def create_blank_file(input_filename, output_filename, value=255):
'''
following example in
http://geoexamples.blogspot.com/2012/12/raster-calculations-with-gdal-and-numpy.html
Created GeoTiff format file called output_filename
with same properties as input_filename.
Limitations: this version limited to single band copy
but could easily be extended by user
input_filename : string. Name of input file
output_filename : string. Name of output file
'''
# open input and get data
g = gdal.Open(input_filename, gdal.GA_ReadOnly)
inband = g.GetRasterBand(1)
indata = inband.ReadAsArray()
# declare and open output and get data
driver = gdal.GetDriverByName("GTiff")
gOut = driver.Create(output_filename, \
g.RasterXSize, g.RasterYSize, \
1, inband.DataType, options=['COMPRESS=LZW'])
outband = gOut.GetRasterBand(1)
# write value to output
# and copy other info
gdalnumeric.BandWriteArray(outband, value + indata * 0)
gdalnumeric.CopyDatasetInfo(g, gOut)
# close the file
del gOut
return (output_filename)
def create_images():
source_folder = 'source_tiffs'
source_path = os.path.join(os.path.dirname(os.path.abspath(__file__)),
source_folder)
if not os.path.exists(source_path):
os.mkdir(source_path)
gdal_driver = gdal.GetDriverByName(OUTPUT_FORMAT)
for tile_name, tile_values in TILES.items():
output_file_name = os.path.join(source_folder, tile_name)
if os.path.isfile(output_file_name):
os.remove(output_file_name)
output_file = gdal_driver.Create(
output_file_name,
tile_x,
tile_y,
tile_bands,
gdal.GDT_Int16 # Int16 to enable NoData value of -999
)
output_file.SetGeoTransform(GEO_TRANSFORM[tile_name])
output_file.SetProjection(TileMerger.SOURCE_FILE_PROJECTION)
target_band = output_file.GetRasterBand(tile_bands)
target_band.SetNoDataValue(2550) # From MODSCAG spec
gdalnumeric.BandWriteArray(target_band, tile_values)
del target_band
del output_file
def raster_file(tmp_input_path):
file_name = str(tmp_input_path / FILE_NAME)
output_file = GDAL_DRIVER.Create(file_name, BAND_VALUES.shape[1],
BAND_VALUES.shape[0], gdal.GDT_Byte)
output_file.SetGeoTransform(GEO_TRANSFORM)
output_file.SetProjection(PROJECTION.ExportToWkt())
target_band = output_file.GetRasterBand(1)
target_band.SetNoDataValue(NO_DATA_VALUE)
gdalnumeric.BandWriteArray(target_band, BAND_VALUES)
del target_band
del output_file
return file_name
def copy_into(self, output_file, source_band=1, target_band=1):
"""
Copy data to target file and filter according to the type given in
the initializer.
output_file -- gdal.Dataset object for the file into which some or all
of this file may be copied.
"""
t_geotransform = output_file.GetGeoTransform()
t_ulx = t_geotransform[0]
t_uly = t_geotransform[3]
t_pixel_width = t_geotransform[1]
t_pixel_height = t_geotransform[5]
# Intersection region
tgw_ulx = max(t_ulx, self.ulx)
if t_pixel_height < 0:
tgw_uly = min(t_uly, self.uly)
else:
tgw_uly = max(t_uly, self.uly)
# Target window in pixel coordinates.
tw_xoff = int((tgw_ulx - t_ulx) / t_pixel_width + 0.1)
tw_yoff = int((tgw_uly - t_uly) / t_pixel_height + 0.1)
source_file = gdal.Open(self.filename, gdalconst.GA_ReadOnly)
target_band = output_file.GetRasterBand(target_band)
source_values = gdalnumeric.BandReadAsArray(
source_file.GetRasterBand(source_band),
buf_type=gdal.GDT_Float32
)
no_data_value = target_band.GetNoDataValue()
# Filter by upper and lower band threshold values
source_values[source_values < self.lower_limit] = no_data_value
source_values[source_values > self.upper_limit] = no_data_value
gdalnumeric.BandWriteArray(
target_band, source_values, xoff=tw_xoff, yoff=tw_yoff
)
del source_values
del source_file
def __copy_band_data(self):
target_band = self.output_file.GetRasterBand(self.BAND_NUMBER)
target_band.SetNoDataValue(self.BAND_NO_DATA_VALUE)
source_values = gdalnumeric.BandReadAsArray(
self.mosaic_vrt.GetRasterBand(self.BAND_NUMBER),
buf_type=self.BAND_DATA_TYPE,
)
# Filter by upper and lower band threshold values
source_values[(source_values < self.lower_limit) | (
source_values > self.upper_limit)] = self.BAND_NO_DATA_VALUE
gdalnumeric.BandWriteArray(target_band, source_values)
target_band.FlushCache()
target_band.SetMetadata(self.BAND_METADATA[self.source_type])
del target_band
del source_values
def merge_swe_with_sca(swe_file, sca_file):
output_file_name = os.path.join(os.path.dirname(sca_file.GetDescription()),
'SWE_by_SCA.tif')
swe_by_sca = gdal.GetDriverByName('MEM').CreateCopy(
output_file_name, sca_file, 0)
swe_by_sca_band = swe_by_sca.GetRasterBand(1)
modis_band = sca_file.GetRasterBand(1)
sca_data = np.ma.masked_values(modis_band.ReadAsArray(),
modis_band.GetNoDataValue(),
copy=False)
sca_data = sca_data / 100
swe_band = swe_file.GetRasterBand(1)
swe_data = np.ma.masked_values(swe_band.ReadAsArray(),
swe_band.GetNoDataValue(),
copy=False)
gdalnumeric.BandWriteArray(swe_by_sca_band,
(sca_data * swe_data).astype(np.int16))
swe_by_sca_band.SetMetadata({
'Description': 'Snow Water Equivalent',
'Unit': 'mm'
})
swe_by_sca_band.ComputeStatistics(0)
swe_by_sca_band.FlushCache()
del modis_band, sca_data
del swe_band, swe_data
del swe_by_sca_band
# GDAL Translate is more efficient with compression for some unknown reason
gdal.Translate(output_file_name,
swe_by_sca,
format='GTiff',
creationOptions=[
"COMPRESS=LZW", "TILED=YES", "BIGTIFF=IF_SAFER",
"NUM_THREADS=ALL_CPUS"
])
del swe_by_sca
def __hdf_to_tif(self):
data = self.northern_swe()
self._tif_file = self.GDAL_DRIVER.Create(
os.path.join(self._file_dir, 'North_SWE_25k_nsidc.tif'),
data.shape[1],
data.shape[0],
1,
gdalconst.GDT_Int16,
)
self.tif_file.SetGeoTransform([
self.NSIDC_NORTH_UL_X, self.SOURCE_SPAT_RES, 0,
self.NSIDC_NORTH_UL_Y, 0, -self.SOURCE_SPAT_RES
])
self.tif_file.SetProjection(self.NSIDC_EASE_GRID_NORTH.ExportToWkt())
band = self.tif_file.GetRasterBand(1)
band.SetNoDataValue(self.NO_DATA_VALUE)
gdalnumeric.BandWriteArray(band, data)
band.FlushCache()
del data
del band
def writeRasterFileFromNumpy(self, pOutNumpy_, outFileName_,
pInitRasterFile_):
"""
Program description:
INPUT_PARAMETERS:
inputValue_ -
COMMENTS:
"""
#Write Gdal file from numpy array
outRasterFileName = tkFileDialog.asksaveasfilename(
defaultextension='TIFF',
filetypes=[('TIFF', '*.tif')],
initialdir=self.workspace,
initialfile=outFileName_,
parent=tkRoot,
title='Save output raster file (GDAL)')
#!!! Only for TIFF, one Numpy band and Float data implemented here
pDriver = gdal.GetDriverByName("GTiff")
pOutRasterDataset = pDriver.Create(
outRasterFileName, pInitRasterFile_.RasterXSize,
pInitRasterFile_.RasterYSize, 1,
GDT_Float32) #New file, settings from original file
gdalnumeric.CopyDatasetInfo(
pInitRasterFile_, pOutRasterDataset
) #Copy metadata information from original file to new file
gdalnumeric.BandWriteArray(pOutRasterDataset.GetRasterBand(1),
pOutNumpy_) # Copy numpy-data to new file
#Close datasets
pOutRasterDataset = None
return
def doit(opts, args):
# pylint: disable=unused-argument
if opts.debug:
print("gdal_calc.py starting calculation %s" % (opts.calc))
# set up global namespace for eval with all functions of gdalnumeric
global_namespace = dict([(key, getattr(gdalnumeric, key))
for key in dir(gdalnumeric) if not key.startswith('__')])
if opts.user_namespace:
global_namespace.update(opts.user_namespace)
if not opts.calc:
raise Exception("No calculation provided.")
