diff options
| -rw-r--r-- | gnu/packages/simulation.scm | 40 |
1 files changed, 20 insertions, 20 deletions
diff --git a/gnu/packages/simulation.scm b/gnu/packages/simulation.scm index ab86e1d792..5341c0ae55 100644 --- a/gnu/packages/simulation.scm +++ b/gnu/packages/simulation.scm @@ -1204,17 +1204,6 @@ command-line utility for mesh optimisation.") "tests/migration/viscoelasticity/test-results") #t)))) (build-system python-build-system) - (inputs - (list fenics openmpi pybind11)) - (native-inputs - (list pkg-config - python-coverage - python-decorator - python-flake8 - python-pkgconfig - python-pytest)) - (propagated-inputs - `(("scipy" ,python-scipy))) (arguments `(#:phases (modify-phases %standard-phases @@ -1245,17 +1234,28 @@ command-line utility for mesh optimisation.") ;; fails with an ImportError if it sees that the backend module ;; has already been loaded. (delete 'sanity-check)))) + (inputs + (list fenics openmpi pybind11)) + (native-inputs + (list pkg-config + python-coverage + python-decorator + python-flake8 + python-pkgconfig + python-pytest)) + (propagated-inputs + (list python-scipy)) (home-page "https://www.dolfin-adjoint.org") (synopsis "Automatic differentiation library") - (description "@code{python-dolfin-adjoint} is a solver of -differential equations associated with a governing system and a -functional of interest. Working from the forward model the solver -automatically derives the discrete adjoint and tangent linear models. -These additional models are key ingredients in many algorithms such as -data assimilation, optimal control, sensitivity analysis, design -optimisation and error estimation. The dolfin-adjoint project -provides the necessary tools and data structures for cases where the -forward model is implemented in @code{fenics} or + (description + "@code{python-dolfin-adjoint} is a solver of differential equations +associated with a governing system and a functional of interest. Working from +the forward model the solver automatically derives the discrete adjoint and +tangent linear models. These additional models are key ingredients in many +algorithms such as data assimilation, optimal control, sensitivity analysis, +design optimisation and error estimation. The dolfin-adjoint project provides +the necessary tools and data structures for cases where the forward model is +implemented in @code{fenics} or @url{https://firedrakeproject.org,firedrake}.") (license license:lgpl3))) |