Experiments

Tools and classes for managing and analyzing experiment data.

hystorian.experiments.cypher.extract_hysteresis(*chans: list[ndarray[Any, dtype[ScalarType]]], len_bias: int, waveform_pulsetime: int, waveform_dutycycle: float = 0.5, num_pts_per_sec: float) → tuple[ndarray[Any, dtype[ScalarType]]]

extract_hist split data from an SSPFM measurement into part where the bias is off, and the bias is on. Therefore it can be used to build P-E loop.

Parameters:

  • len_bias (int) – len_bias is the lenghth of the bias applied during the SSPF. If the data is from an Asylum ARDF you can find it by, for example, doing f.read(“datasets/…/bias/retrace”)[0,0,:]

  • waveform_pulsetime (int) – The length in time of the pulse. If from Asylum can be found in metadata under name “ARDoIVArg3”. f.read(“metadata/…/ArDoIVArg3”)

  • NumPtsPerSec (float) – The number of points per seconds in a pulse. If from Asylum can be computed from the metadata “NumPtsPerSec”: float(f.read(“metadata/…/NumPtsPerSec”))

  • waveform_dutycycle (float, optional) – The length in time of the pulse. If from Asylum can be found in metadata under name “ARDoIVArg4”, by default 0.5 (which is the default value of Asylum)

Returns:

The tuple is twice the size of chans, containing chans[0] ‘on’, chans[0] ‘off’, chans[1] ‘on’, … It splits each channel into on/off where the bias waveform was either 0 (off) or something else (on)

Return type:

tuple[npt.NDArray]