Pastas

Release with many new features and a few deprecations. Should be mostly backward compatible but will throw a few warnings for deprecated features.

Category | Explanation
-- | --
Deprecated | Method "get_tmin_tmax" is replaced by two new methods: "get_tmin" and "get_tmax"
Deprecated | Method "innovations" is replaced by "noise"
Deprecated | Settings argument has been removed from the model __init__
Enhanced | warmup argument can now also take a string e.g. "1000D", a warmup of 1000 days.
Enhanced | all get_methods of the model class now return pandas.Series
Enhanced | Fit report has been improved
Enhanced | Order of keyword arguments in model class is more consistent
New feature | A new stressmodel to multiply timeseries by a factor is implemented (FactorModel
New Feature | An autocorrelation function for irregular timesteps has been implemented.
New Feature | Durbin-Watson test for autocorrelation has been implemented
New Feature | Ljung-Box test for autocorrelation has been implemented
New Feature | ml.plots.diagnositics is introduced, giving an overview of to diagnose model assumptions

Pastas v0.9.5 has been released. This version should be mostly backward compatible with version 0.9.4 but might give different answers due to a change in the default solver. The kind keyword in all method is deprecated, see other changes below.

**Highlights**
- It is now possible to fit the constant not as parameter, but after simulation by using the fit_constant argument in the solve method.
- We now use Scipy's Least_squares solver as the default solver, dropping dependency on LmFit (which is still supported and available).
- You can now solve a model without a noisemodel, and use the optimal parameters as initial values when solving with a noisemodel afterwards.

**Other Changes**

Category | Description
-- | --
Bug Fix | Parameters bounds are changed when keyword up=False.
Deprecated | The show argument in the plotting methods is deprecated.
Deprecated | The kind argument for TimeSeries is deprecated. A string can now be provided for the settings keyword instead. E.g. settings="prec".
Enhanced | All plotting methods now use the tmin and tmax from the model settings.
Enhanced | Standard error is now reported as a percentage of the optimal value in fit_report for easier interpretation.
Enhanced | Logging system is improved, allowing the user to define which level of log message is printed to the console.
New Examples | A new notebook describing the response functions is added.
New Feature | It is now possible to use the optimal parameters when solving after the model has changed. This makes it possible to first solve without, and then with a noisemodel.
New Feature | The Nash-Sutcliffe fit statistic is added to the Stats module.
New Feature | LeastSquares is now the default solver, based on Scipy's least_squares solver. The dependency on LmFit is dropped.

**Next Release**
In the next release new stressmodels will be introduced that add linear or step trends.

Version v0.9.4 of Pastas is released, with multiple bug fixes and further improvements. This version should be compatible with v0.9.3 without many changes to your scripts.

**Highlights:**
- Improved fit report after model optimilisation
- Improved plotting methods
- New plotting method to plot the stresses
- Scipy LeastSquares solver now fully supported
- Improved parameter bounds
- Support to import Waterbase waterlevel measurements (RWS)
- Automatic including a Constant and Noisemodel in Models
- Improved support of the pas-file format to save models and projects
- Introduced the runs test to check for autocorrelation

**Next Release**
For the next release we aim to improve the API, making it more stable and simpler to understand for new users. This includes new examples, test procedures and better documentation. This release is planned for the beginning of March 2018.

The version 0.9.3 of PASTAS is released.

**NOTE! V0.9.3 is NOT backward compatible with v0.9.2.** There are some important API changes, most notably in the naming of the Tseries module, changed to stressmodels to avoid confusion in naming. These names are now fixed to avoid future api-incompatibilities. We are steadily working towards a stable version of pastas with much better backward compatibility.

Highlights:
- Renamed Tseries to Stressmodels
- Noisemodel is automatically added
- introduction of TimeSeries object to handle user provided time series and conversions
- import methods have been refactored to read_knmi, read_dino etc. available from the pastas top-level
- tmin/tmax of solve is used when calculating statistics
- statistics module has been updated. Methods used for a single series are now called as e.g: ps.stats.acf(series)
- significant speed-improvements have been applied, speeding up simulation up to a factor 2
- Pastas Project package is added, allowing dealing with many models efficiently

Next release:
For the next release the focus will be on the statistics package and the project packages, along with some new import methods for other data types. This update will most likely be in late 2018.

The version 0.9.2 of PASTAS is released.

Many bugs have been fixed, but mostly internal changes and optimizations.

**NOTE! V0.9.2 is NOT backward compatible with v0.9.2. Especially, when solving a model the weights have to be explicitly chosen ("swsi" is recommended setting when using a noise model)**

**Highlights:**
- Plotting module has seen significant updates and speedups
- Indexing for Pandas objects have been updates greatly reducing computation times
- Better support to check stresses (major updated on this expected in v0.9.3)
- New statistics have been added
- Weighting and calculations of the innovations have been split, allowing new weights models to be tested and increasing the modular design.
- Scipy LeastSquares optimizer has been added
- new standard import method is: "import pastas as ps"
- various get methods have been added to the Model class to obtain stresses, contributions etcetera from the tseries objects.

**New documentation:**
- The documentation page has been completely updated.
- It is now hosted on ReadTheDocs: Please refer to: http://pastas.readthedocs.io/
- Updates in the software are directly added to the documentation pages
- Notebooks with examples can be added easily and will be converted automatically