AssertionError in prune2df #85
Description
Good afternoon!
Unfortunately, I stacked with the following problem while running prune2df function:
---------------------------------------------------------------------------
AssertionError Traceback (most recent call last)
<ipython-input-16-bcad9b1a0fd3> in <module>
----> 1 df = prune2df(dbs, modules, MOTIF_ANNOTATIONS_FNAME)
~/miniconda3/lib/python3.7/site-packages/pyscenic/prune.py in prune2df(rnkdbs, modules, motif_annotations_fname, rank_threshold, auc_threshold, nes_threshold, motif_similarity_fdr, orthologuous_identity_threshold, weighted_recovery, client_or_address, num_workers, module_chunksize, filter_for_annotation)
349 return _distributed_calc(rnkdbs, modules, motif_annotations_fname, transformation_func, aggregation_func,
350 motif_similarity_fdr, orthologuous_identity_threshold, client_or_address,
--> 351 num_workers, module_chunksize)
352
353
~/miniconda3/lib/python3.7/site-packages/pyscenic/prune.py in _distributed_calc(rnkdbs, modules, motif_annotations_fname, transform_func, aggregate_func, motif_similarity_fdr, orthologuous_identity_threshold, client_or_address, num_workers, module_chunksize)
298 if client_or_address == "dask_multiprocessing":
299 # ... via multiprocessing.
--> 300 return create_graph().compute(scheduler='processes', num_workers=num_workers if num_workers else cpu_count())
301 else:
302 # ... via dask.distributed framework.
~/miniconda3/lib/python3.7/site-packages/dask/base.py in compute(self, **kwargs)
154 dask.base.compute
155 """
--> 156 (result,) = compute(self, traverse=False, **kwargs)
157 return result
158
~/miniconda3/lib/python3.7/site-packages/dask/base.py in compute(*args, **kwargs)
395 keys = [x.__dask_keys__() for x in collections]
396 postcomputes = [x.__dask_postcompute__() for x in collections]
--> 397 results = schedule(dsk, keys, **kwargs)
398 return repack([f(r, *a) for r, (f, a) in zip(results, postcomputes)])
399
~/miniconda3/lib/python3.7/site-packages/dask/multiprocessing.py in get(dsk, keys, num_workers, func_loads, func_dumps, optimize_graph, **kwargs)
190 get_id=_process_get_id, dumps=dumps, loads=loads,
191 pack_exception=pack_exception,
--> 192 raise_exception=reraise, **kwargs)
193 finally:
194 if cleanup:
~/miniconda3/lib/python3.7/site-packages/dask/local.py in get_async(apply_async, num_workers, dsk, result, cache, get_id, rerun_exceptions_locally, pack_exception, raise_exception, callbacks, dumps, loads, **kwargs)
499 _execute_task(task, data) # Re-execute locally
500 else:
--> 501 raise_exception(exc, tb)
502 res, worker_id = loads(res_info)
503 state['cache'][key] = res
~/miniconda3/lib/python3.7/site-packages/dask/compatibility.py in reraise(exc, tb)
109 def reraise(exc, tb=None):
110 if exc.__traceback__ is not tb:
--> 111 raise exc.with_traceback(tb)
112 raise exc
113
~/miniconda3/lib/python3.7/site-packages/dask/local.py in execute_task()
270 try:
271 task, data = loads(task_info)
--> 272 result = _execute_task(task, data)
273 id = get_id()
274 result = dumps((result, id))
~/miniconda3/lib/python3.7/site-packages/dask/local.py in _execute_task()
250 elif istask(arg):
251 func, args = arg[0], arg[1:]
--> 252 args2 = [_execute_task(a, cache) for a in args]
253 return func(*args2)
254 elif not ishashable(arg):
~/miniconda3/lib/python3.7/site-packages/dask/local.py in <listcomp>()
250 elif istask(arg):
251 func, args = arg[0], arg[1:]
--> 252 args2 = [_execute_task(a, cache) for a in args]
253 return func(*args2)
254 elif not ishashable(arg):
~/miniconda3/lib/python3.7/site-packages/dask/local.py in _execute_task()
251 func, args = arg[0], arg[1:]
252 args2 = [_execute_task(a, cache) for a in args]
--> 253 return func(*args2)
254 elif not ishashable(arg):
255 return arg
~/miniconda3/lib/python3.7/site-packages/pyscenic/transform.py in modules2df()
229 #TODO: Remove this restriction.
230 return pd.concat([module2df(db, module, motif_annotations, weighted_recovery, False, module2features_func)
--> 231 for module in modules])
232
233
~/miniconda3/lib/python3.7/site-packages/pyscenic/transform.py in <listcomp>()
229 #TODO: Remove this restriction.
230 return pd.concat([module2df(db, module, motif_annotations, weighted_recovery, False, module2features_func)
--> 231 for module in modules])
232
233
~/miniconda3/lib/python3.7/site-packages/pyscenic/transform.py in module2df()
183 try:
184 df_annotated_features, rccs, rankings, genes, avg2stdrcc = module2features_func(db, module, motif_annotations,
--> 185 weighted_recovery=weighted_recovery)
186 except MemoryError:
187 LOGGER.error("Unable to process \"{}\" on database \"{}\" because ran out of memory. Stacktrace:".format(module.name, db.name))
~/miniconda3/lib/python3.7/site-packages/pyscenic/transform.py in module2features_auc1st_impl()
127 # Calculate recovery curves, AUC and NES values.
128 # For fast unweighted implementation so weights to None.
--> 129 aucs = calc_aucs(df, db.total_genes, weights, auc_threshold)
130 ness = (aucs - aucs.mean()) / aucs.std()
131
~/miniconda3/lib/python3.7/site-packages/pyscenic/recovery.py in aucs()
282 # for calculationg the maximum AUC.
283 maxauc = float((rank_cutoff+1) * y_max)
--> 284 assert maxauc > 0
285 return auc2d(rankings, weights, rank_cutoff, maxauc)
AssertionError: I tried to remove pySCENIC and install latest version from source (0.9.11) since there were kind of similar issue #9, but for my case it didn't solve the problem.