本文整理匯總了Python中osgeo.gdal.GRA_CubicSpline方法的典型用法代碼示例。如果您正苦於以下問題：Python gdal.GRA_CubicSpline方法的具體用法？Python gdal.GRA_CubicSpline怎麽用？Python gdal.GRA_CubicSpline使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類osgeo.gdal的用法示例。
在下文中一共展示了gdal.GRA_CubicSpline方法的2個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: scale_query_to_tile
# 需要導入模塊: from osgeo import gdal [as 別名]
# 或者: from osgeo.gdal import GRA_CubicSpline [as 別名]
def scale_query_to_tile(dsquery, dstile, tiledriver, options, tilefilename=''):
"""Scales down query dataset to the tile dataset"""
querysize = dsquery.RasterXSize
tilesize = dstile.RasterXSize
tilebands = dstile.RasterCount
if options.resampling == 'average':
# Function: gdal.RegenerateOverview()
for i in range(1, tilebands+1):
# Black border around NODATA
res = gdal.RegenerateOverview(dsquery.GetRasterBand(i), dstile.GetRasterBand(i),
'average')
if res != 0:
exit_with_error("RegenerateOverview() failed on %s, error %d" % (
tilefilename, res))
elif options.resampling == 'antialias':
# Scaling by PIL (Python Imaging Library) - improved Lanczos
array = numpy.zeros((querysize, querysize, tilebands), numpy.uint8)
for i in range(tilebands):
array[:, :, i] = gdalarray.BandReadAsArray(dsquery.GetRasterBand(i+1),
0, 0, querysize, querysize)
im = Image.fromarray(array, 'RGBA') # Always four bands
im1 = im.resize((tilesize, tilesize), Image.ANTIALIAS)
if os.path.exists(tilefilename):
im0 = Image.open(tilefilename)
im1 = Image.composite(im1, im0, im1)
im1.save(tilefilename, tiledriver)
else:
if options.resampling == 'near':
gdal_resampling = gdal.GRA_NearestNeighbour
elif options.resampling == 'bilinear':
gdal_resampling = gdal.GRA_Bilinear
elif options.resampling == 'cubic':
gdal_resampling = gdal.GRA_Cubic
elif options.resampling == 'cubicspline':
gdal_resampling = gdal.GRA_CubicSpline
elif options.resampling == 'lanczos':
gdal_resampling = gdal.GRA_Lanczos
# Other algorithms are implemented by gdal.ReprojectImage().
dsquery.SetGeoTransform((0.0, tilesize / float(querysize), 0.0, 0.0, 0.0,
tilesize / float(querysize)))
dstile.SetGeoTransform((0.0, 1.0, 0.0, 0.0, 0.0, 1.0))
res = gdal.ReprojectImage(dsquery, dstile, None, None, gdal_resampling)
if res != 0:
exit_with_error("ReprojectImage() failed on %s, error %d" % (tilefilename, res)) 示例2: scale_query_to_tile
# 需要導入模塊: from osgeo import gdal [as 別名]
# 或者: from osgeo.gdal import GRA_CubicSpline [as 別名]
def scale_query_to_tile(dsquery, dstile, tiledriver, options, tilefilename=''):
"""Scales down query dataset to the tile dataset"""
querysize = dsquery.RasterXSize
tilesize = dstile.RasterXSize
tilebands = dstile.RasterCount
if options.resampling == 'average':
# Function: gdal.RegenerateOverview()
for i in range(1, tilebands + 1):
# Black border around NODATA
res = gdal.RegenerateOverview(dsquery.GetRasterBand(i), dstile.GetRasterBand(i),
'average')
if res != 0:
exit_with_error("RegenerateOverview() failed on %s, error %d" % (
tilefilename, res))
elif options.resampling == 'antialias':
# Scaling by PIL (Python Imaging Library) - improved Lanczos
array = numpy.zeros((querysize, querysize, tilebands), numpy.uint8)
for i in range(tilebands):
array[:, :, i] = gdalarray.BandReadAsArray(dsquery.GetRasterBand(i + 1),
0, 0, querysize, querysize)
im = Image.fromarray(array, 'RGBA') # Always four bands
im1 = im.resize((tilesize, tilesize), Image.ANTIALIAS)
if os.path.exists(tilefilename):
im0 = Image.open(tilefilename)
im1 = Image.composite(im1, im0, im1)
im1.save(tilefilename, tiledriver)
else:
if options.resampling == 'near':
gdal_resampling = gdal.GRA_NearestNeighbour
elif options.resampling == 'bilinear':
gdal_resampling = gdal.GRA_Bilinear
elif options.resampling == 'cubic':
gdal_resampling = gdal.GRA_Cubic
elif options.resampling == 'cubicspline':
gdal_resampling = gdal.GRA_CubicSpline
elif options.resampling == 'lanczos':
gdal_resampling = gdal.GRA_Lanczos
# Other algorithms are implemented by gdal.ReprojectImage().
dsquery.SetGeoTransform((0.0, tilesize / float(querysize), 0.0, 0.0, 0.0,
tilesize / float(querysize)))
dstile.SetGeoTransform((0.0, 1.0, 0.0, 0.0, 0.0, 1.0))
res = gdal.ReprojectImage(dsquery, dstile, None, None, gdal_resampling)
if res != 0:
exit_with_error("ReprojectImage() failed on %s, error %d" % (tilefilename, res))