.\" Man page generated from reStructuredText.
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.TH "PYFR" "1" "Mar 05, 2019" "1.5.0" "PyFR"
.SH NAME
pyfr \- PyFR Documentation
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Contents:
.SH HOME
.SS Overview
.SS What is PyFR?
.sp
PyFR is an open\-source Python based framework for solving
advection\-diffusion type problems on streaming architectures using the
Flux Reconstruction approach of Huynh. The framework is designed to
solve a range of governing systems on mixed unstructured grids
containing various element types. It is also designed to target a range
of hardware platforms via use of an in\-built domain specific language
derived from the Mako templating engine. The current release (PyFR
1.5.0) has the following capabilities:
.INDENT 0.0
.IP \(bu 2
Governing Equations \- Euler, Navier Stokes
.IP \(bu 2
Dimensionality \- 2D, 3D
.IP \(bu 2
Element Types \- Triangles, Quadrilaterals, Hexahedra, Prisms,
Tetrahedra, Pyramids
.IP \(bu 2
Platforms \- CPU Clusters, Nvidia GPU Clusters, AMD GPU Clusters, Intel
Xeon Phi Clusters
.IP \(bu 2
Spatial Discretisation \- High\-Order Flux Reconstruction
.IP \(bu 2
Temporal Discretisation \- Explicit and Implicit (via Dual
Time\-Stepping)
.IP \(bu 2
Precision \- Single, Double
.IP \(bu 2
Mesh Files Imported \- Gmsh (.msh), CGNS (.cgns)
.IP \(bu 2
Solution Files Exported \- Unstructured VTK (.vtu, .pvtu)
.UNINDENT
.SS How do I Cite PyFR?
.sp
To cite PyFR, please reference the following paper:
.INDENT 0.0
.IP \(bu 2
\fI\%PyFR: An Open Source Framework for Solving Advection\-Diffusion Type
Problems on Streaming Architectures using the Flux Reconstruction
Approach. F. D. Witherden, A. M. Farrington, P. E. Vincent. Computer
Physics Communications, Volume 185, Pages 3028\-3040, 2014.\fP
.UNINDENT
.SS Who is Funding PyFR?
.sp
Development of PyFR is supported by the \fI\%Engineering and Physical
Sciences Research Council\fP, \fI\%Innovate UK\fP, the
\fI\%European Commission\fP,
\fI\%BAE Systems\fP,
\fI\%Airbus\fP, and the
\fI\%Air Force Office of Scientific Research\fP\&.
We are also grateful for hardware donations from Nvidia, Intel, and AMD.
.SH THEORY
.SS Flux Reconstruction
.SS Overview
.sp
High\-order numerical methods for unstructured grids combine the
superior accuracy of high\-order spectral or finite difference methods
with the geometrical flexibility of low\-order finite volume or finite
element schemes. The Flux Reconstruction (FR) approach unifies various
high\-order schemes for unstructured grids within a single framework.
Additionally, the FR approach exhibits a significant degree of element
locality, and is thus able to run efficiently on modern streaming
architectures, such as Graphical Processing Units (GPUs). The
aforementioned properties of FR mean it offers a promising route to
performing affordable, and hence industrially relevant, scale\-resolving
simulations of hitherto intractable unsteady flows (involving
separation, acoustics etc.) within the vicinity of real\-world
engineering geometries. An detailed overview of the FR approach is
given in:
.INDENT 0.0
.IP \(bu 2
\fI\%A Flux Reconstruction Approach to High\-Order Schemes Including
Discontinuous Galerkin Methods. H. T. Huynh. AIAA Paper 2007\-4079\fP
.UNINDENT
.SS Linear Stability
.sp
The linear stability of an FR schemes depends on the form of the
correction function. Linear stability issues are discussed in:
.INDENT 0.0
.IP \(bu 2
\fI\%A New Class of High\-Order Energy Stable Flux Reconstruction Schemes.
