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Use this parameter to change between the first or last valid index.
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Fills 'yvalues' in-place.
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Convenience function for interpolate.BPoly.from_derivatives.
|
|
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|
with the specified values and derivatives at breakpoints.
|
|
Parameters
|
----------
|
xi : array-like
|
sorted 1D array of x-coordinates
|
yi : array-like or list of array-likes
|
yi[i][j] is the j-th derivative known at xi[i]
|
order: None or int or array-like of ints. Default: None.
|
Specifies the degree of local polynomials. If not None, some
|
derivatives are ignored.
|
der : int or list
|
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.
|
extrapolate : bool, optional
|
Whether to extrapolate to ouf-of-bounds points based on first and last
|
intervals, or to return NaNs. Default: True.
|
|
See Also
|
--------
|
scipy.interpolate.BPoly.from_derivatives
|
|
Returns
|
-------
|
y : scalar or array-like
|
The result, of length R or length M or M by R.
|
r r rY rV )Zordersr )r
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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, 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,
|
|
r r rW )Únu)r
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Convenience function for cubic spline data interpolator.
|
|
See `scipy.interpolate.CubicSpline` for details.
|
|
Parameters
|
----------
|
xi : array-like, shape (n,)
|
1-d array containing values of the independent variable.
|
Values must be real, finite and in strictly increasing order.
|
yi : array-like
|
Array containing values of the dependent variable. It can have
|
arbitrary number of dimensions, but the length along ``axis``
|
(see below) must match the length of ``x``. Values must be finite.
|
x : scalar or array-like, shape (m,)
|
axis : int, optional
|
Axis along which `y` is assumed to be varying. Meaning that for
|
``x[i]`` the corresponding values are ``np.take(y, i, axis=axis)``.
|
Default is 0.
|
bc_type : string or 2-tuple, optional
|
Boundary condition type. Two additional equations, given by the
|
boundary conditions, are required to determine all coefficients of
|
polynomials on each segment [2]_.
|
If `bc_type` is a string, then the specified condition will be applied
|
at both ends of a spline. Available conditions are:
|
* 'not-a-knot' (default): The first and second segment at a curve end
|
are the same polynomial. It is a good default when there is no
|
information on boundary conditions.
|
* 'periodic': The interpolated functions is assumed to be periodic
|
of period ``x[-1] - x[0]``. The first and last value of `y` must be
|
identical: ``y[0] == y[-1]``. This boundary condition will result in
|
``y'[0] == y'[-1]`` and ``y''[0] == y''[-1]``.
|
* 'clamped': The first derivative at curves ends are zero. Assuming
|
a 1D `y`, ``bc_type=((1, 0.0), (1, 0.0))`` is the same condition.
|
* 'natural': The second derivative at curve ends are zero. Assuming
|
a 1D `y`, ``bc_type=((2, 0.0), (2, 0.0))`` is the same condition.
|
If `bc_type` is a 2-tuple, the first and the second value will be
|
applied at the curve start and end respectively. The tuple values can
|
be one of the previously mentioned strings (except 'periodic') or a
|
tuple `(order, deriv_values)` allowing to specify arbitrary
|
derivatives at curve ends:
|
* `order`: the derivative order, 1 or 2.
|
* `deriv_value`: array-like containing derivative values, shape must
|
be the same as `y`, excluding ``axis`` dimension. For example, if
|
`y` is 1D, then `deriv_value` must be a scalar. If `y` is 3D with
|
the shape (n0, n1, n2) and axis=2, then `deriv_value` must be 2D
|
and have the shape (n0, n1).
|
extrapolate : {bool, 'periodic', None}, optional
|
If bool, determines whether to extrapolate to out-of-bounds points
|
based on first and last intervals, or to return NaNs. If 'periodic',
|
periodic extrapolation is used. If None (default), ``extrapolate`` is
|
set to 'periodic' for ``bc_type='periodic'`` and to True otherwise.
|
|
See Also
|
--------
|
scipy.interpolate.CubicHermiteSpline
|
|
Returns
|
-------
|
y : scalar or array-like
|
The result, of shape (m,)
|
|
References
|
----------
|
.. [1] `Cubic Spline Interpolation
|
<https://en.wikiversity.org/wiki/Cubic_Spline_Interpolation>`_
|
on Wikiversity.
|
.. [2] Carl de Boor, "A Practical Guide to Splines", Springer-Verlag, 1978.
|
r r )rX r r )r
r Z CubicSpline)r r r. rX r r r r r r r! r s M ÿr )r< r0 ra rc r$ c C s¨ t | }| }| ¡ s¤t| d|d}|dkr0d}t| d|d}|dkrNt| }t| ||d |dkrvd|||d
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|
Apply interpolation and limit_area logic to values along a to-be-specified axis.
|
|
Parameters
|
----------
|
values: np.ndarray
|
Input array.
|
method: str
|
Interpolation method. Could be "bfill" or "pad"
|
limit: int, optional
|
Index limit on interpolation.
|
limit_area: str
|
Limit area for interpolation. Can be "inside" or "outside"
|
|
Notes
|
-----
|
Modifies values in-place.
|
rS r| Nr rT )r0 ra rm FrV rn )r r} r\ r rg r& r )r< r0 ra rc r rR rS rT r r r! Ú _interpolate_with_limit_areaç s& ý r r )r< r0 rX ra rc r$ c C s¢ |dk r&t tt|||d|| ¡ dS |dkr6dd ndd }| jdkrl|dkrXtd| td | j ¡} t |}|| }|d
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Perform an actual interpolation of values, values will be make 2-d if
|
needed fills inplace, returns the result.
|
|
Parameters
|
----------
|
values: np.ndarray
|
Input array.
|
method: str, default "pad"
|
Interpolation method. Could be "bfill" or "pad"
|
axis: 0 or 1
|
Interpolation axis
|
limit: int, optional
|
Index limit on interpolation.
|
limit_area: str, optional
|
Limit area for interpolation. Can be "inside" or "outside"
|
|
Notes
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-----
|
Modifies values in-place.
|
N)r0 ra rc r c S s | S ©Nr ©r. r r r! Ú<lambda>I ó z interpolate_2d.<locals>.<lambda>c S s | j S r )ÚTr r r r! r I r rV z0cannot interpolate on a ndim == 1 with axis != 0)rV r2 ©ra ) r& rw r r r[ rZ r Útupler) r8 Ú_pad_2dÚ _backfill_2d)r< r0 rX ra rc ZtransfZtvaluesr r r! rg s. üî
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r¤ ©r2 r3 rV )r[ c C s& t | } |dkrt| S ttd| S )NrV r¯ )r8 Ú _fill_methodsr£ r¤ )r0 r[ r r r! Ú get_fill_func® s r± )r$ c C s t | ddS )NT)r1 )r8 )r0 r r r! Úclean_reindex_fill_methodµ s r² )r c s¤ t | t }t } fdd}|dk rN|dkrDtt | ¡d }n
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|
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|
|
Parameters
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invalid : np.ndarray[bool]
|
fw_limit : int or None
|
forward limit to index
|
bw_limit : int or None
|
backward limit to index
|
|
Returns
|
-------
|
set of indexers
|
|
Notes
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-----
|
This is equivalent to the more readable, but slower
|
|
.. code-block:: python
|
|
def _interp_limit(invalid, fw_limit, bw_limit):
|
for x in np.where(invalid)[0]:
|
if invalid[max(0, x - fw_limit):x + bw_limit + 1].all():
|
yield x
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