Change Log¶

0.4.2 (2016-06-16)¶

Breaking change: pypfilt.forecast will raise an exception if no forecasting dates are provided.
Add installation instructions for Red Hat Enterprise Linux, Fedora, and Mac OS X (using Homebrew).

Enhancement: allow forecasts to resume from cached states, greatly improving the speed with which forecasts can be generated when new or updated observations become available. This is enabled by defining a cache file:
```
params['hist']['cache_file'] = 'cache.hdf5'
```
Enhancement: add option to restrict summary statistics to forecasting simulations, ignoring the initial estimation run. This is enabled by passing only_fs=True as an argument to the pypfilt.summary.HDF5 constructor.

Breaking change: require models to define default parameter bounds by implementing the param_bounds method.
Enhancement: offer the post-regularised particle filter (post-RPF) as an alternative means of avoiding particle impoverishment (as opposed to incorporating stochastic noise into the model equations). This is enabled by setting:
```
params['resample']['regularisation'] = True
```
See the example script (./doc/example/run.py) for a demonstration.
Improved documentation for pypfilt.model.Base and summary statistics.
Add documentation for installing in a virtual environment.

This release includes a complete overhaul of simulation metadata and summary statistics. See ./doc/example/run.py for an overview of these changes.
Breaking change: decrease the default resampling threshold from 75% to 25%.
Breaking change: define base classes for summary statistics and output.
Breaking change: define a base class for simulation models.
Breaking change: collate the resampling and history matrix parameters to reduce clutter.
Breaking change: move pypfilt.metadata_priors to pypfilt.summary.
Bug fix: prevent stats.cov_wt from mutating the history matrix.
Bug fix: ensure that the time-step mapping behaves as documented.
Bug fix: ensure that state vector slices have correct dimensions.
Enhancement: ensure that forecasting dates lie within the simulation period.
Performance improvement: Vectorise the history matrix initialisation.
Host the documentation at Read The Docs.

Notify models whether the current simulation is a forecast (i.e., if there are no observations). This allows deterministic models to add noise when estimating, to allow identical particles to differ in their behaviour, and to avoid doing so when forecasting.

Note that this is a breaking change, as it alters the parameters passed to the model update function.
Simplify the API for running a single simulation; pypfilt.set_limits has been removed and pypfilt.Time is not included in the API documentation, on the grounds that users should not need to make use of this class.
Greater use of NumPy array functions, removing the dependency on six >= 1.7.
Minor corrections to the example script (./doc/example/run.py).

Avoid error messages if no logging handler is configured by the application.
Use a relative path for the output directory. This makes simulation metadata easier to reproduce, since the absolute path of the output directory is no longer included in the output file.
Build a universal wheel via python setup.py bdist_wheel, which supports both Python 2 and Python 3.

Make the output directory a simulation parameter (out_dir) so that it can be changed without affecting the working directory, and vice versa.