lmfit/lmfit-py: 1.2.0

New features: add create_params function (PR #844) add chi2_out and nsigma options to conf_interval2d() add ModelResult.summary() to return many resulting fit statistics and attributes into a JSON-able dict. add correl_table() function to lmfit.printfuncs and correl_mode option to fit_report() and ModelResult.fit_report() to optionally display a RST-formatted table of a correlation matrix. Bug fixes/enhancements: fix bug when setting param.vary=True for a constrained parameter (Issue #859; PR #860) fix bug in reported uncertainties for constrained parameters by better propating uncertainties (Issue #855; PR #856) Coercing of user input data and independent data for Model to float64 ndarrays is somewhat less aggressive and will not increase the precision of numpy ndarrays (see :ref:model_data_coercion_section for details). The resulting calculation from a model or objective function is more aggressively coerced to float64. (Issue #850; PR #853) the default value of epsfcn is increased to 1.e-10 to allow for handling of data with precision less than float64 (Issue #850; PR #853) fix conf_interval2d to use "increase chi-square by sigma*2reduced chi-square" to give the sigma-level probabilities (Issue #848; PR #852) fix reading of older ModelResult (Issue #845; included in PR #844) fix deepcopy of Parameters and user data (mguhyo; PR #837) improve Model.make_params and create_params to take optional dict of Parameter attributes (PR #844) fix reporting of nfev from least_squares to better reflect actual number of function calls (Issue #842; PR #844) fix bug in Model.eval when mixing parameters and keyword arguments (PR #844, #839) re-adds residual to saved Model result (PR #844, #830) ConstantModel and ComplexConstantModel will return an ndarray of the same shape as the independent variable x (JeppeKlitgaard, Issue #840; PR #841) update tests for latest versions of NumPy and SciPy. many fixes of doc typos and updates of dependencies, pre-commit hooks, and CI