errors when calling identify_spatial_genes #3
Description
While using scGCO, encountered the following error
code is running in Python 3.9
gmmDict=scGCO.gmm_model(data_norm)
result_df= identify_spatial_genes(locs, data_norm, cellGraph ,gmmDict)
Traceback :
---------------------------------------------------------------------------
RemoteTraceback Traceback (most recent call last)
RemoteTraceback:
"""
Traceback (most recent call last):
File "/share/anaconda3/envs/SpaBench/lib/python3.9/multiprocessing/pool.py", line 125, in worker
result = (True, func(*args, **kwds))
File "/share/anaconda3/envs/SpaBench/lib/python3.9/multiprocessing/pool.py", line 48, in mapstar
return list(map(*args))
File "/share/anaconda3/envs/SpaBench/lib/python3.9/site-packages/parmap/parmap.py", line 105, in _func_star_many
return func_items_args[0](*list(func_items_args[1]) + func_items_args[2],
File "/share/anaconda3/envs/SpaBench/lib/python3.9/site-packages/scGCO/Graph_cut.py", line 640, in compute_spatial_genomewise_optimize
newLabels, thresholds,label_pred = cut_graph_general_otsu(cellGraph, exp, unary_scale_factor,
File "/share/anaconda3/envs/SpaBench/lib/python3.9/site-packages/scGCO/Graph_cut.py", line 1348, in cut_graph_general_otsu
pair_size = thresholds.shape[0] + 1
IndexError: tuple index out of range
"""
The above exception was the direct cause of the following exception:
IndexError Traceback (most recent call last)
Cell In [14], line 3
1 import scGCO
2 gmmDict=scGCO.gmm_model(data_norm)
----> 3 result_df= identify_spatial_genes(locs, data_norm, cellGraph ,gmmDict)
File /share/anaconda3/envs/SpaBench/lib/python3.9/site-packages/scGCO/Graph_cut.py:729, in identify_spatial_genes(locs, data_norm, cellGraph, gmmDict, smooth_factor, unary_scale_factor, label_cost, algorithm, ncores)
716 ttt = np.array_split(data_norm,num_cores,axis=1)
717 tuples = [(l, d, c, g,ww,nn, s, u, b, a) for l, d, c, g,ww,nn, s, u, b, a in zip(
718 repeat(locs, num_cores),
719 ttt,
(...)
726 repeat(label_cost, num_cores),
727 repeat(algorithm, num_cores))]
--> 729 results = parmap.starmap(compute_spatial_genomewise_optimize, tuples,
730 pm_processes=num_cores, pm_pbar=True)
732 # pool.close()
733 # p_values, genes, diff_p_values, exp_diff, smooth_factors, pred_labels, model_results
734 nnn = [results[i][0] for i in np.arange(len(results))]
File /share/anaconda3/envs/SpaBench/lib/python3.9/site-packages/parmap/parmap.py:317, in starmap(function, iterables, *args, **kwargs)
299 def starmap(function, iterables, *args, **kwargs):
300 """ Equivalent to:
301 >>> return ([function(x1,x2,x3,..., args[0], args[1],...) for
302 >>> (x1,x2,x3...) in iterable])
(...)
315 :type pm_pbar: bool or dict
316 """
--> 317 return _map_or_starmap(function, iterables, args, kwargs, "starmap")
File /share/anaconda3/envs/SpaBench/lib/python3.9/site-packages/parmap/parmap.py:273, in _map_or_starmap(function, iterable, args, kwargs, map_or_starmap)
271 _do_pbar(result, num_tasks, chunksize, tqdm_options=tqdm_options)
272 finally:
--> 273 output = result.get()
274 if close_pool:
275 pool.join()
File /share/anaconda3/envs/SpaBench/lib/python3.9/multiprocessing/pool.py:771, in ApplyResult.get(self, timeout)
769 return self._value
770 else:
--> 771 raise self._value
IndexError: tuple index out of range
Other warnings when running preprocess steps
/share/anaconda3/envs/SpaBench/lib/python3.9/site-packages/tqdm/auto.py:22: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html
from .autonotebook import tqdm as notebook_tqdm
/share/anaconda3/envs/SpaBench/lib/python3.9/site-packages/pysal/lib/weights/util.py:19: UserWarning: geopandas not available. Some functionality will be disabled.
warn('geopandas not available. Some functionality will be disabled.')
/share/anaconda3/envs/SpaBench/lib/python3.9/site-packages/pysal/model/spvcm/abstracts.py:10: UserWarning: The `dill` module is required to use the sqlite backend fully.
from .sqlite import head_to_sql, start_sql
2022-10-23 09:05:32.689209: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: SSE4.1 SSE4.2 AVX AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
/share/anaconda3/envs/SpaBench/lib/python3.9/site-packages/scGCO/Preprocessing.py:170: FutureWarning: Support for multi-dimensional indexing (e.g. `obj[:, None]`) is deprecated and will be removed in a future version. Convert to a numpy array before indexing instead.
data = pd.DataFrame(data.values/normalizing_factor[:,np.newaxis], columns=data.columns, index=data.index)
And another error is multi-threading doesn't work on my linux server, as mentioned in #2 .