Estimating centrality...
[Parallel(n_jobs=7)]: Batch computation too fast (0.0495s.) Setting batch_size=8.
[Parallel(n_jobs=7)]: Done 4 tasks | elapsed: 0.1s
[Parallel(n_jobs=7)]: Done 11 tasks | elapsed: 0.1s
[Parallel(n_jobs=7)]: Done 46 tasks | elapsed: 0.5s
[Parallel(n_jobs=7)]: Done 118 tasks | elapsed: 0.9s
[Parallel(n_jobs=7)]: Done 190 tasks | elapsed: 1.3s
[Parallel(n_jobs=7)]: Done 278 tasks | elapsed: 1.7s
[Parallel(n_jobs=7)]: Done 366 tasks | elapsed: 2.2s
[Parallel(n_jobs=7)]: Done 470 tasks | elapsed: 2.9s
[Parallel(n_jobs=7)]: Done 574 tasks | elapsed: 3.6s
[Parallel(n_jobs=7)]: Done 694 tasks | elapsed: 4.2s
[Parallel(n_jobs=7)]: Done 814 tasks | elapsed: 5.0s
[Parallel(n_jobs=7)]: Done 950 tasks | elapsed: 5.7s
[Parallel(n_jobs=7)]: Done 1086 tasks | elapsed: 6.5s
[Parallel(n_jobs=7)]: Done 1238 tasks | elapsed: 7.4s
[Parallel(n_jobs=7)]: Done 1390 tasks | elapsed: 8.2s
[Parallel(n_jobs=7)]: Done 1558 tasks | elapsed: 9.1s
[Parallel(n_jobs=7)]: Done 1726 tasks | elapsed: 10.2s
[Parallel(n_jobs=7)]: Done 1910 tasks | elapsed: 11.1s
[Parallel(n_jobs=7)]: Done 2094 tasks | elapsed: 12.2s
[Parallel(n_jobs=7)]: Done 2294 tasks | elapsed: 13.3s
[Parallel(n_jobs=7)]: Done 2494 tasks | elapsed: 14.5s
[Parallel(n_jobs=7)]: Done 2710 tasks | elapsed: 15.6s
multiprocessing.pool.RemoteTraceback:
"""
Traceback (most recent call last):
File "/usr/local/lib/python3.5/dist-packages/joblib/_parallel_backends.py", line 350, in __call__
return self.func(*args, **kwargs)
File "/usr/local/lib/python3.5/dist-packages/joblib/parallel.py", line 131, in __call__
return [func(*args, **kwargs) for func, args, kwargs in self.items]
File "/usr/local/lib/python3.5/dist-packages/joblib/parallel.py", line 131, in <listcomp>
return [func(*args, **kwargs) for func, args, kwargs in self.items]
File "/usr/local/lib/python3.5/dist-packages/gpseqc/centrality.py", line 243, in bin_estimate_single
orow[m] = est_2p(st, calc_p, lambda x, y: x / y)
File "/usr/local/lib/python3.5/dist-packages/gpseqc/centrality.py", line 123, in est_2p
a = f1(st, 0)
File "/usr/local/lib/python3.5/dist-packages/gpseqc/centrality.py", line 31, in calc_p
row = st.iloc[ci, :]
File "/usr/local/lib/python3.5/dist-packages/pandas/core/indexing.py", line 1367, in __getitem__
return self._getitem_tuple(key)
File "/usr/local/lib/python3.5/dist-packages/pandas/core/indexing.py", line 1737, in _getitem_tuple
self._has_valid_tuple(tup)
File "/usr/local/lib/python3.5/dist-packages/pandas/core/indexing.py", line 203, in _has_valid_tuple
raise IndexingError('Too many indexers')
pandas.core.indexing.IndexingError: Too many indexers
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/usr/lib/python3.5/multiprocessing/pool.py", line 119, in worker
result = (True, func(*args, **kwds))
File "/usr/local/lib/python3.5/dist-packages/joblib/_parallel_backends.py", line 359, in __call__
raise TransportableException(text, e_type)
joblib.my_exceptions.TransportableException: TransportableException
___________________________________________________________________________
IndexingError Tue Apr 24 13:48:52 2018
PID: 29536 Python 3.5.2: /usr/bin/python3
...........................................................................
