Version 1.1.1
May 27, 2021
-
Implemented just-in-time (jit) compilation of some of the most time-consuming methods using the
numba
package. Execution time
was shortened by 20 % to 40 %. A new demo program was added to highlight these capabilities.Since
numba
is not (yet) a required package foroptbayesexpt
, access tonumba
is tested and a BooleanGOT_NUMBA
is defined with scope extending over the whole optbayesexpt package.
May 21, 2021
-
Support for multi-channel measurements has been added to the OptBayesExpt class. As a result,
demos/lockin/obe_lockin.py
is no longer needed, and it has been removed. -
Support for noise parameter estimation is provided by a new component of the optbayesespt package,
OptBayesExptNoiseParam
, which takes anoise_parameter_index=(int)
argument to identify a parameter as measurement noise. These demos now useOptBayesExptNoiseParam
.demos/line_plus_noise/line_plus_noise.py
,demos/lockin/lockin_of_coil.py
, anddemos/sweeper/sweeper.py
-
Added support for
**kwargs
arguments to OptBayesExpt. Attribute values for OptBayesExpt, parent class ParticlePDF and OptBayesExpt child classes can now be set at instantiation. Keyword argumentsa_param
,resample_threshold
,auto_resample
andscale
are passed to ParticlePdf to tune resampling behavior.OptBayesExpt
useschoke
, andOptBayesExptNoiseParam
usesnoise_parameter_index
.