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  1. xenium_skin_mixed/sample15/log/Abca1.log +135 -0
  2. xenium_skin_mixed/sample15/log/Abca8a.log +135 -0
  3. xenium_skin_mixed/sample15/log/Abhd5.log +135 -0
  4. xenium_skin_mixed/sample15/log/Abraxas2.log +135 -0
  5. xenium_skin_mixed/sample15/log/Acaa2.log +135 -0
  6. xenium_skin_mixed/sample15/log/Ace2.log +135 -0
  7. xenium_skin_mixed/sample15/log/Ackr3.log +135 -0
  8. xenium_skin_mixed/sample15/log/Ackr4.log +135 -0
  9. xenium_skin_mixed/sample15/log/Acsl1.log +135 -0
  10. xenium_skin_mixed/sample15/log/Acvr1.log +135 -0
  11. xenium_skin_mixed/sample15/log/Adgre1.log +135 -0
  12. xenium_skin_mixed/sample15/log/Adipor1.log +135 -0
  13. xenium_skin_mixed/sample15/log/Ago2.log +135 -0
  14. xenium_skin_mixed/sample15/log/Agrn.log +135 -0
  15. xenium_skin_mixed/sample15/log/Akap9.log +135 -0
  16. xenium_skin_mixed/sample15/log/Alox5.log +135 -0
  17. xenium_skin_mixed/sample15/log/Amy2a5.log +135 -0
  18. xenium_skin_mixed/sample15/log/Anln.log +135 -0
  19. xenium_skin_mixed/sample15/log/Ap2a2.log +135 -0
  20. xenium_skin_mixed/sample15/log/Ap3b1.log +135 -0
  21. xenium_skin_mixed/sample15/log/Apaf1.log +135 -0
  22. xenium_skin_mixed/sample15/log/Apc.log +135 -0
  23. xenium_skin_mixed/sample15/log/Apip.log +135 -0
  24. xenium_skin_mixed/sample15/log/Arf2.log +135 -0
  25. xenium_skin_mixed/sample15/log/Arhgap17.log +135 -0
  26. xenium_skin_mixed/sample15/log/Arhgap35.log +135 -0
  27. xenium_skin_mixed/sample15/log/Arhgef3.log +135 -0
  28. xenium_skin_mixed/sample15/log/Arl13b.log +135 -0
  29. xenium_skin_mixed/sample15/log/Asap1.log +135 -0
  30. xenium_skin_mixed/sample15/log/Atf6b.log +135 -0
  31. xenium_skin_mixed/sample15/log/Atg13.log +135 -0
  32. xenium_skin_mixed/sample15/log/Atg7.log +135 -0
  33. xenium_skin_mixed/sample15/log/Atn1.log +135 -0
  34. xenium_skin_mixed/sample15/log/Atp2a3.log +135 -0
  35. xenium_skin_mixed/sample15/log/Atp5o.log +135 -0
  36. xenium_skin_mixed/sample15/log/Atp6v1b2.log +135 -0
  37. xenium_skin_mixed/sample15/log/Atrx.log +135 -0
  38. xenium_skin_mixed/sample15/log/Azi2.log +135 -0
  39. xenium_skin_mixed/sample15/log/Bach1.log +135 -0
  40. xenium_skin_mixed/sample15/log/Bap1.log +135 -0
  41. xenium_skin_mixed/sample15/log/Bcam.log +135 -0
  42. xenium_skin_mixed/sample15/log/Bcl2l11.log +135 -0
  43. xenium_skin_mixed/sample15/log/Bcl7b.log +135 -0
  44. xenium_skin_mixed/sample15/log/Bclaf1.log +135 -0
  45. xenium_skin_mixed/sample15/log/Bcr.log +135 -0
  46. xenium_skin_mixed/sample15/log/Bex3.log +135 -0
  47. xenium_skin_mixed/sample15/log/Birc3.log +135 -0
  48. xenium_skin_mixed/sample15/log/Bmp1.log +135 -0
  49. xenium_skin_mixed/sample15/log/Bmpr2.log +135 -0
  50. xenium_skin_mixed/sample15/log/Bnc2.log +135 -0
xenium_skin_mixed/sample15/log/Abca1.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Abca1
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 650 0.845266 0.000060 100 false 10 0.007815 0.000298
13
+ 1 680 650 0.740073 0.000226 100 false 10 0.000655 0.000314
14
+ 2 5552 650 0.871948 0.000859 100 false 10 0.020288 0.001294
15
+ 3 3231 650 0.750757 0.000809 100 false 10 0.000961 0.000879
16
+ 4 87 650 0.600909 0.000043 100 false 10 0.001950 0.000075
17
+ 5 96 650 0.906368 0.000121 100 false 10 0.000415 0.000146
18
+ 6 1210 650 0.838396 0.003480 100 false 10 0.007375 0.004373
19
+ 7 3 650 0.000000 0.000000 1 true 10 0.000000 0.000000
20
+ 8 448 650 0.967374 0.001552 100 false 10 0.001948 0.001645
21
+ 9 332 650 0.790920 0.000153 100 false 10 0.002670 0.000644
22
+ 10 82 650 0.506783 0.000049 100 false 10 0.007007 0.001602
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.007815
27
+ 0 1 0.006418
28
+ 0 2 0.005036
29
+ 0 3 0.003713
30
+ 0 4 0.002516
31
+ 0 5 0.001524
32
+ 0 6 0.000803
33
+ 0 7 0.000384
34
+ 0 8 0.000239
35
+ 0 9 0.000298
36
+ 1 0 0.000655
37
+ 1 1 0.000542
38
+ 1 2 0.000460
39
+ 1 3 0.000403
40
+ 1 4 0.000367
41
+ 1 5 0.000344
42
+ 1 6 0.000331
43
+ 1 7 0.000323
44
+ 1 8 0.000318
45
+ 1 9 0.000314
46
+ 2 0 0.020288
47
+ 2 1 0.016180
48
+ 2 2 0.012502
49
+ 2 3 0.009310
50
+ 2 4 0.006664
51
+ 2 5 0.004606
52
+ 2 6 0.003118
53
+ 2 7 0.002120
54
+ 2 8 0.001538
55
+ 2 9 0.001294
56
+ 3 0 0.000961
57
+ 3 1 0.000946
58
+ 3 2 0.000937
59
+ 3 3 0.000927
60
+ 3 4 0.000917
61
+ 3 5 0.000908
62
+ 3 6 0.000900
63
+ 3 7 0.000893
64
+ 3 8 0.000886
65
+ 3 9 0.000879
66
+ 4 0 0.001950
67
+ 4 1 0.001647
68
+ 4 2 0.001354
69
+ 4 3 0.001075
70
+ 4 4 0.000815
71
+ 4 5 0.000580
72
+ 4 6 0.000381
73
+ 4 7 0.000226
74
+ 4 8 0.000123
75
+ 4 9 0.000075
76
+ 5 0 0.000415
77
+ 5 1 0.000353
78
+ 5 2 0.000298
79
+ 5 3 0.000252
80
+ 5 4 0.000215
81
+ 5 5 0.000186
82
+ 5 6 0.000166
83
+ 5 7 0.000154
84
+ 5 8 0.000147
85
+ 5 9 0.000146
86
+ 6 0 0.007375
87
+ 6 1 0.006009
88
+ 6 2 0.005524
89
+ 6 3 0.005453
90
+ 6 4 0.005411
91
+ 6 5 0.005260
92
+ 6 6 0.005019
93
+ 6 7 0.004755
94
+ 6 8 0.004528
95
+ 6 9 0.004373
96
+ 7 0 0.000000
97
+ 7 1 0.000000
98
+ 7 2 0.000000
99
+ 7 3 0.000000
100
+ 7 4 0.000000
101
+ 7 5 0.000000
102
+ 7 6 0.000000
103
+ 7 7 0.000000
104
+ 7 8 0.000000
105
+ 7 9 0.000000
106
+ 8 0 0.001948
107
+ 8 1 0.001824
108
+ 8 2 0.001752
109
+ 8 3 0.001714
110
+ 8 4 0.001693
111
+ 8 5 0.001681
112
+ 8 6 0.001673
113
+ 8 7 0.001667
114
+ 8 8 0.001658
115
+ 8 9 0.001645
116
+ 9 0 0.002670
117
+ 9 1 0.002021
118
+ 9 2 0.001403
119
+ 9 3 0.000870
120
+ 9 4 0.000492
121
+ 9 5 0.000319
122
+ 9 6 0.000335
123
+ 9 7 0.000452
124
+ 9 8 0.000573
125
+ 9 9 0.000644
126
+ 10 0 0.007007
127
+ 10 1 0.006523
128
+ 10 2 0.006011
129
+ 10 3 0.005466
130
+ 10 4 0.004888
131
+ 10 5 0.004275
132
+ 10 6 0.003630
133
+ 10 7 0.002958
134
+ 10 8 0.002274
135
+ 10 9 0.001602
xenium_skin_mixed/sample15/log/Abca8a.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Abca8a
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 626 0.587711 0.000023 100 false 10 0.000039 0.000030
13
+ 1 680 626 0.570432 0.000127 100 false 10 0.000282 0.000174
14
+ 2 5552 626 0.480238 0.000042 100 false 10 0.000889 0.000263
15
+ 3 3231 626 0.805855 0.003813 100 false 10 0.005771 0.004219
16
+ 4 87 626 0.000000 0.000000 1 true 10 0.000000 0.000000
17
+ 5 96 626 0.968785 0.000769 100 false 10 0.001405 0.000889
18
+ 6 1210 626 0.328909 0.000233 100 false 10 0.000259 0.000235
19
+ 7 3 626 0.000000 0.000000 1 true 10 0.000000 0.000000
20
+ 8 448 626 0.886397 0.001188 100 false 10 0.007511 0.001748
21
+ 9 332 626 0.955129 0.007227 100 false 10 0.010605 0.006826
22
+ 10 82 626 0.400680 0.000002 100 false 10 0.000007 0.000005
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.000039
27
+ 0 1 0.000038
28
+ 0 2 0.000037
29
+ 0 3 0.000035
30
+ 0 4 0.000034
31
+ 0 5 0.000033
32
+ 0 6 0.000032
33
+ 0 7 0.000031
34
+ 0 8 0.000031
35
+ 0 9 0.000030
36
+ 1 0 0.000282
37
+ 1 1 0.000205
38
+ 1 2 0.000181
39
+ 1 3 0.000199
40
+ 1 4 0.000208
41
+ 1 5 0.000196
42
+ 1 6 0.000180
43
+ 1 7 0.000171
44
+ 1 8 0.000171
45
+ 1 9 0.000174
46
+ 2 0 0.000889
47
+ 2 1 0.000795
48
+ 2 2 0.000708
49
+ 2 3 0.000627
50
+ 2 4 0.000553
51
+ 2 5 0.000484
52
+ 2 6 0.000421
53
+ 2 7 0.000363
54
+ 2 8 0.000311
55
+ 2 9 0.000263
56
+ 3 0 0.005771
57
+ 3 1 0.005383
58
+ 3 2 0.005172
59
+ 3 3 0.004990
60
+ 3 4 0.004801
61
+ 3 5 0.004628
62
+ 3 6 0.004491
63
+ 3 7 0.004388
64
+ 3 8 0.004303
65
+ 3 9 0.004219
66
+ 4 0 0.000000
67
+ 4 1 0.000000
68
+ 4 2 0.000000
69
+ 4 3 0.000000
70
+ 4 4 0.000000
71
+ 4 5 0.000000
72
+ 4 6 0.000000
73
+ 4 7 0.000000
74
+ 4 8 0.000000
75
+ 4 9 0.000000
76
+ 5 0 0.001405
77
+ 5 1 0.001267
78
+ 5 2 0.001174
79
+ 5 3 0.001111
80
+ 5 4 0.001064
81
+ 5 5 0.001023
82
+ 5 6 0.000983
83
+ 5 7 0.000947
84
+ 5 8 0.000916
85
+ 5 9 0.000889
86
+ 6 0 0.000259
87
+ 6 1 0.000253
88
+ 6 2 0.000248
89
+ 6 3 0.000244
90
+ 6 4 0.000241
91
+ 6 5 0.000239
92
+ 6 6 0.000237
93
+ 6 7 0.000236
94
+ 6 8 0.000236
95
+ 6 9 0.000235
96
+ 7 0 0.000000
97
+ 7 1 0.000000
98
+ 7 2 0.000000
99
+ 7 3 0.000000
100
+ 7 4 0.000000
101
+ 7 5 0.000000
102
+ 7 6 0.000000
103
+ 7 7 0.000000
104
+ 7 8 0.000000
105
+ 7 9 0.000000
106
+ 8 0 0.007511
107
+ 8 1 0.005738
108
+ 8 2 0.004211
109
+ 8 3 0.003077
110
+ 8 4 0.002386
111
+ 8 5 0.002041
112
+ 8 6 0.001891
113
+ 8 7 0.001826
114
+ 8 8 0.001786
115
+ 8 9 0.001748
116
+ 9 0 0.010605
117
+ 9 1 0.010027
118
+ 9 2 0.009526
119
+ 9 3 0.008909
120
+ 9 4 0.008433
121
+ 9 5 0.008088
122
+ 9 6 0.007745
123
+ 9 7 0.007387
124
+ 9 8 0.007069
125
+ 9 9 0.006826
126
+ 10 0 0.000007
127
+ 10 1 0.000007
128
+ 10 2 0.000006
129
+ 10 3 0.000006
130
+ 10 4 0.000006
131
+ 10 5 0.000005
132
+ 10 6 0.000005
133
+ 10 7 0.000005
134
+ 10 8 0.000005
135
+ 10 9 0.000005
xenium_skin_mixed/sample15/log/Abhd5.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Abhd5
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 613 0.711020 0.000015 100 false 10 0.000032 0.000017
13
+ 1 680 613 0.488681 0.000155 100 false 10 0.001315 0.000226
14
+ 2 5552 613 0.916983 0.000263 100 false 10 0.001319 0.000552
15
+ 3 3231 613 0.631945 0.000075 100 false 10 0.000163 0.000084
16
+ 4 87 613 0.775619 0.000034 100 false 10 0.000288 0.000067
17
+ 5 96 613 0.898852 0.000021 100 false 10 0.000025 0.000024
18
+ 6 1210 613 0.438563 0.000055 100 false 10 0.000058 0.000056
19
+ 7 3 613 0.000000 0.000000 1 true 10 0.000000 0.000000
20
+ 8 448 613 0.960218 0.000097 100 false 10 0.000353 0.000113
21
+ 9 332 613 0.809806 0.000032 100 false 10 0.000048 0.000039
22
+ 10 82 613 0.823181 0.000004 100 false 10 0.000142 0.000032
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.000032
27
+ 0 1 0.000021
28
+ 0 2 0.000018
29
+ 0 3 0.000018
30
+ 0 4 0.000020
31
+ 0 5 0.000021
32
+ 0 6 0.000021
33
+ 0 7 0.000019
34
+ 0 8 0.000018
35
+ 0 9 0.000017
36
+ 1 0 0.001315
37
+ 1 1 0.001117
38
+ 1 2 0.000917
39
+ 1 3 0.000723
40
+ 1 4 0.000545
41
+ 1 5 0.000399
42
+ 1 6 0.000295
43
+ 1 7 0.000236
44
+ 1 8 0.000217
45
+ 1 9 0.000226
46
+ 2 0 0.001319
47
+ 2 1 0.000862
48
+ 2 2 0.000581
49
+ 2 3 0.000466
50
+ 2 4 0.000477
51
+ 2 5 0.000547
52
+ 2 6 0.000609
53
+ 2 7 0.000629
54
+ 2 8 0.000604
55
+ 2 9 0.000552
56
+ 3 0 0.000163
57
+ 3 1 0.000144
58
+ 3 2 0.000127
59
+ 3 3 0.000112
60
+ 3 4 0.000100
61
+ 3 5 0.000091
62
+ 3 6 0.000085
63
+ 3 7 0.000083
64
+ 3 8 0.000082
65
+ 3 9 0.000084
66
+ 4 0 0.000288
67
+ 4 1 0.000146
68
+ 4 2 0.000068
69
+ 4 3 0.000045
70
+ 4 4 0.000060
71
+ 4 5 0.000084
72
+ 4 6 0.000097
73
+ 4 7 0.000094
74
+ 4 8 0.000082
75
+ 4 9 0.000067
76
+ 5 0 0.000025
77
+ 5 1 0.000025
78
+ 5 2 0.000025
79
+ 5 3 0.000025
80
+ 5 4 0.000024
81
+ 5 5 0.000024
82
+ 5 6 0.000024
83
+ 5 7 0.000024
84
+ 5 8 0.000024
85
+ 5 9 0.000024
86
+ 6 0 0.000058
87
+ 6 1 0.000058
88
+ 6 2 0.000057
89
+ 6 3 0.000057
90
+ 6 4 0.000057
91
+ 6 5 0.000057
92
+ 6 6 0.000057
93
+ 6 7 0.000057
94
+ 6 8 0.000056
95
+ 6 9 0.000056
96
+ 7 0 0.000000
97
+ 7 1 0.000000
98
+ 7 2 0.000000
99
+ 7 3 0.000000
100
+ 7 4 0.000000
101
+ 7 5 0.000000
102
+ 7 6 0.000000
103
+ 7 7 0.000000
104
+ 7 8 0.000000
105
+ 7 9 0.000000
106
+ 8 0 0.000353
107
+ 8 1 0.000289
108
+ 8 2 0.000238
109
+ 8 3 0.000198
110
+ 8 4 0.000168
111
+ 8 5 0.000146
112
+ 8 6 0.000131
113
+ 8 7 0.000121
114
+ 8 8 0.000116
115
+ 8 9 0.000113
116
+ 9 0 0.000048
117
+ 9 1 0.000044
118
+ 9 2 0.000041
119
+ 9 3 0.000039
120
+ 9 4 0.000039
121
+ 9 5 0.000039
122
+ 9 6 0.000040
123
+ 9 7 0.000040
124
+ 9 8 0.000040
125
+ 9 9 0.000039
126
+ 10 0 0.000142
127
+ 10 1 0.000091
128
+ 10 2 0.000051
129
+ 10 3 0.000025
130
+ 10 4 0.000012
131
+ 10 5 0.000012
132
+ 10 6 0.000018
133
+ 10 7 0.000025
134
+ 10 8 0.000030
135
+ 10 9 0.000032
xenium_skin_mixed/sample15/log/Abraxas2.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Abraxas2
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 630 0.588034 0.000043 100 false 10 0.000239 0.000079
13
+ 1 680 630 0.486861 0.000031 100 false 10 0.000163 0.000055
14
+ 2 5552 630 0.499510 0.000055 100 false 10 0.000063 0.000060
15
+ 3 3231 630 0.528128 0.000048 100 false 10 0.000053 0.000050
16
+ 4 87 630 0.369152 0.000035 100 false 10 0.001238 0.000248
17
+ 5 96 630 0.876298 0.000026 100 false 10 0.000116 0.000033
18
+ 6 1210 630 0.175128 0.000072 100 false 10 0.000579 0.000332
19
+ 7 3 630 0.190790 0.000009 100 false 10 0.002705 0.000444
20
+ 8 448 630 0.356365 0.000041 100 false 10 0.000051 0.000046
21
+ 9 332 630 0.722781 0.000026 100 false 10 0.000032 0.000029
22
+ 10 82 630 0.694541 0.000015 100 false 10 0.001375 0.000225
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.000239
27
+ 0 1 0.000176
28
+ 0 2 0.000127
29
+ 0 3 0.000092
30
+ 0 4 0.000070
31
+ 0 5 0.000059
32
+ 0 6 0.000059
33
+ 0 7 0.000065
34
+ 0 8 0.000072
35
+ 0 9 0.000079
36
+ 1 0 0.000163
37
+ 1 1 0.000125
38
+ 1 2 0.000090
39
+ 1 3 0.000062
40
+ 1 4 0.000044
41
+ 1 5 0.000038
42
+ 1 6 0.000040
43
+ 1 7 0.000045
44
+ 1 8 0.000051
45
+ 1 9 0.000055
46
+ 2 0 0.000063
47
+ 2 1 0.000061
48
+ 2 2 0.000061
49
+ 2 3 0.000061
50
+ 2 4 0.000061
51
+ 2 5 0.000061
52
+ 2 6 0.000061
53
+ 2 7 0.000061
54
+ 2 8 0.000060
55
+ 2 9 0.000060
56
+ 3 0 0.000053
57
+ 3 1 0.000053
58
+ 3 2 0.000052
59
+ 3 3 0.000052
60
+ 3 4 0.000051
61
+ 3 5 0.000051
62
+ 3 6 0.000051
63
+ 3 7 0.000050
64
+ 3 8 0.000050
65
+ 3 9 0.000050
66
+ 4 0 0.001238
67
+ 4 1 0.000756
68
+ 4 2 0.000385
69
+ 4 3 0.000149
70
+ 4 4 0.000047
71
+ 4 5 0.000049
72
+ 4 6 0.000106
73
+ 4 7 0.000175
74
+ 4 8 0.000225
75
+ 4 9 0.000248
76
+ 5 0 0.000116
77
+ 5 1 0.000096
78
+ 5 2 0.000078
79
+ 5 3 0.000064
80
+ 5 4 0.000053
81
+ 5 5 0.000045
82
+ 5 6 0.000039
83
+ 5 7 0.000036
84
+ 5 8 0.000034
85
+ 5 9 0.000033
86
+ 6 0 0.000579
87
+ 6 1 0.000552
88
+ 6 2 0.000526
89
+ 6 3 0.000499
90
+ 6 4 0.000472
91
+ 6 5 0.000445
92
+ 6 6 0.000417
93
+ 6 7 0.000389
94
+ 6 8 0.000361
95
+ 6 9 0.000332
96
+ 7 0 0.002705
97
+ 7 1 0.002407
98
+ 7 2 0.002035
99
+ 7 3 0.001578
100
+ 7 4 0.001071
101
+ 7 5 0.000592
102
+ 7 6 0.000270
103
+ 7 7 0.000197
104
+ 7 8 0.000306
105
+ 7 9 0.000444
106
+ 8 0 0.000051
107
+ 8 1 0.000050
108
+ 8 2 0.000049
109
+ 8 3 0.000049
110
+ 8 4 0.000048
111
+ 8 5 0.000048
112
+ 8 6 0.000047
113
+ 8 7 0.000047
114
+ 8 8 0.000046
115
+ 8 9 0.000046
116
+ 9 0 0.000032
117
+ 9 1 0.000031
118
+ 9 2 0.000030
119
+ 9 3 0.000030
120
+ 9 4 0.000029
121
+ 9 5 0.000029
122
+ 9 6 0.000029
123
+ 9 7 0.000029
124
+ 9 8 0.000029
125
+ 9 9 0.000029
126
+ 10 0 0.001375
127
+ 10 1 0.000527
128
+ 10 2 0.000265
129
+ 10 3 0.000489
130
+ 10 4 0.000601
131
+ 10 5 0.000480
132
+ 10 6 0.000289
133
+ 10 7 0.000172
134
+ 10 8 0.000168
135
+ 10 9 0.000225
xenium_skin_mixed/sample15/log/Acaa2.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Acaa2
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 637 0.599327 0.000045 100 false 10 0.000111 0.000063
13
+ 1 680 637 0.560080 0.000118 100 false 10 0.001834 0.000454
14
+ 2 5552 637 0.825156 0.000677 100 false 10 0.003006 0.001510
15
+ 3 3231 637 0.701573 0.000173 100 false 10 0.000194 0.000170
16
+ 4 87 637 0.000000 0.000039 100 false 10 0.004012 0.000208
17
+ 5 96 637 0.925036 0.000047 100 false 10 0.000058 0.000049
18
+ 6 1210 637 0.652578 0.000127 100 false 10 0.000374 0.000164
19
+ 7 3 637 0.000000 0.000000 1 true 10 0.000000 0.000000
20
+ 8 448 637 0.873475 0.000121 100 false 10 0.000556 0.000174
21
+ 9 332 637 0.805948 0.000163 100 false 10 0.000410 0.000222
22
+ 10 82 637 0.418455 0.000021 100 false 10 0.000551 0.000122
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.000111
27
+ 0 1 0.000090
28
+ 0 2 0.000103
29
+ 0 3 0.000076
30
+ 0 4 0.000066
31
+ 0 5 0.000077
32
+ 0 6 0.000079
33
+ 0 7 0.000068
34
+ 0 8 0.000060
35
+ 0 9 0.000063
36
+ 1 0 0.001834
37
+ 1 1 0.001286
38
+ 1 2 0.000788
39
+ 1 3 0.000412
40
+ 1 4 0.000235
41
+ 1 5 0.000273
42
+ 1 6 0.000414
43
+ 1 7 0.000515
44
+ 1 8 0.000522
45
+ 1 9 0.000454
46
+ 2 0 0.003006
47
+ 2 1 0.002791
48
+ 2 2 0.002612
49
+ 2 3 0.002442
50
+ 2 4 0.002270
51
+ 2 5 0.002097
52
+ 2 6 0.001931
53
+ 2 7 0.001776
54
+ 2 8 0.001636
55
+ 2 9 0.001510
56
+ 3 0 0.000194
57
+ 3 1 0.000181
58
+ 3 2 0.000178
59
+ 3 3 0.000178
60
+ 3 4 0.000177
61
+ 3 5 0.000175
62
+ 3 6 0.000172
63
+ 3 7 0.000170
64
+ 3 8 0.000170
65
+ 3 9 0.000170
66
+ 4 0 0.004012
67
+ 4 1 0.003653
68
+ 4 2 0.003257
69
+ 4 3 0.002824
70
+ 4 4 0.002359
71
+ 4 5 0.001871
72
+ 4 6 0.001377
73
+ 4 7 0.000905
74
+ 4 8 0.000497
75
+ 4 9 0.000208
76
+ 5 0 0.000058
77
+ 5 1 0.000056
78
+ 5 2 0.000055
79
+ 5 3 0.000054
80
+ 5 4 0.000053
81
+ 5 5 0.000052
82
+ 5 6 0.000052
83
+ 5 7 0.000051
84
+ 5 8 0.000050
85
+ 5 9 0.000049
86
+ 6 0 0.000374
87
+ 6 1 0.000289
88
+ 6 2 0.000224
89
+ 6 3 0.000180
90
+ 6 4 0.000154
91
+ 6 5 0.000143
92
+ 6 6 0.000143
93
+ 6 7 0.000149
94
+ 6 8 0.000157
95
+ 6 9 0.000164
96
+ 7 0 0.000000
97
+ 7 1 0.000000
98
+ 7 2 0.000000
99
+ 7 3 0.000000
100
+ 7 4 0.000000
101
+ 7 5 0.000000
102
+ 7 6 0.000000
103
+ 7 7 0.000000
104
+ 7 8 0.000000
105
+ 7 9 0.000000
106
+ 8 0 0.000556
107
+ 8 1 0.000411
108
+ 8 2 0.000325
109
+ 8 3 0.000272
110
+ 8 4 0.000231
111
+ 8 5 0.000197
112
+ 8 6 0.000173
113
+ 8 7 0.000164
114
+ 8 8 0.000166
115
+ 8 9 0.000174
116
+ 9 0 0.000410
117
+ 9 1 0.000377
118
+ 9 2 0.000345
119
+ 9 3 0.000315
120
+ 9 4 0.000289
121
+ 9 5 0.000267
122
+ 9 6 0.000251
123
+ 9 7 0.000238
124
+ 9 8 0.000229
125
+ 9 9 0.000222
126
+ 10 0 0.000551
127
+ 10 1 0.000166
128
+ 10 2 0.000131
129
+ 10 3 0.000241
130
+ 10 4 0.000259
131
+ 10 5 0.000194
132
+ 10 6 0.000115
133
+ 10 7 0.000076
134
+ 10 8 0.000089
135
+ 10 9 0.000122
xenium_skin_mixed/sample15/log/Ace2.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Ace2
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 633 0.862834 0.000000 100 false 10 0.000001 0.000000
13
+ 1 680 633 0.199376 0.000001 100 false 10 0.000001 0.000001
14
+ 2 5552 633 0.948385 0.000254 100 false 10 0.001053 0.000381
15
+ 3 3231 633 0.442953 0.000005 100 false 10 0.000009 0.000007
16
+ 4 87 633 0.257646 0.000041 100 false 10 0.000497 0.000145
17
+ 5 96 633 0.000000 0.000000 1 true 10 0.000000 0.000000
18
+ 6 1210 633 0.335355 0.000000 100 false 10 0.000000 0.000000
19
+ 7 3 633 0.000000 0.000000 1 true 10 0.000000 0.000000
20
+ 8 448 633 0.355314 0.000007 100 false 10 0.000007 0.000007
21
+ 9 332 633 0.914931 0.000015 100 false 10 0.000022 0.000018
22
+ 10 82 633 0.000000 0.000000 1 true 10 0.000000 0.000000
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.000001
27
+ 0 1 0.000001
28
+ 0 2 0.000000
29
+ 0 3 0.000000
30
+ 0 4 0.000000
31
+ 0 5 0.000000
32
+ 0 6 0.000000
33
+ 0 7 0.000000
34
+ 0 8 0.000000
35
+ 0 9 0.000000
36
+ 1 0 0.000001
37
+ 1 1 0.000001
38
