Python interpolate.Akima1DInterpolator方法代码示例

# 需要导入模块: from scipy import interpolate [as 别名]
# 或者: from scipy.interpolate import Akima1DInterpolator [as 别名]
def compute_cdf_percentiles(fit, cdf_sigmas=CDF_SIGMAS):
    """
    Compute tabulated percentiles of the PDF
    """
    from scipy.interpolate import Akima1DInterpolator
    from scipy.integrate import cumtrapz
    import scipy.stats

    if cdf_sigmas is None:
        cdf_sigmas = CDF_SIGMAS

    cdf_y = scipy.stats.norm.cdf(cdf_sigmas)

    if len(fit['zgrid']) == 1:
        return np.ones_like(cdf_y)*fit['zgrid'][0], cdf_y

    spl = Akima1DInterpolator(fit['zgrid'], np.log(fit['pdf']), axis=1)
    zrfine = [fit['zgrid'].min(), fit['zgrid'].max()]
    zfine = utils.log_zgrid(zr=zrfine, dz=0.0001)
    ok = np.isfinite(spl(zfine))
    pz_fine = np.exp(spl(zfine))
    pz_fine[~ok] = 0

    cdf_fine = cumtrapz(pz_fine, x=zfine)
    cdf_x = np.interp(cdf_y, cdf_fine/cdf_fine[-1], zfine[1:])

    return cdf_x, cdf_y 

# 需要导入模块: from scipy import interpolate [as 别名]
# 或者: from scipy.interpolate import Akima1DInterpolator [as 别名]
def _akima_interpolate(xi, yi, x, der=0, axis=0):
    """
    Convenience function for akima interpolation.
    xi and yi are arrays of values used to approximate some function f,
    with ``yi = f(xi)``.

    See `Akima1DInterpolator` for details.

    Parameters
    ----------
    xi : array_like
        A sorted list of x-coordinates, of length N.
    yi :  array_like
        A 1-D array of real values.  `yi`'s length along the interpolation
        axis must be equal to the length of `xi`. If N-D array, use axis
        parameter to select correct axis.
    x : scalar or array_like
        Of length M.
    der : int or list, optional
        How many derivatives to extract; None for all potentially
        nonzero derivatives (that is a number equal to the number
        of points), or a list of derivatives to extract. This number
        includes the function value as 0th derivative.
    axis : int, optional
        Axis in the yi array corresponding to the x-coordinate values.

    See Also
    --------
    scipy.interpolate.Akima1DInterpolator

    Returns
    -------
    y : scalar or array_like
        The result, of length R or length M or M by R,

    """
    from scipy import interpolate
    try:
        P = interpolate.Akima1DInterpolator(xi, yi, axis=axis)
    except TypeError:
        # Scipy earlier than 0.17.0 missing axis
        P = interpolate.Akima1DInterpolator(xi, yi)
    if der == 0:
        return P(x)
    elif interpolate._isscalar(der):
        return P(x, der=der)
    else:
        return [P(x, nu) for nu in der] 

# 需要导入模块: from scipy import interpolate [as 别名]
# 或者: from scipy.interpolate import Akima1DInterpolator [as 别名]
def setup(self):
        num_nodes = self.options['num_nodes']

        # Inputs
        self.add_input('I_Li', val=np.ones(num_nodes), units='A',
                       desc='Current demanded per cell')

        # State Variables
        self.add_input('SOC', val=np.ones(num_nodes), units=None, desc='State of charge')

        # Outputs
        self.add_output('V_L',
                        val=np.ones(num_nodes),
                        units='V',
                        desc='Terminal voltage of the battery')

        self.add_output('dXdt:SOC',
                        val=np.ones(num_nodes),
                        units='1/s',
                        desc='Time derivative of state of charge')

        self.add_output('V_oc', val=np.ones(num_nodes), units='V',
                        desc='Open Circuit Voltage')
        self.add_output('I_pack', val=0.1*np.ones(num_nodes), units='A',
                        desc='Total Pack Current')
        self.add_output('V_pack', val=9.0*np.ones(num_nodes), units='V',
                        desc='Total Pack Voltage')
        self.add_output('P_pack', val=1.0*np.ones(num_nodes), units='W',
                        desc='Total Pack Power')

        # Derivatives
        row_col = np.arange(num_nodes)

        self.declare_partials(of='V_oc', wrt=['SOC'], rows=row_col, cols=row_col)
        self.declare_partials(of='V_L', wrt=['SOC'], rows=row_col, cols=row_col)
        self.declare_partials(of='V_L', wrt=['I_Li'], rows=row_col, cols=row_col)
        self.declare_partials(of='dXdt:SOC', wrt=['I_Li'], rows=row_col, cols=row_col)
        self.declare_partials(of='I_pack', wrt=['I_Li'], rows=row_col, cols=row_col)
        self.declare_partials(of='V_pack', wrt=['SOC', 'I_Li'], rows=row_col, cols=row_col)
        self.declare_partials(of='P_pack', wrt=['SOC', 'I_Li'], rows=row_col, cols=row_col)

        self.voltage_model = Akima1DInterpolator(train_SOC, train_V_oc)
        self.voltage_model_derivative = self.voltage_model.derivative()