def show(raster):
from IPython.display import Image
import grass.script as gs
region = gs.region()
gs.run_command('d.erase')
gs.use_temp_region()
gs.run_command('g.region',
align='ortho',
n=region['n'],
s=region['s'],
e=region['e'],
w=region['w'])
gs.run_command('d.rast', map='ortho')
gs.run_command('d.rast', map=raster, values=0, flags='i')
gs.run_command('d.vect',
map='NHDFlowline',
where="FCODE >= 46006",
color='30:144:255')
gs.run_command('d.vect',
map='roads',
where="FULLNAME is not NULL",
color='165:159:159',
width=2)
gs.run_command('d.barscale',
at=[38.0, 97.0],
flags='n',
style='both_ticks',
segment=5,
color='255:255:255',
bgcolor='none')
gs.del_temp_region()
return Image("map.png")
def convert_map(output, variable):
"""Convert imported raster map unit and format."""
# prepare for unit conversion
if flags['c'] and variable in ['tmin', 'tmax', 'tmean']:
grass.message("Converting {} to degree Celcius...".format(output))
a = 0.1
b = 0
elif flags['k'] and variable in ['tmin', 'tmax', 'tmean']:
grass.message("Converting {} to Kelvin...".format(output))
a = 0.1
b = 273.15
elif flags['y'] and variable == 'prec':
grass.message("Converting {} to meter per year...".format(output))
a = 0.012
b = 0
elif flags['f']:
grass.message("Converting {} to floating-point...".format(output))
a = 1
b = 0
else:
a = None
b = None
# convert unit and format
if a or b:
grass.use_temp_region()
grass.run_command('g.region', rast=output)
grass.mapcalc('$output=float($output*$a+$b)', a=a, b=b, output=output,
overwrite=True)
grass.del_temp_region()
def main():
# process command options
input = options['input']
if not gs.find_file(input)['file']:
gs.fatal(_("Raster map <%s> not found") % input)
output = options['output']
if gs.find_file(output)['file'] and not gs.overwrite():
gs.fatal(_("Output map <%s> already exists") % output)
# set aside region for internal use
gs.use_temp_region()
# subset input if desired
region = options.get('region')
if region:
if not gs.find_file(region)['file']:
gs.fatal(_("Raster map <%s> not found") % region)
gs.message("Setting region to %s" % region, flag='i')
gs.run_command('g.region', rast=region, align=input)
else:
gs.message("Using existing GRASS region", flag='i')
gs.debug('='*50)
gs.debug('\n'.join(gs.parse_command('g.region', 'p').keys()))
gs.debug('='*50)
calculate_noise(input, output)
# restore original region
gs.del_temp_region()
return None
def convert_map(output, field):
"""Convert imported raster map unit and format."""
# prepare for unit conversion
if flags['c'] and field in ['tmin', 'tmax', 'tmean']:
grass.message("Converting <%s> to degree Celcius..." % output)
a = 0.1
b = 0
elif flags['k'] and field in ['tmin', 'tmax', 'tmean']:
grass.message("Converting <%s> to Kelvin..." % output)
a = 0.1
b = 273.15
elif flags['y'] and field == 'prec':
grass.message("Converting <%s> to meter per year..." % output)
a = 0.012
b = 0
elif flags['f']:
grass.message("Converting <%s> to floating-point..." % output)
a = 1
b = 0
else:
a = None
b = None
# convert unit and format
if a or b:
grass.use_temp_region()
grass.run_command('g.region', rast=output)
grass.mapcalc('$output=float($output*%s+%s)' % (a, b), output=output)
grass.del_temp_region()
def main():
#create a list for parallel mapcalc modules and a mapcalc module to act as template
mapcalc_list = []
mapcalc = Module("r.mapcalc", overwrite=True, run_=False)
#get number of tiles in each row and col from arguments
tile_rows = int(sys.argv[1])
tile_cols = int(sys.argv[2])
#Create que for parallel processes
queue = ParallelModuleQueue(nprocs=sys.argv[3])
#Use temporary region that will be reset after execution of this script
gscript.use_temp_region()
#Input raster (can be grass raster dataset or externally linked dataset such as tiff vrt etc.)
input="input_raster"
#Read raster boundaries and resolution into numeric variables
info = gscript.raster_info(input)
no = float(info['north'])
so = float(info['south'])
we = float(info['west'])
ea = float(info['east'])
ro = int(info['rows'])
co = int(info['cols'])
ewr = int(info['ewres'])
nsr = int(info['nsres'])
#Start mapcalc module for each tile
k = 0
for i in xrange(tile_rows):
for j in xrange(tile_cols):
#Set processing region to specific part of the raster (column+row)
gscript.run_command('g.region',
n=so+(i+1)*ro/tile_rows*nsr,
s=so+i*ro/tile_rows*nsr,
e=we+(1+j)*co/tile_cols*ewr,
w=we+j*co/tile_cols*ewr,
rows=ro/tile_rows,
cols=co/tile_cols,
nsres=nsr,
ewres=ewr)
#Create a copy of mapcalc template, give it mapcalc expression and put it into parallel que where it will be executed when a process becomes available.
new_mapcalc = copy.deepcopy(mapcalc)
mapcalc_list.append(new_mapcalc)
m = new_mapcalc(expression="test_pygrass_%i = %s * (%i+1)"%(k,input, k))
queue.put(m)
k+=1
#wait for all mapcalc modules to have finished execution
queue.wait()
#print mapcalc returncodes to check that everything went as expected
for mapcalc in mapcalc_list:
print(mapcalc.popen.returncode)
#delete temporary region to restore the region that was in use at the start of the script
gscript.del_temp_region()
def cleanup(self):
"""Remove temporary region and mask.
"""
msgr.debug("Reset mask and region")
if self.raster_mask_id:
msgr.debug("Remove temp MASK...")
self.del_temp_mask()
if self.region_id:
msgr.debug("Remove temp region...")
