segments_selector_congas error

[ViriyaK]

Hello,

I'm trying to follow the tutorial. I used the "multiome_congas_object" provided and segments_selector_congas keeps failing.
Since I'm using your provided example data, I shouldn't have this problem here #33 . I also tried creating the example data from scratch following the object initialization tutorial and the same issue persists. I tried cg = reticulate::import("congas") and it looks like everything loaded correctly.
I have rcongas=0.2.0, congas=0.0.77, R=4.0.3, python=3.7, numpy 1.21.6, torch=1.13.1. I would appreciate any suggestions.

Here is the error message:

filt <- segments_selector_congas(multiome_congas_object)
[1] "segment_selector"
── (R)CONGAS+ hyperparameters auto-config ─────────────────────────────────────────────────────────────────────────────────────────────

── ATAC modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr10:0:39800000 theta_shape = 16.5960379276341, theta_rate = 0.0841842830763062

── RNA modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr10:0:39800000 theta_shape = 19.2665070739235, theta_rate = 0.302134133377605

── (R)CONGAS+ Variational Inference ─────────────────────────────────────────────────────────────────────────────────────────────────

── Fit with k = 1 and lambda = 0.5.
sys:1: UserWarning: The given NumPy array is not writable, and PyTorch does not support non-writable tensors. This means writing to this tensor will result in undefined behavior. You may want to copy the array to protect its data or make it writable before converting it to a tensor. This type of warning will be suppressed for the rest of this program. (Triggered internally at ../torch/csrc/utils/tensor_numpy.cpp:199.)
%!PS-Adobe-3.0

── Fit with k = 2 and lambda = 0.5.

── Fit with k = 3 and lambda = 0.5.
[easypar] 3/3 computations returned errors and will be removed.

── (R)CONGAS+ fits completed in 1s. ──

▣ - [~~~~> ] 9% [ETA 17s] ▶ 00:00:01── (R)CONGAS+ hyperparameters auto-config ─────────────────────────────────────────────────────────────────────────────────────────────

── ATAC modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr10:39800000:133797422 theta_shape = 28.582032985645, theta_rate = 0.0594386646538866

── RNA modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr10:39800000:133797422 theta_shape = 33.4461715488304, theta_rate = 0.279095985648009

── (R)CONGAS+ Variational Inference ─────────────────────────────────────────────────────────────────────────────────────────────────

── Fit with k = 1 and lambda = 0.5.

── Fit with k = 2 and lambda = 0.5.

── Fit with k = 3 and lambda = 0.5.
[easypar] 3/3 computations returned errors and will be removed.

── (R)CONGAS+ fits completed in 405ms. ──

▣ \ [~~~~~~~> ] 14% [ETA 17s] ▶ 00:00:02── (R)CONGAS+ hyperparameters auto-config ─────────────────────────────────────────────────────────────────────────────────────────────

── ATAC modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr13:17700000:114364328 theta_shape = 19.9608938056433, theta_rate = 0.0555713895470692

── RNA modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr13:17700000:114364328 theta_shape = 29.3023824410731, theta_rate = 0.286056789746043

── (R)CONGAS+ Variational Inference ─────────────────────────────────────────────────────────────────────────────────────────────────

── Fit with k = 1 and lambda = 0.5.

── Fit with k = 2 and lambda = 0.5.

── Fit with k = 3 and lambda = 0.5.
[easypar] 3/3 computations returned errors and will be removed.

── (R)CONGAS+ fits completed in 378ms. ──

▣ | [~~~~~~~~~> ] 18% [ETA 17s] ▶ 00:00:03── (R)CONGAS+ hyperparameters auto-config ─────────────────────────────────────────────────────────────────────────────────────────────

── ATAC modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr14:17200000:107043718 theta_shape = 32.5614419641683, theta_rate = 0.0592791874333225

── RNA modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr14:17200000:107043718 theta_shape = 46.6273668935017, theta_rate = 0.306435997460095

── (R)CONGAS+ Variational Inference ─────────────────────────────────────────────────────────────────────────────────────────────────

── Fit with k = 1 and lambda = 0.5.

── Fit with k = 2 and lambda = 0.5.

── Fit with k = 3 and lambda = 0.5.
[easypar] 3/3 computations returned errors and will be removed.

── (R)CONGAS+ fits completed in 398ms. ──

▣ / [~~~~~~~~~~~~> ] 23% [ETA 16s] ▶ 00:00:04── (R)CONGAS+ hyperparameters auto-config ─────────────────────────────────────────────────────────────────────────────────────────────

── ATAC modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr15:19000000:101991189 theta_shape = 24.1861249875677, theta_rate = 0.0490351962800699

── RNA modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr15:19000000:101991189 theta_shape = 39.7649630703425, theta_rate = 0.264126021377491

── (R)CONGAS+ Variational Inference ─────────────────────────────────────────────────────────────────────────────────────────────────

── Fit with k = 1 and lambda = 0.5.

── Fit with k = 2 and lambda = 0.5.

── Fit with k = 3 and lambda = 0.5.
[easypar] 3/3 computations returned errors and will be removed.

── (R)CONGAS+ fits completed in 403ms. ──

▣ - [~~~~~~~~~~~~~~~> ] 27% [ETA 15s] ▶ 00:00:05── (R)CONGAS+ hyperparameters auto-config ─────────────────────────────────────────────────────────────────────────────────────────────

── ATAC modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr16:0:36800000 theta_shape = 17.0430912743007, theta_rate = 0.0502431531953325

── RNA modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr16:0:36800000 theta_shape = 23.5871854403358, theta_rate = 0.292323361055517

── (R)CONGAS+ Variational Inference ─────────────────────────────────────────────────────────────────────────────────────────────────

── Fit with k = 1 and lambda = 0.5.

── Fit with k = 2 and lambda = 0.5.

── Fit with k = 3 and lambda = 0.5.
[easypar] 3/3 computations returned errors and will be removed.

── (R)CONGAS+ fits completed in 371ms. ──

▣ \ [~~~~~~~~~~~~~~~~~> ] 32% [ETA 14s] ▶ 00:00:06── (R)CONGAS+ hyperparameters auto-config ─────────────────────────────────────────────────────────────────────────────────────────────

── ATAC modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr16:36800000:90338345 theta_shape = 19.9737149755649, theta_rate = 0.0622947198276828

── RNA modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr16:36800000:90338345 theta_shape = 24.1920140966164, theta_rate = 0.29300161151334

── (R)CONGAS+ Variational Inference ─────────────────────────────────────────────────────────────────────────────────────────────────

── Fit with k = 1 and lambda = 0.5.

── Fit with k = 2 and lambda = 0.5.

── Fit with k = 3 and lambda = 0.5.
[easypar] 3/3 computations returned errors and will be removed.

── (R)CONGAS+ fits completed in 398ms. ──

▣ | [~~~~~~~~~~~~~~~~~~~~> ] 36% [ETA 13s] ▶ 00:00:07── (R)CONGAS+ hyperparameters auto-config ─────────────────────────────────────────────────────────────────────────────────────────────

── ATAC modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr18:0:18500000 theta_shape = 9.19898572042463, theta_rate = 0.134656196154735

── RNA modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr18:0:18500000 theta_shape = 5.12501035655668, theta_rate = 0.320833337690021

── (R)CONGAS+ Variational Inference ─────────────────────────────────────────────────────────────────────────────────────────────────

── Fit with k = 1 and lambda = 0.5.

── Fit with k = 2 and lambda = 0.5.

── Fit with k = 3 and lambda = 0.5.
[easypar] 3/3 computations returned errors and will be removed.

── (R)CONGAS+ fits completed in 363ms. ──

▣ / [~~~~~~~~~~~~~~~~~~~~~~> ] 41% [ETA 12s] ▶ 00:00:08── (R)CONGAS+ hyperparameters auto-config ─────────────────────────────────────────────────────────────────────────────────────────────

── ATAC modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr18:18500000:80373285 theta_shape = 9.79787953384757, theta_rate = 0.0438621501984607

── RNA modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr18:18500000:80373285 theta_shape = 13.5825852942828, theta_rate = 0.240347578487164

── (R)CONGAS+ Variational Inference ─────────────────────────────────────────────────────────────────────────────────────────────────

── Fit with k = 1 and lambda = 0.5.

── Fit with k = 2 and lambda = 0.5.

── Fit with k = 3 and lambda = 0.5.
[easypar] 3/3 computations returned errors and will be removed.