/usr/local/lib/python3.5/dist-packages/joblib/parallel.py in __call__(self=<joblib.parallel.BatchedCalls object>)
126 def __init__(self, iterator_slice):
127 self.items = list(iterator_slice)
128 self._size = len(self.items)
129
130 def __call__(self):
--> 131 return [func(*args, **kwargs) for func, args, kwargs in self.items]
self.items = [(<function bin_estimate_single>, (2870, chrom start end sum ...2 735658 4
[11504 rows x 9 columns], ['prob_2p', 'prob_f', 'prob_g', 'cor_2p', 'cor_f', 'cor_g', 'roc_2p', 'roc_f', 'roc_g', 'var_2p', 'var_f', 'ff_2p', 'ff_f', 'cv_2p', 'cv_f']), {}), (<function bin_estimate_single>, (2871, chrom start end sum ...2 735658 4
[11504 rows x 9 columns], ['prob_2p', 'prob_f', 'prob_g', 'cor_2p', 'cor_f', 'cor_g', 'roc_2p', 'roc_f', 'roc_g', 'var_2p', 'var_f', 'ff_2p', 'ff_f', 'cv_2p', 'cv_f']), {}), (<function bin_estimate_single>, (2872, chrom start end sum ...2 735658 4
[11504 rows x 9 columns], ['prob_2p', 'prob_f', 'prob_g', 'cor_2p', 'cor_f', 'cor_g', 'roc_2p', 'roc_f', 'roc_g', 'var_2p', 'var_f', 'ff_2p', 'ff_f', 'cv_2p', 'cv_f']), {}), (<function bin_estimate_single>, (2873, chrom start end sum ...2 735658 4
[11504 rows x 9 columns], ['prob_2p', 'prob_f', 'prob_g', 'cor_2p', 'cor_f', 'cor_g', 'roc_2p', 'roc_f', 'roc_g', 'var_2p', 'var_f', 'ff_2p', 'ff_f', 'cv_2p', 'cv_f']), {}), (<function bin_estimate_single>, (2874, chrom start end sum ...2 735658 4
[11504 rows x 9 columns], ['prob_2p', 'prob_f', 'prob_g', 'cor_2p', 'cor_f', 'cor_g', 'roc_2p', 'roc_f', 'roc_g', 'var_2p', 'var_f', 'ff_2p', 'ff_f', 'cv_2p', 'cv_f']), {}), (<function bin_estimate_single>, (2875, chrom start end sum ...2 735658 4
[11504 rows x 9 columns], ['prob_2p', 'prob_f', 'prob_g', 'cor_2p', 'cor_f', 'cor_g', 'roc_2p', 'roc_f', 'roc_g', 'var_2p', 'var_f', 'ff_2p', 'ff_f', 'cv_2p', 'cv_f']), {}), (<function bin_estimate_single>, (2876, chrom start end sum ...2 735658 4
[11504 rows x 9 columns], ['prob_2p', 'prob_f', 'prob_g', 'cor_2p', 'cor_f', 'cor_g', 'roc_2p', 'roc_f', 'roc_g', 'var_2p', 'var_f', 'ff_2p', 'ff_f', 'cv_2p', 'cv_f']), {}), (<function bin_estimate_single>, (2877, chrom start end sum ...2 735658 4
[11504 rows x 9 columns], ['prob_2p', 'prob_f', 'prob_g', 'cor_2p', 'cor_f', 'cor_g', 'roc_2p', 'roc_f', 'roc_g', 'var_2p', 'var_f', 'ff_2p', 'ff_f', 'cv_2p', 'cv_f']), {})]
132
133 def __len__(self):
134 return self._size
135
...........................................................................
/usr/local/lib/python3.5/dist-packages/joblib/parallel.py in <listcomp>(.0=<list_iterator object>)
126 def __init__(self, iterator_slice):
127 self.items = list(iterator_slice)
128 self._size = len(self.items)
129
130 def __call__(self):
--> 131 return [func(*args, **kwargs) for func, args, kwargs in self.items]
func = <function bin_estimate_single>
args = (2877, chrom start end sum ...2 735658 4
[11504 rows x 9 columns], ['prob_2p', 'prob_f', 'prob_g', 'cor_2p', 'cor_f', 'cor_g', 'roc_2p', 'roc_f', 'roc_g', 'var_2p', 'var_f', 'ff_2p', 'ff_f', 'cv_2p', 'cv_f'])
kwargs = {}
132
133 def __len__(self):
134 return self._size
135
...........................................................................