gscript.del_temp_region()
self.raster_writer_queue.put(None)
self.raster_writer_thread.join()
def main():
# start messenger
msgr = Messenger()
# Use temporary GRASS region
grass.use_temp_region()
# reads CLI options
rast_n_file_name = options['friction']
rast_dem_name = options['dem']
rast_start_file_name = options['start_file']
rast_bc_name = options['bc']
rast_bcval_name = options['bcval']
rast_user_name = options['user_inflow']
# Load *.par file
par = Par(msgr, options['par_file'])
par.read()
# Write DEM file
par.write_dem(rast_dem_name, grass.overwrite())
# set computational region to match DEM
par.set_region_from_map(rast_dem_name)
# Write friction
par.write_n_map(rast_n_file_name, grass.overwrite())
# Write start file
par.write_start_h(rast_start_file_name, grass.overwrite())
# boundary conditions
bc = BoundaryConditions(msgr, sim_time=par.sim_time,
region=par.region)
if par.bci_file:
bci_full_path = os.path.join(par.directory, par.bci_file)
bc.read_bci(bci_full_path)
if par.bdy_file:
bdy_full_path = os.path.join(par.directory, par.bdy_file)
bc.read_bdy(bdy_full_path)
# create STDS
bc.create_stds(stds_name=rast_user_name, overwrite=grass.overwrite())
bc.create_stds(rast_bcval_name, overwrite=grass.overwrite())
# Write maps en register them in STDS
bc.populate_user_flow_stds(rast_quser_name=rast_user_name,
overwrite=grass.overwrite())
bc.populate_bc_stds(rast_bcval_name, grass.overwrite())
# write Boundary condition type map
bc.write_bctype(rast_bc_name, grass.overwrite())
# Restore original region
grass.del_temp_region()
return 0
def patch_tiles(mt, out, vari, bc=None, mnth=None):
"""Set region to tiles, and run r.patch"""
bc = (str(bc) if bc else '')
mnth = (str(mnth) if mnth else '')
grass.message("Patching the tiles for {}{}{} to {}"
.format(vari, bc, mnth, out))
if len(mt) > 1:
grass.use_temp_region()
grass.run_command("g.region", raster=mt)
grass.run_command("r.patch", input=mt, output=out)
grass.run_command("g.remove", type="raster", name=mt, flags="f",
quiet=True)
grass.del_temp_region()
else:
# simply rename if there is only one tile
grass.run_command("g.rename", raster=[mt, out])
def run_benchmark(resolution_list, runs, testdict, profile):
regions = []
for resolution in resolution_list:
core.use_temp_region()
core.run_command('g.region', e=50, w=-50, n=50, s=-50, res=resolution, flags='p')
# Adjust the computational region for this process
region = libgis.Cell_head()
libraster.Rast_get_window(ctypes.byref(region))
region.e = 50
region.w = -50
region.n = 50
region.s = -50
region.ew_res = resolution
region.ns_res = resolution
libgis.G_adjust_Cell_head(ctypes.byref(region), 0, 0)
libraster.Rast_set_window(ctypes.byref(region))
libgis.G_set_window(ctypes.byref(region))
# Create two raster maps with random numbers
core.mapcalc("test_a = rand(0, 100)", quite=True, overwrite=True)
core.mapcalc("test_b = rand(0.0, 1.0)", quite=True, overwrite=True)
result = collections.OrderedDict()
result['res'] = resolution
result['cols'] = region.cols
result['rows'] = region.rows
result['cells'] = region.rows * region.cols
result['results'] = copy.deepcopy(testdict)
for execmode, operation in result['results'].items():
print(execmode)
for oper, operdict in operation.items():
operdict['time'], operdict['times'] = mytimer(operdict['func'],runs)
if profile:
filename = '{}_{}_{}'.format(execmode, oper, profile)
cProfile.runctx(operdict['func'].__name__ + '()',
globals(), locals(), filename = filename)
print((' {0}: {1: 40.6f}s'.format(oper, operdict['time'])))
del(operdict['func'])
regions.append(result)
core.del_temp_region()
return regions
def main():
# process command options
input = options['input']
if not gs.find_file(input)['file']:
gs.fatal(_("Raster map <%s> not found") % input)
smooth = options['output']
if gs.find_file(smooth)['file'] and not gs.overwrite():
gs.fatal(_("Output map <%s> already exists") % smooth)
sd = options['sd']
try:
sd = float(sd)
except ValueError:
if not gs.find_file(sd)['file']:
gs.fatal(_("Raster map <%s> not found") % sd)
alpha = float(options['alpha'])
# set aside region for internal use
gs.use_temp_region()
# subset input if desired
region = options.get('region')
if region:
if not gs.find_file(region)['file']:
gs.fatal(_("Raster map <%s> not found") % region)
gs.message("Setting region to %s" % region, flag='i')
gs.run_command('g.region', rast=region, align=input)
else:
gs.message("Using existing GRASS region", flag='i')
gs.debug('='*50)
gs.debug('\n'.join(gs.parse_command('g.region', 'p').keys()))
gs.debug('='*50)
multiscalesmooth(input, smooth, sd, alpha)
# restore original region
gs.del_temp_region()
return None
def main():
global acq_time, esd
"""1st, get input, output, options and flags"""
spectral_bands = options['band'].split(',')
outputsuffix = options['outputsuffix']
utc = options['utc']
doy = options['doy']
sea = options['sea']
radiance = flags['r']
keep_region = flags['k']
# mapset = grass.gisenv()['MAPSET'] # Current Mapset?
# imglst = [spectral_bands]
# images = {}
# for img in imglst: # Retrieving Image Info
# images[img] = Info(img, mapset)
# images[img].read()
# -----------------------------------------------------------------------
# Temporary Region and Files
# -----------------------------------------------------------------------
if not keep_region:
grass.use_temp_region() # to safely modify the region
tmpfile = grass.tempfile() # Temporary file - replace with os.getpid?
tmp = "tmp." + grass.basename(tmpfile) # use its basename
# -----------------------------------------------------------------------
# Global Metadata: Earth-Sun distance, Sun Zenith Angle
# -----------------------------------------------------------------------
# Earth-Sun distance
if doy:
esd = jd_to_esd(int(doy))
elif utc:
acq_utc = AcquisitionTime(utc) # will hold esd (earth-sun distance)
acq_dat = datetime(acq_utc.year, acq_utc.month, acq_utc.day)
esd = acq_utc.esd
else:
grass.fatal(_("Either the UTC string or "
"the Day-of-Year (doy) are required!"))
sza = 90 - float(sea) # Sun Zenith Angle based on Sun Elevation Angle
# -----------------------------------------------------------------------
# Loop processing over all bands
# -----------------------------------------------------------------------
for band in spectral_bands:
global tmp_rad
g.message("|* Processing the %s spectral band" % band, flags='i')
if not keep_region:
g.message("\n|! Matching region to %s" % band) # set region
run('g.region', rast=band) # ## FixMe
# -------------------------------------------------------------------
# Converting to Spectral Radiance
# -------------------------------------------------------------------
msg = "\n|> Converting to Spectral Radiance: " \
# "L(λ) = 10^4 x DN(λ) / CalCoef(λ) x Bandwidth(λ)" # Unicode? ##
g.message(msg)
# -------------------------------------------------------------------
# Band dependent metadata for Spectral Radiance
# -------------------------------------------------------------------
# Why is this necessary? Any function to remove the mapsets name?
if '@' in band:
band_key = (band.split('@')[0])
else:
band_key = band
# get coefficients
if acq_dat < cc_update:
g.message("\n|! Using Pre-2001 Calibration Coefficient values",
flags='i')
cc = float(CC[band_key][0])
else:
cc = float(CC[band_key][1])
# get bandwidth
bw = float(CC[band_key][2])
# inform
msg = " [Calibration Coefficient=%d, Bandwidth=%.1f]" \
% (cc, bw)
g.message(msg)
# convert
tmp_rad = "%s.Radiance" % tmp # Temporary Map
rad = "%s = 10^4 * %s / %f * %f" \
% (tmp_rad, band, cc, bw)
grass.mapcalc(rad, overwrite=True)
# string for metadata
history_rad = rad
history_rad += "Calibration Coefficient=%d; Effective Bandwidth=%.1f" \
% (cc, bw)
title_rad = "%s band (Spectral Radiance)" % band
units_rad = "W / m2 / μm / ster"
description_rad = "At-sensor %s band spectral Radiance (W/m2/μm/sr)" \
% band
if not radiance:
