def do_recode(file, outfile, value_s, value_t, outTypeIn, format, options):
fid0 = gdal.Open(file, GA_ReadOnly)
ns = fid0.RasterXSize
nl = fid0.RasterYSize
nb = fid0.RasterCount
if outTypeIn is None:
outType = fid0.GetRasterBand(1).DataType
else:
outType = ParseType(outTypeIn)
outDrv = gdal.GetDriverByName(format)
outDs = outDrv.Create(outfile, ns, nl, nb, outType, options)
outDs.SetProjection(fid0.GetProjection())
outDs.SetGeoTransform(fid0.GetGeoTransform())
for ib in range(nb):
for il in range(nl):
data0 = N.ravel(
fid0.GetRasterBand(ib + 1).ReadAsArray(0, il, ns, 1))
# set to N.zeros to enable auto cast whenever needed
dataout = N.zeros(ns) + data0
for it in range(len(value_s)):
wtp = (data0 == value_s[it])
if wtp.any():
dataout[wtp] = value_t[it]
dataout.shape = (1, -1)
outDs.GetRasterBand(ib + 1).WriteArray(N.array(dataout), 0, il)
gdal.TermProgress((ib * (ns * nl) + il * ns) / float(ns * nl * nb))
gdal.TermProgress(1)
fpout.write(
str(geotransform[0] + geotransform[1] / 2) + " " +
str(geotransform[0] + geotransform[1] * (band.XSize - 0.5)) + "\n")
if geotransform[5] < 0:
fpout.write(
str(geotransform[3] + geotransform[5] * (band.YSize - 0.5)) + " " +
str(geotransform[3] + geotransform[5] / 2) + "\n")
else:
fpout.write(
str(geotransform[3] + geotransform[5] / 2) + " " +
str(geotransform[3] + geotransform[5] * (band.YSize - 0.5)) + "\n")
fpout.write(
str(band.ComputeRasterMinMax(0)[0]) + " " +
str(band.ComputeRasterMinMax(0)[1]) + "\n")
for i in range(band.YSize - 1, -1, -1):
scanline = band.ReadAsArray(0, i, band.XSize, 1, band.XSize, 1)
j = 0
while j < band.XSize:
fpout.write(str(scanline[0, j]))
j = j + 1
if j % 10: # Print no more than 10 values per line
fpout.write(" ")
else:
fpout.write("\n")
fpout.write("\n")
# Display progress report on terminal
if not quiet:
gdal.TermProgress(float(band.YSize - i) / band.YSize)
if xsize is None:
xsize = abs(geotransform[1])
if ysize is None:
ysize = abs(geotransform[5])
inband = indataset.GetRasterBand(iBand)
if inband is None:
print('Cannot load band', iBand, 'from the', infile)
sys.exit(2)
numtype = gdalnumeric.GDALTypeCodeToNumericTypeCode(typ)
outline = Numeric.empty((1, inband.XSize), numtype)
prev = inband.ReadAsArray(0, 0, inband.XSize, 1, inband.XSize, 1)[0]
outband.WriteArray(outline, 0, 0)
gdal.TermProgress(0.0)
cur = inband.ReadAsArray(0, 1, inband.XSize, 1, inband.XSize, 1)[0]
outband.WriteArray(outline, 0, inband.YSize - 1)
gdal.TermProgress(1.0 / inband.YSize)
dx = 2 * xsize
dy = 2 * ysize
for i in range(1, inband.YSize - 1):
next_ = inband.ReadAsArray(0, i + 1, inband.XSize, 1, inband.XSize, 1)[0]
dzx = (cur[0:-2] - cur[2:]) * elstep
dzy = (prev[1:-1] - next_[1:-1]) * elstep
nx = -dy * dzx
ny = dx * dzy
nz = dx * dy
tif_ds = gtiff_driver.Create(tif_filename, src_ds.RasterXSize,
src_ds.RasterYSize, out_bands)
# ----------------------------------------------------------------------------
# We should copy projection information and so forth at this point.
tif_ds.SetProjection(src_ds.GetProjection())
tif_ds.SetGeoTransform(src_ds.GetGeoTransform())
if src_ds.GetGCPCount() > 0:
tif_ds.SetGCPs(src_ds.GetGCPs(), src_ds.GetGCPProjection())
# ----------------------------------------------------------------------------
# Do the processing one scanline at a time.
gdal.TermProgress(0.0)
for iY in range(src_ds.RasterYSize):
src_data = src_band.ReadAsArray(0, iY, src_ds.RasterXSize, 1)
for iBand in range(out_bands):
band_lookup = lookup[iBand]
dst_data = Numeric.take(band_lookup, src_data)
tif_ds.GetRasterBand(iBand + 1).WriteArray(dst_data, 0, iY)
gdal.TermProgress((iY + 1.0) / src_ds.RasterYSize)
tif_ds = None
# ----------------------------------------------------------------------------
# Translate intermediate file to output format if desired format is not TIFF.
def run(out_file=None, names=None, pre_init=[255]):
global verbose, quiet
verbose = 0
quiet = 0
format = 'GTiff'
ulx = None
psize_x = None
separate = 0
copy_pct = 0
nodata = None
create_options = []
band_type = None
createonly = 0
gdal.AllRegister()
if len(names) == 0:
raise ValueError('No input files selected.')
