def compute_solar_irradiation(inputFile, outputFile, day_of_year, crs='32630'):
# Define grass working set
GRASS_GISDB = 'grassdata'
GRASS_LOCATION = 'GEOPROCESSING'
GRASS_MAPSET = 'PERMANENT'
GRASS_ELEVATIONS_FILENAME = 'ELEVATIONS'
os.environ.update(dict(GRASS_COMPRESS_NULLS='1'))
# Clean previously processed data
if os.path.isdir(GRASS_GISDB):
shutil.rmtree(GRASS_GISDB)
with Session(gisdb=GRASS_GISDB,
location=GRASS_LOCATION,
mapset=GRASS_MAPSET,
create_opts='EPSG:32630') as ses:
# Set project projection to match elevation raster projection
g.proj(epsg=crs, flags='c')
# Load raster file into working directory
r.import_(input=inputFile, output=GRASS_ELEVATIONS_FILENAME, flags='o')
# Set project region to match raster region
g.region(raster=GRASS_ELEVATIONS_FILENAME, flags='s')
# Calculate solar irradiation
gscript.run_command('r.slope.aspect',
elevation=GRASS_ELEVATIONS_FILENAME,
slope='slope',
aspect='aspect')
gscript.run_command('r.sun',
elevation=GRASS_ELEVATIONS_FILENAME,
slope='slope',
aspect='aspect',
beam_rad='beam',
step=1,
day=day_of_year)
# Get extraterrestrial irradiation from history metadata
regex = re.compile(r'\d+\.\d+')
output = gscript.read_command("r.info", flags="h", map=["beam"])
splits = str(output).split('\n')
line = next(filter(lambda line: 'Extraterrestrial' in line, splits))
extraterrestrial_irradiance = float(regex.search(line)[0])
# Export generated results into a GeoTiff file
if os.path.isfile(outputFile):
os.remove(outputFile)
r.out_gdal(input='beam', output=outputFile)
return extraterrestrial_irradiance
for i, reach_no in enumerate(reaches):
# make the directory for this reach
this_dir = DataDirectory + 'Upper_Miss_reach' + str(reach_no) + '/'
try:
os.mkdir(this_dir)
except:
pass
# set the region
g.region(n=str(n[i]), s=str(s[i]), e=str(e[i]), w=str(w[i]), flags='p')
# now output the ENVI bil file
r.out_gdal(input="Upper_Miss_filled",
format="ENVI",
type="Float32",
nodata=-9999,
output=this_dir + 'Upper_Miss_reach' + str(reach_no) + '.bil')
# clip the baseline to this region
v.in_region(output='region_tmp', overwrite=True)
v.overlay(ainput='Mississippi_River',
atype='line',
binput='region_tmp',
output='Mississippi_River_clip_tmp',
operator='and',
overwrite=True)
v.out_ogr(input='Mississippi_River_clip_tmp',
output=this_dir + 'Upper_Miss_baseline_reach' + str(reach_no) +
".shp",
overwrite=True)
# Hansen bin
r.mapcalc(comm_code[i]+'_treecover_GFW_2000_deforestation_threshold'+str(tr)+'_binary = if('+comm_code[i]+'_treecover_GFW_2000_deforestation > '+str(tr)+', 1, 0)',
overwrite = True)
# remove mask and vector_cat to avoid problems
r.mask(flags = 'r')
g.remove(type = 'vector', name = 'vector_cat', flags = 'f')
#---------------------------------------
# exporting all output
# output folder
pa = r'D:\bernardo\00_academico\01_artigos\ms_Lucas_world_landscape_metrics\maps'
os.chdir(pa)
# list maps
list_maps = grass.list_grouped(type = 'raster', pattern = 'com_*')[mapset_name]
# export
for i in list_maps:
# region
g.region(raster = i)
# export
r.out_gdal(input = i, output = i + '_cgs_wgs84.tif',
createopt = 'COMPRESS=DEFLATE,TFW=YES', overwrite = True, flags = 'f')
scanNameNULL = scanName+'__NULL__'+scanNumber
scanNameShaded = scanName+'__shaded__'+scanNumber
try:
r.out_gdal(input=scanNameDEM, output=scanNameDEM+'.tif', format='GTiff', overwrite=False)
"""
# Problem with duplicates
DEMs = gscript.parse_command('g.list', type='raster', pattern='*__DEM__*').keys()
DEMs = sorted(DEMs)
for DEM in DEMs:
outname = DEM+'.tif'
if os.path.isfile(outname):
print "Not overwriting", outname
else:
print DEM
r.out_gdal(input=DEM, output=outname, format='GTiff', overwrite=False)
maps = gscript.parse_command('g.list', type='raster', pattern='*__shaded__*').keys()
maps = sorted(maps)
for mapi in maps:
outname = mapi+'.tif'
if os.path.isfile(outname):
print "Not overwriting", outname
else:
print DEM
r.out_gdal(input=mapi, output=outname, format='GTiff', overwrite=False)
# Placeholder to make these into future functions
def outputByType(self):
print "Directory " + buffer_dir + " already exists"
os.chdir(buffer_dir)
# List of raster to be exported
list_rast_export = grass.list_grouped(type='rast',
pattern='*' + ind + '*')['PERMANENT']
g.region(raster=list_rast_export, flags="ap")
# Loop to export all raster
for j in list_rast_export:
print j
r.out_gdal(input=j,
output=j + '.tif',
createopt="TFW=YES,COMPRESS=DEFLATE",
overwrite=True)
#--------------------------------------------
# Loop for all the other zones
# list maps in cgs-location
all_maps = grass.read_command('r.proj',
location='newLocation_wgs84',
mapset='variables_cut',
