Hello,
When running the Plotly webinar notebook from github, at the following command:
df_pvss = endaq.calc.shock.pseudo_velocity(df, get_log_freqs(df,init_freq=1,bins_per_octave=12), damp=0.05, two_sided=False)-'
Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray.
ValueError Traceback (most recent call last)
in
----> 1 df_pvss = endaq.calc.shock.pseudo_velocity(df,
2 get_log_freqs(df,init_freq=1,bins_per_octave=12),
3 damp=0.05)
4 df_pvss = df_pvss9.8139.37 #convert to in/s
<__array_function__ internals> in apply_along_axis(*args, **kwargs)
[/usr/local/lib/python3.8/dist-packages/numpy/lib/shape_base.py](https://localhost:8080/#) in apply_along_axis(func1d, axis, arr, *args, **kwargs)
377 'Cannot apply_along_axis when any iteration dimensions are 0'
378 ) from None
--> 379 res = asanyarray(func1d(inarr_view[ind0], *args, **kwargs))
380
381 # build a buffer for storing evaluations of func1d.
[/usr/local/lib/python3.8/dist-packages/pandas/core/apply.py](https://localhost:8080/#) in wrapper(*args, **kwargs)
765
766 def wrapper(*args, **kwargs):
--> 767 result = func(*args, **kwargs)
768 if isinstance(result, str):
769 result = np.array(result, dtype=object)
[/usr/local/lib/python3.8/dist-packages/scipy/signal/signaltools.py](https://localhost:8080/#) in lfilter(b, a, x, axis, zi)
2053 else:
2054 if zi is None:
-> 2055 return sigtools._linear_filter(b, a, x, axis)
2056 else:
2057 return sigtools._linear_filter(b, a, x, axis, zi)
ValueError: could not convert b, a, and x to a common type`
Is there a way to fix this ?
Thanks a lot for your help and for providing this software as an open version !
Gilles
Hello, When running the Plotly webinar notebook from github, at the following command:
df_pvss = endaq.calc.shock.pseudo_velocity(df, get_log_freqs(df,init_freq=1,bins_per_octave=12), damp=0.05, two_sided=False)-'I get the following error message:
`---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
TypeError: pseudo_velocity() got an unexpected keyword argument 'two_sided'`
When removing this argument from the list I get new error messages running either Python 3.8, 3.9 or 3.10:
`/usr/local/lib/python3.8/dist-packages/numpy/core/shape_base.py:65: VisibleDeprecationWarning:
Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray.
ValueError Traceback (most recent call last)
/usr/local/lib/python3.8/dist-packages/endaq/calc/shock.py in pseudo_velocity(accel, omega, damp) 313 Q = 1./(2.*damp) 314 --> 315 return accel.apply( 316 functools.partial( 317 scipy.signal.lfilter,
/usr/local/lib/python3.8/dist-packages/pandas/core/frame.py in apply(self, func, axis, raw, result_type, args, **kwargs) 8738 kwargs=kwargs, 8739 ) -> 8740 return op.apply() 8741 8742 def applymap(
/usr/local/lib/python3.8/dist-packages/pandas/core/apply.py in apply(self) 684 # raw 685 elif self.raw: --> 686 return self.apply_raw() 687 688 return self.apply_standard()
/usr/local/lib/python3.8/dist-packages/pandas/core/apply.py in apply_raw(self) 772 return wrapper 773 --> 774 result = np.apply_along_axis(wrap_function(self.f), self.axis, self.values) 775 776 # TODO: mixed type case
<__array_function__ internals> in apply_along_axis(*args, **kwargs) [/usr/local/lib/python3.8/dist-packages/numpy/lib/shape_base.py](https://localhost:8080/#) in apply_along_axis(func1d, axis, arr, *args, **kwargs) 377 'Cannot apply_along_axis when any iteration dimensions are 0' 378 ) from None --> 379 res = asanyarray(func1d(inarr_view[ind0], *args, **kwargs)) 380 381 # build a buffer for storing evaluations of func1d. [/usr/local/lib/python3.8/dist-packages/pandas/core/apply.py](https://localhost:8080/#) in wrapper(*args, **kwargs) 765 766 def wrapper(*args, **kwargs): --> 767 result = func(*args, **kwargs) 768 if isinstance(result, str): 769 result = np.array(result, dtype=object) [/usr/local/lib/python3.8/dist-packages/scipy/signal/signaltools.py](https://localhost:8080/#) in lfilter(b, a, x, axis, zi) 2053 else: 2054 if zi is None: -> 2055 return sigtools._linear_filter(b, a, x, axis) 2056 else: 2057 return sigtools._linear_filter(b, a, x, axis, zi) ValueError: could not convert b, a, and x to a common type` Is there a way to fix this ? Thanks a lot for your help and for providing this software as an open version ! Gilles