Driver = gdal.GetDriverByName(format)
if Driver is None:
raise ValueError(
'Format driver %s not found, pick a supported driver.' % format)
DriverMD = Driver.GetMetadata()
if 'DCAP_CREATE' not in DriverMD:
raise ValueError(
'Format driver %s does not support creation and piecewise writing.\nPlease select a format that does, such as GTiff (the default) or HFA (Erdas Imagine).'
% format)
# Collect information on all the source files.
file_infos = names_to_fileinfos(names)
if ulx is None:
ulx = file_infos[0].ulx
uly = file_infos[0].uly
lrx = file_infos[0].lrx
lry = file_infos[0].lry
for fi in file_infos:
ulx = min(ulx, fi.ulx)
uly = max(uly, fi.uly)
lrx = max(lrx, fi.lrx)
lry = min(lry, fi.lry)
if psize_x is None:
psize_x = file_infos[0].geotransform[1]
psize_y = file_infos[0].geotransform[5]
if band_type is None:
band_type = file_infos[0].band_type
# Try opening as an existing file.
gdal.PushErrorHandler('CPLQuietErrorHandler')
t_fh = gdal.Open(out_file, gdal.GA_Update)
gdal.PopErrorHandler()
# Create output file if it does not already exist.
if t_fh is None:
geotransform = [ulx, psize_x, 0, uly, 0, psize_y]
xsize = int((lrx - ulx) / geotransform[1] + 0.5)
ysize = int((lry - uly) / geotransform[5] + 0.5)
if separate != 0:
bands = len(file_infos)
else:
bands = file_infos[0].bands
t_fh = Driver.Create(out_file, xsize, ysize, bands, band_type,
create_options)
if t_fh is None:
print('Creation failed, terminating gdal_merge.')
sys.exit(1)
t_fh.SetGeoTransform(geotransform)
t_fh.SetProjection(file_infos[0].projection)
if copy_pct:
t_fh.GetRasterBand(1).SetRasterColorTable(file_infos[0].ct)
else:
if separate != 0:
bands = len(file_infos)
if t_fh.RasterCount < bands:
print(
'Existing output file has less bands than the number of input files. You should delete it before. Terminating gdal_merge.'
)
sys.exit(1)
else:
bands = min(file_infos[0].bands, t_fh.RasterCount)
# Do we need to pre-initialize the whole mosaic file to some value?
if pre_init is not None:
if t_fh.RasterCount <= len(pre_init):
for i in range(t_fh.RasterCount):
t_fh.GetRasterBand(i + 1).Fill(pre_init[i])
elif len(pre_init) == 1:
for i in range(t_fh.RasterCount):
t_fh.GetRasterBand(i + 1).Fill(pre_init[0])
# Copy data from source files into output file.
t_band = 1
if quiet == 0 and verbose == 0:
gdal.TermProgress(0.0)
fi_processed = 0
for fi in file_infos:
if createonly != 0:
continue
if verbose != 0:
print("")
print("Processing file %5d of %5d, %6.3f%% completed." \
% (fi_processed+1,len(file_infos),
fi_processed * 100.0 / len(file_infos)) )
fi.report()
if separate == 0:
for band in range(1, bands + 1):
fi.copy_into(t_fh, band, band, nodata)
else:
fi.copy_into(t_fh, 1, t_band, nodata)
t_band = t_band + 1
fi_processed = fi_processed + 1
if quiet == 0 and verbose == 0:
gdal.TermProgress(fi_processed / float(len(file_infos)))
# Force file to be closed.
t_fh = None
float(bv) ]
c = [ \
GT[0] + (i0 + i + 1) * GT[1] + (j0 + j) * GT[2],\
GT[3] + (i0 + i + 1) * GT[4] + (j0 + j) * GT[5],\
float(cv) ]
if 1 == OSRds.IsGeographic():
b[0], b[1] = pyproj.transform(P4ds, P4xy, b[0], b[1])
c[0], c[1] = pyproj.transform(P4ds, P4xy, c[0], c[1])
if nd != av:
## point a is valid
a = [ \
GT[0] + (i0 + i) * GT[1] + (j0 + j) * GT[2],\
GT[3] + (i0 + i) * GT[4] + (j0 + j) * GT[5],\
float(av) ]
if 1 == OSRds.IsGeographic():
a[0], a[1] = pyproj.transform(P4ds, P4xy, a[0], a[1])
mesh.add_facet((a, b, c))
if nd != dv:
## point d is valid
d = [ \
GT[0] + (i0 + i + 1) * GT[1] + (j0 + j + 1) * GT[2],\
GT[3] + (i0 + i + 1) * GT[4] + (j0 + j + 1) * GT[5],\
float(dv) ]
if 1 == OSRds.IsGeographic():
d[0], d[1] = pyproj.transform(P4ds, P4xy, d[0], d[1])
mesh.add_facet((d, c, b))
## update progress each row
gdal.TermProgress(float(j + 1) / nym1)
verbose("actual facet count: %s" % str(mesh.written))
def main(argv=sys.argv):
