ValueError: Expected n_neighbors <= n_samples_fit, but n_neighbors = 40, n_samples_fit = 27, n_samples = 27

[Yifan-debug]

HI,

I'm using comseg (sopa segmentation comseg xxx) and got this error.

[tdefa]

Hello,
Could you write the full error please ?

[Yifan-debug]

\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 'dict_scale': {'x': 1, 'y': 1, 'z': 1}, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 'mean_cell_diameter': 15, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 'max_cell_radius': 20, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 'allow_disconnected_polygon': True, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 'alpha': 0.5, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 'min_rna_per_cell': 5, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 'gene_column': 'feature_name', \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 'norm_vector': False \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd } \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd dataset = "dataset comseg ['transcripts']" \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd dictionary = <module 'comseg.dictionary' from \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd '/projectnb/mylabscc/yzw0093/.conda/envs/SOPA/lib/python3.10/s\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd ds = <module 'comseg.dataset' from \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd '/projectnb/mylabscc/yzw0093/.conda/envs/SOPA/lib/python3.10/s\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd json = <module 'json' from \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd '/projectnb/mylabscc/yzw0093/.conda/envs/SOPA/lib/python3.10/j\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd patch_index = 1 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd path_dataset_folder = PosixPath('BLANK.zarr/.sopa_cache/comseg_boundaries/1') \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd temp_dir = PosixPath('BLANK.zarr/.sopa_cache/comseg_boundaries') \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd /projectnb/mylabscc/yzw0093/.conda/envs/SOPA/lib/python3.10/site-packages/comseg/dataset. \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd py:413 in compute_edge_weight \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd 410 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd #print(df_spots_label) \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd 411 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd 412 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd print("image name : ", image_name) \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 413 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd count_matrix = self.count_matrix_in_situ_from_knn(df_spots_label=df_spo \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd 414 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd n_neighbors=n_neighbo \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd 415 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd radius=radius, \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd 416 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd remove_self_node=remo \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd locals \ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd config = { \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 'dict_scale': {'x': 1, 'y': 1, 'z': 1}, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 'mean_cell_diameter': 15, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 'max_cell_radius': 20, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 'allow_disconnected_polygon': True, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 'alpha': 0.5, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 'min_rna_per_cell': 5, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 'gene_column': 'feature_name', \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 'norm_vector': False \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd } \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd df_spots_label = \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd x y z ... codeword_index \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd fov_name cell \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 0 3391.7065 3639.3567 24.361930 ... 47 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 0 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 1 3395.4580 3640.1191 18.655300 ... 272 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 2 3395.2102 3640.9730 23.315933 ... 273 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 3 3395.5322 3640.5623 24.377308 ... 273 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 4 3392.8232 3638.0117 26.516321 ... 68 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 5 3392.1420 3637.2820 25.908264 ... 63 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 0 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 6 3392.8179 3639.3113 21.829370 ... 63 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 7 3394.7676 3639.4148 22.957743 ... 63 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 8 3395.5786 3640.2358 23.606674 ... 63 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 9 3395.8179 3639.6667 18.918219 ... 383 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 10 3391.9770 3638.5593 24.664627 ... 68 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 0 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 11 3393.0833 3638.9370 24.629425 ... 273 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 12 3394.3208 3638.7800 23.892736 ... 273 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 13 3394.7222 3639.7417 24.760181 ... 115 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 14 3394.8015 3640.0742 24.889961 ... 398 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 15 3392.7598 3640.3574 26.205140 ... 284 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 16 3389.7580 3640.3420 23.515388 ... 383 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 0 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 17 3392.0884 3638.5103 22.403702 ... 383 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 0 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 18 3392.6628 3639.4114 25.234360 ... 383 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 19 3394.2012 3639.0889 23.953222 ... 383 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 20 3390.6800 3640.3286 19.985226 ... 115 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 0 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 21 3392.6260 3640.0698 25.705267 ... 398 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 22 3393.3062 3639.4595 28.005896 ... 368 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 23 3394.0894 3639.3052 22.317970 ... 68 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 24 3394.5140 3639.9922 20.118547 ... 47 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 25 3393.9846 3639.8850 25.834442 ... 383 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 26 3396.5260 3640.5034 22.648502 ... 227 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [27 rows x 12 columns] \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd distance = 'pearson' \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd image_name = 'transcripts' \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd images_subset = None \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd list_img = ['transcripts'] \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd list_of_count_matrix = [] \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd n_neighbors = 40 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd radius = 7.5 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd remove_self_node = False \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd sampling = True \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd sampling_size = 10000 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd self = "dataset comseg ['transcripts']" \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd /projectnb/mylabscc/yzw0093/.conda/envs/SOPA/lib/python3.10/site-packages/comseg/dataset. \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd py:284 in count_matrix_in_situ_from_knn \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd 281 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd array_gene_indexed = np.array([dico_list_features[self.gene_column][i] for \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd 282 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd 283 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd nbrs = NearestNeighbors(n_neighbors=n_neighbors, algorithm='ball_tree').fit \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 284 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd ad = nbrs.kneighbors_graph(list_coordo_order) ## can be optimize here \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd 285 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd distance = nbrs.kneighbors_graph(list_coordo_order, mode='distance') \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd 286 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd ad[distance > radius] = 0 \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd 287 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd ad.eliminate_zeros() \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd locals \ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd array_gene_indexed = array(['Or77', 'LOC5576812', 'Or63', 'Or63', \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 'LOC5570381', 'Or64', 'Or64', \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 'Or64', 'Or64', 'Orco', 'LOC5570381', 'Or63', \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 'Or63', 'LOC5565901', \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 'Or45', 'Or18', 'Orco', 'Orco', 'Orco', 'Orco', \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 'LOC5565901', \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 'Or45', 'Or16', 'LOC5570381', 'Or77', 'Orco', \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 'Or27'], dtype='<U10') \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd df_spots_label = \ufffd\ufffd\ufffd index x y ... codeword_index \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd fov_name cell \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 0 0 3391.7065 3639.3567 ... 