Merge pull request #214 from automl/development

Release SMAC3 version 0.4

.gitignore

@@ -16,7 +16,12 @@ target_algo_runs.json
 
 # Other
 .tox
+.coverage
+.pypirc
+.ipynb_checkpoints/
+*.ipynb
 *~
+.html/
 
 #eclipse files
 .pydevproject 

.travis.yml

@@ -51,12 +51,12 @@ before_install:
   - export CC=`which gcc`
 
 install:
-  - pip install coverage pep8 python-coveralls
+  - pip install pep8 codecov
   - cat requirements.txt | xargs -n 1 -L 1 pip install
   - python setup.py install
 
 # command to run tests, e.g. python setup.py test
 script:
   - nosetests -sv --with-coverage --cover-package=smac
 after_success:
-  - coveralls
+  - codecov

changelog.md

@@ -1,110 +1,139 @@
+# 0.4
+
+* ADD #204: SMAC now always saves runhistory files as `runhistory.json`.
+* MAINT #205: the SMAC repository now uses codecov.io instead of coveralls.io.
+* ADD #83: support of ACLIB 2.0 parameter configuration space file.
+* FIX #206: instances are now explicitly cast to `str`. In case no instance is
+  given, a single `None` is used, which is not cast to `str`.
+* ADD #200: new convenience function to retrieve an `X`, `y` representation
+  of the data to feed it to a new fANOVA implementation.
+* MAINT #198: improved pSMAC interface.
+* FIX #201: improved handling of boolean arguments to SMAC.
+* FIX #194: fixes adaptive capping with re-occurring configurations.
+* ADD #190: new argument `intensification_percentage`.
+* ADD #187: better dependency injection into main SMAC class to avoid
+  ill-configured SMAC objects.
+* ADD #161: log scenario object as a file.
+* ADD #186: show the difference between old and new incumbent in case of an
+  incumbent change.
+* MAINT #159: consistent naming of loggers.
+* ADD #128: new helper method to get the target algorithm evaluator.
+* FIX #165: default value for par = 1.
+* MAINT #153: entries in the trajectory logger are now named tuples.
+* FIX #155: better handling of SMAC shutdown and crashes if the first
+  configuration crashes.
+
 # 0.3
 
 * Major speed improvements when sampling new configurations:
-    * Improved conditional hyperparameter imputation (PR #176)
-    * Faster generation of the one exchange neighborhood (PR #174)
-* FIX #171 potential bug with pSMAC
-* FIX #175 backwards compability for reading runhistory files
+    * Improved conditional hyperparameter imputation (PR #176).
+    * Faster generation of the one exchange neighborhood (PR #174).
+* FIX #171 potential bug with pSMAC.
+* FIX #175 backwards compability for reading runhistory files.
 
 # 0.2.4
 
-* CI only check code quality for python3
+* CI only check code quality for python3.
 * Perform local search on configurations from previous runs as proposed in the
   original paper from 2011 instead of random configurations as implemented
-  before
-* CI run travis-ci unit tests with python3.6
-* FIX #167, remove an endless loop which occured when using pSMAC
+  before.
+* CI run travis-ci unit tests with python3.6.
+* FIX #167, remove an endless loop which occured when using pSMAC.
 
 # 0.2.3
 
-* MAINT refactor Intensifcation and adding unit tests
-* CHANGE StatusType to Enum
-* RM parameter importance package
-* FIX ROAR facade bug for cli
-* ADD easy access of runhistory within Python
-* FIX imputation of censored data
-* FIX conversion of runhistory to EPM training data (in particular running time data)
-* FIX initial run only added once in runhistory
-* MV version number to a separate file
-* MAINT more efficient computations in run_history (assumes average as aggregation function across instances)
+* MAINT refactor Intensifcation and adding unit tests.
+* CHANGE StatusType to Enum.
+* RM parameter importance package.
+* FIX ROAR facade bug for cli.
+* ADD easy access of runhistory within Python.
+* FIX imputation of censored data.
+* FIX conversion of runhistory to EPM training data (in particular running
+  time data).
+* FIX initial run only added once in runhistory.
+* MV version number to a separate file.
+* MAINT more efficient computations in run_history (assumes average as
+  aggregation function across instances).
 
