This is a record of all past optimagic releases and what went into them in reverse chronological order. We follow semantic versioning and all releases are available on Anaconda.org.
This is a minor release that introduces the new algorithm selection tool and several small improvements.
To learn more about the algorithm selection feature check out the following resources:
-
{gh}
549
Add support for Python 3.13 ({ghuser}timmens
) -
{gh}
550
and {gh}534
implement the new algorithm selection tool ({ghuser}janosg
) -
{gh}
548
and {gh}531
improve the documentation ({ghuser}ChristianZimpelmann
) -
{gh}
544
Adjusts the results processing of the nag optimizers to be compatible with the latest releases ({ghuser}timmens
) -
{gh}
543
Adds support for numpy 2.x ({ghuser}timmens
) -
{gh}
536
Adds a how-to guide for choosing local optimizers ({ghuser}mpetrosian
) -
{gh}
535
Allows algorithm classes and instances in estimation functions ({ghuser}timmens
) -
{gh}
532
Makes several small improvements to the documentation.
This is a major release with several breaking changes and deprecations. In this
release we started implementing two major enhancement proposals and renamed the package
from estimagic to optimagic (while keeping the estimagic
namespace for the estimation
capabilities).
The implementation of the two enhancement proposals is not complete and will likely
take until version 0.6.0
. However, all breaking changes and deprecations (with the
exception of a minor change in benchmarking) are already implemented such that updating
to version 0.5.0
is future proof.
- {gh}
500
removes the dashboard, the support for simopt optimizers and thederivative_plot
({ghuser}janosg
) - {gh}
502
renames estimagic to optimagic ({ghuser}janosg
) - {gh}
504
alignsmaximize
andminimize
more closely with scipy. All related deprecations and breaking changes are listed below. As a result, scipy code that uses minimize with the argumentsx0
,fun
,jac
andmethod
will run without changes in optimagic. Similarly, toOptimizeResult
gets some aliases so it behaves more like SciPy's. - {gh}
506
introduces the newBounds
object and deprecateslower_bounds
,upper_bounds
,soft_lower_bounds
andsoft_upper_bounds
({ghuser}janosg
) - {gh}
507
updates the infrastructure so we can make parallel releases under the namesoptimagic
andestimagic
({ghuser}timmens
) - {gh}
508
introduces the newScalingOptions
object and deprecates thescaling_options
argument ofmaximize
andminimize
({ghuser}timmens
) - {gh}
512
implements the new interface for objective functions and derivatives ({ghuser}janosg
) - {gh}
513
implements the newoptimagic.MultistartOptions
object and deprecates themultistart_options
argument ofmaximize
andminimize
({ghuser}timmens
) - {gh}
514
and {gh}516
introduce theNumdiffResult
object that is returned fromfirst_derivative
andsecond_derivative
. It also fixes several bugs in the pytree handling infirst_derivative
andsecond_derivative
and deprecates Richardson Extrapolation and thekey
({ghuser}timmens
) - {gh}
517
introduces the newNumdiffOptions
object for configuring numerical differentiation during optimization or estimation ({ghuser}timmens
) - {gh}
519
rewrites the logging code and introduces newLogOptions
objects ({ghuser}schroedk
) - {gh}
521
introduces the new internal algorithm interface. ({ghuser}janosg
and {ghuser}mpetrosian
) - {gh}
522
introduces the newConstraint
objects and deprecates passing dictionaries or lists of dictionaries as constraints ({ghuser}timmens
)
- When providing a path for the argument
logging
of the functionsmaximize
andminimize
and the file already exists, the default behavior is to raise an error now. Replacement or extension of an existing file must be explicitly configured. - The argument
if_table_exists
inlog_options
has no effect anymore and a corresponding warning is raised. OptimizeResult.history
is now aoptimagic.History
object instead of a dictionary. Dictionary style access is implemented but deprecated. Other dictionary methods might not work.- The result of
first_derivative
andsecond_derivative
is now aoptimagic.NumdiffResult
object instead of a dictionary. Dictionary style access is implemented but other dictionary methods might not work. - The dashboard is removed
- The
derivative_plot
is removed. - Optimizers from Simopt are removed.