infile = None
outfile = None
iBand = 1
quiet = 0
# Parse command line arguments.
i = 1
while i < len(sys.argv):
arg = sys.argv[i]
if arg == '-b':
i = i + 1
iBand = int(sys.argv[i])
elif arg == '-quiet':
quiet = 1
elif infile is None:
infile = arg
elif outfile is None:
outfile = arg
else:
Usage()
i = i + 1
if infile is None:
return Usage()
if outfile is None:
return Usage()
indataset = gdal.Open(infile, gdal.GA_ReadOnly)
if infile is None:
print('Cannot open', infile)
return 2
geotransform = indataset.GetGeoTransform()
band = indataset.GetRasterBand(iBand)
if band is None:
print('Cannot load band', iBand, 'from the', infile)
return 2
if not quiet:
print('Size is ', indataset.RasterXSize, 'x', indataset.RasterYSize,
'x', indataset.RasterCount)
print('Projection is ', indataset.GetProjection())
print('Origin = (', geotransform[0], ',', geotransform[3], ')')
print('Pixel Size = (', geotransform[1], ',', geotransform[5], ')')
print('Converting band number', iBand, 'with type',
gdal.GetDataTypeName(band.DataType))
# Header printing
fpout = open(outfile, "wt")
fpout.write("DSAA\n")
fpout.write(str(band.XSize) + " " + str(band.YSize) + "\n")
fpout.write(
str(geotransform[0] + geotransform[1] / 2) + " " +
str(geotransform[0] + geotransform[1] * (band.XSize - 0.5)) + "\n")
if geotransform[5] < 0:
fpout.write(
str(geotransform[3] + geotransform[5] * (band.YSize - 0.5)) + " " +
str(geotransform[3] + geotransform[5] / 2) + "\n")
else:
fpout.write(
str(geotransform[3] + geotransform[5] / 2) + " " +
str(geotransform[3] + geotransform[5] * (band.YSize - 0.5)) + "\n")
fpout.write(
str(band.ComputeRasterMinMax(0)[0]) + " " +
str(band.ComputeRasterMinMax(0)[1]) + "\n")
for i in range(band.YSize - 1, -1, -1):
scanline = band.ReadAsArray(0, i, band.XSize, 1, band.XSize, 1)
j = 0
while j < band.XSize:
fpout.write(str(scanline[0, j]))
j = j + 1
if j % 10: # Print no more than 10 values per line
fpout.write(" ")
else:
fpout.write("\n")
fpout.write("\n")
# Display progress report on terminal
if not quiet:
gdal.TermProgress(float(band.YSize - i) / band.YSize)
return 0
def hsv_merge(work_root, rgb, gray, dst):
src_rgb_filename = os.path.join(work_root, rgb)
src_greyscale_filename = os.path.join(work_root, gray)
dst_rgb_filename = os.path.join(work_root, dst)
if os.path.exists(dst_rgb_filename):
return
hilldataset = gdal.Open(src_greyscale_filename, GA_ReadOnly)
colordataset = gdal.Open(src_rgb_filename, GA_ReadOnly)
#check for 3 bands in the color file
if (colordataset.RasterCount != 3):
print 'Source image does not appear to have three bands as required.'
sys.exit(1)
#define output format, name, size, type and set projection
out_driver = gdal.GetDriverByName(format)
outdataset = out_driver.Create(dst_rgb_filename, colordataset.RasterXSize, \
colordataset.RasterYSize, colordataset.RasterCount, type)
outdataset.SetProjection(hilldataset.GetProjection())
outdataset.SetGeoTransform(hilldataset.GetGeoTransform())
#assign RGB and hillshade bands
rBand = colordataset.GetRasterBand(1)
gBand = colordataset.GetRasterBand(2)
bBand = colordataset.GetRasterBand(3)
hillband = hilldataset.GetRasterBand(1)
#check for same file size
if ((rBand.YSize != hillband.YSize) or (rBand.XSize != hillband.XSize)):
print 'Color and hilshade must be the same size in pixels.'
sys.exit(1)
#set progress bar to 0
#gdal.TermProgress( 0.0 )
#loop over lines to apply hillshade
for i in range(hillband.YSize - 1, -1, -1):
#load RGB and Hillshade arrays
rScanline = rBand.ReadAsArray(0, i, hillband.XSize, 1, hillband.XSize,
1)
gScanline = gBand.ReadAsArray(0, i, hillband.XSize, 1, hillband.XSize,
1)
bScanline = bBand.ReadAsArray(0, i, hillband.XSize, 1, hillband.XSize,
1)
hillScanline = hillband.ReadAsArray(0, i, hillband.XSize, 1,
hillband.XSize, 1)
#convert to HSV
hsv = rgb_to_hsv(rScanline, gScanline, bScanline)
#replace v with hillshade
hsv_adjusted = numpy.asarray([hsv[0], hsv[1], hillScanline])
#convert back to RGB
dst_rgb = hsv_to_rgb(hsv_adjusted)
#write out new RGB bands to output one band at a time
outband = outdataset.GetRasterBand(1)
outband.WriteArray(dst_rgb[0], 0, i)
outband = outdataset.GetRasterBand(2)
outband.WriteArray(dst_rgb[1], 0, i)
outband = outdataset.GetRasterBand(3)
outband.WriteArray(dst_rgb[2], 0, i)
#update progress line
gdal.TermProgress(1.0 - (float(i) / hillband.YSize))
def Main():
# Say who we are and what we do
print(
"This Python scruipt creates a histogram from a GIS input file using GDAL and Matplotlib"
)
# Do some initialization
indemfile = None
outfile = None
# Parse command line arguments
i = 1
while i < len(sys.argv):
arg = sys.argv[i]
if i == 1:
indemfile = arg
elif i == 2:
outfile = arg
i += 1
# Do some initialization
nbins = 100
grid = True
xlabel = "Elevation"
ylabel = 'Frequency'
verbose = True
# Do we have both filenames?
if indemfile is None or outfile is None:
Usage()
# OK, open the input DEM file using GDAL
indata = gdal.Open(indemfile)
if indemfile == None:
# Error, give up
print("Cannot open", indemfile)
sys.exit(2)
# Now read in some information using GDAL
geotransform = indata.GetGeoTransform()
nBand = 1 # Assume that there is only one band of data
band = indata.GetRasterBand(nBand)
if band == None:
# Error, give up
print("Cannot load band", nBand, "from", indemfile)
sys.exit(2)
if verbose:
# Display some information about the DEM
print("Reading from", indemfile)
print(" Size is", indata.RasterXSize, "x", indata.RasterYSize, "x",
indata.RasterCount)
print(" Projection is", indata.GetProjection())
print(" Origin = (", geotransform[0], ",", geotransform[3], ")")
print(" Pixel size = (", geotransform[1], ",", geotransform[5], ")")
print(" Overall size =", indata.RasterXSize * geotransform[1], ",",
indata.RasterYSize * geotransform[5])
datatype = gdal.GetDataTypeName(band.DataType)
print(" Reading band number", nBand, "with type", datatype)
min = band.GetMinimum()
max = band.GetMaximum()
if min is None or max is None:
(min, max) = band.ComputeRasterMinMax(nBand)
print(" Min = %.3f, Max = %.3f" % (min, max))
if band.GetOverviewCount() > 0:
print(" Band has", band.GetOverviewCount(), "overviews")
if not band.GetRasterColorTable() is None:
print(" Band has a color table with",
band.GetRasterColorTable().GetCount(), "entries")
print("Storing data from", indemfile)
# Now create a 1D array to store the data
data_list = [0] * (indata.RasterXSize * indata.RasterYSize)
# And read the data into the array
n = 0
for i in range(band.YSize - 1, -1, -1):
scanline = band.ReadAsArray(0, i, band.XSize, 1, band.XSize, 1)
j = 0
while j < band.XSize:
data_list[n] = scanline[0, j]
j += 1
n += 1
if verbose:
gdal.TermProgress(float(band.YSize - i) / band.YSize)
n, bins, patches = plt.hist(data_list,
nbins,
normed=False,
cumulative=False,
histtype='bar',
log=False,
facecolor='green',
alpha=0.75)
plt.xlabel(xlabel) # label the x axis
plt.ylabel(ylabel) # label the y axis
plt.grid(grid) # put a grid on it
plt.show() # plot the graph
# Open the output file TODO check that this opens correctly at runtime
fp_out = open(outfile, "w")
for i in range(len(data_list)):
fp_out.write("%7.6f" % data_list[i])
fp_out.write("\n")
fp_out.close()
if verbose:
print("DEM graphed, end of run")
def readGdalFile(self, bandDim_, bandNumber_, dataType_):
"""
Reads a GDAL file and returns data as numpy array
A GDAL dataset contains a list of raster bands all having the same area
and resolution. Furthermore the dataset contains metadata, a georeferencing
transform as well as a coordinate system, the size of the raster and other
information.
INPUT_PARAMETERS:
bandDim - Define which NetCDF dimension should be represented by GDAL bands (string)
bandNumber - Output image file will contain input band numbers from 1 to 'bandNumber';
if bandNumber is 'None', all bands will be reprojected (integer)
dataType - Define output data type of numpy array (string)
RETURN_VALUE:
numpy data array with data from GDAL input dataset
"""
#Get GDAL input dataset and define settings
#-------------------------------------------------------------------------------
#Set data type for output numpy array
firstBand = self.pDataset.GetRasterBand(1)
if not dataType_ == '': #if Parser.dataType is set or if default NUMPY_DATATYPE != '' then use this value
pDataType = self.pProcessingTool.dataType_2Numpy(dataType_) #Convert to numpy dtype
elif not gdal.GetDataTypeName(firstBand.DataType) is None: #use Dataset type value if there is a type available
pDataType = self.pProcessingTool.dataType_2Numpy(gdal.GetDataTypeName(firstBand.DataType)) #Convert to numpy dtype
else:
raise Exception("Error: No valid data type can be set. Input value is: '" + str(dataType_) + "'")
#Define what bands should be used (from 1 to bandNumber, or all bands if bandNumber is None)
bands = self.__getBandNumber(bandNumber_)
#Define what numpy (NetCDF) dimension should correspond to input bands (self.pDataset.RasterCount)
dimY = int(self.pDataset.RasterYSize) #Last but one axis top to bottom: lat -> row
dimX = int(self.pDataset.RasterXSize) #Last axis left to right: lon -> col
if bandDim_ == 'var':
pDocGradsNumpy = numpy.zeros([int(bands), int(1), int(1), dimY, dimX], dtype = pDataType)
elif bandDim_ == 'time':
pDocGradsNumpy = numpy.zeros([int(1), int(bands), int(1), dimY, dimX], dtype = pDataType)
elif bandDim_ == 'height':
pDocGradsNumpy = numpy.zeros([int(1), int(1), int(bands), dimY, dimX], dtype = pDataType)
else:
raise Exception("Error: Value of bandDim argument not allowed. Valid values are 'var', 'time' or 'height'" )
#Read input dataset and save it to numpy file
#-------------------------------------------------------------------------------
#Easiest and best technique for data reading is line per line. Better would be block size reading.
