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octave-forge-stk-2.8.0-bp156.2.4 RPM for ppc64le

From OpenSuSE Leap 15.6 for ppc64le

Name: octave-forge-stk Distribution: SUSE Linux Enterprise 15 SP6
Version: 2.8.0 Vendor: openSUSE
Release: bp156.2.4 Build date: Thu Dec 7 20:53:46 2023
Group: Productivity/Scientific/Math Build host: obs-power8-02
Size: 2992901 Source RPM: octave-forge-stk-2.8.0-bp156.2.4.src.rpm
Packager: https://bugs.opensuse.org
Url: https://gnu-octave.github.io/packages/stk/
Summary: Small Octave Toolbox for Kriging
The STK is a (not so) Small Toolbox for Kriging. Its primary focus
in on the interpolation/regression technique known as kriging, which
is very closely related to Splines and Radial Basis Functions, and can be
interpreted as a non-parametric Bayesian method using a Gaussian Process
(GP) prior. The STK also provides tools for the sequential and
non-sequential design of experiments. Even though it is, currently, mostly
geared towards the Design and Analysis of Computer Experiments (DACE), the
STK can be useful for other applications areas (such as Geostatistics,
Machine Learning, Non-parametric Regression, etc.).
This is part of Octave-Forge project.

Provides

Requires

License

GPL-3.0-or-later

Changelog

* Fri Jan 27 2023 Stefan Brüns <stefan.bruens@rwth-aachen.de>
  - Update to version 2.8.0:
    * Required Octave version number has been raised to 4.0.1.
    * Test functions:
      + stk_testfun_hartman3.m, stk_testfun_hartman6.m: New test
      functions (“Hartman3” and “Hartman6”) from the Dixon & Szego
      (1978) benchmark.
      + stk_testfun_hartman4.m: New test function (“Hartman4”) based
      on Picheny et al (2013), with a different scaling.
      + Most test functions in examples/test_functions are now also
      available under the CC0 license (see each file).
* Sun Aug 21 2022 Atri Bhattacharya <badshah400@gmail.com>
  - Update to version 2.7.0:
    * Required Octave version number has been raised to 4.0.0.
    * Prediction:
    - stk_predict.m now officially supports a shorter calling
      syntax: `[zp, ...] = skt_predict (model, x_prd)` that can be
      used either to compute predictions from any type of model
    - @stk_model_gpposterior/stk_predict.m: no longer exists. The
      base stk_predict function now provides the recommended
      interface for all possible types of models, and then
      dispatches to the (new) internal function stk_predict_ to do
      the actual computations.
    * Models: Removed get_input_data, get_output_data,
      get_prior_model.
    * Arrays:
    - stk_dataframe arrays now possess a sample_size property,
      which can be read using the usual dot-indexing notation or
      through the (slightly faster) getter stk_get_sample_size.
    - stk_model_gpposterior objects also have a sample_size
      property, which corresponds to the sample size of the
      underlying data set and can be read similarly.
    - stk_length: deprecated (use stk_get_sample_size instead).
    - @stk_model_gpposterior/stk_{set,get}_optimizable_parameters.m:
      Fix a bug (erroneous property name).
    * Sequential design of experiments: @stk_sampcrit_akg/set.m:
    * Remove replicated input points when the AKG reference grid is
    * construted using Scott's original method (i.e., taking past
    * observations points plus the candidate point).
    * Examples:
    - stk_example_kb07.m: Add a second figure where nu is fixed to
      5/2 and rho varies.
    - stk_example_doe05.m: Make it possible to use the exact KG
      criterion instead of Scott's approximation.
    - stk_example_doe06.m: New example script, which illustrates a
      simple sequential design strategy to estimate an excursion
      set (failure region) and its volume.
    * Miscellaneous:
    - stk_init.m: Make STK startup faster.
    - startup.m: Run stk_init automatically for in-place use.
    - stk_select_optimizer.m, stk_optim_hasfmincon.m: Removed.
    - README.md: Explain how to initialize STK when using the
      Parallel Computing Toolbox in Matlab, by means of the
      pctRunOnAll function.
    - Internal: source formatting, comments, etc.
* Wed Nov 27 2019 Stefan Brüns <stefan.bruens@rwth-aachen.de>
  - Update to version 2.6.1:
    * Documentation
      + stk_factorialdesign: Provide missing help text. (ticket #91)
      + Fix HTML doc (INDEX structure was broken).
  - Update to version 2.6.0:
    * Required Octave version
      + Required Octave version number has been raised to 3.8.
    * Parameter estimation
      + stk_param_init: The syntax with an additional do_estim_lnv parameter
      is now deprecated. Set model.lognoisevariance to NaN if you want an
      initial estimate for the variance of the noise.
      + stk_param_init_lnv: Refuse noiseless models (error).
      + stk_model_gpposterior: Trigger parameter estimation when lognoisevariance
      is NaN. In the (experimental) case where lognoisevariance is a noise
      model object, parameter estimation is triggered as soon as at least one
      of the optimizable parameters of the model is NaN. (ticket #93)
      + stk_param_relik: Return [] instead of NaN when the derivative with
      respect to lnv is requested for a noiseless model.
      + stk_param_relik: Detect duplicated observation points automatically
      and raise an error for noiseless models.
      + stk_param_getdefaultbounds: Estimation bounds for the regularity parameter
      of the Matérn covariance function are now customizable through the options
      nu_min_dimfun and nu_max_dimfun.
    * Covariance functions
      + Deprecated: stk_noisecov.
    * Models
      + stk_get_input_data, stk_get_output_data, stk_get_prior_model: New getters