- Passing callables with the old internal algorithm interface as
algorithm
tominimize
andmaximize
is not supported anymore. Use the newAlgorithm
objects instead. For examples see: https://tinyurl.com/24a5cner
- The
criterion
argument ofmaximize
andminimize
is renamed tofun
(as in SciPy). - The
derivative
argument ofmaximize
andminimize
is renamed tojac
(as in SciPy) - The
criterion_and_derivative
argument ofmaximize
andminimize
is renamed tofun_and_jac
to align it with the other names. - The
criterion_kwargs
argument ofmaximize
andminimize
is renamed tofun_kwargs
to align it with the other names. - The
derivative_kwargs
argument ofmaximize
andminimize
is renamed tojac_kwargs
to align it with the other names. - The
criterion_and_derivative_kwargs
argument ofmaximize
andminimize
is renamed tofun_and_jac_kwargs
to align it with the other names. - Algorithm specific convergence and stopping criteria are renamed to align them more
with NlOpt and SciPy names.
convergence_relative_criterion_tolerance
->convergence_ftol_rel
convergence_absolute_criterion_tolerance
->convergence_ftol_abs
convergence_relative_params_tolerance
->convergence_xtol_rel
convergence_absolute_params_tolerance
->convergence_xtol_abs
convergence_relative_gradient_tolerance
->convergence_gtol_rel
convergence_absolute_gradient_tolerance
->convergence_gtol_abs
convergence_scaled_gradient_tolerance
->convergence_gtol_scaled
stopping_max_criterion_evaluations
->stopping_maxfun
stopping_max_iterations
->stopping_maxiter
- The arguments
lower_bounds
,upper_bounds
,soft_lower_bounds
andsoft_upper_bounds
are deprecated and replaced byoptimagic.Bounds
. This affectsmaximize
,minimize
,estimate_ml
,estimate_msm
,slice_plot
and several other functions. - The
log_options
argument ofminimize
andmaximize
is deprecated. Instead,LogOptions
objects can be passed under thelogging
argument. - The class
OptimizeLogReader
is deprecated and redirects toSQLiteLogReader
. - The
scaling_options
argument ofmaximize
andminimize
is deprecated. Instead aScalingOptions
object can be passed under thescaling
argument that was previously just a bool. - Objective functions that return a dictionary with the special keys "value",
"contributions" and "root_contributions" are deprecated. Instead, likelihood and
least-squares functions are marked with a
mark.likelihood
ormark.least_squares
decorator. There is a detailed how-to guide that shows the new behavior. This affectsmaximize
,minimize
,slice_plot
and other functions that work with objective functions. - The
multistart_options
argument ofminimize
andmaximize
is deprecated. Instead, aMultistartOptions
object can be passed under themultistart
argument. - Richardson Extrapolation is deprecated in
first_derivative
andsecond_derivative
- The
key
argument is deprecated infirst_derivative
andsecond_derivative
- Passing dictionaries or lists of dictionaries as
constraints
tomaximize
orminimize
is deprecated. Use the newConstraint
objects instead.
This release contains minor improvements and bug fixes. It is the last release before the package will be renamed to optimagic and two large enhancement proposals will be implemented.
- {gh}
490
adds the attributeoptimize_result
to theMomentsResult
class ({ghuser}timmens
) - {gh}
483
fixes a bug in the handling of keyword arguments inbootstrap
({ghuser}alanlujan91
) - {gh}
477
allows to use an identity weighting matrix in MSM estimation ({ghuser}sidd3888
) - {gh}
473
fixes a bug where bootstrap keyword arguments were ignoredget_moments_cov
({ghuser}timmens
) - {gh}
467
, {gh}478
, {gh}479
and {gh}480
improve the documentation ({ghuser}mpetrosian
, {ghuser}segsell
, and {ghuser}timmens
)
This release drastically improves the optimizer benchmarking capabilities, especially with noisy functions and parallel optimizers. It makes tranquilo and numba optional dependencies and is the first version of estimagic to be compatible with Python 3.11.