elif not opts.outF and opts.format.upper() != 'MEM':
raise Exception("No output file provided.")
if opts.format is None:
opts.format = GetOutputDriverFor(opts.outF)
if not hasattr(opts, "color_table"):
opts.color_table = None
if not opts.extent:
opts.extent = EXTENT_IGNORE
else:
opts.extent = parse_extent(opts.extent)
compatible_gt_eps = 0.000001
gt_diff_support = {
GT_INCOMPATIBLE_OFFSET: opts.extent != EXTENT_FAIL,
GT_INCOMPATIBLE_PIXEL_SIZE: False,
GT_INCOMPATIBLE_ROTATION: False,
GT_NON_ZERO_ROTATION: False,
}
gt_diff_error = {
GT_INCOMPATIBLE_OFFSET: 'different offset',
GT_INCOMPATIBLE_PIXEL_SIZE: 'different pixel size',
GT_INCOMPATIBLE_ROTATION: 'different rotation',
GT_NON_ZERO_ROTATION: 'non zero rotation',
}
################################################################
# fetch details of input layers
################################################################
# set up some lists to store data for each band
myFileNames = [] # input filenames
myFiles = [] # input DataSets
myBands = [] # input bands
myAlphaList = [] # input alpha letter that represents each input file
myDataType = [] # string representation of the datatype of each input file
myDataTypeNum = [] # datatype of each input file
myNDV = [] # nodatavalue for each input file
DimensionsCheck = None # dimensions of the output
Dimensions = [] # Dimensions of input files
ProjectionCheck = None # projection of the output
GeoTransformCheck = None # GeoTransform of the output
GeoTransforms = [] # GeoTransform of each input file
GeoTransformDiffer = False # True if we have inputs with different GeoTransforms
myTempFileNames = [] # vrt filename from each input file
myAlphaFileLists = [] # list of the Alphas which holds a list of inputs
# loop through input files - checking dimensions
for alphas, filenames in opts.input_files.items():
if isinstance(filenames, (list, tuple)):
# alpha is a list of files
myAlphaFileLists.append(alphas)
elif is_path_like(filenames) or isinstance(filenames, gdal.Dataset):
# alpha is a single filename or a Dataset
filenames = [filenames]
alphas = [alphas]
else:
# I guess this alphas should be in the global_namespace,
# It would have been better to pass it as user_namepsace, but I'll accept it anyway
global_namespace[alphas] = filenames
continue
for alpha, filename in zip(alphas*len(filenames), filenames):
if not alpha.endswith("_band"):
# check if we have asked for a specific band...
if "%s_band" % alpha in opts.input_files:
myBand = opts.input_files["%s_band" % alpha]
else:
myBand = 1
myF_is_ds = not is_path_like(filename)
if myF_is_ds:
myFile = filename
filename = None
else:
filename = str(filename)
myFile = gdal.Open(filename, gdal.GA_ReadOnly)
if not myFile:
raise IOError("No such file or directory: '%s'" % filename)
myFileNames.append(filename)
myFiles.append(myFile)
myBands.append(myBand)
myAlphaList.append(alpha)
dt = myFile.GetRasterBand(myBand).DataType
myDataType.append(gdal.GetDataTypeName(dt))
myDataTypeNum.append(dt)
myNDV.append(None if opts.hideNoData else myFile.GetRasterBand(myBand).GetNoDataValue())
# check that the dimensions of each layer are the same
myFileDimensions = [myFile.RasterXSize, myFile.RasterYSize]
if DimensionsCheck:
if DimensionsCheck != myFileDimensions:
GeoTransformDiffer = True
if opts.extent in [EXTENT_IGNORE, EXTENT_FAIL]:
raise Exception("Error! Dimensions of file %s (%i, %i) are different from other files (%i, %i). Cannot proceed" %
(filename, myFileDimensions[0], myFileDimensions[1], DimensionsCheck[0], DimensionsCheck[1]))
else:
DimensionsCheck = myFileDimensions
# check that the Projection of each layer are the same
myProjection = myFile.GetProjection()
if ProjectionCheck:
if opts.projectionCheck and ProjectionCheck != myProjection:
raise Exception(
"Error! Projection of file %s %s are different from other files %s. Cannot proceed" %
(filename, myProjection, ProjectionCheck))
else:
ProjectionCheck = myProjection
# check that the GeoTransforms of each layer are the same
myFileGeoTransform = myFile.GetGeoTransform(can_return_null=True)
if opts.extent == EXTENT_IGNORE:
GeoTransformCheck = myFileGeoTransform
else:
Dimensions.append(myFileDimensions)
GeoTransforms.append(myFileGeoTransform)
if not GeoTransformCheck:
GeoTransformCheck = myFileGeoTransform
else:
my_gt_diff = gt_diff(GeoTransformCheck, myFileGeoTransform, eps=compatible_gt_eps, diff_support=gt_diff_support)
if my_gt_diff not in [GT_SAME, GT_ALMOST_SAME]:
GeoTransformDiffer = True
if my_gt_diff not in [GT_COMPATIBLE_DIFF]:
raise Exception(
"Error! GeoTransform of file {} {} is incompatible ({}), first file GeoTransform is {}. Cannot proceed".
format(filename, myFileGeoTransform, gt_diff_error[my_gt_diff], GeoTransformCheck))
if opts.debug:
print("file %s: %s, dimensions: %s, %s, type: %s" % (
alpha, filename, DimensionsCheck[0], DimensionsCheck[1], myDataType[-1]))
# process allBands option
allBandsIndex = None
allBandsCount = 1
if opts.allBands:
if len(opts.calc) > 1:
raise Exception("Error! --allBands implies a single --calc")
try:
allBandsIndex = myAlphaList.index(opts.allBands)
except ValueError:
raise Exception("Error! allBands option was given but Band %s not found. Cannot proceed" % (opts.allBands))
allBandsCount = myFiles[allBandsIndex].RasterCount
if allBandsCount <= 1:
allBandsIndex = None
else:
allBandsCount = len(opts.calc)
if opts.extent not in [EXTENT_IGNORE, EXTENT_FAIL] and (GeoTransformDiffer or not isinstance(opts.extent, EXTENT)):
raise Exception('Error! mixing different GeoTransforms/Extents is not supported yet.')
