ypeError: No matching definition for argument type(s) array(float64, 2d, C), array(int32, 1d, C), array(bool, 1d, C)

[MislavSag]

I am trying to reproduce example from readme. I get error in this line

# Generate signals
fast_ma, slow_ma = vbt.MA.from_combinations(price, windows, 2)

The error message is:

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-15-9abe364754ce> in <module>
      1 # Generate signals
----> 2 fast_ma, slow_ma = vbt.MA.from_combinations(price, windows, 2)

C:\ProgramData\Anaconda3\lib\site-packages\vectorbt\indicators\indicators.py in from_combinations(cls, ts, windows, r, ewm, names, **kwargs)
    202             names = ['ma' + str(i+1) for i in range(r)]
    203         windows, ewm = reshape_fns.broadcast(windows, ewm, writeable=True)
--> 204         cache_dict = cls.from_params(ts, windows, ewm=ewm, return_cache=True, **kwargs)
    205         param_lists = zip(*itertools.combinations(zip(windows, ewm), r))
    206         mas = []

C:\ProgramData\Anaconda3\lib\site-packages\vectorbt\indicators\indicators.py in from_params(cls, ts, window, ewm, **kwargs)
     98             ```
     99         """
--> 100         return super().from_params(ts, window, ewm, **kwargs)
    101 
    102     @classmethod

C:\ProgramData\Anaconda3\lib\site-packages\vectorbt\indicators\factory.py in from_params(cls, name, return_raw, *args, **kwargs)
    614             results = from_params_pipeline(
    615                 ts_list, param_list, level_names, len(output_names),
--> 616                 custom_func, *new_args, pass_lists=pass_lists, return_raw=return_raw, **kwargs)
    617             if return_raw or kwargs.get('return_cache', False):
    618                 return results

C:\ProgramData\Anaconda3\lib\site-packages\vectorbt\indicators\factory.py in from_params_pipeline(ts_list, param_list, level_names, num_outputs, custom_func, pass_lists, param_product, broadcast_kwargs, return_raw, *args, **kwargs)
    405     # Perform main calculation
    406     if pass_lists:
--> 407         output_list = custom_func(ts_list, param_list, *args, **kwargs)
    408     else:
    409         output_list = custom_func(*ts_list, *param_list, *args, **kwargs)

C:\ProgramData\Anaconda3\lib\site-packages\vectorbt\indicators\factory.py in custom_func(ts_list, param_list, return_cache, cache, *args)
    778                 # Caching
    779                 if cache is None and caching_func is not None:
--> 780                     cache = caching_func(*typed_ts_list, *param_list, *args)
    781                 if return_cache:
    782                     return cache

~\AppData\Roaming\Python\Python37\site-packages\numba\dispatcher.py in _explain_matching_error(self, *args, **kws)
    572         msg = ("No matching definition for argument type(s) %s"
    573                % ', '.join(map(str, args)))
--> 574         raise TypeError(msg)
    575 
    576     def _search_new_conversions(self, *args, **kws):

TypeError: No matching definition for argument type(s) array(float64, 2d, C), array(int32, 1d, C), array(bool, 1d, C)

I haven't change anything in the code. Looks like numba error?

[polakowo]

This is similar to https://github.com/polakowo/vectorbt/issues/15#issue-611078630

Try to cast your windows array to np.float64.

The next version of vectorbt will work with any integer data type.

[MislavSag]

I have just tried:

# Define params
windows = np.arange(2, 101)
windows = windows.astype(np.float64)
investment = 100 # in $
commission = 0.001 # in %

# Prepare data
ticker = yf.Ticker("BTC-USD")
price = ticker.history(period="max")['Close']

# Generate signals
fast_ma, slow_ma = vbt.MA.from_combinations(price, windows, 2)

but got the same error.

[polakowo]

I've done a fresh install and tried the readme example and it worked. I think Numba behaves differently across different platforms, which is painful. I will issue a version 0.6 tomorrow or Wednesday, it will be type agnostic.

[MislavSag]

Yeah, numba can behave unexpectedly. I will wait for new release than.

[MislavSag]

There were no new comitts. Probably zou didn't have time to upmake upgrade?

[polakowo]

It's in the works. Had to give it more time to refactor portfolio, will release with one bulk update once everything fits (100% on the weekend).

[MislavSag]

OK, just wanted to check out if I missed anything. I would like to see if your package would fit my needs. I want to backtest my simple ML strategy.