P. E. Vincent, P. Castonguay, A. Jameson. Journal of Scientific Computing,
Volume 47, Number 1, Pages 50\-72, 2011\fP
.IP \(bu 2
\fI\%Insights from von Neumann Analysis of High\-Order Flux Reconstruction
Schemes. P. E. Vincent, P. Castonguay, A. Jameson. Journal of Computational
Physics, Volume 230, Issue 22, Pages 8134\-8154, 2011\fP
.IP \(bu 2
\fI\%A New Class of High\-Order Energy Stable Flux Reconstruction Schemes for
Triangular Elements. P. Castonguay, P. E. Vincent, A. Jameson. Journal of
Scientific Computing, Volume 51, Number 1, Pages 224\-256, 2012\fP
.IP \(bu 2
\fI\%Energy Stable Flux Reconstruction Schemes for Advection\-Diffusion Problems.
P. Castonguay, D. M. Williams, P. E. Vincent, A. Jameson. Computer Methods
in Applied Mechanics and Engineering, Volume 267, Pages 400\-417, 2013\fP
.IP \(bu 2
\fI\%Energy Stable Flux Reconstruction Schemes for Advection\-Diffusion Problems
on Triangles. D. M. Williams, P. Castonguay, P. E. Vincent, A. Jameson.
Journal of Computational Physics, Volume 250, Pages 53\-76, 2013\fP
.IP \(bu 2
\fI\%Energy Stable Flux Reconstruction Schemes for Advection\-Diffusion
Problems on Tetrahedra. D. M. Williams, A. Jameson. Journal of
Scientific Computing, Volume 59, Pages 721\-759, 2014\fP
.IP \(bu 2
\fI\%An Extended Range of Stable\-Symmetric\-Conservative Flux Reconstruction
Correction Functions. P. E. Vincent, A. M. Farrington, F. D. Witherden,
A. Jameson. Computer Methods in Applied Mechanics and Engineering,
Volume 296, Pages 248\-272, 2015\fP
.UNINDENT
.SS Non\-Linear Stability
.sp
The non\-linear stability of an FR schemes depends on the location of the
solution points. Non\-linear stability issues are discussed in:
.INDENT 0.0
.IP \(bu 2
\fI\%On the Non\-Linear Stability of Flux Reconstruction Schemes. A. Jameson,
P. E. Vincent, P. Castonguay. Journal of Scientific Computing, Volume 50,
Number 2, Pages 434\-445, 2012\fP
.IP \(bu 2
\fI\%An Analysis of Solution Point Coordinates for Flux Reconstruction Schemes on
Triangular Elements. F. D. Witherden, P. E. Vincent. Journal of Scientific
Computing, Volume 61, Pages 398\-423, 2014\fP
.UNINDENT
.SH USER GUIDE
.SS Getting Started
.SS Downloading the Source
.sp
PyFR can be obtained \fI\%here\fP\&.
.SS Dependencies
.SS Overview
.sp
PyFR 1.5.0 has a hard dependency on Python 3.3+ and the following
Python packages:
.INDENT 0.0
.IP 1. 3
\fI\%gimmik\fP >= 2.0
.IP 2. 3
\fI\%h5py\fP >= 2.6
.IP 3. 3
\fI\%mako\fP >= 1.0.0
.IP 4. 3
\fI\%mpi4py\fP >= 2.0
.IP 5. 3
\fI\%numpy\fP >= 1.8
.IP 6. 3
\fI\%pytools\fP >= 2016.2.1
.UNINDENT
.sp
Note that due to a bug in \fI\%numpy\fP PyFR is not
compatible with 32\-bit Python distributions.