# ---------------------------------------------------------------
# Converting to Top-of-Atmosphere Reflectance
# ---------------------------------------------------------------
global tmp_toar
msg = "\n|> Converting to Top-of-Atmosphere Reflectance" \
# "ρ(p) = π x L(λ) x d^2 / ESUN(λ) x cos(θ(S))" # Unicode?
g.message(msg)
# ---------------------------------------------------------------
# Band dependent metadata for Spectral Radiance
# ---------------------------------------------------------------
# get esun
esun = CC[band_key][3]
# inform
msg = " [Earth-Sun distane=%f, Mean solar exoatmospheric " \
"irradiance=%.1f]" % (esd, esun)
g.message(msg)
# convert
tmp_toar = "%s.Reflectance" % tmp # Spectral Reflectance
toar = "%s = %f * %s * %f^2 / %f * cos(%f)" \
% (tmp_toar, math.pi, tmp_rad, esd, esun, sza)
grass.mapcalc(toar, overwrite=True)
# strings for output's metadata
history_toar = toar
history_toar += "ESD=%f; BAND_Esun=%f; SZA=%f" % (esd, esun, sza)
title_toar = "%s band (Top of Atmosphere Reflectance)" % band
units_toar = "Unitless planetary reflectance"
description_toar = "Top of Atmosphere `echo ${BAND}` band spectral"
" Reflectance (unitless)"
if tmp_toar:
# history entry
run("r.support", map=tmp_toar, title=title_toar,
units=units_toar, description=description_toar,
source1=source1_toar, source2=source2_toar,
history=history_toar)
# add suffix to basename & rename end product
toar_name = ("%s.%s" % (band.split('@')[0], outputsuffix))
run("g.rename", rast=(tmp_toar, toar_name))
elif tmp_rad:
# history entry
run("r.support", map=tmp_rad,
title=title_rad, units=units_rad, description=description_rad,
source1=source1_rad, source2=source2_rad, history=history_rad)
# add suffix to basename & rename end product
rad_name = ("%s.%s" % (band.split('@')[0], outputsuffix))
run("g.rename", rast=(tmp_rad, rad_name))
# visualising-related information
if not keep_region:
grass.del_temp_region() # restoring previous region settings
g.message("\n|! Region's resolution restored!")
g.message("\n>>> Hint: rebalancing colors "
"(i.colors.enhance) may improve appearance of RGB composites!",
flags='i')
def main():
"""
Main program
"""
# Temporary filenames
# The following three are meant for a test step-by-step cwv estimation, see
# unused functions!
# tmp_ti_mean = tmp_map_name('ti_mean') # for cwv
# tmp_tj_mean = tmp_map_name('tj_mean') # for cwv
# tmp_ratio = tmp_map_name('ratio') # for cwv
tmp_avg_lse = tmp_map_name('avg_lse')
tmp_delta_lse = tmp_map_name('delta_lse')
tmp_cwv = tmp_map_name('cwv')
#tmp_lst = tmp_map_name('lst')
# basic equation for mapcalc
global equation, citation_lst
equation = "{result} = {expression}"
# user input
mtl_file = options['mtl']
if not options['prefix']:
b10 = options['b10']
b11 = options['b11']
t10 = options['t10']
t11 = options['t11']
if not options['clouds']:
qab = options['qab']
cloud_map = False
else:
qab = False
cloud_map = options['clouds']
elif options['prefix']:
prefix = options['prefix']
b10 = prefix + '10'
b11 = prefix + '11'
if not options['clouds']:
qab = prefix + 'QA'
cloud_map = False
else:
cloud_map = options['clouds']
qab = False
qapixel = options['qapixel']
lst_output = options['lst']
# save Brightness Temperature maps?
global brightness_temperature_prefix
if options['prefix_bt']:
brightness_temperature_prefix = options['prefix_bt']
else:
brightness_temperature_prefix = None
global cwv_output
cwv_window_size = int(options['window'])
assertion_for_cwv_window_size_msg = ('A spatial window of size 5^2 or less is not '
'recommended. Please select a larger window. '
'Refer to the manual\'s notes for details.')
assert cwv_window_size >= 7, assertion_for_cwv_window_size_msg
cwv_output = options['cwv']
# optional maps
average_emissivity_map = options['emissivity']
delta_emissivity_map = options['delta_emissivity']
# output for in-between maps?
global emissivity_output, delta_emissivity_output
emissivity_output = options['emissivity_out']
delta_emissivity_output = options['delta_emissivity_out']
global landcover_map, emissivity_class
landcover_map = options['landcover']
emissivity_class = options['emissivity_class']
# flags
global info, null
info = flags['i']
scene_extent = flags['e']
timestamping = flags['t']
null = flags['n']
global rounding
rounding = flags['r']
global celsius
celsius = flags['c']
# ToDo:
# shell = flags['g']
#
# Pre-production actions
#
# Set Region
if scene_extent:
grass.use_temp_region() # safely modify the region
msg = "\n|! Matching region extent to map {name}"
# ToDo: check if extent-B10 == extent-B11? Unnecessary?
# Improve below!
if b10:
run('g.region', rast=b10, align=b10)
msg = msg.format(name=b10)
elif t10:
run('g.region', rast=t10, align=t10)
msg = msg.format(name=t10)
g.message(msg)
elif scene_extent:
grass.warning(_('Operating on current region'))
#
# 1. Mask clouds
#
if cloud_map:
# user-fed cloud map?
msg = '\n|i Using {cmap} as a MASK'.format(cmap=cloud_map)
g.message(msg)
r.mask(raster=cloud_map, flags='i', overwrite=True)
else:
# using the quality assessment band and a "QA" pixel value
mask_clouds(qab, qapixel)
#
# 2. TIRS > Brightness Temperatures
#
if mtl_file:
# if MTL and b10 given, use it to compute at-satellite temperature t10
if b10:
# convert DNs to at-satellite temperatures
t10 = tirs_to_at_satellite_temperature(b10, mtl_file)
# likewise for b11 -> t11
if b11:
# convert DNs to at-satellite temperatures
t11 = tirs_to_at_satellite_temperature(b11, mtl_file)
#
# Initialise a SplitWindowLST object
#
split_window_lst = SplitWindowLST(emissivity_class)
citation_lst = split_window_lst.citation
#
# 3. Land Surface Emissivities
#
# use given fixed class?
if emissivity_class:
if split_window_lst.landcover_class is False:
# replace with meaningful error
g.warning('Unknown land cover class string! Note, this string '
'input option is case sensitive.')
if emissivity_class == 'Random':
msg = "\n|! Random emissivity class selected > " + \
split_window_lst.landcover_class + ' '
else:
msg = '\n|! Retrieving average emissivities *only* for {eclass} '
if info:
msg += '| Average emissivities (channels 10, 11): '
msg += str(split_window_lst.emissivity_t10) + ', ' + \
str(split_window_lst.emissivity_t11)
msg = msg.format(eclass=split_window_lst.landcover_class)
g.message(msg)
# use the FROM-GLC map
elif landcover_map:
if average_emissivity_map:
tmp_avg_lse = average_emissivity_map
if not average_emissivity_map:
determine_average_emissivity(tmp_avg_lse, landcover_map,
split_window_lst.average_lse_mapcalc)
if options['emissivity_out']:
tmp_avg_lse = options['emissivity_out']
if delta_emissivity_map:
tmp_delta_lse = delta_emissivity_map
if not delta_emissivity_map:
determine_delta_emissivity(tmp_delta_lse, landcover_map,
split_window_lst.delta_lse_mapcalc)
if options['delta_emissivity_out']:
tmp_delta_lse = options['delta_emissivity_out']
#
# 4. Modified Split-Window Variance-Covariance Matrix > Column Water Vapor
#
if info:
msg = '\n|i Spatial window of size {n} for Column Water Vapor estimation: '
msg = msg.format(n=cwv_window_size)
g.message(msg)
cwv = Column_Water_Vapor(cwv_window_size, t10, t11)
citation_cwv = cwv.citation
estimate_cwv_big_expression(tmp_cwv, t10, t11, cwv._big_cwv_expression())
if cwv_output:
tmp_cwv = cwv_output
#
# 5. Estimate Land Surface Temperature
#
if info and emissivity_class == 'Random':
msg = '\n|* Will pick a random emissivity class!'