################################################################
# set up output file
################################################################
# open output file exists
if opts.outF and os.path.isfile(opts.outF) and not opts.overwrite:
if allBandsIndex is not None:
raise Exception("Error! allBands option was given but Output file exists, must use --overwrite option!")
if len(opts.calc) > 1:
raise Exception("Error! multiple calc options were given but Output file exists, must use --overwrite option!")
if opts.debug:
print("Output file %s exists - filling in results into file" % (opts.outF))
myOut = gdal.Open(opts.outF, gdal.GA_Update)
if myOut is None:
error = 'but cannot be opened for update'
elif [myOut.RasterXSize, myOut.RasterYSize] != DimensionsCheck:
error = 'but is the wrong size'
elif ProjectionCheck and ProjectionCheck != myOut.GetProjection():
error = 'but is the wrong projection'
elif GeoTransformCheck and GeoTransformCheck != myOut.GetGeoTransform(can_return_null=True):
error = 'but is the wrong geotransform'
else:
error = None
if error:
raise Exception("Error! Output exists, %s. Use the --overwrite option to automatically overwrite the existing file" % error)
myOutB = myOut.GetRasterBand(1)
myOutNDV = myOutB.GetNoDataValue()
myOutType = myOutB.DataType
else:
if opts.outF:
# remove existing file and regenerate
if os.path.isfile(opts.outF):
os.remove(opts.outF)
# create a new file
if opts.debug:
print("Generating output file %s" % (opts.outF))
else:
opts.outF = ''
# find data type to use
if not opts.type:
# use the largest type of the input files
myOutType = max(myDataTypeNum)
else:
myOutType = opts.type
if isinstance(myOutType, str):
myOutType = gdal.GetDataTypeByName(myOutType)
# create file
myOutDrv = gdal.GetDriverByName(opts.format)
myOut = myOutDrv.Create(
opts.outF, DimensionsCheck[0], DimensionsCheck[1], allBandsCount,
myOutType, opts.creation_options)
# set output geo info based on first input layer
if not GeoTransformCheck:
GeoTransformCheck = myFiles[0].GetGeoTransform(can_return_null=True)
if GeoTransformCheck:
myOut.SetGeoTransform(GeoTransformCheck)
if not ProjectionCheck:
ProjectionCheck = myFiles[0].GetProjection()
if ProjectionCheck:
myOut.SetProjection(ProjectionCheck)
if opts.NoDataValue is None:
myOutNDV = None if opts.hideNoData else DefaultNDVLookup[myOutType] # use the default noDataValue for this datatype
elif isinstance(opts.NoDataValue, str) and opts.NoDataValue.lower() == 'none':
myOutNDV = None # not to set any noDataValue
else:
myOutNDV = opts.NoDataValue # use the given noDataValue
for i in range(1, allBandsCount + 1):
myOutB = myOut.GetRasterBand(i)
if myOutNDV is not None:
myOutB.SetNoDataValue(myOutNDV)
if opts.color_table:
# set color table and color interpretation
if is_path_like(opts.color_table):
raise Exception('Error! reading a color table from a file is not supported yet')
myOutB.SetRasterColorTable(opts.color_table)
myOutB.SetRasterColorInterpretation(gdal.GCI_PaletteIndex)
myOutB = None # write to band
myOutTypeName = gdal.GetDataTypeName(myOutType)
if opts.debug:
print("output file: %s, dimensions: %s, %s, type: %s" % (opts.outF, myOut.RasterXSize, myOut.RasterYSize, myOutTypeName))
################################################################
# find block size to chop grids into bite-sized chunks
################################################################
# use the block size of the first layer to read efficiently
myBlockSize = myFiles[0].GetRasterBand(myBands[0]).GetBlockSize()
# find total x and y blocks to be read
nXBlocks = (int)((DimensionsCheck[0] + myBlockSize[0] - 1) / myBlockSize[0])
nYBlocks = (int)((DimensionsCheck[1] + myBlockSize[1] - 1) / myBlockSize[1])
myBufSize = myBlockSize[0] * myBlockSize[1]
if opts.debug:
print("using blocksize %s x %s" % (myBlockSize[0], myBlockSize[1]))
# variables for displaying progress
ProgressCt = -1
ProgressMk = -1
ProgressEnd = nXBlocks * nYBlocks * allBandsCount
################################################################
# start looping through each band in allBandsCount
################################################################
for bandNo in range(1, allBandsCount + 1):
################################################################
# start looping through blocks of data
################################################################
# store these numbers in variables that may change later
nXValid = myBlockSize[0]
nYValid = myBlockSize[1]
# loop through X-lines
for X in range(0, nXBlocks):
# in case the blocks don't fit perfectly
# change the block size of the final piece
if X == nXBlocks - 1:
nXValid = DimensionsCheck[0] - X * myBlockSize[0]
# find X offset
myX = X * myBlockSize[0]
# reset buffer size for start of Y loop
nYValid = myBlockSize[1]
myBufSize = nXValid * nYValid
# loop through Y lines
for Y in range(0, nYBlocks):
ProgressCt += 1
if 10 * ProgressCt / ProgressEnd % 10 != ProgressMk and not opts.quiet:
ProgressMk = 10 * ProgressCt / ProgressEnd % 10
from sys import version_info
if version_info >= (3, 0, 0):
exec('print("%d.." % (10*ProgressMk), end=" ")')
else:
exec('print 10*ProgressMk, "..",')
# change the block size of the final piece
if Y == nYBlocks - 1:
nYValid = DimensionsCheck[1] - Y * myBlockSize[1]
myBufSize = nXValid * nYValid
# find Y offset
myY = Y * myBlockSize[1]
# create empty buffer to mark where nodata occurs
myNDVs = None
# make local namespace for calculation
local_namespace = {}
val_lists = defaultdict(list)
# fetch data for each input layer
for i, Alpha in enumerate(myAlphaList):
# populate lettered arrays with values
if allBandsIndex is not None and allBandsIndex == i:
myBandNo = bandNo
else:
myBandNo = myBands[i]
myval = gdalnumeric.BandReadAsArray(myFiles[i].GetRasterBand(myBandNo),
xoff=myX, yoff=myY,
win_xsize=nXValid, win_ysize=nYValid)
if myval is None:
raise Exception('Input block reading failed from filename %s' % filename[i])
# fill in nodata values
if myNDV[i] is not None:
# myNDVs is a boolean buffer.
# a cell equals to 1 if there is NDV in any of the corresponding cells in input raster bands.
if myNDVs is None:
# this is the first band that has NDV set. we initializes myNDVs to a zero buffer
# as we didn't see any NDV value yet.
myNDVs = numpy.zeros(myBufSize)
myNDVs.shape = (nYValid, nXValid)
myNDVs = 1 * numpy.logical_or(myNDVs == 1, myval == myNDV[i])
# add an array of values for this block to the eval namespace
if Alpha in myAlphaFileLists:
val_lists[Alpha].append(myval)
else:
local_namespace[Alpha] = myval
myval = None
for lst in myAlphaFileLists:
local_namespace[lst] = val_lists[lst]
# try the calculation on the array blocks
calc = opts.calc[bandNo-1 if len(opts.calc) > 1 else 0]
try:
myResult = eval(calc, global_namespace, local_namespace)
except:
print("evaluation of calculation %s failed" % (calc))
raise
# Propagate nodata values (set nodata cells to zero
# then add nodata value to these cells).
if myNDVs is not None and myOutNDV is not None:
myResult = ((1 * (myNDVs == 0)) * myResult) + (myOutNDV * myNDVs)
elif not isinstance(myResult, numpy.ndarray):
myResult = numpy.ones((nYValid, nXValid)) * myResult
# write data block to the output file
myOutB = myOut.GetRasterBand(bandNo)
if gdalnumeric.BandWriteArray(myOutB, myResult, xoff=myX, yoff=myY) != 0:
raise Exception('Block writing failed')
myOutB = None # write to band
# remove temp files
for idx, tempFile in enumerate(myTempFileNames):
myFiles[idx] = None
os.remove(tempFile)
gdal.ErrorReset()
myOut.FlushCache()
if gdal.GetLastErrorMsg() != '':
raise Exception('Dataset writing failed')
if not opts.quiet:
print("100 - Done")
return myOut
def doit(opts, args):
# pylint: disable=unused-argument
if opts.debug:
print("gdal_calc.py starting calculation %s" % (opts.calc))
# set up global namespace for eval with all functions of gdalnumeric
global_namespace = dict([(key, getattr(gdalnumeric, key))
for key in dir(gdalnumeric) if not key.startswith('__')])
if not opts.calc:
raise Exception("No calculation provided.")
