TypeError: data type 'float128' not understood

[daliycn]

%%time adata=ov.pp.qc(adata, tresh={'mito_perc': 0.2, 'nUMIs': 500, 'detected_genes': 250}, doublets_method='sccomposite', batch_key=None)

TypeError Traceback (most recent call last) File :1

File d:\anaconda\envs\omicverse\lib\site-packages\omicverse\pp_qc.py:184, in qc(adata, kwargs) 182 else: 183 print('CPU mode activated') --> 184 return qc_cpu(adata,kwargs)

File d:\anaconda\envs\omicverse\lib\site-packages\omicverse\pp_qc.py:270, in qc_cpu(adata, mode, min_cells, min_genes, nmads, max_cells_ratio, max_genes_ratio, batch_key, doublets, doublets_method, path_viz, tresh, mt_startswith, mt_genes) 268 if batch_key is None: 269 from ._sccomposite import composite_rna --> 270 multiplet_classification, consistency = composite_rna(adata) 271 adata.obs['sccomposite_doublet']=multiplet_classification 272 adata.obs['sccomposite_consistency']=consistency

File d:\anaconda\envs\omicverse\lib\site-packages\omicverse\pp_sccomposite.py:309, in composite_rna(adata, multiomics, N, lr, p, stable_criterion, stable_number, tolerance) 307 theta,alpha,beta,decay, loss,p = MLE_rna(stable, N=N, p=p, lr=lr, tolerance=tolerance) 308 rna_fit = rna_fit_goodness(stable, alpha, beta, theta, decay, k=N) --> 309 prob_singlet = prob_k0_rna(stable, theta, alpha, beta, decay, 0, k=N) 310 prob_doublet = 1-prob_singlet 311 doublet_classification = np.where(prob_doublet > 0.5, 1, 0)

File d:\anaconda\envs\omicverse\lib\site-packages\omicverse\pp_sccomposite.py:185, in prob_k0_rna(data, theta, alpha, beta, decay, k0, k) 183 logsumexp_ks = special.logsumexp(one_ks, axis = 1) ... --> 185 log_prob = log_prob.astype('float128') 186 prob = np.exp(log_prob, dtype=np.float128) 189 return prob

TypeError: data type 'float128' not understood

[StickTaTa]

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