Version info :bta_lib-1.0.0
Python version 3.8

import btalib
df = pd.read_csv('2006-day-001.txt', parse_dates=True, index_col='Date')
kama = btalib.kama(df)

TypeError Traceback (most recent call last)
Input In [1089], in <cell line: 1>()
----> 1 kama = btalib.kama(df)

File ~/miniforge3/envs/tf_ml/lib/python3.8/site-packages/btalib/indicator.py:152, in MetaIndicator.call(cls, *args, **kwargs)
150 # Auto-call base classes
151 for b_init in reversed(list(dict.fromkeys(b.init for b in bases))):
--> 152 b_init(self, *args, **kwargs)
154 # delete old aliases only meant for operational purposes
155 for oalias in ('l', 'lines', 'data', 'd', 'datas'):

File ~/miniforge3/envs/tf_ml/lib/python3.8/site-packages/btalib/indicators/kama.py:84, in kama.init(self)
81 sc = (effratio * (scfast - scslow) + scslow).pow(2)
83 # Get the _ewm window function and calculate the dynamic mean on it
---> 84 self.o.kama = self.i0._ewm(
85 span=self.p.period, alpha=sc, _seed=self.p._seed)._mean()

File ~/miniforge3/envs/tf_ml/lib/python3.8/site-packages/btalib/meta/lines.py:357, in multifunc_op.<locals>._MultiFunc_Op._mean(self)
353 vals[i] = prev = prev + alphai * (vals[i] - prev)
355 return vals # can return vals, made Series via getattr
--> 357 return self._apply(_dynalpha)

File ~/miniforge3/envs/tf_ml/lib/python3.8/site-packages/btalib/meta/lines.py:379, in multifunc_op.<locals>._MultiFunc_Op.getattr.<locals>.call_op(*args, **kwargs)
375 arg = arg._series[self._minidx:]
377 sargs.append(arg)
--> 379 result[self._minidx:] = r = op(*sargs, **kwargs) # run/store
380 result = result.astype(r.dtype, copy=False)
381 return self._line._clone(result, period=self._minperiod)

File ~/miniforge3/envs/tf_ml/lib/python3.8/site-packages/pandas/core/window/rolling.py:590, in BaseWindow._apply(self, func, name, numba_cache_key, numba_args, **kwargs)
587 return result
589 if self.method == "single":
--> 590 return self._apply_blockwise(homogeneous_func, name)
591 else:
592 return self._apply_tablewise(homogeneous_func, name)

File ~/miniforge3/envs/tf_ml/lib/python3.8/site-packages/pandas/core/window/rolling.py:442, in BaseWindow._apply_blockwise(self, homogeneous_func, name)
437 """
438 Apply the given function to the DataFrame broken down into homogeneous
439 sub-frames.
440 """
441 if self._selected_obj.ndim == 1:
--> 442 return self._apply_series(homogeneous_func, name)
444 obj = self._create_data(self._selected_obj)
445 if name == "count":
446 # GH 12541: Special case for count where we support date-like types

File ~/miniforge3/envs/tf_ml/lib/python3.8/site-packages/pandas/core/window/rolling.py:431, in BaseWindow._apply_series(self, homogeneous_func, name)
428 except (TypeError, NotImplementedError) as err:
429 raise DataError("No numeric types to aggregate") from err
--> 431 result = homogeneous_func(values)
432 return obj._constructor(result, index=obj.index, name=obj.name)

File ~/miniforge3/envs/tf_ml/lib/python3.8/site-packages/pandas/core/window/rolling.py:582, in BaseWindow._apply.<locals>.homogeneous_func(values)
579 return func(x, start, end, min_periods, *numba_args)
581 with np.errstate(all="ignore"):
--> 582 result = calc(values)
584 if numba_cache_key is not None:
585 NUMBA_FUNC_CACHE[numba_cache_key] = func

File ~/miniforge3/envs/tf_ml/lib/python3.8/site-packages/pandas/core/window/rolling.py:579, in BaseWindow._apply.<locals>.homogeneous_func.<locals>.calc(x)
571 start, end = window_indexer.get_window_bounds(
572 num_values=len(x),
573 min_periods=min_periods,
574 center=self.center,
575 closed=self.closed,
576 )
577 self._check_window_bounds(start, end, len(x))
--> 579 return func(x, start, end, min_periods, *numba_args)

TypeError: _dynalpha() takes 1 positional argument but 4 were given