def ssave(self, name):
import copy
from py4j.java_gateway import JavaClass
cls = JavaClass('org.mrgeo.mapalgebra.save.SaveMapOp', gateway_client=self.gateway._gateway_client)
if hasattr(self, 'mapop') and self.is_instance_of(self.mapop, 'org.mrgeo.mapalgebra.MapOp') and type(
name) is str:
op = cls.create(self.mapop, str(name))
else:
raise Exception('input types differ (TODO: expand this message!)')
if (op.setup(self.job, self.context.getConf()) and
op.execute(self.context) and
op.teardown(self.job, self.context.getConf())):
new_resource = copy.copy(self)
new_resource.mapop = op
return new_resource
return
def ssave(self,name):
import copy
from numbers import Number
from py4j.java_gateway import JavaClass
cls = JavaClass('org.mrgeo.mapalgebra.save.SaveMapOp', gateway_client=self.gateway._gateway_client)
if hasattr(self, 'mapop') and self.is_instance_of(self.mapop, 'org.mrgeo.mapalgebra.MapOp') and type(name) is str:
op = cls.create(self.mapop, str(name))
else:
raise Exception('input types differ (TODO: expand this message!)')
if (op.setup(self.job, self.context.getConf()) and
op.execute(self.context) and
op.teardown(self.job, self.context.getConf())):
new_resource = copy.copy(self)
new_resource.mapop = op
return new_resource
return None
def eexport(self,name,singleFile=False,zoom=-1,numTiles=-1,mosaic=-1,format="tif",randomTiles=False,tms=False,colorscale="",tileids="",bounds="",allLevels=False,overridenodata=float('-inf')):
import copy
from numbers import Number
import base64
import numpy
from osgeo import gdal_array
import zlib
from osgeo import gdal
from py4j.java_gateway import JavaClass
cls = JavaClass('org.mrgeo.mapalgebra.ExportMapOp', gateway_client=self.gateway._gateway_client)
local_name = name
name = 'In-Memory'
if hasattr(self, 'mapop') and self.is_instance_of(self.mapop, 'org.mrgeo.mapalgebra.raster.RasterMapOp') and type(name) is str and isinstance(singleFile, (int, long, float, str)) and isinstance(zoom, (int, long, float)) and isinstance(numTiles, (int, long, float)) and isinstance(mosaic, (int, long, float)) and type(format) is str and isinstance(randomTiles, (int, long, float, str)) and isinstance(tms, (int, long, float, str)) and type(colorscale) is str and type(tileids) is str and type(bounds) is str and isinstance(allLevels, (int, long, float, str)) and isinstance(overridenodata, (int, long, float)):
op = cls.create(self.mapop, str(name), True if singleFile else False, int(zoom), int(numTiles), int(mosaic), str(format), True if randomTiles else False, True if tms else False, str(colorscale), str(tileids), str(bounds), True if allLevels else False, float(overridenodata))
else:
raise Exception('input types differ (TODO: expand this message!)')
if (op.setup(self.job, self.context.getConf()) and
op.execute(self.context) and
op.teardown(self.job, self.context.getConf())):
new_resource = copy.copy(self)
new_resource.mapop = op
gdalutils = JavaClass('org.mrgeo.utils.GDALUtils', gateway_client=self.gateway._gateway_client)
java_image = op.image()
width = java_image.getRasterXSize()
height = java_image.getRasterYSize()
options = []
if format == 'jpg' or format == 'jpeg':
driver_name = 'jpeg'
extension = 'jpg'
elif format == 'tif' or format == 'tiff' or format == 'geotif' or format == 'geotiff' or format == 'gtif' or format == 'gtiff':
driver_name = 'GTiff'
options.append('INTERLEAVE=BAND')
options.append('COMPRESS=DEFLATE')
options.append('PREDICTOR=1')
options.append('ZLEVEL=6')
options.append('TILES=YES')
if width < 2048:
options.append('BLOCKXSIZE=' + str(width))
else:
options.append('BLOCKXSIZE=2048')
if height < 2048:
options.append('BLOCKYSIZE=' + str(height))
else:
options.append('BLOCKYSIZE=2048')
extension = 'tif'
else:
driver_name = format
extension = format
datatype = java_image.GetRasterBand(1).getDataType()
if not local_name.endswith(extension):
local_name += "." + extension
driver = gdal.GetDriverByName(driver_name)
local_image = driver.Create(local_name, width, height, java_image.getRasterCount(), datatype, options)
local_image.SetProjection(str(java_image.GetProjection()))
local_image.SetGeoTransform(java_image.GetGeoTransform())
java_nodatas = gdalutils.getnodatas(java_image)
for i in xrange(1, local_image.RasterCount + 1):
start = time.time()
raw_data = gdalutils.getRasterDataAsCompressedBase64(java_image, i, 0, 0, width, height)
print('compressed/encoded data ' + str(len(raw_data)))
decoded_data = base64.b64decode(raw_data)
print('decoded data ' + str(len(decoded_data)))
decompressed_data = zlib.decompress(decoded_data, 16 + zlib.MAX_WBITS)
print('decompressed data ' + str(len(decompressed_data)))
byte_data = numpy.frombuffer(decompressed_data, dtype='b')
print('byte data ' + str(len(byte_data)))
image_data = byte_data.view(gdal_array.GDALTypeCodeToNumericTypeCode(datatype))
print('gdal-type data ' + str(len(image_data)))
image_data = image_data.reshape((-1, width))
#print('reshaped ' + str(len(byte_data)))
#print(byte_data)
#for j in xrange(0, 10):
# print(byte_data[j])
print('reshaped ' + str(len(image_data)) + " x " + str(len(image_data[0])))
band = local_image.GetRasterBand(i)
print('writing local image')
band.WriteArray(image_data)
print('done')
end = time.time()
print("elapsed time: " + str(end - start) + " sec.")
band.SetNoDataValue(java_nodatas[i - 1])
local_image.FlushCache()
print('flushed cache')
return new_resource
return None