#Reading one pixel at a time is inefficient. Reading the entire image at once is most efficient, but can cause
#problems if RAM is not sufficient.
for cnBand in range(1, bands + 1, 1): #For all bands defined
pInBand = self.pDataset.GetRasterBand(cnBand) #GetRasterBand is 1-based index
for cnRow in range(pInBand.YSize -1, -1, -1): #Each row in file, Y origin is on upper left in GDAL!
#DimRowCount must run in inverse order as cnRow (from lower left to upper left) because of Y origin
dimRowCn = pInBand.YSize - 1 - cnRow
#scanline = pInBand.ReadAsArray(0, cnRow, pInBand.XSize, 1, \
# pInBand.XSize, 1, GDT_Float32 )
#data = GdalRasterBand.ReadRaster(int nXOffset, int nYOffset, int nXSize, int nYSize, \
#int nBuffXSize, int nBuffYSize, GdalDataType eBufType, int nPixelSpace, int nLineSpace)
scanline = pInBand.ReadRaster( 0, cnRow, pInBand.XSize, 1, \
pInBand.XSize, 1, GDT_Float32 )
#Convert data and cast to numpy data array
#To unpack use IEEE 754 binary32 (for 'f') or binary 64 (for 'd') format
scanline_tupleOfFloats = struct.unpack('f' * pInBand.XSize, scanline)# convert data to Python values
scanline_numpy = numpy.asarray(scanline_tupleOfFloats)
if bandDim_ == 'var':
pDocGradsNumpy[cnBand-1,0,0,dimRowCn,:] = scanline_numpy.astype(pDataType) #cnBand - 1 because of 1-based index
elif bandDim_ == 'time':
pDocGradsNumpy[0,cnBand-1,0,dimRowCn,:] = scanline_numpy.astype(pDataType) #cnBand - 1 because of 1-based index
elif bandDim_ == 'height':
pDocGradsNumpy[0,0,cnBand-1,dimRowCn,:] = scanline_numpy.astype(pDataType) #cnBand - 1 because of 1-based index
else:
raise Exception("Error: Value of bandDim argument ('" + str(bandDim_) + "') not allowed. Valid values are 'var', 'time' or 'height'")
#gdal.TermProgress(float(pInBand.YSize-cnRow) / pInBand.YSize)
gdal.TermProgress(1-(float(self.pDataset.RasterCount - cnBand) / self.pDataset.RasterCount))
return pDocGradsNumpy
# Points b and c are required for both facets, so if either
# are unavailable, we can skip this pixel altogether.
if skip(bv) or skip(cv):
continue
b = (t[0] + ((xmin + x) * t[1]) + ((ymin + y + 1) * t[2]),
t[3] + ((xmin + x) * t[4]) + ((ymin + y + 1) * t[5]),
(zscale * (float(bv) - zmin)) + args.base)
c = (t[0] + ((xmin + x + 1) * t[1]) + ((ymin + y) * t[2]),
t[3] + ((xmin + x + 1) * t[4]) + ((ymin + y) * t[5]),
(zscale * (float(cv) - zmin)) + args.base)
if not skip(av):
a = (t[0] + ((xmin + x) * t[1]) + ((ymin + y) * t[2]),
t[3] + ((xmin + x) * t[4]) + ((ymin + y) * t[5]),
(zscale * (float(av) - zmin)) + args.base)
mesh.add_facet((a, b, c))
if not skip(dv):
d = (t[0] + ((xmin + x + 1) * t[1]) + ((ymin + y + 1) * t[2]),
t[3] + ((xmin + x + 1) * t[4]) + ((ymin + y + 1) * t[5]),
(zscale * (float(dv) - zmin)) + args.base)
mesh.add_facet((d, c, b))
# Update progress each row
gdal.TermProgress(float(y + 1) / mh)
log("actual facet count: %s" % str(mesh.written))
goreStart = 0
goreCenter = goreWidth / 2
# iterate over each gore as specified by the user
# based on C# implementation by winski software
for i in range(gores):
# iterate over each pixel in output gore
for x in range(goreWidth):
dn = inline[0, goreStart + x]
# set new position for pixel value in output array
# updated with round to increase overlap at gore edge
newX = int(round(goreCenter + math.cos((-math.pi/2.0) + (math.pi * float(y) / float(iBand.YSize))) \
* (x - (goreWidth / 2.0))))
dstline[newX] = dn
# move start and center to the correct places
goreStart = goreStart + goreWidth
goreCenter = goreCenter + goreWidth
#write out scanline for the current band
out_array = np.asarray([dstline])
outband.WriteArray(out_array, 0, y)
#update progress line
if not quiet:
gdal.TermProgress(1.0 - (float(y) / iBand.YSize))
#set output to None to close file
outdataset = None
#gdal.TermProgress( 0.0 )