.SS CUDA Backend
.sp
The CUDA backend targets NVIDIA GPUs with a compute capability of 2.0
or greater. The backend requires:
.INDENT 0.0
.IP 1. 3
\fI\%CUDA\fP >= 4.2
.IP 2. 3
\fI\%pycuda\fP >= 2015.1
.UNINDENT
.SS MIC Backend
.sp
The MIC backend targets Intel Xeon Phi co\-processors. The backend
requires:
.INDENT 0.0
.IP 1. 3
ICC >= 14.0
.IP 2. 3
Intel MKL >= 11.1
.IP 3. 3
Intel MPSS >= 3.3
.IP 4. 3
\fI\%pymic\fP >= 0.7 (post commit 4d8a2da)
.UNINDENT
.SS OpenCL Backend
.sp
The OpenCL backend targets a range of accelerators including GPUs from
AMD and NVIDIA. The backend requires:
.INDENT 0.0
.IP 1. 3
OpenCL
.IP 2. 3
\fI\%pyopencl\fP
>= 2015.2.4
.IP 3. 3
\fI\%clBLAS\fP
.UNINDENT
.SS OpenMP Backend
.sp
The OpenMP backend targets multi\-core CPUs. The backend requires:
.INDENT 0.0
.IP 1. 3
GCC >= 4.9
.IP 2. 3
A BLAS library compiled as a shared library
(e.g. \fI\%OpenBLAS\fP)
.UNINDENT
.SS Running in Parallel
.sp
To partition meshes for running in parallel it is also necessary to
have one of the following partitioners installed:
.INDENT 0.0
.IP 1. 3
\fI\%metis\fP >= 5.0
.IP 2. 3
\fI\%scotch\fP >= 6.0
.UNINDENT
.SS Importing CGNS Meshes
.sp
To import CGNS meshes it is necessary to have the following installed:
.INDENT 0.0
.IP 1. 3
\fI\%CGNS\fP >= 3.3 (develop branch post commit
e0faea6)
.UNINDENT
.SS Installation
.sp
Before running PyFR 1.5.0 it is first necessary to either install
the software using the provided \fBsetup.py\fP installer or add the root
PyFR directory to \fBPYTHONPATH\fP using:
.INDENT 0.0
.INDENT 3.5
.sp
.nf
.ft C
user@computer ~/PyFR$ export PYTHONPATH=.:$PYTHONPATH
.ft P
.fi
.UNINDENT
.UNINDENT
.sp
To manage installation of Python dependencies we strongly recommend
using \fI\%pip\fP and
\fI\%virtualenv\fP\&.
.SS Running PyFR
.SS Overview
.sp
PyFR 1.5.0 uses three distinct file formats:
.INDENT 0.0
.IP 1. 3
\fB\&.ini\fP \-\-\- configuration file
.IP 2. 3
\fB\&.pyfrm\fP \-\-\- mesh file
.IP 3. 3
\fB\&.pyfrs\fP \-\-\- solution file
.UNINDENT
.sp
The following commands are available from the \fBpyfr\fP program:
.INDENT 0.0
.IP 1. 3
\fBpyfr import\fP \-\-\- convert a \fI\%Gmsh\fP .msh file or \fI\%CGNS\fP .cgns file into a PyFR .pyfrm file.
.sp
Example:
.INDENT 3.0
.INDENT 3.5
.sp
.nf
.ft C
pyfr import mesh.msh mesh.pyfrm
.ft P
.fi
.UNINDENT
.UNINDENT
.IP 2. 3
\fBpyfr partition\fP \-\-\- partition an existing mesh and
associated solution files.
.sp
Example:
.INDENT 3.0
.INDENT 3.5
.sp
.nf
.ft C
pyfr partition 2 mesh.pyfrm solution.pyfrs .
.ft P
.fi
.UNINDENT
.UNINDENT
.IP 3. 3
\fBpyfr run\fP \-\-\- start a new PyFR simulation. Example:
.INDENT 3.0
.INDENT 3.5
.sp
.nf
.ft C
pyfr run mesh.pyfrm configuration.ini
.ft P
.fi
.UNINDENT
.UNINDENT
.IP 4. 3
\fBpyfr restart\fP \-\-\- restart a PyFR simulation from an existing
solution file. Example:
.INDENT 3.0
.INDENT 3.5
.sp
.nf
.ft C
pyfr restart mesh.pyfrm solution.pyfrs
.ft P
.fi
.UNINDENT
.UNINDENT
.IP 5. 3
\fBpyfr export\fP \-\-\- convert a PyFR .pyfrs file into an
unstructured VTK .vtu or .pvtu file. Example:
.INDENT 3.0
.INDENT 3.5
.sp
.nf
.ft C
pyfr export mesh.pyfrm solution.pyfrs solution.vtu
.ft P
.fi
.UNINDENT
.UNINDENT
.UNINDENT
.SS Running in Parallel
.sp
\fBpyfr\fP can be run in parallel. To do so prefix \fBpyfr\fP with
\fBmpirun \-n <cores/devices>\fP\&. Note that the mesh must be
pre\-partitioned, and the number of cores or devices must be equal to
the number of partitions.
