Source: openturns
Section: science
Priority: optional
Maintainer: Debian Science Maintainers <debian-science-maintainers@lists.alioth.debian.org>
Uploaders: Pierre Gruet <pgt@debian.org>
Build-Depends: debhelper-compat (= 13),
               bison,
               cmake,
               coinor-libbonmin-dev,
               coinor-libipopt-dev,
               dh-python,
               gfortran,
               flex,
               libblas-dev,
               libboost-math-dev,
               libceres-dev,
               libcminpack-dev,
               libdlib-dev,
               libhdf5-dev,
               libhmat-oss-dev (>= 1.7.1),
               liblapack-dev,
               libmpc-dev,
               libmpfr-dev,
               libmuparser-dev,
               libnlopt-cxx-dev,
               libpagmo-dev,
               libprimesieve-dev,
               libspectra-dev,
               libtbb-dev,
               libxml2-dev,
               python3-dev,
               swig
Standards-Version: 4.6.2
Homepage: https://openturns.github.io/www/
Vcs-Browser: https://salsa.debian.org/science-team/openturns
Vcs-Git: https://salsa.debian.org/science-team/openturns.git
Rules-Requires-Root: no

Package: libopenturns0.21
Section: libs
Architecture: any
Depends: ${shlibs:Depends},
         ${misc:Depends},
         openturns-common
Suggests: python3-openturns
Description: dynamic libraries for OpenTURNS
 OpenTURNS is a powerful and generic tool to treat and quantify
 uncertainties in numerical simulations in design, optimization and
 control. It allows both sensitivity and reliability analysis studies:
  * define the outputs of interest and decision criteria;
  * quantify and model the source of uncertainties;
  * propagate uncertainties and/or analyse sensitivity
  * rank the sources of uncertainty
 .
 Targeted users are all engineers who want to introduce the
 probabilistic dimension in their so far deterministic studies.
 .
 This package provides the dynamic libraries.

Package: libopenturns-dev
Section: libdevel
Architecture: any
Depends: ${misc:Depends},
         libopenturns0.21 (= ${binary:Version}),
         libceres-dev,
         libhmat-oss-dev
Description: headers and development libraries for OpenTURNS
 OpenTURNS is a powerful and generic tool to treat and quantify
 uncertainties in numerical simulations in design, optimization and
 control. It allows both sensitivity and reliability analysis studies:
  * defining the outputs of interest and decision criterion;
  * quantify and model the source of uncertainties;
  * propagate uncertainties and/or analyse sensitivity and
  * rank the sources of uncertainty
 .
 Targeted users are all engineers who want to introduce the
 probabilistic dimension in their so far deterministic studies.
 .
 This package contains development files needed to build OpenTURNS applications.

Package: openturns-common
Architecture: all
Depends: ${shlibs:Depends},
         ${misc:Depends}
Multi-Arch: foreign
Description: generic tool to treat and quantify uncertainties (common files)
 OpenTURNS is a powerful and generic tool to treat and quantify
 uncertainties in numerical simulations in design, optimization and
 control. It allows both sensitivity and reliability analysis studies:
  * defining the outputs of interest and decision criterion;
  * quantify and model the source of uncertainties;
  * propagate uncertainties and/or analyse sensitivity and
  * rank the sources of uncertainty
 .
 Targeted users are all engineers who want to introduce the
 probabilistic dimension in their so far deterministic studies.
 .
 This package contains the configuration file for the versioned library
 package.

Package: python3-openturns
Section: python
Architecture: any
Depends: ${shlibs:Depends},
         ${misc:Depends},
         libopenturns0.21 (= ${binary:Version}),
         ${python3:Depends}
Provides: ${python3:Provides}
Suggests: python3-matplotlib,
          python3-scipy
Description: Python3 front-end of OpenTURNS (aka TUI)
 OpenTURNS is a powerful and generic tool to treat and quantify
 uncertainties in numerical simulations in design, optimization and
 control. It allows both sensitivity and reliability analysis studies:
  * defining the outputs of interest and decision criterion;
  * quantify and model the source of uncertainties;
  * propagate uncertainties and/or analyse sensitivity and
  * rank the sources of uncertainty
 .
 Targeted users are all engineers who want to introduce the
 probabilistic dimension in their so far deterministic studies.
 .
 This package provides the Python3 bindings to the library.