/usr/local/lib/python3.5/dist-packages/gpseqc/centrality.py in bin_estimate_single(i=2877, df= chrom start end sum ...2 735658 4
[11504 rows x 9 columns], mlist=['prob_2p', 'prob_f', 'prob_g', 'cor_2p', 'cor_f', 'cor_g', 'roc_2p', 'roc_f', 'roc_g', 'var_2p', 'var_f', 'ff_2p', 'ff_f', 'cv_2p', 'cv_f'])
238
239 # Calculate requested metrics
240 for m in mlist:
241 # Probability
242 if m == "prob_2p": # two-points
--> 243 orow[m] = est_2p(st, calc_p, lambda x, y: x / y)
orow = 'chr6'
m = 'prob_2p'
st = 0 chr6
1 87000000
2 88000000
3 ... 596776
8 3
Name: 2877, dtype: object
244 elif m == "prob_f": # fixed
245 orow[m] = est_f(st, calc_p, lambda x, y: x / y)
246 elif m == "prob_g": # global
247 orow[m] = est_g(st, calc_p, lambda x, y: x / y)
...........................................................................
/usr/local/lib/python3.5/dist-packages/gpseqc/centrality.py in est_2p(st=0 chr6
1 87000000
2 88000000
3 ... 596776
8 3
Name: 2877, dtype: object, f1=<function calc_p>, f2=<function bin_estimate_single.<locals>.<lambda>>)
118 f2 (fun): function for putting conditions together.
119
120 Returns:
121 Estimated centrality.
122 '''
--> 123 a = f1(st, 0)
a = undefined
f1 = <function calc_p>
st = 0 chr6
1 87000000
2 88000000
3 ... 596776
8 3
Name: 2877, dtype: object
124 b = f1(st, st.shape[0] - 1)
125 return(f2(b, a))
126
127 def est_f(st, f1, f2):
...........................................................................
/usr/local/lib/python3.5/dist-packages/gpseqc/centrality.py in calc_p(st=0 chr6
1 87000000
2 88000000
3 ... 596776
8 3
Name: 2877, dtype: object, ci=0)
26
27 Returns:
28 float
29 '''
30 assert ci < st.shape[0], "requested condition (index) not found."
---> 31 row = st.iloc[ci, :]
row = undefined
st.iloc = <pandas.core.indexing._iLocIndexer object>
ci = 0
32 p = (row['cond_nreads'] * row['count'])
33 p = row['sum'] / p if 0 != p else np.nan
34 return(p)
35
...........................................................................
/usr/local/lib/python3.5/dist-packages/pandas/core/indexing.py in __getitem__(self=<pandas.core.indexing._iLocIndexer object>, key=(0, slice(None, None, None)))
1362 try:
1363 if self._is_scalar_access(key):
1364 return self._getitem_scalar(key)
1365 except (KeyError, IndexError):
1366 pass
-> 1367 return self._getitem_tuple(key)
self._getitem_tuple = <bound method _iLocIndexer._getitem_tuple of <pandas.core.indexing._iLocIndexer object>>
key = (0, slice(None, None, None))
1368 else:
1369 # we by definition only have the 0th axis
1370 axis = self.axis or 0
1371
...........................................................................
/usr/local/lib/python3.5/dist-packages/pandas/core/indexing.py in _getitem_tuple(self=<pandas.core.indexing._iLocIndexer object>, tup=(0, slice(None, None, None)))
1732
1733 return True
1734
1735 def _getitem_tuple(self, tup):
1736
-> 1737 self._has_valid_tuple(tup)
self._has_valid_tuple = <bound method _NDFrameIndexer._has_valid_tuple of <pandas.core.indexing._iLocIndexer object>>
tup = (0, slice(None, None, None))
1738 try:
1739 return self._getitem_lowerdim(tup)
1740 except:
1741 pass
...........................................................................