── (R)CONGAS+ fits completed in 440ms. ──

▣ - [~~~~~~~~~~~~~~~~~~~~~~~~~> ] 45% [ETA 12s] ▶ 00:00:09── (R)CONGAS+ hyperparameters auto-config ─────────────────────────────────────────────────────────────────────────────────────────────

── ATAC modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr20:0:28100000 theta_shape = 12.9891247773717, theta_rate = 0.108091548460782

── RNA modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr20:0:28100000 theta_shape = 9.04539771906856, theta_rate = 0.348686599653812

── (R)CONGAS+ Variational Inference ─────────────────────────────────────────────────────────────────────────────────────────────────

── Fit with k = 1 and lambda = 0.5.

── Fit with k = 2 and lambda = 0.5.

── Fit with k = 3 and lambda = 0.5.
[easypar] 3/3 computations returned errors and will be removed.

── (R)CONGAS+ fits completed in 413ms. ──

▣ \ [~~~~~~~~~~~~~~~~~~~~~~~~~~~> ] 50% [ETA 11s] ▶ 00:00:10── (R)CONGAS+ hyperparameters auto-config ─────────────────────────────────────────────────────────────────────────────────────────────

── ATAC modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr20:28100000:64444167 theta_shape = 16.7495458203469, theta_rate = 0.059895742835331

── RNA modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr20:28100000:64444167 theta_shape = 23.5914247154515, theta_rate = 0.349365010140936

── (R)CONGAS+ Variational Inference ─────────────────────────────────────────────────────────────────────────────────────────────────

── Fit with k = 1 and lambda = 0.5.

── Fit with k = 2 and lambda = 0.5.

── Fit with k = 3 and lambda = 0.5.
[easypar] 3/3 computations returned errors and will be removed.

── (R)CONGAS+ fits completed in 422ms. ──

▣ | [~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~> ] 55% [ETA 10s] ▶ 00:00:11── (R)CONGAS+ hyperparameters auto-config ─────────────────────────────────────────────────────────────────────────────────────────────

── ATAC modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr21:12000000:46709983 theta_shape = 17.4526453771287, theta_rate = 0.09145137682503

── RNA modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr21:12000000:46709983 theta_shape = 15.2965409629744, theta_rate = 0.309333181646816

── (R)CONGAS+ Variational Inference ─────────────────────────────────────────────────────────────────────────────────────────────────

── Fit with k = 1 and lambda = 0.5.

── Fit with k = 2 and lambda = 0.5.

── Fit with k = 3 and lambda = 0.5.
[easypar] 3/3 computations returned errors and will be removed.

── (R)CONGAS+ fits completed in 415ms. ──

▣ / [~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~> ] 59% [ETA 9s] ▶ 00:00:12── (R)CONGAS+ hyperparameters auto-config ─────────────────────────────────────────────────────────────────────────────────────────────

── ATAC modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr3:0:90900000 theta_shape = 30.4862086428994, theta_rate = 0.0659232813205122

── RNA modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr3:0:90900000 theta_shape = 31.4825978140826, theta_rate = 0.24702629331773

── (R)CONGAS+ Variational Inference ─────────────────────────────────────────────────────────────────────────────────────────────────

── Fit with k = 1 and lambda = 0.5.

── Fit with k = 2 and lambda = 0.5.

── Fit with k = 3 and lambda = 0.5.
[easypar] 3/3 computations returned errors and will be removed.

── (R)CONGAS+ fits completed in 380ms. ──

▣ - [~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~> ] 64% [ETA 8s] ▶ 00:00:13── (R)CONGAS+ hyperparameters auto-config ─────────────────────────────────────────────────────────────────────────────────────────────

── ATAC modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr3:90900000:198295559 theta_shape = 9.17167289102108, theta_rate = 0.0155177176789159

── RNA modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr3:90900000:198295559 theta_shape = 14.326975650189, theta_rate = 0.0910771911618621

── (R)CONGAS+ Variational Inference ─────────────────────────────────────────────────────────────────────────────────────────────────

── Fit with k = 1 and lambda = 0.5.

── Fit with k = 2 and lambda = 0.5.

── Fit with k = 3 and lambda = 0.5.
[easypar] 3/3 computations returned errors and will be removed.

── (R)CONGAS+ fits completed in 408ms. ──

▣ \ [~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~> ] 68% [ETA 7s] ▶ 00:00:14── (R)CONGAS+ hyperparameters auto-config ─────────────────────────────────────────────────────────────────────────────────────────────

── ATAC modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr5:0:48800000 theta_shape = 13.8361699983597, theta_rate = 0.117399901296547

── RNA modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr5:0:48800000 theta_shape = 11.1585598232312, theta_rate = 0.377512519837774

── (R)CONGAS+ Variational Inference ─────────────────────────────────────────────────────────────────────────────────────────────────

── Fit with k = 1 and lambda = 0.5.

