gigablochs.bloch.labelling_efficiency

gigablochs.bloch.labelling_efficiency#

gigablochs.bloch.labelling_efficiency(long_mag_inverted, long_mag_control=1)[source]#

Compute the labeling efficiency from inverted and control longitudinal magnetizations.

Parameters:

  • long_mag_inverted (array_like or float) – Longitudinal magnetization measured in the inverted (label) condition. May be a scalar or an array; if an array, it must be broadcastable with long_mag_control.

  • long_mag_control (array_like or float, optional) – Longitudinal magnetization measured in the control condition (default: 1). May be a scalar or an array; if an array, it must be broadcastable with long_mag_inverted.

Returns:

efficiency – The absolute labeling efficiency computed element-wise as |long_mag_control - long_mag_inverted| / |2 * long_mag_control|. The return has the same shape as the broadcasted inputs. For physically meaningful inputs, values typically lie in [0, 1].

Return type:

float or ndarray

Notes

  • If long_mag_control is zero, the result is undefined (division by zero). When using NumPy, this will produce inf or nan values and may emit a runtime warning.

  • This function does not validate input types beyond relying on NumPy broadcasting semantics; pass numeric scalars or array-like objects.

Examples

>>> labelling_efficiency(0.2)
0.4
>>> labelling_efficiency(np.array([0.9, 0.8, 0, -0.9, -1]))
array([0.05, 0.1, 0.5, 0.95, 1. ])
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