
geoTrans, poly, ulX, ulY, lrX, lrY = gT.getRasterExtent(srcRas_ds)
transform_WGS84_To_UTM, transform_UTM_To_WGS84, utm_cs \
= gT.createUTMTransform(poly)
line = ogr.Geometry(ogr.wkbLineString)
line.AddPoint(geoTrans[0], geoTrans[3])
line.AddPoint(geoTrans[0]+geoTrans[1], geoTrans[3])
line.Transform(transform_WGS84_To_UTM)
metersIndex = line.Length()
memdrv = gdal.GetDriverByName('MEM')
dst_ds = memdrv.Create('', cols, rows, 1, gdal.GDT_Byte)
dst_ds.SetGeoTransform(srcRas_ds.GetGeoTransform())
dst_ds.SetProjection(srcRas_ds.GetProjection())
band = dst_ds.GetRasterBand(1)
band.SetNoDataValue(noDataValue)
gdal.RasterizeLayer(dst_ds, [1], source_layer, burn_values=[burn_values])
srcBand = dst_ds.GetRasterBand(1)
memdrv2 = gdal.GetDriverByName('MEM')
prox_ds = memdrv2.Create('', cols, rows, 1, gdal.GDT_Int16)
prox_ds.SetGeoTransform(srcRas_ds.GetGeoTransform())
prox_ds.SetProjection(srcRas_ds.GetProjection())
proxBand = prox_ds.GetRasterBand(1)
proxBand.SetNoDataValue(noDataValue)
opt_string = 'NODATA='+str(noDataValue)
options = [opt_string]
gdal.ComputeProximity(srcBand, proxBand, options)
memdrv3 = gdal.GetDriverByName('MEM')
proxIn_ds = memdrv3.Create('', cols, rows, 1, gdal.GDT_Int16)
proxIn_ds.SetGeoTransform(srcRas_ds.GetGeoTransform())
proxIn_ds.SetProjection(srcRas_ds.GetProjection())
proxInBand = proxIn_ds.GetRasterBand(1)
proxInBand.SetNoDataValue(noDataValue)
opt_string2 = 'VALUES='+str(noDataValue)
options = [opt_string, opt_string2]
gdal.ComputeProximity(srcBand, proxInBand, options)
proxIn = gdalnumeric.BandReadAsArray(proxInBand)
proxOut = gdalnumeric.BandReadAsArray(proxBand)
proxTotal = proxIn.astype(float) - proxOut.astype(float)
proxTotal = proxTotal*metersIndex
proxTotal *= dist_mult
proxTotal = np.clip(proxTotal, -1*vmax_dist, 1*vmax_dist)
if npDistFileName != '':
np.save(npDistFileName, proxTotal)
# Create temporal raster
rasterize_options = gdal.RasterizeOptions(
xRes=xres, yRes=yres, allTouched=True, burnValues=[1]
)
temp1 = gdal.Rasterize(
"/vsimem/temp", feature.get("path"), options=rasterize_options
)
temp1_band = temp1.GetRasterBand(1)
# Create temporal proximity raster
driver = gdal.GetDriverByName("MEM")
temp2 = driver.Create("temp2", temp1.RasterXSize, temp1.RasterYSize)
temp2.SetGeoTransform(temp1.GetGeoTransform())
temp2.SetProjection(temp1.GetProjection())
temp2_band = temp2.GetRasterBand(1)
gdal.ComputeProximity(temp1_band, temp2_band, ["VALUES=1"])
temp2_band.FlushCache()
# Clip to region area
warp_options = gdal.WarpOptions(
outputBounds=match_ds.rio.bounds(),
creationOptions=["COMPRESS=LZW"],
outputType=gdal.GDT_Int16,
dstNodata=NODATA_VALUE,
cutlineDSName=region.get("path"),
)
dst_fn = os.path.join(output_folder, f"{feature.get('name')}_proximity.tif")
temp3 = gdal.Warp(dst_fn, temp2, options=warp_options)
stack.append(temp3.ReadAsArray())
stack = np.stack(stack)
def create_dist_map(rasterSrc,
vectorSrc,
npDistFileName='',
noDataValue=0,
burn_values=1,
dist_mult=1,
vmax_dist=64):
'''
Create building signed distance transform from Yuan 2016
(https://arxiv.org/pdf/1602.06564v1.pdf).
vmax_dist: absolute value of maximum distance (meters) from building edge
Adapted from createNPPixArray in labeltools
'''
## open source vector file that truth data
source_ds = ogr.Open(vectorSrc)
source_layer = source_ds.GetLayer()
## extract data from src Raster File to be emulated
## open raster file that is to be emulated
srcRas_ds = gdal.Open(rasterSrc)
cols = srcRas_ds.RasterXSize
rows = srcRas_ds.RasterYSize
geoTrans, poly, ulX, ulY, lrX, lrY = gT.getRasterExtent(srcRas_ds)
transform_WGS84_To_UTM, transform_UTM_To_WGS84, utm_cs \
= gT.createUTMTransform(poly)
line = ogr.Geometry(ogr.wkbLineString)
line.AddPoint(geoTrans[0], geoTrans[3])
line.AddPoint(geoTrans[0] + geoTrans[1], geoTrans[3])
line.Transform(transform_WGS84_To_UTM)
metersIndex = line.Length()
memdrv = gdal.GetDriverByName('MEM')
dst_ds = memdrv.Create('', cols, rows, 1, gdal.GDT_Byte)
dst_ds.SetGeoTransform(srcRas_ds.GetGeoTransform())
dst_ds.SetProjection(srcRas_ds.GetProjection())
band = dst_ds.GetRasterBand(1)
band.SetNoDataValue(noDataValue)
gdal.RasterizeLayer(dst_ds, [1], source_layer, burn_values=[burn_values])
srcBand = dst_ds.GetRasterBand(1)
memdrv2 = gdal.GetDriverByName('MEM')
prox_ds = memdrv2.Create('', cols, rows, 1, gdal.GDT_Int16)
prox_ds.SetGeoTransform(srcRas_ds.GetGeoTransform())
prox_ds.SetProjection(srcRas_ds.GetProjection())
proxBand = prox_ds.GetRasterBand(1)
proxBand.SetNoDataValue(noDataValue)
opt_string = 'NODATA=' + str(noDataValue)
options = [opt_string]
gdal.ComputeProximity(srcBand, proxBand, options)
memdrv3 = gdal.GetDriverByName('MEM')
proxIn_ds = memdrv3.Create('', cols, rows, 1, gdal.GDT_Int16)
proxIn_ds.SetGeoTransform(srcRas_ds.GetGeoTransform())
proxIn_ds.SetProjection(srcRas_ds.GetProjection())
proxInBand = proxIn_ds.GetRasterBand(1)
proxInBand.SetNoDataValue(noDataValue)
opt_string2 = 'VALUES=' + str(noDataValue)
options = [opt_string, opt_string2]
#options = ['NODATA=0', 'VALUES=0']
gdal.ComputeProximity(srcBand, proxInBand, options)
proxIn = gdalnumeric.BandReadAsArray(proxInBand)
proxOut = gdalnumeric.BandReadAsArray(proxBand)
proxTotal = proxIn.astype(float) - proxOut.astype(float)
proxTotal = proxTotal * metersIndex
proxTotal *= dist_mult
# clip array
proxTotal = np.clip(proxTotal, -1 * vmax_dist, 1 * vmax_dist)
if npDistFileName != '':
# save as numpy file since some values will be negative
np.save(npDistFileName, proxTotal)
#cv2.imwrite(npDistFileName, proxTotal)
return proxTotal
# =============================================================================
if dst_ds is None:
if format is None:
format = GetOutputDriverFor(dst_filename)
drv = gdal.GetDriverByName(format)
dst_ds = drv.Create(dst_filename, src_ds.RasterXSize, src_ds.RasterYSize,
1, gdal.GetDataTypeByName(creation_type),
creation_options)
dst_ds.SetGeoTransform(src_ds.GetGeoTransform())
dst_ds.SetProjection(src_ds.GetProjectionRef())
dstband = dst_ds.GetRasterBand(1)
