Question

我正在开发一种使用熊猫进行活动识别的算法。在某种程度上，我正在这样做

feat = data[['x','y','z']].rolling(wsize, int(wsize/2)).apply(rms).add_suffix('_rms')

但是我收到此错误：

AttributeError                            Traceback (most recent call last)
<ipython-input-5-95eebeaeb992> in <module>
      1 data2 = read_data('all')
----> 2 feats, y = get_features2(data2, 2)
      3 X_train, X_test, y_train, y_test = train_test_split(feats, y, test_size=.25,
      4                                                     random_state=0, stratify=y)
      5 best_model.fit(X_train, y_train)

<ipython-input-4-8175c64d7de8> in get_features2(data, wsize_sec, overlap)
     19 
     20     #mean_mag = pd.rolling_apply((data**2).sum(axis=1), wsize, lambda ts: np.sqrt(ts).mean(), wsize/2)
---> 21     mean_mag = (data**2).sum(axis=1).swifter.rolling(wsize, int(wsize/2)).aplly(lambda ts: np.sqrt(ts).mean())
     22 
     23     mean_mag.name = 'mean_mag'

AttributeError: 'Rolling' object has no attribute 'aplly'

然后我尝试了迅捷

feat = data[['x','y','z']].swifter.rolling(wsize, int(wsize/2)).apply(rms).add_suffix('_rms')

现在错误已更改为：

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-10-95eebeaeb992> in <module>
      1 data2 = read_data('all')
----> 2 feats, y = get_features2(data2, 2)
      3 X_train, X_test, y_train, y_test = train_test_split(feats, y, test_size=.25,
      4                                                     random_state=0, stratify=y)
      5 best_model.fit(X_train, y_train)

<ipython-input-9-7810ed7c08b3> in get_features2(data, wsize_sec, overlap)
     15 
     16     #feat = pd.rolling_apply(data[['x','y','z']], wsize, rms, wsize/2).add_suffix('_rms')
---> 17     feat = data[['x','y','z']].swifter.rolling(wsize, int(wsize/2)).apply(rms).add_suffix('_rms')
     18     feats = feats.join(feat)
     19 

~/.local/lib/python3.6/site-packages/swifter/swifter.py in apply(self, func, *args, **kwds)
    344         # if pandas apply takes too long, use dask
    345         if est_apply_duration > self._dask_threshold:
--> 346             return self._dask_apply(func, *args, **kwds)
    347         else:  # use pandas
    348             if self._progress_bar:

~/.local/lib/python3.6/site-packages/swifter/swifter.py in _dask_apply(self, func, *args, **kwds)
    329                 return self._obj_dd.apply(func, *args, **kwds).compute(scheduler=self._scheduler)
    330         else:
--> 331             return self._obj_dd.apply(func, *args, **kwds).compute(scheduler=self._scheduler)
    332 
    333     def apply(self, func, *args, **kwds):

~/.local/lib/python3.6/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 

~/.local/lib/python3.6/site-packages/dask/base.py in compute(*args, **kwargs)
    391     schedule = get_scheduler(scheduler=kwargs.pop('scheduler', None),
    392                              collections=collections,
--> 393                              get=kwargs.pop('get', None))
    394 
    395     dsk = collections_to_dsk(collections, optimize_graph, **kwargs)

~/.local/lib/python3.6/site-packages/dask/base.py in get_scheduler(get, scheduler, collections, cls)
    868         elif "Client" in type(scheduler).__name__ and hasattr(scheduler, 'get'):
    869             return scheduler.get
--> 870         elif scheduler.lower() in named_schedulers:
    871             return named_schedulers[scheduler.lower()]
    872         elif scheduler.lower() in ('dask.distributed', 'distributed'):

AttributeError: 'bool' object has no attribute 'lower'

如何解决此错误？我正在使用python 3.6和pandas 0.24.2。

这是完整的代码： https://github.com/pauloaferreiraa/Thesis/blob/master/analysis_python3.ipynb

滚动没有属性适用

0 个答案: