def convert(self, img_file):
"""
Convert a raw GFMS image into a GeoTIFF
:param img_file: Name of raw image file from GFMS
(assumed to be in temp directory)
:return: Name of converted GeoTIFF file
"""
basename = os.path.splitext(img_file)[0]
aig_file = "{}.aig".format(basename)
tif_file = "{}.tif".format(basename)
outfile = open(os.path.join(self.tmp_dir, aig_file), "w")
infile = open(os.path.join(self.tmp_dir, img_file), "rb")
try:
coords = struct.unpack('f'*self.rows*self.cols,
infile.read(4*self.rows*self.cols))
outfile.write(self.header)
for idx, value in enumerate(coords):
outfile.write(str(value) + " ")
if (idx + 1) % 2458 == 0:
outfile.write("\n")
finally:
outfile.close()
infile.close()
gdal_translate(os.path.join(self.tmp_dir, aig_file),
os.path.join(self.tmp_dir, tif_file),
projection="EPSG:4326")
return tif_file
def convert(self, img_file):
"""
Convert a raw GFMS image into a GeoTIFF
:param img_file: Name of raw image file from GFMS
(assumed to be in temp directory)
:return: Name of converted GeoTIFF file
"""
basename = os.path.splitext(img_file)[0]
aig_file = "{}.aig".format(basename)
tif_file = "{}.tif".format(basename)
outfile = open(os.path.join(self.tmp_dir, aig_file), "w")
infile = open(os.path.join(self.tmp_dir, img_file), "rb")
try:
coords = struct.unpack('f' * self.rows * self.cols,
infile.read(4 * self.rows * self.cols))
outfile.write(self.header)
for idx, value in enumerate(coords):
outfile.write(str(value) + " ")
if (idx + 1) % 2458 == 0:
outfile.write("\n")
finally:
outfile.close()
infile.close()
gdal_translate(os.path.join(self.tmp_dir, aig_file),
os.path.join(self.tmp_dir, tif_file),
projection="EPSG:4326")
return tif_file
def extract_band(self, tif, band, outname):
outfile = os.path.join(self.tmp_dir, outname)
gdal_translate(tif,
outfile,
bands=[band],
projection='EPSG:4326',
options=['TILED=YES', 'COMPRESS=LZW'])
return outfile
def convert(self, nc_file):
tif_file = "{}.tif".format(nc_file)
nc_transform = nc_convert(os.path.join(self.tmp_dir, nc_file))
cdo_transform = cdo_invert(os.path.join(self.tmp_dir, nc_transform))
band = get_band_count(cdo_transform)
gdal_translate(cdo_transform, os.path.join(self.tmp_dir, tif_file),
bands=[band], projection='EPSG:4326')
return tif_file
def convert(self, nc_file):
tif_file = "{}.tif".format(nc_file)
nc_transform = nc_convert(os.path.join(self.tmp_dir, nc_file))
cdo_transform = cdo_invert(os.path.join(self.tmp_dir, nc_transform))
band = get_band_count(cdo_transform)
gdal_translate(cdo_transform,
os.path.join(self.tmp_dir, tif_file),
bands=[band],
projection='EPSG:4326')
return tif_file
def convert(self, tif_file):
layer_title, imgtime = self.parse_name(tif_file)
time_format = imgtime.strftime('%Y%m%dT%H0000000Z')
tif_out = "{prefix}_{time}.tif".format(prefix=self.layer_name,
time=time_format)
# Use gdal_translate to embed projection info
gdal_translate(os.path.join(self.tmp_dir, tif_file),
os.path.join(self.tmp_dir, tif_out),
nodata=0,
projection="EPSG:4326")
return tif_out
def convert(self, tif_file):
layer_title, imgtime = self.parse_name(tif_file)
time_format = imgtime.strftime('%Y%m%dT%H0000000Z')
tif_out = "{prefix}_{time}.tif".format(