grass.verbose(msg)
estimate_lst(lst_output, t10, t11,
tmp_avg_lse, tmp_delta_lse, tmp_cwv,
split_window_lst.sw_lst_mapcalc)
#
# Post-production actions
#
# remove MASK
r.mask(flags='r', verbose=True)
# time-stamping
if timestamping:
add_timestamp(mtl_file, lst_output)
if cwv_output:
add_timestamp(mtl_file, cwv_output)
# Apply color table
if celsius:
run('r.colors', map=lst_output, color='celsius')
else:
# color table for kelvin
run('r.colors', map=lst_output, color='kelvin')
# ToDo: helper function for r.support
# strings for metadata
history_lst = '\n' + citation_lst
history_lst += '\n\n' + citation_cwv
history_lst += '\n\nSplit-Window model: '
history_lst += split_window_lst._equation # :wsw_lst_mapcalc
description_lst = ('Land Surface Temperature derived from a split-window algorithm. ')
if celsius:
title_lst = 'Land Surface Temperature (C)'
units_lst = 'Celsius'
else:
title_lst = 'Land Surface Temperature (K)'
units_lst = 'Kelvin'
landsat8_metadata = Landsat8_MTL(mtl_file)
source1_lst = landsat8_metadata.scene_id
source2_lst = landsat8_metadata.origin
# history entry
run("r.support", map=lst_output, title=title_lst,
units=units_lst, description=description_lst,
source1=source1_lst, source2=source2_lst,
history=history_lst)
# (re)name the LST product
#run("g.rename", rast=(tmp_lst, lst_output))
# restore region
if scene_extent:
grass.del_temp_region() # restoring previous region settings
g.message("|! Original Region restored")
# print citation
if info:
print '\nSource: ' + citation_lst
def main():
pan = options['pan']
msxlst = options['msx'].split(',')
outputsuffix = options['suffix']
custom_ratio = options['ratio']
center = options['center']
center2 = options['center2']
modulation = options['modulation']
modulation2 = options['modulation2']
if options['trim']:
trimming_factor = float(options['trim'])
else:
trimming_factor = False
histogram_match = flags['l']
second_pass = flags['2']
color_match = flags['c']
# # Check & warn user about "ns == ew" resolution of current region ======
# region = grass.region()
# nsr = region['nsres']
# ewr = region['ewres']
#
# if nsr != ewr:
# msg = ('>>> Region's North:South ({ns}) and East:West ({ew}) '
# 'resolutions do not match!')
# msg = msg.format(ns=nsr, ew=ewr)
# g.message(msg, flags='w')
mapset = grass.gisenv()['MAPSET'] # Current Mapset?
region = grass.region() # and region settings
# List images and their properties
imglst = [pan]
imglst.extend(msxlst) # List of input imagery
images = {}
for img in imglst: # Retrieving Image Info
images[img] = Info(img, mapset)
images[img].read()
panres = images[pan].nsres # Panchromatic resolution
grass.use_temp_region() # to safely modify the region
run('g.region', res=panres) # Respect extent, change resolution
g.message("|! Region's resolution matched to Pan's ({p})".format(p=panres))
# Loop Algorithm over Multi-Spectral images
for msx in msxlst:
g.message("\nProcessing image: {m}".format(m=msx))
# Tracking command history -- Why don't do this all r.* modules?
cmd_history = []
#
# 1. Compute Ratio
#
g.message("\n|1 Determining ratio of low to high resolution")
# Custom Ratio? Skip standard computation method.
if custom_ratio:
ratio = float(custom_ratio)
g.message('Using custom ratio, overriding standard method!',
flags='w')
# Multi-Spectral resolution(s), multiple
else:
# Image resolutions
g.message(" > Retrieving image resolutions")
msxres = images[msx].nsres
# check
if panres == msxres:
msg = ("The Panchromatic's image resolution ({pr}) "
"equals to the Multi-Spectral's one ({mr}). "
"Something is probably not right! "
"Please check your input images.")
msg = msg.format(pr=panres, mr=msxres)
grass.fatal(_(msg))
# compute ratio
ratio = msxres / panres
msg_ratio = (' >> Resolution ratio '
'low ({m:.{dec}f}) to high ({p:.{dec}f}): {r:.1f}')
msg_ratio = msg_ratio.format(m=msxres, p=panres, r=ratio, dec=3)
g.message(msg_ratio)
# 2nd Pass requested, yet Ratio < 5.5
if second_pass and ratio < 5.5:
g.message(" >>> Resolution ratio < 5.5, skipping 2nd pass.\n"
" >>> If you insist, force it via the <ratio> option!",
flags='i')
second_pass = bool(0)
#
# 2. High Pass Filtering
#
g.message('\n|2 High Pass Filtering the Panchromatic Image')
tmpfile = grass.tempfile() # Temporary file - replace with os.getpid?
tmp = 'tmp.' + grass.basename(tmpfile) # use its basenam
tmp_pan_hpf = '{tmp}_pan_hpf'.format(tmp=tmp) # HPF image
tmp_msx_blnr = '{tmp}_msx_blnr'.format(tmp=tmp) # Upsampled MSx
tmp_msx_hpf = '{tmp}_msx_hpf'.format(tmp=tmp) # Fused image
tmp_hpf_matrix = grass.tempfile() # ASCII filter
# Construct and apply Filter
hpf = get_high_pass_filter(ratio, center)
hpf_ascii(center, hpf, tmp_hpf_matrix, second_pass)
run('r.mfilter', input=pan, filter=tmp_hpf_matrix,
output=tmp_pan_hpf,
title='High Pass Filtered Panchromatic image',
overwrite=True)
# 2nd pass
if second_pass and ratio > 5.5:
# Temporary files
tmp_pan_hpf_2 = '{tmp}_pan_hpf_2'.format(tmp=tmp) # 2nd Pass HPF image
tmp_hpf_matrix_2 = grass.tempfile() # 2nd Pass ASCII filter
# Construct and apply 2nd Filter
hpf_2 = get_high_pass_filter(ratio, center2)
hpf_ascii(center2, hpf_2, tmp_hpf_matrix_2, second_pass)
run('r.mfilter',
input=pan,
filter=tmp_hpf_matrix_2,
output=tmp_pan_hpf_2,
title='2-High-Pass Filtered Panchromatic Image',
overwrite=True)
#
# 3. Upsampling low resolution image
#
g.message("\n|3 Upsampling (bilinearly) low resolution image")
run('r.resamp.interp',
method='bilinear', input=msx, output=tmp_msx_blnr, overwrite=True)
#
# 4. Weighting the High Pass Filtered image(s)
#
g.message("\n|4 Weighting the High-Pass-Filtered image (HPFi)")
# Compute (1st Pass) Weighting
msg_w = " > Weighting = StdDev(MSx) / StdDev(HPFi) * " \
"Modulating Factor"
g.message(msg_w)
# StdDev of Multi-Spectral Image(s)
msx_avg = avg(msx)
msx_sd = stddev(msx)
g.message(" >> StdDev of <{m}>: {sd:.3f}".format(m=msx, sd=msx_sd))
# StdDev of HPF Image
hpf_sd = stddev(tmp_pan_hpf)
g.message(" >> StdDev of HPFi: {sd:.3f}".format(sd=hpf_sd))
# Modulating factor
modulator = get_modulator_factor(modulation, ratio)
g.message(" >> Modulating Factor: {m:.2f}".format(m=modulator))
# weighting HPFi
weighting = hpf_weight(msx_sd, hpf_sd, modulator, 1)
#
# 5. Adding weighted HPF image to upsampled Multi-Spectral band
#
g.message("\n|5 Adding weighted HPFi to upsampled image")
fusion = '{hpf} = {msx} + {pan} * {wgt}'
fusion = fusion.format(hpf=tmp_msx_hpf, msx=tmp_msx_blnr,
pan=tmp_pan_hpf, wgt=weighting)
grass.mapcalc(fusion)
# command history
hst = 'Weigthing applied: {msd:.3f} / {hsd:.3f} * {mod:.3f}'
cmd_history.append(hst.format(msd=msx_sd, hsd=hpf_sd, mod=modulator))
if second_pass and ratio > 5.5:
#
# 4+ 2nd Pass Weighting the High Pass Filtered image
#
g.message("\n|4+ 2nd Pass Weighting the HPFi")
# StdDev of HPF Image #2
hpf_2_sd = stddev(tmp_pan_hpf_2)
