def wronskian(functions, var, method='bareis'):
    from .dense import Matrix

    for index in range(0, len(functions)):
        functions[index] = sympify(functions[index])
    n = len(functions)
    if n == 0:
        return 1
    W = Matrix(n, n, lambda i, j: functions[i].diff(var, j))
    return W.det(method)
Download most recent pricing information from GCE and save locally
dataset/ETHPy150Open sympy/sympy/sympy/matrices/dense.py/wronskian--crossover with--dataset/ETHPy150Open saltstack/salt/salt/cloud/clouds/gce.py/update_pricing