# =============================================================================
# Invoke algorithm.
# =============================================================================
if quiet_flag:
prog_func = None
else:
prog_func = gdal.TermProgress_nocb
gdal.ComputeProximity(srcband, dstband, options, callback=prog_func)
srcband = None
dstband = None
src_ds = None
dst_ds = None
def proximity_shp(fn_shp, raster_ref, type_prox='both'):
# create memory raster based on reference raster
raster_ds = create_mem_raster_on_ref(raster_ref)
# open .shp with GDAL
shp_ds = gdal.OpenEx(fn_shp, gdal.OF_VECTOR)
# rasterize
opts = gdal.RasterizeOptions(burnValues=[1], bands=[1])
gdal.Rasterize(raster_ds, shp_ds, options=opts)
# close shp
shp_ds = None
drv = gdal.GetDriverByName('MEM')
proxy_ds = drv.Create('', raster_ds.RasterXSize, raster_ds.RasterYSize, 1,
gdal.GetDataTypeByName('Float32'))
if type_prox == 'exterior':
gdal.ComputeProximity(raster_ds.GetRasterBand(1),
proxy_ds.GetRasterBand(1),
["VALUES=1", "DISTUNITS=GEO"])
proxy_array = proxy_ds.GetRasterBand(1).ReadAsArray()
elif type_prox == 'interior':
raster_arr = raster_ds.GetRasterBand(1).ReadAsArray()
mask = (raster_arr == 1)
raster_arr[mask] = raster_ds.GetRasterBand(1).GetNoDataValue()
raster_arr[~mask] = 1
raster_ds.GetRasterBand(1).WriteArray(raster_arr)
gdal.ComputeProximity(raster_ds.GetRasterBand(1),
proxy_ds.GetRasterBand(1),
["VALUES=1", "DISTUNITS=GEO"])
proxy_array = proxy_ds.GetRasterBand(1).ReadAsArray()
elif type_prox == 'both':
gdal.ComputeProximity(raster_ds.GetRasterBand(1),
proxy_ds.GetRasterBand(1),
["VALUES=1", "DISTUNITS=GEO"])
proxy_ext = proxy_ds.GetRasterBand(1).ReadAsArray()
raster_arr = raster_ds.GetRasterBand(1).ReadAsArray()
mask = (raster_arr == 1)
raster_arr[mask] = raster_ds.GetRasterBand(1).GetNoDataValue()
raster_arr[~mask] = 1
raster_ds.GetRasterBand(1).WriteArray(raster_arr)
gdal.ComputeProximity(raster_ds.GetRasterBand(1),
proxy_ds.GetRasterBand(1),
["VALUES=1", "DISTUNITS=GEO"])
proxy_int = proxy_ds.GetRasterBand(1).ReadAsArray()
proxy_array = proxy_ext + proxy_int
else:
sys.exit('Type of proximity:' + type_prox +
' not recognized. Must be "interior", "exterior" or "both".')
return proxy_array
def __call__(self, maxdepth, pickle_name=None):
"""
Traverse the landcover array. For every point of type
'water', calculate the distance to the nearest non-water
point, stopping at maxdepth.