#loop over lines to apply hillshade
for i in range(hillband.YSize - 1, -1, -1):
#load RGB and Hillshade arrays
rScanline = rBand.ReadAsArray(0, i, hillband.XSize, 1, hillband.XSize, 1)
gScanline = gBand.ReadAsArray(0, i, hillband.XSize, 1, hillband.XSize, 1)
bScanline = bBand.ReadAsArray(0, i, hillband.XSize, 1, hillband.XSize, 1)
hillScanline = hillband.ReadAsArray(0, i, hillband.XSize, 1,
hillband.XSize, 1)
#convert to HSV
hsv = rgb_to_hsv(rScanline, gScanline, bScanline)
#replace v with hillshade
hsv_adjusted = numpy.asarray([hsv[0], hsv[1], hillScanline])
#convert back to RGB
dst_rgb = hsv_to_rgb(hsv_adjusted)
#write out new RGB bands to output one band at a time
outband = outdataset.GetRasterBand(1)
outband.WriteArray(dst_rgb[0], 0, i)
outband = outdataset.GetRasterBand(2)
outband.WriteArray(dst_rgb[1], 0, i)
outband = outdataset.GetRasterBand(3)
outband.WriteArray(dst_rgb[2], 0, i)
#update progress line
gdal.TermProgress(1.0 - (float(i) / hillband.YSize))
def main(argv=sys.argv):
infile = None
outfile = None
iBand = 1 # The first band will be converted by default
driver_name = 'GTiff'
typ = gdal.GDT_Byte
lsrcaz = None
lsrcel = None
elstep = 1.0
xsize = None
ysize = None
dyn_range = 255.0
# Parse command line arguments.
i = 1
while i < len(argv):
arg = argv[i]
if arg == '-b':
i += 1
iBand = int(argv[i])
elif arg == '-ot':
i += 1
typ = ParseType(argv[i])
elif arg == '-lsrcaz':
i += 1
lsrcaz = float(argv[i])
elif arg == '-lsrcel':
i += 1
lsrcel = float(argv[i])
elif arg == '-elstep':
i += 1
elstep = float(argv[i])
elif arg == '-dx':
i += 1
xsize = float(argv[i])
elif arg == '-dy':
i += 1
ysize = float(argv[i])
elif arg == '-r':
i += 1
dyn_range = float(argv[i])
elif infile is None:
infile = arg
elif outfile is None:
outfile = arg
else:
return Usage()
i += 1
if infile is None:
return Usage()
if outfile is None:
return Usage()
if lsrcaz is None:
return Usage()
if lsrcel is None:
return Usage()
# translate angles from degrees to radians
lsrcaz = lsrcaz / 180.0 * math.pi
lsrcel = lsrcel / 180.0 * math.pi
lx = -math.sin(lsrcaz) * math.cos(lsrcel)
ly = math.cos(lsrcaz) * math.cos(lsrcel)
lz = math.sin(lsrcel)
lxyz = math.sqrt(lx**2 + ly**2 + lz**2)
indataset = gdal.Open(infile, gdal.GA_ReadOnly)
if indataset is None:
print('Cannot open', infile)
return 2
if indataset.RasterXSize < 3 or indataset.RasterYSize < 3:
print('Input image is too small to process, minimum size is 3x3')
return 3
out_driver = gdal.GetDriverByName(driver_name)
outdataset = out_driver.Create(outfile, indataset.RasterXSize,
indataset.RasterYSize,
indataset.RasterCount, typ)
outband = outdataset.GetRasterBand(1)
geotransform = indataset.GetGeoTransform()
projection = indataset.GetProjection()
if xsize is None:
xsize = abs(geotransform[1])
if ysize is None:
ysize = abs(geotransform[5])
inband = indataset.GetRasterBand(iBand)
if inband is None:
print('Cannot load band', iBand, 'from the', infile)
return 2
numtype = gdal_array.GDALTypeCodeTonpTypeCode(typ)
outline = np.empty((1, inband.XSize), numtype)
prev = inband.ReadAsArray(0, 0, inband.XSize, 1, inband.XSize, 1)[0]
outband.WriteArray(outline, 0, 0)
gdal.TermProgress(0.0)
cur = inband.ReadAsArray(0, 1, inband.XSize, 1, inband.XSize, 1)[0]
outband.WriteArray(outline, 0, inband.YSize - 1)
gdal.TermProgress(1.0 / inband.YSize)
dx = 2 * xsize
dy = 2 * ysize
for i in range(1, inband.YSize - 1):
next_ = inband.ReadAsArray(0, i + 1, inband.XSize, 1, inband.XSize,
1)[0]
dzx = (cur[0:-2] - cur[2:]) * elstep
dzy = (prev[1:-1] - next_[1:-1]) * elstep
nx = -dy * dzx
ny = dx * dzy
nz = dx * dy
nxyz = nx * nx + ny * ny + nz * nz
nlxyz = nx * lx + ny * ly + nz * lz
cosine = dyn_range * (nlxyz / (lxyz * np.sqrt(nxyz)))
cosine = np.clip(cosine, 0.0, dyn_range)
outline[0, 1:-1] = cosine.astype(numtype)