[polakowo]

I released the version 0.6 without explicit typing. It requires numba 0.49.

[MislavSag]

After installation, when I try to import vectorbt, it returns:

---------------------------------------------------------------------------
ModuleNotFoundError                       Traceback (most recent call last)
c:\Users\Mislav\Documents\GitHub\trademl\trademl\modeling\random_forest\train_rf.py in 
----> 395 import vectorbt as vbt

C:\ProgramData\Anaconda3\lib\site-packages\vectorbt\__init__.py in 
----> 1 from vectorbt import utils, accessors, timeseries, widgets, signals, portfolio, indicators, defaults
      2 
      3 # Most important classes
      4 from vectorbt.widgets import Indicator, Bar, Scatter, Histogram, Heatmap
      5 from vectorbt.portfolio import Portfolio

C:\ProgramData\Anaconda3\lib\site-packages\vectorbt\utils\__init__.py in 
      1 """Utility functions and classes for various parts of `vectorbt`."""
      2 
----> 3 from vectorbt.utils import checks, combine_fns, common, index_fns, indexing, reshape_fns, accessors

C:\ProgramData\Anaconda3\lib\site-packages\vectorbt\utils\checks.py in 
      3 import numpy as np
      4 import pandas as pd
----> 5 from numba.core.registry import CPUDispatcher
      6 
      7 from vectorbt.utils import reshape_fns

ModuleNotFoundError: No module named 'numba.core'

I have the latest version of numba installed.

[polakowo]

Which exact version of numba do you have installed? I cannot reproduce this error.

[MislavSag]

I uninstall and install the package again and now I can import the package, but get following error:

---------------------------------------------------------------------------
TypingError                               Traceback (most recent call last)
<ipython-input-4-9abe364754ce> in <module>
      1 # Generate signals
----> 2 fast_ma, slow_ma = vbt.MA.from_combinations(price, windows, 2)

C:\ProgramData\Anaconda3\lib\site-packages\vectorbt\indicators\indicators.py in from_combinations(cls, ts, windows, r, ewm, names, **kwargs)
    203             names = ['ma' + str(i+1) for i in range(r)]
    204         windows, ewm = reshape_fns.broadcast(windows, ewm, writeable=True)
--> 205         cache_dict = cls.from_params(ts, windows, ewm=ewm, return_cache=True, **kwargs)
    206         param_lists = zip(*itertools.combinations(zip(windows, ewm), r))
    207         mas = []

C:\ProgramData\Anaconda3\lib\site-packages\vectorbt\indicators\indicators.py in from_params(cls, ts, window, ewm, **kwargs)
     99             ```
    100         """
--> 101         return super().from_params(ts, window, ewm, **kwargs)
    102 
    103     @classmethod

C:\ProgramData\Anaconda3\lib\site-packages\vectorbt\indicators\factory.py in from_params(cls, name, return_raw, pipeline_kwargs, *args, **kwargs)
    611             results = from_params_pipeline(
    612                 ts_list, param_list, level_names, len(output_names),
--> 613                 custom_func, *new_args, return_raw=return_raw, **kwargs)
    614             if return_raw or kwargs.get('return_cache', False):
    615                 return results

C:\ProgramData\Anaconda3\lib\site-packages\vectorbt\indicators\factory.py in from_params_pipeline(ts_list, param_list, level_names, num_outputs, custom_func, pass_lists, pass_2d, param_product, broadcast_kwargs, return_raw, *args, **kwargs)
    409         array_list = tuple(map(lambda x: np.asarray(x), ts_list))
    410     if pass_lists:
--> 411         output_list = custom_func(array_list, param_list, *args, **kwargs)
    412     else:
    413         output_list = custom_func(*array_list, *param_list, *args, **kwargs)

C:\ProgramData\Anaconda3\lib\site-packages\vectorbt\indicators\factory.py in custom_func(ts_arr_list, param_list, return_cache, cache, *args)
    778                 # Caching
    779                 if cache is None and caching_func is not None:
--> 780                     cache = caching_func(*ts_arr_list, *param_list, *args)
    781                 if return_cache:
    782                     return cache

C:\ProgramData\Anaconda3\lib\site-packages\numba\core\dispatcher.py in _compile_for_args(self, *args, **kws)
    399                 e.patch_message(msg)
    400 
--> 401             error_rewrite(e, 'typing')
    402         except errors.UnsupportedError as e:
    403             # Something unsupported is present in the user code, add help info