elif not opts.outF:
raise Exception("No output file provided.")
if opts.format is None:
opts.format = GetOutputDriverFor(opts.outF)
################################################################
# fetch details of input layers
################################################################
# set up some lists to store data for each band
myFiles = []
myBands = []
myAlphaList = []
myDataType = []
myDataTypeNum = []
myNDV = []
DimensionsCheck = None
# loop through input files - checking dimensions
for myI, myF in opts.input_files.items():
if not myI.endswith("_band"):
# check if we have asked for a specific band...
if "%s_band" % myI in opts.input_files:
myBand = opts.input_files["%s_band" % myI]
else:
myBand = 1
myFile = gdal.Open(myF, gdal.GA_ReadOnly)
if not myFile:
raise IOError("No such file or directory: '%s'" % myF)
myFiles.append(myFile)
myBands.append(myBand)
myAlphaList.append(myI)
myDataType.append(gdal.GetDataTypeName(myFile.GetRasterBand(myBand).DataType))
myDataTypeNum.append(myFile.GetRasterBand(myBand).DataType)
myNDV.append(myFile.GetRasterBand(myBand).GetNoDataValue())
# check that the dimensions of each layer are the same
if DimensionsCheck:
if DimensionsCheck != [myFile.RasterXSize, myFile.RasterYSize]:
raise Exception("Error! Dimensions of file %s (%i, %i) are different from other files (%i, %i). Cannot proceed" %
(myF, myFile.RasterXSize, myFile.RasterYSize, DimensionsCheck[0], DimensionsCheck[1]))
else:
DimensionsCheck = [myFile.RasterXSize, myFile.RasterYSize]
if opts.debug:
print("file %s: %s, dimensions: %s, %s, type: %s" % (myI, myF, DimensionsCheck[0], DimensionsCheck[1], myDataType[-1]))
# process allBands option
allBandsIndex = None
allBandsCount = 1
if opts.allBands:
try:
allBandsIndex = myAlphaList.index(opts.allBands)
except ValueError:
raise Exception("Error! allBands option was given but Band %s not found. Cannot proceed" % (opts.allBands))
allBandsCount = myFiles[allBandsIndex].RasterCount
if allBandsCount <= 1:
allBandsIndex = None
################################################################
# set up output file
################################################################
# open output file exists
if os.path.isfile(opts.outF) and not opts.overwrite:
if allBandsIndex is not None:
raise Exception("Error! allBands option was given but Output file exists, must use --overwrite option!")
if opts.debug:
print("Output file %s exists - filling in results into file" % (opts.outF))
myOut = gdal.Open(opts.outF, gdal.GA_Update)
if [myOut.RasterXSize, myOut.RasterYSize] != DimensionsCheck:
raise Exception("Error! Output exists, but is the wrong size. Use the --overwrite option to automatically overwrite the existing file")
myOutB = myOut.GetRasterBand(1)
myOutNDV = myOutB.GetNoDataValue()
myOutType = gdal.GetDataTypeName(myOutB.DataType)
else:
# remove existing file and regenerate
if os.path.isfile(opts.outF):
os.remove(opts.outF)
# create a new file
if opts.debug:
print("Generating output file %s" % (opts.outF))
# find data type to use
if not opts.type:
# use the largest type of the input files
myOutType = gdal.GetDataTypeName(max(myDataTypeNum))
else:
myOutType = opts.type
# create file
myOutDrv = gdal.GetDriverByName(opts.format)
myOut = myOutDrv.Create(
opts.outF, DimensionsCheck[0], DimensionsCheck[1], allBandsCount,
gdal.GetDataTypeByName(myOutType), opts.creation_options)
# set output geo info based on first input layer
myOut.SetGeoTransform(myFiles[0].GetGeoTransform())
myOut.SetProjection(myFiles[0].GetProjection())
if opts.NoDataValue is not None:
myOutNDV = opts.NoDataValue
else:
myOutNDV = DefaultNDVLookup[myOutType]
for i in range(1, allBandsCount + 1):
myOutB = myOut.GetRasterBand(i)
myOutB.SetNoDataValue(myOutNDV)
# write to band
myOutB = None
if opts.debug:
print("output file: %s, dimensions: %s, %s, type: %s" % (opts.outF, myOut.RasterXSize, myOut.RasterYSize, myOutType))
################################################################
# find block size to chop grids into bite-sized chunks
################################################################
# use the block size of the first layer to read efficiently
myBlockSize = myFiles[0].GetRasterBand(myBands[0]).GetBlockSize()
# find total x and y blocks to be read
nXBlocks = (int)((DimensionsCheck[0] + myBlockSize[0] - 1) / myBlockSize[0])
nYBlocks = (int)((DimensionsCheck[1] + myBlockSize[1] - 1) / myBlockSize[1])
myBufSize = myBlockSize[0] * myBlockSize[1]
if opts.debug:
print("using blocksize %s x %s" % (myBlockSize[0], myBlockSize[1]))
# variables for displaying progress
ProgressCt = -1
ProgressMk = -1
ProgressEnd = nXBlocks * nYBlocks * allBandsCount
################################################################
# start looping through each band in allBandsCount
################################################################
for bandNo in range(1, allBandsCount + 1):
################################################################
# start looping through blocks of data
################################################################
# store these numbers in variables that may change later
nXValid = myBlockSize[0]
nYValid = myBlockSize[1]
# loop through X-lines
for X in range(0, nXBlocks):
# in case the blocks don't fit perfectly
# change the block size of the final piece
if X == nXBlocks - 1:
nXValid = DimensionsCheck[0] - X * myBlockSize[0]
# find X offset
myX = X * myBlockSize[0]
# reset buffer size for start of Y loop
nYValid = myBlockSize[1]
myBufSize = nXValid * nYValid
# loop through Y lines
for Y in range(0, nYBlocks):
ProgressCt += 1
if 10 * ProgressCt / ProgressEnd % 10 != ProgressMk and not opts.quiet:
ProgressMk = 10 * ProgressCt / ProgressEnd % 10
from sys import version_info
if version_info >= (3, 0, 0):
exec('print("%d.." % (10*ProgressMk), end=" ")')
else:
exec('print 10*ProgressMk, "..",')
# change the block size of the final piece
if Y == nYBlocks - 1:
nYValid = DimensionsCheck[1] - Y * myBlockSize[1]
myBufSize = nXValid * nYValid
# find Y offset
myY = Y * myBlockSize[1]
# create empty buffer to mark where nodata occurs
myNDVs = None
# make local namespace for calculation
local_namespace = {}
# fetch data for each input layer
for i, Alpha in enumerate(myAlphaList):
# populate lettered arrays with values
if allBandsIndex is not None and allBandsIndex == i:
myBandNo = bandNo
else:
myBandNo = myBands[i]
myval = gdalnumeric.BandReadAsArray(myFiles[i].GetRasterBand(myBandNo),
xoff=myX, yoff=myY,
win_xsize=nXValid, win_ysize=nYValid)
# fill in nodata values
if myNDV[i] is not None:
if myNDVs is None:
myNDVs = numpy.zeros(myBufSize)
myNDVs.shape = (nYValid, nXValid)
myNDVs = 1 * numpy.logical_or(myNDVs == 1, myval == myNDV[i])
# add an array of values for this block to the eval namespace
local_namespace[Alpha] = myval
myval = None
# try the calculation on the array blocks
try:
myResult = eval(opts.calc, global_namespace, local_namespace)
except:
print("evaluation of calculation %s failed" % (opts.calc))
