Mrestimator

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* __Changed__: OutputHandlers set_xdata() now adjusts existing data and is slightly smarter. Now returns an array containing the indices where the x axis value is right for the provided data (wrt the existing context). See the example in the documentation.
* __Changed__: When calling OutputHanlders `add_coefficients()` or `add_ts()`, the meta data and plot range will be extended using `set_xdata`. Trying to add duplicates only changes their style to the new provided values (without adding meta).
* __Changed__: The parameters of `simulate_branching()` are different. `activity` is now `a`, `m` is no longer optional and it is possible to set a (time dependent) drive using `h`.
* __Fixed__: Calling `fit()` with only one trial does not crash anymore due to missing uncertainties
* __Fixed__: Calling `fit()` without specifying `steps` now uses the range used in `coefficients()`.
* __New__: added `full_analysis()`, the wrapper function to chain individual tasks together.
* __New__: added `simulate_subsampling()`
* __New__: Whenn adding time series to the `OutputHandler` in trial structure with more than one trial via `add_ts()`, they are drawn slightly transparent by default. Setting `alpha` overwrites this. `add_ts` does not use the new `set_xdata()` yet.
* __New__: Versionbump so we have the last digit for bugfixes :)
* __New__: Mr. Estimator came up with his logo.

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* __Changed__: `full_analysis()` argument `fitfunctions` renamed to `fitfuncs` to be consistent with `fit()` and `coefficients()`
* __Changed__: `full_analysis()` was rewritten, now only has three required arguments: `data`, `dt` and `kmax`, where `kmax` can be substituted by `steps` or `tmax`.
* __Changed__: concerning the `seed` argument for various functions:
all functions take either `seed=None` (no reseeding), `seed='random'` (reseeding to a random value - causing irreproducible resaults) or to a fixed value `seed=int(yourseed)`.
Per default, analysis functions - `full_analysis()`, `fit()` and `coefficients()` - produce same results by seeding to a fixed value each call. (only confidence intervals are affected by seeding)
Per default, `simulate_branching()` and `simulate_subsampling()` seed to `random`.
* __Fixed__: when calling branching process with `subp` and providing a seed, the subsampling no longer reseeds the rng device. (hence every call produces the same outcome, as expected)
* __Fixed__: `simulate_subsampling()` now returns np arrays of correct dimensions
* __New__: `full_analysis()` now shows a warning in the overview panel if consistency checks fail (so far only one).
* __New__: Version number is printed into the overview panel of `full_analysis()` and into saved meta data

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* __Changed__: We reworked the structure of `CoefficientResult` to be more consistent. This is now a completely _selfsimilar_ , where each child-entry has exactly the same structure as the parent. The new attributes `trialcrs` and `bootstrapcrs` replaced `samples`. Both are now lists containing again `CoefficientResults`, any (previously multidmensional) ndarrays are now 1d.
* __Changed__: Per default, `full_analysis()` initialises the random number generator (used for bootstrapping) once per call and passes `None` to the seed arguments of lower functions so they do not reseed. We introduced the convention that `seed=None` tells that function to use the current state of the rng without seeding. (Added an `auto` option for seeding where needed)
* __Changed__: All prints now use the logging module. Hopefully nothing broke :P.
* __Changed__: Default log level to console is now 'INFO', and some logs that one _could_ consider info go to 'DEBUG' to decrease the spam. Default loglevel to file is 'DEBUG' (logfile placed in the default temporary directory, which is also printed when loading the toolbox).
* __Changed__: When providing no loglevel to `full_analysis()` it uses the currently set level of `mre._logstreamhandler`.
* __Fixed__: When calling `full_analysis()` with one trial, a running average is shown instead of an empty plot.
* __New__: Added quantiles (and standard errors) to fit results if bootstrapping. The new default option, `numboot='auto'` calculates 250 bootstrap samples for the exponential and exp+offset fit functions (which are decently fast) and skips error estimation for the builtin complex (and custom) fits.
* __New__: Added function ``set_logfile(fname, loglevel='DEBUG')`` to change the path of the global logfile + level. This should allow running the toolbox in parallel, with a seperate logfile per thread and relatively silent/no console output when combining with `mre._logstreamhandler.setLevel('ERROR')` or calling `full_analysis(..., loglevel='ERROR')`
* __New__: Undocumented way to change the respective loglevels is e.g. ``mre._logstreamhandler.setLevel('WARNING')`` for console and ``mre._logfilehandler.setLevel('DEBUG')`` for file
* __New__: Added custom handler class that does not log 'None Type' Traces if `log.exception()` is called without a `try` statement