- {gh}
464
Makes tranquilo and numba optional dependencies ({ghuser}janosg
) - {gh}
461
Updates docstrings for procss_benchmark_results ({ghuser}segsell
) - {gh}
460
Fixes several bugs in the processing of benchmark results with noisy functions ({ghuser}janosg
) - {gh}
459
Prepares benchmarking functionality for parallel optimizers ({ghuser}mpetrosian
and {ghuser}janosg
) - {gh}
457
Removes some unused files ({ghuser}segsell
) - {gh}
455
Improves a local pre-commit hook ({ghuser}ChristianZimpelmann
)
- {gh}
379
Improves the estimation table ({ghuser}ChristianZimpelmann
) - {gh}
445
fixes line endings in local pre-commit hook ({ghuser}ChristianZimpelmann
) - {gh}
443
, {gh}444
, {gh}445
, {gh}446
, {gh}448
and {gh}449
are a major refactoring of tranquilo ({ghuser}timmens
and {ghuser}janosg
) - {gh}
441
Adds an aggregated convergence plot for benchmarks ({ghuser}mpetrosian
) - {gh}
435
Completes the cartis-roberts benchmark set ({ghuser}segsell
)
- {gh}
437
removes fuzzywuzzy as dependency ({ghuser}aidatak97
) - {gh}
432
makes logging compatible with sqlalchemy 2.x ({ghuser}janosg
) - {gh}
430
refactors the getter functions in Tranquilo ({ghuser}janosg
) - {gh}
427
improves pre-commit setup ({ghuser}timmens
and {ghuser}hmgaudecker
) - {gh}
425
improves handling of notebooks in documentation ({ghuser}baharcos
) - {gh}
423
and {gh}399
add code to calculate poisdeness constants ({ghuser}segsell
) - {gh}
420
improve CI infrastructure ({ghuser}hmgaudecker
, {ghuser}janosg
) - {gh}
407
adds global optimizers from scipy ({ghuser}baharcos
)
- {gh}
416
improves documentation and packaging ({ghuser}janosg
)
- {gh}
412
Improves the output of the fides optimizer among other small changes ({ghuser}janosg
) - {gh}
411
Fixes a bug in multistart optimizations with least squares optimizers. See {gh}410
for details ({ghuser}janosg
) - {gh}
404
speeds up the gqtpar subsolver ({ghuser}mpetrosian
) - {gh}
400
refactors subsolvers ({ghuser}mpetrosian
) - {gh}
398
, {gh}397
, {gh}395
, {gh}390
, {gh}389
, {gh}388
continue with the implementation of tranquilo ({ghuser}segsell
, {ghuser}timmens
, {ghuser}mpetrosian
, {ghuser}janosg
) - {gh}
391
speeds up the bntr subsolver ({ghuser}mpetrosian
)
- {gh}
307
Adopts a code of condact and governance model - {gh}
384
Polish documentation ({ghuser}janosg
and {ghuser}mpetrosian
) - {gh}
374
Moves the documentation to MyST ({ghuser}baharcos
) - {gh}
365
Adds copybuttos to documentation ({ghuser}amageh
) - {gh}
371
Refactors the pounders algorithm ({ghuser}segsell
) - {gh}
369
Fixes CI ({ghuser}janosg
) - {gh}
367
Fixes the linux environment ({ghuser}timmens
) - {gh}
294
Adds the very first experimental version of tranquilo ({ghuser}janosg
, {ghuser}timmens
, {ghuser}segsell
, {ghuser}mpetrosian
)
- {gh}
366
Update ({ghuser}segsell
) - {gh}
362
Polish documentation ({ghuser}segsell
)
- {gh}
364
Use local random number generators ({ghuser}timmens
) - {gh}
363
Fix pounders test cases ({ghuser}segsell
) - {gh}
361
Update estimation code ({ghuser}timmens
) - {gh}
360
Update results object documentation ({ghuser}timmens
)
- {gh}
357
Adds jax support ({ghuser}janosg
) - {gh}
359
Improves error handling with violated constaints ({ghuser}timmens
) - {gh}
358
Improves cartis roberts set of test functions and improves the default latex rendering of MultiIndex tables ({ghuser}mpetrosian
)
- {gh}
355
Improves test coverage of contraints processing ({ghuser}janosg
) - {gh}
354
Improves test coverage for bounds processing ({ghuser}timmens
) - {gh}
353
Improves history plots ({ghuser}timmens
) - {gh}
352
Improves scaling and benchmarking ({ghuser}janosg
) - {gh}
351
Improves estimation summaries ({ghuser}timmens
) - {gh}
350
Allow empty queries or selectors in constraints ({ghuser}janosg
)
- {gh}
349
fixes multiple small bugs and adds test cases for all of them ({ghuser}mpetrosian
, {ghuser}janosg
and {ghuser}timmens
)
Fist release with pytree support in optimization, estimation and differentiation and much better result objects in optimization and estimation.