/usr/local/lib/python3.5/dist-packages/pandas/core/indexing.py in _has_valid_tuple(self=<pandas.core.indexing._iLocIndexer object>, key=(0, slice(None, None, None)))
198
199 def _has_valid_tuple(self, key):
200 """ check the key for valid keys across my indexer """
201 for i, k in enumerate(key):
202 if i >= self.obj.ndim:
--> 203 raise IndexingError('Too many indexers')
204 if not self._has_valid_type(k, i):
205 raise ValueError("Location based indexing can only have "
206 "[{types}] types"
207 .format(types=self._valid_types))
IndexingError: Too many indexers
___________________________________________________________________________
"""
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/usr/local/lib/python3.5/dist-packages/joblib/parallel.py", line 699, in retrieve
self._output.extend(job.get(timeout=self.timeout))
File "/usr/lib/python3.5/multiprocessing/pool.py", line 608, in get
raise self._value
joblib.my_exceptions.TransportableException: TransportableException
___________________________________________________________________________
IndexingError Tue Apr 24 13:48:52 2018
PID: 29536 Python 3.5.2: /usr/bin/python3
...........................................................................
/usr/local/lib/python3.5/dist-packages/joblib/parallel.py in __call__(self=<joblib.parallel.BatchedCalls object>)
126 def __init__(self, iterator_slice):
127 self.items = list(iterator_slice)
128 self._size = len(self.items)
129
130 def __call__(self):
--> 131 return [func(*args, **kwargs) for func, args, kwargs in self.items]
self.items = [(<function bin_estimate_single>, (2870, chrom start end sum ...2 735658 4
[11504 rows x 9 columns], ['prob_2p', 'prob_f', 'prob_g', 'cor_2p', 'cor_f', 'cor_g', 'roc_2p', 'roc_f', 'roc_g', 'var_2p', 'var_f', 'ff_2p', 'ff_f', 'cv_2p', 'cv_f']), {}), (<function bin_estimate_single>, (2871, chrom start end sum ...2 735658 4
[11504 rows x 9 columns], ['prob_2p', 'prob_f', 'prob_g', 'cor_2p', 'cor_f', 'cor_g', 'roc_2p', 'roc_f', 'roc_g', 'var_2p', 'var_f', 'ff_2p', 'ff_f', 'cv_2p', 'cv_f']), {}), (<function bin_estimate_single>, (2872, chrom start end sum ...2 735658 4
[11504 rows x 9 columns], ['prob_2p', 'prob_f', 'prob_g', 'cor_2p', 'cor_f', 'cor_g', 'roc_2p', 'roc_f', 'roc_g', 'var_2p', 'var_f', 'ff_2p', 'ff_f', 'cv_2p', 'cv_f']), {}), (<function bin_estimate_single>, (2873, chrom start end sum ...2 735658 4
[11504 rows x 9 columns], ['prob_2p', 'prob_f', 'prob_g', 'cor_2p', 'cor_f', 'cor_g', 'roc_2p', 'roc_f', 'roc_g', 'var_2p', 'var_f', 'ff_2p', 'ff_f', 'cv_2p', 'cv_f']), {}), (<function bin_estimate_single>, (2874, chrom start end sum ...2 735658 4
[11504 rows x 9 columns], ['prob_2p', 'prob_f', 'prob_g', 'cor_2p', 'cor_f', 'cor_g', 'roc_2p', 'roc_f', 'roc_g', 'var_2p', 'var_f', 'ff_2p', 'ff_f', 'cv_2p', 'cv_f']), {}), (<function bin_estimate_single>, (2875, chrom start end sum ...2 735658 4
[11504 rows x 9 columns], ['prob_2p', 'prob_f', 'prob_g', 'cor_2p', 'cor_f', 'cor_g', 'roc_2p', 'roc_f', 'roc_g', 'var_2p', 'var_f', 'ff_2p', 'ff_f', 'cv_2p', 'cv_f']), {}), (<function bin_estimate_single>, (2876, chrom start end sum ...2 735658 4
[11504 rows x 9 columns], ['prob_2p', 'prob_f', 'prob_g', 'cor_2p', 'cor_f', 'cor_g', 'roc_2p', 'roc_f', 'roc_g', 'var_2p', 'var_f', 'ff_2p', 'ff_f', 'cv_2p', 'cv_f']), {}), (<function bin_estimate_single>, (2877, chrom start end sum ...2 735658 4
[11504 rows x 9 columns], ['prob_2p', 'prob_f', 'prob_g', 'cor_2p', 'cor_f', 'cor_g', 'roc_2p', 'roc_f', 'roc_g', 'var_2p', 'var_f', 'ff_2p', 'ff_f', 'cv_2p', 'cv_f']), {})]
132
133 def __len__(self):
134 return self._size
135
...........................................................................
