def save_local_robustness_results_to_csv(results, samples, outdir):
'''
saves local robustness summary and detailed results in csv format.
'''
n_inputs, n_outputs = len(samples[0][0]), len(samples[0][1])
summary_lines = ['leps,ueps\n']
details_lines = [
's,leps,ueps,spred,' +
','.join([f'cex_x{x}' for x in range(n_inputs)] +
[f'cex_y{y}' for y in range(n_outputs)]) + '\n'
]
summary, details = results
summary_lines.append(','.join([str(summary[0]), str(summary[1])]) + '\n')
for s, detail in enumerate(details):
leps, ueps, spred, cex = detail[0], detail[1], samples[s][1].index(
max(samples[s][1])), detail[2]
cex = cex[0] if cex else ([0 for i in range(n_inputs)],
[0 for i in range(n_outputs)])
details_lines.append(','.join(
[str(s), str(leps), str(ueps),
str(spred)] + [str(x)
for x in cex[0]] + [str(y)
for y in cex[1]]) + '\n')
create_dirpath(outdir)
summary_file = os.path.join(outdir, 'local_summary.csv')
details_file = os.path.join(outdir, 'local_details.csv')
with open(summary_file, 'w') as f:
f.writelines(summary_lines)
logger.info(f'wrote summary to {summary_file}')
with open(details_file, 'w') as f:
f.writelines(details_lines)
logger.info(f'wrote detils to {details_file}')
def save_sensitivity_results_to_csv(results, samples, outdir):
'''
saves sensitivity summary and detailed results in csv format.
@param results (dict): sensitivity results dictionary ({x0: (summary_tuple, details_list), ...})
@param outdir (string): output directory
'''
summary_lines = ['x,leps,ueps\n']
details_lines = ['x,s,leps,ueps,spred\n']
for x_id, result in results.items():
x = int(x_id[1:])
summary, details = result
summary_lines.append(','.join(
[str(x), str(summary[0]), str(summary[1])]) + '\n')
details_lines.extend([
','.join([
str(x),
str(s),
str(detail[0]),
str(detail[1]),
str(samples[s][1].index(max(samples[s][1])))
]) + '\n' for s, detail in enumerate(details)
])
summary_file = os.path.join(outdir, 'summary.csv')
details_file = os.path.join(outdir, 'details.csv')
create_dirpath(outdir)
with open(summary_file, 'w') as f:
f.writelines(summary_lines)
logger.info(f'wrote summary to {summary_file}')
with open(details_file, 'w') as f:
f.writelines(details_lines)
logger.info(f'wrote detils to {details_file}')
def save(lgkm, outpath='./lgkm.p', serialize=False, include_data=False):
'''
saves a LabelGuidedKMeans object (or list of dicts) to a pickle
Parameters
lgkm : LabelGuidedKMeans object
outpath : the output filepath
serialized : bool (if true, serializes lgkm to list of dicts)
include_data : bool (if true, saves X and Y - much larger file size)
'''
data = lgkm if not serialize else LabelGuidedKMeansUtils.serialize_regions(
lgkm, include_data=include_data)
create_dirpath(os.path.dirname(os.path.abspath(outpath)))
pickle.dump(data, open(outpath, 'wb'))
print(f'saved to {outpath}')
def save_verified_regions(vregions, outdir=default_outdir, n_categories=5):
n_features, n_categories = vregions[0]['centroid'].shape[0], n_categories
header = ','.join([f'cx{i}' for i in range(n_features)] + [
'radius', 'epsilon', 'n', 'density', 'category', 'oradius', 'duration'
] + [f'cex_x{x}' for x in range(n_features)] +
[f'cex_y{y}' for y in range(n_categories)])
rows = []
for r in vregions:
cex = r['counterexample']
cex = cex[0] if cex else (['' for i in range(n_features)],
['' for i in range(n_categories)])
rows.append(','.join([str(x) for x in r['centroid']] + [
str(v) for v in (r['radius'], r['epsilon'], r['n'], r['density'],
r['category'], r['oradius'], r['duration'])
] + [str(x) for x in cex[0]] + [str(y) for y in cex[1]]))
create_dirpath(outdir)
outpath = os.path.join(outdir, 'vregions.csv')
with open(outpath, 'w') as f:
f.writelines('\n'.join([header] + rows))
logger.info(f'wrote verified regions to {outpath}')
def save_regions_csv(lgkm, sort=True, sortrev=True, outpath='./lgkm.csv'):
'''
saves a LabelGuidedKMeans object's regions to CSV
Parameters
lgkm : LabelGuidedKMeans object
sort : bool (sorts in ascending order by radius & density)
sortrev : bool (reverses order of sort)
outpath : the output filepath
'''
regions = lgkm.get_regions(sort=sort, sortrev=sortrev)
n_features = regions[0].centroid.shape[0]
header = ','.join([f'cx{i}' for i in range(n_features)] +
['radius', 'n', 'density', 'category'])
rows = []
for r in regions:
rows.append(','.join(
[str(x) for x in r.centroid] +
[str(v) for v in (r.radius, r.n, r.density, r.category)]))
create_dirpath(outpath)
with open(outpath, 'w') as f:
f.writelines('\n'.join([header] + rows))
print(f'saved regions to {outpath}')