but they affect lsqfit:
- Function gvar.add_parameter_distribution has been added to allow new
prior distributions, in addition to log-normal and sqrt-normal. This
allows one, for example, to restrict a parameter to a particular
interval (see the Overview section on Non-Gaussian Priors).
- To signal a log-normal prior for a parameter 'c' in nonlinear_fit one must
now include an entry for prior['log(c)'] in the prior. Previously one could
leave out the parentheses in the key, using prior['logc'] instead. The
parenthesis are now essential. The same is true for sqrt-normal priors,
where one would include prior['sqrt(c)'], not prior['sqrtc'].
FIX FOR LEGACY CODE: To help convert legacy code, there is a new utility
function that adds the needed parentheses: use
prior = gvar.add_parameter_parentheses(prior)
to add parentheses to keys in dictionary prior of the form logc or sqrtdd
(which become log(c) or sqrt(dd)) in dictionary prior.
Other changes are behind the scenes: eg, more tests, more examples.