/usr/local/lib/python3.5/dist-packages/joblib/parallel.py in <listcomp>(.0=<list_iterator object>)
126 def __init__(self, iterator_slice):
127 self.items = list(iterator_slice)
128 self._size = len(self.items)
129
130 def __call__(self):
--> 131 return [func(*args, **kwargs) for func, args, kwargs in self.items]
func = <function bin_estimate_single>
args = (2877, chrom start end sum ...2 735658 4
[11504 rows x 9 columns], ['prob_2p', 'prob_f', 'prob_g', 'cor_2p', 'cor_f', 'cor_g', 'roc_2p', 'roc_f', 'roc_g', 'var_2p', 'var_f', 'ff_2p', 'ff_f', 'cv_2p', 'cv_f'])
kwargs = {}
132
133 def __len__(self):
134 return self._size
135
...........................................................................
/usr/local/lib/python3.5/dist-packages/gpseqc/centrality.py in bin_estimate_single(i=2877, df= chrom start end sum ...2 735658 4
[11504 rows x 9 columns], mlist=['prob_2p', 'prob_f', 'prob_g', 'cor_2p', 'cor_f', 'cor_g', 'roc_2p', 'roc_f', 'roc_g', 'var_2p', 'var_f', 'ff_2p', 'ff_f', 'cv_2p', 'cv_f'])
238
239 # Calculate requested metrics
240 for m in mlist:
241 # Probability
242 if m == "prob_2p": # two-points
--> 243 orow[m] = est_2p(st, calc_p, lambda x, y: x / y)
orow = 'chr6'
m = 'prob_2p'
st = 0 chr6
1 87000000
2 88000000
3 ... 596776
8 3
Name: 2877, dtype: object
244 elif m == "prob_f": # fixed
245 orow[m] = est_f(st, calc_p, lambda x, y: x / y)
246 elif m == "prob_g": # global
247 orow[m] = est_g(st, calc_p, lambda x, y: x / y)
...........................................................................
/usr/local/lib/python3.5/dist-packages/gpseqc/centrality.py in est_2p(st=0 chr6
1 87000000
2 88000000
3 ... 596776
8 3
Name: 2877, dtype: object, f1=<function calc_p>, f2=<function bin_estimate_single.<locals>.<lambda>>)
118 f2 (fun): function for putting conditions together.
119
120 Returns:
121 Estimated centrality.
122 '''
--> 123 a = f1(st, 0)
a = undefined
f1 = <function calc_p>
st = 0 chr6
1 87000000
2 88000000
3 ... 596776
8 3
Name: 2877, dtype: object
124 b = f1(st, st.shape[0] - 1)
125 return(f2(b, a))
126
127 def est_f(st, f1, f2):
...........................................................................
/usr/local/lib/python3.5/dist-packages/gpseqc/centrality.py in calc_p(st=0 chr6
1 87000000
2 88000000
3 ... 596776
8 3
Name: 2877, dtype: object, ci=0)
26
27 Returns:
28 float
29 '''
30 assert ci < st.shape[0], "requested condition (index) not found."
---> 31 row = st.iloc[ci, :]
row = undefined
st.iloc = <pandas.core.indexing._iLocIndexer object>
ci = 0
32 p = (row['cond_nreads'] * row['count'])
33 p = row['sum'] / p if 0 != p else np.nan
34 return(p)
35
...........................................................................
/usr/local/lib/python3.5/dist-packages/pandas/core/indexing.py in __getitem__(self=<pandas.core.indexing._iLocIndexer object>, key=(0, slice(None, None, None)))
1362 try:
1363 if self._is_scalar_access(key):
1364 return self._getitem_scalar(key)
1365 except (KeyError, IndexError):
1366 pass
-> 1367 return self._getitem_tuple(key)
self._getitem_tuple = <bound method _iLocIndexer._getitem_tuple of <pandas.core.indexing._iLocIndexer object>>
key = (0, slice(None, None, None))
1368 else:
1369 # we by definition only have the 0th axis
1370 axis = self.axis or 0
1371
...........................................................................
/usr/local/lib/python3.5/dist-packages/pandas/core/indexing.py in _getitem_tuple(self=<pandas.core.indexing._iLocIndexer object>, tup=(0, slice(None, None, None)))
1732
1733 return True
1734
1735 def _getitem_tuple(self, tup):
1736
-> 1737 self._has_valid_tuple(tup)
self._has_valid_tuple = <bound method _NDFrameIndexer._has_valid_tuple of <pandas.core.indexing._iLocIndexer object>>
tup = (0, slice(None, None, None))
1738 try:
1739 return self._getitem_lowerdim(tup)
1740 except:
1741 pass
...........................................................................
