pyinterp.reduced_gaussian.apply

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pyinterp.reduced_gaussian.apply#

pyinterp.reduced_gaussian.apply(source, callback, lon, lat, time=None, *, args=None, fields=None, n_out=None, blend='columns', chunk_size=65536, time_method='linear', interval=None, max_step_gap=None, bounds_error=False, num_threads=0)[source]#

Compute values per point from the interpolated columns of the fields.

The columns are interpolated in C++, in parallel and without the GIL. Two kinds of callbacks consume them:

  • A Python callable, called on blocks of chunk_size points as callback(columns, points, a, b): columns maps each field to its interpolated values (as interpolate() returns them), points holds lon, lat, time (for a series) and the arrays of args, a and b are the hybrid coefficients of the half levels (or None). It returns an array of shape (block,) or (block, n_out). Write it with numpy operations over the block.

  • A ColumnKernel made with column_kernel(): a numba function called for each point from several threads, without the GIL, for computations that do not vectorize over points.

Parameters:

  • source (Grid | Series) – A Grid, or a Series of grids in time.

  • callback (Callable[..., ArrayLike] | ColumnKernel) – The function applied to the columns.

  • lon (ArrayLike) – Longitudes of the points, in degrees.

  • lat (ArrayLike) – Latitudes of the points, in degrees.

  • time (ArrayLike | None) – Dates of the points, required for a series.

  • args (Mapping[str, ArrayLike] | None) – Extra values per point, passed to the callback by name (in this order in the point array of a kernel).

  • fields (Sequence[str] | None) – Names of the fields given to the callback; all by default.

  • n_out (int | None) – Number of values computed per point; by default that of the kernel, or 1.

  • blend (Blend) – For a series, "columns" blends the columns of the two steps then calls the callback once; "results" calls it on the columns of each step and blends its results, which costs twice as much: it interpolates in time the result rather than the fields, which differs for a callback nonlinear in them.

  • chunk_size (int) – Number of points per call of a Python callable.

  • time_method (TimeMethod) – See interpolate().

  • interval (Duration) – See interpolate().

  • max_step_gap (Duration) – See interpolate().

  • bounds_error (bool) – Raise instead of returning NaN for a point that cannot be interpolated, or for which a kernel returns a non-zero code.

  • num_threads (int) – Number of threads; 0 uses all the cores.

Returns:

The values, shape (n,) if n_out is 1, else (n, n_out); NaN where a point cannot be interpolated.

Return type:

NDArray[np.float64]

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