raise
# Propagate nodata values (set nodata cells to zero
# then add nodata value to these cells).
if myNDVs is not None:
myResult = ((1 * (myNDVs == 0)) * myResult) + (myOutNDV * myNDVs)
elif not isinstance(myResult, numpy.ndarray):
myResult = numpy.ones((nYValid, nXValid)) * myResult
# write data block to the output file
myOutB = myOut.GetRasterBand(bandNo)
gdalnumeric.BandWriteArray(myOutB, myResult, xoff=myX, yoff=myY)
if not opts.quiet:
print("100 - Done")
def main():
# initiate the parser
parser = argparse.ArgumentParser(
description='Summarize a set of rasters layers.')
parser.add_argument('files', nargs='+', help='input raster file(s)')
parser.add_argument('--outfile', '-o', required=True, help='output raster')
band_help = 'bands to summarize. ' + \
'single file: bands in this file to summarize (default all bands); ' + \
'multiple files: bands in corresponding files to summarize (default = 1)'
parser.add_argument('--bands', '-b', nargs='+', type=int, help=band_help)
function_help = 'function to apply to cell values across layers.' + \
'meannz gives a mean of the non-zero values.' + \
'count counts the number layers with non-negative values for each cell.' + \
'richness counts the number of layers with positive values for each cell.'
parser.add_argument('--function',
'-f',
dest='summary_function',
default='mean',
choices=[
'mean', 'median', 'max', 'sum', 'meannz', 'count',
'richness'
],
help="summarization function (default = 'mean')")
parser.add_argument(
'--block_size',
'-s',
nargs=2,
type=int,
help='x and y dimensions of blocks to process (default based on input)'
)
parser.add_argument(
'--nrows',
'-n',
type=int,
help=
'number of rows to process in a single block (block_size ignored if provided)'
)
parser.add_argument('--overwrite',
'-w',
action="store_true",
help='overwrite existing file')
parser.add_argument(
'--creation-option',
'--co',
dest='creation_options',
default=[],
action='append',
help=
'passes one or more creation options to the output format driver multiple'
)
parser.add_argument('--quiet',
'-q',
action="store_true",
help='supress messages')
# read arguments from the command line
args = parser.parse_args()
# summarize multiple bands of same file or bands across files
if len(args.files) == 1:
# use all bands if not specified
if not args.bands:
b = gdal.Open(args.files[0], gdal.GA_ReadOnly).RasterCount
args.bands = [i for i in range(1, b + 1)]
# elif len(args.bands) == 1:
# raise Exception('For a single input file, provide multiple bands to summarize over.')
args.files = [args.files[0]] * len(args.bands)
else:
# use band 1 if not specified
if not args.bands:
args.bands = [1] * len(args.files)
elif len(args.bands) == 1:
args.bands = [args.bands[0]] * len(args.files)
elif len(args.bands) != len(args.files):
raise Exception(
'The number of bands must be 1 or equal to the number of input files.'
)
# set up some default nodatavalues for each datatype
ndv_lookup = {
'Byte': 255,
'UInt16': 65535,
'Int16': -32767,
'UInt32': 4294967293,
'Int32': -2147483647,
'Float32': 3.402823466E+38,
'Float64': 1.7976931348623158E+308
}
stack = []
in_type = []
in_ndv = []
raster_dim = None
block_size = None
out_transform = None
out_projection = None
# pass over files to get metadata and check arguments
for i in range(len(args.files)):
f = args.files[i]
b = args.bands[i]
s = gdal.Open(f, gdal.GA_ReadOnly)
# check that file exists
if not s:
raise IOError('No such file or directory: {}'.format(f))
# check that band is valid
if b > s.RasterCount:
raise IOError('Invalid band number ({}) for file: {}'.format(b, f))
# get specified band
r = s.GetRasterBand(b)
# store raster file
stack.append(s)
# metadata
in_type.append(r.DataType)
dt_name = gdal.GetDataTypeName(r.DataType).lower()
in_ndv.append(np.float64(r.GetNoDataValue()).astype(dt_name))
# check that the dimensions of each layer are the same
if raster_dim:
if raster_dim != [s.RasterXSize, s.RasterYSize]:
raise Exception('Input files have different dimensions.')
else:
raster_dim = [s.RasterXSize, s.RasterYSize]
# block size to chop grids into bite-sized chunks
if not block_size:
# use the block size of the first layer to read efficiently
# or use user provided block size
if not args.nrows:
if not args.block_size:
block_size = s.GetRasterBand(1).GetBlockSize()
else:
# block size can't be larger than raster dimensions
block_size = np.minimum(args.block_size,
raster_dim).tolist()
else:
block_size = [raster_dim[0], min(raster_dim[1], args.nrows)]
# get geo info from first layer
if not out_transform:
out_transform = s.GetGeoTransform()
if not out_projection:
out_projection = s.GetProjection()
# prepare output file
if os.path.isfile(args.outfile) and not args.overwrite:
raise Exception(
"Output exists, use the --overwrite to overwrite the existing file"
)
else:
# remove existing file and regenerate
if os.path.isfile(args.outfile):
os.remove(args.outfile)
# for sum use the largest type of the input files
# otherise use a value suitable for the function
if args.summary_function == 'sum':
out_type = gdal.GetDataTypeName(max(in_type))
out_type_np = out_type.lower()
np_nan = 0
elif args.summary_function == 'mean':
out_type = 'Float32'
out_type_np = out_type.lower()
np_nan = np.nan
elif args.summary_function == 'median':
out_type = 'Float32'
out_type_np = out_type.lower()
np_nan = np.nan
elif args.summary_function == 'max':
out_type = 'Float32'
out_type_np = out_type.lower()
np_nan = np.nan
elif args.summary_function == 'meannz':
out_type = 'Float32'
out_type_np = out_type.lower()
np_nan = np.nan
elif args.summary_function == 'count':
out_type = 'Int16'
out_type_np = out_type.lower()
np_nan = -1
elif args.summary_function == 'richness':
out_type = 'Int16'
out_type_np = out_type.lower()
np_nan = -1
# create file
out_driver = gdal.GetDriverByName('GTiff')
r_out = out_driver.Create(args.outfile, raster_dim[0], raster_dim[1],
1, gdal.GetDataTypeByName(out_type),
args.creation_options)
# set output geo info based on first input layer
r_out.SetGeoTransform(out_transform)
r_out.SetProjection(out_projection)
# set no data value
out_ndv = ndv_lookup[out_type]
out_ndv_np = np.float64(out_ndv).astype(out_type_np)
r_out.GetRasterBand(1).SetNoDataValue(out_ndv)
# find total x and y blocks to be read
xblocks = math.ceil(raster_dim[0] / block_size[0])
yblocks = math.ceil(raster_dim[1] / block_size[1])
# loop through blocks of data
# store these numbers in variables that may change later
xvalid = block_size[0]
yvalid = block_size[1]
# variables for displaying progress
progress_cnt = -1
progress_stp = 0
progress_end = xblocks * yblocks