g.message(" >> StdDev of 2nd HPFi: {h:.3f}".format(h=hpf_2_sd))
# Modulating factor #2
modulator_2 = get_modulator_factor2(modulation2)
msg = ' >> 2nd Pass Modulating Factor: {m:.2f}'
g.message(msg.format(m=modulator_2))
# 2nd Pass weighting
weighting_2 = hpf_weight(msx_sd, hpf_2_sd, modulator_2, 2)
#
# 5+ Adding weighted HPF image to upsampled Multi-Spectral band
#
g.message("\n|5+ Adding small-kernel-based weighted 2nd HPFi "
"back to fused image")
add_back = '{final} = {msx_hpf} + {pan_hpf} * {wgt}'
add_back = add_back.format(final=tmp_msx_hpf, msx_hpf=tmp_msx_hpf,
pan_hpf=tmp_pan_hpf_2, wgt=weighting_2)
grass.mapcalc(add_back)
# 2nd Pass history entry
hst = "2nd Pass Weighting: {m:.3f} / {h:.3f} * {mod:.3f}"
cmd_history.append(hst.format(m=msx_sd, h=hpf_2_sd, mod=modulator_2))
if color_match:
g.message("\n|* Matching output to input color table")
run('r.colors', map=tmp_msx_hpf, raster=msx)
#
# 6. Stretching linearly the HPF-Sharpened image(s) to match the Mean
# and Standard Deviation of the input Multi-Sectral image(s)
#
if histogram_match:
# adapt output StdDev and Mean to the input(ted) ones
g.message("\n|+ Matching histogram of Pansharpened image "
"to %s" % (msx), flags='v')
# Collect stats for linear histogram matching
msx_hpf_avg = avg(tmp_msx_hpf)
msx_hpf_sd = stddev(tmp_msx_hpf)
# expression for mapcalc
lhm = '{out} = ({hpf} - {hpfavg}) / {hpfsd} * {msxsd} + {msxavg}'
lhm = lhm.format(out=tmp_msx_hpf, hpf=tmp_msx_hpf,
hpfavg=msx_hpf_avg, hpfsd=msx_hpf_sd,
msxsd=msx_sd, msxavg=msx_avg)
# compute
grass.mapcalc(lhm, quiet=True, overwrite=True)
# update history string
cmd_history.append("Linear Histogram Matching: %s" % lhm)
#
# Optional. Trim to remove black border effect (rectangular only)
#
if trimming_factor:
tf = trimming_factor
# communicate
msg = '\n|* Trimming output image border pixels by '
msg += '{factor} times the low resolution\n'.format(factor=tf)
nsew = ' > Input extent: n: {n}, s: {s}, e: {e}, w: {w}'
nsew = nsew.format(n=region.n, s=region.s, e=region.e, w=region.w)
msg += nsew
g.message(msg)
# re-set borders
region.n -= tf * images[msx].nsres
region.s += tf * images[msx].nsres
region.e -= tf * images[msx].ewres
region.w += tf * images[msx].ewres
# communicate and act
msg = ' > Output extent: n: {n}, s: {s}, e: {e}, w: {w}'
msg = msg.format(n=region.n, s=region.s, e=region.e, w=region.w)
g.message(msg)
# modify only the extent
run('g.region',
n=region.n, s=region.s, e=region.e, w=region.w)
trim = "{out} = {input}".format(out=tmp_msx_hpf, input=tmp_msx_hpf)
grass.mapcalc(trim)
#
# End of Algorithm
# history entry
run("r.support", map=tmp_msx_hpf, history="\n".join(cmd_history))
# add suffix to basename & rename end product
msx_name = "{base}.{suffix}"
msx_name = msx_name.format(base=msx.split('@')[0], suffix=outputsuffix)
run("g.rename", raster=(tmp_msx_hpf, msx_name))
# remove temporary files
cleanup()
# visualising-related information
grass.del_temp_region() # restoring previous region settings
g.message("\n|! Original Region restored")
g.message("\n>>> Hint, rebalancing colors (via i.colors.enhance) "
"may improve appearance of RGB composites!",
flags='i')
def main():
global acq_time, esd
"""1st, get input, output, options and flags"""
spectral_bands = options['band'].split(',')
outputsuffix = options['outputsuffix']
utc = options['utc']
doy = options['doy']
sea = options['sea']
radiance = flags['r']
if radiance and outputsuffix == 'toar':
outputsuffix = 'rad'
g.message("Output-suffix set to %s" % outputsuffix)
keep_region = flags['k']
info = flags['i']
# -----------------------------------------------------------------------
# Equations
# -----------------------------------------------------------------------
if info:
# conversion to Radiance based on (1)
msg = "|i Spectral Radiance = K * DN / Effective Bandwidth | " \
"Reflectance = ( Pi * Radiance * ESD^2 ) / BAND_Esun * cos(SZA)"
g.message(msg)
# -----------------------------------------------------------------------
# List images and their properties
# -----------------------------------------------------------------------
mapset = grass.gisenv()['MAPSET'] # Current Mapset?
# imglst = [pan]
# imglst.extend(msxlst) # List of input imagery
images = {}
for img in spectral_bands: # Retrieving Image Info
images[img] = Info(img, mapset)
images[img].read()
# -----------------------------------------------------------------------
# Temporary Region and Files
# -----------------------------------------------------------------------
if not keep_region:
grass.use_temp_region() # to safely modify the region
tmpfile = grass.tempfile() # Temporary file - replace with os.getpid?
tmp = "tmp." + grass.basename(tmpfile) # use its basename
# -----------------------------------------------------------------------
# Global Metadata: Earth-Sun distance, Sun Zenith Angle
# -----------------------------------------------------------------------
# Earth-Sun distance
if doy:
g.message("|! Using Day of Year to calculate Earth-Sun distance.")
esd = jd_to_esd(int(doy))
elif (not doy) and utc:
acq_utc = AcquisitionTime(utc) # will hold esd (earth-sun distance)
esd = acq_utc.esd
else:
grass.fatal(_("Either the UTC string or "
"the Day-of-Year (doy) are required!"))
sza = 90 - float(sea) # Sun Zenith Angle based on Sun Elevation Angle
# -----------------------------------------------------------------------
# Loop processing over all bands
# -----------------------------------------------------------------------
for band in spectral_bands:
global tmp_rad
# -------------------------------------------------------------------
# Match bands region if... ?
# -------------------------------------------------------------------
if not keep_region:
run('g.region', rast=band) # ## FixMe?
msg = "\n|! Region matching the %s spectral band" % band
g.message(msg)
elif keep_region:
msg = "|! Operating on current region"
g.message(msg)
# -------------------------------------------------------------------
# Band dependent metadata for Spectral Radiance
# -------------------------------------------------------------------
g.message("\n|* Processing the %s band" % band, flags='i')
# Why is this necessary? Any function to remove the mapsets name?
if '@' in band:
band = (band.split('@')[0])
# get absolute calibration factor
acf = float(CF_BW_ESUN[band][2])
acf_msg = "K=" + str(acf)
# effective bandwidth
bw = float(CF_BW_ESUN[band][0])
# -------------------------------------------------------------------
# Converting to Spectral Radiance
# -------------------------------------------------------------------
msg = "\n|> Converting to Spectral Radiance " \
"| Conversion Factor %s, Bandwidth=%.3f" % (acf_msg, bw)
g.message(msg)
# convert
tmp_rad = "%s.Radiance" % tmp # Temporary Map
rad = "%s = %f * %s / %f" \
% (tmp_rad, acf, band, bw) # Attention: 32-bit calculations requ.
