axis=1)
sims.append(tmp)
return pandas.concat(sims, keys=range(len(sims))), len(sims)
# read the data files
def read_data(files):
data = []
for infile in files:
with open(infile, 'r') as file:
tmp = pandas.read_csv(file,
delimiter=' ',
header=0,
engine='python')
tmp = tmp.set_index('time',
drop=False).rename_axis(None,
axis=0).drop('time',
axis=1)
data.append(tmp)
return pandas.concat(data, keys=range(len(data))), len(data)
if __name__ == '__main__':
args = argsparser(**{'simulator': 'KaSim v3.5'})
data, len_data = read_data(args.data) # read data files
sims, len_sims = read_sims(args.sims) # read sims files
# calculate fitness
doerror(args, data, len_data, sims, len_sims)
return pandas.concat(sims, keys=range(len(sims))), len(sims)
# read the data files
def read_data(files):
data = []
for infile in files:
with open(infile, 'r') as file:
tmp = io.StringIO(
file.read()
[1:]) # remove the # at the beginning of simulations files
tmp = pandas.read_csv(tmp,
delim_whitespace=True,
header=0,
engine='python')
tmp = tmp.set_index('time',
drop=False).rename_axis(None,
axis=0).drop('time',
axis=1)
data.append(tmp)
return pandas.concat(data, keys=range(len(data))), len(data)
if __name__ == '__main__':
args = argsparser(**{'simulator': 'BNG2'})
data, len_data = read_data(args.data) # read data files
sims, len_sims = read_sims(args.sims) # read sims files
# calculate fitness
doerror(args, data, len_data, sims, len_sims)
sims[ind].set_index('compartment', append=True, inplace=True)
sims[ind] = sims[ind].reorder_levels(['compartment', 'time'])
return pandas.concat(sims, keys=range(len(sims))), len(sims)
# read the data files
def read_data(files):
data = []
for ind, infile in enumerate(files):
with open(infile, 'r') as input:
data.append(
pandas.read_csv(input, delimiter=' ',
engine='python').set_index('time'))
# mark each data file with the corresponding compartment
name = list(data[ind].columns)[0]
data[ind]['compartment'] = name
data[ind].set_index('compartment', append=True, inplace=True)
data[ind] = data[ind].reorder_levels(['compartment', 'time'])
return pandas.concat(data, keys=range(len(data))), len(data)
if __name__ == '__main__':
args = argsparser(**{'simulator': 'PISKaS v1.3'})
data, len_data = read_data(args.data) # read data files
sims, len_sims = read_sims(args.sims) # read sims files
# calculate fitness
doerror(args, data, len_data, sims, len_sims)
axis=1)
sims.append(tmp)
return pandas.concat(sims, keys=range(len(sims))), len(sims)
# read the data files
def read_data(files):
data = []
for infile in files:
with open(infile, 'r') as file:
tmp = pandas.read_csv(file,
delimiter=', ',
header=0,
engine='python')
tmp = tmp.set_index('time',
drop=False).rename_axis(None,
axis=0).drop('time',
axis=1)
data.append(tmp)
return pandas.concat(data, keys=range(len(data))), len(data)
if __name__ == '__main__':
args = argsparser(**{'simulator': 'NFsim'})
data, len_data = read_data(args.data) # read data files
sims, len_sims = read_sims(args.sims) # read sims files
# calculate fitness
doerror(args, data, len_data, sims, len_sims)
# read the data files
def read_data(files):
data = []
for infile in files:
with open(infile, 'r') as file:
tmp = pandas.read_csv(file,
delimiter='\t',
header=0,
engine='python')
tmp = tmp.set_index('time',
drop=False).rename_axis(None,
axis=0).drop('time',
axis=1)
data.append(tmp)
return pandas.concat(data, keys=range(len(data))), len(data)
if __name__ == '__main__':
args = argsparser(**{'simulator': 'Tellurium v2.1.5'})
if args.lower is not None:
args.lower, _ = read_data(args.lower) # read lower limit if set
if args.upper is not None:
args.upper, _ = read_data(args.upper) # read upper limit if set
data, len_data = read_data(args.data) # read data files
sims, len_sims = read_sims(args.sims) # read sims files
doerror(args, data, len_data, sims, len_sims) # calculate fitness