Closed hongruhusanofi closed 9 months ago
I got the same error. These are versions of my models.
mofapy2 = v0.7.0
pandas = 1.5.3
numpy = 1.26.0
When I downgraded mofapy2 to 0.6.7, I got different error message below:
IndexError Traceback (most recent call last)
Cell In[76], line 1
----> 1 mu.tl.mofa(mdata, n_factors=20, gpu_mode=True)
File ~/mambaforge/envs/multiome/lib/python3.9/site-packages/muon/_core/tools.py:642, in mofa(data, groups_label, use_raw, use_layer, use_var, use_obs, likelihoods, n_factors, scale_views, scale_groups, center_groups, ard_weights, ard_factors, spikeslab_weights, spikeslab_factors, n_iterations, convergence_mode, use_float32, gpu_mode, gpu_device, svi_mode, svi_batch_size, svi_learning_rate, svi_forgetting_rate, svi_start_stochastic, smooth_covariate, smooth_warping, smooth_kwargs, save_parameters, save_data, save_metadata, seed, outfile, expectations, save_interrupted, verbose, quiet, copy)
639 if use_var:
640 # Set the weights of features that were not used to zero
641 data.varm["LFs"] = np.zeros(shape=(data.n_vars, w.shape[1]))
--> 642 data.varm["LFs"][data.var[use_var]] = w
643 else:
644 data.varm["LFs"] = w
IndexError: only integers, slices (`:`), ellipsis (`...`), numpy.newaxis (`None`) and integer or boolean arrays are valid indices
mofapy2 : v0.6.7 numpy : v1.22.4 pandas : v1.5.3
I was able to run through the entire Jupyter notebook named getting_started_python.ipynb
, which could be downloaded from the mofapy2 GitHub without any errors. However, the error was triggered by another Jupyter notebook and a sample data file downloaded from the muon-tutorials."
But the Mu data has a new embedding X_mofa
.
And the iteration stopped at 13 with the message 'Converged!'. While I believe this number of iterations is too low, can I still use the X_mofa in mdata for downstream analysis in this situation?
just tried using the data.frame option following the mofapy2, it worked fine so there should be something wrong wit the MOUN mu.tl.mofa
wrapper. @jjuhyunkim maybe we could open another issue under the moun github page
Yes, you are right,
I was able to resolve the error by executing the following line of code before running MOFA to integrate my data
mdata.var['highly_variable']=mdata.var['highly_variable'].to_list()
Thank you for your comments
Hi, I have some issue with training
and
AttributeError: 'BayesNet' object has no attribute 'train_stats'