/usr/local/lib/python3.5/dist-packages/pandas/core/indexing.py in _has_valid_tuple(self=<pandas.core.indexing._iLocIndexer object>, key=(0, slice(None, None, None)))
198
199 def _has_valid_tuple(self, key):
200 """ check the key for valid keys across my indexer """
201 for i, k in enumerate(key):
202 if i >= self.obj.ndim:
--> 203 raise IndexingError('Too many indexers')
204 if not self._has_valid_type(k, i):
205 raise ValueError("Location based indexing can only have "
206 "[{types}] types"
207 .format(types=self._valid_types))
IndexingError: Too many indexers
___________________________________________________________________________
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/usr/local/bin/gpseqc_estimate", line 504, in <module>
est = centrality.bin_estimate_parallel(comb, toCalc, args.threads)
File "/usr/local/lib/python3.5/dist-packages/gpseqc/centrality.py", line 213, in bin_estimate_parallel
for i in list(set(df.index)))
File "/usr/local/lib/python3.5/dist-packages/joblib/parallel.py", line 789, in __call__
self.retrieve()
File "/usr/local/lib/python3.5/dist-packages/joblib/parallel.py", line 740, in retrieve
raise exception
joblib.my_exceptions.JoblibIndexingError: JoblibIndexingError
___________________________________________________________________________
Multiprocessing exception:
...........................................................................
/usr/local/bin/gpseqc_estimate in <module>()
499
500 # Estimate centrality of each bin
501 if 1 == args.threads:
502 est = centrality.bin_estimate(comb, toCalc)
503 else:
--> 504 est = centrality.bin_estimate_parallel(comb, toCalc, args.threads)
505 df_saveas(est, "estimated.%s.tsv" % descr, args)
506
507 # (10) Rank bins ---------------------------------------------------------------
508 print("Ranking bins...")
...........................................................................
/usr/local/lib/python3.5/dist-packages/gpseqc/centrality.py in bin_estimate_parallel(df= chrom start end sum ...2 735658 4
[11504 rows x 9 columns], mlist=['prob_2p', 'prob_f', 'prob_g', 'cor_2p', 'cor_f', 'cor_g', 'roc_2p', 'roc_f', 'roc_g', 'var_2p', 'var_f', 'ff_2p', 'ff_f', 'cv_2p', 'cv_f'], threads=7, progress=True)
208 verbose = 10 if progress else 0
209
210 # Iterate over bins
211 odf = Parallel(n_jobs = threads, verbose = verbose)(
212 delayed(bin_estimate_single)(i, df, mlist)
--> 213 for i in list(set(df.index)))
df.index = Int64Index([ 370, 2325, 2323, 2328, 2428, 2425, ...9, 142],
dtype='int64', length=11504)
214
215 # Assemble output
216 odf = pd.concat(odf, axis = 1).transpose()
217 columns = ['chrom', 'start', 'end']
...........................................................................
/usr/local/lib/python3.5/dist-packages/joblib/parallel.py in __call__(self=Parallel(n_jobs=7), iterable=<generator object bin_estimate_parallel.<locals>.<genexpr>>)
784 if pre_dispatch == "all" or n_jobs == 1:
785 # The iterable was consumed all at once by the above for loop.
786 # No need to wait for async callbacks to trigger to
787 # consumption.
788 self._iterating = False
--> 789 self.retrieve()
self.retrieve = <bound method Parallel.retrieve of Parallel(n_jobs=7)>
790 # Make sure that we get a last message telling us we are done
791 elapsed_time = time.time() - self._start_time
792 self._print('Done %3i out of %3i | elapsed: %s finished',
793 (len(self._output), len(self._output),
---------------------------------------------------------------------------
Sub-process traceback:
---------------------------------------------------------------------------
IndexingError Tue Apr 24 13:48:52 2018
PID: 29536 Python 3.5.2: /usr/bin/python3
...........................................................................