47 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 0 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 1 1 3395.4580 3640.1191 ... 272 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 2 2 3395.2102 3640.9730 ... 273 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 3 3 3395.5322 3640.5623 ... 273 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 4 4 3392.8232 3638.0117 ... 68 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 5 5 3392.1420 3637.2820 ... 63 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 0 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 6 6 3392.8179 3639.3113 ... 63 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 7 7 3394.7676 3639.4148 ... 63 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 8 8 3395.5786 3640.2358 ... 63 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 9 9 3395.8179 3639.6667 ... 383 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 10 10 3391.9770 3638.5593 ... 68 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 0 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 11 11 3393.0833 3638.9370 ... 273 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 12 12 3394.3208 3638.7800 ... 273 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 13 13 3394.7222 3639.7417 ... 115 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 14 14 3394.8015 3640.0742 ... 398 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 15 15 3392.7598 3640.3574 ... 284 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 16 16 3389.7580 3640.3420 ... 383 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 0 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 17 17 3392.0884 3638.5103 ... 383 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 0 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 18 18 3392.6628 3639.4114 ... 383 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 19 19 3394.2012 3639.0889 ... 383 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 20 20 3390.6800 3640.3286 ... 115 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 0 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 21 21 3392.6260 3640.0698 ... 398 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 22 22 3393.3062 3639.4595 ... 368 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 23 23 3394.0894 3639.3052 ... 68 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 24 24 3394.5140 3639.9922 ... 47 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 25 25 3393.9846 3639.8850 ... 383 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 26 26 3396.5260 3640.5034 ... 227 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd F6 95 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [27 rows x 13 columns] \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd dico_list_features = { \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 'index': [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, ... +17], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 'x': [ \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 3391.7065, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 3395.458, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 3395.2102, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 3395.5322, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 3392.8232, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 3392.142, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 3392.8179, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 3394.7676, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 3395.5786, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 3395.8179, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd ... +17 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 'y': [ \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 3639.3567, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 3640.1191, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 3640.973, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 3640.5623, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 3638.0117, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 3637.282, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 3639.3113, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 3639.4148, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 3640.2358, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 3639.6667, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd ... +17 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 'z': [ \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 24.36193, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 18.6553, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 23.315933, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 24.377308, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 26.516321, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 25.908264, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 21.82937, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 22.957743, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 23.606674, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 18.918219, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd ... +17 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 'feature_name': [ \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 'Or77', \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 'LOC5576812', \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 'Or63', \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 'Or63', \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 'LOC5570381', \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
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\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 'Or64', \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 'Or64', \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 'Or64', \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 'Orco', \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd ... +17 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
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\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd ... +17 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
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\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd ... +17 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
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\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd ... +17 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 'transcript_id': [ \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 281706904945958, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 281706904947020, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 281706904947365, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 281706904947368, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 281706904947659, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 281706904949073, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 281706904949085, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 281706904949125, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 281706904949134, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 281706904949496, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd ... +17 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
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\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 1.7060547, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
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\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 0.0, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
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\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 0.0, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 0.25341797, \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
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\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd ... +3 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd } \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd feature = 'cell' \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd gene_id = 10 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
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\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd } \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