grass.mapcalc(rad, overwrite=True)
# strings for metadata
history_rad = rad
history_rad += "Conversion Factor=%f; Effective Bandwidth=%.3f" \
% (acf, bw)
title_rad = ""
description_rad = "Top-of-Atmosphere %s band spectral Radiance " \
"[W/m^2/sr/μm]" % band
units_rad = "W / sq.m. / μm / ster"
if not radiance:
# ---------------------------------------------------------------
# Converting to Top-of-Atmosphere Reflectance
# ---------------------------------------------------------------
global tmp_toar
msg = "\n|> Converting to Top-of-Atmosphere Reflectance"
g.message(msg)
esun = float(CF_BW_ESUN[band][1])
msg = " %s band mean solar exoatmospheric irradiance=%.2f" \
% (band, esun)
g.message(msg)
# convert
tmp_toar = "%s.Reflectance" % tmp # Spectral Reflectance
toar = "%s = %f * %s * %f^2 / %f * cos(%f)" \
% (tmp_toar, math.pi, tmp_rad, esd, esun, sza)
grass.mapcalc(toar, overwrite=True)
# report range? Using a flag and skip actual conversion?
# todo?
# strings for metadata
title_toar = "%s band (Top of Atmosphere Reflectance)" % band
description_toar = "Top of Atmosphere %s band spectral Reflectance" \
% band
units_toar = "Unitless planetary reflectance"
history_toar = "K=%f; Bandwidth=%.1f; ESD=%f; Esun=%.2f; SZA=%.1f" \
% (acf, bw, esd, esun, sza)
if tmp_toar:
# history entry
run("r.support", map=tmp_toar, title=title_toar,
units=units_toar, description=description_toar,
source1=source1_toar, source2=source2_toar,
history=history_toar)
# add suffix to basename & rename end product
toar_name = ("%s.%s" % (band.split('@')[0], outputsuffix))
run("g.rename", rast=(tmp_toar, toar_name))
elif tmp_rad:
# history entry
run("r.support", map=tmp_rad,
title=title_rad, units=units_rad, description=description_rad,
source1=source1_rad, source2=source2_rad, history=history_rad)
# add suffix to basename & rename end product
rad_name = ("%s.%s" % (band.split('@')[0], outputsuffix))
run("g.rename", rast=(tmp_rad, rad_name))
# visualising-related information
if not keep_region:
grass.del_temp_region() # restoring previous region settings
g.message("\n|! Region's resolution restored!")
g.message("\n>>> Hint: rebalancing colors "
"(i.colors.enhance) may improve appearance of RGB composites!",
flags='i')
def main():
global TMPLOC, SRCGISRC, GISDBASE, TMP_REG_NAME
GDALdatasource = options['input']
output = options['output']
method = options['resample']
memory = options['memory']
bands = options['band']
tgtres = options['resolution']
title = options["title"]
if options['resolution_value']:
if tgtres != 'value':
grass.fatal(_("To set custom resolution value, select 'value' in resolution option"))
tgtres_value = float(options['resolution_value'])
if tgtres_value <= 0:
grass.fatal(_("Resolution value can't be smaller than 0"))
elif tgtres == 'value':
grass.fatal(_("Please provide the resolution for the imported dataset or change to 'estimated' resolution"))
grassenv = grass.gisenv()
tgtloc = grassenv['LOCATION_NAME']
tgtmapset = grassenv['MAPSET']
GISDBASE = grassenv['GISDBASE']
tgtgisrc = os.environ['GISRC']
SRCGISRC = grass.tempfile()
TMPLOC = 'temp_import_location_' + str(os.getpid())
f = open(SRCGISRC, 'w')
f.write('MAPSET: PERMANENT\n')
f.write('GISDBASE: %s\n' % GISDBASE)
f.write('LOCATION_NAME: %s\n' % TMPLOC)
f.write('GUI: text\n')
f.close()
tgtsrs = grass.read_command('g.proj', flags='j', quiet=True)
# create temp location from input without import
grass.verbose(_("Creating temporary location for <%s>...") % GDALdatasource)
parameters = dict(input=GDALdatasource, output=output,
memory=memory, flags='c', title=title,
location=TMPLOC, quiet=True)
if bands:
parameters['band'] = bands
try:
grass.run_command('r.in.gdal', **parameters)
except CalledModuleError:
grass.fatal(_("Unable to read GDAL dataset <%s>") % GDALdatasource)
# switch to temp location
os.environ['GISRC'] = str(SRCGISRC)
# switch to target location
os.environ['GISRC'] = str(tgtgisrc)
# try r.in.gdal directly first
additional_flags = 'l' if flags['l'] else ''
if flags['o']:
additional_flags += 'o'
if flags['o'] or grass.run_command('r.in.gdal', input=GDALdatasource, flags='j',
errors='status', quiet=True) == 0:
parameters = dict(input=GDALdatasource, output=output,
memory=memory, flags='k' + additional_flags)
if bands:
parameters['band'] = bands
try:
grass.run_command('r.in.gdal', **parameters)
grass.verbose(_("Input <%s> successfully imported without reprojection") % GDALdatasource)
return 0
except CalledModuleError as e:
grass.fatal(_("Unable to import GDAL dataset <%s>") % GDALdatasource)
# make sure target is not xy
if grass.parse_command('g.proj', flags='g')['name'] == 'xy_location_unprojected':
grass.fatal(_("Coordinate reference system not available for current location <%s>") % tgtloc)
# switch to temp location
os.environ['GISRC'] = str(SRCGISRC)
# make sure input is not xy
if grass.parse_command('g.proj', flags='g')['name'] == 'xy_location_unprojected':
grass.fatal(_("Coordinate reference system not available for input <%s>") % GDALdatasource)
# import into temp location
grass.verbose(_("Importing <%s> to temporary location...") % GDALdatasource)
parameters = dict(input=GDALdatasource, output=output,
memory=memory, flags='k' + additional_flags)
if bands:
parameters['band'] = bands
try:
grass.run_command('r.in.gdal', **parameters)
except CalledModuleError:
grass.fatal(_("Unable to import GDAL dataset <%s>") % GDALdatasource)
outfiles = grass.list_grouped('raster')['PERMANENT']
