def _fprime(score, x, k_params, alpha):
    x_arr = np.asarray(x)
    params = x_arr[:k_params].ravel()
    # Call the numpy version
    # The derivative just appends a vector of constants
    fprime_arr = np.append(score(params), alpha)
    # Return
    return matrix(fprime_arr, (1, 2 * k_params))
a.hstacked(b) <==> a.stacked(b, axis=-1)
dataset/ETHPy150Open statsmodels/statsmodels/statsmodels/base/l1_cvxopt.py/_fprime--crossover with--dataset/ETHPy150Open CountZer0/PipelineConstructionSet/python/maya/site-packages/pymel-1.0.5/extras/completion/py/pymel/util/arrays.py/Array.hstacked