- fixes a bug in
BinaryLogitStep
simulation where the output is not updated correctly - adds a
resid
attribute to fittedOLSRegressionStep
models, for diagnostics
- allows segmented large MNL models to be estimated with a
MergedChoiceTable
that's passed in by the user (rather than generated automatically), thus achieving parity with the non-segmented model class
- fixes a bug with the
out_transform
parameter forOLSRegressionStep
- introduces classes for storing common settings:
shared.CoreTemplateSettings
,shared.OutputColumnSettings
- adds new shared functions:
shared.register_column()
,utils.cols_in_expression()
- modifies
ColumnFromExpression
template to divide its parameters into three groups
- adds new template:
data.ColumnFromExpression
- adds new data management utilities:
utils.validate_table()
,utils.validate_all_tables()
,utils.merge_tables()
- updates
utils.get_data()
to use the new merge tool - updates
BinaryLogitStep
andOLSRegressionStep
to use the shared to useutils.get_data()
, removing any reliance on Orca broadcasts - raises the
pandas
requirement to 0.23
- adds an
mct
argment toSegmentedLargeMultinomialLogitStep.fit_all()
- adds an
interaction_terms
argument toSegmentedLargeMultinomialLogitStep.run_all()
- adds template for saving data:
data.SaveTable()
- renames
io.TableFromDisk()
todata.LoadTable()
- fixes a crash in small MNL simulation
- adds first data i/o template:
io.TableFromDisk()
- adds support for
autorun
template property
- patch to incorporate the
out_transform
bug fix forOLSRegressionStep
, from 0.2.dev7
- patch to incorporate the small MNL bug fix from 0.2.dev1
- adds support for passing multiple tables of interaction terms in large MNL
- enables on-the-fly creation of output columns in small MNL
- allows join keys to be used as data filters in MNL simulation
- fixes an OLS simulation bug that raised an error when the output column didn't exist yet
- implements
out_transform
for OLS simulation
- fixes a string comparison bug that caused problems with binary logit output in Windows
- adds
model
as an attribute of large MNL model steps, which provides achoicemodels.MultinomialLogitResults
object and is available any time after a model step is fitted - enables on-the-fly creation of output columns in large MNL
- fixes a large MNL simulation bug when there are no valid choosers or alternatives after evaluating the filters
- moves unit tests out of the module directory
- fixes a bug with interaction terms passed into
LargeMultinomialLogitStep.run()
- narrows the output of
utils.get_data()
to include only the columns requested (plus the index of the primary table) -- previously Orca had also provided some extra columns such as join keys
-
adds a new function
utils.get_data()
to assemble data from Orca, automatically detecting columns included in model expressions and filters -
implements
SegmentedLargeMultinomialLogit.run_all()
- fixes a model expression persistence bug in the small MNL template
- fixes a bug to allow large MNL simulation with multiple chooser tables
- improves installation and testing
- adds an
interaction_terms
parameter that users can manually pass toLargeMultinomialLogitStep.run()
, as a temporary solution until interaction terms are fully handled by the templates - also adds a
chooser_batch_size
parameter in the same place, to reduce memory pressure when there are large numbers of choosers
- adds a tool for testing template validity
- adds new
LargeMultinomialLogitStep
parameters related to choice simulation:constrained_choices
,alt_capacity
,chooser_size
, andmax_iter
- updates
LargeMultinomialLogitStep.run()
to use improved simulation utilities from ChoiceModels 0.2.dev4
- adds a template for segmented large MNL models:
SegmentedLargeMultinomialLogitStep
, which can automatically generate a set of large MNL models based on segmentation rules
- adds a
@modelmanager.template
decorator that makes a class available to the currently running instance of ModelManager
- moves the
register()
operation tomodelmanager
(previously it was a method implemented by the individual templates) - adds general ModelManager support for supplemental objects like pickled model results