 # 0.2.2
 
-* FIX 124: SMAC could crash if the number of instances was less than seven
+* FIX 124: SMAC could crash if the number of instances was less than seven.
 * FIX 126: Memory limit was not correctly passed to the target algorithm
-  evaluator
+  evaluator.
 * Local search is now started from the configurations with highest EI, drawn by
-  random sampling
-* Reduce the number of trees to 10 to allow faster predictions (as in SMAC2)
+  random sampling.
+* Reduce the number of trees to 10 to allow faster predictions (as in SMAC2).
 * Do an adaptive number of stochastic local search iterations instead of a fixd
-  number (a5914a1d97eed2267ae82f22bd53246c92fe1e2c)
+  number (a5914a1d97eed2267ae82f22bd53246c92fe1e2c).
 * FIX a bug which didn't make SMAC run at least two configurations per call to
-  intensify
-* ADD more efficient data structure to update the cost of a configuration
+  intensify.
+* ADD more efficient data structure to update the cost of a configuration.
 * FIX do only count a challenger as a run if it actually was run
-  (and not only considered)(a993c29abdec98c114fc7d456ded1425a6902ce3)
+  (and not only considered)(a993c29abdec98c114fc7d456ded1425a6902ce3).
 
 # 0.2.1
 
-* CI: travis-ci continuous integration on OSX
+* CI: travis-ci continuous integration on OSX.
 * ADD: initial design for mulitple configurations, initial design for a 
-  random configuration
+  random configuration.
 * MAINT: use sklearn PCA if more than 7 instance features are available (as 
-  in SMAC 1 and 2)
-* MAINT: use same minimum step size for the stochastic local search as in SMAC2.
+  in SMAC 1 and 2).
+* MAINT: use same minimum step size for the stochastic local search as in
+  SMAC2.
 * MAINT: use same number of imputation iterations as in SMAC2.
 * FIX 98: automatically seed the configuration space object based on the SMAC
   seed.
 
 # 0.2
 
 * ADD 55: Separate modules for the initial design and a more flexible 
-  constructor for the SMAC class
-* ADD 41: Add ROAR (random online adaptive racing) class
+  constructor for the SMAC class.
+* ADD 41: Add ROAR (random online adaptive racing) class.
 * ADD 82: Add fmin_smac, a scipy.optimize.fmin_l_bfgs_b-like interface to the
-  SMAC algorithm
+  SMAC algorithm.
 * NEW documentation at https://automl.github.io/SMAC3/stable and 
-  https://automl.github.io/SMAC3/dev
+  https://automl.github.io/SMAC3/dev.
 * FIX 62: intensification previously used a random seed from np.random 
-  instead of from SMAC's own random number generator
-* FIX 42: class RunHistory can now be pickled
+  instead of from SMAC's own random number generator.
+* FIX 42: class RunHistory can now be pickled.
 * FIX 48: stats and runhistory objects are now injected into the target 
-  algorithm execution classes
+  algorithm execution classes.
 * FIX 72: it is now mandatory to either specify a configuration space or to 
-  pass the path to a PCS file
+  pass the path to a PCS file.
 * FIX 49: allow passing a callable directly to SMAC. SMAC will wrap the 
-  callable with the appropriate target algorithm runner
+  callable with the appropriate target algorithm runner.
 
 # 0.1.3
 
-* FIX 63 using memory limit for function target algorithms (broken since 0.1.1)
+* FIX 63 using memory limit for function target algorithms (broken since 0.1.1).
 
 # 0.1.2
 
-* FIX 58 output of the final statistics
-* FIX 56 using the command line target algorithms (broken since 0.1.1)
-* FIX 50 as variance prediction, we use the average predicted variance across the instances
+* FIX 58 output of the final statistics.
+* FIX 56 using the command line target algorithms (broken since 0.1.1).
+* FIX 50 as variance prediction, we use the average predicted variance across
+  the instances.
 
 # 0.1.1
 
-* NEW leading ones examples
-* NEW raise exception if unknown parameters are given in the scenario file
-* FIX 17/26/35/37/38/39/40/46
-* CHANGE requirement of ConfigSpace package to 0.2.1
-* CHANGE cutoff default is now None instead of 99999999999
+* NEW leading ones examples.
+* NEW raise exception if unknown parameters are given in the scenario file.
+* FIX 17/26/35/37/38/39/40/46.
+* CHANGE requirement of ConfigSpace package to 0.2.1.
+* CHANGE cutoff default is now None instead of 99999999999.
 
 
 # 0.1.0
 
-* Moved to github instead of bitbucket
-* ADD further unit tests
-* CHANGE Stats object instead of static class
-* CHANGE requirement of ConfigSpace package to 0.2.0
-* FIX intensify runs at least two challengers
-* FIX intensify skips incumbent as challenger
-* FIX Function TAE runner passes random seed to target function
-* FIX parsing of emtpy lines in scenario file
+* Moved to github instead of bitbucket.
+* ADD further unit tests.
+* CHANGE Stats object instead of static class.
+* CHANGE requirement of ConfigSpace package to 0.2.0.
+* FIX intensify runs at least two challengers.
+* FIX intensify skips incumbent as challenger.
+* FIX Function TAE runner passes random seed to target function.
+* FIX parsing of emtpy lines in scenario file.
 
 # 0.0.1
 
-* initial release
+* initial release.