C:\ProgramData\Anaconda3\lib\site-packages\numba\core\dispatcher.py in error_rewrite(e, issue_type)
    342                 raise e
    343             else:
--> 344                 reraise(type(e), e, None)
    345 
    346         argtypes = []

C:\ProgramData\Anaconda3\lib\site-packages\numba\core\utils.py in reraise(tp, value, tb)
     78         value = tp()
     79     if value.__traceback__ is not tb:
---> 80         raise value.with_traceback(tb)
     81     raise value
     82 

TypingError: Failed in nopython mode pipeline (step: nopython frontend)
Failed in nopython mode pipeline (step: nopython frontend)
Failed in nopython mode pipeline (step: nopython frontend)
Invalid use of Function(<built-in function getitem>) with argument(s) of type(s): (array(float64, 1d, C), float64)
 * parameterized
In definition 0:
    All templates rejected with literals.
In definition 1:
    All templates rejected without literals.
In definition 2:
    All templates rejected with literals.
In definition 3:
    All templates rejected without literals.
In definition 4:
    All templates rejected with literals.
In definition 5:
    All templates rejected without literals.
In definition 6:
    All templates rejected with literals.
In definition 7:
    All templates rejected without literals.
In definition 8:
    All templates rejected with literals.
In definition 9:
    All templates rejected without literals.
In definition 10:
    All templates rejected with literals.
In definition 11:
    All templates rejected without literals.
In definition 12:
    TypeError: unsupported array index type float64 in [float64]
    raised from C:\ProgramData\Anaconda3\lib\site-packages\numba\core\typing\arraydecl.py:69
In definition 13:
    TypeError: unsupported array index type float64 in [float64]
    raised from C:\ProgramData\Anaconda3\lib\site-packages\numba\core\typing\arraydecl.py:69
In definition 14:
    All templates rejected with literals.
In definition 15:
    All templates rejected without literals.
This error is usually caused by passing an argument of a type that is unsupported by the named function.
[1] During: typing of intrinsic-call at C:\ProgramData\Anaconda3\lib\site-packages\vectorbt\timeseries\nb.py (373)

File "..\..\ProgramData\Anaconda3\lib\site-packages\vectorbt\timeseries\nb.py", line 373:
def rolling_mean_1d_nb(a, window, minp=None):
    <source elided>
        else:
            window_len = window - (nancnt - nancnt_arr[i-window])
            ^

[1] During: resolving callee type: type(CPUDispatcher(<function rolling_mean_1d_nb at 0x0000014CA5F82DC8>))
[2] During: typing of call at C:\ProgramData\Anaconda3\lib\site-packages\vectorbt\timeseries\nb.py (387)

[3] During: resolving callee type: type(CPUDispatcher(<function rolling_mean_1d_nb at 0x0000014CA5F82DC8>))
[4] During: typing of call at C:\ProgramData\Anaconda3\lib\site-packages\vectorbt\timeseries\nb.py (387)

File "..\..\ProgramData\Anaconda3\lib\site-packages\vectorbt\timeseries\nb.py", line 387:
def rolling_mean_nb(a, window, minp=None):
    <source elided>
    for col in range(a.shape[1]):
        result[:, col] = rolling_mean_1d_nb(a[:, col], window, minp=minp)
        ^

[1] During: resolving callee type: type(CPUDispatcher(<function rolling_mean_nb at 0x0000014CA5F8A558>))
[2] During: typing of call at C:\ProgramData\Anaconda3\lib\site-packages\vectorbt\indicators\indicators.py (44)

[3] During: resolving callee type: type(CPUDispatcher(<function rolling_mean_nb at 0x0000014CA5F8A558>))
[4] During: typing of call at C:\ProgramData\Anaconda3\lib\site-packages\vectorbt\indicators\indicators.py (44)

[5] During: resolving callee type: type(CPUDispatcher(<function rolling_mean_nb at 0x0000014CA5F8A558>))
[6] During: typing of call at C:\ProgramData\Anaconda3\lib\site-packages\vectorbt\indicators\indicators.py (44)

File "..\..\ProgramData\Anaconda3\lib\site-packages\vectorbt\indicators\indicators.py", line 44:
def ma_caching_nb(ts, windows, ewms):
    <source elided>
            else:
                ma = timeseries.nb.rolling_mean_nb(ts, windows[i], minp=windows[i])
                ^

when I try to execute: fast_ma, slow_ma = vbt.MA.from_combinations(price, windows, 2) from the sample code from the readme.