Breaking changes
- New
OptimizeResult
object is returned bymaximize
andminimize
. This breaks all code that expects the old result dictionary. Usage of the new result is explained in the getting started tutorial on optimization. - New internal optimizer interface that can break optimization with custom optimizers
- The inferface of
process_constraints
changed quite drastically. This breaks code that usedprocess_constraints
to get the number of free parameters or check if constraints are valid. There are new high level functionsestimagic.check_constraints
andestimagic.count_free_params
instead. - Some functions from
estimagic.logging.read_log
are removed and replaced byestimagic.OptimizeLogReader
. - Convenience functions to create namedtuples are removed from
estimagic.utilities
. - {gh}
346
Add option to use nonlinear constraints ({ghuser}timmens
) - {gh}
345
Moves estimation_table to new latex functionality of pandas ({ghuser}mpetrosian
) - {gh}
344
Adds pytree support to slice_plot ({ghuser}janosg
) - {gh}
343
Improves the result object of estimation functions and makes msm estimation pytree compatible ({ghuser}janosg
) - {gh}
342
Improves default options of the fides optimizer, allows single constraints and polishes the documentation ({ghuser}janosg
) - {gh}
340
Enables history collection for optimizers that evaluate the criterion function in parallel ({ghuser}janosg
) - {gh}
339
Incorporates user feedback and polishes the documentation. - {gh}
338
Improves log reading functions ({ghuser}janosg
) - {gh}
336
Adds pytree support to the dashboard ({ghuser}roecla
). - {gh}
335
Introduces anOptimizeResult
object and functionality for history plotting ({ghuser}janosg
). - {gh}
333
Uses new history collection feature to speed up benchmarking ({ghuser}segsell
). - {gh}
330
Is a major rewrite of the estimation code ({ghuser}timmens
). - {gh}
328
Improves quadratic surrogate solvers used in pounders and tranquilo ({ghuser}segsell
). - {gh}
326
Improves documentation of numerical derivatives ({ghuser}timmens
). - {gh}
325
Improves the slice_plot ({ghuser}mpetrosian
) - {gh}
324
Adds ability to collect optimization histories without logging ({ghuser}janosg
). - {gh}
311
and {gh}288
rewrite all plotting code in plotly ({ghuser}timmens
and {ghuser}aidatak97
). - {gh}
306
improves quadratic surrogate solvers used in pounders and tranquilo ({ghuser}segsell
). - {gh}
305
allows pytrees during optimization and rewrites large parts of the constraints processing ({ghuser}janosg
). - {gh}
303
introduces a new optimizer interface that makes it easier to add optimizers and makes it possible to access optimizer specific information outside of the intrenal_criterion_and_derivative ({ghuser}janosg
and {ghuser}roecla
).
- {gh}
302
Drastically improves error handling during optimization ({ghuser}janosg
).
- {gh}
304
Removes the chaospy dependency ({ghuser}segsell
).
