SinghalDivya
commented
1 year ago Hi,
Thank you for your prompt response.
I did try running mv.velocity_graph(adata_result), still get the same error.
computing velocity graph (using 1/12 cores) 100% 4060/4060 [00:07<00:00, 596.01cells/s]
ValueError Traceback (most recent call last) Cell In[112], line 1 ----> 1 mv.velocity_graph(adata_result)
File /work/gallo_lab/divya/softwares/miniconda3/envs/multi_velo/lib/python3.8/site-packages/multivelo/dynamical_chrom_func.py:3039, in velocity_graph(adata, vkey, xkey, kwargs) 3037 if vkey+'_norm_genes' not in adata.var.columns: 3038 adata.var[vkey+'_norm_genes'] = adata.var[vkey+'_genes'] -> 3039 scv.tl.velocity_graph(adata, vkey=vkey+'_norm', xkey=xkey, kwargs)
File /work/gallo_lab/divya/softwares/miniconda3/envs/multi_velo/lib/python3.8/site-packages/scvelo/tools/velocity_graph.py:363, in velocity_graph(data, vkey, xkey, tkey, basis, n_neighbors, n_recurse_neighbors, random_neighbors_at_max, sqrt_transform, variance_stabilization, gene_subset, compute_uncertainties, approx, mode_neighbors, copy, n_jobs, backend) 359 n_jobs = get_n_jobs(n_jobs=n_jobs) 360 logg.info( 361 f"computing velocity graph (using {n_jobs}/{os.cpu_count()} cores)", r=True 362 ) --> 363 vgraph.compute_cosines(n_jobs=n_jobs, backend=backend) 365 adata.uns[f"{vkey}_graph"] = vgraph.graph 366 adata.uns[f"{vkey}_graph_neg"] = vgraph.graph_neg
File /work/gallo_lab/divya/softwares/miniconda3/envs/multi_velo/lib/python3.8/site-packages/scvelo/tools/velocity_graph.py:175, in VelocityGraph.compute_cosines(self, n_jobs, backend) 172 n_obs = self.X.shape[0] 174 # TODO: Use batches and vectorize calculation of dX in self._calculate_cosines --> 175 res = parallelize( 176 self._compute_cosines, 177 range(self.X.shape[0]), 178 n_jobs=n_jobs, 179 unit="cells", 180 backend=backend, 181 )() 182 uncertainties, vals, rows, cols = map(_flatten, zip(*res)) 184 vals = np.hstack(vals)
File /work/gallo_lab/divya/softwares/miniconda3/envs/multi_velo/lib/python3.8/site-packages/scvelo/core/_parallelize.py:138, in parallelize.
ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 2 dimensions. The detected shape was (1, 4) + inhomogeneous part.
Regards,
Divya
On May 16, 2023, at 9:17 PM, Chen Li @.***> wrote:
mv.velocity_graph(adata_result)
danielee0707
theAeon
Hi, Thank you for creating an interesting tool. I am running into a following error when I ran latent time. Could you please guide me through this error.
