def main():
args = parse_args()
tags = ['staplestates{}'.format(i) for i in range(1, args.stapletypes + 1)]
filebase = '{}/{}-{}'.format(args.input_dir, args.system, args.vari)
out_filebase = '{}/{}-{}_staplestates-means'.format(args.output_dir,
args.system, args.vari)
figsize = (plot.cm_to_inches(18), plot.cm_to_inches(12))
plot.set_default_appearance()
f = plt.figure(figsize=figsize, dpi=300)
gs = gridspec.GridSpec(1, 2, width_ratios=[10, 1], height_ratios=[1])
ax = create_axis(f, gs, args.system)
aves, stds = plot.read_expectations(filebase)
if args.rtag:
aves = aves[aves[args.rtag] == args.rvalue]
stds = stds[stds[args.rtag] == args.rvalue]
for j, tag in enumerate(tags):
xvars = aves[args.xtag]
ax.errorbar(xvars, aves[tag], yerr=stds[tag], marker='o')
# Write to file
plt.tight_layout(pad=0.5, h_pad=0, w_pad=0)
f.savefig(out_filebase + '.png', transparent=True)
f.savefig(out_filebase + '.pdf', transparent=True)
def main():
args = parse_args()
inp_filebase = '{}/{}-{}'.format(args.input_dir, args.system, args.vari)
out_filebase = '{}/{}-{}_staplestates-melting'.format(args.output_dir,
args.system, args.vari)
index_to_stapletype = np.loadtxt(args.mapfile, dtype=int)
figsize = (plot.cm_to_inches(18), plot.cm_to_inches(12))
plot.set_default_appearance()
f = plt.figure(figsize=figsize, dpi=300)
gs = gridspec.GridSpec(1, 1, width_ratios=[1], height_ratios=[1])
gs_main = gridspec.GridSpecFromSubplotSpec(1, 1, subplot_spec=gs[:, :])
ax = f.add_subplot(gs_main[0])
ax.axis('off')
aves, stds = plot.read_expectations(inp_filebase)
if args.rtag:
aves = aves[aves[args.rtag] == args.rvalue]
stds = stds[stds[args.rtag] == args.rvalue]
temps = aves.temp
melting_points = estimate_melting_points(args.stapletypes, aves, temps)
melting_array = fill_assembled_shape_array(melting_points, index_to_stapletype)
# Plot simulation melting points
min_t = np.min(melting_array)
max_t = np.max(melting_array)
im = ax.imshow(melting_array, vmin=min_t, vmax=max_t)
plt.colorbar(im, orientation='horizontal')
plt.tight_layout(pad=0.5, h_pad=0, w_pad=0)
f.savefig(out_filebase + '.png', transparent=True)
f.savefig(out_filebase + '.pdf', transparent=True)
def main():
args = parse_args()
out_filebase = '{}_{}-barrier-vs-temp'.format(args.output_filebase,
args.tag)
figsize = (plot.cm_to_inches(18), plot.cm_to_inches(12))
plot.set_default_appearance()
f = plt.figure(figsize=figsize, dpi=300)
ax = f.add_subplot()
# Calculate barriers
barriers = []
barrier_stds = []
for system, vari in zip(args.systems, args.varis):
filebase = '{}/{}-{}_{}-lfes-melting'.format(args.input_dir, system,
vari, args.tag)
lfes = pd.read_csv('{}.aves'.format(filebase), sep=' ', index_col=0)
lfes = lfes[lfes.index <= args.assembled_op]
lfe_stds = pd.read_csv('{}.stds'.format(filebase),
sep=' ',
index_col=0)
temp = lfes.columns[0]
lfes = lfes[temp]
lfe_stds = lfe_stds[temp]
peaks, stds = calc_barrier_heights_and_errors(lfes, lfe_stds, temp)
barriers.append(peaks[0])
barrier_stds.append(stds[0])
ax.errorbar(args.x_range, barriers, yerr=barrier_stds, marker='o')