+ 1 2 0.000001
39
+ 1 3 0.000001
40
+ 1 4 0.000001
41
+ 1 5 0.000001
42
+ 1 6 0.000001
43
+ 1 7 0.000001
44
+ 1 8 0.000001
45
+ 1 9 0.000001
46
+ 2 0 0.001053
47
+ 2 1 0.000908
48
+ 2 2 0.000775
49
+ 2 3 0.000657
50
+ 2 4 0.000558
51
+ 2 5 0.000482
52
+ 2 6 0.000430
53
+ 2 7 0.000399
54
+ 2 8 0.000386
55
+ 2 9 0.000381
56
+ 3 0 0.000009
57
+ 3 1 0.000008
58
+ 3 2 0.000008
59
+ 3 3 0.000008
60
+ 3 4 0.000007
61
+ 3 5 0.000007
62
+ 3 6 0.000007
63
+ 3 7 0.000007
64
+ 3 8 0.000007
65
+ 3 9 0.000007
66
+ 4 0 0.000497
67
+ 4 1 0.000346
68
+ 4 2 0.000214
69
+ 4 3 0.000117
70
+ 4 4 0.000070
71
+ 4 5 0.000071
72
+ 4 6 0.000099
73
+ 4 7 0.000129
74
+ 4 8 0.000145
75
+ 4 9 0.000145
76
+ 5 0 0.000000
77
+ 5 1 0.000000
78
+ 5 2 0.000000
79
+ 5 3 0.000000
80
+ 5 4 0.000000
81
+ 5 5 0.000000
82
+ 5 6 0.000000
83
+ 5 7 0.000000
84
+ 5 8 0.000000
85
+ 5 9 0.000000
86
+ 6 0 0.000000
87
+ 6 1 0.000000
88
+ 6 2 0.000000
89
+ 6 3 0.000000
90
+ 6 4 0.000000
91
+ 6 5 0.000000
92
+ 6 6 0.000000
93
+ 6 7 0.000000
94
+ 6 8 0.000000
95
+ 6 9 0.000000
96
+ 7 0 0.000000
97
+ 7 1 0.000000
98
+ 7 2 0.000000
99
+ 7 3 0.000000
100
+ 7 4 0.000000
101
+ 7 5 0.000000
102
+ 7 6 0.000000
103
+ 7 7 0.000000
104
+ 7 8 0.000000
105
+ 7 9 0.000000
106
+ 8 0 0.000007
107
+ 8 1 0.000007
108
+ 8 2 0.000007
109
+ 8 3 0.000007
110
+ 8 4 0.000007
111
+ 8 5 0.000007
112
+ 8 6 0.000007
113
+ 8 7 0.000007
114
+ 8 8 0.000007
115
+ 8 9 0.000007
116
+ 9 0 0.000022
117
+ 9 1 0.000021
118
+ 9 2 0.000020
119
+ 9 3 0.000020
120
+ 9 4 0.000019
121
+ 9 5 0.000019
122
+ 9 6 0.000019
123
+ 9 7 0.000018
124
+ 9 8 0.000018
125
+ 9 9 0.000018
126
+ 10 0 0.000000
127
+ 10 1 0.000000
128
+ 10 2 0.000000
129
+ 10 3 0.000000
130
+ 10 4 0.000000
131
+ 10 5 0.000000
132
+ 10 6 0.000000
133
+ 10 7 0.000000
134
+ 10 8 0.000000
135
+ 10 9 0.000000
xenium_skin_mixed/sample15/log/Ackr3.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Ackr3
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 609 0.822847 0.000034 100 false 10 0.000230 0.000074
13
+ 1 680 609 0.900798 0.000882 100 false 10 0.001873 0.001033
14
+ 2 5552 609 0.823933 0.000140 100 false 10 0.000587 0.000222
15
+ 3 3231 609 0.679525 0.003234 100 false 10 0.010477 0.004167
16
+ 4 87 609 0.518388 0.000026 100 false 10 0.000043 0.000029
17
+ 5 96 609 0.936668 0.000027 100 false 10 0.000146 0.000071
18
+ 6 1210 609 0.540093 0.000107 100 false 10 0.000150 0.000124
19
+ 7 3 609 0.000000 0.000000 1 true 10 0.000000 0.000000
20
+ 8 448 609 0.841837 0.000100 100 false 10 0.000217 0.000114
21
+ 9 332 609 0.906983 0.000371 100 false 10 0.001727 0.000617
22
+ 10 82 609 0.646839 0.000014 100 false 10 0.000161 0.000031
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.000230
27
+ 0 1 0.000080
28
+ 0 2 0.000083
29
+ 0 3 0.000126
30
+ 0 4 0.000120
31
+ 0 5 0.000086
32
+ 0 6 0.000058
33
+ 0 7 0.000052
34
+ 0 8 0.000063
35
+ 0 9 0.000074
36
+ 1 0 0.001873
37
+ 1 1 0.001635
38
+ 1 2 0.001538
39
+ 1 3 0.001449
40
+ 1 4 0.001344
41
+ 1 5 0.001243
42
+ 1 6 0.001166
43
+ 1 7 0.001114
44
+ 1 8 0.001073
45
+ 1 9 0.001033
46
+ 2 0 0.000587
47
+ 2 1 0.000437
48
+ 2 2 0.000317
49
+ 2 3 0.000233
50
+ 2 4 0.000184
51
+ 2 5 0.000168
52
+ 2 6 0.000176
53
+ 2 7 0.000194
54
+ 2 8 0.000211
55
+ 2 9 0.000222
56
+ 3 0 0.010477
57
+ 3 1 0.008703
58
+ 3 2 0.007194
59
+ 3 3 0.005969
60
+ 3 4 0.005037
61
+ 3 5 0.004400
62
+ 3 6 0.004043
63
+ 3 7 0.003933
64
+ 3 8 0.004004
65
+ 3 9 0.004167
66
+ 4 0 0.000043
67
+ 4 1 0.000032
68
+ 4 2 0.000036
69
+ 4 3 0.000035
70
+ 4 4 0.000031
71
+ 4 5 0.000029
72
+ 4 6 0.000029
73
+ 4 7 0.000030
74
+ 4 8 0.000030
75
+ 4 9 0.000029
76
+ 5 0 0.000146
77
+ 5 1 0.000116
78
+ 5 2 0.000098
79
+ 5 3 0.000090
80
+ 5 4 0.000088
81
+ 5 5 0.000088
82
+ 5 6 0.000086
83
+ 5 7 0.000083
84
+ 5 8 0.000077
85
+ 5 9 0.000071
86
+ 6 0 0.000150
87
+ 6 1 0.000141
88
+ 6 2 0.000133
89
+ 6 3 0.000128
90
+ 6 4 0.000125
91
+ 6 5 0.000124
92
+ 6 6 0.000124
93
+ 6 7 0.000124
94
+ 6 8 0.000124
95
+ 6 9 0.000124
96
+ 7 0 0.000000
97
+ 7 1 0.000000
98
+ 7 2 0.000000
99
+ 7 3 0.000000
100
+ 7 4 0.000000
101
+ 7 5 0.000000
102
+ 7 6 0.000000
103
+ 7 7 0.000000
104
+ 7 8 0.000000
105
+ 7 9 0.000000
106
+ 8 0 0.000217
107
+ 8 1 0.000174
108
+ 8 2 0.000142
109
+ 8 3 0.000120
110
+ 8 4 0.000108
111
+ 8 5 0.000103
112
+ 8 6 0.000103
113
+ 8 7 0.000107
114
+ 8 8 0.000111
115
+ 8 9 0.000114
116
+ 9 0 0.001727
117
+ 9 1 0.001427
118
+ 9 2 0.001189
119
+ 9 3 0.001016
120
+ 9 4 0.000896
121
+ 9 5 0.000815
122
+ 9 6 0.000759
123
+ 9 7 0.000713
124
+ 9 8 0.000667
125
+ 9 9 0.000617
126
+ 10 0 0.000161
127
+ 10 1 0.000102
128
+ 10 2 0.000061
129
+ 10 3 0.000036
130
+ 10 4 0.000024
131
+ 10 5 0.000021
132
+ 10 6 0.000022
133
+ 10 7 0.000025
134
+ 10 8 0.000028
135
+ 10 9 0.000031
xenium_skin_mixed/sample15/log/Ackr4.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Ackr4
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 611 0.611542 0.000004 100 false 10 0.000051 0.000008
13
+ 1 680 611 0.757949 0.000013 100 false 10 0.000179 0.000026
14
+ 2 5552 611 0.867916 0.000789 100 false 10 0.002373 0.001176
15
+ 3 3231 611 0.735575 0.000477 100 false 10 0.000556 0.000496
16
+ 4 87 611 0.781492 0.000037 100 false 10 0.000482 0.000087
17
+ 5 96 611 0.000000 0.000000 1 true 10 0.000000 0.000000
18
+ 6 1210 611 0.752457 0.000009 100 false 10 0.000100 0.000013
19
+ 7 3 611 0.000000 0.000000 1 true 10 0.000000 0.000000
20
+ 8 448 611 0.451475 0.000002 100 false 10 0.000004 0.000004
21
+ 9 332 611 0.540314 0.000004 100 false 10 0.000013 0.000007
22
+ 10 82 611 0.000000 0.000000 1 true 10 0.000000 0.000000
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.000051
27
+ 0 1 0.000035
28
+ 0 2 0.000023
29
+ 0 3 0.000014
30
+ 0 4 0.000008
31
+ 0 5 0.000005
32
+ 0 6 0.000004
33
+ 0 7 0.000005
34
+ 0 8 0.000006
35
+ 0 9 0.000008
36
+ 1 0 0.000179
37
+ 1 1 0.000144
38
+ 1 2 0.000113
39
+ 1 3 0.000086
40
+ 1 4 0.000064
41
+ 1 5 0.000047
42
+ 1 6 0.000036
43
+ 1 7 0.000029
44
+ 1 8 0.000026
45
+ 1 9 0.000026
46
+ 2 0 0.002373
47
+ 2 1 0.001453
48
+ 2 2 0.001183
49
+ 2 3 0.001397
50
+ 2 4 0.001571
51
+ 2 5 0.001505
52
+ 2 6 0.001330
53
+ 2 7 0.001187
54
+ 2 8 0.001141
55
+ 2 9 0.001176
56
+ 3 0 0.000556
57
+ 3 1 0.000541
58
+ 3 2 0.000530
59
+ 3 3 0.000522
60
+ 3 4 0.000516
61
+ 3 5 0.000512
62
+ 3 6 0.000508
63
+ 3 7 0.000504
64
+ 3 8 0.000500
65
+ 3 9 0.000496
66
+ 4 0 0.000482
67
+ 4 1 0.000366
68
+ 4 2 0.000269
69
+ 4 3 0.000192
70
+ 4 4 0.000135
71
+ 4 5 0.000098
72
+ 4 6 0.000078
73
+ 4 7 0.000072
74
+ 4 8 0.000077
75
+ 4 9 0.000087
76
+ 5 0 0.000000
77
+ 5 1 0.000000
78
+ 5 2 0.000000
79
+ 5 3 0.000000
80
+ 5 4 0.000000
81
+ 5 5 0.000000
82
+ 5 6 0.000000
83
+ 5 7 0.000000
84
+ 5 8 0.000000
85
+ 5 9 0.000000
86
+ 6 0 0.000100
87
+ 6 1 0.000084
88
+ 6 2 0.000069
89
+ 6 3 0.000056
90
+ 6 4 0.000044
91
+ 6 5 0.000034
92
+ 6 6 0.000025
93
+ 6 7 0.000019
94
+ 6 8 0.000015
95
+ 6 9 0.000013
96
+ 7 0 0.000000
97
+ 7 1 0.000000
98
+ 7 2 0.000000
99
+ 7 3 0.000000
100
+ 7 4 0.000000
101
+ 7 5 0.000000
102
+ 7 6 0.000000
103
+ 7 7 0.000000
104
+ 7 8 0.000000
105
+ 7 9 0.000000
106
+ 8 0 0.000004
107
+ 8 1 0.000004
108
+ 8 2 0.000004
109
+ 8 3 0.000004
110
+ 8 4 0.000004
111
+ 8 5 0.000004
112
+ 8 6 0.000004
113
+ 8 7 0.000004
114
+ 8 8 0.000004
115
+ 8 9 0.000004
116
+ 9 0 0.000013
117
+ 9 1 0.000011
118
+ 9 2 0.000009
119
+ 9 3 0.000008
120
+ 9 4 0.000008
121
+ 9 5 0.000007
122
+ 9 6 0.000007
123
+ 9 7 0.000007
124
+ 9 8 0.000007
125
+ 9 9 0.000007
126
+ 10 0 0.000000
127
+ 10 1 0.000000
128
+ 10 2 0.000000
129
+ 10 3 0.000000
130
+ 10 4 0.000000
131
+ 10 5 0.000000
132
+ 10 6 0.000000
133
+ 10 7 0.000000
134
+ 10 8 0.000000
135
+ 10 9 0.000000
xenium_skin_mixed/sample15/log/Acsl1.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Acsl1
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 644 0.877694 0.000066 100 false 10 0.001936 0.000130
13
+ 1 680 644 0.763510 0.001563 100 false 10 0.017305 0.002852
14
+ 2 5552 644 0.974688 0.000307 100 false 10 0.001842 0.000566
15
+ 3 3231 644 0.376229 0.000537 100 false 10 0.000573 0.000553
16
+ 4 87 644 0.346271 0.000039 100 false 10 0.000153 0.000082
17
+ 5 96 644 0.928606 0.000811 100 false 10 0.002330 0.000919
18
+ 6 1210 644 0.349500 0.000751 100 false 10 0.000774 0.000750
19
+ 7 3 644 0.224818 0.000000 100 false 10 0.002794 0.000506
20
+ 8 448 644 0.982330 0.004168 100 false 10 0.012807 0.005852
21
+ 9 332 644 0.231977 0.000047 100 false 10 0.000247 0.000091
22
+ 10 82 644 0.647424 0.000016 100 false 10 0.000561 0.000085
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.001936
27
+ 0 1 0.001572
28
+ 0 2 0.001249
29
+ 0 3 0.000969
30
+ 0 4 0.000733
31
+ 0 5 0.000539
32
+ 0 6 0.000387
33
+ 0 7 0.000272
34
+ 0 8 0.000188
35
+ 0 9 0.000130
36
+ 1 0 0.017305
37
+ 1 1 0.015021
38
+ 1 2 0.012851
39
+ 1 3 0.010805
40
+ 1 4 0.008908
41
+ 1 5 0.007199
42
+ 1 6 0.005717
43
+ 1 7 0.004492
44
+ 1 8 0.003537
45
+ 1 9 0.002852
46
+ 2 0 0.001842
47
+ 2 1 0.001452
48
+ 2 2 0.001279
49
+ 2 3 0.001172
50
+ 2 4 0.001047
51
+ 2 5 0.000902
52
+ 2 6 0.000765
53
+ 2 7 0.000663
54
+ 2 8 0.000600
55
+ 2 9 0.000566
56
+ 3 0 0.000573
57
+ 3 1 0.000567
58
+ 3 2 0.000563
59
+ 3 3 0.000561
60
+ 3 4 0.000560
61
+ 3 5 0.000559
62
+ 3 6 0.000558
63
+ 3 7 0.000556
64
+ 3 8 0.000555
65
+ 3 9 0.000553
66
+ 4 0 0.000153
67
+ 4 1 0.000147
68
+ 4 2 0.000138
69
+ 4 3 0.000109
70
+ 4 4 0.000106
71
+ 4 5 0.000110
72
+ 4 6 0.000099
73
+ 4 7 0.000085
74
+ 4 8 0.000081
75
+ 4 9 0.000082
76
+ 5 0 0.002330
77
+ 5 1 0.001892
78
+ 5 2 0.001540
79
+ 5 3 0.001273
80
+ 5 4 0.001089
81
+ 5 5 0.000979
82
+ 5 6 0.000926
83
+ 5 7 0.000911
84
+ 5 8 0.000913
85
+ 5 9 0.000919
86
+ 6 0 0.000774
87
+ 6 1 0.000768
88
+ 6 2 0.000765
89
+ 6 3 0.000762
90
+ 6 4 0.000759
91
+ 6 5 0.000757
92
+ 6 6 0.000755
93
+ 6 7 0.000753
94
+ 6 8 0.000752
95
+ 6 9 0.000750
96
+ 7 0 0.002794
97
+ 7 1 0.002639
98
+ 7 2 0.002466
99
+ 7 3 0.002274
100
+ 7 4 0.002059
101
+ 7 5 0.001814
102
+ 7 6 0.001531
103
+ 7 7 0.001205
104
+ 7 8 0.000850
105
+ 7 9 0.000506
106
+ 8 0 0.012807
107
+ 8 1 0.009316
108
+ 8 2 0.006927
109
+ 8 3 0.005629
110
+ 8 4 0.005259
111
+ 8 5 0.005466
112
+ 8 6 0.005839
113
+ 8 7 0.006074
114
+ 8 8 0.006065
115
+ 8 9 0.005852
116
+ 9 0 0.000247
117
+ 9 1 0.000231
118
+ 9 2 0.000215
119
+ 9 3 0.000198
120
+ 9 4 0.000180
121
+ 9 5 0.000162
122
+ 9 6 0.000143
123
+ 9 7 0.000125
124
+ 9 8 0.000107
125
+ 9 9 0.000091
126
+ 10 0 0.000561
127
+ 10 1 0.000488
128
+ 10 2 0.000416
129
+ 10 3 0.000346
130
+ 10 4 0.000280
131
+ 10 5 0.000219
132
+ 10 6 0.000165
133
+ 10 7 0.000123
134
+ 10 8 0.000095
135
+ 10 9 0.000085
xenium_skin_mixed/sample15/log/Acvr1.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Acvr1
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 616 0.771902 0.000015 100 false 10 0.000508 0.000059
13
+ 1 680 616 0.383694 0.000037 100 false 10 0.000076 0.000044
14
+ 2 5552 616 0.658462 0.000058 100 false 10 0.000129 0.000078
15
+ 3 3231 616 0.755170 0.000061 100 false 10 0.000125 0.000075
16
+ 4 87 616 0.360259 0.000012 100 false 10 0.000014 0.000013
17
+ 5 96 616 0.705998 0.000009 100 false 10 0.000010 0.000010
18
+ 6 1210 616 0.313660 0.000025 100 false 10 0.000026 0.000026
19
+ 7 3 616 0.124892 0.000054 100 false 10 0.000404 0.000028
20
+ 8 448 616 0.779650 0.000033 100 false 10 0.000078 0.000044
21
+ 9 332 616 0.815064 0.000055 100 false 10 0.000523 0.000098
22
+ 10 82 616 0.141359 0.000005 100 false 10 0.000025 0.000012
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.000508
27
+ 0 1 0.000415
28
+ 0 2 0.000327
29
+ 0 3 0.000246
30
+ 0 4 0.000173
31
+ 0 5 0.000114
32
+ 0 6 0.000071
33
+ 0 7 0.000048
34
+ 0 8 0.000045
35
+ 0 9 0.000059
36
+ 1 0 0.000076
37
+ 1 1 0.000069
38
+ 1 2 0.000064
39
+ 1 3 0.000059
40
+ 1 4 0.000054
41
+ 1 5 0.000051
42
+ 1 6 0.000048
43
+ 1 7 0.000046
44
+ 1 8 0.000044
45
+ 1 9 0.000044
46
+ 2 0 0.000129
47
+ 2 1 0.000115
48
+ 2 2 0.000104
49
+ 2 3 0.000095
50
+ 2 4 0.000088
51
+ 2 5 0.000083
52
+ 2 6 0.000079
53
+ 2 7 0.000078
54
+ 2 8 0.000077
55
+ 2 9 0.000078
56
+ 3 0 0.000125
57
+ 3 1 0.000117
58
+ 3 2 0.000109
59
+ 3 3 0.000101
60
+ 3 4 0.000095
61
+ 3 5 0.000089
62
+ 3 6 0.000084
63
+ 3 7 0.000080
64
+ 3 8 0.000077
65
+ 3 9 0.000075
66
+ 4 0 0.000014
67
+ 4 1 0.000014
68
+ 4 2 0.000014
69
+ 4 3 0.000014
70
+ 4 4 0.000014
71
+ 4 5 0.000014
72
+ 4 6 0.000013
73
+ 4 7 0.000013
74
+ 4 8 0.000013
75
+ 4 9 0.000013
76
+ 5 0 0.000010
77
+ 5 1 0.000010
78
+ 5 2 0.000010
79
+ 5 3 0.000010
80
+ 5 4 0.000010
81
+ 5 5 0.000010
82
+ 5 6 0.000010
83
+ 5 7 0.000010
84
+ 5 8 0.000010
85
+ 5 9 0.000010
86
+ 6 0 0.000026
87
+ 6 1 0.000026
88
+ 6 2 0.000026
89
+ 6 3 0.000026
90
+ 6 4 0.000026
91
+ 6 5 0.000026
92
+ 6 6 0.000026
93
+ 6 7 0.000026
94
+ 6 8 0.000026
95
+ 6 9 0.000026
96
+ 7 0 0.000404
97
+ 7 1 0.000223
98
+ 7 2 0.000086
99
+ 7 3 0.000028
100
+ 7 4 0.000051
101
+ 7 5 0.000091
102
+ 7 6 0.000103
103
+ 7 7 0.000087
104
+ 7 8 0.000056
105
+ 7 9 0.000028
106
+ 8 0 0.000078
107
+ 8 1 0.000074
108
+ 8 2 0.000071
109
+ 8 3 0.000067
110
+ 8 4 0.000063
111
+ 8 5 0.000059
112
+ 8 6 0.000055
113
+ 8 7 0.000052
114
+ 8 8 0.000048
115
+ 8 9 0.000044
116
+ 9 0 0.000523
117
+ 9 1 0.000415
118
+ 9 2 0.000324
119
+ 9 3 0.000250
120
+ 9 4 0.000194
121
+ 9 5 0.000154
122
+ 9 6 0.000126
123
+ 9 7 0.000109
124
+ 9 8 0.000100
125
+ 9 9 0.000098
126
+ 10 0 0.000025
127
+ 10 1 0.000024
128
+ 10 2 0.000022
129
+ 10 3 0.000020
130
+ 10 4 0.000018
131
+ 10 5 0.000017
132
+ 10 6 0.000015
133
+ 10 7 0.000014
134
+ 10 8 0.000013
135
+ 10 9 0.000012
xenium_skin_mixed/sample15/log/Adgre1.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Adgre1
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 629 0.926868 0.000392 100 false 10 0.030565 0.005738
13
+ 1 680 629 0.522197 0.000053 100 false 10 0.000093 0.000067
14
+ 2 5552 629 0.612572 0.000021 100 false 10 0.000682 0.000035
15
+ 3 3231 629 0.496713 0.000084 100 false 10 0.000126 0.000110
16
+ 4 87 629 0.511045 0.000219 100 false 10 0.000316 0.000212
17
+ 5 96 629 0.953604 0.000530 100 false 10 0.006403 0.001396
18
+ 6 1210 629 0.789870 0.003302 100 false 10 0.021172 0.004109
19
+ 7 3 629 0.000000 0.000000 1 true 10 0.000000 0.000000
20
+ 8 448 629 0.604934 0.000032 100 false 10 0.000050 0.000039
21
+ 9 332 629 0.626227 0.000016 100 false 10 0.000027 0.000020
22
+ 10 82 629 0.627559 0.000160 100 false 10 0.001696 0.000339
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.030565
27
+ 0 1 0.023681
28
+ 0 2 0.017305
29
+ 0 3 0.011700
30
+ 0 4 0.007194
31
+ 0 5 0.004191
32
+ 0 6 0.002951
33
+ 0 7 0.003388
34
+ 0 8 0.004718
35
+ 0 9 0.005738
36
+ 1 0 0.000093
37
+ 1 1 0.000081
38
+ 1 2 0.000074
39
+ 1 3 0.000070
40
+ 1 4 0.000068
41
+ 1 5 0.000068
42
+ 1 6 0.000069
43
+ 1 7 0.000069
44
+ 1 8 0.000068
45
+ 1 9 0.000067
46
+ 2 0 0.000682
47
+ 2 1 0.000588
48
+ 2 2 0.000493
49
+ 2 3 0.000400
50
+ 2 4 0.000311
51
+ 2 5 0.000228
52
+ 2 6 0.000154
53
+ 2 7 0.000095
54
+ 2 8 0.000054
55
+ 2 9 0.000035
56
+ 3 0 0.000126
57
+ 3 1 0.000111
58
+ 3 2 0.000118
59
+ 3 3 0.000119
60
+ 3 4 0.000115
61
+ 3 5 0.000110
62
+ 3 6 0.000109
63
+ 3 7 0.000110
64
+ 3 8 0.000112
65
+ 3 9 0.000110
66
+ 4 0 0.000316
67
+ 4 1 0.000284
68
+ 4 2 0.000319
69
+ 4 3 0.000243
70
+ 4 4 0.000265
71
+ 4 5 0.000253
72
+ 4 6 0.000220
73
+ 4 7 0.000232
74
+ 4 8 0.000235
75
+ 4 9 0.000212
76
+ 5 0 0.006403
77
+ 5 1 0.004675
78
+ 5 2 0.003260
79
+ 5 3 0.002189
80
+ 5 4 0.001469
81
+ 5 5 0.001082
82
+ 5 6 0.000974
83
+ 5 7 0.001056
84
+ 5 8 0.001225
85
+ 5 9 0.001396
86
+ 6 0 0.021172
87
+ 6 1 0.017040
88
+ 6 2 0.013571
89
+ 6 3 0.010736
90
+ 6 4 0.008490
91
+ 6 5 0.006780
92
+ 6 6 0.005545
93
+ 6 7 0.004729
94
+ 6 8 0.004272
95
+ 6 9 0.004109
96
+ 7 0 0.000000
97
+ 7 1 0.000000
98
+ 7 2 0.000000
99
+ 7 3 0.000000
100
+ 7 4 0.000000
101
+ 7 5 0.000000
102
+ 7 6 0.000000
103
+ 7 7 0.000000
104
+ 7 8 0.000000
105
+ 7 9 0.000000
106
+ 8 0 0.000050
107
+ 8 1 0.000047
108
+ 8 2 0.000045
109
+ 8 3 0.000043
110
+ 8 4 0.000042
111
+ 8 5 0.000041
112
+ 8 6 0.000040
113
+ 8 7 0.000039
114
+ 8 8 0.000039
115
+ 8 9 0.000039
116
+ 9 0 0.000027
117
+ 9 1 0.000025
118
+ 9 2 0.000024
119
+ 9 3 0.000023
120
+ 9 4 0.000023
121
+ 9 5 0.000022
122
+ 9 6 0.000021
123
+ 9 7 0.000021
124
+ 9 8 0.000020
125
+ 9 9 0.000020
126
+ 10 0 0.001696
127
+ 10 1 0.000525
128
+ 10 2 0.000179
129
+ 10 3 0.000582
130
+ 10 4 0.000732
131
+ 10 5 0.000512
132
+ 10 6 0.000253
133
+ 10 7 0.000158
134
+ 10 8 0.000226
135
+ 10 9 0.000339
xenium_skin_mixed/sample15/log/Adipor1.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Adipor1
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 630 0.477743 0.000111 100 false 10 0.003143 0.000741
13
+ 1 680 630 0.764436 0.000333 100 false 10 0.000608 0.000421
14
+ 2 5552 630 0.675445 0.001175 100 false 10 0.001407 0.001260
15
+ 3 3231 630 0.703441 0.000173 100 false 10 0.000251 0.000205
16
+ 4 87 630 0.451908 0.000063 100 false 10 0.008919 0.001850
17
+ 5 96 630 0.813735 0.000246 100 false 10 0.000413 0.000279
18
+ 6 1210 630 0.523651 0.000343 100 false 10 0.000692 0.000367
19
+ 7 3 630 0.257261 0.000269 100 false 10 0.011093 0.004525
20
+ 8 448 630 0.660826 0.000100 100 false 10 0.000368 0.000134
21
+ 9 332 630 0.750560 0.000164 100 false 10 0.002116 0.000326
22
+ 10 82 630 0.431262 0.000075 100 false 10 0.017946 0.000856
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.003143
27
+ 0 1 0.002031
28
+ 0 2 0.001049
29
+ 0 3 0.000390
30
+ 0 4 0.000203
31
+ 0 5 0.000403
32
+ 0 6 0.000687
33
+ 0 7 0.000850
34
+ 0 8 0.000857
35
+ 0 9 0.000741
36
+ 1 0 0.000608
37
+ 1 1 0.000486
38
+ 1 2 0.000487
39
+ 1 3 0.000504
40
+ 1 4 0.000486
41
+ 1 5 0.000452
42
+ 1 6 0.000426
43
+ 1 7 0.000419
44
+ 1 8 0.000422
45
+ 1 9 0.000421
46
+ 2 0 0.001407
47
+ 2 1 0.001338
48
+ 2 2 0.001373
49
+ 2 3 0.001304
50
+ 2 4 0.001277
51
+ 2 5 0.001303
52
+ 2 6 0.001308
53
+ 2 7 0.001279
54
+ 2 8 0.001256
55
+ 2 9 0.001260
56
+ 3 0 0.000251
57
+ 3 1 0.000228
58
+ 3 2 0.000212
59
+ 3 3 0.000203
60
+ 3 4 0.000201
61
+ 3 5 0.000203
62
+ 3 6 0.000207
63
+ 3 7 0.000209
64
+ 3 8 0.000208
65
+ 3 9 0.000205
66
+ 4 0 0.008919
67
+ 4 1 0.005599
68
+ 4 2 0.002707
69
+ 4 3 0.000766
70
+ 4 4 0.000092
71
+ 4 5 0.000421
72
+ 4 6 0.001087
73
+ 4 7 0.001617
74
+ 4 8 0.001866
75
+ 4 9 0.001850
76
+ 5 0 0.000413
77
+ 5 1 0.000351
78
+ 5 2 0.000306
79
+ 5 3 0.000278
80
+ 5 4 0.000266
81
+ 5 5 0.000267
82
+ 5 6 0.000275
83
+ 5 7 0.000282
84
+ 5 8 0.000283
85
+ 5 9 0.000279
86
+ 6 0 0.000692
87
+ 6 1 0.000533
88
+ 6 2 0.000452
89
+ 6 3 0.000444
90
+ 6 4 0.000464
91
+ 6 5 0.000461
92
+ 6 6 0.000431