── Fit with k = 2 and lambda = 0.5.

── Fit with k = 3 and lambda = 0.5.
[easypar] 3/3 computations returned errors and will be removed.

── (R)CONGAS+ fits completed in 374ms. ──

▣ | [~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~> ] 73% [ETA 6s] ▶ 00:00:15── (R)CONGAS+ hyperparameters auto-config ─────────────────────────────────────────────────────────────────────────────────────────────

── ATAC modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr5:48800000:181538259 theta_shape = 36.2259386456759, theta_rate = 0.0587019106997879

── RNA modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr5:48800000:181538259 theta_shape = 55.297803538416, theta_rate = 0.291341685975456

── (R)CONGAS+ Variational Inference ─────────────────────────────────────────────────────────────────────────────────────────────────

── Fit with k = 1 and lambda = 0.5.

── Fit with k = 2 and lambda = 0.5.

── Fit with k = 3 and lambda = 0.5.
[easypar] 3/3 computations returned errors and will be removed.

── (R)CONGAS+ fits completed in 416ms. ──

▣ / [~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~> ] 77% [ETA 5s] ▶ 00:00:16── (R)CONGAS+ hyperparameters auto-config ─────────────────────────────────────────────────────────────────────────────────────────────

── ATAC modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr7:0:60100000 theta_shape = 11.9716723078498, theta_rate = 0.0335830102341236

── RNA modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr7:0:60100000 theta_shape = 13.1313284095014, theta_rate = 0.148145381976511

── (R)CONGAS+ Variational Inference ─────────────────────────────────────────────────────────────────────────────────────────────────

── Fit with k = 1 and lambda = 0.5.

── Fit with k = 2 and lambda = 0.5.

── Fit with k = 3 and lambda = 0.5.
[easypar] 3/3 computations returned errors and will be removed.

── (R)CONGAS+ fits completed in 374ms. ──

▣ - [~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~> ] 82% [ETA 4s] ▶ 00:00:17── (R)CONGAS+ hyperparameters auto-config ─────────────────────────────────────────────────────────────────────────────────────────────

── ATAC modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr7:60100000:159345973 theta_shape = 19.7981159850749, theta_rate = 0.0382327873757624

── RNA modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr7:60100000:159345973 theta_shape = 31.6129710536964, theta_rate = 0.222384539371425

── (R)CONGAS+ Variational Inference ─────────────────────────────────────────────────────────────────────────────────────────────────

── Fit with k = 1 and lambda = 0.5.

── Fit with k = 2 and lambda = 0.5.

── Fit with k = 3 and lambda = 0.5.
[easypar] 3/3 computations returned errors and will be removed.

── (R)CONGAS+ fits completed in 402ms. ──

▣ \ [~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~> ] 86% [ETA 3s] ▶ 00:00:18── (R)CONGAS+ hyperparameters auto-config ─────────────────────────────────────────────────────────────────────────────────────────────

── ATAC modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr8:0:45200000 theta_shape = 14.1072176973478, theta_rate = 0.0781279251668481

── RNA modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr8:0:45200000 theta_shape = 14.9569403672792, theta_rate = 0.329116181747571

── (R)CONGAS+ Variational Inference ─────────────────────────────────────────────────────────────────────────────────────────────────

── Fit with k = 1 and lambda = 0.5.

── Fit with k = 2 and lambda = 0.5.

── Fit with k = 3 and lambda = 0.5.
[easypar] 3/3 computations returned errors and will be removed.

── (R)CONGAS+ fits completed in 399ms. ──

▣ | [~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~> ] 91% [ETA 2s] ▶ 00:00:19── (R)CONGAS+ hyperparameters auto-config ─────────────────────────────────────────────────────────────────────────────────────────────

── ATAC modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr8:45200000:145138636 theta_shape = 27.8974694734093, theta_rate = 0.06936839538262

── RNA modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr8:45200000:145138636 theta_shape = 35.132342423001, theta_rate = 0.330736562667865

── (R)CONGAS+ Variational Inference ─────────────────────────────────────────────────────────────────────────────────────────────────

── Fit with k = 1 and lambda = 0.5.