prefix=self.layer_name,
time=time_format)
# Use gdal_translate to embed projection info
gdal_translate(os.path.join(self.tmp_dir, tif_file),
os.path.join(self.tmp_dir, tif_out),
nodata=0, projection="EPSG:4326")
return tif_out
def process(self):
for var, res, rcp, year, gcm in itertools.product(
self.climate_vars,
self.resolutions,
self.rcps,
self.years,
self.gcms):
outdir = os.path.join(
self.tmp_dir, self.prefix, 'future', var[0], res)
dl_name = "{}_{}_{}_{}_{}_{}.zip".format(
self.prefix, gcm[0], rcp, var[0], year, res)
print dl_name
if not os.path.exists(os.path.join(self.tmp_dir, dl_name)):
try:
self.download(self.base_url.format(
rcp=rcp, gcm=gcm[0], res=res, yr=str(year)[2:],
var=var[0]), dl_name)
except HTTPError:
continue
try:
ZipFile(os.path.join(
self.tmp_dir, dl_name)).extractall(path=outdir)
layer_name = "WorldClim {rcp} conditions w/{gcm} GCM for " + \
"{yr} at RCP {rcp}: {var}, {res} resolution"
varcount = 20 if var[0] == 'bi' else 13
var_iterator = range(1, varcount)
for v in var_iterator:
name = '{}_{}_{}_{}{}_{}_{}'.format(
self.prefix, rcp, gcm[0], var[0],
v, year, res)
original_tif = os.path.join(
outdir, '{}{}{}{}{}.tif'.format(
gcm[0], rcp, var[0], str(year)[2:], v))
tif = original_tif.replace('.tif', '_4326.tif')
gdal_translate(original_tif,
tif,
projection='EPSG:4326',
options=['COMPRESS=DEFLATE'])
title = layer_name.format(
rcp=float(rcp/10),
gcm=gcm[1],
var=self.custom_title(var, v),
yr=year,
res=res.replace('-', '.'))
desc = (self.base_description + self.desc).format(
rcp=float(rcp/10), gcm=gcm[1], yr=year,
res=res.replace('-', '.')
)
self.publish(tif, name, title, desc)
finally:
self.cleanup(outdir)
def process(self):
for var, res, rcp, year, gcm in itertools.product(
self.climate_vars, self.resolutions, self.rcps, self.years,
self.gcms):
outdir = os.path.join(self.tmp_dir, self.prefix, 'future', var[0],
res)
dl_name = "{}_{}_{}_{}_{}_{}.zip".format(self.prefix, gcm[0], rcp,
var[0], year, res)
print dl_name
if not os.path.exists(os.path.join(self.tmp_dir, dl_name)):
try:
self.download(
self.base_url.format(rcp=rcp,
gcm=gcm[0],
res=res,
yr=str(year)[2:],
var=var[0]), dl_name)
except HTTPError:
continue
try:
ZipFile(os.path.join(self.tmp_dir,
dl_name)).extractall(path=outdir)
layer_name = "WorldClim {rcp} conditions w/{gcm} GCM for " + \
"{yr} at RCP {rcp}: {var}, {res} resolution"
varcount = 20 if var[0] == 'bi' else 13
var_iterator = range(1, varcount)
for v in var_iterator:
name = '{}_{}_{}_{}{}_{}_{}'.format(
self.prefix, rcp, gcm[0], var[0], v, year, res)
original_tif = os.path.join(
outdir,
'{}{}{}{}{}.tif'.format(gcm[0], rcp, var[0],
str(year)[2:], v))
tif = original_tif.replace('.tif', '_4326.tif')
gdal_translate(original_tif,
tif,
projection='EPSG:4326',
options=['COMPRESS=DEFLATE'])
title = layer_name.format(rcp=float(rcp / 10),
gcm=gcm[1],
var=self.custom_title(var, v),
yr=year,
res=res.replace('-', '.'))
desc = (self.base_description + self.desc).format(
rcp=float(rcp / 10),
gcm=gcm[1],
yr=year,
res=res.replace('-', '.'))
self.publish(tif, name, title, desc)
finally:
self.cleanup(outdir)
def convert(self, dl_file, imgtime):
"""
Set the correct projection on the image and save as a GeoTIFF.