computing velocity graph (using 1/12 cores) 100% 4060/4060 [00:07<00:00, 520.87cells/s]
ValueError Traceback (most recent call last) Cell In[113], line 1 ----> 1 mv.latent_time(adata_result)
File /work/gallo_lab/divya/softwares/miniconda3/envs/multi_velo/lib/python3.8/site-packages/multivelo/dynamical_chrom_func.py:3097, in latent_time(adata, vkey, kwargs) 3095 raise ValueError('Normalized velocity matrix is not found. Please multivelo.run velocity_graph function first.') 3096 if vkey+'_norm_graph' not in adata.uns.keys(): -> 3097 velocity_graph(adata, vkey=vkey, kwargs) 3098 scv.tl.latent_time(adata, vkey=vkey+'_norm', **kwargs)
File /work/gallo_lab/divya/softwares/miniconda3/envs/multi_velo/lib/python3.8/site-packages/multivelo/dynamical_chrom_func.py:3039, in velocity_graph(adata, vkey, xkey, kwargs) 3037 if vkey+'_norm_genes' not in adata.var.columns: 3038 adata.var[vkey+'_norm_genes'] = adata.var[vkey+'_genes'] -> 3039 scv.tl.velocity_graph(adata, vkey=vkey+'_norm', xkey=xkey, kwargs)
File /work/gallo_lab/divya/softwares/miniconda3/envs/multi_velo/lib/python3.8/site-packages/scvelo/tools/velocity_graph.py:363, in velocity_graph(data, vkey, xkey, tkey, basis, n_neighbors, n_recurse_neighbors, random_neighbors_at_max, sqrt_transform, variance_stabilization, gene_subset, compute_uncertainties, approx, mode_neighbors, copy, n_jobs, backend) 359 n_jobs = get_n_jobs(n_jobs=n_jobs) 360 logg.info( 361 f"computing velocity graph (using {n_jobs}/{os.cpu_count()} cores)", r=True 362 ) --> 363 vgraph.compute_cosines(n_jobs=n_jobs, backend=backend) 365 adata.uns[f"{vkey}_graph"] = vgraph.graph 366 adata.uns[f"{vkey}_graph_neg"] = vgraph.graph_neg
File /work/gallo_lab/divya/softwares/miniconda3/envs/multi_velo/lib/python3.8/site-packages/scvelo/tools/velocity_graph.py:175, in VelocityGraph.compute_cosines(self, n_jobs, backend) 172 n_obs = self.X.shape[0] 174 # TODO: Use batches and vectorize calculation of dX in self._calculate_cosines --> 175 res = parallelize( 176 self._compute_cosines, 177 range(self.X.shape[0]), 178 n_jobs=n_jobs, 179 unit="cells", 180 backend=backend, 181 )() 182 uncertainties, vals, rows, cols = map(_flatten, zip(*res)) 184 vals = np.hstack(vals)
File /work/gallo_lab/divya/softwares/miniconda3/envs/multi_velo/lib/python3.8/site-packages/scvelo/core/_parallelize.py:138, in parallelize..wrapper(*args, *kwargs)
126 pbar, queue, thread = None, None, None
128 res = Parallel(n_jobs=n_jobs, backend=backend)(
129 delayed(callback)(
130 ((i, cs) if use_ixs else (cs,)),
(...)
135 for i, cs in enumerate(collections)
136 )
--> 138 res = np.array(res) if as_array else res
139 if thread is not None:
140 thread.join()
ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 2 dimensions. The detected shape was (1, 4) + inhomogeneous part.
####### my adata_result looks like the following :
AnnData object with n_obs × n_vars = 4060 × 718 obs: 'n_counts', 'module' var: 'Accession', 'Chromosome', 'End', 'Start', 'Strand', 'fit_alpha_c', 'fit_alpha', 'fit_beta', 'fit_gamma', 'fit_t_sw1', 'fit_t_sw2', 'fit_t_sw3', 'fit_scale_cc', 'fit_rescale_c', 'fit_rescale_u', 'fit_alignment_scaling', 'fit_model', 'fit_direction', 'fit_loss', 'fit_likelihood', 'fit_likelihood_c', 'fit_ssd_c', 'fit_var_c', 'fit_c0', 'fit_u0', 'fit_s0', 'fit_anchor_min_idx', 'fit_anchor_max_idx', 'fit_anchor_velo_min_idx', 'fit_anchor_velo_max_idx', 'velo_s_genes', 'velo_u_genes', 'velo_chrom_genes', 'velo_s_norm_genes' uns: 'module_colors', 'neighbors', 'pca', 'umap', 'velo_chrom_params', 'velo_s_params', 'velo_u_params', 'velo_s_norm_params' obsm: 'X_pca', 'X_umap' varm: 'PCs', 'fit_anchor_c', 'fit_anchor_c_sw', 'fit_anchor_c_velo', 'fit_anchor_s', 'fit_anchor_s_sw', 'fit_anchor_s_velo', 'fit_anchor_u', 'fit_anchor_u_sw', 'fit_anchor_u_velo' layers: 'ATAC', 'Ms', 'Mu', 'ambiguous', 'fit_state', 'fit_t', 'matrix', 'spliced', 'unspliced', 'velo_chrom', 'velo_s', 'velo_u', 'velo_s_norm' obsp: '_ATAC_conn', '_RNA_conn', 'connectivities', 'distances'