[MislavSag]

Numba version: numba 0.49.1 pypi_0 pypi

[polakowo]

It's getting weirder. Can you try windows = windows.astype(np.int32)

[MislavSag]

I change it:

import vectorbt as vbt
import numpy as np
import yfinance as yf

# Define params
windows = np.arange(2, 101)
windows = windows.astype(np.int32)
investment = 100 # in $
commission = 0.001 # in %

# Prepare data
ticker = yf.Ticker("BTC-USD")
price = ticker.history(period="max")['Close']

fast_ma, slow_ma = vbt.MA.from_combinations(price, windows, 2)

and now it returns:

---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
<ipython-input-10-18625ececc3b> in <module>
     13 price = ticker.history(period="max")['Close']
     14 
---> 15 fast_ma, slow_ma = vbt.MA.from_combinations(price, windows, 2)

C:\ProgramData\Anaconda3\lib\site-packages\vectorbt\indicators\indicators.py in from_combinations(cls, ts, windows, r, ewm, names, **kwargs)
    208         for i, param_list in enumerate(param_lists):
    209             i_windows, i_ewm = zip(*param_list)
--> 210             mas.append(cls.from_params(ts, i_windows, ewm=i_ewm, cache=cache_dict, name=names[i], **kwargs))
    211         return tuple(mas)
    212 

C:\ProgramData\Anaconda3\lib\site-packages\vectorbt\indicators\indicators.py in from_params(cls, ts, window, ewm, **kwargs)
     99             ```
    100         """
--> 101         return super().from_params(ts, window, ewm, **kwargs)
    102 
    103     @classmethod

C:\ProgramData\Anaconda3\lib\site-packages\vectorbt\indicators\factory.py in from_params(cls, name, return_raw, pipeline_kwargs, *args, **kwargs)
    611             results = from_params_pipeline(
    612                 ts_list, param_list, level_names, len(output_names),
--> 613                 custom_func, *new_args, return_raw=return_raw, **kwargs)
    614             if return_raw or kwargs.get('return_cache', False):
    615                 return results

C:\ProgramData\Anaconda3\lib\site-packages\vectorbt\indicators\factory.py in from_params_pipeline(ts_list, param_list, level_names, num_outputs, custom_func, pass_lists, pass_2d, param_product, broadcast_kwargs, return_raw, *args, **kwargs)
    409         array_list = tuple(map(lambda x: np.asarray(x), ts_list))
    410     if pass_lists:
--> 411         output_list = custom_func(array_list, param_list, *args, **kwargs)
    412     else:
    413         output_list = custom_func(*array_list, *param_list, *args, **kwargs)

C:\ProgramData\Anaconda3\lib\site-packages\vectorbt\indicators\factory.py in custom_func(ts_arr_list, param_list, return_cache, cache, *args)
    793                     typed_param_tuples,
    794                     *args,
--> 795                     *cache)
    796         else:
    797             if num_outputs > 1:

C:\ProgramData\Anaconda3\lib\site-packages\numba\typed\dictobject.py in impl()
    731         ix, val = _dict_lookup(d, castedkey, hash(castedkey))
    732         if ix == DKIX.EMPTY:
--> 733             raise KeyError()
    734         elif ix < DKIX.EMPTY:
    735             raise AssertionError("internal dict error during lookup")

KeyError: 

[polakowo]

That's a bit better. Can you run this after importing all the other stuff:

import itertools

def from_combinations(ts, windows, r, ewm=False, names=None, **kwargs):
    if names is None:
        names = ['ma' + str(i+1) for i in range(r)]
    print(windows.dtype)
    windows, ewm = vbt.utils.reshape_fns.broadcast(windows, ewm, writeable=True)
    print(windows.dtype)
    cache_dict = vbt.MA.from_params(ts, windows, ewm=ewm, return_cache=True, **kwargs)
    param_lists = zip(*itertools.combinations(zip(windows, ewm), r))
    mas = []
    for i, param_list in enumerate(param_lists):
        i_windows, i_ewm = zip(*param_list)
        print(np.asarray(i_windows).dtype)
        mas.append(vbt.MA.from_params(ts, i_windows, ewm=i_ewm, cache=cache_dict, name=names[i], **kwargs))
    return tuple(mas)

from_combinations(price, windows, 2)