93
+ 6 7 0.000396
94
+ 6 8 0.000372
95
+ 6 9 0.000367
96
+ 7 0 0.011093
97
+ 7 1 0.010404
98
+ 7 2 0.009727
99
+ 7 3 0.009058
100
+ 7 4 0.008392
101
+ 7 5 0.007723
102
+ 7 6 0.007027
103
+ 7 7 0.006278
104
+ 7 8 0.005455
105
+ 7 9 0.004525
106
+ 8 0 0.000368
107
+ 8 1 0.000337
108
+ 8 2 0.000306
109
+ 8 3 0.000276
110
+ 8 4 0.000245
111
+ 8 5 0.000216
112
+ 8 6 0.000188
113
+ 8 7 0.000164
114
+ 8 8 0.000146
115
+ 8 9 0.000134
116
+ 9 0 0.002116
117
+ 9 1 0.001638
118
+ 9 2 0.001266
119
+ 9 3 0.000973
120
+ 9 4 0.000737
121
+ 9 5 0.000549
122
+ 9 6 0.000408
123
+ 9 7 0.000318
124
+ 9 8 0.000290
125
+ 9 9 0.000326
126
+ 10 0 0.017946
127
+ 10 1 0.015558
128
+ 10 2 0.013123
129
+ 10 3 0.010631
130
+ 10 4 0.008086
131
+ 10 5 0.005558
132
+ 10 6 0.003225
133
+ 10 7 0.001411
134
+ 10 8 0.000555
135
+ 10 9 0.000856
xenium_skin_mixed/sample15/log/Ago2.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Ago2
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 642 0.753830 0.000065 100 false 10 0.000452 0.000149
13
+ 1 680 642 0.335865 0.000053 100 false 10 0.000132 0.000057
14
+ 2 5552 642 0.727474 0.000087 100 false 10 0.000205 0.000110
15
+ 3 3231 642 0.704609 0.000047 100 false 10 0.000048 0.000048
16
+ 4 87 642 0.267967 0.000045 100 false 10 0.001224 0.000317
17
+ 5 96 642 0.953158 0.000211 100 false 10 0.000614 0.000291
18
+ 6 1210 642 0.573463 0.000055 100 false 10 0.000213 0.000088
19
+ 7 3 642 0.000000 0.000000 1 true 10 0.000000 0.000000
20
+ 8 448 642 0.690362 0.000040 100 false 10 0.000052 0.000047
21
+ 9 332 642 0.735840 0.000030 100 false 10 0.000045 0.000037
22
+ 10 82 642 0.606290 0.000031 100 false 10 0.007537 0.001659
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.000452
27
+ 0 1 0.000314
28
+ 0 2 0.000223
29
+ 0 3 0.000182
30
+ 0 4 0.000180
31
+ 0 5 0.000193
32
+ 0 6 0.000199
33
+ 0 7 0.000192
34
+ 0 8 0.000174
35
+ 0 9 0.000149
36
+ 1 0 0.000132
37
+ 1 1 0.000104
38
+ 1 2 0.000083
39
+ 1 3 0.000069
40
+ 1 4 0.000061
41
+ 1 5 0.000057
42
+ 1 6 0.000055
43
+ 1 7 0.000055
44
+ 1 8 0.000056
45
+ 1 9 0.000057
46
+ 2 0 0.000205
47
+ 2 1 0.000164
48
+ 2 2 0.000133
49
+ 2 3 0.000113
50
+ 2 4 0.000102
51
+ 2 5 0.000099
52
+ 2 6 0.000100
53
+ 2 7 0.000104
54
+ 2 8 0.000107
55
+ 2 9 0.000110
56
+ 3 0 0.000048
57
+ 3 1 0.000048
58
+ 3 2 0.000048
59
+ 3 3 0.000048
60
+ 3 4 0.000048
61
+ 3 5 0.000048
62
+ 3 6 0.000048
63
+ 3 7 0.000048
64
+ 3 8 0.000048
65
+ 3 9 0.000048
66
+ 4 0 0.001224
67
+ 4 1 0.000717
68
+ 4 2 0.000356
69
+ 4 3 0.000158
70
+ 4 4 0.000104
71
+ 4 5 0.000140
72
+ 4 6 0.000209
73
+ 4 7 0.000271
74
+ 4 8 0.000308
75
+ 4 9 0.000317
76
+ 5 0 0.000614
77
+ 5 1 0.000473
78
+ 5 2 0.000371
79
+ 5 3 0.000307
80
+ 5 4 0.000274
81
+ 5 5 0.000264
82
+ 5 6 0.000269
83
+ 5 7 0.000280
84
+ 5 8 0.000288
85
+ 5 9 0.000291
86
+ 6 0 0.000213
87
+ 6 1 0.000158
88
+ 6 2 0.000116
89
+ 6 3 0.000089
90
+ 6 4 0.000078
91
+ 6 5 0.000078
92
+ 6 6 0.000084
93
+ 6 7 0.000090
94
+ 6 8 0.000091
95
+ 6 9 0.000088
96
+ 7 0 0.000000
97
+ 7 1 0.000000
98
+ 7 2 0.000000
99
+ 7 3 0.000000
100
+ 7 4 0.000000
101
+ 7 5 0.000000
102
+ 7 6 0.000000
103
+ 7 7 0.000000
104
+ 7 8 0.000000
105
+ 7 9 0.000000
106
+ 8 0 0.000052
107
+ 8 1 0.000051
108
+ 8 2 0.000050
109
+ 8 3 0.000049
110
+ 8 4 0.000048
111
+ 8 5 0.000048
112
+ 8 6 0.000048
113
+ 8 7 0.000047
114
+ 8 8 0.000047
115
+ 8 9 0.000047
116
+ 9 0 0.000045
117
+ 9 1 0.000044
118
+ 9 2 0.000043
119
+ 9 3 0.000042
120
+ 9 4 0.000041
121
+ 9 5 0.000040
122
+ 9 6 0.000039
123
+ 9 7 0.000038
124
+ 9 8 0.000038
125
+ 9 9 0.000037
126
+ 10 0 0.007537
127
+ 10 1 0.005184
128
+ 10 2 0.002959
129
+ 10 3 0.001202
130
+ 10 4 0.000319
131
+ 10 5 0.000401
132
+ 10 6 0.000989
133
+ 10 7 0.001505
134
+ 10 8 0.001725
135
+ 10 9 0.001659
xenium_skin_mixed/sample15/log/Agrn.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Agrn
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 643 0.848699 0.000010 100 false 10 0.000068 0.000014
13
+ 1 680 643 0.843452 0.000076 100 false 10 0.000101 0.000086
14
+ 2 5552 643 0.929960 0.000445 100 false 10 0.001052 0.000720
15
+ 3 3231 643 0.705792 0.000032 100 false 10 0.000180 0.000083
16
+ 4 87 643 0.270515 0.000019 100 false 10 0.000082 0.000032
17
+ 5 96 643 0.685528 0.000061 100 false 10 0.000144 0.000097
18
+ 6 1210 643 0.326695 0.000008 100 false 10 0.000022 0.000015
19
+ 7 3 643 0.000000 0.000000 1 true 10 0.000000 0.000000
20
+ 8 448 643 0.506872 0.000037 100 false 10 0.000088 0.000047
21
+ 9 332 643 0.907734 0.000169 100 false 10 0.000592 0.000187
22
+ 10 82 643 0.290742 0.000008 100 false 10 0.000008 0.000008
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.000068
27
+ 0 1 0.000057
28
+ 0 2 0.000048
29
+ 0 3 0.000039
30
+ 0 4 0.000032
31
+ 0 5 0.000026
32
+ 0 6 0.000021
33
+ 0 7 0.000018
34
+ 0 8 0.000016
35
+ 0 9 0.000014
36
+ 1 0 0.000101
37
+ 1 1 0.000096
38
+ 1 2 0.000096
39
+ 1 3 0.000094
40
+ 1 4 0.000092
41
+ 1 5 0.000089
42
+ 1 6 0.000088
43
+ 1 7 0.000087
44
+ 1 8 0.000087
45
+ 1 9 0.000086
46
+ 2 0 0.001052
47
+ 2 1 0.001014
48
+ 2 2 0.000927
49
+ 2 3 0.000903
50
+ 2 4 0.000866
51
+ 2 5 0.000823
52
+ 2 6 0.000799
53
+ 2 7 0.000779
54
+ 2 8 0.000749
55
+ 2 9 0.000720
56
+ 3 0 0.000180
57
+ 3 1 0.000167
58
+ 3 2 0.000154
59
+ 3 3 0.000142
60
+ 3 4 0.000131
61
+ 3 5 0.000120
62
+ 3 6 0.000110
63
+ 3 7 0.000100
64
+ 3 8 0.000091
65
+ 3 9 0.000083
66
+ 4 0 0.000082
67
+ 4 1 0.000038
68
+ 4 2 0.000037
69
+ 4 3 0.000048
70
+ 4 4 0.000050
71
+ 4 5 0.000042
72
+ 4 6 0.000034
73
+ 4 7 0.000029
74
+ 4 8 0.000029
75
+ 4 9 0.000032
76
+ 5 0 0.000144
77
+ 5 1 0.000133
78
+ 5 2 0.000124
79
+ 5 3 0.000117
80
+ 5 4 0.000110
81
+ 5 5 0.000105
82
+ 5 6 0.000101
83
+ 5 7 0.000099
84
+ 5 8 0.000097
85
+ 5 9 0.000097
86
+ 6 0 0.000022
87
+ 6 1 0.000021
88
+ 6 2 0.000020
89
+ 6 3 0.000019
90
+ 6 4 0.000018
91
+ 6 5 0.000017
92
+ 6 6 0.000017
93
+ 6 7 0.000016
94
+ 6 8 0.000015
95
+ 6 9 0.000015
96
+ 7 0 0.000000
97
+ 7 1 0.000000
98
+ 7 2 0.000000
99
+ 7 3 0.000000
100
+ 7 4 0.000000
101
+ 7 5 0.000000
102
+ 7 6 0.000000
103
+ 7 7 0.000000
104
+ 7 8 0.000000
105
+ 7 9 0.000000
106
+ 8 0 0.000088
107
+ 8 1 0.000081
108
+ 8 2 0.000074
109
+ 8 3 0.000068
110
+ 8 4 0.000063
111
+ 8 5 0.000058
112
+ 8 6 0.000054
113
+ 8 7 0.000051
114
+ 8 8 0.000049
115
+ 8 9 0.000047
116
+ 9 0 0.000592
117
+ 9 1 0.000489
118
+ 9 2 0.000402
119
+ 9 3 0.000331
120
+ 9 4 0.000277
121
+ 9 5 0.000237
122
+ 9 6 0.000212
123
+ 9 7 0.000197
124
+ 9 8 0.000190
125
+ 9 9 0.000187
126
+ 10 0 0.000008
127
+ 10 1 0.000008
128
+ 10 2 0.000008
129
+ 10 3 0.000008
130
+ 10 4 0.000008
131
+ 10 5 0.000008
132
+ 10 6 0.000008
133
+ 10 7 0.000008
134
+ 10 8 0.000008
135
+ 10 9 0.000008
xenium_skin_mixed/sample15/log/Akap9.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Akap9
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 636 0.699932 0.000060 100 false 10 0.002463 0.000535
13
+ 1 680 636 0.356874 0.000067 100 false 10 0.000138 0.000072
14
+ 2 5552 636 0.739561 0.000131 100 false 10 0.000230 0.000152
15
+ 3 3231 636 0.698810 0.000100 100 false 10 0.000160 0.000112
16
+ 4 87 636 0.219009 0.000030 100 false 10 0.000581 0.000066
17
+ 5 96 636 0.674556 0.000065 100 false 10 0.000119 0.000079
18
+ 6 1210 636 0.334413 0.000072 100 false 10 0.000813 0.000103
19
+ 7 3 636 0.198804 0.000014 100 false 10 0.000304 0.000045
20
+ 8 448 636 0.544531 0.000087 100 false 10 0.000561 0.000110
21
+ 9 332 636 0.410216 0.000116 100 false 10 0.001367 0.000264
22
+ 10 82 636 0.217147 0.000070 100 false 10 0.000488 0.000118
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.002463
27
+ 0 1 0.001436
28
+ 0 2 0.000622
29
+ 0 3 0.000202
30
+ 0 4 0.000201
31
+ 0 5 0.000410
32
+ 0 6 0.000598
33
+ 0 7 0.000676
34
+ 0 8 0.000644
35
+ 0 9 0.000535
36
+ 1 0 0.000138
37
+ 1 1 0.000119
38
+ 1 2 0.000104
39
+ 1 3 0.000093
40
+ 1 4 0.000084
41
+ 1 5 0.000078
42
+ 1 6 0.000074
43
+ 1 7 0.000072
44
+ 1 8 0.000072
45
+ 1 9 0.000072
46
+ 2 0 0.000230
47
+ 2 1 0.000215
48
+ 2 2 0.000202
49
+ 2 3 0.000190
50
+ 2 4 0.000180
51
+ 2 5 0.000171
52
+ 2 6 0.000164
53
+ 2 7 0.000158
54
+ 2 8 0.000154
55
+ 2 9 0.000152
56
+ 3 0 0.000160
57
+ 3 1 0.000140
58
+ 3 2 0.000125
59
+ 3 3 0.000115
60
+ 3 4 0.000110
61
+ 3 5 0.000108
62
+ 3 6 0.000108
63
+ 3 7 0.000109
64
+ 3 8 0.000110
65
+ 3 9 0.000112
66
+ 4 0 0.000581
67
+ 4 1 0.000315
68
+ 4 2 0.000119
69
+ 4 3 0.000044
70
+ 4 4 0.000089
71
+ 4 5 0.000162
72
+ 4 6 0.000186
73
+ 4 7 0.000161
74
+ 4 8 0.000112
75
+ 4 9 0.000066
76
+ 5 0 0.000119
77
+ 5 1 0.000113
78
+ 5 2 0.000106
79
+ 5 3 0.000101
80
+ 5 4 0.000096
81
+ 5 5 0.000092
82
+ 5 6 0.000088
83
+ 5 7 0.000085
84
+ 5 8 0.000082
85
+ 5 9 0.000079
86
+ 6 0 0.000813
87
+ 6 1 0.000725
88
+ 6 2 0.000636
89
+ 6 3 0.000545
90
+ 6 4 0.000454
91
+ 6 5 0.000364
92
+ 6 6 0.000279
93
+ 6 7 0.000203
94
+ 6 8 0.000143
95
+ 6 9 0.000103
96
+ 7 0 0.000304
97
+ 7 1 0.000234
98
+ 7 2 0.000162
99
+ 7 3 0.000096
100
+ 7 4 0.000045
101
+ 7 5 0.000013
102
+ 7 6 0.000005
103
+ 7 7 0.000014
104
+ 7 8 0.000031
105
+ 7 9 0.000045
106
+ 8 0 0.000561
107
+ 8 1 0.000476
108
+ 8 2 0.000397
109
+ 8 3 0.000323
110
+ 8 4 0.000257
111
+ 8 5 0.000198
112
+ 8 6 0.000150
113
+ 8 7 0.000115
114
+ 8 8 0.000101
115
+ 8 9 0.000110
116
+ 9 0 0.001367
117
+ 9 1 0.000849
118
+ 9 2 0.000547
119
+ 9 3 0.000477
120
+ 9 4 0.000528
121
+ 9 5 0.000562
122
+ 9 6 0.000532
123
+ 9 7 0.000451
124
+ 9 8 0.000352
125
+ 9 9 0.000264
126
+ 10 0 0.000488
127
+ 10 1 0.000236
128
+ 10 2 0.000109
129
+ 10 3 0.000096
130
+ 10 4 0.000140
131
+ 10 5 0.000181
132
+ 10 6 0.000194
133
+ 10 7 0.000181
134
+ 10 8 0.000151
135
+ 10 9 0.000118
xenium_skin_mixed/sample15/log/Alox5.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Alox5
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 588 0.333787 0.000677 100 false 10 0.002745 0.000773
13
+ 1 680 588 0.288976 0.000004 100 false 10 0.000011 0.000006
14
+ 2 5552 588 0.777363 0.000036 100 false 10 0.000050 0.000043
15
+ 3 3231 588 0.295047 0.000058 100 false 10 0.000129 0.000076
16
+ 4 87 588 0.715728 0.000890 100 false 10 0.120863 0.022877
17
+ 5 96 588 0.862616 0.000563 100 false 10 0.001020 0.000588
18
+ 6 1210 588 0.676140 0.000478 100 false 10 0.000542 0.000486
19
+ 7 3 588 0.000000 0.000000 1 true 10 0.000000 0.000000
20
+ 8 448 588 0.392070 0.000015 100 false 10 0.000015 0.000015
21
+ 9 332 588 0.333149 0.000001 100 false 10 0.000002 0.000002
22
+ 10 82 588 0.571234 0.000287 100 false 10 0.000663 0.000342
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.002745
27
+ 0 1 0.001428
28
+ 0 2 0.001019
29
+ 0 3 0.001184
30
+ 0 4 0.001392
31
+ 0 5 0.001431
32
+ 0 6 0.001313
33
+ 0 7 0.001114
34
+ 0 8 0.000911
35
+ 0 9 0.000773
36
+ 1 0 0.000011
37
+ 1 1 0.000010
38
+ 1 2 0.000009
39
+ 1 3 0.000009
40
+ 1 4 0.000008
41
+ 1 5 0.000008
42
+ 1 6 0.000007
43
+ 1 7 0.000007
44
+ 1 8 0.000006
45
+ 1 9 0.000006
46
+ 2 0 0.000050
47
+ 2 1 0.000049
48
+ 2 2 0.000048
49
+ 2 3 0.000047
50
+ 2 4 0.000046
51
+ 2 5 0.000045
52
+ 2 6 0.000044
53
+ 2 7 0.000044
54
+ 2 8 0.000043
55
+ 2 9 0.000043
56
+ 3 0 0.000129
57
+ 3 1 0.000107
58
+ 3 2 0.000088
59
+ 3 3 0.000074
60
+ 3 4 0.000066
61
+ 3 5 0.000066
62
+ 3 6 0.000070
63
+ 3 7 0.000075
64
+ 3 8 0.000077
65
+ 3 9 0.000076
66
+ 4 0 0.120863
67
+ 4 1 0.073568
68
+ 4 2 0.035037
69
+ 4 3 0.010283
70
+ 4 4 0.002256
71
+ 4 5 0.007864
72
+ 4 6 0.018009
73
+ 4 7 0.024947
74
+ 4 8 0.026289
75
+ 4 9 0.022877
76
+ 5 0 0.001020
77
+ 5 1 0.000918
78
+ 5 2 0.000834
79
+ 5 3 0.000765
80
+ 5 4 0.000711
81
+ 5 5 0.000667
82
+ 5 6 0.000634
83
+ 5 7 0.000611
84
+ 5 8 0.000596
85
+ 5 9 0.000588
86
+ 6 0 0.000542
87
+ 6 1 0.000528
88
+ 6 2 0.000516
89
+ 6 3 0.000507
90
+ 6 4 0.000501
91
+ 6 5 0.000496
92
+ 6 6 0.000493
93
+ 6 7 0.000490
94
+ 6 8 0.000488
95
+ 6 9 0.000486
96
+ 7 0 0.000000
97
+ 7 1 0.000000
98
+ 7 2 0.000000
99
+ 7 3 0.000000
100
+ 7 4 0.000000
101
+ 7 5 0.000000
102
+ 7 6 0.000000
103
+ 7 7 0.000000
104
+ 7 8 0.000000
105
+ 7 9 0.000000
106
+ 8 0 0.000015
107
+ 8 1 0.000015
108
+ 8 2 0.000015
109
+ 8 3 0.000015
110
+ 8 4 0.000015
111
+ 8 5 0.000015
112
+ 8 6 0.000015
113
+ 8 7 0.000015
114
+ 8 8 0.000015
115
+ 8 9 0.000015
116
+ 9 0 0.000002
117
+ 9 1 0.000002
118
+ 9 2 0.000002
119
+ 9 3 0.000002
120
+ 9 4 0.000002
121
+ 9 5 0.000002
122
+ 9 6 0.000002
123
+ 9 7 0.000002
124
+ 9 8 0.000002
125
+ 9 9 0.000002
126
+ 10 0 0.000663
127
+ 10 1 0.000467
128
+ 10 2 0.000369
129
+ 10 3 0.000345
130
+ 10 4 0.000357
131
+ 10 5 0.000376
132
+ 10 6 0.000385
133
+ 10 7 0.000380
134
+ 10 8 0.000364
135
+ 10 9 0.000342
xenium_skin_mixed/sample15/log/Amy2a5.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Amy2a5
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 608 0.243009 0.000039 100 false 10 0.001613 0.000360
13
+ 1 680 608 0.515620 0.000081 100 false 10 0.000460 0.000182
14
+ 2 5552 608 0.479919 0.000079 100 false 10 0.001552 0.000131
15
+ 3 3231 608 0.248773 0.000124 100 false 10 0.000159 0.000134
16
+ 4 87 608 0.430104 0.000022 100 false 10 0.001337 0.000148
17
+ 5 96 608 0.689426 0.000055 100 false 10 0.000167 0.000077
18
+ 6 1210 608 0.144599 0.000099 100 false 10 0.000855 0.000236
19
+ 7 3 608 0.000000 0.000000 1 true 10 0.000000 0.000000
20
+ 8 448 608 0.620129 0.000080 100 false 10 0.000110 0.000094
21
+ 9 332 608 0.618387 0.000043 100 false 10 0.000068 0.000045
22
+ 10 82 608 0.279085 0.000015 100 false 10 0.000175 0.000022
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.001613
27
+ 0 1 0.001238
28
+ 0 2 0.000821
29
+ 0 3 0.000423
30
+ 0 4 0.000143
31
+ 0 5 0.000057
32
+ 0 6 0.000126
33
+ 0 7 0.000237
34
+ 0 8 0.000321
35
+ 0 9 0.000360
36
+ 1 0 0.000460
37
+ 1 1 0.000378
38
+ 1 2 0.000298
39
+ 1 3 0.000222
40
+ 1 4 0.000161
41
+ 1 5 0.000126
42
+ 1 6 0.000125
43
+ 1 7 0.000151
44
+ 1 8 0.000176
45
+ 1 9 0.000182
46
+ 2 0 0.001552
47
+ 2 1 0.001396
48
+ 2 2 0.001222
49
+ 2 3 0.001027
50
+ 2 4 0.000819
51
+ 2 5 0.000605
52
+ 2 6 0.000398
53
+ 2 7 0.000227
54
+ 2 8 0.000131
55
+ 2 9 0.000131
56
+ 3 0 0.000159
57
+ 3 1 0.000147
58
+ 3 2 0.000138
59
+ 3 3 0.000133
60
+ 3 4 0.000131
61
+ 3 5 0.000131
62
+ 3 6 0.000132
63
+ 3 7 0.000133
64
+ 3 8 0.000134
65
+ 3 9 0.000134
66
+ 4 0 0.001337
67
+ 4 1 0.001096
68
+ 4 2 0.000855
69
+ 4 3 0.000622
70
+ 4 4 0.000408
71
+ 4 5 0.000228
72
+ 4 6 0.000102
73
+ 4 7 0.000051
74
+ 4 8 0.000076
75
+ 4 9 0.000148
76
+ 5 0 0.000167
77
+ 5 1 0.000127
78
+ 5 2 0.000097
79
+ 5 3 0.000077
80
+ 5 4 0.000068
81
+ 5 5 0.000068
82
+ 5 6 0.000071
83
+ 5 7 0.000076
84
+ 5 8 0.000078
85
+ 5 9 0.000077
86
+ 6 0 0.000855
87
+ 6 1 0.000782
88
+ 6 2 0.000709
89
+ 6 3 0.000635
90
+ 6 4 0.000561
91
+ 6 5 0.000489
92
+ 6 6 0.000418
93
+ 6 7 0.000352
94
+ 6 8 0.000291
95
+ 6 9 0.000236
96
+ 7 0 0.000000
97
+ 7 1 0.000000
98
+ 7 2 0.000000
99
+ 7 3 0.000000
100
+ 7 4 0.000000
101
+ 7 5 0.000000
102
+ 7 6 0.000000
103
+ 7 7 0.000000
104
+ 7 8 0.000000
105
+ 7 9 0.000000
106
+ 8 0 0.000110
107
+ 8 1 0.000102
108
+ 8 2 0.000098
109
+ 8 3 0.000097
110
+ 8 4 0.000098
111
+ 8 5 0.000098
112
+ 8 6 0.000098
113
+ 8 7 0.000097
114
+ 8 8 0.000096
115
+ 8 9 0.000094
116
+ 9 0 0.000068
117
+ 9 1 0.000062
118
+ 9 2 0.000057
119
+ 9 3 0.000053
120
+ 9 4 0.000050
121
+ 9 5 0.000048
122
+ 9 6 0.000046
123
+ 9 7 0.000046
124
+ 9 8 0.000045
125
+ 9 9 0.000045
126
+ 10 0 0.000175
127
+ 10 1 0.000078
128
+ 10 2 0.000026
129
+ 10 3 0.000032
130
+ 10 4 0.000058
131
+ 10 5 0.000069
132
+ 10 6 0.000063
133
+ 10 7 0.000048
134
+ 10 8 0.000031
135
+ 10 9 0.000022
xenium_skin_mixed/sample15/log/Anln.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Anln
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 661 0.446446 0.000036 100 false 10 0.000078 0.000047
13
+ 1 680 661 0.502895 0.000011 100 false 10 0.000017 0.000013
14
+ 2 5552 661 0.728864 0.000815 100 false 10 0.001355 0.000920
15
+ 3 3231 661 0.387484 0.000014 100 false 10 0.000015 0.000015
16
+ 4 87 661 0.523808 0.000014 100 false 10 0.004417 0.000597
17
+ 5 96 661 0.908973 0.000006 100 false 10 0.000009 0.000007
18
+ 6 1210 661 0.300733 0.000027 100 false 10 0.000037 0.000033
19
+ 7 3 661 0.251444 0.000037 100 false 10 0.002435 0.000261
20
+ 8 448 661 0.744244 0.000002 100 false 10 0.000004 0.000004
21
+ 9 332 661 0.874032 0.000033 100 false 10 0.000121 0.000063
22
+ 10 82 661 0.525830 0.000018 100 false 10 0.000066 0.000020
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.000078
27
+ 0 1 0.000064
28
+ 0 2 0.000053
29
+ 0 3 0.000047
30
+ 0 4 0.000043
31
+ 0 5 0.000043
32
+ 0 6 0.000044
33
+ 0 7 0.000045
34
+ 0 8 0.000046
35
+ 0 9 0.000047
36
+ 1 0 0.000017
37
+ 1 1 0.000016
38
+ 1 2 0.000016
39
+ 1 3 0.000015
40
+ 1 4 0.000015
41
+ 1 5 0.000014
42
+ 1 6 0.000014
43
+ 1 7 0.000014
44
+ 1 8 0.000013
45
+ 1 9 0.000013
46
+ 2 0 0.001355
47
+ 2 1 0.001088
48
+ 2 2 0.000962
49
+ 2 3 0.000951
50
+ 2 4 0.000995
51
+ 2 5 0.001030
52
+ 2 6 0.001029
53
+ 2 7 0.000998
54
+ 2 8 0.000956
55
+ 2 9 0.000920
56
+ 3 0 0.000015
57
+ 3 1 0.000015
58
+ 3 2 0.000015
59
+ 3 3 0.000015
60
+ 3 4 0.000015
61
+ 3 5 0.000015
62
+ 3 6 0.000015
63
+ 3 7 0.000015
64
+ 3 8 0.000015
65
+ 3 9 0.000015
66
+ 4 0 0.004417
67
+ 4 1 0.003480
68
+ 4 2 0.002399
69
+ 4 3 0.001304
70
+ 4 4 0.000453
71
+ 4 5 0.000064
72
+ 4 6 0.000070
73
+ 4 7 0.000250
74
+ 4 8 0.000446
75
+ 4 9 0.000597
76
+ 5 0 0.000009
77
+ 5 1 0.000009
78
+ 5 2 0.000009
79
+ 5 3 0.000008
80
+ 5 4 0.000008
81
+ 5 5 0.000008
82
+ 5 6 0.000008
83
+ 5 7 0.000008
84
+ 5 8 0.000008
85
+ 5 9 0.000007
86
+ 6 0 0.000037
87
+ 6 1 0.000036
88
+ 6 2 0.000036
89
+ 6 3 0.000035
90
+ 6 4 0.000035
91
+ 6 5 0.000034
92
+ 6 6 0.000034
93
+ 6 7 0.000033
94
+ 6 8 0.000033
95
+ 6 9 0.000033
96
+ 7 0 0.002435
97
+ 7 1 0.002250
98
+ 7 2 0.002054
99
+ 7 3 0.001847
100
+ 7 4 0.001607
101
+ 7 5 0.001341
102
+ 7 6 0.001054
103
+ 7 7 0.000763
104
+ 7 8 0.000488
105
+ 7 9 0.000261
106
+ 8 0 0.000004
107
+ 8 1 0.000004
108
+ 8 2 0.000004
109
+ 8 3 0.000004
110
+ 8 4 0.000004
111
+ 8 5 0.000004
112
+ 8 6 0.000004
113
+ 8 7 0.000004
114
+ 8 8 0.000004
115
+ 8 9 0.000004
116
+ 9 0 0.000121
117
+ 9 1 0.000112
118
+ 9 2 0.000104
119
+ 9 3 0.000097
120
+ 9 4 0.000090
121
+ 9 5 0.000083
122
+ 9 6 0.000077
123
+ 9 7 0.000072
124
+ 9 8 0.000067
125
+ 9 9 0.000063
126
+ 10 0 0.000066
127
+ 10 1 0.000057
128
+ 10 2 0.000049
129
+ 10 3 0.000042
130
+ 10 4 0.000036
131
+ 10 5 0.000030
132
+ 10 6 0.000026
133
+ 10 7 0.000023
134
+ 10 8 0.000021
135
+ 10 9 0.000020
xenium_skin_mixed/sample15/log/Ap2a2.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Ap2a2
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 624 0.762323 0.000349 100 false 10 0.001392 0.000835