/usr/local/lib/python3.5/dist-packages/joblib/parallel.py in __call__(self=<joblib.parallel.BatchedCalls object>)
126 def __init__(self, iterator_slice):
127 self.items = list(iterator_slice)
128 self._size = len(self.items)
129
130 def __call__(self):
--> 131 return [func(*args, **kwargs) for func, args, kwargs in self.items]
self.items = [(<function bin_estimate_single>, (2870, chrom start end sum ...2 735658 4
[11504 rows x 9 columns], ['prob_2p', 'prob_f', 'prob_g', 'cor_2p', 'cor_f', 'cor_g', 'roc_2p', 'roc_f', 'roc_g', 'var_2p', 'var_f', 'ff_2p', 'ff_f', 'cv_2p', 'cv_f']), {}), (<function bin_estimate_single>, (2871, chrom start end sum ...2 735658 4
[11504 rows x 9 columns], ['prob_2p', 'prob_f', 'prob_g', 'cor_2p', 'cor_f', 'cor_g', 'roc_2p', 'roc_f', 'roc_g', 'var_2p', 'var_f', 'ff_2p', 'ff_f', 'cv_2p', 'cv_f']), {}), (<function bin_estimate_single>, (2872, chrom start end sum ...2 735658 4
[11504 rows x 9 columns], ['prob_2p', 'prob_f', 'prob_g', 'cor_2p', 'cor_f', 'cor_g', 'roc_2p', 'roc_f', 'roc_g', 'var_2p', 'var_f', 'ff_2p', 'ff_f', 'cv_2p', 'cv_f']), {}), (<function bin_estimate_single>, (2873, chrom start end sum ...2 735658 4
[11504 rows x 9 columns], ['prob_2p', 'prob_f', 'prob_g', 'cor_2p', 'cor_f', 'cor_g', 'roc_2p', 'roc_f', 'roc_g', 'var_2p', 'var_f', 'ff_2p', 'ff_f', 'cv_2p', 'cv_f']), {}), (<function bin_estimate_single>, (2874, chrom start end sum ...2 735658 4
[11504 rows x 9 columns], ['prob_2p', 'prob_f', 'prob_g', 'cor_2p', 'cor_f', 'cor_g', 'roc_2p', 'roc_f', 'roc_g', 'var_2p', 'var_f', 'ff_2p', 'ff_f', 'cv_2p', 'cv_f']), {}), (<function bin_estimate_single>, (2875, chrom start end sum ...2 735658 4
[11504 rows x 9 columns], ['prob_2p', 'prob_f', 'prob_g', 'cor_2p', 'cor_f', 'cor_g', 'roc_2p', 'roc_f', 'roc_g', 'var_2p', 'var_f', 'ff_2p', 'ff_f', 'cv_2p', 'cv_f']), {}), (<function bin_estimate_single>, (2876, chrom start end sum ...2 735658 4
[11504 rows x 9 columns], ['prob_2p', 'prob_f', 'prob_g', 'cor_2p', 'cor_f', 'cor_g', 'roc_2p', 'roc_f', 'roc_g', 'var_2p', 'var_f', 'ff_2p', 'ff_f', 'cv_2p', 'cv_f']), {}), (<function bin_estimate_single>, (2877, chrom start end sum ...2 735658 4
[11504 rows x 9 columns], ['prob_2p', 'prob_f', 'prob_g', 'cor_2p', 'cor_f', 'cor_g', 'roc_2p', 'roc_f', 'roc_g', 'var_2p', 'var_f', 'ff_2p', 'ff_f', 'cv_2p', 'cv_f']), {})]
132
133 def __len__(self):
134 return self._size
135
...........................................................................
/usr/local/lib/python3.5/dist-packages/joblib/parallel.py in <listcomp>(.0=<list_iterator object>)
126 def __init__(self, iterator_slice):
127 self.items = list(iterator_slice)
128 self._size = len(self.items)
129
130 def __call__(self):
--> 131 return [func(*args, **kwargs) for func, args, kwargs in self.items]
func = <function bin_estimate_single>
args = (2877, chrom start end sum ...2 735658 4
[11504 rows x 9 columns], ['prob_2p', 'prob_f', 'prob_g', 'cor_2p', 'cor_f', 'cor_g', 'roc_2p', 'roc_f', 'roc_g', 'var_2p', 'var_f', 'ff_2p', 'ff_f', 'cv_2p', 'cv_f'])
kwargs = {}
132
133 def __len__(self):
134 return self._size
135
...........................................................................
