def mrgidx(ipr_paths, irr_paths, idx):
if isinstance(irr_paths,str):
irrf = NetCDFFile(irr_paths)
else:
irrf = file_master([NetCDFFile(irr_path) for irr_path in irr_paths])
if isinstance(ipr_paths,str):
iprf = NetCDFFile(ipr_paths)
else:
iprf = file_master([NetCDFFile(ipr_path) for ipr_path in ipr_paths])
# Process and Reaction keys should exclude TFLAG
pr_keys = [pr for pr in iprf.variables.keys() if pr not in ('TFLAG',)]
rr_keys = [rr for rr in irrf.variables.keys() if rr not in ('TFLAG',)]
# Attempt to order reactions by number
# this is not necessary, but is nice and clean
try:
rr_keys = [(int(rr.split('_')[1]), rr) for rr in rr_keys]
rr_keys.sort()
rr_keys = [rr[1] for rr in rr_keys]
except:
warn("Cannot sort reaction keys")
# Processes are predicated by a delimiter
prcs = list(set(['_'.join(pr.split('_')[:-1]) for pr in pr_keys]))
# Species are preceded by a delimiter
spcs = list(set(['_'.join(pr.split('_')[-1:]) for pr in pr_keys]))
# Select a dummy variable for extracting properties
pr_tmp = iprf.variables[pr_keys[0]]
# Create an empty file and decorate
# it as necessary
outf = PseudoNetCDFFile()
outf.Species = "".join([spc.ljust(16) for spc in spcs])
outf.Process = "".join([prc.ljust(16) for prc in prcs])
outf.Reactions = "".join([rr_key.ljust(16) for rr_key in rr_keys])
outf.createDimension("PROCESS", len(prcs))
outf.createDimension("SPECIES", len(spcs))
outf.createDimension("RXN", len(rr_keys))
outf.createDimension("TSTEP", pr_tmp[:,0,0,0].shape[0])
outf.createDimension("TSTEP_STAG", len(outf.dimensions["TSTEP"])+1)
outf.createDimension("ROW", 1)
outf.createDimension("LAY", 1)
outf.createDimension("COL", 1)
outf.createDimension("VAR", 3)
outf.createDimension("DATE-TIME", 2)
tflag = outf.createVariable("TFLAG", "i", ('TSTEP', 'VAR', 'DATE-TIME'))
tflag.__dict__.update(dict(units = "<YYYYJJJ,HHDDMM>", var_desc = 'TFLAG'.ljust(16), long_name = 'TFLAG'.ljust(16)))
tflag[:,:,:] = iprf.variables['TFLAG'][:][:,[0],:]
shape = outf.createVariable("SHAPE", "i", ("TSTEP", "LAY", "ROW", "COL"))
shape.__dict__.update(dict(units = "ON/OFF", var_desc = "SHAPE".ljust(16), long_name = "SHAPE".ljust(16)))
shape[:] = 1
irr = outf.createVariable("IRR", "f", ("TSTEP", "RXN"))
irr.__dict__.update(dict(units = pr_tmp.units, var_desc = "IRR".ljust(16), long_name = "IRR".ljust(16)))
ipr = outf.createVariable("IPR", "f", ("TSTEP", "SPECIES", "PROCESS"))
irr.__dict__.update(dict(units = pr_tmp.units, var_desc = "IPR".ljust(16), long_name = "IPR".ljust(16)))
for rr, var in zip(rr_keys,irr.swapaxes(0,1)):
var[:] = irrf.variables[rr][:][idx]
for prc, prcvar in zip(prcs,ipr.swapaxes(0,2)):
for spc, spcvar in zip(spcs,prcvar):
try:
spcvar[:] = iprf.variables['_'.join([prc,spc])][:][idx]
except KeyError as es:
warn(str(es))
return outf
def mrgidx(ipr_paths, irr_paths, idx):
if isinstance(irr_paths, str):
irrf = NetCDFFile(irr_paths)
else:
irrf = file_master([NetCDFFile(irr_path) for irr_path in irr_paths])
if isinstance(ipr_paths, str):
iprf = NetCDFFile(ipr_paths)
else:
iprf = file_master([NetCDFFile(ipr_path) for ipr_path in ipr_paths])
# Process and Reaction keys should exclude TFLAG
pr_keys = [pr for pr in iprf.variables.keys() if pr not in ('TFLAG', )]
rr_keys = [rr for rr in irrf.variables.keys() if rr not in ('TFLAG', )]
# Attempt to order reactions by number
# this is not necessary, but is nice and clean
try:
rr_keys = [(int(rr.split('_')[1]), rr) for rr in rr_keys]
rr_keys.sort()
rr_keys = [rr[1] for rr in rr_keys]
except:
warn("Cannot sort reaction keys")
# Processes are predicated by a delimiter
prcs = list(set(['_'.join(pr.split('_')[:-1]) for pr in pr_keys]))
# Species are preceded by a delimiter
spcs = list(set(['_'.join(pr.split('_')[-1:]) for pr in pr_keys]))
# Select a dummy variable for extracting properties
pr_tmp = iprf.variables[pr_keys[0]]
# Create an empty file and decorate
# it as necessary
outf = PseudoNetCDFFile()
outf.Species = "".join([spc.ljust(16) for spc in spcs])
outf.Process = "".join([prc.ljust(16) for prc in prcs])
outf.Reactions = "".join([rr_key.ljust(16) for rr_key in rr_keys])
outf.createDimension("PROCESS", len(prcs))
outf.createDimension("SPECIES", len(spcs))
outf.createDimension("RXN", len(rr_keys))
outf.createDimension("TSTEP", pr_tmp[:, 0, 0, 0].shape[0])
outf.createDimension("TSTEP_STAG", len(outf.dimensions["TSTEP"]) + 1)
outf.createDimension("ROW", 1)
outf.createDimension("LAY", 1)
outf.createDimension("COL", 1)
outf.createDimension("VAR", 3)
outf.createDimension("DATE-TIME", 2)
tflag = outf.createVariable("TFLAG", "i", ('TSTEP', 'VAR', 'DATE-TIME'))
tflag.__dict__.update(
dict(units="<YYYYJJJ,HHDDMM>",
var_desc='TFLAG'.ljust(16),
long_name='TFLAG'.ljust(16)))
tflag[:, :, :] = iprf.variables['TFLAG'][:][:, [0], :]
shape = outf.createVariable("SHAPE", "i", ("TSTEP", "LAY", "ROW", "COL"))
shape.__dict__.update(
dict(units="ON/OFF",
var_desc="SHAPE".ljust(16),
long_name="SHAPE".ljust(16)))
shape[:] = 1
irr = outf.createVariable("IRR", "f", ("TSTEP", "RXN"))
irr.__dict__.update(
dict(units=pr_tmp.units,
var_desc="IRR".ljust(16),
long_name="IRR".ljust(16)))
ipr = outf.createVariable("IPR", "f", ("TSTEP", "SPECIES", "PROCESS"))
irr.__dict__.update(
dict(units=pr_tmp.units,
var_desc="IPR".ljust(16),
long_name="IPR".ljust(16)))
for rr, var in zip(rr_keys, irr.swapaxes(0, 1)):
var[:] = irrf.variables[rr][:][idx]
for prc, prcvar in zip(prcs, ipr.swapaxes(0, 2)):
for spc, spcvar in zip(spcs, prcvar):
try:
spcvar[:] = iprf.variables['_'.join([prc, spc])][:][idx]
except KeyError as es:
warn(str(es))
return outf
