Example #1
0
def newton_laurent_step(system, solutions, precision='d', decimals=100):
    """
    Applies one Newton step to the solutions of the Laurent system.
    For each solution, prints its last line of diagnostics.
    Four levels of precision are supported:
    d  : standard double precision (1.1e-15 or 2^(-53)),
    dd : double double precision (4.9e-32 or 2^(-104)),
    qd : quad double precision (1.2e-63 or 2^(-209)).
    mp : arbitrary precision, where the number of decimal places
    in the working precision is determined by decimals.
    """
    if(precision == 'd'):
        from interface import store_standard_laurent_system
        from interface import store_standard_solutions, load_standard_solutions
        store_standard_laurent_system(system)
        store_standard_solutions(len(system), solutions)
        from phcpy.phcpy2c2 import py2c_standard_Newton_Laurent_step
        py2c_standard_Newton_Laurent_step()
        result = load_standard_solutions()
    elif(precision == 'dd'):
        from interface import store_dobldobl_laurent_system
        from interface import store_dobldobl_solutions, load_dobldobl_solutions
        store_dobldobl_laurent_system(system)
        store_dobldobl_solutions(len(system), solutions)
        from phcpy.phcpy2c2 import py2c_dobldobl_Newton_Laurent_step
        py2c_dobldobl_Newton_Laurent_step()
        result = load_dobldobl_solutions()
    elif(precision == 'qd'):
        from interface import store_quaddobl_laurent_system
        from interface import store_quaddobl_solutions, load_quaddobl_solutions
        store_quaddobl_laurent_system(system)
        store_quaddobl_solutions(len(system), solutions)
        from phcpy.phcpy2c2 import py2c_quaddobl_Newton_Laurent_step
        py2c_quaddobl_Newton_Laurent_step()
        result = load_quaddobl_solutions()
    elif(precision == 'mp'):
        from interface import store_multprec_laurent_system
        from interface import store_multprec_solutions, load_multprec_solutions
        store_multprec_laurent_system(system, decimals)
        store_multprec_solutions(len(system), solutions)
        from phcpy.phcpy2c2 import py2c_multprec_Newton_Laurent_step
        py2c_multprec_Newton_Laurent_step(decimals)
        result = load_multprec_solutions()
    else:
        print 'wrong argument for precision'
        return None
    for sol in result:
        strsol = sol.split('\n')
        print strsol[-1]
    return result
Example #2
0
def mixed_volume(pols, stable=False):
    """
    Given in pols a list of string representations of polynomials,
    this function returns the mixed volume of the system.
    This is an interface to Algorithm 846: MixedVol of ACM TOMS,
    developed by Tangan Gao, T.Y. Li, Mengnien Wu, and Li Xing.
    If the option stable is set to True, then on return is a tuple
    containing the mixed volume and the stable mixed volume.
    The mixed volume counts the solutions with all their coordinates
    nonzero, the stable mixed volume counts all affine roots.
    Note that the stable mixed volume does not apply to systems
    with negative exponents.
    Incorrectly parsed strings will result in a negative value on return.
    """
    from phcpy.phcpy2c2 import py2c_celcon_clear_container
    from phcpy.phcpy2c2 import py2c_mixed_volume
    from phcpy.interface import store_standard_system
    from phcpy.interface import store_standard_laurent_system
    py2c_celcon_clear_container()
    if stable:
        fail = store_standard_system(pols)
    else:
        fail = store_standard_laurent_system(pols)
    if(fail != 0):
        return -fail  # a negative number is clearly wrong
    else:
        return py2c_mixed_volume(stable)