# plt.legend()
plt.tight_layout(pad=0.5, h_pad=0, w_pad=0)
f.savefig(out_filebase + '.png', transparent=True)
f.savefig(out_filebase + '.pdf', transparent=True)
def main():
args = parse_args()
out_filebase = '{}_{}-lfes-melting'.format(args.output_filebase, args.tag)
figsize = (plot.cm_to_inches(14), plot.cm_to_inches(10))
plot.set_default_appearance()
f = plt.figure(figsize=figsize, dpi=300)
ax = f.add_subplot(1, 1, 1)
ax.set_ylabel('$k_\mathrm{b}T$')
ax.set_ylim([-0.5, 20])
for system, vari in zip(args.systems, args.varis):
filebase = '{}/{}-{}_{}-lfes-melting'.format(args.input_dir, system,
vari, args.tag)
lfes = pd.read_csv('{}.aves'.format(filebase), sep=' ', index_col=0)
lfe_stds = pd.read_csv('{}.stds'.format(filebase),
sep=' ',
index_col=0)
temp = lfes.columns[0]
lfes = lfes[temp]
lfe_stds = lfe_stds[temp]
ax.errorbar(lfes.index,
lfes,
yerr=lfe_stds,
marker='o',
label='{}-{}, {} K'.format(system, vari, temp))
plt.legend()
plt.tight_layout(pad=0.5, h_pad=0, w_pad=0)
f.savefig('{}.png'.format(out_filebase), transparent=True)
f.savefig('{}.pdf'.format(out_filebase), transparent=True)
def main():
args = parse_args()
tags = ['numstaples', 'numfulldomains', 'nummisdomains', 'numstackedpairs']
yaxis_labels = [
'(Mis)bound staples', 'Bound domain pairs', 'Misbound domain pairs',
'Stacked pairs'
]
figsize = (plot.cm_to_inches(14), plot.cm_to_inches(11))
plot.set_default_appearance()
f = plt.figure(figsize=figsize, dpi=300)
gs = gridspec.GridSpec(3,
2,
width_ratios=[1, 1],
height_ratios=[10, 10, 1])
gs_main = gridspec.GridSpecFromSubplotSpec(2,
2,
subplot_spec=gs[:2, :],
wspace=0.3,
hspace=0.3)
axes = create_axes(f, gs_main, yaxis_labels)
all_assembled_values = []
for assembled_values in args.all_assembled_values:
parsed_values = []
for assembled_value in assembled_values.split(','):
parsed_values.append(int(assembled_value))
all_assembled_values.append(parsed_values)
for assembled_values in all_assembled_values:
for i, assembled_value in enumerate(assembled_values):
ax = axes[i]
ax.axhline(assembled_value, linestyle='--', color='0.8')
for system, vari in zip(args.systems, args.varis):
sim_filebases = '{}/{}-{}'.format(args.input_dir, system, vari)
all_aves, all_stds = plot.read_expectations(sim_filebases)
xvars = all_aves[args.xtag]
for i, tag in enumerate(tags):
means = all_aves[tag]
stds = all_stds[tag]
ax = axes[i]
ax.errorbar(xvars, means, yerr=stds, marker='o', label=vari)
# Plot legend
gs_lgd = gridspec.GridSpecFromSubplotSpec(1, 1, subplot_spec=gs[2, :])
ax = f.add_subplot(gs_lgd[0])
ax.set_axis_off()
handles, labels = axes[0].get_legend_handles_labels()
ax.legend(handles, labels, loc='center', frameon=False, ncol=1)
gs.tight_layout(f, pad=1.0, h_pad=0, w_pad=0)
f.savefig(args.output_filebase + '.png', transparent=True)
f.savefig(args.output_filebase + '.pdf', transparent=True)
def main():
args = parse_args()
op_tag = 'numfulldomains'
tagbase = 'domainstate'
tags = ['{}{}'.format(tagbase, i) for i in range(args.scaffolddomains)]