13
+ 1 680 624 0.408039 0.000150 100 false 10 0.000255 0.000200
14
+ 2 5552 624 0.773813 0.000099 100 false 10 0.000151 0.000120
15
+ 3 3231 624 0.688161 0.000249 100 false 10 0.000692 0.000386
16
+ 4 87 624 0.210795 0.000024 100 false 10 0.000158 0.000049
17
+ 5 96 624 0.682802 0.000253 100 false 10 0.000324 0.000266
18
+ 6 1210 624 0.824744 0.003432 100 false 10 0.019408 0.006228
19
+ 7 3 624 0.000000 0.000000 1 true 10 0.000000 0.000000
20
+ 8 448 624 0.855297 0.000211 100 false 10 0.001496 0.000288
21
+ 9 332 624 0.781827 0.000099 100 false 10 0.000145 0.000105
22
+ 10 82 624 0.740238 0.000064 100 false 10 0.015470 0.003609
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.001392
27
+ 0 1 0.001664
28
+ 0 2 0.001244
29
+ 0 3 0.000965
30
+ 0 4 0.001123
31
+ 0 5 0.001072
32
+ 0 6 0.000843
33
+ 0 7 0.000764
34
+ 0 8 0.000837
35
+ 0 9 0.000835
36
+ 1 0 0.000255
37
+ 1 1 0.000254
38
+ 1 2 0.000234
39
+ 1 3 0.000228
40
+ 1 4 0.000226
41
+ 1 5 0.000217
42
+ 1 6 0.000212
43
+ 1 7 0.000211
44
+ 1 8 0.000207
45
+ 1 9 0.000200
46
+ 2 0 0.000151
47
+ 2 1 0.000127
48
+ 2 2 0.000136
49
+ 2 3 0.000136
50
+ 2 4 0.000127
51
+ 2 5 0.000121
52
+ 2 6 0.000122
53
+ 2 7 0.000124
54
+ 2 8 0.000124
55
+ 2 9 0.000120
56
+ 3 0 0.000692
57
+ 3 1 0.000615
58
+ 3 2 0.000537
59
+ 3 3 0.000459
60
+ 3 4 0.000389
61
+ 3 5 0.000348
62
+ 3 6 0.000366
63
+ 3 7 0.000414
64
+ 3 8 0.000417
65
+ 3 9 0.000386
66
+ 4 0 0.000158
67
+ 4 1 0.000085
68
+ 4 2 0.000050
69
+ 4 3 0.000046
70
+ 4 4 0.000058
71
+ 4 5 0.000070
72
+ 4 6 0.000073
73
+ 4 7 0.000068
74
+ 4 8 0.000059
75
+ 4 9 0.000049
76
+ 5 0 0.000324
77
+ 5 1 0.000297
78
+ 5 2 0.000285
79
+ 5 3 0.000286
80
+ 5 4 0.000288
81
+ 5 5 0.000286
82
+ 5 6 0.000281
83
+ 5 7 0.000274
84
+ 5 8 0.000269
85
+ 5 9 0.000266
86
+ 6 0 0.019408
87
+ 6 1 0.013642
88
+ 6 2 0.009435
89
+ 6 3 0.006703
90
+ 6 4 0.005273
91
+ 6 5 0.004868
92
+ 6 6 0.005105
93
+ 6 7 0.005592
94
+ 6 8 0.006022
95
+ 6 9 0.006228
96
+ 7 0 0.000000
97
+ 7 1 0.000000
98
+ 7 2 0.000000
99
+ 7 3 0.000000
100
+ 7 4 0.000000
101
+ 7 5 0.000000
102
+ 7 6 0.000000
103
+ 7 7 0.000000
104
+ 7 8 0.000000
105
+ 7 9 0.000000
106
+ 8 0 0.001496
107
+ 8 1 0.001240
108
+ 8 2 0.001014
109
+ 8 3 0.000820
110
+ 8 4 0.000659
111
+ 8 5 0.000530
112
+ 8 6 0.000432
113
+ 8 7 0.000361
114
+ 8 8 0.000315
115
+ 8 9 0.000288
116
+ 9 0 0.000145
117
+ 9 1 0.000134
118
+ 9 2 0.000125
119
+ 9 3 0.000118
120
+ 9 4 0.000113
121
+ 9 5 0.000109
122
+ 9 6 0.000107
123
+ 9 7 0.000105
124
+ 9 8 0.000105
125
+ 9 9 0.000105
126
+ 10 0 0.015470
127
+ 10 1 0.013002
128
+ 10 2 0.010795
129
+ 10 3 0.008972
130
+ 10 4 0.007533
131
+ 10 5 0.006410
132
+ 10 6 0.005519
133
+ 10 7 0.004786
134
+ 10 8 0.004164
135
+ 10 9 0.003609
xenium_skin_mixed/sample15/log/Ap3b1.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Ap3b1
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 620 0.432170 0.000075 100 false 10 0.000895 0.000175
13
+ 1 680 620 0.401844 0.000117 100 false 10 0.001127 0.000275
14
+ 2 5552 620 0.383725 0.000078 100 false 10 0.000512 0.000138
15
+ 3 3231 620 0.382932 0.000101 100 false 10 0.000583 0.000279
16
+ 4 87 620 0.000000 0.000017 100 false 10 0.000038 0.000030
17
+ 5 96 620 0.384214 0.000105 100 false 10 0.000285 0.000102
18
+ 6 1210 620 0.268864 0.000181 100 false 10 0.000319 0.000205
19
+ 7 3 620 0.000000 0.000000 24 true 10 0.000129 0.000015
20
+ 8 448 620 0.490787 0.000064 100 false 10 0.000192 0.000123
21
+ 9 332 620 0.638492 0.000056 100 false 10 0.000489 0.000087
22
+ 10 82 620 0.151560 0.000077 100 false 10 0.000808 0.000223
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.000895
27
+ 0 1 0.000381
28
+ 0 2 0.000159
29
+ 0 3 0.000189
30
+ 0 4 0.000297
31
+ 0 5 0.000361
32
+ 0 6 0.000360
33
+ 0 7 0.000309
34
+ 0 8 0.000238
35
+ 0 9 0.000175
36
+ 1 0 0.001127
37
+ 1 1 0.000837
38
+ 1 2 0.000593
39
+ 1 3 0.000412
40
+ 1 4 0.000298
41
+ 1 5 0.000243
42
+ 1 6 0.000229
43
+ 1 7 0.000240
44
+ 1 8 0.000259
45
+ 1 9 0.000275
46
+ 2 0 0.000512
47
+ 2 1 0.000458
48
+ 2 2 0.000406
49
+ 2 3 0.000355
50
+ 2 4 0.000307
51
+ 2 5 0.000262
52
+ 2 6 0.000222
53
+ 2 7 0.000187
54
+ 2 8 0.000159
55
+ 2 9 0.000138
56
+ 3 0 0.000583
57
+ 3 1 0.000540
58
+ 3 2 0.000499
59
+ 3 3 0.000460
60
+ 3 4 0.000424
61
+ 3 5 0.000390
62
+ 3 6 0.000359
63
+ 3 7 0.000330
64
+ 3 8 0.000303
65
+ 3 9 0.000279
66
+ 4 0 0.000038
67
+ 4 1 0.000045
68
+ 4 2 0.000035
69
+ 4 3 0.000035
70
+ 4 4 0.000037
71
+ 4 5 0.000034
72
+ 4 6 0.000031
73
+ 4 7 0.000031
74
+ 4 8 0.000032
75
+ 4 9 0.000030
76
+ 5 0 0.000285
77
+ 5 1 0.000243
78
+ 5 2 0.000207
79
+ 5 3 0.000177
80
+ 5 4 0.000154
81
+ 5 5 0.000135
82
+ 5 6 0.000121
83
+ 5 7 0.000112
84
+ 5 8 0.000105
85
+ 5 9 0.000102
86
+ 6 0 0.000319
87
+ 6 1 0.000289
88
+ 6 2 0.000267
89
+ 6 3 0.000252
90
+ 6 4 0.000241
91
+ 6 5 0.000233
92
+ 6 6 0.000226
93
+ 6 7 0.000219
94
+ 6 8 0.000212
95
+ 6 9 0.000205
96
+ 7 0 0.000129
97
+ 7 1 0.000116
98
+ 7 2 0.000103
99
+ 7 3 0.000089
100
+ 7 4 0.000075
101
+ 7 5 0.000060
102
+ 7 6 0.000046
103
+ 7 7 0.000034
104
+ 7 8 0.000023
105
+ 7 9 0.000015
106
+ 8 0 0.000192
107
+ 8 1 0.000183
108
+ 8 2 0.000174
109
+ 8 3 0.000166
110
+ 8 4 0.000158
111
+ 8 5 0.000151
112
+ 8 6 0.000143
113
+ 8 7 0.000137
114
+ 8 8 0.000130
115
+ 8 9 0.000123
116
+ 9 0 0.000489
117
+ 9 1 0.000421
118
+ 9 2 0.000355
119
+ 9 3 0.000291
120
+ 9 4 0.000232
121
+ 9 5 0.000182
122
+ 9 6 0.000141
123
+ 9 7 0.000113
124
+ 9 8 0.000095
125
+ 9 9 0.000087
126
+ 10 0 0.000808
127
+ 10 1 0.000667
128
+ 10 2 0.000511
129
+ 10 3 0.000345
130
+ 10 4 0.000192
131
+ 10 5 0.000099
132
+ 10 6 0.000115
133
+ 10 7 0.000198
134
+ 10 8 0.000240
135
+ 10 9 0.000223
xenium_skin_mixed/sample15/log/Apaf1.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Apaf1
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 602 0.773324 0.000103 100 false 10 0.000326 0.000159
13
+ 1 680 602 0.812954 0.000084 100 false 10 0.000380 0.000135
14
+ 2 5552 602 0.588325 0.000023 100 false 10 0.000040 0.000029
15
+ 3 3231 602 0.726626 0.000162 100 false 10 0.000370 0.000208
16
+ 4 87 602 0.183929 0.000006 100 false 10 0.000113 0.000021
17
+ 5 96 602 0.836534 0.000103 100 false 10 0.000274 0.000133
18
+ 6 1210 602 0.745861 0.000096 100 false 10 0.000780 0.000176
19
+ 7 3 602 0.000000 0.000000 1 true 10 0.000000 0.000000
20
+ 8 448 602 0.809802 0.000042 100 false 10 0.000065 0.000049
21
+ 9 332 602 0.276543 0.000033 100 false 10 0.000046 0.000036
22
+ 10 82 602 0.427719 0.000048 100 false 10 0.001204 0.000274
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.000326
27
+ 0 1 0.000239
28
+ 0 2 0.000211
29
+ 0 3 0.000211
30
+ 0 4 0.000215
31
+ 0 5 0.000211
32
+ 0 6 0.000200
33
+ 0 7 0.000186
34
+ 0 8 0.000171
35
+ 0 9 0.000159
36
+ 1 0 0.000380
37
+ 1 1 0.000343
38
+ 1 2 0.000306
39
+ 1 3 0.000273
40
+ 1 4 0.000244
41
+ 1 5 0.000219
42
+ 1 6 0.000196
43
+ 1 7 0.000174
44
+ 1 8 0.000153
45
+ 1 9 0.000135
46
+ 2 0 0.000040
47
+ 2 1 0.000032
48
+ 2 2 0.000030
49
+ 2 3 0.000031
50
+ 2 4 0.000032
51
+ 2 5 0.000032
52
+ 2 6 0.000032
53
+ 2 7 0.000031
54
+ 2 8 0.000030
55
+ 2 9 0.000029
56
+ 3 0 0.000370
57
+ 3 1 0.000300
58
+ 3 2 0.000245
59
+ 3 3 0.000208
60
+ 3 4 0.000188
61
+ 3 5 0.000184
62
+ 3 6 0.000189
63
+ 3 7 0.000197
64
+ 3 8 0.000205
65
+ 3 9 0.000208
66
+ 4 0 0.000113
67
+ 4 1 0.000085
68
+ 4 2 0.000058
69
+ 4 3 0.000035
70
+ 4 4 0.000019
71
+ 4 5 0.000010
72
+ 4 6 0.000008
73
+ 4 7 0.000011
74
+ 4 8 0.000016
75
+ 4 9 0.000021
76
+ 5 0 0.000274
77
+ 5 1 0.000243
78
+ 5 2 0.000217
79
+ 5 3 0.000196
80
+ 5 4 0.000178
81
+ 5 5 0.000163
82
+ 5 6 0.000152
83
+ 5 7 0.000144
84
+ 5 8 0.000138
85
+ 5 9 0.000133
86
+ 6 0 0.000780
87
+ 6 1 0.000688
88
+ 6 2 0.000601
89
+ 6 3 0.000518
90
+ 6 4 0.000441
91
+ 6 5 0.000370
92
+ 6 6 0.000308
93
+ 6 7 0.000255
94
+ 6 8 0.000211
95
+ 6 9 0.000176
96
+ 7 0 0.000000
97
+ 7 1 0.000000
98
+ 7 2 0.000000
99
+ 7 3 0.000000
100
+ 7 4 0.000000
101
+ 7 5 0.000000
102
+ 7 6 0.000000
103
+ 7 7 0.000000
104
+ 7 8 0.000000
105
+ 7 9 0.000000
106
+ 8 0 0.000065
107
+ 8 1 0.000059
108
+ 8 2 0.000054
109
+ 8 3 0.000051
110
+ 8 4 0.000049
111
+ 8 5 0.000048
112
+ 8 6 0.000048
113
+ 8 7 0.000048
114
+ 8 8 0.000049
115
+ 8 9 0.000049
116
+ 9 0 0.000046
117
+ 9 1 0.000042
118
+ 9 2 0.000038
119
+ 9 3 0.000036
120
+ 9 4 0.000034
121
+ 9 5 0.000034
122
+ 9 6 0.000034
123
+ 9 7 0.000035
124
+ 9 8 0.000035
125
+ 9 9 0.000036
126
+ 10 0 0.001204
127
+ 10 1 0.000880
128
+ 10 2 0.000583
129
+ 10 3 0.000332
130
+ 10 4 0.000156
131
+ 10 5 0.000086
132
+ 10 6 0.000126
133
+ 10 7 0.000215
134
+ 10 8 0.000274
135
+ 10 9 0.000274
xenium_skin_mixed/sample15/log/Apc.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Apc
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 669 0.505006 0.000068 100 false 10 0.004448 0.001737
13
+ 1 680 669 0.727057 0.000163 100 false 10 0.000479 0.000219
14
+ 2 5552 669 0.747312 0.000076 100 false 10 0.000300 0.000106
15
+ 3 3231 669 0.577338 0.000052 100 false 10 0.000056 0.000055
16
+ 4 87 669 0.132652 0.000039 100 false 10 0.001744 0.000302
17
+ 5 96 669 0.948917 0.000014 100 false 10 0.000032 0.000021
18
+ 6 1210 669 0.701223 0.000059 100 false 10 0.000145 0.000068
19
+ 7 3 669 0.229179 0.000000 100 false 10 0.000253 0.000005
20
+ 8 448 669 0.794831 0.000064 100 false 10 0.000101 0.000068
21
+ 9 332 669 0.720957 0.000080 100 false 10 0.000108 0.000085
22
+ 10 82 669 0.489223 0.000028 100 false 10 0.000970 0.000082
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.004448
27
+ 0 1 0.004160
28
+ 0 2 0.003873
29
+ 0 3 0.003587
30
+ 0 4 0.003300
31
+ 0 5 0.003007
32
+ 0 6 0.002708
33
+ 0 7 0.002397
34
+ 0 8 0.002074
35
+ 0 9 0.001737
36
+ 1 0 0.000479
37
+ 1 1 0.000406
38
+ 1 2 0.000349
39
+ 1 3 0.000306
40
+ 1 4 0.000276
41
+ 1 5 0.000256
42
+ 1 6 0.000243
43
+ 1 7 0.000234
44
+ 1 8 0.000227
45
+ 1 9 0.000219
46
+ 2 0 0.000300
47
+ 2 1 0.000230
48
+ 2 2 0.000175
49
+ 2 3 0.000134
50
+ 2 4 0.000108
51
+ 2 5 0.000095
52
+ 2 6 0.000091
53
+ 2 7 0.000094
54
+ 2 8 0.000100
55
+ 2 9 0.000106
56
+ 3 0 0.000056
57
+ 3 1 0.000055
58
+ 3 2 0.000055
59
+ 3 3 0.000055
60
+ 3 4 0.000055
61
+ 3 5 0.000055
62
+ 3 6 0.000055
63
+ 3 7 0.000055
64
+ 3 8 0.000055
65
+ 3 9 0.000055
66
+ 4 0 0.001744
67
+ 4 1 0.000991
68
+ 4 2 0.000414
69
+ 4 3 0.000102
70
+ 4 4 0.000083
71
+ 4 5 0.000250
72
+ 4 6 0.000412
73
+ 4 7 0.000467
74
+ 4 8 0.000414
75
+ 4 9 0.000302
76
+ 5 0 0.000032
77
+ 5 1 0.000030
78
+ 5 2 0.000029
79
+ 5 3 0.000027
80
+ 5 4 0.000026
81
+ 5 5 0.000025
82
+ 5 6 0.000024
83
+ 5 7 0.000023
84
+ 5 8 0.000022
85
+ 5 9 0.000021
86
+ 6 0 0.000145
87
+ 6 1 0.000124
88
+ 6 2 0.000106
89
+ 6 3 0.000091
90
+ 6 4 0.000080
91
+ 6 5 0.000073
92
+ 6 6 0.000069
93
+ 6 7 0.000067
94
+ 6 8 0.000067
95
+ 6 9 0.000068
96
+ 7 0 0.000253
97
+ 7 1 0.000227
98
+ 7 2 0.000196
99
+ 7 3 0.000160
100
+ 7 4 0.000120
101
+ 7 5 0.000079
102
+ 7 6 0.000042
103
+ 7 7 0.000017
104
+ 7 8 0.000005
105
+ 7 9 0.000005
106
+ 8 0 0.000101
107
+ 8 1 0.000093
108
+ 8 2 0.000087
109
+ 8 3 0.000081
110
+ 8 4 0.000077
111
+ 8 5 0.000073
112
+ 8 6 0.000071
113
+ 8 7 0.000069
114
+ 8 8 0.000069
115
+ 8 9 0.000068
116
+ 9 0 0.000108
117
+ 9 1 0.000101
118
+ 9 2 0.000096
119
+ 9 3 0.000091
120
+ 9 4 0.000088
121
+ 9 5 0.000086
122
+ 9 6 0.000085
123
+ 9 7 0.000084
124
+ 9 8 0.000084
125
+ 9 9 0.000085
126
+ 10 0 0.000970
127
+ 10 1 0.000574
128
+ 10 2 0.000237
129
+ 10 3 0.000066
130
+ 10 4 0.000121
131
+ 10 5 0.000245
132
+ 10 6 0.000283
133
+ 10 7 0.000236
134
+ 10 8 0.000153
135
+ 10 9 0.000082
xenium_skin_mixed/sample15/log/Apip.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Apip
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 593 0.254407 0.000029 100 false 10 0.000037 0.000030
13
+ 1 680 593 0.289543 0.000033 100 false 10 0.000090 0.000054
14
+ 2 5552 593 0.587788 0.000017 100 false 10 0.000042 0.000019
15
+ 3 3231 593 0.575973 0.000031 100 false 10 0.000035 0.000034
16
+ 4 87 593 0.172089 0.000006 100 false 10 0.000168 0.000020
17
+ 5 96 593 0.776393 0.000031 100 false 10 0.000050 0.000041
18
+ 6 1210 593 0.391849 0.000045 100 false 10 0.000178 0.000106
19
+ 7 3 593 0.000000 0.000000 1 true 10 0.000000 0.000000
20
+ 8 448 593 0.825394 0.000068 100 false 10 0.000558 0.000141
21
+ 9 332 593 0.833496 0.000013 100 false 10 0.000024 0.000020
22
+ 10 82 593 0.240327 0.000017 100 false 10 0.000204 0.000022
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.000037
27
+ 0 1 0.000032
28
+ 0 2 0.000031
29
+ 0 3 0.000031
30
+ 0 4 0.000032
31
+ 0 5 0.000032
32
+ 0 6 0.000032
33
+ 0 7 0.000031
34
+ 0 8 0.000031
35
+ 0 9 0.000030
36
+ 1 0 0.000090
37
+ 1 1 0.000081
38
+ 1 2 0.000074
39
+ 1 3 0.000068
40
+ 1 4 0.000064
41
+ 1 5 0.000061
42
+ 1 6 0.000059
43
+ 1 7 0.000058
44
+ 1 8 0.000056
45
+ 1 9 0.000054
46
+ 2 0 0.000042
47
+ 2 1 0.000038
48
+ 2 2 0.000034
49
+ 2 3 0.000030
50
+ 2 4 0.000027
51
+ 2 5 0.000025
52
+ 2 6 0.000023
53
+ 2 7 0.000021
54
+ 2 8 0.000020
55
+ 2 9 0.000019
56
+ 3 0 0.000035
57
+ 3 1 0.000035
58
+ 3 2 0.000034
59
+ 3 3 0.000034
60
+ 3 4 0.000034
61
+ 3 5 0.000034
62
+ 3 6 0.000034
63
+ 3 7 0.000034
64
+ 3 8 0.000034
65
+ 3 9 0.000034
66
+ 4 0 0.000168
67
+ 4 1 0.000074
68
+ 4 2 0.000018
69
+ 4 3 0.000010
70
+ 4 4 0.000028
71
+ 4 5 0.000045
72
+ 4 6 0.000051
73
+ 4 7 0.000045
74
+ 4 8 0.000033
75
+ 4 9 0.000020
76
+ 5 0 0.000050
77
+ 5 1 0.000046
78
+ 5 2 0.000043
79
+ 5 3 0.000042
80
+ 5 4 0.000041
81
+ 5 5 0.000041
82
+ 5 6 0.000041
83
+ 5 7 0.000041
84
+ 5 8 0.000041
85
+ 5 9 0.000041
86
+ 6 0 0.000178
87
+ 6 1 0.000169
88
+ 6 2 0.000161
89
+ 6 3 0.000153
90
+ 6 4 0.000146
91
+ 6 5 0.000138
92
+ 6 6 0.000130
93
+ 6 7 0.000122
94
+ 6 8 0.000114
95
+ 6 9 0.000106
96
+ 7 0 0.000000
97
+ 7 1 0.000000
98
+ 7 2 0.000000
99
+ 7 3 0.000000
100
+ 7 4 0.000000
101
+ 7 5 0.000000
102
+ 7 6 0.000000
103
+ 7 7 0.000000
104
+ 7 8 0.000000
105
+ 7 9 0.000000
106
+ 8 0 0.000558
107
+ 8 1 0.000496
108
+ 8 2 0.000436
109
+ 8 3 0.000378
110
+ 8 4 0.000325
111
+ 8 5 0.000275
112
+ 8 6 0.000232
113
+ 8 7 0.000194
114
+ 8 8 0.000164
115
+ 8 9 0.000141
116
+ 9 0 0.000024
117
+ 9 1 0.000023
118
+ 9 2 0.000023
119
+ 9 3 0.000022
120
+ 9 4 0.000022
121
+ 9 5 0.000021
122
+ 9 6 0.000021
123
+ 9 7 0.000020
124
+ 9 8 0.000020
125
+ 9 9 0.000020
126
+ 10 0 0.000204
127
+ 10 1 0.000083
128
+ 10 2 0.000027
129
+ 10 3 0.000037
130
+ 10 4 0.000066
131
+ 10 5 0.000078
132
+ 10 6 0.000070
133
+ 10 7 0.000052
134
+ 10 8 0.000033
135
+ 10 9 0.000022
xenium_skin_mixed/sample15/log/Arf2.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Arf2
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 622 0.716050 0.000036 100 false 10 0.002111 0.000088
13
+ 1 680 622 0.495755 0.000095 100 false 10 0.000380 0.000128
14
+ 2 5552 622 0.470201 0.000015 100 false 10 0.000020 0.000017
15
+ 3 3231 622 0.738458 0.000036 100 false 10 0.000089 0.000043
16
+ 4 87 622 0.216334 0.000028 100 false 10 0.000898 0.000195
17
+ 5 96 622 0.916985 0.000014 100 false 10 0.000032 0.000024
18
+ 6 1210 622 0.695824 0.000070 100 false 10 0.000093 0.000075
19
+ 7 3 622 0.202069 0.000001 100 false 10 0.000270 0.000019
20
+ 8 448 622 0.763401 0.000072 100 false 10 0.000105 0.000084
21
+ 9 332 622 0.637539 0.000032 100 false 10 0.000062 0.000041
22
+ 10 82 622 0.770210 0.000019 100 false 10 0.002120 0.000271
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.002111
27
+ 0 1 0.001922
28
+ 0 2 0.001729
29
+ 0 3 0.001520
30
+ 0 4 0.001288
31
+ 0 5 0.001028
32
+ 0 6 0.000744
33
+ 0 7 0.000455
34
+ 0 8 0.000211
35
+ 0 9 0.000088
36
+ 1 0 0.000380
37
+ 1 1 0.000322
38
+ 1 2 0.000271
39
+ 1 3 0.000227
40
+ 1 4 0.000192
41
+ 1 5 0.000164
42
+ 1 6 0.000144
43
+ 1 7 0.000131
44
+ 1 8 0.000126
45
+ 1 9 0.000128
46
+ 2 0 0.000020
47
+ 2 1 0.000019
48
+ 2 2 0.000018
49
+ 2 3 0.000018
50
+ 2 4 0.000018
51
+ 2 5 0.000017
52
+ 2 6 0.000017
53
+ 2 7 0.000017
54
+ 2 8 0.000017
55
+ 2 9 0.000017
56
+ 3 0 0.000089
57
+ 3 1 0.000080
58
+ 3 2 0.000072
59
+ 3 3 0.000065
60
+ 3 4 0.000059
61
+ 3 5 0.000054
62
+ 3 6 0.000050
63
+ 3 7 0.000047
64
+ 3 8 0.000045
65
+ 3 9 0.000043
66
+ 4 0 0.000898
67
+ 4 1 0.000623
68
+ 4 2 0.000349
69
+ 4 3 0.000129
70
+ 4 4 0.000036
71
+ 4 5 0.000084
72
+ 4 6 0.000177
73
+ 4 7 0.000232
74
+ 4 8 0.000234
75
+ 4 9 0.000195
76
+ 5 0 0.000032
77
+ 5 1 0.000031
78
+ 5 2 0.000030
79
+ 5 3 0.000029
80
+ 5 4 0.000028
81
+ 5 5 0.000027
82
+ 5 6 0.000027
83
+ 5 7 0.000026
84
+ 5 8 0.000025
85
+ 5 9 0.000024
86
+ 6 0 0.000093
87
+ 6 1 0.000085
88
+ 6 2 0.000079
89
+ 6 3 0.000076
90
+ 6 4 0.000075
91
+ 6 5 0.000074
92
+ 6 6 0.000075
93
+ 6 7 0.000075
94
+ 6 8 0.000075
95
+ 6 9 0.000075
96
+ 7 0 0.000270
97
+ 7 1 0.000218
98
+ 7 2 0.000164
99
+ 7 3 0.000112
100
+ 7 4 0.000065
101
+ 7 5 0.000029
102
+ 7 6 0.000008
103
+ 7 7 0.000002
104
+ 7 8 0.000008
105
+ 7 9 0.000019
106
+ 8 0 0.000105
107
+ 8 1 0.000094
108
+ 8 2 0.000090
109
+ 8 3 0.000088
110
+ 8 4 0.000087
111
+ 8 5 0.000087
112
+ 8 6 0.000088
113
+ 8 7 0.000087
114
+ 8 8 0.000086
115
+ 8 9 0.000084
116
+ 9 0 0.000062
117
+ 9 1 0.000053
118
+ 9 2 0.000046
119
+ 9 3 0.000043
120
+ 9 4 0.000041
121
+ 9 5 0.000040
122
+ 9 6 0.000040
123
+ 9 7 0.000041
124
+ 9 8 0.000041
125
+ 9 9 0.000041
126
+ 10 0 0.002120
127
+ 10 1 0.001440
128
+ 10 2 0.000806
129
+ 10 3 0.000328
130
+ 10 4 0.000182
131
+ 10 5 0.000378
132
+ 10 6 0.000565
133
+ 10 7 0.000568
134
+ 10 8 0.000436
135
+ 10 9 0.000271
xenium_skin_mixed/sample15/log/Arhgap17.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Arhgap17
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 619 0.677262 0.000031 100 false 10 0.000229 0.000058
13
+ 1 680 619 0.536864 0.000073 100 false 10 0.000246 0.000127
14
+ 2 5552 619 0.668438 0.000037 100 false 10 0.000094 0.000050
15
+ 3 3231 619 0.452281 0.000031 100 false 10 0.000034 0.000034
16
+ 4 87 619 0.498580 0.000014 100 false 10 0.001153 0.000220
17
+ 5 96 619 0.182201 0.000041 100 false 10 0.000132 0.000057
18
+ 6 1210 619 0.680273 0.000088 100 false 10 0.000365 0.000110
19
+ 7 3 619 0.000000 0.000000 1 true 10 0.000000 0.000000
20
+ 8 448 619 0.795647 0.000017 100 false 10 0.000037 0.000026
21
+ 9 332 619 0.744558 0.000029 100 false 10 0.000039 0.000035
22
+ 10 82 619 0.430849 0.000029 100 false 10 0.000050 0.000035
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.000229
27
+ 0 1 0.000170
28
+ 0 2 0.000122
29
+ 0 3 0.000085
30
+ 0 4 0.000060
31
+ 0 5 0.000047
32
+ 0 6 0.000043
33
+ 0 7 0.000045
34
+ 0 8 0.000051
35
+ 0 9 0.000058
36
+ 1 0 0.000246
37
+ 1 1 0.000174
38
+ 1 2 0.000130
39
+ 1 3 0.000114
40
+ 1 4 0.000116
41