# is output a group?
group = False
path = os.path.join(GISDBASE, TMPLOC, 'group', output)
if os.path.exists(path):
group = True
path = os.path.join(GISDBASE, TMPLOC, 'group', output, 'POINTS')
if os.path.exists(path):
grass.fatal(_("Input contains GCPs, rectification is required"))
# switch to target location
os.environ['GISRC'] = str(tgtgisrc)
region = grass.region()
rflags = None
if flags['n']:
rflags = 'n'
for outfile in outfiles:
n = region['n']
s = region['s']
e = region['e']
w = region['w']
grass.use_temp_region()
if options['extent'] == 'input':
# r.proj -g
try:
tgtextents = grass.read_command('r.proj', location=TMPLOC,
mapset='PERMANENT',
input=outfile, flags='g',
memory=memory, quiet=True)
except CalledModuleError:
grass.fatal(_("Unable to get reprojected map extent"))
try:
srcregion = grass.parse_key_val(tgtextents, val_type=float, vsep=' ')
n = srcregion['n']
s = srcregion['s']
e = srcregion['e']
w = srcregion['w']
except ValueError: # import into latlong, expect 53:39:06.894826N
srcregion = grass.parse_key_val(tgtextents, vsep=' ')
n = grass.float_or_dms(srcregion['n'][:-1]) * \
(-1 if srcregion['n'][-1] == 'S' else 1)
s = grass.float_or_dms(srcregion['s'][:-1]) * \
(-1 if srcregion['s'][-1] == 'S' else 1)
e = grass.float_or_dms(srcregion['e'][:-1]) * \
(-1 if srcregion['e'][-1] == 'W' else 1)
w = grass.float_or_dms(srcregion['w'][:-1]) * \
(-1 if srcregion['w'][-1] == 'W' else 1)
grass.run_command('g.region', n=n, s=s, e=e, w=w)
# v.in.region in tgt
vreg = TMP_REG_NAME = 'vreg_tmp_' + str(os.getpid())
grass.run_command('v.in.region', output=vreg, quiet=True)
grass.del_temp_region()
# reproject to src
# switch to temp location
os.environ['GISRC'] = str(SRCGISRC)
try:
grass.run_command('v.proj', input=vreg, output=vreg,
location=tgtloc, mapset=tgtmapset, quiet=True)
except CalledModuleError:
grass.fatal(_("Unable to reproject to source location"))
# set region from region vector
grass.run_command('g.region', raster=outfile)
grass.run_command('g.region', vector=vreg)
# align to first band
grass.run_command('g.region', align=outfile)
# get number of cells
cells = grass.region()['cells']
estres = math.sqrt((n - s) * (e - w) / cells)
# remove from source location for multi bands import
grass.run_command('g.remove', type='vector', name=vreg,
flags='f', quiet=True)
os.environ['GISRC'] = str(tgtgisrc)
grass.run_command('g.remove', type='vector', name=vreg,
flags='f', quiet=True)
grass.message(_("Estimated target resolution for input band <{out}>: {res}").format(out=outfile, res=estres))
if flags['e']:
continue
if options['extent'] == 'input':
grass.use_temp_region()
grass.run_command('g.region', n=n, s=s, e=e, w=w)
res = None
if tgtres == 'estimated':
res = estres
elif tgtres == 'value':
res = tgtres_value
grass.message(_("Using given resolution for input band <{out}>: {res}").format(out=outfile, res=res))
# align to requested resolution
grass.run_command('g.region', res=res, flags='a')
else:
curr_reg = grass.region()
grass.message(_("Using current region resolution for input band "
"<{out}>: nsres={ns}, ewres={ew}").format(out=outfile, ns=curr_reg['nsres'],
ew=curr_reg['ewres']))
# r.proj
grass.message(_("Reprojecting <%s>...") % outfile)
try:
grass.run_command('r.proj', location=TMPLOC,
mapset='PERMANENT', input=outfile,
method=method, resolution=res,
memory=memory, flags=rflags, quiet=True)
except CalledModuleError:
grass.fatal(_("Unable to to reproject raster <%s>") % outfile)
if grass.raster_info(outfile)['min'] is None:
grass.fatal(_("The reprojected raster <%s> is empty") % outfile)
if options['extent'] == 'input':
grass.del_temp_region()
if flags['e']:
return 0
if group:
grass.run_command('i.group', group=output, input=','.join(outfiles))
# TODO: write metadata with r.support
return 0
def main():
global usermask, mapset, tmp_rmaps, tmp_vmaps
input = options['input']
output = options['output']
tension = options['tension']
smooth = options['smooth']
method = options['method']
edge = int(options['edge'])
segmax = int(options['segmax'])
npmin = int(options['npmin'])
quiet = True # FIXME
mapset = grass.gisenv()['MAPSET']
unique = str(os.getpid()) # Shouldn't we use temp name?
prefix = 'r_fillnulls_%s_' % unique
failed_list = list() # a list of failed holes. Caused by issues with v.surf.rst. Connected with #1813
#check if input file exists
if not grass.find_file(input)['file']:
grass.fatal(_("Raster map <%s> not found") % input)
# save original region
reg_org = grass.region()
# check if a MASK is already present
# and remove it to not interfere with NULL lookup part
# as we don't fill MASKed parts!
if grass.find_file('MASK', mapset = mapset)['file']:
usermask = "usermask_mask." + unique
grass.message(_("A user raster mask (MASK) is present. Saving it..."))
grass.run_command('g.rename', quiet = quiet, rast = ('MASK',usermask))
#check if method is rst to use v.surf.rst
if method == 'rst':
# idea: filter all NULLS and grow that area(s) by 3 pixel, then
# interpolate from these surrounding 3 pixel edge
filling = prefix + 'filled'
grass.use_temp_region()
grass.run_command('g.region', align = input, quiet = quiet)
region = grass.region()
ns_res = region['nsres']
ew_res = region['ewres']
grass.message(_("Using RST interpolation..."))
grass.message(_("Locating and isolating NULL areas..."))
# creating binary (0/1) map
if usermask:
grass.message(_("Skipping masked raster parts"))
grass.mapcalc("$tmp1 = if(isnull($input) && !($mask == 0 || isnull($mask)),1,null())",
tmp1 = prefix + 'nulls', input = input, mask = usermask)
else:
grass.mapcalc("$tmp1 = if(isnull($input),1,null())",
tmp1 = prefix + 'nulls', input = input)
tmp_rmaps.append(prefix + 'nulls')
# restoring user's mask, if present
# to ignore MASKed original values
if usermask:
grass.message(_("Restoring user mask (MASK)..."))
if grass.run_command('g.rename', quiet = quiet, rast = (usermask, 'MASK')) != 0:
grass.warning(_("Failed to restore user MASK!"))
usermask = None
# grow identified holes by X pixels
grass.message(_("Growing NULL areas"))
tmp_rmaps.append(prefix + 'grown')
if grass.run_command('r.grow', input = prefix + 'nulls', radius = edge + 0.01,
old = 1, new = 1, out = prefix + 'grown', quiet = quiet) != 0:
grass.fatal(_("abandoned. Removing temporary map, restoring user mask if needed:"))
# assign unique IDs to each hole or hole system (holes closer than edge distance)
grass.message(_("Assigning IDs to NULL areas"))
tmp_rmaps.append(prefix + 'clumped')
if grass.run_command('r.clump', input = prefix + 'grown', output = prefix + 'clumped', quiet = quiet) != 0:
grass.fatal(_("abandoned. Removing temporary map, restoring user mask if needed:"))
# get a list of unique hole cat's
grass.mapcalc("$out = if(isnull($inp), null(), $clumped)",
out = prefix + 'holes', inp = prefix + 'nulls', clumped = prefix + 'clumped')
tmp_rmaps.append(prefix + 'holes')
# use new IDs to identify holes
if grass.run_command('r.to.vect', flags = 'v', input = prefix + 'holes', output = prefix + 'holes',
type = 'area', quiet = quiet) != 0:
grass.fatal(_("abandoned. Removing temporary maps, restoring user mask if needed:"))
tmp_vmaps.append(prefix + 'holes')
# get a list of unique hole cat's
cats_file_name = grass.tempfile(False)
grass.run_command('v.db.select', flags = 'c', map = prefix + 'holes', columns = 'cat', file = cats_file_name, quiet = quiet)
cat_list = list()
cats_file = file(cats_file_name)
for line in cats_file:
cat_list.append(line.rstrip('\n'))
cats_file.close()
os.remove(cats_file_name)
if len(cat_list) < 1:
grass.fatal(_("Input map has no holes. Check region settings."))