outband.WriteArray(outline, 0, i)
prev = cur
cur = next_
# Display progress report on terminal
gdal.TermProgress(float(i + 1) / (inband.YSize - 1))
outdataset.SetGeoTransform(geotransform)
outdataset.SetProjection(projection)
return 0
def main(argv=None):
global verbose, quiet
verbose = 0
quiet = 0
names = []
format = 'GTiff'
out_file = 'out.tif'
ulx = None
psize_x = None
separate = 0
copy_pct = 0
nodata = None
create_options = []
pre_init = []
band_type = None
createonly = 0
gdal.AllRegister()
if argv is None:
argv = sys.argv
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 == '-o':
i = i + 1
out_file = argv[i]
elif arg == '-v':
verbose = 1
elif arg == '-q' or arg == '-quiet':
quiet = 1
elif arg == '-createonly':
createonly = 1
elif arg == '-separate':
separate = 1
elif arg == '-seperate':
separate = 1
elif arg == '-pct':
copy_pct = 1
elif arg == '-ot':
i = i + 1
band_type = gdal.GetDataTypeByName(argv[i])
if band_type == gdal.GDT_Unknown:
print('Unknown GDAL data type: ', argv[i])
sys.exit(1)
elif arg == '-init':
i = i + 1
str_pre_init = argv[i].split()
for x in str_pre_init:
pre_init.append(float(x))
elif arg == '-n':
i = i + 1
nodata = float(argv[i])
elif arg == '-f':
# for backward compatibility.
i = i + 1
format = argv[i]
elif arg == '-of':
i = i + 1
format = argv[i]
elif arg == '-co':
i = i + 1
create_options.append(argv[i])
elif arg == '-ps':
psize_x = float(argv[i + 1])
psize_y = -1 * abs(float(argv[i + 2]))
i = i + 2
elif arg == '-ul_lr':
ulx = float(argv[i + 1])
uly = float(argv[i + 2])
lrx = float(argv[i + 3])
lry = float(argv[i + 4])
i = i + 4
elif arg[:1] == '-':
print('Unrecognised command option: ', arg)
Usage()
sys.exit(1)
else:
# Expand any possible wildcards from command line arguments
f = glob.glob(arg)
if len(f) == 0:
print('File not found: "%s"' % (str(arg)))
names += f # append 1 or more files
i = i + 1
if len(names) == 0:
print('No input files selected.')
Usage()
sys.exit(1)
Driver = gdal.GetDriverByName(format)
if Driver is None:
print('Format driver %s not found, pick a supported driver.' % format)
sys.exit(1)
DriverMD = Driver.GetMetadata()
if 'DCAP_CREATE' not in DriverMD:
print(
'Format driver %s does not support creation and piecewise writing.\nPlease select a format that does, such as GTiff (the default) or HFA (Erdas Imagine).'
% format)
sys.exit(1)
# Collect information on all the source files.
file_infos = names_to_fileinfos(names)
if ulx is None:
ulx = file_infos[0].ulx
uly = file_infos[0].uly
lrx = file_infos[0].lrx
lry = file_infos[0].lry
for fi in file_infos:
ulx = min(ulx, fi.ulx)
uly = max(uly, fi.uly)
lrx = max(lrx, fi.lrx)
lry = min(lry, fi.lry)
if psize_x is None:
psize_x = file_infos[0].geotransform[1]
psize_y = file_infos[0].geotransform[5]
if band_type is None:
band_type = file_infos[0].band_type
# Try opening as an existing file.
gdal.PushErrorHandler('CPLQuietErrorHandler')
t_fh = gdal.Open(out_file, gdal.GA_Update)
gdal.PopErrorHandler()
# Create output file if it does not already exist.
if t_fh is None:
geotransform = [ulx, psize_x, 0, uly, 0, psize_y]
xsize = int((lrx - ulx) / geotransform[1] + 0.5)
ysize = int((lry - uly) / geotransform[5] + 0.5)
if separate != 0:
bands = len(file_infos)
else:
bands = file_infos[0].bands
t_fh = Driver.Create(out_file, xsize, ysize, bands, band_type,
create_options)
if t_fh is None:
print('Creation failed, terminating gdal_merge.')
sys.exit(1)
t_fh.SetGeoTransform(geotransform)
t_fh.SetProjection(file_infos[0].projection)
if copy_pct:
t_fh.GetRasterBand(1).SetRasterColorTable(file_infos[0].ct)
else:
if separate != 0:
bands = len(file_infos)
if t_fh.RasterCount < bands:
print(
'Existing output file has less bands than the number of input files. You should delete it before. Terminating gdal_merge.'
