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zserialout.py
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zserialout.py
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from scipy.io import FortranFile
import os,sys,time,re
import numpy as np
obs=False
groups = None
debug=False #'for boradcast'
for i in sys.argv[1:]:
if i=='--obs':
if rank==0:
obs = int(tuple(open('include.obs'))[0].strip().replace('!obs:',''))
print 'observations being used, number of obs: ',int(obs)
if '.h5' in i :
filename = i.strip()
if '--debug' in i:
debug = True
print obs,filename
if filename:
###read args
extend = True
rewind = False
if not debug:
os.system(' touch temp.txt && rm temp.txt')
debug = '>>temp.txt'
def readfun(filename):
'''
reads unformatted fortran files
'''
f = FortranFile('Outputs/'+filename, 'r')
names = ''.join(f.read_reals('c'))
data = []
while True:
try:
data.append(f.read_reals(dtype=np.float_))
except TypeError:
break
#array = np.reshape(array, (nspecs,-1))
f.close()
return [names.replace(' ',''),np.array(data)]
from progressbar import ProgressBar
pbar = ProgressBar()
import h5py
hf = h5py.File(filename, 'a')
#ics = []
#ics.extend([hf['icspecs'],hf['icconst']])
###extend????
#[ics.append(i) for i in hf['icruns']]
#ics = np.array(ics)
head= hf.attrs['ictime'] + '\n' + '!'.join(['%15s'%i for i in hf['icspecs']])+ '\n' + '!'.join(['%15s'%i for i in hf['icconst']])
############################################
###hf.attrs['ictime']=1000
##################### DEL
print 'duration' , hf.attrs['ictime']
np.savetxt('Init_cons.dat', hf['icruns'], fmt='%15e', delimiter='!', newline='\n', header= head,comments='')
groups = [[int(item.attrs['id']),item.name] for item in hf.values() if isinstance(item, h5py.Group)]
lgroups = len(groups)
for n in xrange(lgroups):
g = groups[n]
#set the model
model='model'
if '-' in g[1]:
if runsaved: model='save/exec/%s/model'%(g[1].split('-')[-1])
else: description = g[1].split('-')[0]
#run cmd
version = os.popen('./%s 0 0 --version'%(model)).read()
run ='./%s %s %d %s'%(model,int(g[0]),obs,debug)
print '\n'+ run, ' of version ' , version ;
##the actual run
start = time.strftime("%s");os.system(run)
wall = int(time.strftime("%s")) - int(start)
#return data
data = {'wall':wall,'group':g[1],'vers':version.strip(),'id':g[0]}
#next task
n+=(ncpus-1)
for i in pbar(xrange(lgroups)):
#blocking recieve!
req = data
#req.Wait()
g = hf[req['group']]
print 'Finished' , req, '. Cleaning and Saving.'
g.attrs['version'] = req['vers']
for dataset in ['spec','rate','flux']:
data = readfun('%s.%s'%(req['id'],dataset))
print data[1].shape,len(data[
0].split(','))#remove non/zero results through mask
dataarr = data[0].split(',')
mask = data[1].sum(axis=0)
if dataset != 'spec':
#only save reaction which contain species
match = re.compile(r'\b(\w+)\b')
fltr=set(fltr)
keep = [len(set(match.findall(i))-fltr)==0 for i in dataarr]
mask *= np.array(keep)
mask = np.where(mask)
fltr = np.array(dataarr)[mask]
g.attrs[dataset + u'head'] = ','.join(fltr)
data[1] = np.squeeze(data[1][...,mask],axis = 1)
try: g[dataset]
except:extend=False
if not extend :
g.create_dataset(dataset, data=data[1] , chunks=True,maxshape=(None,None))
else:
print 'already saved'
#print g[dataset]
#g[dataset] = g[dataset].extend(data[1]) ### if exists extend this
#use lines below
#g[dataset].resize((g[dataset].shape[0] + data[1].shape[0]),axis=0)
#g[dataset][-data[1].shape[0]:] = data[1]
### move status bar to here !!!
#print g[dataset]
#print req,g.items()
hf.close()
print 'written' , filename