progress_stps = [round(progress_end * i / 100) for i in range(0, 101, 10)]
# message
if not args.quiet:
m = "Processing {} X {} raster (cols X rows) in {} blocks of {} X {}"
m = m.format(raster_dim[0], raster_dim[1], xblocks * yblocks,
block_size[0], block_size[1])
print(m)
# loop through x dimension
for x in range(0, xblocks):
# in case the blocks don't fit perfectly
# change the block size of the final piece
if x == xblocks - 1:
xvalid = raster_dim[0] - x * block_size[0]
# find x offset
x_off = x * block_size[0]
# reset buffer size for start of Y loop
yvalid = block_size[1]
# loop through y dimension
for y in range(0, yblocks):
# progress bar
progress_cnt += 1
if progress_cnt == progress_stps[progress_stp] and not args.quiet:
print('%d...' % (10 * progress_stp), end="", flush=True)
progress_stp += 1
# change the block size of the final piece
if y == yblocks - 1:
yvalid = raster_dim[1] - y * block_size[1]
# find y offset
y_off = y * block_size[1]
# create empty buffer to mark where nodata occurs
ndv_buffer = None
# make array to store block
block = np.empty(shape=(len(stack), yvalid, xvalid),
dtype='float32')
# fetch data for each input layer
for i in range(len(stack)):
vals = gdalnumeric.BandReadAsArray(stack[i].GetRasterBand(
args.bands[i]),
xoff=x_off,
yoff=y_off,
win_xsize=xvalid,
win_ysize=yvalid)
if out_type != "Int16":
vals = vals.astype(out_type_np)
# fill in nodata values
if in_ndv[i] is not None:
vals[vals == in_ndv[i]] = np_nan
# add block to array
block[i] = vals
vals = None
# ignore empty slice warnings
with warnings.catch_warnings():
warnings.simplefilter('ignore', category=RuntimeWarning)
if args.summary_function == 'sum':
result = np.nansum(block, axis=0)
elif args.summary_function == 'mean':
result = np.nanmean(block, axis=0)
elif args.summary_function == 'median':
result = np.nanmedian(block, axis=0)
elif args.summary_function == 'max':
result = np.nanmax(block, axis=0)
elif args.summary_function == 'meannz':
block = np.ma.masked_equal(block, 0)
result = np.nanmean(block, axis=0)
elif args.summary_function == 'count':
result = np.nansum(block >= 0, axis=0)
elif args.summary_function == 'richness':
result = np.nansum(block > 0, axis=0)
# replace nan with no data value
result[np.isnan(result)] = out_ndv_np
# write data block to the output file
gdalnumeric.BandWriteArray(r_out.GetRasterBand(1),
result,
xoff=x_off,
yoff=y_off)
# end progress bar
if not args.quiet:
print('100 - Done')
def run(self):
self._abort = False
self.progress.emit("Starting RasterBender", float(0), float(0))
#####################################
# Step 1 : create the delaunay mesh #
#####################################
self.progress.emit("Loading delaunay mesh...", float(0), float(0))
# Create the delaunay triangulation
triangles, pointsA, pointsB, hull, constraints = triangulate.triangulate(
self.pairsLayer, self.pairsLimitToSelection, self.constraintsLayer,
self.constraintsLimitToSelection, self.bufferValue)
###############################
# Step 2. Opening the dataset #
###############################
self.progress.emit(
"Opening the dataset... This shouldn't be too long...", float(0),
float(0))
#Open the dataset
gdal.UseExceptions()
# Read the source data into numpy arrays
dsSource = gdal.Open(self.sourcePath, gdal.GA_ReadOnly)
sourceDataR = gdalnumeric.BandReadAsArray(dsSource.GetRasterBand(1))
sourceDataG = gdalnumeric.BandReadAsArray(dsSource.GetRasterBand(2))
sourceDataB = gdalnumeric.BandReadAsArray(dsSource.GetRasterBand(3))
# Get the transformation
pixW = float(dsSource.RasterXSize - 1) #width in pixel
pixH = float(dsSource.RasterYSize - 1) #width in pixel
mapW = float(dsSource.RasterXSize) * dsSource.GetGeoTransform()[
1] #width in map units
mapH = float(dsSource.RasterYSize) * dsSource.GetGeoTransform()[
5] #width in map units
offX = dsSource.GetGeoTransform()[0] #offset in map units
offY = dsSource.GetGeoTransform()[3] #offset in map units
# Open the target into numpy array
#dsTarget = gdal.Open(self.targetPath, gdal.GA_Update )
driver = gdal.GetDriverByName("GTiff")
dsTarget = driver.CreateCopy(self.targetPath, dsSource, 0)
#dsTarget.SetGeoTransform( dsSource.GetGeoTransform() )
dsTarget = None #close
def xyToQgsPoint(x, y):
return QgsPoint(offX + mapW * (x / pixW), offY + mapH * (y / pixH))
def qgsPointToXY(qgspoint):
return (int((qgspoint.x() - offX) / mapW * pixW),
int((qgspoint.y() - offY) / mapH * pixH))
#######################################
# Step 3A. Looping through the blocks #
#######################################
#Loop through every block
blockCountX = dsSource.RasterXSize // self.blockSize + 1
blockCountY = dsSource.RasterYSize // self.blockSize + 1
blockCount = blockCountX * blockCountY
blockI = 0
displayTotal = dsSource.RasterXSize * dsSource.RasterYSize
displayStep = min((self.blockSize**2) / 20,
10000) # update gui every n steps
self.progress.emit("Starting computation... This can take a while...",
float(0), float(0))
for blockNumY in range(0, blockCountY):
blockOffsetY = blockNumY * self.blockSize
blockH = min(self.blockSize, dsSource.RasterYSize - blockOffsetY)
if blockH <= 0: continue
for blockNumX in range(0, blockCountX):
blockOffsetX = blockNumX * self.blockSize
blockW = min(self.blockSize,
dsSource.RasterXSize - blockOffsetX)
if blockW <= 0: continue
blockI += 1
pixelCount = blockW * blockH
pixelI = 0
blockRectangle = QgsRectangle(
xyToQgsPoint(blockOffsetX, blockOffsetY),
xyToQgsPoint(blockOffsetX + blockW, blockOffsetY + blockH)
) # this is the shape of the block, used for optimization
# We check if the block intersects the hull, if not, we skip it
if not hull.intersects(blockRectangle):
self.progress.emit(
"Block %i out of %i is out of the convex hull, we skip it..."
% (blockI, blockCount), float(0),
float(blockI / float(blockCount)))
continue
# We create the trifinder for the block
blockTrifinder = trifinder.Trifinder(pointsB, triangles,
blockRectangle)
targetDataR = gdalnumeric.BandReadAsArray(
dsSource.GetRasterBand(1), blockOffsetX, blockOffsetY,
blockW, blockH)
targetDataG = gdalnumeric.BandReadAsArray(
dsSource.GetRasterBand(2), blockOffsetX, blockOffsetY,
blockW, blockH)
targetDataB = gdalnumeric.BandReadAsArray(
dsSource.GetRasterBand(3), blockOffsetX, blockOffsetY,
blockW, blockH)
#######################################
# Step 3B. Looping through the pixels #
#######################################
# Loop through every pixel
for y in range(0, blockH):
for x in range(0, blockW):
# If abort was called, we finish the process
if self._abort:
self.error.emit(
"Aborted on pixel %i out of %i on block %i out of %i..."