- {gh}
295
Fixes a small bug in estimation_table ({ghuser}mpetrosian
). - {gh}
286
Adds pytree support for first and second derivative ({ghuser}timmens
). - {gh}
285
Allows to use estimation functions with external optimization ({ghuser}janosg
). - {gh}
283
Adds fast solvers for quadratic trustregion subproblems ({ghuser}segsell
). - {gh}
282
Vastly improves estimation tables ({ghuser}mpetrosian
). - {gh}
281
Adds some tools to work with pytrees ({ghuser}janosg
and {ghuser}timmens
). - {gh}
278
adds Estimagic Enhancement Proposal 1 for the use of Pytrees in Estimagic ({ghuser}janosg
)
- {gh}
276
Add parallel Nelder-Mead algorithm by {ghuser}jacekb95
- {gh}
267
Update fides by {ghuser}roecla
- {gh}
265
Refactor pounders algorithm by {ghuser}segsell
and {ghuser}janosg
. - {gh}
261
Add pure Python pounders algorithm by {ghuser}segsell
.
- {gh}
260
Update MSM and ML notebooks by {ghuser}timmens
. - {gh}
259
Several small fixes and improvements by {ghuser}janosg
and {ghuser}roecla
.
Add a lot of new functionality with a few minor breaking changes. We have more
optimizers, better error handling, bootstrap and inference for method of simulated
moments. The breaking changes are:
- logging is disabled by default during optimization.
- the log_option "if_exists" was renamed to "if_table_exists"
- The comparison plot function is removed.
- first_derivative now returns a dictionary, independent of arguments.
- structure of the logging database has changed
- there is an additional boolean flag named scaling
in minimize and maximize
- {gh}
251
Allows the loading, running and visualization of benchmarks ({ghuser}janosg
, {ghuser}mpetrosian
and {ghuser}roecla
) - {gh}
196
Adds support for multistart optimizations ({ghuser}asouther4
and {ghuser}janosg
) - {gh}
248
Adds the fides optimizer ({ghuser}roecla
) - {gh}
146
Addsestimate_ml
functionality ({ghuser}janosg
, {ghuser}LuisCald
and {ghuser}s6soverd
). - {gh}
235
Improves the documentation ({ghuser}roecla
) - {gh}
216
Adds the ipopt optimizer ({ghuser}roecla
) - {gh}
215
Adds optimizers from the pygmo library ({ghuser}roecla
and {ghuser}janosg
) - {gh}
212
Adds optimizers from the nlopt library ({ghuser}mpetrosian
) - {gh}
228
Restructures testing and makes changes to log_options. - {gh}
149
Addsestimate_msm
functionality ({ghuser}janosg
and {ghuser}loikein
) - {gh}
219
Several enhancements by ({ghuser}tobiasraabe
) - {gh}
218
Improve documentation by ({ghuser}sofyaakimova
) and ({ghuser}effieHan
) - {gh}
214
Fix bug with overlapping "fixed" and "linear" constraints ({ghuser}janosg
) - {gh}
211
Improve error handling of log reading functions by ({ghuser}janosg
) - {gh}
210
Automatically drop empty constraints by ({ghuser}janosg
) - {gh}
192
Add option to scale optimization problems by ({ghuser}janosg
) - {gh}
202
Refactoring of bootstrap code ({ghuser}janosg
) - {gh}
148
Add bootstrap functionality ({ghuser}RobinMusolff
) - {gh}
208
Several small improvements ({ghuser}janosg
) - {gh}
206
Improve latex and html tables ({ghuser}mpetrosian
) - {gh}
205
Add scipy's least squares optimizers (based on {gh}197
by ({ghuser}yradeva93
) - {gh}
198
More unit tests for optimizers ({ghuser}mchandra12
) - {gh}
200
Plot intermediate outputs offirst_derivative
({ghuser}timmens
)
- {gh}
195
Illustrate optimizers in documentation ({ghuser}sofyaakimova
), ({ghuser}effieHan
) and ({ghuser}janosg
) - {gh}
201
More stable covariance matrix calculation ({ghuser}janosg
) - {gh}
199
Return intermediate outputs of first_derivative ({ghuser}timmens
)
- {gh}
189
Improve documentation and logging ({ghuser}roecla
)
This release greatly expands the set of available optimization algorithms, has a better and prettier dashboard and improves the documentation.
