Distfit

* Check whether matplotlib version >= 3.5.2 is installed

* Change title in `plot_summary(title='new new title')`
*

* Fix for ylim in plot_summary
* multtest can be set in the predict function and is removed from the initialization.
* font sizes can be set in all figures
* Code cleaning

* Add in setup and requirements that matplotlib>=3.6.3 to prevent error regarding rotation

* rotation='vertical' replaced for 45 for matplotlib

* Added bootstrap test with KS-test 18
`dfit = distfit(n_boots=100)
`
* Updated plot_summary() with the bootstrap results
* Updated `dfit.summary` results with `bootstrap_score bootstrap_pass`
* Renamed `distr `into `name` in `dfit.summary` and now it is similar to the dictionary `dfit.model`
* Disables warning messages for colourmap
* See [documentation ](https://erdogant.github.io/distfit/pages/html/Performance.html#bootstrapping)for more information about the bootstrapping approach
* Updated docstrings

Read the blog about distfit [here](https://towardsdatascience.com/how-to-find-the-best-theoretical-distribution-for-your-data-a26e5673b4bd)!