inp_filebase = '{}/{}-{}-{}'.format(args.input_dir, args.system, args.vari,
op_tag)
index_to_domaintype = np.loadtxt(args.mapfile, dtype=int)
figsize = (plot.cm_to_inches(18), plot.cm_to_inches(12))
for op_value in range(1, args.scaffolddomains + 1):
out_filebase = '{}/{}-{}_{}-{}-{}-freqs'.format(
args.output_dir, args.system, args.vari, op_tag, op_value, tagbase)
plot.set_default_appearance()
f = plt.figure(figsize=figsize, dpi=300)
gs = gridspec.GridSpec(1, 1, width_ratios=[1], height_ratios=[1])
gs_main = gridspec.GridSpecFromSubplotSpec(1, 1, subplot_spec=gs[:, :])
ax = f.add_subplot(gs_main[0])
ax.axis('off')
aves, stds = plot.read_expectations(inp_filebase)
if not op_value in aves[op_tag].values:
continue
reduced_aves = aves[aves[op_tag] == op_value]
freqs = [reduced_aves[t] for t in tags]
freq_array = fill_assembled_shape_array(freqs, index_to_domaintype)
# Plot simulation melting points
min_t = np.min(0)
max_t = np.max(1)
im = ax.imshow(freq_array, vmin=min_t, vmax=max_t)
plt.colorbar(im, orientation='horizontal')
plt.tight_layout(pad=0.5, h_pad=0, w_pad=0)
f.savefig(out_filebase + '.png', transparent=True)
f.savefig(out_filebase + '.pdf', transparent=True)
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'
]
figsize = (plot.cm_to_inches(18), plot.cm_to_inches(36))
plot.set_default_appearance()
f, axes = plt.subplots(3, 1, figsize=figsize, dpi=300)
for rep in range(args.reps):
ax = axes[rep]
ax.set_xlabel('Walltime / s')
timeseries = {}
times = []
for tag in tags:
timeseries[tag] = []
for run in range(args.runs):
filebase = '{}/{}-{}_run-{}_rep-{}-{}'.format(
args.input_dir, args.system, args.vari, run, rep, args.temp)
ops_filename = '{}.ops'.format(filebase)
ops = read_ops_from_file(ops_filename, tags, skip)
times_filename = '{}.times'.format(filebase)
new_times = np.loadtxt(times_filename, skiprows=1)[::skip, 1]
if run != 0:
new_times += times[-1]
times.extend(new_times.tolist())
for tag in tags:
timeseries[tag].extend(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)
def main():
args = parse_args()
tags = ['numstaples', 'numfulldomains', 'nummisdomains', 'numstackedpairs']
yaxis_labels = [
'(Mis)bound staples', 'Bound domain pairs', 'Misbound domain pairs',
'Stacked pairs'
]
figsize = (plot.cm_to_inches(14), plot.cm_to_inches(11))
plot.set_default_appearance()
f = plt.figure(figsize=figsize, dpi=300)
gs = gridspec.GridSpec(3,
2,
width_ratios=[1, 1],
height_ratios=[10, 10, 1])
gs_main = gridspec.GridSpecFromSubplotSpec(2,
2,
subplot_spec=gs[:2, :],
wspace=0.3,
hspace=0.3)
gs_cb = gridspec.GridSpecFromSubplotSpec(1, 1, subplot_spec=gs[2, :])
axes = create_axes(f, gs_main, yaxis_labels)
norm = mpl.colors.Normalize(vmin=args.smults[0], vmax=args.smults[-1])
cmap = mpl.cm.viridis
scalarmap = mpl.cm.ScalarMappable(norm=norm, cmap=cmap)
all_assembled_values = []
for assembled_values in args.all_assembled_values:
parsed_values = []
for assembled_value in assembled_values.split(','):
parsed_values.append(int(assembled_value))
all_assembled_values.append(parsed_values)