Keyword arguments:
maxdepth -- maximum value for depth
"""
if self.canCL and self.wantCL:
# Create working array
xlen, ylen = self.lcarray.shape
workingarr = np.array(self.lcarray.ravel(), dtype=np.int32)
# These values do not change from run to run.
ylen_arg = np.uint32(ylen)
maxdepth_arg = np.uint32(maxdepth)
# Calculate how many base elements can be evaluated per run.
# Each run requires xlen, ylen, currdepth, and maxdepth -- all 32bit.
static_data = 4 * 4
# Each base element requires two 32bit integers.
bytes_per_elem_single = 2 * 4
bytes_per_elem_total = bytes_per_elem_single
# Use rows instead of elems for two-dimensional arrays.
bytes_per_row_single = bytes_per_elem_single * ylen
bytes_per_row_total = bytes_per_elem_total * ylen
# Check both single and total limits on rows-per-slice.
rps_single = [
int(0.95 * device.max_mem_alloc_size / bytes_per_row_single)
for device in self.devices
]
rps_total = [
int((0.95 * device.global_mem_size - static_data) /
bytes_per_row_total) for device in self.devices
]
row_limits = [
min(rps_single[x], rps_total[x])
for x in xrange(len(self.devices))
]
# NB: Only supporting one device for now.
best_device = np.argmax(row_limits)
best_rows = row_limits[best_device]
global_size = self.global_size[self.devices[best_device]]
local_size = self.local_size[self.devices[best_device]]
# For now, at least, do not create retval or chunk buffer here.
# Iterate through this entire mess once per depth level
row_list = np.array([x for x in xrange(xlen)])
negfound = False
for row_chunk in chunks(row_list, best_rows):
# Do not prepend buffer rows for first row.
realfirst = row_chunk[0]
if (row_chunk[0] != row_list[0]):
realfirst -= maxdepth
# Do not postpend buffer rows for last row.
reallast = row_chunk[-1]
if (row_chunk[-1] != row_list[-1]):
reallast += maxdepth
# Create retvals and chunk buffer here instead of above.
chunk = np.copy(workingarr[realfirst * ylen:reallast * ylen])
outchunk_buf = cla.empty(self.queue, chunk.shape, chunk.dtype)
inchunk_buf = cla.to_device(self.queue, chunk)
newxlen = reallast - realfirst
newxlen_arg = np.uint32(newxlen)
lenchunk = newxlen * ylen
lenchunk_arg = np.uint32(lenchunk)
currdepth = 0
while (currdepth <= maxdepth):
currdepth_arg = np.uint32(currdepth)
if (currdepth % 2 == 0):
event = self.program.bathy(self.queue, global_size,
local_size,
outchunk_buf.data,
inchunk_buf.data,
newxlen_arg, ylen_arg,
currdepth_arg, maxdepth_arg)
else:
event = self.program.bathy(self.queue, global_size,
local_size,
inchunk_buf.data,
outchunk_buf.data,
newxlen_arg, ylen_arg,
currdepth_arg, maxdepth_arg)
event.wait()
currdepth += 1
# Copy relevant part of outchunk_buf to workingarr.
chunk_arr = outchunk_buf.get()
copytop = 0
if (row_chunk[0] != row_list[0]):
copytop += maxdepth
copybot = len(row_chunk) - 1
workingarr[row_chunk[0] * ylen:row_chunk[-1] *
ylen] = chunk_arr[copytop * ylen:copybot * ylen]
results = workingarr.reshape(
(self.lcarray.shape))[maxdepth:-1 * maxdepth,
maxdepth:-1 * maxdepth]
else:
(depthz, depthx) = self.lcarray.shape
drv = gdal.GetDriverByName('MEM')
depthds = drv.Create('', depthx, depthz, 1,
gdal.GetDataTypeByName('Byte'))
depthds.SetGeoTransform(self.geotrans)
depthds.SetProjection(self.projection)
depthband = depthds.GetRasterBand(1)
depthband.WriteArray(self.lcarray)
# create a duplicate dataset called bathyds
bathyds = drv.Create('', depthx, depthz, 1,
gdal.GetDataTypeByName('Byte'))
bathyds.SetGeoTransform(self.geotrans)
bathyds.SetProjection(self.projection)
bathyband = bathyds.GetRasterBand(1)
# run compute proximity
values = ','.join([str(x) for x in xrange(256) if x is not 11])
options = [
'MAXDIST=%d' % maxdepth,
'NODATA=%d' % maxdepth,
'VALUES=%s' % values
]
gdal.ComputeProximity(depthband, bathyband, options)
# extract array
results = bathyband.ReadAsArray(maxdepth, maxdepth,
bathyds.RasterXSize - 2 * maxdepth,
bathyds.RasterYSize - 2 * maxdepth)
if pickle_name is not None:
# Pickle variables for testing purposes.
picklefilename = 'bathy-%s.pkl.gz' % pickle_name
print 'Pickling to %s...' % picklefilename
f = gzip.open(picklefilename, 'wb')
pickle.dump(self.lcarray, f, -1)
pickle.dump(self.geotrans, f, -1)
pickle.dump(self.projection, f, -1)
pickle.dump(maxdepth, f, -1)
# pickle.dump(results, f, -1)
return results
def calcDist2ImgVals(inputValsImg,
outputDistImg,
pxlVals,
valsImgBand=1,
gdalformat='KEA',
maxDist=None,
noDataVal=None,
unitGEO=True):
"""
A function to calculate the distance to the nearest pixel value with one of the specified values.
Where:
:param inputValsImg: is a string specifying the input image file.
:param outputDistImg: is a string specfiying the output image file.
:param pxlVals: is a number of list of numbers specifying the features to which the distance from should be calculated.
:param valsImgBand: is an integer specifying the image band of the input image to be used (Default = 1).
:param gdalformat: is a string specifying the output image format (Default = KEA)
:param maxDist: is a number specifying the maximum distance to be calculated, if None not max value is used (Default = None).
:param noDataVal: is the no data value in the input image for which distance should not be calculated for (Default = None; None = no specified no data value).
:param unitGEO: is a boolean specifying the output distance units. True = Geographic units (e.g., metres), False is in Pixels (Default = True).
Example::
import rsgislib.imagecalc
cloudsImg = 'LS5TM_20110701_lat52lon421_r24p204_clouds.kea'
dist2Clouds = 'LS5TM_20110701_lat52lon421_r24p204_distclouds.kea'
# Pixel value 1 == Clouds
# Pixel value 2 == Cloud Shadows
rsgislib.imagecalc.calcDist2ImgVals(cloudsImg, dist2Clouds, pxlVals=[1,2])
"""
# Check gdal is available
if not haveGDALPy:
raise ImportError("The GDAL python bindings are required for "
"calcDist2ImgVals function could not be imported")
import rsgislib.imageutils
haveListVals = False
if type(pxlVals) is list:
haveListVals = True
proxOptions = []
if maxDist is not None:
proxOptions.append('MAXDIST=' + str(maxDist))
if noDataVal is not None:
proxOptions.append('NODATA=' + str(noDataVal))
if unitGEO:
proxOptions.append('DISTUNITS=GEO')
else:
proxOptions.append('DISTUNITS=PIXEL')
if haveListVals:
strVals = ''
first = True
for val in pxlVals:
if first:
strVals = str(val)
first = False
else:
strVals = strVals + "," + str(val)
proxOptions.append('VALUES=' + strVals)
else:
proxOptions.append('VALUES=' + str(pxlVals))
valsImgDS = gdal.Open(inputValsImg, gdal.GA_ReadOnly)
valsImgBand = valsImgDS.GetRasterBand(valsImgBand)
rsgislib.imageutils.createCopyImage(inputValsImg, outputDistImg, 1, 0.0,
gdalformat, rsgislib.TYPE_32FLOAT)
distImgDS = gdal.Open(outputDistImg, gdal.GA_Update)
distImgBand = distImgDS.GetRasterBand(1)
gdal.ComputeProximity(valsImgBand,
distImgBand,
proxOptions,
callback=gdal.TermProgress)
distImgBand = None
distImgDS = None
classImgBand = None
classImgDS = None