`sm_bluesky.common.math`#

Members

`cal_range_num`	Calculate the start, end and the number of steps for a scan.
`edges_from_centres`	Cell edges halfway between nearest point centres.
`step_size_to_step_num`	Quick conversion to step from step size.
`to_float`	Convert to a finite float, or None if that is not possible.
`binned_axis`	Evenly spaced cells, for an axis that moves continuously (fast scans).
`extract_xyz`	Pull (x, y, z) out of a dictionary of data.
`grid_heatmap`	Bin scattered (x, y, z) points into a NxM matrix for pcolormesh to draw.
`unique_axis`	One cell per distinct position.

sm_bluesky.common.math.cal_range_num(cen: float, range: float, size: float) → tuple[float, float, int][source]#: Calculate the start, end and the number of steps for a scan.

sm_bluesky.common.math.edges_from_centres(centres: list[float]) → list[float][source]#: Cell edges halfway between nearest point centres.

sm_bluesky.common.math.step_size_to_step_num(start: float, end: float, step_size: float) → int[source]#

Quick conversion to step from step size.

Parameters:

Returns:

Number of steps.

Return type:

int

sm_bluesky.common.math.to_float(value: Any) → float | None[source]#: Convert to a finite float, or None if that is not possible.

sm_bluesky.common.math.binned_axis(values: list[float], n_bins: int) → tuple[list[float], list[int]][source]#: Evenly spaced cells, for an axis that moves continuously (fast scans).

sm_bluesky.common.math.extract_xyz(scan_data: dict[str, list[Any]], x_field: str | None, y_field: str | None, z_field: str | None) → tuple[list[float], list[float], list[float]][source]#: Pull (x, y, z) out of a dictionary of data.

sm_bluesky.common.math.grid_heatmap(xs: list[float], ys: list[float], zs: list[float]) → tuple[list[float], list[float], Any] | None[source]#: Bin scattered (x, y, z) points into a NxM matrix for pcolormesh to draw.

sm_bluesky.common.math.unique_axis(values: list[float]) → tuple[list[float], list[int]][source]#: One cell per distinct position.

sm_bluesky.common.math#