[MislavSag]

Code:

import vectorbt as vbt
import numpy as np
import yfinance as yf

# Define params
windows = np.arange(2, 101)
windows = windows.astype(np.int32)
investment = 100 # in $
commission = 0.001 # in %

# Prepare data
ticker = yf.Ticker("BTC-USD")
price = ticker.history(period="max")['Close']

import itertools

def from_combinations(ts, windows, r, ewm=False, names=None, **kwargs):
    if names is None:
        names = ['ma' + str(i+1) for i in range(r)]
    print(windows.dtype)
    windows, ewm = vbt.utils.reshape_fns.broadcast(windows, ewm, writeable=True)
    print(windows.dtype)
    cache_dict = vbt.MA.from_params(ts, windows, ewm=ewm, return_cache=True, **kwargs)
    param_lists = zip(*itertools.combinations(zip(windows, ewm), r))
    mas = []
    for i, param_list in enumerate(param_lists):
        i_windows, i_ewm = zip(*param_list)
        print(np.asarray(i_windows).dtype)
        mas.append(vbt.MA.from_params(ts, i_windows, ewm=i_ewm, cache=cache_dict, name=names[i], **kwargs))
    return tuple(mas)

from_combinations(price, windows, 2)

Error:

int32
int32
int32

---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
<ipython-input-13-d2cd9b19a7d9> in <module>
     30     return tuple(mas)
     31 
---> 32 from_combinations(price, windows, 2)

<ipython-input-13-d2cd9b19a7d9> in from_combinations(ts, windows, r, ewm, names, **kwargs)
     27         i_windows, i_ewm = zip(*param_list)
     28         print(np.asarray(i_windows).dtype)
---> 29         mas.append(vbt.MA.from_params(ts, i_windows, ewm=i_ewm, cache=cache_dict, name=names[i], **kwargs))
     30     return tuple(mas)
     31 

C:\ProgramData\Anaconda3\lib\site-packages\vectorbt\indicators\indicators.py in from_params(cls, ts, window, ewm, **kwargs)
     99             ```
    100         """
--> 101         return super().from_params(ts, window, ewm, **kwargs)
    102 
    103     @classmethod

C:\ProgramData\Anaconda3\lib\site-packages\vectorbt\indicators\factory.py in from_params(cls, name, return_raw, pipeline_kwargs, *args, **kwargs)
    611             results = from_params_pipeline(
    612                 ts_list, param_list, level_names, len(output_names),
--> 613                 custom_func, *new_args, return_raw=return_raw, **kwargs)
    614             if return_raw or kwargs.get('return_cache', False):
    615                 return results

C:\ProgramData\Anaconda3\lib\site-packages\vectorbt\indicators\factory.py in from_params_pipeline(ts_list, param_list, level_names, num_outputs, custom_func, pass_lists, pass_2d, param_product, broadcast_kwargs, return_raw, *args, **kwargs)
    409         array_list = tuple(map(lambda x: np.asarray(x), ts_list))
    410     if pass_lists:
--> 411         output_list = custom_func(array_list, param_list, *args, **kwargs)
    412     else:
    413         output_list = custom_func(*array_list, *param_list, *args, **kwargs)

C:\ProgramData\Anaconda3\lib\site-packages\vectorbt\indicators\factory.py in custom_func(ts_arr_list, param_list, return_cache, cache, *args)
    793                     typed_param_tuples,
    794                     *args,
--> 795                     *cache)
    796         else:
    797             if num_outputs > 1:

C:\ProgramData\Anaconda3\lib\site-packages\numba\typed\dictobject.py in impl()
    731         ix, val = _dict_lookup(d, castedkey, hash(castedkey))
    732         if ix == DKIX.EMPTY:
--> 733             raise KeyError()
    734         elif ix < DKIX.EMPTY:
    735             raise AssertionError("internal dict error during lookup")

KeyError: 

[polakowo]

And this?