- {gh}
187
Implement dot notation in algo_options ({ghuser}roecla
) - {gh}
183
Improve documentation ({ghuser}SofiaBadini
) - {gh}
182
Allow for constraints in likelihood inference ({ghuser}janosg
) - {gh}
181
Add DF-OLS optimizer from Numerical Algorithm Group ({ghuser}roecla
) - {gh}
180
Add pybobyqa optimizer from Numerical Algorithm Group ({ghuser}roecla
) - {gh}
179
Allow base_steps and min_steps to be scalars ({ghuser}tobiasraabe
) - {gh}
178
Refactoring of dashboard code ({ghuser}roecla
) - {gh}
177
Add stride as a new dashboard argument ({ghuser}roecla
) - {gh}
176
Minor fix of plot width in dashboard ({ghuser}janosg
) - {gh}
174
Various dashboard improvements ({ghuser}roecla
) - {gh}
173
Add new color palettes and use them in dashboard ({ghuser}janosg
) - {gh}
172
Add high level log reading functions ({ghuser}janosg
)
This release entails a complete rewrite of the optimization code with many breaking changes. In particular, some optimizers that were available before are not anymore. Those will be re-introduced soon. The breaking changes include:
- The database is restructured. The new version simplifies the code, makes logging faster and avoids the sql column limit.
- Users can provide closed form derivative and/or criterion_and_derivative where the latter one can exploit synergies in the calculation of criterion and derivative. This is also compatible with constraints.
- Our own (parallelized) first_derivative function is used to calculate gradients during the optimization when no closed form gradients are provided.
- Optimizer options like convergence criteria and optimization results are harmonized across optimizers.
- Users can choose from several batch evaluators whenever we parallelize (e.g. for parallel optimizations or parallel function evaluations for numerical derivatives) or pass in their own batch evaluator function as long as it has a compatible interface. The batch evaluator interface also standardizes error handling.
- There is a well defined internal optimizer interface. Users can select the pre-implemented optimizers by algorithm="name_of_optimizer" or their own optimizer by algorithm=custom_minimize_function
- Optimizers from pygmo and nlopt are no longer supported (will be re-introduced)
- Greatly improved error handling.
- {gh}
169
Add additional dashboard arguments - {gh}
168
Rename lower and upper to lower_bound and upper_bound ({ghuser}ChristianZimpelmann
) - {gh}
167
Improve dashboard styling ({ghuser}roecla
) - {gh}
166
Re-add POUNDERS from TAO ({ghuser}tobiasraabe
) - {gh}
165
Re-add the scipy optimizers with harmonized options ({ghuser}roecla
) - {gh}
164
Closed form derivatives for parameter transformations ({ghuser}timmens
) - {gh}
163
Complete rewrite of optimization with breaking changes ({ghuser}janosg
) - {gh}
162
Improve packaging and relax version constraints ({ghuser}tobiasraabe
) - {gh}
160
Generate parameter tables in tex and html ({ghuser}mpetrosian
)
- {gh}
130
Improve wrapping of POUNDERS algorithm ({ghuser}mo2561057
) - {gh}
159
Add Richardson Extrapolation to first_derivative ({ghuser}timmens
)
- {gh}
158
allows to specify a gradient in maximize and minimize ({ghuser}janosg
)
- {gh}
154
Version restrictions for pygmo ({ghuser}janosg
) - {gh}
153
adds documentation for the CLI ({ghuser}tobiasraabe
) - {gh}
152
makes estimagic work with pandas 1.0 ({ghuser}SofiaBadini
)
- {gh}
151
estimagic becomes a noarch package. ({ghuser}janosg
). - {gh}
150
adds command line interface to the dashboard ({ghuser}tobiasraabe
)