)
sys.exit(1)
else:
bands = min(file_infos[0].bands, t_fh.RasterCount)
# Do we need to pre-initialize the whole mosaic file to some value?
if pre_init is not None:
if t_fh.RasterCount <= len(pre_init):
for i in range(t_fh.RasterCount):
t_fh.GetRasterBand(i + 1).Fill(pre_init[i])
elif len(pre_init) == 1:
for i in range(t_fh.RasterCount):
t_fh.GetRasterBand(i + 1).Fill(pre_init[0])
# Copy data from source files into output file.
t_band = 1
if quiet == 0 and verbose == 0:
gdal.TermProgress(0.0)
fi_processed = 0
for fi in file_infos:
if createonly != 0:
continue
if verbose != 0:
print("")
print("Processing file %5d of %5d, %6.3f%% completed." \
% (fi_processed+1,len(file_infos),
fi_processed * 100.0 / len(file_infos)) )
fi.report()
if separate == 0:
for band in range(1, bands + 1):
fi.copy_into(t_fh, band, band, nodata)
else:
fi.copy_into(t_fh, 1, t_band, nodata)
t_band = t_band + 1
fi_processed = fi_processed + 1
if quiet == 0 and verbose == 0:
gdal.TermProgress(fi_processed / float(len(file_infos)))
# Force file to be closed.
t_fh = None
def main(argv):
frmt = 'GTiff'
src_filename = None
dst_filename = None
src_band_n = 1
dst_band_n = 1
lut_filename = None
create_options = []
gdal.AllRegister()
argv = gdal.GeneralCmdLineProcessor(argv)
if argv is None:
return 0
# Parse command line arguments.
i = 1
while i < len(argv):
arg = argv[i]
if arg == '-of':
i = i + 1
frmt = argv[i]
elif arg == '-co':
i = i + 1
create_options.append(argv[i])
elif arg == '-lutfile':
i = i + 1
lut_filename = 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 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 lut_filename is None:
Usage()
# ----------------------------------------------------------------------------
# Load the LUT file.
lut = read_lut(lut_filename)
max_val = 0
for entry in lut:
if entry > max_val:
max_val = entry
if max_val > 255:
tc = numpy.uint16
gc = gdal.GDT_UInt16
else:
tc = numpy.uint8
gc = gdal.GDT_Byte
# ----------------------------------------------------------------------------
# Convert the LUT from a normal array to a numpy style array.
if len(lut) <= 256:
lookup = numpy.arange(256)
for i in range(min(256, len(lut))):
lookup[i] = lut[i]
else:
lookup = numpy.arange(65536)
for i in range(min(65536, len(lut))):
lookup[i] = lut[i]
lookup = lookup.astype(tc)
# ----------------------------------------------------------------------------
# Open source file
if dst_filename is None:
src_ds = gdal.Open(src_filename, gdal.GA_Update)
dst_ds = src_ds
else:
src_ds = gdal.Open(src_filename)
dst_ds = None
if src_ds is None:
print('Unable to open ', src_filename)
return 1
src_band = src_ds.GetRasterBand(src_band_n)
# ----------------------------------------------------------------------------
# Open or create output file.
dst_driver = gdal.GetDriverByName(frmt)
if dst_driver is None:
print('"%s" driver not registered.' % frmt)
return 1
if dst_ds is None:
try:
dst_ds = gdal.Open(dst_filename, gdal.GA_Update)
except:
dst_ds = None
if dst_ds is None:
dst_ds = dst_driver.Create(dst_filename,
src_ds.RasterXSize,
src_ds.RasterYSize,
1, gc, options=create_options)
dst_ds.SetProjection(src_ds.GetProjection())
dst_ds.SetGeoTransform(src_ds.GetGeoTransform())
dst_band = dst_ds.GetRasterBand(dst_band_n)
# ----------------------------------------------------------------------------
# Do the processing one scanline at a time.
gdal.TermProgress(0.0)
for iY in range(src_ds.RasterYSize):
src_data = src_band.ReadAsArray(0, iY, src_ds.RasterXSize, 1)
dst_data = numpy.take(lookup, src_data)
dst_band.WriteArray(dst_data, 0, iY)
gdal.TermProgress((iY + 1.0) / src_ds.RasterYSize)
src_ds = None
dst_ds = None
return 0
red_band = red_dataset.GetRasterBand(1)
if (green_dataset.RasterCount > 1):
green_band = green_dataset.GetRasterBand(2)
else:
green_band = green_dataset.GetRasterBand(1)
if (blue_dataset.RasterCount > 2):
blue_band = blue_dataset.GetRasterBand(3)
else:
blue_band = blue_dataset.GetRasterBand(1)
red_outband = outdataset.GetRasterBand(1)
green_outband = outdataset.GetRasterBand(2)
blue_outband = outdataset.GetRasterBand(3)
gdal.TermProgress(0.0)
for i in range(red_band.YSize - 1, -1, -1):
red_scanline = red_band.ReadAsArray(0, i, red_band.XSize, 1,
red_band.XSize, 1).astype(float)
green_scanline = green_band.ReadAsArray(0, i, green_band.XSize, 1,
green_band.XSize, 1).astype(float)
blue_scanline = blue_band.ReadAsArray(0, i, blue_band.XSize, 1,
blue_band.XSize, 1).astype(float)
red_scanline = numpy.power(red_scanline * scale / 65535.0,
1.0 / gamma) * 255.0
green_scanline = numpy.power(green_scanline * scale / 65535.0,
1.0 / gamma) * 255.0
blue_scanline = numpy.power(blue_scanline * scale / 65535.0,
1.0 / gamma) * 255.0