import itertools

def from_combinations(ts, windows, r, ewm=False, names=None, **kwargs):
    if names is None:
        names = ['ma' + str(i+1) for i in range(r)]
    windows, ewm = vbt.utils.reshape_fns.broadcast(windows, ewm, writeable=True)
    cache_dict = vbt.MA.from_params(ts, windows, ewm=ewm, return_cache=True, **kwargs)
    print(cache_dict)
    param_lists = zip(*itertools.combinations(zip(windows, ewm), r))
    mas = []
    for i, param_list in enumerate(param_lists):
        i_windows, i_ewm = zip(*param_list)
        print(i_windows)
        print(i_ewm)
        mas.append(vbt.MA.from_params(ts, i_windows, ewm=i_ewm, cache=cache_dict, name=names[i], **kwargs))
    return tuple(mas)

from_combinations(price, np.arange(1, 5), 2)

[MislavSag]

After change:

KeyError                                  Traceback (most recent call last)
<ipython-input-14-6b500a098cf6> in <module>
     30     return tuple(mas)
     31 
---> 32 from_combinations(price, np.arange(1, 5), 2)

<ipython-input-14-6b500a098cf6> in from_combinations(ts, windows, r, ewm, names, **kwargs)
     20     windows, ewm = vbt.utils.reshape_fns.broadcast(windows, ewm, writeable=True)
     21     cache_dict = vbt.MA.from_params(ts, windows, ewm=ewm, return_cache=True, **kwargs)
---> 22     print(cache_dict)
     23     param_lists = zip(*itertools.combinations(zip(windows, ewm), r))
     24     mas = []

C:\ProgramData\Anaconda3\lib\site-packages\numba\typed\typeddict.py in __str__(self)
    181     def __str__(self):
    182         buf = []
--> 183         for k, v in self.items():
    184             buf.append("{}: {}".format(k, v))
    185         return '{{{0}}}'.format(', '.join(buf))

C:\ProgramData\Anaconda3\lib\_collections_abc.py in __iter__(self)
    742     def __iter__(self):
    743         for key in self._mapping:
--> 744             yield (key, self._mapping[key])
    745 
    746 ItemsView.register(dict_items)

C:\ProgramData\Anaconda3\lib\site-packages\numba\typed\typeddict.py in __getitem__(self, key)
    149             raise KeyError(key)
    150         else:
--> 151             return _getitem(self, key)
    152 
    153     def __setitem__(self, key, value):

C:\ProgramData\Anaconda3\lib\site-packages\numba\typed\dictobject.py in impl()
    731         ix, val = _dict_lookup(d, castedkey, hash(castedkey))
    732         if ix == DKIX.EMPTY:
--> 733             raise KeyError()
    734         elif ix < DKIX.EMPTY:
    735             raise AssertionError("internal dict error during lookup")

KeyError: 

Plus warning:

C:\ProgramData\Anaconda3\lib\site-packages\numba\typed\typeddict.py:39: NumbaTypeSafetyWarning:

unsafe cast from UniTuple(int64 x 2) to Tuple(int32, int64). Precision may be lost.

[polakowo]

I guess I know where the error is coming from. Can you try whether the following code will succeed and what's your output?

from numba import njit
from vectorbt import timeseries

@njit
def ma_caching_nb(ts, windows, ewms):
    """Numba-compiled caching function for `MA`."""
    cache_dict = dict()

    for i in range(windows.shape[0]):
        h = hash((windows[i], ewms[i]))
        if h not in cache_dict:
            if ewms[i]:
                ma = timeseries.nb.ewm_mean_nb(ts, windows[i], minp=windows[i])
            else:
                ma = timeseries.nb.rolling_mean_nb(ts, windows[i], minp=windows[i])
            cache_dict[h] = ma
    return cache_dict

print(ma_caching_nb(price.vbt.to_2d_array(), np.asarray([1, 2, 3, 3]), np.asarray([True, False, False, False])))

[MislavSag]

That code works. Here is the output:

{3713081631935493181: [[ 457.33]
 [ 424.44]
 [ 394.8 ]
 ...
 [9593.9 ]
 [8756.43]
 [8791.9 ]], 3713082714464823281: [[     nan]
 [ 440.885]
 [ 409.62 ]
 ...
 [9718.285]
 [9175.165]
 [8774.165]], 3713083796993070856: [[          nan]
 [          nan]
 [ 425.52333333]
 ...
 [9796.03      ]
 [9397.66666667]
 [9047.41      ]]}

[polakowo]

The fix is now on master branch. You can reinstall vectorbt completely and try again. Hopefully it works now.

[MislavSag]

I can reproduce a readme example now. I think this can be closed. great work.

[polakowo]

Finally, great!