Version 1.2.2 Release Notes (July 14, 2023)

New features:

• add ModelResult.uvars output to a ModelResult after a successful fit
  that contains ufloats from the uncertainties package which can be
  used for downstream calculations that propagate the uncertainties (and
  correlations) of the variable Parameters. (PR #888)

• Outputs of residual functions, including Model._residual, are more
  explicitly coerced to 1d-arrays of dataype Float64. This decreases the
  expectation for the user-supplied code to return ndarrays, and increases the
  tolerance for more "array-like" objects or ndarrays that are not Float64 or
  1-dimensional. (PR #899)

• Model.fit now takes a coerce_farray option, defaulting to True to
  control whether to input data and independent variables that are "array-like"
  are coerced to ndarrays of datatype Float64 or Complex128. If set to
  False then independent data that "array-like" (pandas.Series, int32
  arrays, etc) will be sent to the model function unaltered. The user may then
  use other features of these objects, but may also need to explicitly coerce
  the datatype of the result the change described above about coercing the
  result causes problems. (Discussion #873; PR #899)

Bug fixes/enhancements:

• fixed bug in Model.make_params() for non-composite models that use a
  prefix (Discussion #892; Issue #893; PR #895)

• fixed bug with aborted fits for several methods having incorrect or invalid
  fit statistics. (Discussion #894; Issue #896; PR #897)

• Model.eval_uncertainty now correctly calculates complex (real/imaginary pairs)
  uncertainties for Models that generate complex results. (Issue #900; PR #901)

• Model.eval now returns and array-like value. This adds to the coercion
  features above and fixes a bug for composite models that return lists (Issue #875; PR #901)

• the HTML representation for a ModelResult or MinimizerResult are
  improved, and create fewer entries in the Table of Contents for Jupyter lab.
  (Issue #884; PR #883; PR #902)