Loading zoo/ccip/publish.py +12 −12 Original line number Diff line number Diff line Loading @@ -207,18 +207,18 @@ def export_model_to_dir(file_in_repo: str, output_dir: str, repository: str = 'd with open(metrics_file, 'w') as f: json.dump(metrics, fp=f, indent=4, sort_keys=True, ensure_ascii=False) # clustering_file = os.path.join(output_dir, 'cluster.json') # logging.info(f'Creating clustering measurement {clustering_file!r} ...') # c_results = {} # for cname, method, xrange in [ # ('dbscan_free', 'dbscan', (2, 5)), # ('dbscan_2', 'dbscan', (2, 2)), # ('optics', 'optics', (2, 5)), # ]: # params, score = clustering_metrics(dist, cids, method=method, min_samples_range=xrange) # c_results[cname] = {**params, 'score': score} # with open(clustering_file, 'w') as f: # json.dump(c_results, fp=f, indent=4, sort_keys=True, ensure_ascii=False) clustering_file = os.path.join(output_dir, 'cluster.json') logging.info(f'Creating clustering measurement {clustering_file!r} ...') c_results = {} for cname, method, xrange in [ ('dbscan_free', 'dbscan', (2, 5)), ('dbscan_2', 'dbscan', (2, 2)), ('optics', 'optics', (2, 5)), ]: params, score = clustering_metrics(dist, cids, method=method, min_samples_range=xrange) c_results[cname] = {**params, 'score': score} with open(clustering_file, 'w') as f: json.dump(c_results, fp=f, indent=4, sort_keys=True, ensure_ascii=False) for name, img in plots.items(): plt_file = os.path.join(output_dir, f'plt_{name}.png') Loading Loading
zoo/ccip/publish.py +12 −12 Original line number Diff line number Diff line Loading @@ -207,18 +207,18 @@ def export_model_to_dir(file_in_repo: str, output_dir: str, repository: str = 'd with open(metrics_file, 'w') as f: json.dump(metrics, fp=f, indent=4, sort_keys=True, ensure_ascii=False) # clustering_file = os.path.join(output_dir, 'cluster.json') # logging.info(f'Creating clustering measurement {clustering_file!r} ...') # c_results = {} # for cname, method, xrange in [ # ('dbscan_free', 'dbscan', (2, 5)), # ('dbscan_2', 'dbscan', (2, 2)), # ('optics', 'optics', (2, 5)), # ]: # params, score = clustering_metrics(dist, cids, method=method, min_samples_range=xrange) # c_results[cname] = {**params, 'score': score} # with open(clustering_file, 'w') as f: # json.dump(c_results, fp=f, indent=4, sort_keys=True, ensure_ascii=False) clustering_file = os.path.join(output_dir, 'cluster.json') logging.info(f'Creating clustering measurement {clustering_file!r} ...') c_results = {} for cname, method, xrange in [ ('dbscan_free', 'dbscan', (2, 5)), ('dbscan_2', 'dbscan', (2, 2)), ('optics', 'optics', (2, 5)), ]: params, score = clustering_metrics(dist, cids, method=method, min_samples_range=xrange) c_results[cname] = {**params, 'score': score} with open(clustering_file, 'w') as f: json.dump(c_results, fp=f, indent=4, sort_keys=True, ensure_ascii=False) for name, img in plots.items(): plt_file = os.path.join(output_dir, f'plt_{name}.png') Loading