flags='l').replace('\r', '').split('\n')
all_regions = grass.read_command('v.proj',
location='newLocation_wgs84',
mapset='variables_cut',
flags='l').replace('\r', '').split('\n')
# NPP ext in the end
r.mapcalc(i+'_MOD17A3_Science_NPP_mean_00_15_exp = '+i+'_MOD17A3_Science_NPP_mean_00_15', overwrite = True)
# export maps
maps_exp = grass.list_grouped(type = 'raster', pattern = i+'*exp')['akde']
names = ['HFP2009', 'livestock_cattle_density', 'net_primary_productivity', 'forest_year',
'population_density', 'road_dist', 'road_density_km_per100km2', 'protected_areas',
'bio12_annual_precipitation', 'bio15_precipitation_seasonality']
names_exp = [i+'_'+nm for nm in names]
pa = r'E:\_neojaguardatabase\other_limits_cut_variables\akde\maps'
os.chdir(pa)
for mm in range(len(maps_exp)):
if 'NPP' in maps_exp[mm]:
r.out_gdal(input = maps_exp[mm], output = names_exp[mm],
createopt = 'COMPRESS=DEFLATE', overwrite = True, flags = 'f')
else:
r.out_gdal(input = maps_exp[mm], output = names_exp[mm],
createopt = 'COMPRESS=DEFLATE', overwrite = True)
# save statistics
f = open('table_akde.csv', 'a+')
f.write(ind_codmatch+';'+kern)
for mm in range(len(maps_exp)):
var = grass.parse_command('r.univar', map = maps_exp[mm], flags = 'g')
if len(var) == 0:
val = 'NA'
else:
val = var['mean'].encode("utf-8")
f.write(';'+val)
#That's mostly because I don't know how to programmatically
#rescale a float to an int
print "Recoding raster layer"
rules = "0.0:" + str(vals[-1]) + ":0:255"
#r.recode(input=raster_layer, rules=rules, output=recoded_raster_layer)
g.write_command('r.recode', input=raster_layer, rule='-', output=recoded_raster_layer, stdin=rules)
# Now, we apply our color table
# Again, we'll pipe this from stdin, but you should probably use a file.
# These rules get way more complicated, since we need multiple lines,
# but I'm still too lazy to write to a file. Also, \n's are fun.
print "Applying new color table"
color_rules = "0% blue\n33.33% green\n66.67% yellow\n100% red"
g.write_command('r.colors', map=recoded_raster_layer, rules='-', stdin=color_rules)
# Set NULL values to remove noise
# I'm doing a fairly aggressive data purge, use respnsibly
print "Nullifying nulls"
r.null(map=recoded_raster_layer, setnull="0-20")
# Finally, write it to a GeoTiff
print "Writing file: %s" % os.path.join(data_directory, output_file)
r.out_gdal(input=recoded_raster_layer,
format="GTiff",
type="Byte",
output=os.path.join(data_directory, output_file),
createopt="INTERLEAVE=PIXEL, TFW=YES, PROFILE=GeoTIFF")
# That's all folks!
print "Congrats, it is finished."
scanNameShaded = scanName+'__shaded__'+scanNumber
try:
r.out_gdal(input=scanNameDEM, output=scanNameDEM+'.tif', format='GTiff', overwrite=False)
"""
# Problem with duplicates
DEMs = gscript.parse_command('g.list', type='raster',
pattern='*__DEM__*').keys()
DEMs = sorted(DEMs)
for DEM in DEMs:
outname = DEM + '.tif'
if os.path.isfile(outname):
print "Not overwriting", outname
else:
print DEM
r.out_gdal(input=DEM, output=outname, format='GTiff', overwrite=False)
maps = gscript.parse_command('g.list', type='raster',
pattern='*__shaded__*').keys()
maps = sorted(maps)
for mapi in maps:
outname = mapi + '.tif'
if os.path.isfile(outname):
print "Not overwriting", outname
else:
print DEM
r.out_gdal(input=mapi, output=outname, format='GTiff', overwrite=False)
# Placeholder to make these into future functions
def outputByType(self):
from mower import GrassSession
DEM = "/home/mperry/projects/shortcreek/dem/dem.img"
with GrassSession(DEM) as gs:
from grass.pygrass.modules.shortcuts import raster
# Import/Link to External GDAL data
raster.external(input=DEM, output="dem")
# Perform calculations
raster.mapcalc(expression="demft=dem*3.28084")
raster.slope_aspect(elevation="demft", slope="slope", aspect="aspect")
# Export from GRASS to GDAL
from grass.pygrass.gis import Mapset
m = Mapset()
for r in m.glist('rast'):
if r == "dem":
# don't save the original
continue
raster.out_gdal(r, format="GTiff", output="/tmp/{}.tif".format(r), overwrite=True)
from mower import GrassSession
DEM = "/home/mperry/projects/shortcreek/dem/dem.img"
with GrassSession(DEM) as gs:
from grass.pygrass.modules.shortcuts import raster
# Import/Link to External GDAL data
raster.external(input=DEM, output="dem")
# Perform calculations
raster.mapcalc(expression="demft=dem*3.28084")
raster.slope_aspect(elevation="demft", slope="slope", aspect="aspect")
# Export from GRASS to GDAL
from grass.pygrass.gis import Mapset
m = Mapset()
for r in m.glist('rast'):
if r == "dem":
# don't save the original
continue
raster.out_gdal(r,
format="GTiff",
output="/tmp/{}.tif".format(r),
overwrite=True)