"""
tif_file = "{prefix}_{year}{month}{day}T{hour}0000000Z.tif".format(
prefix=self.prefix,
year=str(imgtime.year),
month='{0:02d}'.format(imgtime.month),
day='{0:02d}'.format(imgtime.day), hour='{0:02d}'.format(
imgtime.hour))
gdal_translate(os.path.join(self.tmp_dir, dl_file),
os.path.join(self.tmp_dir, tif_file),
projection='EPSG:4326',
options=['COMPRESS=DEFLATE'])
return tif_file
def process(self):
for var in self.climate_vars:
for res in self.resolutions:
outdir = os.path.join(
self.tmp_dir, self.prefix, 'current', var[0], res)
dl_zips = [[var][0][0]]
if res == '30s' and [var][0][0] == 'bio':
dl_zips = ['bio1-9', 'bio10-19']
for dl in dl_zips:
dl_name = "{}_{}_{}_{}.zip".format(self.prefix, "current",
dl, res)
if not os.path.exists(os.path.join(self.tmp_dir, dl_name)):
self.download(self.base_url.format(
self.version, dl, res), dl_name)
try:
ZipFile(os.path.join(
self.tmp_dir, dl_name)).extractall(path=outdir)
layer_name = \
"WorldClim current conditions: {var}, {res} resolution"
varcount = 20 if var[0] == 'bio' else 13
var_iterator = range(1, varcount)
for v in var_iterator:
name = '{}_cur_{}{}_{}'.format(
self.prefix, var[0], v, res)
bil = os.path.join(
outdir, '{}{}.bil'.format(var[0], v))
tif = bil.replace('.bil', '.tif')
gdal_translate(bil,
tif,
projection='EPSG:4326',
options=['COMPRESS=DEFLATE'])
title = layer_name.format(
var=self.custom_title(var, v),
res=res.replace('-', '.'))
desc = (self.base_description + self.desc).format(
self.custom_title(var, v)
)
self.publish(tif, name, title, desc)
finally:
self.cleanup(outdir)
def process(self):
for var in self.climate_vars:
for res in self.resolutions:
outdir = os.path.join(self.tmp_dir, self.prefix, 'current',
var[0], res)
dl_zips = [[var][0][0]]
if res == '30s' and [var][0][0] == 'bio':
dl_zips = ['bio1-9', 'bio10-19']
for dl in dl_zips:
dl_name = "{}_{}_{}_{}.zip".format(self.prefix, "current",
dl, res)
if not os.path.exists(os.path.join(self.tmp_dir, dl_name)):
self.download(
self.base_url.format(self.version, dl, res),
dl_name)
try:
ZipFile(os.path.join(self.tmp_dir,
dl_name)).extractall(path=outdir)
layer_name = \
"WorldClim current conditions: {var}, {res} resolution"
varcount = 20 if var[0] == 'bio' else 13
var_iterator = range(1, varcount)
for v in var_iterator:
name = '{}_cur_{}{}_{}'.format(self.prefix, var[0], v,
res)
bil = os.path.join(outdir,
'{}{}.bil'.format(var[0], v))
tif = bil.replace('.bil', '.tif')
gdal_translate(bil,
tif,
projection='EPSG:4326',
options=['COMPRESS=DEFLATE'])
title = layer_name.format(var=self.custom_title(
var, v),
res=res.replace('-', '.'))
desc = (self.base_description + self.desc).format(
self.custom_title(var, v))
self.publish(tif, name, title, desc)
finally:
self.cleanup(outdir)
def extract_band(self, tif, band, outname):
outfile = os.path.join(self.tmp_dir, outname)
gdal_translate(tif, outfile, bands=[band],
projection='EPSG:4326',
options=['TILED=YES', 'COMPRESS=LZW'])
return outfile
