Python scipy.interpolate._isscalar() Examples

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Example #1
Source File: missing.py    From recruit with Apache License 2.0 4 votes vote down vote up
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] 
Example #2
Source File: missing.py    From vnpy_crypto with MIT License 4 votes vote down vote up
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] 
Example #3
Source File: missing.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 4 votes vote down vote up
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] 
Example #4
Source File: missing.py    From Splunking-Crime with GNU Affero General Public License v3.0 4 votes vote down vote up
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] 
Example #5
Source File: missing.py    From elasticintel with GNU General Public License v3.0 4 votes vote down vote up
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]