def run_sweep(args_dict, base_outdir, extra_argsets=None, **kwargs):
"""Run a parameter sweep
args_dict is a dictionary of argument lists.
extra_argsets is a list of argdicts for arguments which have to come
in groups.
"""
# Generate list of parameter sets
if extra_argsets is not None:
parameter_dicts = sum([generate_argdicts(args_dict, a) for a in extra_argsets], [])
else:
parameter_dicts = generate_argdicts(args_dict, None)
# Find out which arguments have different values in different runs
varying_args = utils.find_varying_value_keys(parameter_dicts)
# Run on all args.
out = utils.parallel_map(_run, parameter_dicts, it.repeat(base_outdir),
it.repeat(varying_args), **kwargs)
# Extract err_codes etc into separate lists and force execution (just
# in case it's still an iterator)
err_codes, outdirs = utils.unzip(list(out))
return err_codes, outdirs
def convergence_rate(dataset, error_norm_norm=max):
"""For a set of convergence tests calculate the rate of covergence.
Parameter "error_norm_norm" is used to convert the list of error
norms at each time step to a single error norm.
"""
# Check that we have a set of convergence tests
assert all([d['-convergence-test'] == "1" for d in dataset])
# Check that all parameters other than -ref match
def arguments_match(data1, data2, exclusions=['-ref', '-outdir']):
for k, v in data1.items():
if is_arg_key(k) and not k in exclusions:
if v != data2[k]:
return False
return True
assert all([arguments_match(dataset[1], d) for d in dataset[1:]])
# Extract data to be fitted
dts, errs = utils.unzip([( sp.mean(d['dts']), error_norm_norm(d['error_norms']) )
for d in dataset])
# fit the data to a 2nd order polynomial
def f(x, a, b, c):
return a*(x**b) + c
parameters, covar = sp.optimize.curve_fit(f, dts, errs)
rate = parameters[1] # rate of convergence = power of x (second
# parameter).
return rate
def main():
parser = argparse.ArgumentParser()
parser.add_argument('parameter_file')
args = parser.parse_args()
with open(args.parameter_file, 'r') as pfile:
args_file = ast.literal_eval(pfile.read())
try:
args_dict = args_file[0]
extra = list(args_file[1:])
except KeyError:
args_dict = args_file
extra = None
argdicts = sum([mm.generate_argdicts(args_dict, extra_args_dicts=e) for e in extra], [])
arglists, _, _ = utils.unzip([mm.argdict2list(a) for a in argdicts])
for a in arglists:
print("./driver", ' '.join(a), "\n")
return 0