+ 1 5 0.000127
42
+ 1 6 0.000135
43
+ 1 7 0.000138
44
+ 1 8 0.000134
45
+ 1 9 0.000127
46
+ 2 0 0.000094
47
+ 2 1 0.000075
48
+ 2 2 0.000062
49
+ 2 3 0.000054
50
+ 2 4 0.000051
51
+ 2 5 0.000051
52
+ 2 6 0.000051
53
+ 2 7 0.000052
54
+ 2 8 0.000051
55
+ 2 9 0.000050
56
+ 3 0 0.000034
57
+ 3 1 0.000034
58
+ 3 2 0.000034
59
+ 3 3 0.000034
60
+ 3 4 0.000034
61
+ 3 5 0.000034
62
+ 3 6 0.000034
63
+ 3 7 0.000034
64
+ 3 8 0.000034
65
+ 3 9 0.000034
66
+ 4 0 0.001153
67
+ 4 1 0.001023
68
+ 4 2 0.000898
69
+ 4 3 0.000781
70
+ 4 4 0.000669
71
+ 4 5 0.000565
72
+ 4 6 0.000467
73
+ 4 7 0.000376
74
+ 4 8 0.000293
75
+ 4 9 0.000220
76
+ 5 0 0.000132
77
+ 5 1 0.000121
78
+ 5 2 0.000110
79
+ 5 3 0.000100
80
+ 5 4 0.000090
81
+ 5 5 0.000081
82
+ 5 6 0.000074
83
+ 5 7 0.000067
84
+ 5 8 0.000061
85
+ 5 9 0.000057
86
+ 6 0 0.000365
87
+ 6 1 0.000308
88
+ 6 2 0.000259
89
+ 6 3 0.000218
90
+ 6 4 0.000185
91
+ 6 5 0.000159
92
+ 6 6 0.000139
93
+ 6 7 0.000125
94
+ 6 8 0.000116
95
+ 6 9 0.000110
96
+ 7 0 0.000000
97
+ 7 1 0.000000
98
+ 7 2 0.000000
99
+ 7 3 0.000000
100
+ 7 4 0.000000
101
+ 7 5 0.000000
102
+ 7 6 0.000000
103
+ 7 7 0.000000
104
+ 7 8 0.000000
105
+ 7 9 0.000000
106
+ 8 0 0.000037
107
+ 8 1 0.000036
108
+ 8 2 0.000034
109
+ 8 3 0.000032
110
+ 8 4 0.000031
111
+ 8 5 0.000030
112
+ 8 6 0.000029
113
+ 8 7 0.000028
114
+ 8 8 0.000027
115
+ 8 9 0.000026
116
+ 9 0 0.000039
117
+ 9 1 0.000038
118
+ 9 2 0.000037
119
+ 9 3 0.000036
120
+ 9 4 0.000035
121
+ 9 5 0.000035
122
+ 9 6 0.000035
123
+ 9 7 0.000035
124
+ 9 8 0.000035
125
+ 9 9 0.000035
126
+ 10 0 0.000050
127
+ 10 1 0.000034
128
+ 10 2 0.000040
129
+ 10 3 0.000041
130
+ 10 4 0.000037
131
+ 10 5 0.000034
132
+ 10 6 0.000034
133
+ 10 7 0.000035
134
+ 10 8 0.000036
135
+ 10 9 0.000035
xenium_skin_mixed/sample15/log/Arhgap35.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Arhgap35
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 639 0.619625 0.000014 100 false 10 0.000123 0.000031
13
+ 1 680 639 0.489368 0.000055 100 false 10 0.000613 0.000096
14
+ 2 5552 639 0.822961 0.000081 100 false 10 0.000491 0.000139
15
+ 3 3231 639 0.792627 0.000065 100 false 10 0.000123 0.000079
16
+ 4 87 639 0.493472 0.000015 100 false 10 0.000062 0.000020
17
+ 5 96 639 0.875215 0.000051 100 false 10 0.000175 0.000066
18
+ 6 1210 639 0.286222 0.000034 100 false 10 0.000045 0.000037
19
+ 7 3 639 0.247185 0.000125 100 false 10 0.000177 0.000067
20
+ 8 448 639 0.847767 0.000054 100 false 10 0.000099 0.000067
21
+ 9 332 639 0.797181 0.000091 100 false 10 0.000554 0.000134
22
+ 10 82 639 0.396063 0.000017 100 false 10 0.000084 0.000031
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.000123
27
+ 0 1 0.000080
28
+ 0 2 0.000051
29
+ 0 3 0.000034
30
+ 0 4 0.000025
31
+ 0 5 0.000022
32
+ 0 6 0.000023
33
+ 0 7 0.000025
34
+ 0 8 0.000028
35
+ 0 9 0.000031
36
+ 1 0 0.000613
37
+ 1 1 0.000483
38
+ 1 2 0.000360
39
+ 1 3 0.000257
40
+ 1 4 0.000183
41
+ 1 5 0.000136
42
+ 1 6 0.000111
43
+ 1 7 0.000100
44
+ 1 8 0.000096
45
+ 1 9 0.000096
46
+ 2 0 0.000491
47
+ 2 1 0.000379
48
+ 2 2 0.000283
49
+ 2 3 0.000206
50
+ 2 4 0.000152
51
+ 2 5 0.000120
52
+ 2 6 0.000109
53
+ 2 7 0.000113
54
+ 2 8 0.000125
55
+ 2 9 0.000139
56
+ 3 0 0.000123
57
+ 3 1 0.000103
58
+ 3 2 0.000088
59
+ 3 3 0.000078
60
+ 3 4 0.000073
61
+ 3 5 0.000072
62
+ 3 6 0.000074
63
+ 3 7 0.000076
64
+ 3 8 0.000078
65
+ 3 9 0.000079
66
+ 4 0 0.000062
67
+ 4 1 0.000029
68
+ 4 2 0.000022
69
+ 4 3 0.000028
70
+ 4 4 0.000033
71
+ 4 5 0.000034
72
+ 4 6 0.000031
73
+ 4 7 0.000026
74
+ 4 8 0.000022
75
+ 4 9 0.000020
76
+ 5 0 0.000175
77
+ 5 1 0.000156
78
+ 5 2 0.000138
79
+ 5 3 0.000123
80
+ 5 4 0.000108
81
+ 5 5 0.000096
82
+ 5 6 0.000086
83
+ 5 7 0.000077
84
+ 5 8 0.000071
85
+ 5 9 0.000066
86
+ 6 0 0.000045
87
+ 6 1 0.000044
88
+ 6 2 0.000042
89
+ 6 3 0.000041
90
+ 6 4 0.000040
91
+ 6 5 0.000039
92
+ 6 6 0.000038
93
+ 6 7 0.000038
94
+ 6 8 0.000037
95
+ 6 9 0.000037
96
+ 7 0 0.000177
97
+ 7 1 0.000144
98
+ 7 2 0.000136
99
+ 7 3 0.000128
100
+ 7 4 0.000114
101
+ 7 5 0.000099
102
+ 7 6 0.000088
103
+ 7 7 0.000080
104
+ 7 8 0.000074
105
+ 7 9 0.000067
106
+ 8 0 0.000099
107
+ 8 1 0.000088
108
+ 8 2 0.000081
109
+ 8 3 0.000075
110
+ 8 4 0.000071
111
+ 8 5 0.000068
112
+ 8 6 0.000067
113
+ 8 7 0.000067
114
+ 8 8 0.000067
115
+ 8 9 0.000067
116
+ 9 0 0.000554
117
+ 9 1 0.000476
118
+ 9 2 0.000405
119
+ 9 3 0.000341
120
+ 9 4 0.000285
121
+ 9 5 0.000238
122
+ 9 6 0.000200
123
+ 9 7 0.000170
124
+ 9 8 0.000149
125
+ 9 9 0.000134
126
+ 10 0 0.000084
127
+ 10 1 0.000056
128
+ 10 2 0.000036
129
+ 10 3 0.000025
130
+ 10 4 0.000021
131
+ 10 5 0.000022
132
+ 10 6 0.000025
133
+ 10 7 0.000029
134
+ 10 8 0.000031
135
+ 10 9 0.000031
xenium_skin_mixed/sample15/log/Arhgef3.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Arhgef3
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 689 0.727553 0.000031 100 false 10 0.000115 0.000056
13
+ 1 680 689 0.773274 0.000174 100 false 10 0.002185 0.000316
14
+ 2 5552 689 0.938801 0.000054 100 false 10 0.000725 0.000257
15
+ 3 3231 689 0.627132 0.000085 100 false 10 0.000183 0.000119
16
+ 4 87 689 0.665278 0.000013 100 false 10 0.000193 0.000020
17
+ 5 96 689 0.727774 0.000043 100 false 10 0.000173 0.000065
18
+ 6 1210 689 0.890587 0.000555 100 false 10 0.001135 0.000667
19
+ 7 3 689 0.275639 0.000121 100 false 10 0.000357 0.000083
20
+ 8 448 689 0.846939 0.000030 100 false 10 0.000059 0.000041
21
+ 9 332 689 0.890030 0.000032 100 false 10 0.000536 0.000128
22
+ 10 82 689 0.660882 0.000052 100 false 10 0.003626 0.000815
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.000115
27
+ 0 1 0.000050
28
+ 0 2 0.000060
29
+ 0 3 0.000076
30
+ 0 4 0.000073
31
+ 0 5 0.000059
32
+ 0 6 0.000047
33
+ 0 7 0.000045
34
+ 0 8 0.000050
35
+ 0 9 0.000056
36
+ 1 0 0.002185
37
+ 1 1 0.001783
38
+ 1 2 0.001427
39
+ 1 3 0.001126
40
+ 1 4 0.000883
41
+ 1 5 0.000691
42
+ 1 6 0.000542
43
+ 1 7 0.000431
44
+ 1 8 0.000356
45
+ 1 9 0.000316
46
+ 2 0 0.000725
47
+ 2 1 0.000564
48
+ 2 2 0.000425
49
+ 2 3 0.000315
50
+ 2 4 0.000244
51
+ 2 5 0.000214
52
+ 2 6 0.000217
53
+ 2 7 0.000235
54
+ 2 8 0.000252
55
+ 2 9 0.000257
56
+ 3 0 0.000183
57
+ 3 1 0.000159
58
+ 3 2 0.000139
59
+ 3 3 0.000124
60
+ 3 4 0.000115
61
+ 3 5 0.000111
62
+ 3 6 0.000113
63
+ 3 7 0.000116
64
+ 3 8 0.000119
65
+ 3 9 0.000119
66
+ 4 0 0.000193
67
+ 4 1 0.000145
68
+ 4 2 0.000104
69
+ 4 3 0.000071
70
+ 4 4 0.000045
71
+ 4 5 0.000027
72
+ 4 6 0.000017
73
+ 4 7 0.000014
74
+ 4 8 0.000015
75
+ 4 9 0.000020
76
+ 5 0 0.000173
77
+ 5 1 0.000117
78
+ 5 2 0.000081
79
+ 5 3 0.000066
80
+ 5 4 0.000069
81
+ 5 5 0.000077
82
+ 5 6 0.000082
83
+ 5 7 0.000080
84
+ 5 8 0.000073
85
+ 5 9 0.000065
86
+ 6 0 0.001135
87
+ 6 1 0.000943
88
+ 6 2 0.000814
89
+ 6 3 0.000736
90
+ 6 4 0.000697
91
+ 6 5 0.000683
92
+ 6 6 0.000681
93
+ 6 7 0.000680
94
+ 6 8 0.000677
95
+ 6 9 0.000667
96
+ 7 0 0.000357
97
+ 7 1 0.000239
98
+ 7 2 0.000164
99
+ 7 3 0.000139
100
+ 7 4 0.000140
101
+ 7 5 0.000141
102
+ 7 6 0.000134
103
+ 7 7 0.000119
104
+ 7 8 0.000101
105
+ 7 9 0.000083
106
+ 8 0 0.000059
107
+ 8 1 0.000056
108
+ 8 2 0.000053
109
+ 8 3 0.000051
110
+ 8 4 0.000049
111
+ 8 5 0.000047
112
+ 8 6 0.000045
113
+ 8 7 0.000044
114
+ 8 8 0.000042
115
+ 8 9 0.000041
116
+ 9 0 0.000536
117
+ 9 1 0.000449
118
+ 9 2 0.000360
119
+ 9 3 0.000272
120
+ 9 4 0.000190
121
+ 9 5 0.000122
122
+ 9 6 0.000082
123
+ 9 7 0.000075
124
+ 9 8 0.000098
125
+ 9 9 0.000128
126
+ 10 0 0.003626
127
+ 10 1 0.002676
128
+ 10 2 0.001674
129
+ 10 3 0.000751
130
+ 10 4 0.000163
131
+ 10 5 0.000131
132
+ 10 6 0.000455
133
+ 10 7 0.000745
134
+ 10 8 0.000861
135
+ 10 9 0.000815
xenium_skin_mixed/sample15/log/Arl13b.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Arl13b
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 591 0.548357 0.000040 100 false 10 0.002269 0.000478
13
+ 1 680 591 0.531943 0.000088 100 false 10 0.000102 0.000090
14
+ 2 5552 591 0.820196 0.000185 100 false 10 0.000307 0.000239
15
+ 3 3231 591 0.510603 0.000166 100 false 10 0.000209 0.000167
16
+ 4 87 591 0.156170 0.000049 100 false 10 0.000279 0.000074
17
+ 5 96 591 0.753114 0.000053 100 false 10 0.000496 0.000214
18
+ 6 1210 591 0.332629 0.000051 100 false 10 0.000327 0.000074
19
+ 7 3 591 0.000000 0.000000 26 true 10 0.000010 0.000000
20
+ 8 448 591 0.679106 0.000071 100 false 10 0.000136 0.000087
21
+ 9 332 591 0.647296 0.000052 100 false 10 0.000127 0.000075
22
+ 10 82 591 0.228347 0.000021 100 false 10 0.000242 0.000032
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.002269
27
+ 0 1 0.002010
28
+ 0 2 0.001742
29
+ 0 3 0.001477
30
+ 0 4 0.001228
31
+ 0 5 0.001010
32
+ 0 6 0.000830
33
+ 0 7 0.000685
34
+ 0 8 0.000570
35
+ 0 9 0.000478
36
+ 1 0 0.000102
37
+ 1 1 0.000099
38
+ 1 2 0.000097
39
+ 1 3 0.000096
40
+ 1 4 0.000094
41
+ 1 5 0.000093
42
+ 1 6 0.000092
43
+ 1 7 0.000091
44
+ 1 8 0.000091
45
+ 1 9 0.000090
46
+ 2 0 0.000307
47
+ 2 1 0.000255
48
+ 2 2 0.000283
49
+ 2 3 0.000274
50
+ 2 4 0.000252
51
+ 2 5 0.000245
52
+ 2 6 0.000254
53
+ 2 7 0.000257
54
+ 2 8 0.000250
55
+ 2 9 0.000239
56
+ 3 0 0.000209
57
+ 3 1 0.000195
58
+ 3 2 0.000185
59
+ 3 3 0.000178
60
+ 3 4 0.000173
61
+ 3 5 0.000170
62
+ 3 6 0.000168
63
+ 3 7 0.000167
64
+ 3 8 0.000167
65
+ 3 9 0.000167
66
+ 4 0 0.000279
67
+ 4 1 0.000077
68
+ 4 2 0.000071
69
+ 4 3 0.000128
70
+ 4 4 0.000145
71
+ 4 5 0.000121
72
+ 4 6 0.000083
73
+ 4 7 0.000058
74
+ 4 8 0.000057
75
+ 4 9 0.000074
76
+ 5 0 0.000496
77
+ 5 1 0.000462
78
+ 5 2 0.000430
79
+ 5 3 0.000399
80
+ 5 4 0.000367
81
+ 5 5 0.000337
82
+ 5 6 0.000307
83
+ 5 7 0.000277
84
+ 5 8 0.000246
85
+ 5 9 0.000214
86
+ 6 0 0.000327
87
+ 6 1 0.000249
88
+ 6 2 0.000181
89
+ 6 3 0.000127
90
+ 6 4 0.000089
91
+ 6 5 0.000068
92
+ 6 6 0.000060
93
+ 6 7 0.000061
94
+ 6 8 0.000067
95
+ 6 9 0.000074
96
+ 7 0 0.000010
97
+ 7 1 0.000003
98
+ 7 2 0.000001
99
+ 7 3 0.000002
100
+ 7 4 0.000003
101
+ 7 5 0.000003
102
+ 7 6 0.000002
103
+ 7 7 0.000001
104
+ 7 8 0.000000
105
+ 7 9 0.000000
106
+ 8 0 0.000136
107
+ 8 1 0.000125
108
+ 8 2 0.000116
109
+ 8 3 0.000108
110
+ 8 4 0.000101
111
+ 8 5 0.000096
112
+ 8 6 0.000092
113
+ 8 7 0.000089
114
+ 8 8 0.000088
115
+ 8 9 0.000087
116
+ 9 0 0.000127
117
+ 9 1 0.000119
118
+ 9 2 0.000112
119
+ 9 3 0.000105
120
+ 9 4 0.000098
121
+ 9 5 0.000093
122
+ 9 6 0.000087
123
+ 9 7 0.000083
124
+ 9 8 0.000078
125
+ 9 9 0.000075
126
+ 10 0 0.000242
127
+ 10 1 0.000125
128
+ 10 2 0.000048
129
+ 10 3 0.000025
130
+ 10 4 0.000046
131
+ 10 5 0.000074
132
+ 10 6 0.000080
133
+ 10 7 0.000068
134
+ 10 8 0.000048
135
+ 10 9 0.000032
xenium_skin_mixed/sample15/log/Asap1.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Asap1
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 650 0.731733 0.000339 100 false 10 0.046171 0.017456
13
+ 1 680 650 0.740609 0.000135 100 false 10 0.002395 0.000463
14
+ 2 5552 650 0.885157 0.000095 100 false 10 0.000305 0.000167
15
+ 3 3231 650 0.776099 0.000426 100 false 10 0.000635 0.000480
16
+ 4 87 650 0.249994 0.000062 100 false 10 0.000720 0.000134
17
+ 5 96 650 0.866564 0.000148 100 false 10 0.000213 0.000163
18
+ 6 1210 650 0.832421 0.000196 100 false 10 0.000382 0.000243
19
+ 7 3 650 0.255480 0.000046 100 false 10 0.000633 0.000116
20
+ 8 448 650 0.928781 0.000104 100 false 10 0.000407 0.000150
21
+ 9 332 650 0.771800 0.000038 100 false 10 0.000083 0.000053
22
+ 10 82 650 0.441142 0.000053 100 false 10 0.003182 0.000645
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.046171
27
+ 0 1 0.043387
28
+ 0 2 0.040547
29
+ 0 3 0.037636
30
+ 0 4 0.034623
31
+ 0 5 0.031486
32
+ 0 6 0.028198
33
+ 0 7 0.024743
34
+ 0 8 0.021132
35
+ 0 9 0.017456
36
+ 1 0 0.002395
37
+ 1 1 0.001633
38
+ 1 2 0.000941
39
+ 1 3 0.000427
40
+ 1 4 0.000221
41
+ 1 5 0.000346
42
+ 1 6 0.000574
43
+ 1 7 0.000672
44
+ 1 8 0.000612
45
+ 1 9 0.000463
46
+ 2 0 0.000305
47
+ 2 1 0.000219
48
+ 2 2 0.000174
49
+ 2 3 0.000159
50
+ 2 4 0.000162
51
+ 2 5 0.000169
52
+ 2 6 0.000175
53
+ 2 7 0.000176
54
+ 2 8 0.000173
55
+ 2 9 0.000167
56
+ 3 0 0.000635
57
+ 3 1 0.000566
58
+ 3 2 0.000513
59
+ 3 3 0.000478
60
+ 3 4 0.000459
61
+ 3 5 0.000456
62
+ 3 6 0.000461
63
+ 3 7 0.000470
64
+ 3 8 0.000477
65
+ 3 9 0.000480
66
+ 4 0 0.000720
67
+ 4 1 0.000197
68
+ 4 2 0.000129
69
+ 4 3 0.000278
70
+ 4 4 0.000336
71
+ 4 5 0.000271
72
+ 4 6 0.000165
73
+ 4 7 0.000094
74
+ 4 8 0.000091
75
+ 4 9 0.000134
76
+ 5 0 0.000213
77
+ 5 1 0.000204
78
+ 5 2 0.000197
79
+ 5 3 0.000191
80
+ 5 4 0.000184
81
+ 5 5 0.000179
82
+ 5 6 0.000174
83
+ 5 7 0.000170
84
+ 5 8 0.000167
85
+ 5 9 0.000163
86
+ 6 0 0.000382
87
+ 6 1 0.000300
88
+ 6 2 0.000251
89
+ 6 3 0.000229
90
+ 6 4 0.000227
91
+ 6 5 0.000234
92
+ 6 6 0.000244
93
+ 6 7 0.000249
94
+ 6 8 0.000248
95
+ 6 9 0.000243
96
+ 7 0 0.000633
97
+ 7 1 0.000426
98
+ 7 2 0.000249
99
+ 7 3 0.000125
100
+ 7 4 0.000063
101
+ 7 5 0.000054
102
+ 7 6 0.000074
103
+ 7 7 0.000100
104
+ 7 8 0.000115
105
+ 7 9 0.000116
106
+ 8 0 0.000407
107
+ 8 1 0.000361
108
+ 8 2 0.000319
109
+ 8 3 0.000281
110
+ 8 4 0.000248
111
+ 8 5 0.000220
112
+ 8 6 0.000196
113
+ 8 7 0.000177
114
+ 8 8 0.000161
115
+ 8 9 0.000150
116
+ 9 0 0.000083
117
+ 9 1 0.000076
118
+ 9 2 0.000070
119
+ 9 3 0.000064
120
+ 9 4 0.000060
121
+ 9 5 0.000057
122
+ 9 6 0.000055
123
+ 9 7 0.000054
124
+ 9 8 0.000053
125
+ 9 9 0.000053
126
+ 10 0 0.003182
127
+ 10 1 0.001852
128
+ 10 2 0.000874
129
+ 10 3 0.000307
130
+ 10 4 0.000118
131
+ 10 5 0.000179
132
+ 10 6 0.000341
133
+ 10 7 0.000500
134
+ 10 8 0.000606
135
+ 10 9 0.000645
xenium_skin_mixed/sample15/log/Atf6b.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Atf6b
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 643 0.519702 0.000065 100 false 10 0.000509 0.000193
13
+ 1 680 643 0.579572 0.000073 100 false 10 0.001429 0.000336
14
+ 2 5552 643 0.833629 0.000121 100 false 10 0.000165 0.000148
15
+ 3 3231 643 0.690855 0.000062 100 false 10 0.000067 0.000065
16
+ 4 87 643 0.148867 0.000036 100 false 10 0.015881 0.006661
17
+ 5 96 643 0.571386 0.000087 100 false 10 0.000148 0.000093
18
+ 6 1210 643 0.712360 0.000102 100 false 10 0.000104 0.000101
19
+ 7 3 643 0.216960 0.000033 100 false 10 0.002601 0.000118
20
+ 8 448 643 0.589355 0.000039 100 false 10 0.000054 0.000046
21
+ 9 332 643 0.806445 0.000047 100 false 10 0.000076 0.000068
22
+ 10 82 643 0.680410 0.000041 100 false 10 0.000742 0.000066
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.000509
27
+ 0 1 0.000343
28
+ 0 2 0.000423
29
+ 0 3 0.000366
30
+ 0 4 0.000279
31
+ 0 5 0.000259
32
+ 0 6 0.000283
33
+ 0 7 0.000275
34
+ 0 8 0.000231
35
+ 0 9 0.000193
36
+ 1 0 0.001429
37
+ 1 1 0.001088
38
+ 1 2 0.000762
39
+ 1 3 0.000477
40
+ 1 4 0.000268
41
+ 1 5 0.000178
42
+ 1 6 0.000211
43
+ 1 7 0.000298
44
+ 1 8 0.000349
45
+ 1 9 0.000336
46
+ 2 0 0.000165
47
+ 2 1 0.000165
48
+ 2 2 0.000161
49
+ 2 3 0.000157
50
+ 2 4 0.000156
51
+ 2 5 0.000155
52
+ 2 6 0.000152
53
+ 2 7 0.000150
54
+ 2 8 0.000149
55
+ 2 9 0.000148
56
+ 3 0 0.000067
57
+ 3 1 0.000066
58
+ 3 2 0.000065
59
+ 3 3 0.000064
60
+ 3 4 0.000064
61
+ 3 5 0.000065
62
+ 3 6 0.000065
63
+ 3 7 0.000065
64
+ 3 8 0.000065
65
+ 3 9 0.000065
66
+ 4 0 0.015881
67
+ 4 1 0.015490
68
+ 4 2 0.015015
69
+ 4 3 0.014429
70
+ 4 4 0.013701
71
+ 4 5 0.012795
72
+ 4 6 0.011669
73
+ 4 7 0.010283
74
+ 4 8 0.008612
75
+ 4 9 0.006661
76
+ 5 0 0.000148
77
+ 5 1 0.000132
78
+ 5 2 0.000118
79
+ 5 3 0.000107
80
+ 5 4 0.000099
81
+ 5 5 0.000094
82
+ 5 6 0.000092
83
+ 5 7 0.000091
84
+ 5 8 0.000092
85
+ 5 9 0.000093
86
+ 6 0 0.000104
87
+ 6 1 0.000103
88
+ 6 2 0.000103
89
+ 6 3 0.000102
90
+ 6 4 0.000102
91
+ 6 5 0.000101
92
+ 6 6 0.000101
93
+ 6 7 0.000101
94
+ 6 8 0.000101
95
+ 6 9 0.000101
96
+ 7 0 0.002601
97
+ 7 1 0.002090
98
+ 7 2 0.001581
99
+ 7 3 0.001110
100
+ 7 4 0.000691
101
+ 7 5 0.000356
102
+ 7 6 0.000132
103
+ 7 7 0.000034
104
+ 7 8 0.000042
105
+ 7 9 0.000118
106
+ 8 0 0.000054
107
+ 8 1 0.000051
108
+ 8 2 0.000052
109
+ 8 3 0.000051
110
+ 8 4 0.000049
111
+ 8 5 0.000048
112
+ 8 6 0.000048
113
+ 8 7 0.000048
114
+ 8 8 0.000047
115
+ 8 9 0.000046
116
+ 9 0 0.000076
117
+ 9 1 0.000074
118
+ 9 2 0.000073
119
+ 9 3 0.000073
120
+ 9 4 0.000072
121
+ 9 5 0.000071
122
+ 9 6 0.000070
123
+ 9 7 0.000070
124
+ 9 8 0.000069
125
+ 9 9 0.000068
126
+ 10 0 0.000742
127
+ 10 1 0.000527
128
+ 10 2 0.000361
129
+ 10 3 0.000241
130
+ 10 4 0.000159
131
+ 10 5 0.000106
132
+ 10 6 0.000076
133
+ 10 7 0.000062
134
+ 10 8 0.000060
135
+ 10 9 0.000066
xenium_skin_mixed/sample15/log/Atg13.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Atg13
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 594 0.608720 0.000035 100 false 10 0.000749 0.000134
13
+ 1 680 594 0.230896 0.000050 100 false 10 0.000142 0.000060
14
+ 2 5552 594 0.818063 0.000595 100 false 10 0.017594 0.001316
15
+ 3 3231 594 0.459589 0.000094 100 false 10 0.000095 0.000094
16
+ 4 87 594 0.000000 0.000030 100 false 10 0.003419 0.000687
17
+ 5 96 594 0.625489 0.000065 100 false 10 0.000069 0.000063
18
+ 6 1210 594 0.636129 0.000053 100 false 10 0.000073 0.000058
19
+ 7 3 594 0.125123 0.000000 100 false 10 0.000065 0.000020
20
+ 8 448 594 0.311845 0.000092 100 false 10 0.000444 0.000131
21
+ 9 332 594 0.863705 0.000130 100 false 10 0.000375 0.000220
22
+ 10 82 594 0.281288 0.000045 100 false 10 0.000305 0.000068
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.000749
27
+ 0 1 0.000662
28
+ 0 2 0.000578
29
+ 0 3 0.000497
30
+ 0 4 0.000421
31
+ 0 5 0.000351
32
+ 0 6 0.000288
33
+ 0 7 0.000230
34
+ 0 8 0.000178
35
+ 0 9 0.000134
36
+ 1 0 0.000142
37
+ 1 1 0.000127
38
+ 1 2 0.000113
39
+ 1 3 0.000101
40
+ 1 4 0.000090
41
+ 1 5 0.000080
42
+ 1 6 0.000073
43
+ 1 7 0.000067
44
+ 1 8 0.000063
45
+ 1 9 0.000060
46
+ 2 0 0.017594
47
+ 2 1 0.014912
48
+ 2 2 0.012316
49
+ 2 3 0.009874
50
+ 2 4 0.007650
51
+ 2 5 0.005690
52
+ 2 6 0.004044
53
+ 2 7 0.002756
54
+ 2 8 0.001853
55
+ 2 9 0.001316
56
+ 3 0 0.000095
57
+ 3 1 0.000095
58
+ 3 2 0.000094
59
+ 3 3 0.000094
60
+ 3 4 0.000094
61
+ 3 5 0.000094
62
+ 3 6 0.000094
63
+ 3 7 0.000094
64
+ 3 8 0.000094
65
+ 3 9 0.000094
66
+ 4 0 0.003419
67
+ 4 1 0.002636
68
+ 4 2 0.001831
69
+ 4 3 0.001073
70
+ 4 4 0.000463
71
+ 4 5 0.000119
72
+ 4 6 0.000102
73
+ 4 7 0.000308
74
+ 4 8 0.000543
75
+ 4 9 0.000687
76
+ 5 0 0.000069
77
+ 5 1 0.000068
78
+ 5 2 0.000067
79
+ 5 3 0.000066
80
+ 5 4 0.000066
81
+ 5 5 0.000065
82
+ 5 6 0.000065
83
+ 5 7 0.000064
84
+ 5 8 0.000064
85
+ 5 9 0.000063
86
+ 6 0 0.000073
87
+ 6 1 0.000070
88
+ 6 2 0.000068
89
+ 6 3 0.000065
90
+ 6 4 0.000063
91
+ 6 5 0.000062
92
+ 6 6 0.000061
93
+ 6 7 0.000060
94
+ 6 8 0.000059
95
