gnu: python-dolfin-adjoint: Adjust package style.
* gnu/packages/simulation.scm (python-dolfin-adjoint): Move inputs after arguments. [description]: Place it on a new line, fix indentation. Change-Id: I3d971e48b4072258ed0b41af5c202e64af9de8f3
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@ -1204,17 +1204,6 @@ command-line utility for mesh optimisation.")
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"tests/migration/viscoelasticity/test-results")
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"tests/migration/viscoelasticity/test-results")
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#t))))
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#t))))
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(build-system python-build-system)
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(build-system python-build-system)
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(inputs
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(list fenics openmpi pybind11))
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(native-inputs
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(list pkg-config
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python-coverage
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python-decorator
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python-flake8
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python-pkgconfig
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python-pytest))
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(propagated-inputs
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`(("scipy" ,python-scipy)))
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(arguments
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(arguments
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`(#:phases
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`(#:phases
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(modify-phases %standard-phases
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(modify-phases %standard-phases
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@ -1245,17 +1234,28 @@ command-line utility for mesh optimisation.")
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;; fails with an ImportError if it sees that the backend module
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;; fails with an ImportError if it sees that the backend module
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;; has already been loaded.
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;; has already been loaded.
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(delete 'sanity-check))))
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(delete 'sanity-check))))
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(inputs
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(list fenics openmpi pybind11))
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(native-inputs
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(list pkg-config
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python-coverage
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python-decorator
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python-flake8
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python-pkgconfig
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python-pytest))
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(propagated-inputs
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(list python-scipy))
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(home-page "https://www.dolfin-adjoint.org")
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(home-page "https://www.dolfin-adjoint.org")
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(synopsis "Automatic differentiation library")
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(synopsis "Automatic differentiation library")
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(description "@code{python-dolfin-adjoint} is a solver of
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(description
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differential equations associated with a governing system and a
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"@code{python-dolfin-adjoint} is a solver of differential equations
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functional of interest. Working from the forward model the solver
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associated with a governing system and a functional of interest. Working from
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automatically derives the discrete adjoint and tangent linear models.
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the forward model the solver automatically derives the discrete adjoint and
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These additional models are key ingredients in many algorithms such as
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tangent linear models. These additional models are key ingredients in many
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data assimilation, optimal control, sensitivity analysis, design
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algorithms such as data assimilation, optimal control, sensitivity analysis,
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optimisation and error estimation. The dolfin-adjoint project
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design optimisation and error estimation. The dolfin-adjoint project provides
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provides the necessary tools and data structures for cases where the
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the necessary tools and data structures for cases where the forward model is
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forward model is implemented in @code{fenics} or
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implemented in @code{fenics} or
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@url{https://firedrakeproject.org,firedrake}.")
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@url{https://firedrakeproject.org,firedrake}.")
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(license license:lgpl3)))
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(license license:lgpl3)))
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