── Fit with k = 2 and lambda = 0.5.

── Fit with k = 3 and lambda = 0.5.
[easypar] 3/3 computations returned errors and will be removed.

── (R)CONGAS+ fits completed in 373ms. ──

▣ / [~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~> ] 95% [ETA 1s] ▶ 00:00:20── (R)CONGAS+ hyperparameters auto-config ─────────────────────────────────────────────────────────────────────────────────────────────

── ATAC modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr9:0:43000000 theta_shape = 16.6486078181994, theta_rate = 0.102991815277321

── RNA modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr9:0:43000000 theta_shape = 14.6886573893498, theta_rate = 0.323785250033893

── (R)CONGAS+ Variational Inference ─────────────────────────────────────────────────────────────────────────────────────────────────

── Fit with k = 1 and lambda = 0.5.

── Fit with k = 2 and lambda = 0.5.

── Fit with k = 3 and lambda = 0.5.
[easypar] 3/3 computations returned errors and will be removed.

── (R)CONGAS+ fits completed in 394ms. ──

── (R)CONGAS+ hyperparameters auto-config ─────────────────────────────────────────────────────────────────────────────────────────────

── ATAC modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr9:43000000:138394717 theta_shape = 12.6405354431144, theta_rate = 0.022602435565188

── RNA modality ──

→ Negative Binomial likelihood, estimating Gamma shape and rate

── Estimating segment factors
→ 1: chr9:43000000:138394717 theta_shape = 15.3629122806536, theta_rate = 0.124101739386109

── (R)CONGAS+ Variational Inference ─────────────────────────────────────────────────────────────────────────────────────────────────

── Fit with k = 1 and lambda = 0.5.

── Fit with k = 2 and lambda = 0.5.

── Fit with k = 3 and lambda = 0.5.
[easypar] 3/3 computations returned errors and will be removed.

── (R)CONGAS+ fits completed in 367ms. ──

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Error in f():
! Argument 1 must be a data frame or a named atomic vector.
Run rlang::last_trace() to see where the error occurred.

[Militeee]

Hey @lucreziaPatruno I tried to look into it but was not able to replicate the error, it runs just fine on my Mac Mini at home. Can you give it a try and see if you get the error?

[ViriyaK]

@Militeee thank you for looking into this so quickly! I thought it might be a HPC specific issue so I tried running it on my Macbook as well. Mostly the same package versions as above with exception of R=4.1.0, but it still gives me the same error.

[lucreziaPatruno]

Hi @ViriyaK , I also tried on my laptop and everything is working fine.
I am not sure about what might be causing this issue. I recently pushed a small change to the CONGASp python package, can you please try uninstalling it from the r-reticulate conda environment and then reinstalling it manually?
conda activate r-reticulate
pip uninstall congas
pip install git+https://github.com/caravagnalab/CONGASp

BW
Lucrezia

[ViriyaK]

Thanks @lucreziaPatruno. I've tried that and also tried creating a fresh conda environment with just python 3.7.12 and pip install git+https://github.com/caravagnalab/CONGASp and load it with use_condaenv("congas") and the error is still there. Same on both my laptop and HPC.
Although it seems like on HPC, the error says "(Triggered internally at ../torch/csrc/utils/tensor_numpy.cpp:199.)" and on my Macbook Pro is says "(Triggered internally at /Users/runner/work/pytorch/pytorch/pytorch/torch/csrc/utils/tensor_numpy.cpp:205.)". I don't know if this helpful at all but I'm just reporting anything I see.

[caravagn]

@lucreziaPatruno @Militeee how about we release a singulairty image?

[iovlaicu]

Hello! I also tried following the tutorial (with R=4.3.3, RCongas=0.2.0) by both loading the "multiome_congas_object" provided and also recreating it from scratch, and I get the exact same error as @ViriyaK when filt <- segments_selector_congas(multiome_congas_object) fails. I also tried it both on my laptop and HPC (using a singularity image), and the same issue persists.

[Militeee]

Hi, I'll try to see if I can reproduce the issue, in case I don't me and @lucreziaPatruno will try to come up asap with a usable docker image.

[Militeee]

Update on that, I was not able to replicate the error myself, I am working on a docker/singularity image with Rstudio inside.

In the meantime @iovlaicu or @ViriyaK do you mind pasting here the conda environment where you are running congas? I suspect this may be an issue with some versions of torch/pyro