% (pixelI, pixelCount, blockI, blockCount),
float(0), float(0))
return
pixelI += 1
# Ever now and then, we update the status
if pixelI % displayStep == 0:
self.progress.emit(
"Working on pixel %i out of %i on block %i out of %i... Trifinder has %i triangles"
% (pixelI, pixelCount, blockI, blockCount,
len(blockTrifinder.triangles)),
float(pixelI) / float(pixelCount),
float(blockI) / float(blockCount))
# We find in which triangle the point lies using the trifinder.
p = xyToQgsPoint(blockOffsetX + x, blockOffsetY + y)
tri = blockTrifinder.find(p)
if tri is None:
# If it's in no triangle, we don't change it
continue
# If it's in a triangle, we transform the coordinates
newP = trimapper.map(p, pointsB[tri[0]],
pointsB[tri[1]], pointsB[tri[2]],
pointsA[tri[0]], pointsA[tri[1]],
pointsA[tri[2]])
newX, newY = qgsPointToXY(newP)
# TODO : this would maybe get interpolated results
#ident = sourceRaster.dataProvider().identify( pt, QgsRaster.IdentifyFormatValue)
#targetDataR[y][x] = ident.results()[1]
#targetDataG[y][x] = ident.results()[2]
#targetDataB[y][x] = ident.results()[3]
try:
if newY < 0 or newX < 0:
raise IndexError() #avoid looping
targetDataR[y][x] = sourceDataR[newY][newX]
targetDataG[y][x] = sourceDataG[newY][newX]
targetDataB[y][x] = sourceDataB[newY][newX]
except IndexError, e:
targetDataR[y][x] = 0
targetDataG[y][x] = 0
targetDataB[y][x] = 0
# Write to the image
dsTarget = gdal.Open(self.targetPath, gdal.GA_Update)
gdalnumeric.BandWriteArray(dsTarget.GetRasterBand(1),
targetDataR, blockOffsetX,
blockOffsetY)
gdalnumeric.BandWriteArray(dsTarget.GetRasterBand(2),
targetDataG, blockOffsetX,
blockOffsetY)
gdalnumeric.BandWriteArray(dsTarget.GetRasterBand(3),
targetDataB, blockOffsetX,
blockOffsetY)
dsTarget = None
def files_mean(file_array, filename_out):
myFiles=[]
myNDV=[]
DimensionsCheck=None
allBandsCount=1
myOutNDV=-32767
for (i, filename) in enumerate(file_array):
if os.path.isfile(filename):
myFile = gdal.Open(filename, gdal.GA_ReadOnly)
if not myFile:
raise IOError("No such file or directory: '%s'" % myFile)
myFiles.append(myFile)
myNDV.append(myFile.GetRasterBand(1).GetNoDataValue())
if DimensionsCheck:
if DimensionsCheck != [myFile.RasterXSize, myFile.RasterYSize]:
raise Exception("Error! Dimensions of file %s (%i, %i) are different from other files (%i, %i). Cannot proceed" % (myF, myFile.RasterXSize, myFile.RasterYSize, DimensionsCheck[0], DimensionsCheck[1]))
else:
DimensionsCheck = [myFile.RasterXSize, myFile.RasterYSize]
if os.path.isfile(filename_out):
os.remove(filename_out)
myBlockSize=myFiles[0].GetRasterBand(1).GetBlockSize();
# store these numbers in variables that may change later
nXValid = myBlockSize[0]
nYValid = myBlockSize[1]
# find total x and y blocks to be read
nXBlocks = (int)((DimensionsCheck[0] + myBlockSize[0] - 1) / myBlockSize[0]);
nYBlocks = (int)((DimensionsCheck[1] + myBlockSize[1] - 1) / myBlockSize[1]);
myBufSize = myBlockSize[0]*myBlockSize[1]
myOutDrv = gdal.GetDriverByName('GTiff')
myOut = myOutDrv.Create(filename_out, DimensionsCheck[0], DimensionsCheck[1], 1,gdal.GDT_Float32)
# set output geo info based on first input layer
myOut.SetGeoTransform(myFiles[0].GetGeoTransform())
myOut.SetProjection(myFiles[0].GetProjection())
for bandNo in range(1,allBandsCount+1):
for X in range(0,nXBlocks):
if X==nXBlocks-1:
nXValid = DimensionsCheck[0] - X * myBlockSize[0]
myBufSize = nXValid*nYValid
# find X offset
myX=X*myBlockSize[0]
# reset buffer size for start of Y loop
nYValid = myBlockSize[1]
myBufSize = nXValid*nYValid
# loop through Y lines
for Y in range(0,nYBlocks):
# change the block size of the final piece
if Y==nYBlocks-1:
nYValid = DimensionsCheck[1] - Y * myBlockSize[1]
myBufSize = nXValid*nYValid
# find Y offset
myY=Y*myBlockSize[1]
# create empty buffer to mark where nodata occurs
myNDVs = None
# make local namespace for calculation
local_namespace = []
for (i, myFile) in enumerate(myFiles):
myval=gdalnumeric.BandReadAsArray(myFile.GetRasterBand(1),
xoff=myX, yoff=myY,
win_xsize=nXValid, win_ysize=nYValid)
# fill in nodata values
if myNDV[i] is not None:
if myNDVs is None:
myNDVs = numpy.zeros(myBufSize)
myNDVs.shape=(nYValid,nXValid)
myNDVs=1*numpy.logical_or(myNDVs==1, myval==myNDV[i])
local_namespace.append(myval)
myval=None
# calculate mean between bands using Numpy
myResult = numpy.mean(local_namespace, axis=0)
if myNDVs is not None:
myResult = ((1*(myNDVs==0))*myResult) + (myOutNDV*myNDVs)
elif not isinstance(myResult, numpy.ndarray):
myResult = numpy.ones( (nYValid,nXValid) ) * myResult
myOutB=myOut.GetRasterBand(bandNo)
gdalnumeric.BandWriteArray(myOutB, myResult, xoff=myX, yoff=myY)
return
# how to use it
files_mean(['./input_01.tif', './input_02.tif', './input_02.tif', ... './input_n.tif',],'./output.tif')
def write_tif(self, outname, data2write= False, dtype = 1, nodata = False, option = 'COMPRESS=DEFLATE'):
'''dtype: ....
if nodata set to True the orig nodata value will be assigned to the raster,
if it is not a double ( in this case no nodata will be assigned)
write_tif(outname, data2write=False, dtype=1, nodata=False, option='Compress=Deflate')
dtypes:
0 --> Int16
1 --> Int32
2 --> UIit16
3 --> UInt32
4 --> Float32
5 --> Float64
6 --> UInt8
'''
dtypeL = [zz_gdalcon.GDT_Int16, zz_gdalcon.GDT_Int32,
zz_gdalcon.GDT_UInt16, zz_gdalcon.GDT_UInt32,
zz_gdalcon.GDT_Float32, zz_gdalcon.GDT_Float64,
zz_gdalcon.GDT_Byte]
try:
if type(data2write) != type(self.data):
data2write = self.data
if len(data2write.shape)==3:
nr_of_bands = data2write.shape[0]
elif len(data2write.shape)==2:
nr_of_bands = 1
else:
raise NameError('ERROR: in Number of Bands')
if not 'int' in str(np.result_type(data2write)):
dataOut = self.driver.Create(outname, self.columns, self.rows, nr_of_bands, dtypeL[dtype])
else:
dataOut = self.driver.Create(outname, self.columns, self.rows, nr_of_bands, dtypeL[dtype], options=[option])
#dataOut.SetGeoTransform(self.intif.GetGeoTransform())
zz_gdalnum.CopyDatasetInfo(self.intif, dataOut)
for band in range(nr_of_bands):
bandOut = dataOut.GetRasterBand(band+1)
if nodata:
#test if nodate can be set
if isinstance(nodata, bool) and 'e' not in str(self.nodata):
nodata = self.nodata
if 'e' in str(nodata):
nodata = False
if nodata:
bandOut.SetNoDataValue(nodata)
if nr_of_bands==1:
zz_gdalnum.BandWriteArray(bandOut,data2write)
else:
zz_gdalnum.BandWriteArray(bandOut,data2write[band,:,:])
bandOut = None
dataOut = None
#print 0
except IOError as e:
print "I/O error({0}): {1}".format(e.errno, e.strerror)
except ValueError:
print ("Could not write the nodata value")
except:
print "Unexpected error:", sys.exc_info()
def write_tif(file_with_srid,full_output_name, data, dtype= 1, nodata=None, option=False ):
'''
write data to tif
>>> write_tif(file_with_srid, full_output_name, data, 1, nodata=None, option=False)
file_wite_srid --> the original file with spatial infromations
full_output_name --> path + filename + tile type e.g.: r'c:\\temp\\file1.tif'
data --> data you want to write to tif
dtype --> Output data type (int, float ...)
