[Bug] Uninformative TypeError using tsfeatures when series_length < 12

[chillerobscuro]

I'm trying to run this on a test series of length 11 and freq='D', and getting TypeError: 'float' object is not subscriptable.

Is this expected/unavoidable? Ideally it could be fixed even if some features must return NaN or similar. Otherwise there could be a more informative error, or just check if the series_length is too small and raise an exception. Here is some code that breaks when the series_length is 11, but works when it's 12.

import numpy as np
import pandas as pd
from tsfeatures import tsfeatures

periods = 11
ind = pd.date_range(start='2000-01-01', periods=periods, freq='D')
vals = np.random.rand(periods)

df = pd.DataFrame({'ds':ind, 'y':vals, 'unique_id':1})
print(f'Inferred freq: {pd.infer_freq(df.ds)}')
print(df.head())

tsfeatures(df)

Output >

Inferred freq: D
          ds         y  unique_id
0 2000-01-01  0.576768          1
1 2000-01-02  0.482616          1
2 2000-01-03  0.848193          1
3 2000-01-04  0.180783          1
4 2000-01-05  0.060860          1

---------------------------------------------------------------------------
RemoteTraceback                           Traceback (most recent call last)
RemoteTraceback: 
"""
Traceback (most recent call last):
  File "/usr/local/Cellar/python@3.9/3.9.4/Frameworks/Python.framework/Versions/3.9/lib/python3.9/multiprocessing/pool.py", line 125, in worker
    result = (True, func(*args, **kwds))
  File "/usr/local/Cellar/python@3.9/3.9.4/Frameworks/Python.framework/Versions/3.9/lib/python3.9/multiprocessing/pool.py", line 51, in starmapstar
    return list(itertools.starmap(args[0], args[1]))
  File "/Users/loganduffy/Code/ts/notebooks/tsdl/lib/python3.9/site-packages/tsfeatures/tsfeatures.py", line 871, in _get_feats
    c_map = ChainMap(*[dict_feat for dict_feat in [func(ts, freq) for func in features]])
  File "/Users/loganduffy/Code/ts/notebooks/tsdl/lib/python3.9/site-packages/tsfeatures/tsfeatures.py", line 871, in <listcomp>
    c_map = ChainMap(*[dict_feat for dict_feat in [func(ts, freq) for func in features]])
  File "/Users/loganduffy/Code/ts/notebooks/tsdl/lib/python3.9/site-packages/tsfeatures/tsfeatures.py", line 539, in pacf_features
    pacf_5 = np.sum(pacfx[1:6] ** 2)
TypeError: 'float' object is not subscriptable
"""

The above exception was the direct cause of the following exception:

TypeError                                 Traceback (most recent call last)
Input In [239], in <cell line: 13>()
     10 print(f'Inferred freq: {pd.infer_freq(df.ds)}')
     11 print(df.head())
---> 13 tsfeatures(df)

File ~/Code/ts/notebooks/tsdl/lib/python3.9/site-packages/tsfeatures/tsfeatures.py:916, in tsfeatures(ts, freq, features, dict_freqs, scale, threads)
    912 partial_get_feats = partial(_get_feats, freq=freq, scale=scale,
    913                             features=features, dict_freqs=dict_freqs)
    915 with Pool(threads) as pool:
--> 916     ts_features = pool.starmap(partial_get_feats, ts.groupby('unique_id'))
    918 ts_features = pd.concat(ts_features).rename_axis('unique_id')
    919 ts_features = ts_features.reset_index()

File /usr/local/Cellar/python@3.9/3.9.4/Frameworks/Python.framework/Versions/3.9/lib/python3.9/multiprocessing/pool.py:372, in Pool.starmap(self, func, iterable, chunksize)
    366 def starmap(self, func, iterable, chunksize=None):
    367     '''
    368     Like `map()` method but the elements of the `iterable` are expected to
    369     be iterables as well and will be unpacked as arguments. Hence
    370     `func` and (a, b) becomes func(a, b).
    371     '''
--> 372     return self._map_async(func, iterable, starmapstar, chunksize).get()

File /usr/local/Cellar/python@3.9/3.9.4/Frameworks/Python.framework/Versions/3.9/lib/python3.9/multiprocessing/pool.py:771, in ApplyResult.get(self, timeout)
    769     return self._value
    770 else:
--> 771     raise self._value

TypeError: 'float' object is not subscriptable

[AzulGarza]

Hey @chillerobscuro! Thank you for reporting this.

I was able to reproduce the error. Let me dig into it.

[chillerobscuro]

Hey @FedericoGarza I know these things take time but any luck finding the root issue? If it's a straightforward fix I could open a PR

[AzulGarza]

hey @chillerobscuro! We release a new version (0.4.0) that fixes the issue 🙌