      for model properties, that replace get_input_data, get_output_data and
      get_prior_model respectively (now deprecated).
      + stk_get_observation_variances: New getter, which returns the vector of
      variances associated to the observations that have been used to build a model.
      + stk_gaussiannoise_, stk_gaussiannoise_het0: New classes representing Gaussian
      noise models. Currently in experimental state, these two classes are merely a
      proof-of-concept. Other noise model classes can be defined by subclassing
      stk_gaussiannoise_. (ticket #38)
      + stk_example_misc05: Demonstrate the use of noise model objects to estimate
      the dispersion parameter in an heteroscedatic case.
      + stk_simulate_noise: New function to simulate noise sample replicates.
    * stk_dataframe and related classes
      + stk_dataframe: Accept char vectors (or strings) as colnames or rownames
      argument when there is only one column or one row (ticket #92)
      + @stk_dataframe/sort: Argument dim can now be skipped, as in the base sort function.
      + @stk_dataframe/unique: Overload base function.
    * Graphics
      + stk_plot1d: Do not create a legend systematically. (ticket #82)
      + stk_legend: New function to create a legend, using the graphical objects for
      which a non-empty DisplayName has been provided.
      + stk_plot_shadedci: Change gray levels and improve legend.
    * Miscellaneous
      + stk_options_set: Make it possible to set all options at once using an option
      structure. Add help text.
      + stk_runtests: Return test results in a structure.
      + stk_sampling_nesteddesign: Fix help text.
* Wed Jul 18 2018 badshah400@gmail.com
  - Update to version 2.5.1:
    * tk_dominatedhv: Workaround for Octave 4.4 issue (ticket #89)
    * Documentation fixes.
    * stk_option_set: Return option struct only if nargout > 0.
* Wed Sep 27 2017 badshah400@gmail.com
  - Update to version 2.5.0
    * Required Octave version number has been raised to 3.6.0.
    * Sequential design of experiments:
    - `stk_sampcrit_akg_eval`: New function.  Computes the
      Approximate Knowledge Gradient (AKG) sampling criterion.
    - `stk_example_doe05`: Example script that demonstrates the
      use of the AKG and EQI sampling criteria for noisy
      optimization.
    - New (experimental) classes to represent sampling criterion
      objects: `stk_sampcrit_ei`, `stk_sampcrit_akg`,
      `stk_sampcrit_eqi`.
    - `stk_sampcrit_ei_eval`: Remove deprecated calling forms.
    * Design of experiments:
    - `stk_factorialdesign`: Accept one-variable `stk_dataframe`
      objects as factors and preserve column names in this case.
    - `stk_sampling_nesteddesign`: New function to create nested
      designs.
    - `stk_sampling_nestedlhs`: New function to create nested LHS
      (NLHS).
    - `stk_sampling_sobol`: Fix help text.
    * Validation of models:
    - `stk_distrib_normal_crps`: New function to compare
      observations and predictive (Gaussian) density.
    - Calling `stk_predict_leaveoneout` with no output arguments
      now automatically creates two cross-validation diagnostics
      in two subplots: prediction VS observations (left panel) and
      normalized residuals (right panel).
    - `stk_predict_leaveoneout` uses now the virtual LOO formula.
    * `stk_dataframe` and related classes
    - `stk_hrect`: Preserve column names for `stk_dataframe`
      inputs.
    - `@stk_dataframe/find`: Overload base function to support
      calling find with an stk_dataframe as first input argument.
    - `@stk_dataframe/plotmatrix`: Overload base function to
      enrich `plotmatrix` graphics with variable names when
      possible.
    * Logical functions:
    - Operations that normally return logical (`lt`, `eq`,
      `and`...) now return logical values for `stk_dataframe`
      arguments.
    - New overloaded functions for `stk_dataframe` objects:
      `isinf`, `isnan`, `isfinite`.
    * Testing array membership:
    - `@stk_dataframe/ismember`: No longer assumes `rows` flag for
      consistency with the base `ismember` function.
    - `stk_factorialdesign/ismember`: New function.  Tests
      membership for factorial designs much more efficiently than
      for plain arrays or data frames.
    * `stk_generate_samplepaths` now returns a plain numerical array instead of
      a data frame.
    * Miscellaneous:
    - `stk_plot_probdom2d`: New function to represent the
      uncertainty about a 2D Pareto front.  This function is
      currently considered experimental and should not be expected
      to produce a reliable representation of the uncertainty for
      difficult or high-dimensional optimization problems.
    - New test case: "truss3" (Koski, 1985; Das, 1997).
    - Many functions have been optimized for speed.
    - `stk_plot1d`: Handle the case where `xt` is not sorted.
    - Support old-style STK structures (with a `.a` field) has
      been removed.
* Wed Nov 11 2015 dmitry_r@opensuse.org
  - Update to version 2.3.4
    * Bug fixes and minor changes
* Tue Oct 13 2015 dmitry_r@opensuse.org
  - Update to version 2.3.3
    * Bug fixes and minor changes
* Tue Jul 07 2015 dmitry_r@opensuse.org
  - Update to version 2.3.2
    * Bug fixes and minor changes
* Mon Jun 22 2015 dmitry_r@opensuse.org
  - Update to version 2.3.1
    * Bugfix release
* Mon May 18 2015 dmitry_r@opensuse.org
  - Update to version 2.3.0
* Thu Apr 16 2015 dmitry_r@opensuse.org
  - Update to version 2.2.1
    * Octave 4.0 compatibility
* Thu Feb 26 2015 dmitry_r@opensuse.org
  - Split from octave-forge package, version 2.2.0

Files

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Fabrice Bellet, Tue Jul 9 19:51:39 2024