triplet_formats.py example does not work

[sherbold]

I failed to run the triplet_format example. Here is the stacktrace:

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
Cell In[1], line 62
     58 data = [triplets_ordered, (triplets_boolean, answers_boolean),
     59         (triplets_numeric, answers_numeric), triplet_spmatrix]
     60 formats = ["list-order", "list-boolean", "list-count", "tensor-count"]
---> 62 timings = [
     63     (time_convert_triplet(triplets, to_format),
     64      f"{from_format}->{to_format}")
     65     for from_format, triplets in zip(formats, data)
     66     for to_format in formats
     67 ]
     69 for seconds, desc in sorted(timings):
     70     print(f"{seconds * 1000:.2f}ms {desc}")

Cell In[1], line 63, in <listcomp>(.0)
     58 data = [triplets_ordered, (triplets_boolean, answers_boolean),
     59         (triplets_numeric, answers_numeric), triplet_spmatrix]
     60 formats = ["list-order", "list-boolean", "list-count", "tensor-count"]
     62 timings = [
---> 63     (time_convert_triplet(triplets, to_format),
     64      f"{from_format}->{to_format}")
     65     for from_format, triplets in zip(formats, data)
     66     for to_format in formats
     67 ]
     69 for seconds, desc in sorted(timings):
     70     print(f"{seconds * 1000:.2f}ms {desc}")

Cell In[1], line 54, in time_convert_triplet(triplets, to_format)
     52 def time_convert_triplet(triplets, to_format):
     53     time_start = time.process_time()
---> 54     check_query_response(triplets, result_format=to_format)
     55     return (time.process_time() - time_start)

File ~/test/cblearn/cblearn/utils/_validate_data.py:292, in check_query_response(query, response, result_format, standard)
    290     query = check_tensor_query_response(query, (QueryFormat.TENSOR, input_response_format), standard=False)
    291     query, response = query.coords.T, query.data
--> 292 return check_list_query_response(query, response, (output_query_format, output_response_format),
    293                                  standard=standard)

File ~/test/cblearn/cblearn/utils/_validate_data.py:135, in check_list_query_response(query, response, result_format, standard)
    132     raise ValueError(f"Expects result_format list-..., got {result_format}.")
    134 if response_format is ResponseFormat.ORDER:
--> 135     return check_order_list_query_response(query, response)
    136 elif response_format is ResponseFormat.BOOLEAN:
    137     return check_bool_list_query_response(query, response, standard=standard)

File ~/test/cblearn/cblearn/utils/_validate_data.py:96, in check_order_list_query_response(query, response)
     95 def check_order_list_query_response(query, response):
---> 96     query, response = _check_list_query_response(query, response)
     97     __, input_response_format = data_format(query, response)
     99     if input_response_format is ResponseFormat.COUNT:

File ~/test/cblearn/cblearn/utils/_validate_data.py:15, in _check_list_query_response(query, response)
     13 def _check_list_query_response(query, response):
     14     if response is None:
---> 15         return check_array(query, dtype=np.uint32), None
     16     else:
     17         return check_X_y(query, response, dtype=np.uint32)

File ~/test/cblearn/venv/lib/python3.10/site-packages/sklearn/utils/validation.py:904, in check_array(array, accept_sparse, accept_large_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, estimator, input_name)
    899 warnings.simplefilter("error", ComplexWarning)
    900 if dtype is not None and xp.isdtype(dtype, "integral"):
    901     # Conversion float -> int should not contain NaN or
    902     # inf (numpy#14412). We cannot use casting='safe' because
    903     # then conversion float -> int would be disallowed.
--> 904     array = _asarray_with_order(array, order=order, xp=xp)
    905     if xp.isdtype(array.dtype, ("real floating", "complex floating")):
    906         _assert_all_finite(
    907             array,
    908             allow_nan=False,
   (...)
    911             input_name=input_name,
    912         )

File ~/test/cblearn/venv/lib/python3.10/site-packages/sklearn/utils/_array_api.py:380, in _asarray_with_order(array, dtype, order, copy, xp)
    378     array = numpy.array(array, order=order, dtype=dtype)
    379 else:
--> 380     array = numpy.asarray(array, order=order, dtype=dtype)
    382 # At this point array is a NumPy ndarray. We convert it to an array
    383 # container that is consistent with the input's namespace.
    384 return xp.asarray(array)

ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 2 dimensions. The detected shape was (2, 1000000) + inhomogeneous part.

Run with Ubuntu 22.10, Python 3.10, based on latest version from repo installed following contributor instructions.

(cc openjournals/joss-reviews#6139)

[haniyeka]

I get the same error with python 3.9 and Ubuntu 22.04.3.

(cc openjournals/joss-reviews#6139)

[dekuenstle]

Should be fixed now in the latest release:
https://github.com/cblearn/cblearn/releases/tag/0.2.0