for assembled_values in all_assembled_values:
for i, assembled_value in enumerate(assembled_values):
ax = axes[i]
ax.axhline(assembled_value, linestyle='--', color='0.8')
for system, vari in zip(args.systems, args.varis):
sim_filebases = '{}/{}-{}'.format(args.input_dir, system, vari)
all_aves, all_stds = plot.read_expectations(sim_filebases)
for smult in args.smults:
reduced_aves = all_aves[all_aves['bias'] == smult]
reduced_stds = all_stds[all_stds['bias'] == smult]
xvars = reduced_aves['temp']
for i, tag in enumerate(tags):
means = reduced_aves[tag]
stds = reduced_stds[tag]
ax = axes[i]
ax.errorbar(xvars,
means,
yerr=stds,
marker='o',
label=vari,
color=scalarmap.to_rgba(smult))
# Plot legend
ax = f.add_subplot(gs_cb[0])
cbar = mpl.colorbar.ColorbarBase(ax,
orientation='horizontal',
cmap=cmap,
norm=norm)
gs.tight_layout(f, pad=1.0, h_pad=0, w_pad=0)
f.savefig(args.output_filebase + '.png', transparent=True)
f.savefig(args.output_filebase + '.pdf', transparent=True)
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)
def main():
args = parse_args()
tag2 = args.tag2
figsize = (plot.cm_to_inches(8.5), plot.cm_to_inches(7))
tag1s = [
'staplestates{}'.format(i) for i in range(1, args.stapletypes + 1)
]
for tag1 in tag1s:
inp_filebase = '{}/{}-{}_{}-{}-lfes'.format(args.input_dir,
args.system, args.vari,
tag1, tag2)
out_filebase = '{}/{}-{}_{}-{}-lfes-all'.format(
args.output_dir, args.system, args.vari, tag1, tag2)
plot.set_default_appearance()
f = plt.figure(figsize=figsize, dpi=300)
gs = gridspec.GridSpec(2, 1, width_ratios=[1], height_ratios=[20, 1])
gs_main = gridspec.GridSpecFromSubplotSpec(1,
1,
subplot_spec=gs[0, :],
wspace=0,
hspace=0)
gs_cb = gridspec.GridSpecFromSubplotSpec(1, 1, subplot_spec=gs[1, :])
ax = f.add_subplot(gs[0])
ax.set_ylabel('$k_\mathrm{b}T$')
norm = mpl.colors.Normalize(vmin=args.temps[0], vmax=args.temps[-1])
cmap = mpl.cm.viridis
scalarmap = mpl.cm.ScalarMappable(norm=norm, cmap=cmap)
aves_filename = '{}.aves'.format(inp_filebase, tag1, tag2)
aves = pd.read_csv(aves_filename, sep=' ')
aves_one = aves[aves[tag1] == 1].sort_values(tag2).set_index(tag2)
aves_zero = aves[aves[tag1] == 0].sort_values(tag2).set_index(tag2)
aves_diff = aves_one - aves_zero
stds_filename = '{}.stds'.format(inp_filebase, tag1, tag2)
stds = pd.read_csv(stds_filename, sep=' ')
stds_one = stds[stds[tag1] == 1].sort_values(tag2).set_index(tag2)
stds_zero = stds[stds[tag1] == 0].sort_values(tag2).set_index(tag2)
stds_prop = np.sqrt(stds_one**2 + stds_zero**2)
for i, temp in enumerate(args.temps):
temp_key = '{:.3f}'.format(temp)
ax.errorbar(aves_diff.index,
aves_diff[temp_key],
yerr=stds_prop[temp_key],
marker='o',
color=scalarmap.to_rgba(temp))
# Colorbar
ax = f.add_subplot(gs_cb[0])
cbar = mpl.colorbar.ColorbarBase(ax,
orientation='horizontal',
cmap=cmap,
norm=norm)
ax.set_xlabel('Temperature / K')
plt.tight_layout(pad=0.5, h_pad=0, w_pad=0)
f.savefig('{}.png'.format(out_filebase), transparent=True)
f.savefig('{}.pdf'.format(out_filebase), transparent=True)
