def construct_conditions(args, fileformatter, inp_filebase, system_file):
bias_tags, windows = us_process.read_windows_file(args.windows_filename)
bias_functions = json.load(open(args.bias_functions_filename))
op_tags = us_process.get_op_tags_from_bias_functions(
bias_functions, bias_tags)
# Linear square well functions are all the same
for bias_function in bias_functions['origami']['bias_functions']:
if bias_function['type'] == 'LinearStepWell':
slope = bias_function['slope']
min_outside_bias = bias_function['min_bias']
grid_biases = []
for window in windows:
for rep in range(args.reps):
filebase = '{}_run-{}_rep-{}'.format(inp_filebase, args.run, rep)
grid_biases.append(biases.GridBias(op_tags, window,
min_outside_bias, slope, args.temp, filebase))
conditions_map = {'temp': [args.temp],
'staple_m': [args.staple_m],
'bias': grid_biases}
# either get rid of this too or make a list of filebases for creating sim collections
return conditions.AllSimConditions(conditions_map, fileformatter, system_file)
def main():
filebase = 'inps/snodin-staple_temp-344_run-0_rep-0' # simualation identification name
wins_filename = 'inps/snodin_344_staple.windows' # windows file
tags, wins = us_process.read_windows_file(
wins_filename
) # returns [tag1, tag2, ..,] and [((min1, max1), (min2, max2), ...)]
pmfs_filename = 'outs/snodin-long_temp-344_run-1_rep-0_pmfs.sds'
pmf_array = np.loadtxt(pmfs_filename, skiprows=1)
pmfs = {(i[0], i[1]): i[2]
for i in pmf_array} # dictionary for each line{(col1, col2):col3}
for win in wins:
biases = {'biases': []}
domain_lims = [win[0][0], win[1][0]]
staple_lims = [win[0][1], win[1][1]]
for domain in range(domain_lims[0], domain_lims[1] + 1):
for staple in range(staple_lims[0], staple_lims[1] + 1):
point = (staple, domain)
if point not in pmfs:
continue
elif np.isnan(pmfs[point]):
continue
else:
biases_entry = {}
biases_entry['point'] = [domain, staple]
biases_entry['bias'] = -pmfs[point]
biases['biases'].append(biases_entry)
win_filename = us_process.create_win_filename(win, filebase)
json.dump(biases,
open(win_filename, 'w'),
indent=4,
separators=(',', ': '))
def main():
args = parse_args()
tags, wins = us_process.read_windows_file(args.wins_filename)
for i, win in enumerate(wins):
inp_postfix = '_iter-{}.trj'.format(args.iteration)
trj_inp_filename = us_process.create_win_filename(win,
args.inp_filebase, inp_postfix)
trj_out_filename = us_process.create_win_filename(win,
args.out_filebase, '.trj.restart')
trj_file = files.UnparsedMultiLineStepInpFile(trj_inp_filename)
with open(trj_out_filename, 'w') as out:
out.write(trj_file.get_last_step())
def main():
args = parse_args()
# random.seed(123450897)
traj_file = files.TxtTrajInpFile(args.sim_filebase + '.trj',
args.system_file)
bias_tags, wins = us_process.read_windows_file(args.win_file)
bias_functions = json.load(open(args.bias_functions_filename))
op_tags = us_process.get_op_tags_from_bias_functions(
bias_functions, bias_tags)
ops = datatypes.OrderParams.from_file(args.sim_filebase)
op_to_config = sort_by_ops(ops, op_tags)
for i, win in enumerate(wins):
config = us_process.select_config_by_op_in_win(i, win, ops,
op_to_config)
win_filename = us_process.create_win_filename(win, args.out_filebase,
args.ext)
config_file = files.TxtTrajOutFile(win_filename)
config_file.write_config(traj_file.get_chains(config), 0)
def main():
parser = argparse.ArgumentParser()
parser.add_argument(
'system_file',
type=str,
help='System file')
parser.add_argument(
'win_file',
type=str,
help='Windows file')
parser.add_argument(
'sim_filebase',
type=str,
help='Filebase of simulation to select configs from')
parser.add_argument(
'out_filebase',
type=str,
help='Filebase of starting config trj files')
parser.add_argument(
'ext',
type=str,
help='Starting config trj file extension')
args = parser.parse_args()
system_filename = args.system_file
wins_filename = args.win_file
sim_filebase = args.sim_filebase
out_filebase = args.out_filebase
ext = args.ext
traj_file = PlainTextTrajFile(sim_filebase + '.trj', system_filename)
tags, wins = read_windows_file(wins_filename)
ops = read_ops_from_file(sim_filebase + '.ops', tags, 0)
op_to_config = sort_by_ops(ops, tags)
for i, win in enumerate(wins):
config = select_config_by_op_in_win(i, win, ops, op_to_config)
win_filename = create_win_filename(win, out_filebase, ext)
config_file = PlainTextTrajOutFile(win_filename)
config_file.write_config(traj_file.chains(config), 0)
def main():
args = parse_args()
skip = 1
out_filebase = '{}/{}-{}_timeseries'.format(args.output_dir, args.system,
args.vari)
tags = ['numstaples', 'numfulldomains', 'nummisdomains', 'numstackedpairs']
labels = [
'Bound staples', 'Bound domains', 'Misbound domains', 'Stacked pairs'
]
bias_tags, windows = us_process.read_windows_file(args.windows_filename)
figsize = (plot.cm_to_inches(18), plot.cm_to_inches(36 * len(windows)))
plot.set_default_appearance()
f, axes = plt.subplots(3 * len(windows), 1, figsize=figsize, dpi=300)
ax_i = -1
for window in windows:
for rep in range(args.reps):
ax_i += 1
ax = axes[ax_i]
ax.set_xlabel('Walltime / s')
timeseries = {}
times = []
for tag in tags:
timeseries[tag] = []
# Create window file postfix
postfix = '_win'
for win_min in window[0]:
postfix += '-' + str(win_min)
postfix += '-'
for win_max in window[1]:
postfix += '-' + str(win_max)
filebase = '{}/{}-{}_run-{}_rep-{}{}_iter-prod'.format(
args.input_dir, args.system, args.vari, args.run, rep, postfix)
ops_filename = '{}.ops'.format(filebase)
ops = read_ops_from_file(ops_filename, tags, skip)
times_filename = '{}.times'.format(filebase)
times = np.loadtxt(times_filename, skiprows=1)[::skip, 1]
for tag in tags:
timeseries[tag] = ops[tag]
# Plot timeseries
for i, tag in enumerate(tags):
ax.plot(times,
timeseries[tag],
marker=None,
label=labels[i],
color='C{}'.format(i),
zorder=4 - i)
# Plot expected value
for i, tag in enumerate(tags):
if args.assembled_values[i] != 0:
ax.axhline(args.assembled_values[i],
linestyle='--',
color='C{}'.format(i))
# Plot legend
ax = axes[0]
handles, labels = ax.get_legend_handles_labels()
lgd = ax.legend(handles,
labels,
frameon=False,
loc='center',
bbox_to_anchor=(0.7, 0.25))
plt.tight_layout(pad=0.5, h_pad=0, w_pad=0)
f.savefig('{}.pdf'.format(out_filebase), transparent=True)
f.savefig('{}.png'.format(out_filebase), transparent=True)