input number between 0 and 5:
- 0 --> Int16
- 1 --> Int32
- 2 --> UInt16
- 3 --> UInt32
- 4 --> Float32
- 5 --> Float64
- 6 --> UInt8
--> default is Int32
nodata --> by default there will be no NoData Value asigned
if True:
it will put the max Value for Unsigned Integers
it will put the min Value for signed Integers and floats
if you put a Value --> this Value will be the NoData Value
option --> "COMPRESS=DEFLATE"
if data is a 3d array it will write all bands to the tif (in single bands)
'''
dtypeL = [zz_gdalcon.GDT_Int16,
zz_gdalcon.GDT_Int32,
zz_gdalcon.GDT_UInt16,
zz_gdalcon.GDT_UInt32,
zz_gdalcon.GDT_Float32,
zz_gdalcon.GDT_Float64,
zz_gdalcon.GDT_Byte]
try:
inTiff, driver, inCols, inRows = read_tif_info(file_with_srid)
if len(data.shape)==3:
nr_of_bands = data.shape[0]
elif len(data.shape)==2:
nr_of_bands = 1
else:
print('error in Bands')
sys.exit(1)
#print(nr_of_bands)
if option:
dataOut = driver.Create(full_output_name,inCols,inRows,nr_of_bands, dtypeL[dtype],options=[option])
else:
dataOut = driver.Create(full_output_name,inCols,inRows,nr_of_bands, dtypeL[dtype])
zz_gdalnum.CopyDatasetInfo(inTiff,dataOut)
for band in range(nr_of_bands):
bandOut = dataOut.GetRasterBand(band+1)
if nodata is not None:
bandOut.SetNoDataValue(nodata)
if nr_of_bands==1:
zz_gdalnum.BandWriteArray(bandOut,data)
else:
zz_gdalnum.BandWriteArray(bandOut,data[band,:,:])
bandOut = None
dataOut = None
except IOError as e:
print "I/O error({0}): {1}".format(e.errno, e.strerror)
except ValueError:
print ("Could not write the nodata value")
except:
print "Unexpected error:", sys.exc_info()
def compare ( TET_tem_path, SST_tem_path, outputFile ):
if os.path.exists(outputFile) == False:
os.mkdir(outputFile)
elif os.path.exists(outputFile) == True:
return
os.chdir(outputFile)
TET_tem = gdal.Open(TET_tem_path)
SST_tem = gdal.Open(SST_tem_path)
MIR_band = TET_tem.GetRasterBand(1)
TIR_band = TET_tem.GetRasterBand(2)
SST_band = SST_tem.GetRasterBand(1)
MIR_data = MIR_band.ReadAsArray()
TIR_data = TIR_band.ReadAsArray()
SST_data = SST_band.ReadAsArray()
default_tem = 274.15 * np.ones(SST_data.shape)
# MIR_deg = MIR_data + default_tem
# TIR_deg = TIR_data + default_tem
SST_K = SST_data + default_tem
diff_MIR = MIR_data - SST_K
diff_TIR = TIR_data - SST_K
logic1 = np.where(np.absolute(diff_MIR)>50)
diff_MIR[logic1] = 0
logic2 = np.where(np.absolute(diff_TIR)>50)
diff_TIR[logic2] = 0
diff_MIR_max = diff_MIR.max()
diff_TIR_max = diff_TIR.max()
diff_MIR_min = diff_MIR.min()
diff_TIR_min = diff_TIR.min()
diff_MIR_mean = diff_MIR.mean()
diff_TIR_mean = diff_TIR.mean()
diff_MIR_std = diff_MIR.std()
diff_TIR_std = diff_TIR.std()
diff_MIR_median = np.median(diff_MIR[diff_MIR.nonzero()])
diff_TIR_median = np.median(diff_TIR[diff_TIR.nonzero()])
abs_diff_MIR = np.absolute(diff_MIR)
abs_diff_TIR = np.absolute(diff_TIR)
abs_diff_MIR_mean = abs_diff_MIR.mean()
abs_diff_TIR_mean = abs_diff_TIR.mean()
abs_diff_MIR_std = abs_diff_MIR.std()
abs_diff_TIR_std = abs_diff_TIR.std()
f = open( os.path.join(outputFile, 'statistics_info.txt'), 'w' )
f.write('Difference between SST and TET temperature.\n')
f.write('MIR band.\tUnit: degrees Celsius.\n')
f.write('Maximum: %s.\nMinimum: %s.\n' %(str(diff_MIR_max), str(diff_MIR_min)))
f.write('Mean: %s.\nStandard Deviation: %s.\nMedian Value: %s.\n' %(str(diff_MIR_mean), str(diff_MIR_std), str(diff_MIR_median)))
f.write('Absolute Mean: %s.\nAbsolute Standard Deviation: %s.\n\n' %(str(abs_diff_MIR_mean), str(abs_diff_MIR_std)))
f.write('Difference between SST and TET temperature.\n')
f.write('TIR band.\tUnit: degrees Celsius.\n')
f.write('Maximum: %s.\nMinimum: %s.\n' %(str(diff_TIR_max), str(diff_TIR_min)))
f.write('Mean: %s.\nStandard Deviation: %s.\nMedian Value: %s.\n' %(str(diff_TIR_mean), str(diff_TIR_std), str(diff_TIR_median)))
f.write('Absolute Mean: %s.\nAbsolute Standard Deviation: %s.\n' %(str(abs_diff_TIR_mean), str(abs_diff_TIR_std)))
f.close()
driver = gdal.GetDriverByName('GTiff')
MIR_out = driver.Create('diff_MIR.tif', TET_tem.RasterXSize, TET_tem.RasterYSize, 1, MIR_band.DataType)
gdalnumeric.CopyDatasetInfo(TET_tem, MIR_out)
MIR_bandOut = MIR_out.GetRasterBand(1)
MIR_bandOut.SetNoDataValue(0.0)
gdalnumeric.BandWriteArray(MIR_bandOut, diff_MIR)
TIR_out = driver.Create('diff_TIR.tif', TET_tem.RasterXSize, TET_tem.RasterYSize, 1, TIR_band.DataType)
gdalnumeric.CopyDatasetInfo(TET_tem, TIR_out)
TIR_bandOut = TIR_out.GetRasterBand(1)
TIR_bandOut.SetNoDataValue(0.0)
gdalnumeric.BandWriteArray(TIR_bandOut, diff_TIR)
print 'end'