# GTC Hole is NULL area in a raster map
grass.message(_("Processing %d map holes") % len(cat_list))
first = True
hole_n = 1
for cat in cat_list:
holename = prefix + 'hole_' + cat
# GTC Hole is a NULL area in a raster map
grass.message(_("Filling hole %s of %s") % (hole_n, len(cat_list)))
hole_n = hole_n + 1
# cut out only CAT hole for processing
if grass.run_command('v.extract', input = prefix + 'holes', output = holename + '_pol',
cats = cat, quiet = quiet) != 0:
grass.fatal(_("abandoned. Removing temporary maps, restoring user mask if needed:"))
tmp_vmaps.append(holename + '_pol')
# zoom to specific hole with a buffer of two cells around the hole to remove rest of data
if grass.run_command('g.region', vect = holename + '_pol', align = input,
w = 'w-%d' % (edge * 2 * ew_res), e = 'e+%d' % (edge * 2 * ew_res),
n = 'n+%d' % (edge * 2 * ns_res), s = 's-%d' % (edge * 2 * ns_res),
quiet = quiet) != 0:
grass.fatal(_("abandoned. Removing temporary maps, restoring user mask if needed:"))
# remove temporary map to not overfill disk
if grass.run_command('g.remove', flags = 'fb', type = 'vect', pattern = holename + '_pol', quiet = quiet) != 0:
grass.fatal(_("abandoned. Removing temporary maps, restoring user mask if needed:"))
tmp_vmaps.remove(holename + '_pol')
# copy only data around hole
grass.mapcalc("$out = if($inp == $catn, $inp, null())",
out = holename, inp = prefix + 'holes', catn = cat)
tmp_rmaps.append(holename)
# If here loop is split into two, next part of loop can be run in parallel
# (except final result patching)
# Downside - on large maps such approach causes large disk usage
# grow hole border to get it's edge area
tmp_rmaps.append(holename + '_grown')
if grass.run_command('r.grow', input = holename, radius = edge + 0.01,
old = -1, out = holename + '_grown', quiet = quiet) != 0:
grass.fatal(_("abandoned. Removing temporary map, restoring user mask if needed:"))
# no idea why r.grow old=-1 doesn't replace existing values with NULL
grass.mapcalc("$out = if($inp == -1, null(), $dem)",
out = holename + '_edges', inp = holename + '_grown', dem = input)
tmp_rmaps.append(holename + '_edges')
# convert to points for interpolation
tmp_vmaps.append(holename)
if grass.run_command('r.to.vect', input = holename + '_edges', output = holename,
type = 'point', flags = 'z', quiet = quiet) != 0:
grass.fatal(_("abandoned. Removing temporary maps, restoring user mask if needed:"))
# count number of points to control segmax parameter for interpolation:
pointsnumber = grass.vector_info_topo(map = holename)['points']
grass.verbose(_("Interpolating %d points") % pointsnumber)
if pointsnumber < 2:
grass.verbose(_("No points to interpolate"))
failed_list.append(holename)
continue
# Avoid v.surf.rst warnings
if pointsnumber < segmax:
npmin = pointsnumber + 1
segmax = pointsnumber
# launch v.surf.rst
tmp_rmaps.append(holename + '_dem')
if grass.run_command('v.surf.rst', quiet = quiet, input = holename, elev = holename + '_dem',
tension = tension, smooth = smooth,
segmax = segmax, npmin = npmin) != 0:
# GTC Hole is NULL area in a raster map
grass.fatal(_("Failed to fill hole %s") % cat)
# v.surf.rst sometimes fails with exit code 0
# related bug #1813
if not grass.find_file(holename + '_dem')['file']:
try:
tmp_rmaps.remove(holename)
tmp_rmaps.remove(holename + '_grown')
tmp_rmaps.remove(holename + '_edges')
tmp_rmaps.remove(holename + '_dem')
tmp_vmaps.remove(holename)
except:
pass
grass.warning(_("Filling has failed silently. Leaving temporary maps with prefix <%s> for debugging.") % holename)
failed_list.append(holename)
continue
# append hole result to interpolated version later used to patch into original DEM
if first:
tmp_rmaps.append(filling)
grass.run_command('g.region', align = input, rast = holename + '_dem', quiet = quiet)
grass.mapcalc("$out = if(isnull($inp), null(), $dem)",
out = filling, inp = holename, dem = holename + '_dem')
first = False
else:
tmp_rmaps.append(filling + '_tmp')
grass.run_command('g.region', align = input, rast = (filling, holename + '_dem'), quiet = quiet)
grass.mapcalc("$out = if(isnull($inp), if(isnull($fill), null(), $fill), $dem)",
out = filling + '_tmp', inp = holename, dem = holename + '_dem', fill = filling)
if grass.run_command('g.rename', rast = (filling + '_tmp', filling),
overwrite = True, quiet = quiet) != 0:
grass.fatal(_("abandoned. Removing temporary maps, restoring user mask if needed:"))
tmp_rmaps.remove(filling + '_tmp') # this map has been removed. No need for later cleanup.
# remove temporary maps to not overfill disk
try:
tmp_rmaps.remove(holename)
tmp_rmaps.remove(holename + '_grown')
tmp_rmaps.remove(holename + '_edges')
tmp_rmaps.remove(holename + '_dem')
except:
pass
if grass.run_command('g.remove', quiet = quiet, flags = 'fb', type = 'rast', pattern =
(holename, holename + '_grown', holename + '_edges', holename + '_dem')) != 0:
grass.fatal(_("abandoned. Removing temporary maps, restoring user mask if needed:"))
try:
tmp_vmaps.remove(holename)
except:
pass
if grass.run_command('g.remove', quiet = quiet, flags = 'fb', type = 'vect', pattern = holename) != 0:
grass.fatal(_("abandoned. Removing temporary maps, restoring user mask if needed:"))
#check if method is different from rst to use r.resamp.bspline
if method != 'rst':
grass.message(_("Using %s bspline interpolation") % method)
# clone current region
grass.use_temp_region()
grass.run_command('g.region', align = input)
reg = grass.region()
# launch r.resamp.bspline
tmp_rmaps.append(prefix + 'filled')
if usermask:
grass.run_command('r.resamp.bspline', input = input, mask = usermask,
output = prefix + 'filled', method = method,
ew_step = 3 * reg['ewres'], ns_step = 3 * reg['nsres'],
_lambda = 0.01, flags = 'n')
else:
grass.run_command('r.resamp.bspline', input = input,
output = prefix + 'filled', method = method,
ew_step = 3 * reg['ewres'], ns_step = 3 * reg['nsres'],
_lambda = 0.01, flags = 'n')
# restoring user's mask, if present:
if usermask:
grass.message(_("Restoring user mask (MASK)..."))
if grass.run_command('g.rename', quiet = quiet, rast = (usermask, 'MASK')) != 0:
grass.warning(_("Failed to restore user MASK!"))
usermask = None
# set region to original extents, align to input
grass.run_command('g.region', n = reg_org['n'], s = reg_org['s'],
e = reg_org['e'], w = reg_org['w'], align = input)
# patch orig and fill map
grass.message(_("Patching fill data into NULL areas..."))
# we can use --o here as g.parser already checks on startup
grass.run_command('r.patch', input = (input,prefix + 'filled'), output = output, overwrite = True)
# restore the real region
grass.del_temp_region()
grass.message(_("Filled raster map is: %s") % output)
# write cmd history:
grass.raster_history(output)
if len(failed_list) > 0:
grass.warning(_("Following holes where not filled. Temporary maps with are left in place to allow examination of unfilled holes"))
outlist = failed_list[0]
for hole in failed_list[1:]:
outlist = ', ' + outlist
grass.message(outlist)
grass.message(_("Done."))