+ 6 9 0.000058
96
+ 7 0 0.000065
97
+ 7 1 0.000047
98
+ 7 2 0.000033
99
+ 7 3 0.000024
100
+ 7 4 0.000022
101
+ 7 5 0.000023
102
+ 7 6 0.000025
103
+ 7 7 0.000025
104
+ 7 8 0.000023
105
+ 7 9 0.000020
106
+ 8 0 0.000444
107
+ 8 1 0.000374
108
+ 8 2 0.000312
109
+ 8 3 0.000257
110
+ 8 4 0.000211
111
+ 8 5 0.000175
112
+ 8 6 0.000150
113
+ 8 7 0.000135
114
+ 8 8 0.000129
115
+ 8 9 0.000131
116
+ 9 0 0.000375
117
+ 9 1 0.000328
118
+ 9 2 0.000291
119
+ 9 3 0.000264
120
+ 9 4 0.000245
121
+ 9 5 0.000233
122
+ 9 6 0.000226
123
+ 9 7 0.000223
124
+ 9 8 0.000221
125
+ 9 9 0.000220
126
+ 10 0 0.000305
127
+ 10 1 0.000238
128
+ 10 2 0.000180
129
+ 10 3 0.000135
130
+ 10 4 0.000102
131
+ 10 5 0.000080
132
+ 10 6 0.000069
133
+ 10 7 0.000065
134
+ 10 8 0.000065
135
+ 10 9 0.000068
xenium_skin_mixed/sample15/log/Atg7.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Atg7
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 616 0.591127 0.000048 100 false 10 0.000816 0.000086
13
+ 1 680 616 0.674054 0.000069 100 false 10 0.001246 0.000146
14
+ 2 5552 616 0.642022 0.000110 100 false 10 0.000140 0.000121
15
+ 3 3231 616 0.651691 0.000110 100 false 10 0.000116 0.000114
16
+ 4 87 616 0.361345 0.000012 100 false 10 0.000026 0.000016
17
+ 5 96 616 0.690354 0.000176 100 false 10 0.000471 0.000189
18
+ 6 1210 616 0.647590 0.000182 100 false 10 0.000287 0.000210
19
+ 7 3 616 0.000000 0.000000 1 true 10 0.000000 0.000000
20
+ 8 448 616 0.753086 0.000047 100 false 10 0.000143 0.000082
21
+ 9 332 616 0.490366 0.000033 100 false 10 0.000111 0.000055
22
+ 10 82 616 0.659491 0.000045 100 false 10 0.001361 0.000296
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.000816
27
+ 0 1 0.000607
28
+ 0 2 0.000426
29
+ 0 3 0.000281
30
+ 0 4 0.000174
31
+ 0 5 0.000105
32
+ 0 6 0.000069
33
+ 0 7 0.000060
34
+ 0 8 0.000068
35
+ 0 9 0.000086
36
+ 1 0 0.001246
37
+ 1 1 0.001030
38
+ 1 2 0.000817
39
+ 1 3 0.000615
40
+ 1 4 0.000435
41
+ 1 5 0.000290
42
+ 1 6 0.000190
43
+ 1 7 0.000138
44
+ 1 8 0.000129
45
+ 1 9 0.000146
46
+ 2 0 0.000140
47
+ 2 1 0.000135
48
+ 2 2 0.000131
49
+ 2 3 0.000129
50
+ 2 4 0.000127
51
+ 2 5 0.000126
52
+ 2 6 0.000125
53
+ 2 7 0.000124
54
+ 2 8 0.000123
55
+ 2 9 0.000121
56
+ 3 0 0.000116
57
+ 3 1 0.000116
58
+ 3 2 0.000116
59
+ 3 3 0.000115
60
+ 3 4 0.000115
61
+ 3 5 0.000115
62
+ 3 6 0.000115
63
+ 3 7 0.000114
64
+ 3 8 0.000114
65
+ 3 9 0.000114
66
+ 4 0 0.000026
67
+ 4 1 0.000015
68
+ 4 2 0.000019
69
+ 4 3 0.000020
70
+ 4 4 0.000018
71
+ 4 5 0.000015
72
+ 4 6 0.000015
73
+ 4 7 0.000016
74
+ 4 8 0.000017
75
+ 4 9 0.000016
76
+ 5 0 0.000471
77
+ 5 1 0.000422
78
+ 5 2 0.000375
79
+ 5 3 0.000332
80
+ 5 4 0.000294
81
+ 5 5 0.000261
82
+ 5 6 0.000234
83
+ 5 7 0.000214
84
+ 5 8 0.000199
85
+ 5 9 0.000189
86
+ 6 0 0.000287
87
+ 6 1 0.000262
88
+ 6 2 0.000242
89
+ 6 3 0.000227
90
+ 6 4 0.000218
91
+ 6 5 0.000214
92
+ 6 6 0.000212
93
+ 6 7 0.000211
94
+ 6 8 0.000211
95
+ 6 9 0.000210
96
+ 7 0 0.000000
97
+ 7 1 0.000000
98
+ 7 2 0.000000
99
+ 7 3 0.000000
100
+ 7 4 0.000000
101
+ 7 5 0.000000
102
+ 7 6 0.000000
103
+ 7 7 0.000000
104
+ 7 8 0.000000
105
+ 7 9 0.000000
106
+ 8 0 0.000143
107
+ 8 1 0.000118
108
+ 8 2 0.000099
109
+ 8 3 0.000086
110
+ 8 4 0.000079
111
+ 8 5 0.000078
112
+ 8 6 0.000079
113
+ 8 7 0.000082
114
+ 8 8 0.000083
115
+ 8 9 0.000082
116
+ 9 0 0.000111
117
+ 9 1 0.000105
118
+ 9 2 0.000100
119
+ 9 3 0.000093
120
+ 9 4 0.000087
121
+ 9 5 0.000080
122
+ 9 6 0.000073
123
+ 9 7 0.000066
124
+ 9 8 0.000060
125
+ 9 9 0.000055
126
+ 10 0 0.001361
127
+ 10 1 0.001149
128
+ 10 2 0.000928
129
+ 10 3 0.000700
130
+ 10 4 0.000473
131
+ 10 5 0.000266
132
+ 10 6 0.000122
133
+ 10 7 0.000096
134
+ 10 8 0.000194
135
+ 10 9 0.000296
xenium_skin_mixed/sample15/log/Atn1.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Atn1
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 633 0.531064 0.000043 100 false 10 0.000244 0.000060
13
+ 1 680 633 0.485746 0.000106 100 false 10 0.000341 0.000137
14
+ 2 5552 633 0.800887 0.000101 100 false 10 0.001103 0.000209
15
+ 3 3231 633 0.838567 0.000152 100 false 10 0.000175 0.000157
16
+ 4 87 633 0.100311 0.000026 100 false 10 0.000119 0.000057
17
+ 5 96 633 0.977275 0.000050 100 false 10 0.000379 0.000133
18
+ 6 1210 633 0.604372 0.000059 100 false 10 0.000073 0.000065
19
+ 7 3 633 0.000000 0.000000 1 true 10 0.000000 0.000000
20
+ 8 448 633 0.862136 0.000125 100 false 10 0.000211 0.000141
21
+ 9 332 633 0.854952 0.000138 100 false 10 0.000859 0.000251
22
+ 10 82 633 0.567560 0.000051 100 false 10 0.005510 0.000171
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.000244
27
+ 0 1 0.000114
28
+ 0 2 0.000067
29
+ 0 3 0.000081
30
+ 0 4 0.000107
31
+ 0 5 0.000117
32
+ 0 6 0.000109
33
+ 0 7 0.000091
34
+ 0 8 0.000072
35
+ 0 9 0.000060
36
+ 1 0 0.000341
37
+ 1 1 0.000224
38
+ 1 2 0.000170
39
+ 1 3 0.000174
40
+ 1 4 0.000195
41
+ 1 5 0.000196
42
+ 1 6 0.000178
43
+ 1 7 0.000156
44
+ 1 8 0.000141
45
+ 1 9 0.000137
46
+ 2 0 0.001103
47
+ 2 1 0.000894
48
+ 2 2 0.000715
49
+ 2 3 0.000568
50
+ 2 4 0.000452
51
+ 2 5 0.000364
52
+ 2 6 0.000301
53
+ 2 7 0.000258
54
+ 2 8 0.000228
55
+ 2 9 0.000209
56
+ 3 0 0.000175
57
+ 3 1 0.000165
58
+ 3 2 0.000161
59
+ 3 3 0.000161
60
+ 3 4 0.000162
61
+ 3 5 0.000162
62
+ 3 6 0.000162
63
+ 3 7 0.000160
64
+ 3 8 0.000159
65
+ 3 9 0.000157
66
+ 4 0 0.000119
67
+ 4 1 0.000057
68
+ 4 2 0.000070
69
+ 4 3 0.000083
70
+ 4 4 0.000072
71
+ 4 5 0.000055
72
+ 4 6 0.000047
73
+ 4 7 0.000050
74
+ 4 8 0.000056
75
+ 4 9 0.000057
76
+ 5 0 0.000379
77
+ 5 1 0.000320
78
+ 5 2 0.000264
79
+ 5 3 0.000213
80
+ 5 4 0.000170
81
+ 5 5 0.000137
82
+ 5 6 0.000118
83
+ 5 7 0.000115
84
+ 5 8 0.000122
85
+ 5 9 0.000133
86
+ 6 0 0.000073
87
+ 6 1 0.000069
88
+ 6 2 0.000066
89
+ 6 3 0.000065
90
+ 6 4 0.000064
91
+ 6 5 0.000064
92
+ 6 6 0.000064
93
+ 6 7 0.000064
94
+ 6 8 0.000064
95
+ 6 9 0.000065
96
+ 7 0 0.000000
97
+ 7 1 0.000000
98
+ 7 2 0.000000
99
+ 7 3 0.000000
100
+ 7 4 0.000000
101
+ 7 5 0.000000
102
+ 7 6 0.000000
103
+ 7 7 0.000000
104
+ 7 8 0.000000
105
+ 7 9 0.000000
106
+ 8 0 0.000211
107
+ 8 1 0.000198
108
+ 8 2 0.000187
109
+ 8 3 0.000177
110
+ 8 4 0.000169
111
+ 8 5 0.000161
112
+ 8 6 0.000155
113
+ 8 7 0.000149
114
+ 8 8 0.000145
115
+ 8 9 0.000141
116
+ 9 0 0.000859
117
+ 9 1 0.000748
118
+ 9 2 0.000649
119
+ 9 3 0.000562
120
+ 9 4 0.000485
121
+ 9 5 0.000419
122
+ 9 6 0.000363
123
+ 9 7 0.000316
124
+ 9 8 0.000279
125
+ 9 9 0.000251
126
+ 10 0 0.005510
127
+ 10 1 0.004774
128
+ 10 2 0.004034
129
+ 10 3 0.003303
130
+ 10 4 0.002605
131
+ 10 5 0.001948
132
+ 10 6 0.001351
133
+ 10 7 0.000835
134
+ 10 8 0.000429
135
+ 10 9 0.000171
xenium_skin_mixed/sample15/log/Atp2a3.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Atp2a3
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 628 0.706902 0.000130 100 false 10 0.001509 0.000309
13
+ 1 680 628 0.887377 0.002060 100 false 10 0.060348 0.003760
14
+ 2 5552 628 0.638222 0.000044 100 false 10 0.000262 0.000090
15
+ 3 3231 628 0.457840 0.000054 100 false 10 0.000106 0.000065
16
+ 4 87 628 0.792807 0.000057 100 false 10 0.004869 0.000704
17
+ 5 96 628 0.923678 0.000651 100 false 10 0.002673 0.000910
18
+ 6 1210 628 0.650015 0.000139 100 false 10 0.000164 0.000151
19
+ 7 3 628 0.000000 0.000000 26 true 10 0.000463 0.000070
20
+ 8 448 628 0.919082 0.000490 100 false 10 0.001064 0.000474
21
+ 9 332 628 0.802713 0.000004 100 false 10 0.000023 0.000015
22
+ 10 82 628 0.353900 0.000519 100 false 10 0.060361 0.006864
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.001509
27
+ 0 1 0.001055
28
+ 0 2 0.000681
29
+ 0 3 0.000411
30
+ 0 4 0.000252
31
+ 0 5 0.000188
32
+ 0 6 0.000189
33
+ 0 7 0.000223
34
+ 0 8 0.000268
35
+ 0 9 0.000309
36
+ 1 0 0.060348
37
+ 1 1 0.051296
38
+ 1 2 0.042640
39
+ 1 3 0.034467
40
+ 1 4 0.026891
41
+ 1 5 0.020055
42
+ 1 6 0.014148
43
+ 1 7 0.009367
44
+ 1 8 0.005882
45
+ 1 9 0.003760
46
+ 2 0 0.000262
47
+ 2 1 0.000178
48
+ 2 2 0.000116
49
+ 2 3 0.000078
50
+ 2 4 0.000060
51
+ 2 5 0.000059
52
+ 2 6 0.000066
53
+ 2 7 0.000076
54
+ 2 8 0.000085
55
+ 2 9 0.000090
56
+ 3 0 0.000106
57
+ 3 1 0.000088
58
+ 3 2 0.000073
59
+ 3 3 0.000063
60
+ 3 4 0.000058
61
+ 3 5 0.000057
62
+ 3 6 0.000059
63
+ 3 7 0.000062
64
+ 3 8 0.000064
65
+ 3 9 0.000065
66
+ 4 0 0.004869
67
+ 4 1 0.002639
68
+ 4 2 0.001069
69
+ 4 3 0.000299
70
+ 4 4 0.000303
71
+ 4 5 0.000748
72
+ 4 6 0.001133
73
+ 4 7 0.001213
74
+ 4 8 0.001023
75
+ 4 9 0.000704
76
+ 5 0 0.002673
77
+ 5 1 0.001789
78
+ 5 2 0.001191
79
+ 5 3 0.000885
80
+ 5 4 0.000822
81
+ 5 5 0.000896
82
+ 5 6 0.000985
83
+ 5 7 0.001021
84
+ 5 8 0.000988
85
+ 5 9 0.000910
86
+ 6 0 0.000164
87
+ 6 1 0.000159
88
+ 6 2 0.000156
89
+ 6 3 0.000155
90
+ 6 4 0.000155
91
+ 6 5 0.000155
92
+ 6 6 0.000154
93
+ 6 7 0.000153
94
+ 6 8 0.000152
95
+ 6 9 0.000151
96
+ 7 0 0.000463
97
+ 7 1 0.000137
98
+ 7 2 0.000108
99
+ 7 3 0.000148
100
+ 7 4 0.000116
101
+ 7 5 0.000049
102
+ 7 6 0.000007
103
+ 7 7 0.000013
104
+ 7 8 0.000047
105
+ 7 9 0.000070
106
+ 8 0 0.001064
107
+ 8 1 0.000895
108
+ 8 2 0.000778
109
+ 8 3 0.000698
110
+ 8 4 0.000638
111
+ 8 5 0.000588
112
+ 8 6 0.000544
113
+ 8 7 0.000509
114
+ 8 8 0.000485
115
+ 8 9 0.000474
116
+ 9 0 0.000023
117
+ 9 1 0.000022
118
+ 9 2 0.000021
119
+ 9 3 0.000020
120
+ 9 4 0.000019
121
+ 9 5 0.000018
122
+ 9 6 0.000017
123
+ 9 7 0.000017
124
+ 9 8 0.000016
125
+ 9 9 0.000015
126
+ 10 0 0.060361
127
+ 10 1 0.045195
128
+ 10 2 0.030649
129
+ 10 3 0.017850
130
+ 10 4 0.008154
131
+ 10 5 0.002381
132
+ 10 6 0.000649
133
+ 10 7 0.001956
134
+ 10 8 0.004523
135
+ 10 9 0.006864
xenium_skin_mixed/sample15/log/Atp5o.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Atp5o
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 654 0.767555 0.000111 100 false 10 0.002752 0.000173
13
+ 1 680 654 0.408371 0.000173 100 false 10 0.003585 0.001019
14
+ 2 5552 654 0.831799 0.000575 100 false 10 0.012167 0.002879
15
+ 3 3231 654 0.624484 0.000199 100 false 10 0.000264 0.000243
16
+ 4 87 654 0.418070 0.000082 100 false 10 0.000784 0.000222
17
+ 5 96 654 0.761480 0.000123 100 false 10 0.001620 0.000427
18
+ 6 1210 654 0.748567 0.000507 100 false 10 0.000942 0.000562
19
+ 7 3 654 0.162026 0.000002 100 false 10 0.004120 0.000723
20
+ 8 448 654 0.831346 0.000200 100 false 10 0.001769 0.000512
21
+ 9 332 654 0.726478 0.000126 100 false 10 0.000167 0.000135
22
+ 10 82 654 0.462366 0.000113 100 false 10 0.004479 0.000383
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.002752
27
+ 0 1 0.000784
28
+ 0 2 0.000175
29
+ 0 3 0.000554
30
+ 0 4 0.000983
31
+ 0 5 0.001035
32
+ 0 6 0.000795
33
+ 0 7 0.000465
34
+ 0 8 0.000225
35
+ 0 9 0.000173
36
+ 1 0 0.003585
37
+ 1 1 0.003144
38
+ 1 2 0.002745
39
+ 1 3 0.002390
40
+ 1 4 0.002079
41
+ 1 5 0.001806
42
+ 1 6 0.001568
43
+ 1 7 0.001360
44
+ 1 8 0.001178
45
+ 1 9 0.001019
46
+ 2 0 0.012167
47
+ 2 1 0.008668
48
+ 2 2 0.005844
49
+ 2 3 0.003682
50
+ 2 4 0.002190
51
+ 2 5 0.001414
52
+ 2 6 0.001366
53
+ 2 7 0.001874
54
+ 2 8 0.002505
55
+ 2 9 0.002879
56
+ 3 0 0.000264
57
+ 3 1 0.000265
58
+ 3 2 0.000258
59
+ 3 3 0.000254
60
+ 3 4 0.000254
61
+ 3 5 0.000252
62
+ 3 6 0.000248
63
+ 3 7 0.000245
64
+ 3 8 0.000244
65
+ 3 9 0.000243
66
+ 4 0 0.000784
67
+ 4 1 0.000206
68
+ 4 2 0.000367
69
+ 4 3 0.000460
70
+ 4 4 0.000325
71
+ 4 5 0.000170
72
+ 4 6 0.000130
73
+ 4 7 0.000190
74
+ 4 8 0.000242
75
+ 4 9 0.000222
76
+ 5 0 0.001620
77
+ 5 1 0.001455
78
+ 5 2 0.001297
79
+ 5 3 0.001148
80
+ 5 4 0.001006
81
+ 5 5 0.000872
82
+ 5 6 0.000745
83
+ 5 7 0.000627
84
+ 5 8 0.000519
85
+ 5 9 0.000427
86
+ 6 0 0.000942
87
+ 6 1 0.000833
88
+ 6 2 0.000768
89
+ 6 3 0.000722
90
+ 6 4 0.000678
91
+ 6 5 0.000636
92
+ 6 6 0.000601
93
+ 6 7 0.000578
94
+ 6 8 0.000567
95
+ 6 9 0.000562
96
+ 7 0 0.004120
97
+ 7 1 0.003283
98
+ 7 2 0.002317
99
+ 7 3 0.001389
100
+ 7 4 0.000592
101
+ 7 5 0.000126
102
+ 7 6 0.000070
103
+ 7 7 0.000292
104
+ 7 8 0.000558
105
+ 7 9 0.000723
106
+ 8 0 0.001769
107
+ 8 1 0.001431
108
+ 8 2 0.001112
109
+ 8 3 0.000825
110
+ 8 4 0.000592
111
+ 8 5 0.000438
112
+ 8 6 0.000380
113
+ 8 7 0.000408
114
+ 8 8 0.000471
115
+ 8 9 0.000512
116
+ 9 0 0.000167
117
+ 9 1 0.000158
118
+ 9 2 0.000158
119
+ 9 3 0.000152
120
+ 9 4 0.000146
121
+ 9 5 0.000143
122
+ 9 6 0.000143
123
+ 9 7 0.000141
124
+ 9 8 0.000138
125
+ 9 9 0.000135
126
+ 10 0 0.004479
127
+ 10 1 0.001830
128
+ 10 2 0.000511
129
+ 10 3 0.000660
130
+ 10 4 0.001286
131
+ 10 5 0.001574
132
+ 10 6 0.001439
133
+ 10 7 0.001059
134
+ 10 8 0.000648
135
+ 10 9 0.000383
xenium_skin_mixed/sample15/log/Atp6v1b2.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Atp6v1b2
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 626 0.597389 0.000543 100 false 10 0.009461 0.002255
13
+ 1 680 626 0.534259 0.000177 100 false 10 0.000282 0.000204
14
+ 2 5552 626 0.923570 0.000548 100 false 10 0.010245 0.002143
15
+ 3 3231 626 0.634926 0.000388 100 false 10 0.000580 0.000407
16
+ 4 87 626 0.185573 0.000088 100 false 10 0.004760 0.001001
17
+ 5 96 626 0.802046 0.000287 100 false 10 0.000967 0.000318
18
+ 6 1210 626 0.734727 0.002796 100 false 10 0.005570 0.002833
19
+ 7 3 626 0.128217 0.000669 100 false 10 0.010128 0.001623
20
+ 8 448 626 0.837101 0.000180 100 false 10 0.000612 0.000239
21
+ 9 332 626 0.828212 0.000111 100 false 10 0.000693 0.000154
22
+ 10 82 626 0.589903 0.000074 100 false 10 0.002288 0.000414
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.009461
27
+ 0 1 0.004796
28
+ 0 2 0.001966
29
+ 0 3 0.000767
30
+ 0 4 0.000663
31
+ 0 5 0.001075
32
+ 0 6 0.001592
33
+ 0 7 0.001998
34
+ 0 8 0.002219
35
+ 0 9 0.002255
36
+ 1 0 0.000282
37
+ 1 1 0.000242
38
+ 1 2 0.000214
39
+ 1 3 0.000198
40
+ 1 4 0.000192
41
+ 1 5 0.000193
42
+ 1 6 0.000197
43
+ 1 7 0.000201
44
+ 1 8 0.000203
45
+ 1 9 0.000204
46
+ 2 0 0.010245
47
+ 2 1 0.008525
48
+ 2 2 0.007014
49
+ 2 3 0.005717
50
+ 2 4 0.004633
51
+ 2 5 0.003759
52
+ 2 6 0.003090
53
+ 2 7 0.002613
54
+ 2 8 0.002307
55
+ 2 9 0.002143
56
+ 3 0 0.000580
57
+ 3 1 0.000531
58
+ 3 2 0.000514
59
+ 3 3 0.000488
60
+ 3 4 0.000460
61
+ 3 5 0.000440
62
+ 3 6 0.000430
63
+ 3 7 0.000423
64
+ 3 8 0.000415
65
+ 3 9 0.000407
66
+ 4 0 0.004760
67
+ 4 1 0.003325
68
+ 4 2 0.002065
69
+ 4 3 0.001066
70
+ 4 4 0.000418
71
+ 4 5 0.000191
72
+ 4 6 0.000331
73
+ 4 7 0.000636
74
+ 4 8 0.000892
75
+ 4 9 0.001001
76
+ 5 0 0.000967
77
+ 5 1 0.000851
78
+ 5 2 0.000741
79
+ 5 3 0.000642
80
+ 5 4 0.000553
81
+ 5 5 0.000479
82
+ 5 6 0.000419
83
+ 5 7 0.000374
84
+ 5 8 0.000341
85
+ 5 9 0.000318
86
+ 6 0 0.005570
87
+ 6 1 0.004765
88
+ 6 2 0.004094
89
+ 6 3 0.003553
90
+ 6 4 0.003157
91
+ 6 5 0.002907
92
+ 6 6 0.002786
93
+ 6 7 0.002762
94
+ 6 8 0.002791
95
+ 6 9 0.002833
96
+ 7 0 0.010128
97
+ 7 1 0.006446
98
+ 7 2 0.003539
99
+ 7 3 0.001618
100
+ 7 4 0.000760
101
+ 7 5 0.000745
102
+ 7 6 0.001127
103
+ 7 7 0.001506
104
+ 7 8 0.001690
105
+ 7 9 0.001623
106
+ 8 0 0.000612
107
+ 8 1 0.000451
108
+ 8 2 0.000326
109
+ 8 3 0.000254
110
+ 8 4 0.000240
111
+ 8 5 0.000261
112
+ 8 6 0.000280
113
+ 8 7 0.000280
114
+ 8 8 0.000263
115
+ 8 9 0.000239
116
+ 9 0 0.000693
117
+ 9 1 0.000595
118
+ 9 2 0.000502
119
+ 9 3 0.000416
120
+ 9 4 0.000340
121
+ 9 5 0.000274
122
+ 9 6 0.000222
123
+ 9 7 0.000184
124
+ 9 8 0.000161
125
+ 9 9 0.000154
126
+ 10 0 0.002288
127
+ 10 1 0.001386
128
+ 10 2 0.000901
129
+ 10 3 0.000838
130
+ 10 4 0.000955
131
+ 10 5 0.000993
132
+ 10 6 0.000894
133
+ 10 7 0.000716
134
+ 10 8 0.000537
135
+ 10 9 0.000414
xenium_skin_mixed/sample15/log/Atrx.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Atrx
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 623 0.351777 0.000088 100 false 10 0.003636 0.000395
13
+ 1 680 623 0.579456 0.000123 100 false 10 0.000321 0.000140
14
+ 2 5552 623 0.822914 0.000100 100 false 10 0.000589 0.000330
15
+ 3 3231 623 0.564088 0.000137 100 false 10 0.000250 0.000162
16
+ 4 87 623 0.200045 0.000049 100 false 10 0.002335 0.000503
17
+ 5 96 623 0.846102 0.000103 100 false 10 0.000179 0.000107
18
+ 6 1210 623 0.512327 0.000096 100 false 10 0.000153 0.000104
19
+ 7 3 623 0.269467 0.000004 100 false 10 0.002841 0.000474
20
+ 8 448 623 0.793323 0.000169 100 false 10 0.000214 0.000188
21
+ 9 332 623 0.806304 0.000070 100 false 10 0.000118 0.000078
22
+ 10 82 623 0.263164 0.000071 100 false 10 0.007032 0.000646
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.003636
27
+ 0 1 0.003030
28
+ 0 2 0.002409
29
+ 0 3 0.001800
30
+ 0 4 0.001245
31
+ 0 5 0.000795
32
+ 0 6 0.000488
33
+ 0 7 0.000340
34
+ 0 8 0.000326
35
+ 0 9 0.000395
36
+ 1 0 0.000321
37
+ 1 1 0.000246
38
+ 1 2 0.000192
39
+ 1 3 0.000163
40
+ 1 4 0.000156
41
+ 1 5 0.000160
42
+ 1 6 0.000162
43
+ 1 7 0.000159
44
+ 1 8 0.000150
45
+ 1 9 0.000140
46
+ 2 0 0.000589
47
+ 2 1 0.000462
48
+ 2 2 0.000371
49
+ 2 3 0.000317
50
+ 2 4 0.000301
51
+ 2 5 0.000314
52
+ 2 6 0.000337
53
+ 2 7 0.000349
54
+ 2 8 0.000345
55
+ 2 9 0.000330
56
+ 3 0 0.000250
57
+ 3 1 0.000215
58
+ 3 2 0.000187
59
+ 3 3 0.000166
60
+ 3 4 0.000153
61
+ 3 5 0.000149
62
+ 3 6 0.000150
63
+ 3 7 0.000156
64
+ 3 8 0.000160
65
+ 3 9 0.000162
66
+ 4 0 0.002335
67
+ 4 1 0.001523
68
+ 4 2 0.000822
69
+ 4 3 0.000326
70
+ 4 4 0.000101
71
+ 4 5 0.000143
72
+ 4 6 0.000327
73
+ 4 7 0.000488
74
+ 4 8 0.000547
75
+ 4 9 0.000503
76
+ 5 0 0.000179
77
+ 5 1 0.000157
78
+ 5 2 0.000141
79
+ 5 3 0.000128
80
+ 5 4 0.000119
81
+ 5 5 0.000113
82
+ 5 6 0.000109
83
+ 5 7 0.000108
84
+ 5 8 0.000107
85
+ 5 9 0.000107
86
+ 6 0 0.000153
87
+ 6 1 0.000118
88
+ 6 2 0.000103
89
+ 6 3 0.000105
90
+ 6 4 0.000112
91
+ 6 5 0.000116
92
+ 6 6 0.000116
93
+ 6 7 0.000113
94
+ 6 8 0.000108
95
+ 6 9 0.000104
96
+ 7 0 0.002841
97
+ 7 1 0.002546
98
+ 7 2 0.002185
99
+ 7 3 0.001738
100
+ 7 4 0.001191
101
+ 7 5 0.000603
102
+ 7 6 0.000139
103
+ 7 7 0.000013
104
+ 7 8 0.000228
105
+ 7 9 0.000474
106
+ 8 0 0.000214
107
+ 8 1 0.000210
108
+ 8 2 0.000206
109
+ 8 3 0.000203
110
+ 8 4 0.000200
111
+ 8 5 0.000197
112
+ 8 6 0.000195
113
+ 8 7 0.000192
114
+ 8 8 0.000190
115
+ 8 9 0.000188
116
+ 9 0 0.000118
117
+ 9 1 0.000103
118
+ 9 2 0.000091
119
+ 9 3 0.000083
120
+ 9 4 0.000078
121
+ 9 5 0.000075
122
+ 9 6 0.000075
123
+ 9 7 0.000076
124
+ 9 8 0.000077
125
+ 9 9 0.000078
126
+ 10 0 0.007032
127
+ 10 1 0.005966
128
+ 10 2 0.004813
129
+ 10 3 0.003598
130
+ 10 4 0.002384
131
+ 10 5 0.001288
132
+ 10 6 0.000488
133
+ 10 7 0.000146
134
+ 10 8 0.000271
135
+ 10 9 0.000646
xenium_skin_mixed/sample15/log/Azi2.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Azi2
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 640 0.404372 0.000053 100 false 10 0.000619 0.000167