/usr/local/lib/python3.5/dist-packages/gpseqc/centrality.py in bin_estimate_single(i=2877, df= chrom start end sum ...2 735658 4
[11504 rows x 9 columns], mlist=['prob_2p', 'prob_f', 'prob_g', 'cor_2p', 'cor_f', 'cor_g', 'roc_2p', 'roc_f', 'roc_g', 'var_2p', 'var_f', 'ff_2p', 'ff_f', 'cv_2p', 'cv_f'])
238
239 # Calculate requested metrics
240 for m in mlist:
241 # Probability
242 if m == "prob_2p": # two-points
--> 243 orow[m] = est_2p(st, calc_p, lambda x, y: x / y)
orow = 'chr6'
m = 'prob_2p'
st = 0 chr6
1 87000000
2 88000000
3 ... 596776
8 3
Name: 2877, dtype: object
244 elif m == "prob_f": # fixed
245 orow[m] = est_f(st, calc_p, lambda x, y: x / y)
246 elif m == "prob_g": # global
247 orow[m] = est_g(st, calc_p, lambda x, y: x / y)
...........................................................................
/usr/local/lib/python3.5/dist-packages/gpseqc/centrality.py in est_2p(st=0 chr6
1 87000000
2 88000000
3 ... 596776
8 3
Name: 2877, dtype: object, f1=<function calc_p>, f2=<function bin_estimate_single.<locals>.<lambda>>)
118 f2 (fun): function for putting conditions together.
119
120 Returns:
121 Estimated centrality.
122 '''
--> 123 a = f1(st, 0)
a = undefined
f1 = <function calc_p>
st = 0 chr6
1 87000000
2 88000000
3 ... 596776
8 3
Name: 2877, dtype: object
124 b = f1(st, st.shape[0] - 1)
125 return(f2(b, a))
126
127 def est_f(st, f1, f2):
...........................................................................
/usr/local/lib/python3.5/dist-packages/gpseqc/centrality.py in calc_p(st=0 chr6
1 87000000
2 88000000
3 ... 596776
8 3
Name: 2877, dtype: object, ci=0)
26
27 Returns:
28 float
29 '''
30 assert ci < st.shape[0], "requested condition (index) not found."
---> 31 row = st.iloc[ci, :]
row = undefined
st.iloc = <pandas.core.indexing._iLocIndexer object>
ci = 0
32 p = (row['cond_nreads'] * row['count'])
33 p = row['sum'] / p if 0 != p else np.nan
34 return(p)
35
...........................................................................
/usr/local/lib/python3.5/dist-packages/pandas/core/indexing.py in __getitem__(self=<pandas.core.indexing._iLocIndexer object>, key=(0, slice(None, None, None)))
1362 try:
1363 if self._is_scalar_access(key):
1364 return self._getitem_scalar(key)
1365 except (KeyError, IndexError):
1366 pass
-> 1367 return self._getitem_tuple(key)
self._getitem_tuple = <bound method _iLocIndexer._getitem_tuple of <pandas.core.indexing._iLocIndexer object>>
key = (0, slice(None, None, None))
1368 else:
1369 # we by definition only have the 0th axis
1370 axis = self.axis or 0
1371
...........................................................................
/usr/local/lib/python3.5/dist-packages/pandas/core/indexing.py in _getitem_tuple(self=<pandas.core.indexing._iLocIndexer object>, tup=(0, slice(None, None, None)))
1732
1733 return True
1734
1735 def _getitem_tuple(self, tup):
1736
-> 1737 self._has_valid_tuple(tup)
self._has_valid_tuple = <bound method _NDFrameIndexer._has_valid_tuple of <pandas.core.indexing._iLocIndexer object>>
tup = (0, slice(None, None, None))
1738 try:
1739 return self._getitem_lowerdim(tup)
1740 except:
1741 pass
...........................................................................
/usr/local/lib/python3.5/dist-packages/pandas/core/indexing.py in _has_valid_tuple(self=<pandas.core.indexing._iLocIndexer object>, key=(0, slice(None, None, None)))
198
199 def _has_valid_tuple(self, key):
200 """ check the key for valid keys across my indexer """
201 for i, k in enumerate(key):
202 if i >= self.obj.ndim:
--> 203 raise IndexingError('Too many indexers')
204 if not self._has_valid_type(k, i):
205 raise ValueError("Location based indexing can only have "
206 "[{types}] types"
207 .format(types=self._valid_types))
IndexingError: Too many indexers