I’m currently using a Python library called “scoringrules” to calculate energy and variogram scores for multivariate forecasts. It serves similar purposes as the scoringRules library in R.

I ran into an array shape problem even though my arrays both have shapes (1, 24).

So I went back to the github page for a test code and I’m facing a similar issue with the test code provided by the original author. The code was run as provided on the github page.

import numpy as np
    import pytest
    from scoringrules._energy import energy_score
    from scoringrules.backend import backends
    # Define the backends you want to test
    RUN_TESTS = ["numba", "jax"]
    # Filter available backends based on RUN_TESTS
    BACKENDS = [b for b in backends.available_backends if b in 
    RUN_TESTS]
   # Register the filtered backends
   for backend in RUN_TESTS:
        backends.register_backend(backend)
    ENSEMBLE_SIZE = 51
    N = 100
    N_VARS = 3
    @pytest.mark.parametrize("backend", BACKENDS)
    def test_energy_score(backend):
        obs = np.random.randn(N, N_VARS)
        fct = np.expand_dims(obs, axis=-2) + np.random.randn(N, 
     ENSEMBLE_SIZE, N_VARS)
        res = energy_score(obs, fct, backend=backend)
        if backend in ["numpy", "numba"]:
            assert isinstance(res, np.ndarray)
        elif backend == "jax":
            assert isinstance(res, jax.Array)
        
    x = test_energy_score(backend)
    print(x)
    print(x.shape)

The test code from the github (https://github.com/frazane/scoringrules/blob/main/tests/test_energy.py) returned this :

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
Cell In[12], line 32
     29     elif backend == "jax":
     30         assert isinstance(res, jax.Array)
---> 32 x = test_energy_score(backend)
     33 print(x)
     34 print(x.shape)

Cell In[12], line 25, in test_energy_score(backend)
     22 obs = np.random.randn(N, N_VARS)
     23 fct = np.expand_dims(obs, axis=-2) + np.random.randn(N, ENSEMBLE_SIZE, N_VARS)
---> 25 res = energy_score(obs, fct, backend=backend)
     27 if backend in ["numpy", "numba"]:
     28     assert isinstance(res, np.ndarray)

File ~anaconda3Libsite-packagesscoringrules_energy.py:52, in energy_score(forecasts, observations, m_axis, v_axis, backend)
     20 r"""Compute the Energy Score for a finite multivariate ensemble.
     21 
     22 The Energy Score is a multivariate scoring rule expressed as
   (...)
     49     The computed Energy Score.
     50 """
     51 backend = backend if backend is not None else backends._active
---> 52 forecasts, observations = multivariate_array_check(
     53     forecasts, observations, m_axis, v_axis, backend=backend
     54 )
     56 if backend == "numba":
     57     return energy._energy_score_gufunc(forecasts, observations)

File ~anaconda3Libsite-packagesscoringrulescoreutils.py:31, in multivariate_array_check(fcts, obs, m_axis, v_axis, backend)
     29 m_axis = m_axis if m_axis >= 0 else fcts.ndim + m_axis
     30 v_axis = v_axis if v_axis >= 0 else fcts.ndim + v_axis
---> 31 _multivariate_shape_compatibility(fcts, obs, m_axis)
     32 return _multivariate_shape_permute(fcts, obs, m_axis, v_axis, backend=backend)

File ~anaconda3Libsite-packagesscoringrulescoreutils.py:12, in _multivariate_shape_compatibility(fcts, obs, m_axis)
     10 o_shape_broadcast = o_shape[:m_axis] + (f_shape[m_axis],) + o_shape[m_axis:]
     11 if o_shape_broadcast != f_shape:
---> 12     raise ValueError(
     13         f"Forecasts shape {f_shape} and observations shape {o_shape} are not compatible for broadcasting!"
     14     )

ValueError: Forecasts shape (100, 3) and observations shape (100, 51, 3) are not compatible for broadcasting!

Tried to : Test a code for calculating energy score of multivariate forecasts. Forecast array was of shape (100,3) and observation array of shape (100, 51, 3). Several other tries were made where forecast and observation arrays were of the same shape but in vain.

Expected result : Energy score array of shape (100, 3)