13
+ 1 680 640 0.586283 0.000122 100 false 10 0.000330 0.000177
14
+ 2 5552 640 0.690479 0.000097 100 false 10 0.000321 0.000143
15
+ 3 3231 640 0.762377 0.000101 100 false 10 0.000128 0.000109
16
+ 4 87 640 0.544155 0.000048 100 false 10 0.000872 0.000099
17
+ 5 96 640 0.666089 0.000213 100 false 10 0.001232 0.000310
18
+ 6 1210 640 0.414635 0.000161 100 false 10 0.000248 0.000186
19
+ 7 3 640 0.000000 0.000000 1 true 10 0.000000 0.000000
20
+ 8 448 640 0.700650 0.000150 100 false 10 0.001464 0.000431
21
+ 9 332 640 0.697109 0.000081 100 false 10 0.000338 0.000121
22
+ 10 82 640 0.664224 0.000124 100 false 10 0.003503 0.000907
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.000619
27
+ 0 1 0.000319
28
+ 0 2 0.000164
29
+ 0 3 0.000141
30
+ 0 4 0.000185
31
+ 0 5 0.000229
32
+ 0 6 0.000247
33
+ 0 7 0.000237
34
+ 0 8 0.000206
35
+ 0 9 0.000167
36
+ 1 0 0.000330
37
+ 1 1 0.000243
38
+ 1 2 0.000186
39
+ 1 3 0.000157
40
+ 1 4 0.000152
41
+ 1 5 0.000161
42
+ 1 6 0.000173
43
+ 1 7 0.000180
44
+ 1 8 0.000182
45
+ 1 9 0.000177
46
+ 2 0 0.000321
47
+ 2 1 0.000250
48
+ 2 2 0.000193
49
+ 2 3 0.000150
50
+ 2 4 0.000125
51
+ 2 5 0.000114
52
+ 2 6 0.000117
53
+ 2 7 0.000126
54
+ 2 8 0.000136
55
+ 2 9 0.000143
56
+ 3 0 0.000128
57
+ 3 1 0.000123
58
+ 3 2 0.000119
59
+ 3 3 0.000116
60
+ 3 4 0.000113
61
+ 3 5 0.000111
62
+ 3 6 0.000110
63
+ 3 7 0.000109
64
+ 3 8 0.000109
65
+ 3 9 0.000109
66
+ 4 0 0.000872
67
+ 4 1 0.000360
68
+ 4 2 0.000113
69
+ 4 3 0.000105
70
+ 4 4 0.000210
71
+ 4 5 0.000290
72
+ 4 6 0.000294
73
+ 4 7 0.000240
74
+ 4 8 0.000164
75
+ 4 9 0.000099
76
+ 5 0 0.001232
77
+ 5 1 0.000692
78
+ 5 2 0.000371
79
+ 5 3 0.000327
80
+ 5 4 0.000441
81
+ 5 5 0.000525
82
+ 5 6 0.000526
83
+ 5 7 0.000465
84
+ 5 8 0.000381
85
+ 5 9 0.000310
86
+ 6 0 0.000248
87
+ 6 1 0.000207
88
+ 6 2 0.000191
89
+ 6 3 0.000197
90
+ 6 4 0.000206
91
+ 6 5 0.000206
92
+ 6 6 0.000199
93
+ 6 7 0.000191
94
+ 6 8 0.000186
95
+ 6 9 0.000186
96
+ 7 0 0.000000
97
+ 7 1 0.000000
98
+ 7 2 0.000000
99
+ 7 3 0.000000
100
+ 7 4 0.000000
101
+ 7 5 0.000000
102
+ 7 6 0.000000
103
+ 7 7 0.000000
104
+ 7 8 0.000000
105
+ 7 9 0.000000
106
+ 8 0 0.001464
107
+ 8 1 0.001098
108
+ 8 2 0.000787
109
+ 8 3 0.000548
110
+ 8 4 0.000392
111
+ 8 5 0.000323
112
+ 8 6 0.000328
113
+ 8 7 0.000372
114
+ 8 8 0.000415
115
+ 8 9 0.000431
116
+ 9 0 0.000338
117
+ 9 1 0.000188
118
+ 9 2 0.000118
119
+ 9 3 0.000117
120
+ 9 4 0.000144
121
+ 9 5 0.000164
122
+ 9 6 0.000168
123
+ 9 7 0.000159
124
+ 9 8 0.000141
125
+ 9 9 0.000121
126
+ 10 0 0.003503
127
+ 10 1 0.002924
128
+ 10 2 0.002370
129
+ 10 3 0.001836
130
+ 10 4 0.001326
131
+ 10 5 0.000873
132
+ 10 6 0.000549
133
+ 10 7 0.000463
134
+ 10 8 0.000665
135
+ 10 9 0.000907
xenium_skin_mixed/sample15/log/Bach1.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Bach1
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 641 0.621357 0.000147 100 false 10 0.006953 0.001525
13
+ 1 680 641 0.386412 0.000054 100 false 10 0.000381 0.000109
14
+ 2 5552 641 0.820313 0.000329 100 false 10 0.002193 0.000676
15
+ 3 3231 641 0.404842 0.000136 100 false 10 0.000194 0.000166
16
+ 4 87 641 0.638915 0.000032 100 false 10 0.000284 0.000080
17
+ 5 96 641 0.927426 0.000096 100 false 10 0.000210 0.000133
18
+ 6 1210 641 0.794866 0.000256 100 false 10 0.001000 0.000299
19
+ 7 3 641 0.182174 0.000085 100 false 10 0.001536 0.000192
20
+ 8 448 641 0.620780 0.000134 100 false 10 0.000597 0.000145
21
+ 9 332 641 0.928042 0.000359 100 false 10 0.000650 0.000407
22
+ 10 82 641 0.489847 0.000078 100 false 10 0.004256 0.000885
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.006953
27
+ 0 1 0.005133
28
+ 0 2 0.003408
29
+ 0 3 0.001894
30
+ 0 4 0.000781
31
+ 0 5 0.000268
32
+ 0 6 0.000416
33
+ 0 7 0.000943
34
+ 0 8 0.001389
35
+ 0 9 0.001525
36
+ 1 0 0.000381
37
+ 1 1 0.000272
38
+ 1 2 0.000174
39
+ 1 3 0.000105
40
+ 1 4 0.000073
41
+ 1 5 0.000068
42
+ 1 6 0.000077
43
+ 1 7 0.000090
44
+ 1 8 0.000101
45
+ 1 9 0.000109
46
+ 2 0 0.002193
47
+ 2 1 0.001435
48
+ 2 2 0.000900
49
+ 2 3 0.000575
50
+ 2 4 0.000429
51
+ 2 5 0.000414
52
+ 2 6 0.000476
53
+ 2 7 0.000563
54
+ 2 8 0.000636
55
+ 2 9 0.000676
56
+ 3 0 0.000194
57
+ 3 1 0.000187
58
+ 3 2 0.000184
59
+ 3 3 0.000181
60
+ 3 4 0.000179
61
+ 3 5 0.000176
62
+ 3 6 0.000173
63
+ 3 7 0.000170
64
+ 3 8 0.000168
65
+ 3 9 0.000166
66
+ 4 0 0.000284
67
+ 4 1 0.000159
68
+ 4 2 0.000089
69
+ 4 3 0.000066
70
+ 4 4 0.000075
71
+ 4 5 0.000095
72
+ 4 6 0.000107
73
+ 4 7 0.000107
74
+ 4 8 0.000096
75
+ 4 9 0.000080
76
+ 5 0 0.000210
77
+ 5 1 0.000182
78
+ 5 2 0.000161
79
+ 5 3 0.000145
80
+ 5 4 0.000136
81
+ 5 5 0.000133
82
+ 5 6 0.000132
83
+ 5 7 0.000133
84
+ 5 8 0.000133
85
+ 5 9 0.000133
86
+ 6 0 0.001000
87
+ 6 1 0.000856
88
+ 6 2 0.000729
89
+ 6 3 0.000621
90
+ 6 4 0.000530
91
+ 6 5 0.000455
92
+ 6 6 0.000396
93
+ 6 7 0.000352
94
+ 6 8 0.000320
95
+ 6 9 0.000299
96
+ 7 0 0.001536
97
+ 7 1 0.000848
98
+ 7 2 0.000329
99
+ 7 3 0.000058
100
+ 7 4 0.000046
101
+ 7 5 0.000185
102
+ 7 6 0.000315
103
+ 7 7 0.000345
104
+ 7 8 0.000291
105
+ 7 9 0.000192
106
+ 8 0 0.000597
107
+ 8 1 0.000520
108
+ 8 2 0.000444
109
+ 8 3 0.000371
110
+ 8 4 0.000303
111
+ 8 5 0.000241
112
+ 8 6 0.000190
113
+ 8 7 0.000155
114
+ 8 8 0.000140
115
+ 8 9 0.000145
116
+ 9 0 0.000650
117
+ 9 1 0.000484
118
+ 9 2 0.000509
119
+ 9 3 0.000516
120
+ 9 4 0.000470
121
+ 9 5 0.000421
122
+ 9 6 0.000404
123
+ 9 7 0.000411
124
+ 9 8 0.000417
125
+ 9 9 0.000407
126
+ 10 0 0.004256
127
+ 10 1 0.002892
128
+ 10 2 0.001696
129
+ 10 3 0.000787
130
+ 10 4 0.000268
131
+ 10 5 0.000149
132
+ 10 6 0.000309
133
+ 10 7 0.000563
134
+ 10 8 0.000776
135
+ 10 9 0.000885
xenium_skin_mixed/sample15/log/Bap1.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Bap1
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 640 0.423885 0.000012 100 false 10 0.000115 0.000043
13
+ 1 680 640 0.498487 0.000038 100 false 10 0.000064 0.000052
14
+ 2 5552 640 0.642043 0.000043 100 false 10 0.000053 0.000046
15
+ 3 3231 640 0.509807 0.000046 100 false 10 0.000108 0.000070
16
+ 4 87 640 0.000000 0.000015 100 false 10 0.000458 0.000026
17
+ 5 96 640 0.847570 0.000006 100 false 10 0.000009 0.000008
18
+ 6 1210 640 0.331936 0.000047 100 false 10 0.000047 0.000047
19
+ 7 3 640 0.000000 0.000000 1 true 10 0.000000 0.000000
20
+ 8 448 640 0.368227 0.000047 100 false 10 0.000086 0.000056
21
+ 9 332 640 0.614468 0.000037 100 false 10 0.000039 0.000038
22
+ 10 82 640 0.478863 0.000055 100 false 10 0.000286 0.000063
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.000115
27
+ 0 1 0.000106
28
+ 0 2 0.000097
29
+ 0 3 0.000088
30
+ 0 4 0.000080
31
+ 0 5 0.000072
32
+ 0 6 0.000064
33
+ 0 7 0.000056
34
+ 0 8 0.000050
35
+ 0 9 0.000043
36
+ 1 0 0.000064
37
+ 1 1 0.000061
38
+ 1 2 0.000060
39
+ 1 3 0.000059
40
+ 1 4 0.000057
41
+ 1 5 0.000056
42
+ 1 6 0.000055
43
+ 1 7 0.000054
44
+ 1 8 0.000053
45
+ 1 9 0.000052
46
+ 2 0 0.000053
47
+ 2 1 0.000049
48
+ 2 2 0.000046
49
+ 2 3 0.000045
50
+ 2 4 0.000045
51
+ 2 5 0.000046
52
+ 2 6 0.000046
53
+ 2 7 0.000046
54
+ 2 8 0.000046
55
+ 2 9 0.000046
56
+ 3 0 0.000108
57
+ 3 1 0.000102
58
+ 3 2 0.000097
59
+ 3 3 0.000092
60
+ 3 4 0.000087
61
+ 3 5 0.000083
62
+ 3 6 0.000079
63
+ 3 7 0.000076
64
+ 3 8 0.000073
65
+ 3 9 0.000070
66
+ 4 0 0.000458
67
+ 4 1 0.000377
68
+ 4 2 0.000295
69
+ 4 3 0.000217
70
+ 4 4 0.000146
71
+ 4 5 0.000088
72
+ 4 6 0.000047
73
+ 4 7 0.000025
74
+ 4 8 0.000019
75
+ 4 9 0.000026
76
+ 5 0 0.000009
77
+ 5 1 0.000009
78
+ 5 2 0.000009
79
+ 5 3 0.000009
80
+ 5 4 0.000008
81
+ 5 5 0.000008
82
+ 5 6 0.000008
83
+ 5 7 0.000008
84
+ 5 8 0.000008
85
+ 5 9 0.000008
86
+ 6 0 0.000047
87
+ 6 1 0.000047
88
+ 6 2 0.000047
89
+ 6 3 0.000047
90
+ 6 4 0.000047
91
+ 6 5 0.000047
92
+ 6 6 0.000047
93
+ 6 7 0.000047
94
+ 6 8 0.000047
95
+ 6 9 0.000047
96
+ 7 0 0.000000
97
+ 7 1 0.000000
98
+ 7 2 0.000000
99
+ 7 3 0.000000
100
+ 7 4 0.000000
101
+ 7 5 0.000000
102
+ 7 6 0.000000
103
+ 7 7 0.000000
104
+ 7 8 0.000000
105
+ 7 9 0.000000
106
+ 8 0 0.000086
107
+ 8 1 0.000073
108
+ 8 2 0.000067
109
+ 8 3 0.000065
110
+ 8 4 0.000064
111
+ 8 5 0.000063
112
+ 8 6 0.000061
113
+ 8 7 0.000059
114
+ 8 8 0.000057
115
+ 8 9 0.000056
116
+ 9 0 0.000039
117
+ 9 1 0.000039
118
+ 9 2 0.000039
119
+ 9 3 0.000039
120
+ 9 4 0.000039
121
+ 9 5 0.000038
122
+ 9 6 0.000038
123
+ 9 7 0.000038
124
+ 9 8 0.000038
125
+ 9 9 0.000038
126
+ 10 0 0.000286
127
+ 10 1 0.000231
128
+ 10 2 0.000184
129
+ 10 3 0.000147
130
+ 10 4 0.000118
131
+ 10 5 0.000097
132
+ 10 6 0.000081
133
+ 10 7 0.000071
134
+ 10 8 0.000065
135
+ 10 9 0.000063
xenium_skin_mixed/sample15/log/Bcam.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Bcam
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 627 0.230359 0.000014 100 false 10 0.000025 0.000014
13
+ 1 680 627 0.912798 0.001811 100 false 10 0.010826 0.002676
14
+ 2 5552 627 0.943921 0.002632 100 false 10 0.075170 0.021415
15
+ 3 3231 627 0.610965 0.000232 100 false 10 0.000578 0.000293
16
+ 4 87 627 0.696034 0.000216 100 false 10 0.001154 0.000403
17
+ 5 96 627 0.953781 0.000112 100 false 10 0.001551 0.000402
18
+ 6 1210 627 0.746569 0.000085 100 false 10 0.000169 0.000122
19
+ 7 3 627 0.177478 0.000038 100 false 10 0.000161 0.000028
20
+ 8 448 627 0.913713 0.002322 100 false 10 0.021613 0.006998
21
+ 9 332 627 0.974496 0.000685 100 false 10 0.004842 0.000994
22
+ 10 82 627 0.505774 0.000003 100 false 10 0.000111 0.000011
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.000025
27
+ 0 1 0.000022
28
+ 0 2 0.000020
29
+ 0 3 0.000017
30
+ 0 4 0.000016
31
+ 0 5 0.000015
32
+ 0 6 0.000014
33
+ 0 7 0.000014
34
+ 0 8 0.000014
35
+ 0 9 0.000014
36
+ 1 0 0.010826
37
+ 1 1 0.008523
38
+ 1 2 0.006940
39
+ 1 3 0.005868
40
+ 1 4 0.005077
41
+ 1 5 0.004423
42
+ 1 6 0.003848
43
+ 1 7 0.003351
44
+ 1 8 0.002952
45
+ 1 9 0.002676
46
+ 2 0 0.075170
47
+ 2 1 0.058641
48
+ 2 2 0.045651
49
+ 2 3 0.035997
50
+ 2 4 0.029308
51
+ 2 5 0.025124
52
+ 2 6 0.022914
53
+ 2 7 0.022019
54
+ 2 8 0.021713
55
+ 2 9 0.021415
56
+ 3 0 0.000578
57
+ 3 1 0.000471
58
+ 3 2 0.000386
59
+ 3 3 0.000325
60
+ 3 4 0.000287
61
+ 3 5 0.000270
62
+ 3 6 0.000267
63
+ 3 7 0.000274
64
+ 3 8 0.000284
65
+ 3 9 0.000293
66
+ 4 0 0.001154
67
+ 4 1 0.000659
68
+ 4 2 0.000388
69
+ 4 3 0.000283
70
+ 4 4 0.000287
71
+ 4 5 0.000347
72
+ 4 6 0.000409
73
+ 4 7 0.000438
74
+ 4 8 0.000432
75
+ 4 9 0.000403
76
+ 5 0 0.001551
77
+ 5 1 0.001071
78
+ 5 2 0.000692
79
+ 5 3 0.000448
80
+ 5 4 0.000349
81
+ 5 5 0.000359
82
+ 5 6 0.000403
83
+ 5 7 0.000429
84
+ 5 8 0.000425
85
+ 5 9 0.000402
86
+ 6 0 0.000169
87
+ 6 1 0.000156
88
+ 6 2 0.000146
89
+ 6 3 0.000138
90
+ 6 4 0.000131
91
+ 6 5 0.000127
92
+ 6 6 0.000124
93
+ 6 7 0.000123
94
+ 6 8 0.000122
95
+ 6 9 0.000122
96
+ 7 0 0.000161
97
+ 7 1 0.000106
98
+ 7 2 0.000062
99
+ 7 3 0.000032
100
+ 7 4 0.000015
101
+ 7 5 0.000010
102
+ 7 6 0.000014
103
+ 7 7 0.000021
104
+ 7 8 0.000026
105
+ 7 9 0.000028
106
+ 8 0 0.021613
107
+ 8 1 0.015873
108
+ 8 2 0.011086
109
+ 8 3 0.007513
110
+ 8 4 0.005445
111
+ 8 5 0.004996
112
+ 8 6 0.005774
113
+ 8 7 0.006819
114
+ 8 8 0.007294
115
+ 8 9 0.006998
116
+ 9 0 0.004842
117
+ 9 1 0.004174
118
+ 9 2 0.003567
119
+ 9 3 0.003005
120
+ 9 4 0.002496
121
+ 9 5 0.002048
122
+ 9 6 0.001661
123
+ 9 7 0.001344
124
+ 9 8 0.001114
125
+ 9 9 0.000994
126
+ 10 0 0.000111
127
+ 10 1 0.000052
128
+ 10 2 0.000018
129
+ 10 3 0.000012
130
+ 10 4 0.000025
131
+ 10 5 0.000035
132
+ 10 6 0.000034
133
+ 10 7 0.000026
134
+ 10 8 0.000016
135
+ 10 9 0.000011
xenium_skin_mixed/sample15/log/Bcl2l11.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Bcl2l11
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 662 0.645678 0.000030 100 false 10 0.000215 0.000067
13
+ 1 680 662 0.376044 0.000037 100 false 10 0.000052 0.000040
14
+ 2 5552 662 0.703430 0.000059 100 false 10 0.000362 0.000151
15
+ 3 3231 662 0.520096 0.000026 100 false 10 0.000053 0.000032
16
+ 4 87 662 0.646805 0.000002 100 false 10 0.000002 0.000002
17
+ 5 96 662 0.582248 0.000029 100 false 10 0.000051 0.000039
18
+ 6 1210 662 0.719397 0.000038 100 false 10 0.000066 0.000043
19
+ 7 3 662 0.150258 0.000000 100 false 10 0.000102 0.000007
20
+ 8 448 662 0.495837 0.000005 100 false 10 0.000007 0.000007
21
+ 9 332 662 0.661106 0.000033 100 false 10 0.000049 0.000045
22
+ 10 82 662 0.502459 0.000033 100 false 10 0.000942 0.000034
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.000215
27
+ 0 1 0.000136
28
+ 0 2 0.000078
29
+ 0 3 0.000043
30
+ 0 4 0.000032
31
+ 0 5 0.000037
32
+ 0 6 0.000049
33
+ 0 7 0.000060
34
+ 0 8 0.000066
35
+ 0 9 0.000067
36
+ 1 0 0.000052
37
+ 1 1 0.000050
38
+ 1 2 0.000048
39
+ 1 3 0.000047
40
+ 1 4 0.000045
41
+ 1 5 0.000044
42
+ 1 6 0.000043
43
+ 1 7 0.000042
44
+ 1 8 0.000041
45
+ 1 9 0.000040
46
+ 2 0 0.000362
47
+ 2 1 0.000290
48
+ 2 2 0.000234
49
+ 2 3 0.000194
50
+ 2 4 0.000169
51
+ 2 5 0.000155
52
+ 2 6 0.000149
53
+ 2 7 0.000148
54
+ 2 8 0.000149
55
+ 2 9 0.000151
56
+ 3 0 0.000053
57
+ 3 1 0.000050
58
+ 3 2 0.000048
59
+ 3 3 0.000045
60
+ 3 4 0.000043
61
+ 3 5 0.000040
62
+ 3 6 0.000038
63
+ 3 7 0.000036
64
+ 3 8 0.000034
65
+ 3 9 0.000032
66
+ 4 0 0.000002
67
+ 4 1 0.000002
68
+ 4 2 0.000002
69
+ 4 3 0.000002
70
+ 4 4 0.000002
71
+ 4 5 0.000002
72
+ 4 6 0.000002
73
+ 4 7 0.000002
74
+ 4 8 0.000002
75
+ 4 9 0.000002
76
+ 5 0 0.000051
77
+ 5 1 0.000049
78
+ 5 2 0.000046
79
+ 5 3 0.000044
80
+ 5 4 0.000042
81
+ 5 5 0.000041
82
+ 5 6 0.000040
83
+ 5 7 0.000040
84
+ 5 8 0.000039
85
+ 5 9 0.000039
86
+ 6 0 0.000066
87
+ 6 1 0.000062
88
+ 6 2 0.000058
89
+ 6 3 0.000055
90
+ 6 4 0.000052
91
+ 6 5 0.000049
92
+ 6 6 0.000047
93
+ 6 7 0.000045
94
+ 6 8 0.000044
95
+ 6 9 0.000043
96
+ 7 0 0.000102
97
+ 7 1 0.000052
98
+ 7 2 0.000025
99
+ 7 3 0.000017
100
+ 7 4 0.000020
101
+ 7 5 0.000024
102
+ 7 6 0.000024
103
+ 7 7 0.000020
104
+ 7 8 0.000014
105
+ 7 9 0.000007
106
+ 8 0 0.000007
107
+ 8 1 0.000007
108
+ 8 2 0.000007
109
+ 8 3 0.000007
110
+ 8 4 0.000007
111
+ 8 5 0.000007
112
+ 8 6 0.000007
113
+ 8 7 0.000007
114
+ 8 8 0.000007
115
+ 8 9 0.000007
116
+ 9 0 0.000049
117
+ 9 1 0.000048
118
+ 9 2 0.000048
119
+ 9 3 0.000047
120
+ 9 4 0.000047
121
+ 9 5 0.000046
122
+ 9 6 0.000046
123
+ 9 7 0.000045
124
+ 9 8 0.000045
125
+ 9 9 0.000045
126
+ 10 0 0.000942
127
+ 10 1 0.000755
128
+ 10 2 0.000573
129
+ 10 3 0.000407
130
+ 10 4 0.000269
131
+ 10 5 0.000164
132
+ 10 6 0.000095
133
+ 10 7 0.000055
134
+ 10 8 0.000037
135
+ 10 9 0.000034
xenium_skin_mixed/sample15/log/Bcl7b.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Bcl7b
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 649 0.776837 0.000094 100 false 10 0.001965 0.000384
13
+ 1 680 649 0.561448 0.000091 100 false 10 0.001191 0.000242
14
+ 2 5552 649 0.530474 0.000085 100 false 10 0.000118 0.000093
15
+ 3 3231 649 0.725669 0.000114 100 false 10 0.000136 0.000127
16
+ 4 87 649 0.534016 0.000044 100 false 10 0.000319 0.000094
17
+ 5 96 649 0.937657 0.000045 100 false 10 0.000211 0.000102
18
+ 6 1210 649 0.629111 0.000132 100 false 10 0.000167 0.000141
19
+ 7 3 649 0.202895 0.000012 100 false 10 0.000244 0.000034
20
+ 8 448 649 0.692708 0.000198 100 false 10 0.000986 0.000346
21
+ 9 332 649 0.757890 0.000103 100 false 10 0.000195 0.000115
22
+ 10 82 649 0.468904 0.000039 100 false 10 0.000749 0.000078
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.001965
27
+ 0 1 0.001499
28
+ 0 2 0.001077
29
+ 0 3 0.000720
30
+ 0 4 0.000446
31
+ 0 5 0.000274
32
+ 0 6 0.000208
33
+ 0 7 0.000232
34
+ 0 8 0.000306
35
+ 0 9 0.000384
36
+ 1 0 0.001191
37
+ 1 1 0.000929
38
+ 1 2 0.000684
39
+ 1 3 0.000465
40
+ 1 4 0.000287
41
+ 1 5 0.000164
42
+ 1 6 0.000109
43
+ 1 7 0.000123
44
+ 1 8 0.000181
45
+ 1 9 0.000242
46
+ 2 0 0.000118
47
+ 2 1 0.000103
48
+ 2 2 0.000096
49
+ 2 3 0.000095
50
+ 2 4 0.000097
51
+ 2 5 0.000099
52
+ 2 6 0.000099
53
+ 2 7 0.000097
54
+ 2 8 0.000095
55
+ 2 9 0.000093
56
+ 3 0 0.000136
57
+ 3 1 0.000134
58
+ 3 2 0.000132
59
+ 3 3 0.000131
60
+ 3 4 0.000130
61
+ 3 5 0.000129
62
+ 3 6 0.000129
63
+ 3 7 0.000128
64
+ 3 8 0.000127
65
+ 3 9 0.000127
66
+ 4 0 0.000319
67
+ 4 1 0.000149
68
+ 4 2 0.000085
69
+ 4 3 0.000131
70
+ 4 4 0.000164
71
+ 4 5 0.000137
72
+ 4 6 0.000096
73
+ 4 7 0.000077
74
+ 4 8 0.000081
75
+ 4 9 0.000094
76
+ 5 0 0.000211
77
+ 5 1 0.000176
78
+ 5 2 0.000152
79
+ 5 3 0.000137
80
+ 5 4 0.000129
81
+ 5 5 0.000125
82
+ 5 6 0.000121
83
+ 5 7 0.000116
84
+ 5 8 0.000109
85
+ 5 9 0.000102
86
+ 6 0 0.000167
87
+ 6 1 0.000155
88
+ 6 2 0.000147
89
+ 6 3 0.000142
90
+ 6 4 0.000140
91
+ 6 5 0.000139
92
+ 6 6 0.000140
93
+ 6 7 0.000140
94
+ 6 8 0.000141
95
+ 6 9 0.000141
96
+ 7 0 0.000244
97
+ 7 1 0.000196
98
+ 7 2 0.000099
99
+ 7 3 0.000046
100
+ 7 4 0.000040
101
+ 7 5 0.000029
102
+ 7 6 0.000019
103
+ 7 7 0.000025
104
+ 7 8 0.000035
105
+ 7 9 0.000034
106
+ 8 0 0.000986
107
+ 8 1 0.000666
108
+ 8 2 0.000450
109
+ 8 3 0.000349
110
+ 8 4 0.000341
111
+ 8 5 0.000373
112
+ 8 6 0.000400
113
+ 8 7 0.000403
114
+ 8 8 0.000382
115
+ 8 9 0.000346
116
+ 9 0 0.000195
117
+ 9 1 0.000169
118
+ 9 2 0.000150
119
+ 9 3 0.000137
120
+ 9 4 0.000127
121
+ 9 5 0.000121
122
+ 9 6 0.000118
123
+ 9 7 0.000116
124
+ 9 8 0.000115
125
+ 9 9 0.000115
126
+ 10 0 0.000749
127
+ 10 1 0.000636
128
+ 10 2 0.000529
129
+ 10 3 0.000429
130
+ 10 4 0.000340
131
+ 10 5 0.000263
132
+ 10 6 0.000199
133
+ 10 7 0.000147
134
+ 10 8 0.000107
135
+ 10 9 0.000078
xenium_skin_mixed/sample15/log/Bclaf1.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Bclaf1
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 639 0.698162 0.000100 100 false 10 0.000395 0.000134
13
+ 1 680 639 0.341603 0.000135 100 false 10 0.000903 0.000252
14
+ 2 5552 639 0.848609 0.000150 100 false 10 0.000462 0.000243
15
+ 3 3231 639 0.693458 0.000161 100 false 10 0.000328 0.000180
16
+ 4 87 639 0.595765 0.000059 100 false 10 0.016463 0.002732
17
+ 5 96 639 0.946250 0.000088 100 false 10 0.000432 0.000143
18
+ 6 1210 639 0.522699 0.000132 100 false 10 0.000187 0.000147
19
+ 7 3 639 0.141132 0.000000 100 false 10 0.000045 0.000008
20
+ 8 448 639 0.668441 0.000169 100 false 10 0.000330 0.000185
21
+ 9 332 639 0.803405 0.000080 100 false 10 0.000365 0.000125
22
+ 10 82 639 0.525604 0.000145 100 false 10 0.000351 0.000156
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.000395
27
+ 0 1 0.000209
28
+ 0 2 0.000314
29
+ 0 3 0.000259
30
+ 0 4 0.000172
31
+ 0 5 0.000159
32
+ 0 6 0.000196
33
+ 0 7 0.000199
34
+ 0 8 0.000163
35
+ 0 9 0.000134
36
+ 1 0 0.000903
37
+ 1 1 0.000567
38
+ 1 2 0.000323
39
+ 1 3 0.000205
40
+ 1 4 0.000213
41
+ 1 5 0.000280
42