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\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 23.515388, 3640.342 , 3389.758 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 22.403702, 3638.5103 , 3392.0884 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 25.23436 , 3639.4114 , 3392.6628 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 23.953222, 3639.0889 , 3394.2012 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 19.985226, 3640.3286 , 3390.68 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 25.705267, 3640.0698 , 3392.626 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 28.005896, 3639.4595 , 3393.3062 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 22.31797 , 3639.3052 , 3394.0894 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 20.118547, 3639.9922 , 3394.514 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 25.834442, 3639.885 , 3393.9846 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 22.648502, 3640.5034 , 3396.526 ]]) \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd n_neighbors = 40 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd nbrs = NearestNeighbors(algorithm='ball_tree', \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd n_neighbors=40) \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd radius = 7.5 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd remove_self_node = False \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd sampling = True \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd sampling_size = 10001 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd self = "dataset comseg ['transcripts']" \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd /projectnb/mylabscc/yzw0093/.conda/envs/SOPA/lib/python3.10/site-packages/sklearn/neighbo \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd rs/_base.py:1007 in kneighbors_graph \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd 1004 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd 1005 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd # construct CSR matrix representation of the k-NN graph \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd 1006 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd if mode == "connectivity": \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 1007 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd A_ind = self.kneighbors(X, n_neighbors, return_distance=False) \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd 1008 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd n_queries = A_ind.shape[0] \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd 1009 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd A_data = np.ones(n_queries * n_neighbors) \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd 1010 \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd locals \ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd mode = 'connectivity' \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd n_neighbors = 40 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd self = NearestNeighbors(algorithm='ball_tree', n_neighbors=40) \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd X = array([[ 24.36193 , 3639.3567 , 3391.7065 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 18.6553 , 3640.1191 , 3395.458 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 23.315933, 3640.973 , 3395.2102 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 24.377308, 3640.5623 , 3395.5322 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 26.516321, 3638.0117 , 3392.8232 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 25.908264, 3637.282 , 3392.142 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 21.82937 , 3639.3113 , 3392.8179 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 22.957743, 3639.4148 , 3394.7676 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 23.606674, 3640.2358 , 3395.5786 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 18.918219, 3639.6667 , 3395.8179 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 24.664627, 3638.5593 , 3391.977 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 24.629425, 3638.937 , 3393.0833 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 23.892736, 3638.78 , 3394.3208 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 24.760181, 3639.7417 , 3394.7222 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 24.889961, 3640.0742 , 3394.8015 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 26.20514 , 3640.3574 , 3392.7598 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 23.515388, 3640.342 , 3389.758 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 22.403702, 3638.5103 , 3392.0884 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 25.23436 , 3639.4114 , 3392.6628 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 23.953222, 3639.0889 , 3394.2012 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 19.985226, 3640.3286 , 3390.68 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 25.705267, 3640.0698 , 3392.626 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 28.005896, 3639.4595 , 3393.3062 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 22.31797 , 3639.3052 , 3394.0894 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 20.118547, 3639.9922 , 3394.514 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 25.834442, 3639.885 , 3393.9846 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 22.648502, 3640.5034 , 3396.526 ]]) \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd /projectnb/mylabscc/yzw0093/.conda/envs/SOPA/lib/python3.10/site-packages/sklearn/neighbo \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd rs/_base.py:834 in kneighbors \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd 831 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd inequality_str = "n_neighbors < n_samples_fit" \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd 832 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd else: \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd 833 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd inequality_str = "n_neighbors <= n_samples_fit" \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd 834 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd raise ValueError( \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd 835 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd f"Expected {inequality_str}, but " \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd 836 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd f"n_neighbors = {n_neighbors}, n_samples_fit = {n_samples_fit}, " \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd 837 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd f"n_samples = {X.shape[0]}" # include n_samples for common tests \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd locals \ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd inequality_str = 'n_neighbors <= n_samples_fit' \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd n_neighbors = 40 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd n_samples_fit = 27 \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd query_is_train = False \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd return_distance = False \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd self = NearestNeighbors(algorithm='ball_tree', n_neighbors=40) \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd X = array([[ 24.36193 , 3639.3567 , 3391.7065 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 18.6553 , 3640.1191 , 3395.458 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 23.315933, 3640.973 , 3395.2102 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 24.377308, 3640.5623 , 3395.5322 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 26.516321, 3638.0117 , 3392.8232 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 25.908264, 3637.282 , 3392.142 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 21.82937 , 3639.3113 , 3392.8179 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 22.957743, 3639.4148 , 3394.7676 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 23.606674, 3640.2358 , 3395.5786 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 18.918219, 3639.6667 , 3395.8179 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 24.664627, 3638.5593 , 3391.977 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 24.629425, 3638.937 , 3393.0833 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 23.892736, 3638.78 , 3394.3208 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 24.760181, 3639.7417 , 3394.7222 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 24.889961, 3640.0742 , 3394.8015 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 26.20514 , 3640.3574 , 3392.7598 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 23.515388, 3640.342 , 3389.758 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 22.403702, 3638.5103 , 3392.0884 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 25.23436 , 3639.4114 , 3392.6628 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 23.953222, 3639.0889 , 3394.2012 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 19.985226, 3640.3286 , 3390.68 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 25.705267, 3640.0698 , 3392.626 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 28.005896, 3639.4595 , 3393.3062 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 22.31797 , 3639.3052 , 3394.0894 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 20.118547, 3639.9922 , 3394.514 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 25.834442, 3639.885 , 3393.9846 ], \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd [ 22.648502, 3640.5034 , 3396.526 ]]) \ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd \ufffd\ufffd\ufffd
\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd\ufffd
ValueError: Expected n_neighbors <= n_samples_fit, but n_neighbors = 40, n_samples_fit = 27,
n_samples = 27

[Yifan-debug]

Hi, I'm sorry, It's a quite long error code. with a lot words not showing. I only can show half of them

[tdefa]

Hi, I had this kind of error when running comseg on crop where there is no RNA (or less than 40)
Maybe this is the reason of the error ?