Upgrade path

This document outlines how to upgrade existing scripts to new versions of fwdpy11. This guide is likely imperfect/incomplete.

0.8.2

  • The first kwarg/positional argument for initializing a fwdpy11.DemographyDebugger has been renamed initial_deme_sizes. As the argument is required, and previously only took one possible type, we expect this change to not really break anyone’s code.

0.8.0

  • fwdpy11.DiscreteDemography can no longer be initialized with a numpy array as a positional argument. Now, pass it as the value to the set_deme_sizes keyword argument.

  • Initialization of fwdpy11.SetMigrationRates has changed for the case of resetting the entire migration matrix. See here.

  • The shape kwarg to initialize a fwdpy11.GammaS has been renamed shape_parameter.

  • The matrix kwarg to initialize a fwdpy11.MultivariateGaussianEffects has been renamed cov_matrix.

  • The kwarg gw2w for genetic value objects init methods has been replaced with gvalue_to_fitness.

  • The when kwargs for fwdpy11.Optimum and fwdpy11.PleiotropicOptima init methods is now the third positional argument rather than the first. This change should be caught at run time (the new classes won’t auto-convert float to int, and is fixed by adding parameter names when initializing instances of these types.

  • The type of fwdpy11.TableCollection.input_left and fwdpy11.TableCollection.output_right has changed to a simple index vector (#529). This change is a BIG memory savings when simulating large regions.

0.5.0

The following functions and types previously required a fwdpy11.MutationVector argument, but no longer do:

The extra argument could be eliminated due to the new attributes added to fwdpy11.MutationRecord.

0.2.0

This release also separates out the data representing a diploid into two classes, fwdpy11.DiploidGenotype and fwdpy11.DiploidMetadata. See diploids and processingpopsNP for type details and details on how these new classes affect processing populations using NumPy, respectively.

This release contains major changes to how genetic values are calculated and to how simulations parameters are stored. These changes are major simplifications to the package. See genetic_values_types and Setting up the parameters for a simulation for details.

The changes to how diploid data are stored completely changes how custom genetic values calculations are implemented. See customgvalues and stateful_fitness for examples.

Another major change is that genetic value and noise functions are no longer allowed to be written in Python. We may bring that back in a later release.

class:fwdpy11.sampling.DataMatrix has been completely refactored. See DataMatrix and StateMatrix for overview of current API.

The function fwdpy11.sampling.matrix_to_sample() now returns a tuple with two elements, which represent neutral and selected gentoypes, respectively. The previous API made you choose neutral or selected for the return value, which was a list.

Support for tree sequences will likely have a big impact on how you think about carrying out simulations. See ts and Data structures related to tree sequences for details.

0.1.4

Changes to DataMatrix

The member types fwdpy11.sampling.DataMatrix.ndim_neutral and fwdpy11.sampling.DataMatrix.ndim_selected are now read-only attributes. In previous versions, they were functions. To upgrade, simply remove any trailing (). In other words change this:

x.ndim_neutral()

To this:

x.ndim_neutral

The properties fwdpy11.sampling.DataMatrix.neutral and fwdpy11.sampling.DataMatrix.selected are now writeable. This allows you to recode the data as needed. For example, if you wish to swap the 0/1 values for a column, subtract 1 then multiply by -1. The result will affect the data stored on the C++ side.