+ 1 6 0.000329
43
+ 1 7 0.000334
44
+ 1 8 0.000301
45
+ 1 9 0.000252
46
+ 2 0 0.000462
47
+ 2 1 0.000358
48
+ 2 2 0.000304
49
+ 2 3 0.000283
50
+ 2 4 0.000280
51
+ 2 5 0.000281
52
+ 2 6 0.000277
53
+ 2 7 0.000267
54
+ 2 8 0.000255
55
+ 2 9 0.000243
56
+ 3 0 0.000328
57
+ 3 1 0.000303
58
+ 3 2 0.000279
59
+ 3 3 0.000258
60
+ 3 4 0.000239
61
+ 3 5 0.000223
62
+ 3 6 0.000209
63
+ 3 7 0.000197
64
+ 3 8 0.000187
65
+ 3 9 0.000180
66
+ 4 0 0.016463
67
+ 4 1 0.012244
68
+ 4 2 0.008124
69
+ 4 3 0.004459
70
+ 4 4 0.001700
71
+ 4 5 0.000260
72
+ 4 6 0.000202
73
+ 4 7 0.001035
74
+ 4 8 0.002035
75
+ 4 9 0.002732
76
+ 5 0 0.000432
77
+ 5 1 0.000332
78
+ 5 2 0.000257
79
+ 5 3 0.000216
80
+ 5 4 0.000203
81
+ 5 5 0.000200
82
+ 5 6 0.000193
83
+ 5 7 0.000179
84
+ 5 8 0.000160
85
+ 5 9 0.000143
86
+ 6 0 0.000187
87
+ 6 1 0.000175
88
+ 6 2 0.000168
89
+ 6 3 0.000163
90
+ 6 4 0.000160
91
+ 6 5 0.000158
92
+ 6 6 0.000155
93
+ 6 7 0.000152
94
+ 6 8 0.000149
95
+ 6 9 0.000147
96
+ 7 0 0.000045
97
+ 7 1 0.000025
98
+ 7 2 0.000010
99
+ 7 3 0.000003
100
+ 7 4 0.000001
101
+ 7 5 0.000003
102
+ 7 6 0.000006
103
+ 7 7 0.000008
104
+ 7 8 0.000009
105
+ 7 9 0.000008
106
+ 8 0 0.000330
107
+ 8 1 0.000264
108
+ 8 2 0.000220
109
+ 8 3 0.000201
110
+ 8 4 0.000198
111
+ 8 5 0.000201
112
+ 8 6 0.000202
113
+ 8 7 0.000198
114
+ 8 8 0.000192
115
+ 8 9 0.000185
116
+ 9 0 0.000365
117
+ 9 1 0.000301
118
+ 9 2 0.000246
119
+ 9 3 0.000201
120
+ 9 4 0.000167
121
+ 9 5 0.000143
122
+ 9 6 0.000128
123
+ 9 7 0.000122
124
+ 9 8 0.000122
125
+ 9 9 0.000125
126
+ 10 0 0.000351
127
+ 10 1 0.000231
128
+ 10 2 0.000179
129
+ 10 3 0.000179
130
+ 10 4 0.000199
131
+ 10 5 0.000211
132
+ 10 6 0.000205
133
+ 10 7 0.000188
134
+ 10 8 0.000170
135
+ 10 9 0.000156
xenium_skin_mixed/sample15/log/Bcr.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Bcr
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 635 0.536696 0.000010 100 false 10 0.000024 0.000011
13
+ 1 680 635 0.952553 0.000320 100 false 10 0.006274 0.000594
14
+ 2 5552 635 0.908520 0.000225 100 false 10 0.002675 0.000415
15
+ 3 3231 635 0.433706 0.000055 100 false 10 0.000056 0.000056
16
+ 4 87 635 0.543409 0.000043 100 false 10 0.000546 0.000059
17
+ 5 96 635 0.872551 0.000139 100 false 10 0.000466 0.000170
18
+ 6 1210 635 0.226309 0.000026 100 false 10 0.000027 0.000026
19
+ 7 3 635 0.195351 0.000000 100 false 10 0.000027 0.000008
20
+ 8 448 635 0.818103 0.000055 100 false 10 0.000103 0.000072
21
+ 9 332 635 0.765514 0.000067 100 false 10 0.000126 0.000089
22
+ 10 82 635 0.149086 0.000027 100 false 10 0.000583 0.000164
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.000024
27
+ 0 1 0.000021
28
+ 0 2 0.000019
29
+ 0 3 0.000017
30
+ 0 4 0.000016
31
+ 0 5 0.000014
32
+ 0 6 0.000013
33
+ 0 7 0.000012
34
+ 0 8 0.000012
35
+ 0 9 0.000011
36
+ 1 0 0.006274
37
+ 1 1 0.005058
38
+ 1 2 0.004009
39
+ 1 3 0.003132
40
+ 1 4 0.002414
41
+ 1 5 0.001837
42
+ 1 6 0.001381
43
+ 1 7 0.001031
44
+ 1 8 0.000773
45
+ 1 9 0.000594
46
+ 2 0 0.002675
47
+ 2 1 0.002199
48
+ 2 2 0.001776
49
+ 2 3 0.001409
50
+ 2 4 0.001100
51
+ 2 5 0.000849
52
+ 2 6 0.000656
53
+ 2 7 0.000522
54
+ 2 8 0.000443
55
+ 2 9 0.000415
56
+ 3 0 0.000056
57
+ 3 1 0.000056
58
+ 3 2 0.000056
59
+ 3 3 0.000056
60
+ 3 4 0.000056
61
+ 3 5 0.000056
62
+ 3 6 0.000056
63
+ 3 7 0.000056
64
+ 3 8 0.000056
65
+ 3 9 0.000056
66
+ 4 0 0.000546
67
+ 4 1 0.000374
68
+ 4 2 0.000248
69
+ 4 3 0.000163
70
+ 4 4 0.000109
71
+ 4 5 0.000076
72
+ 4 6 0.000059
73
+ 4 7 0.000052
74
+ 4 8 0.000053
75
+ 4 9 0.000059
76
+ 5 0 0.000466
77
+ 5 1 0.000421
78
+ 5 2 0.000378
79
+ 5 3 0.000336
80
+ 5 4 0.000296
81
+ 5 5 0.000259
82
+ 5 6 0.000227
83
+ 5 7 0.000201
84
+ 5 8 0.000182
85
+ 5 9 0.000170
86
+ 6 0 0.000027
87
+ 6 1 0.000027
88
+ 6 2 0.000027
89
+ 6 3 0.000027
90
+ 6 4 0.000027
91
+ 6 5 0.000027
92
+ 6 6 0.000027
93
+ 6 7 0.000026
94
+ 6 8 0.000026
95
+ 6 9 0.000026
96
+ 7 0 0.000027
97
+ 7 1 0.000017
98
+ 7 2 0.000010
99
+ 7 3 0.000006
100
+ 7 4 0.000006
101
+ 7 5 0.000006
102
+ 7 6 0.000008
103
+ 7 7 0.000008
104
+ 7 8 0.000008
105
+ 7 9 0.000008
106
+ 8 0 0.000103
107
+ 8 1 0.000097
108
+ 8 2 0.000092
109
+ 8 3 0.000088
110
+ 8 4 0.000084
111
+ 8 5 0.000081
112
+ 8 6 0.000078
113
+ 8 7 0.000076
114
+ 8 8 0.000074
115
+ 8 9 0.000072
116
+ 9 0 0.000126
117
+ 9 1 0.000137
118
+ 9 2 0.000112
119
+ 9 3 0.000103
120
+ 9 4 0.000107
121
+ 9 5 0.000100
122
+ 9 6 0.000090
123
+ 9 7 0.000088
124
+ 9 8 0.000091
125
+ 9 9 0.000089
126
+ 10 0 0.000583
127
+ 10 1 0.000484
128
+ 10 2 0.000380
129
+ 10 3 0.000277
130
+ 10 4 0.000185
131
+ 10 5 0.000116
132
+ 10 6 0.000086
133
+ 10 7 0.000099
134
+ 10 8 0.000135
135
+ 10 9 0.000164
xenium_skin_mixed/sample15/log/Bex3.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Bex3
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 640 0.756070 0.000042 100 false 10 0.000060 0.000045
13
+ 1 680 640 0.457905 0.000038 100 false 10 0.000180 0.000062
14
+ 2 5552 640 0.890807 0.000107 100 false 10 0.000382 0.000206
15
+ 3 3231 640 0.736981 0.000051 100 false 10 0.000120 0.000068
16
+ 4 87 640 0.281510 0.000016 100 false 10 0.000059 0.000025
17
+ 5 96 640 0.876519 0.000028 100 false 10 0.000029 0.000026
18
+ 6 1210 640 0.671344 0.000054 100 false 10 0.000245 0.000070
19
+ 7 3 640 0.000000 0.000000 1 true 10 0.000000 0.000000
20
+ 8 448 640 0.941383 0.000035 100 false 10 0.000135 0.000049
21
+ 9 332 640 0.648189 0.000026 100 false 10 0.000029 0.000028
22
+ 10 82 640 0.176836 0.000033 100 false 10 0.000237 0.000040
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.000060
27
+ 0 1 0.000049
28
+ 0 2 0.000047
29
+ 0 3 0.000049
30
+ 0 4 0.000050
31
+ 0 5 0.000050
32
+ 0 6 0.000048
33
+ 0 7 0.000047
34
+ 0 8 0.000046
35
+ 0 9 0.000045
36
+ 1 0 0.000180
37
+ 1 1 0.000157
38
+ 1 2 0.000133
39
+ 1 3 0.000110
40
+ 1 4 0.000088
41
+ 1 5 0.000069
42
+ 1 6 0.000054
43
+ 1 7 0.000048
44
+ 1 8 0.000051
45
+ 1 9 0.000062
46
+ 2 0 0.000382
47
+ 2 1 0.000294
48
+ 2 2 0.000238
49
+ 2 3 0.000211
50
+ 2 4 0.000204
51
+ 2 5 0.000209
52
+ 2 6 0.000216
53
+ 2 7 0.000218
54
+ 2 8 0.000214
55
+ 2 9 0.000206
56
+ 3 0 0.000120
57
+ 3 1 0.000110
58
+ 3 2 0.000102
59
+ 3 3 0.000095
60
+ 3 4 0.000088
61
+ 3 5 0.000083
62
+ 3 6 0.000078
63
+ 3 7 0.000074
64
+ 3 8 0.000071
65
+ 3 9 0.000068
66
+ 4 0 0.000059
67
+ 4 1 0.000030
68
+ 4 2 0.000040
69
+ 4 3 0.000041
70
+ 4 4 0.000032
71
+ 4 5 0.000025
72
+ 4 6 0.000025
73
+ 4 7 0.000028
74
+ 4 8 0.000028
75
+ 4 9 0.000025
76
+ 5 0 0.000029
77
+ 5 1 0.000028
78
+ 5 2 0.000028
79
+ 5 3 0.000027
80
+ 5 4 0.000027
81
+ 5 5 0.000026
82
+ 5 6 0.000026
83
+ 5 7 0.000026
84
+ 5 8 0.000026
85
+ 5 9 0.000026
86
+ 6 0 0.000245
87
+ 6 1 0.000141
88
+ 6 2 0.000101
89
+ 6 3 0.000112
90
+ 6 4 0.000127
91
+ 6 5 0.000125
92
+ 6 6 0.000108
93
+ 6 7 0.000088
94
+ 6 8 0.000074
95
+ 6 9 0.000070
96
+ 7 0 0.000000
97
+ 7 1 0.000000
98
+ 7 2 0.000000
99
+ 7 3 0.000000
100
+ 7 4 0.000000
101
+ 7 5 0.000000
102
+ 7 6 0.000000
103
+ 7 7 0.000000
104
+ 7 8 0.000000
105
+ 7 9 0.000000
106
+ 8 0 0.000135
107
+ 8 1 0.000101
108
+ 8 2 0.000075
109
+ 8 3 0.000059
110
+ 8 4 0.000049
111
+ 8 5 0.000045
112
+ 8 6 0.000044
113
+ 8 7 0.000045
114
+ 8 8 0.000047
115
+ 8 9 0.000049
116
+ 9 0 0.000029
117
+ 9 1 0.000029
118
+ 9 2 0.000029
119
+ 9 3 0.000029
120
+ 9 4 0.000029
121
+ 9 5 0.000028
122
+ 9 6 0.000028
123
+ 9 7 0.000028
124
+ 9 8 0.000028
125
+ 9 9 0.000028
126
+ 10 0 0.000237
127
+ 10 1 0.000186
128
+ 10 2 0.000141
129
+ 10 3 0.000104
130
+ 10 4 0.000076
131
+ 10 5 0.000056
132
+ 10 6 0.000045
133
+ 10 7 0.000039
134
+ 10 8 0.000039
135
+ 10 9 0.000040
xenium_skin_mixed/sample15/log/Birc3.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Birc3
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 611 0.939218 0.000177 100 false 10 0.000317 0.000238
13
+ 1 680 611 0.533772 0.000046 100 false 10 0.000112 0.000070
14
+ 2 5552 611 0.405884 0.000049 100 false 10 0.000068 0.000055
15
+ 3 3231 611 0.530873 0.000081 100 false 10 0.000184 0.000107
16
+ 4 87 611 0.234496 0.000015 100 false 10 0.000485 0.000074
17
+ 5 96 611 0.874632 0.000066 100 false 10 0.000155 0.000102
18
+ 6 1210 611 0.538800 0.000135 100 false 10 0.000160 0.000135
19
+ 7 3 611 0.000000 0.000000 13 true 10 0.000097 0.000019
20
+ 8 448 611 0.764597 0.000034 100 false 10 0.000035 0.000034
21
+ 9 332 611 0.551810 0.000038 100 false 10 0.000101 0.000059
22
+ 10 82 611 0.357673 0.000087 100 false 10 0.012141 0.000543
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.000317
27
+ 0 1 0.000451
28
+ 0 2 0.000288
29
+ 0 3 0.000263
30
+ 0 4 0.000322
31
+ 0 5 0.000282
32
+ 0 6 0.000220
33
+ 0 7 0.000221
34
+ 0 8 0.000248
35
+ 0 9 0.000238
36
+ 1 0 0.000112
37
+ 1 1 0.000105
38
+ 1 2 0.000099
39
+ 1 3 0.000093
40
+ 1 4 0.000088
41
+ 1 5 0.000083
42
+ 1 6 0.000079
43
+ 1 7 0.000076
44
+ 1 8 0.000073
45
+ 1 9 0.000070
46
+ 2 0 0.000068
47
+ 2 1 0.000061
48
+ 2 2 0.000057
49
+ 2 3 0.000054
50
+ 2 4 0.000054
51
+ 2 5 0.000054
52
+ 2 6 0.000054
53
+ 2 7 0.000055
54
+ 2 8 0.000055
55
+ 2 9 0.000055
56
+ 3 0 0.000184
57
+ 3 1 0.000170
58
+ 3 2 0.000158
59
+ 3 3 0.000147
60
+ 3 4 0.000137
61
+ 3 5 0.000129
62
+ 3 6 0.000122
63
+ 3 7 0.000116
64
+ 3 8 0.000111
65
+ 3 9 0.000107
66
+ 4 0 0.000485
67
+ 4 1 0.000247
68
+ 4 2 0.000085
69
+ 4 3 0.000024
70
+ 4 4 0.000048
71
+ 4 5 0.000100
72
+ 4 6 0.000132
73
+ 4 7 0.000132
74
+ 4 8 0.000108
75
+ 4 9 0.000074
76
+ 5 0 0.000155
77
+ 5 1 0.000126
78
+ 5 2 0.000123
79
+ 5 3 0.000126
80
+ 5 4 0.000125
81
+ 5 5 0.000120
82
+ 5 6 0.000113
83
+ 5 7 0.000107
84
+ 5 8 0.000104
85
+ 5 9 0.000102
86
+ 6 0 0.000160
87
+ 6 1 0.000155
88
+ 6 2 0.000151
89
+ 6 3 0.000148
90
+ 6 4 0.000145
91
+ 6 5 0.000142
92
+ 6 6 0.000140
93
+ 6 7 0.000138
94
+ 6 8 0.000136
95
+ 6 9 0.000135
96
+ 7 0 0.000097
97
+ 7 1 0.000076
98
+ 7 2 0.000058
99
+ 7 3 0.000042
100
+ 7 4 0.000030
101
+ 7 5 0.000022
102
+ 7 6 0.000017
103
+ 7 7 0.000016
104
+ 7 8 0.000017
105
+ 7 9 0.000019
106
+ 8 0 0.000035
107
+ 8 1 0.000035
108
+ 8 2 0.000035
109
+ 8 3 0.000034
110
+ 8 4 0.000034
111
+ 8 5 0.000034
112
+ 8 6 0.000034
113
+ 8 7 0.000034
114
+ 8 8 0.000034
115
+ 8 9 0.000034
116
+ 9 0 0.000101
117
+ 9 1 0.000096
118
+ 9 2 0.000091
119
+ 9 3 0.000086
120
+ 9 4 0.000081
121
+ 9 5 0.000077
122
+ 9 6 0.000072
123
+ 9 7 0.000068
124
+ 9 8 0.000064
125
+ 9 9 0.000059
126
+ 10 0 0.012141
127
+ 10 1 0.010159
128
+ 10 2 0.008086
129
+ 10 3 0.006026
130
+ 10 4 0.004138
131
+ 10 5 0.002586
132
+ 10 6 0.001482
133
+ 10 7 0.000831
134
+ 10 8 0.000554
135
+ 10 9 0.000543
xenium_skin_mixed/sample15/log/Bmp1.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Bmp1
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 629 0.959988 0.000141 100 false 10 0.000613 0.000377
13
+ 1 680 629 0.767921 0.000885 100 false 10 0.015576 0.004145
14
+ 2 5552 629 0.809521 0.000474 100 false 10 0.000823 0.000527
15
+ 3 3231 629 0.909769 0.003950 100 false 10 0.008605 0.005234
16
+ 4 87 629 0.411226 0.000023 100 false 10 0.000206 0.000031
17
+ 5 96 629 0.958138 0.000295 100 false 10 0.001204 0.000575
18
+ 6 1210 629 0.770406 0.001369 100 false 10 0.002723 0.001408
19
+ 7 3 629 0.000000 0.000000 100 false 10 0.000047 0.000011
20
+ 8 448 629 0.932007 0.000880 100 false 10 0.008920 0.003461
21
+ 9 332 629 0.964368 0.002255 100 false 10 0.009198 0.003024
22
+ 10 82 629 0.939932 0.000078 100 false 10 0.018112 0.001383
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.000613
27
+ 0 1 0.000822
28
+ 0 2 0.000498
29
+ 0 3 0.000517
30
+ 0 4 0.000559
31
+ 0 5 0.000460
32
+ 0 6 0.000360
33
+ 0 7 0.000357
34
+ 0 8 0.000396
35
+ 0 9 0.000377
36
+ 1 0 0.015576
37
+ 1 1 0.010228
38
+ 1 2 0.005813
39
+ 1 3 0.002908
40
+ 1 4 0.001778
41
+ 1 5 0.002029
42
+ 1 6 0.002878
43
+ 1 7 0.003678
44
+ 1 8 0.004118
45
+ 1 9 0.004145
46
+ 2 0 0.000823
47
+ 2 1 0.000676
48
+ 2 2 0.000609
49
+ 2 3 0.000584
50
+ 2 4 0.000569
51
+ 2 5 0.000554
52
+ 2 6 0.000538
53
+ 2 7 0.000528
54
+ 2 8 0.000524
55
+ 2 9 0.000527
56
+ 3 0 0.008605
57
+ 3 1 0.006973
58
+ 3 2 0.005925
59
+ 3 3 0.005400
60
+ 3 4 0.005254
61
+ 3 5 0.005301
62
+ 3 6 0.005382
63
+ 3 7 0.005411
64
+ 3 8 0.005358
65
+ 3 9 0.005234
66
+ 4 0 0.000206
67
+ 4 1 0.000170
68
+ 4 2 0.000138
69
+ 4 3 0.000111
70
+ 4 4 0.000089
71
+ 4 5 0.000071
72
+ 4 6 0.000056
73
+ 4 7 0.000045
74
+ 4 8 0.000036
75
+ 4 9 0.000031
76
+ 5 0 0.001204
77
+ 5 1 0.000981
78
+ 5 2 0.000829
79
+ 5 3 0.000736
80
+ 5 4 0.000683
81
+ 5 5 0.000656
82
+ 5 6 0.000640
83
+ 5 7 0.000623
84
+ 5 8 0.000602
85
+ 5 9 0.000575
86
+ 6 0 0.002723
87
+ 6 1 0.001901
88
+ 6 2 0.001511
89
+ 6 3 0.001464
90
+ 6 4 0.001574
91
+ 6 5 0.001654
92
+ 6 6 0.001641
93
+ 6 7 0.001563
94
+ 6 8 0.001472
95
+ 6 9 0.001408
96
+ 7 0 0.000047
97
+ 7 1 0.000028
98
+ 7 2 0.000015
99
+ 7 3 0.000009
100
+ 7 4 0.000009
101
+ 7 5 0.000012
102
+ 7 6 0.000014
103
+ 7 7 0.000015
104
+ 7 8 0.000013
105
+ 7 9 0.000011
106
+ 8 0 0.008920
107
+ 8 1 0.005636
108
+ 8 2 0.004346
109
+ 8 3 0.004299
110
+ 8 4 0.004492
111
+ 8 5 0.004471
112
+ 8 6 0.004247
113
+ 8 7 0.003952
114
+ 8 8 0.003681
115
+ 8 9 0.003461
116
+ 9 0 0.009198
117
+ 9 1 0.007360
118
+ 9 2 0.005750
119
+ 9 3 0.004738
120
+ 9 4 0.004660
121
+ 9 5 0.004896
122
+ 9 6 0.004655
123
+ 9 7 0.004035
124
+ 9 8 0.003405
125
+ 9 9 0.003024
126
+ 10 0 0.018112
127
+ 10 1 0.014488
128
+ 10 2 0.011098
129
+ 10 3 0.008009
130
+ 10 4 0.005301
131
+ 10 5 0.003098
132
+ 10 6 0.001559
133
+ 10 7 0.000814
134
+ 10 8 0.000840
135
+ 10 9 0.001383
xenium_skin_mixed/sample15/log/Bmpr2.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Bmpr2
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 630 0.560994 0.000110 100 false 10 0.000911 0.000177
13
+ 1 680 630 0.661053 0.001062 100 false 10 0.004986 0.002130
14
+ 2 5552 630 0.846459 0.000740 100 false 10 0.002048 0.000956
15
+ 3 3231 630 0.880704 0.000296 100 false 10 0.000466 0.000331
16
+ 4 87 630 0.437511 0.000076 100 false 10 0.015527 0.000393
17
+ 5 96 630 0.974128 0.000372 100 false 10 0.004512 0.001097
18
+ 6 1210 630 0.333767 0.000261 100 false 10 0.001877 0.000420
19
+ 7 3 630 0.189714 0.000010 100 false 10 0.000112 0.000019
20
+ 8 448 630 0.867938 0.000302 100 false 10 0.004356 0.000794
21
+ 9 332 630 0.884672 0.000299 100 false 10 0.001169 0.000406
22
+ 10 82 630 0.657611 0.000036 100 false 10 0.005726 0.003091
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.000911
27
+ 0 1 0.000421
28
+ 0 2 0.000186
29
+ 0 3 0.000170
30
+ 0 4 0.000259
31
+ 0 5 0.000332
32
+ 0 6 0.000344
33
+ 0 7 0.000303
34
+ 0 8 0.000238
35
+ 0 9 0.000177
36
+ 1 0 0.004986
37
+ 1 1 0.003084
38
+ 1 2 0.002092
39
+ 1 3 0.001802
40
+ 1 4 0.001896
41
+ 1 5 0.002097
42
+ 1 6 0.002248
43
+ 1 7 0.002299
44
+ 1 8 0.002250
45
+ 1 9 0.002130
46
+ 2 0 0.002048
47
+ 2 1 0.001391
48
+ 2 2 0.001023
49
+ 2 3 0.000927
50
+ 2 4 0.001017
51
+ 2 5 0.001142
52
+ 2 6 0.001189
53
+ 2 7 0.001146
54
+ 2 8 0.001053
55
+ 2 9 0.000956
56
+ 3 0 0.000466
57
+ 3 1 0.000395
58
+ 3 2 0.000359
59
+ 3 3 0.000352
60
+ 3 4 0.000359
61
+ 3 5 0.000364
62
+ 3 6 0.000362
63
+ 3 7 0.000353
64
+ 3 8 0.000342
65
+ 3 9 0.000331
66
+ 4 0 0.015527
67
+ 4 1 0.012924
68
+ 4 2 0.010221
69
+ 4 3 0.007528
70
+ 4 4 0.005020
71
+ 4 5 0.002894
72
+ 4 6 0.001341
73
+ 4 7 0.000470
74
+ 4 8 0.000218
75
+ 4 9 0.000393
76
+ 5 0 0.004512
77
+ 5 1 0.003425
78
+ 5 2 0.002491
79
+ 5 3 0.001748
80
+ 5 4 0.001236
81
+ 5 5 0.000976
82
+ 5 6 0.000921
83
+ 5 7 0.000973
84
+ 5 8 0.001050
85
+ 5 9 0.001097
86
+ 6 0 0.001877
87
+ 6 1 0.001590
88
+ 6 2 0.001326
89
+ 6 3 0.001086
90
+ 6 4 0.000877
91
+ 6 5 0.000702
92
+ 6 6 0.000566
93
+ 6 7 0.000474
94
+ 6 8 0.000427
95
+ 6 9 0.000420
96
+ 7 0 0.000112
97
+ 7 1 0.000097
98
+ 7 2 0.000083
99
+ 7 3 0.000069
100
+ 7 4 0.000058
101
+ 7 5 0.000049
102
+ 7 6 0.000039
103
+ 7 7 0.000031
104
+ 7 8 0.000024
105
+ 7 9 0.000019
106
+ 8 0 0.004356
107
+ 8 1 0.003389
108
+ 8 2 0.002467
109
+ 8 3 0.001673
110
+ 8 4 0.001123
111
+ 8 5 0.000871
112
+ 8 6 0.000817
113
+ 8 7 0.000828
114
+ 8 8 0.000830
115
+ 8 9 0.000794
116
+ 9 0 0.001169
117
+ 9 1 0.000959
118
+ 9 2 0.000787
119
+ 9 3 0.000651
120
+ 9 4 0.000547
121
+ 9 5 0.000473
122
+ 9 6 0.000425
123
+ 9 7 0.000401
124
+ 9 8 0.000396
125
+ 9 9 0.000406
126
+ 10 0 0.005726
127
+ 10 1 0.005403
128
+ 10 2 0.005088
129
+ 10 3 0.004780
130
+ 10 4 0.004480
131
+ 10 5 0.004187
132
+ 10 6 0.003903
133
+ 10 7 0.003626
134
+ 10 8 0.003355
135
+ 10 9 0.003091
xenium_skin_mixed/sample15/log/Bnc2.log ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format spacetravlr_training_log v1
2
+ gene Bnc2
3
+ seed_only false
4
+ per_cell_cnn_export true
5
+ cnn_epochs_config 10
6
+ learning_rate 0.0002
7
+ lasso_n_iter_max 100
8
+ lasso_tol 0.0001
9
+
10
+ # summary: cluster_id, n_cells, n_modulators, lasso_r2, lasso_train_mse, lasso_fista_iters, lasso_converged, cnn_epochs_ran, cnn_mse_first, cnn_mse_last
11
+ cluster_id n_cells n_modulators lasso_r2 lasso_train_mse lasso_fista_iters lasso_converged cnn_epochs_ran cnn_mse_first cnn_mse_last
12
+ 0 219 650 0.796169 0.000009 100 false 10 0.000014 0.000014
13
+ 1 680 650 0.690343 0.000012 100 false 10 0.000103 0.000023
14
+ 2 5552 650 0.952614 0.000115 100 false 10 0.001123 0.000387
15
+ 3 3231 650 0.750449 0.000071 100 false 10 0.000116 0.000073
16
+ 4 87 650 0.536292 0.000003 100 false 10 0.000053 0.000022
17
+ 5 96 650 0.971584 0.000009 100 false 10 0.000019 0.000015
18
+ 6 1210 650 0.367386 0.000017 100 false 10 0.000017 0.000017
19
+ 7 3 650 0.000000 0.000000 1 true 10 0.000000 0.000000
20
+ 8 448 650 0.892972 0.000039 100 false 10 0.000259 0.000063
21
+ 9 332 650 0.984129 0.000195 100 false 10 0.001745 0.000490
22
+ 10 82 650 0.741813 0.000000 100 false 10 0.000046 0.000002
23
+
24
+ # cnn_mse_by_epoch: cluster_id, epoch, train_mse
25
+ cluster_id epoch train_mse
26
+ 0 0 0.000014
27
+ 0 1 0.000014
28
+ 0 2 0.000014
29
+ 0 3 0.000014
30
+ 0 4 0.000014
31
+ 0 5 0.000014
32
+ 0 6 0.000014
33
+ 0 7 0.000014
34
+ 0 8 0.000014
35
+ 0 9 0.000014
36
+ 1 0 0.000103
37
+ 1 1 0.000076
38
+ 1 2 0.000053
39
+ 1 3 0.000035
40
+ 1 4 0.000023
41
+ 1 5 0.000017
42
+ 1 6 0.000016
43
+ 1 7 0.000017
44
+ 1 8 0.000020
45
+ 1 9 0.000023
46
+ 2 0 0.001123
47
+ 2 1 0.000870
48
+ 2 2 0.000668
49
+ 2 3 0.000520
50
+ 2 4 0.000423
51
+ 2 5 0.000371
52
+ 2 6 0.000353
53
+ 2 7 0.000359
54
+ 2 8 0.000375
55
+ 2 9 0.000387
56
+ 3 0 0.000116
57
+ 3 1 0.000105
58
+ 3 2 0.000096
59
+ 3 3 0.000088
60
+ 3 4 0.000082
61
+ 3 5 0.000078
62
+ 3 6 0.000075
63
+ 3 7 0.000074
64
+ 3 8 0.000073
65
+ 3 9 0.000073
66
+ 4 0 0.000053
67
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