.SS Configuration File (.ini)
.SS Overview
.sp
The .ini configuration file parameterises the simulation. It is written
in the \fI\%INI\fP format.
Parameters are grouped into sections. The roles of each section and
their associated parameters are described below.
.SS [backend]
.sp
Parameterises the backend with
.INDENT 0.0
.IP 1. 3
\fBprecision\fP \-\-\- number precision:
.INDENT 3.0
.INDENT 3.5
\fBsingle\fP | \fBdouble\fP
.UNINDENT
.UNINDENT
.IP 2. 3
\fBrank\-allocator\fP \-\-\- MPI rank allocator:
.INDENT 3.0
.INDENT 3.5
\fBlinear\fP | \fBrandom\fP
.UNINDENT
.UNINDENT
.UNINDENT
.sp
Example:
.INDENT 0.0
.INDENT 3.5
.sp
.nf
.ft C
[backend]
precision = double
rank\-allocator = linear
.ft P
.fi
.UNINDENT
.UNINDENT
.SS [backend\-cuda]
.sp
Parameterises the CUDA backend with
.INDENT 0.0
.IP 1. 3
\fBdevice\-id\fP \-\-\- method for selecting which device(s) to run on:
.INDENT 3.0
.INDENT 3.5
\fIint\fP | \fBround\-robin\fP | \fBlocal\-rank\fP
.UNINDENT
.UNINDENT
.IP 2. 3
\fBgimmik\-max\-nnz\fP \-\-\- cutoff for GiMMiK in terms of the number of
non\-zero entires in a constant matrix:
.INDENT 3.0
.INDENT 3.5
\fIint\fP
.UNINDENT
.UNINDENT
.IP 3. 3
\fBmpi\-type\fP \-\-\- type of MPI library that is being used:
.INDENT 3.0
.INDENT 3.5
\fBstandard\fP | \fBcuda\-aware\fP
.UNINDENT
.UNINDENT
.IP 4. 3
\fBblock\-1d\fP \-\-\- block size for one dimensional pointwise kernels:
.INDENT 3.0
.INDENT 3.5
\fIint\fP
.UNINDENT
.UNINDENT
.IP 5. 3
\fBblock\-2d\fP \-\-\- block size for two dimensional pointwise kernels:
.INDENT 3.0
.INDENT 3.5
\fIint\fP, \fIint\fP
.UNINDENT
.UNINDENT
.UNINDENT
.sp
Example:
.INDENT 0.0
.INDENT 3.5
.sp
.nf
.ft C
[backend\-cuda]
device\-id = round\-robin
gimmik\-max\-nnz = 512
mpi\-type = standard
block\-1d = 64
block\-2d = 128, 2
.ft P
.fi
.UNINDENT
.UNINDENT
.SS [backend\-mic]
.sp
Parameterises the MIC backend with
.INDENT 0.0
.IP 1. 3
\fBdevice\-id\fP \-\-\- for selecting which device(s) to run on:
.INDENT 3.0
.INDENT 3.5
\fIint\fP | \fBlocal\-rank\fP
.UNINDENT
.UNINDENT
.IP 2. 3
\fBmkl\-root\fP \-\-\- path to MKL root directory:
.INDENT 3.0
.INDENT 3.5
\fIstring\fP
.UNINDENT
.UNINDENT
.UNINDENT
.SS [backend\-opencl]
.sp
Parameterises the OpenCL backend with
.INDENT 0.0
.IP 1. 3
\fBplatform\-id\fP \-\-\- for selecting platform id:
.INDENT 3.0
.INDENT 3.5
\fIint\fP | \fIstring\fP
.UNINDENT
.UNINDENT
.IP 2. 3
\fBdevice\-type\fP \-\-\- for selecting what type of device(s) to run on:
.INDENT 3.0
.INDENT 3.5
\fBall\fP | \fBcpu\fP | \fBgpu\fP | \fBaccelerator\fP
.UNINDENT
.UNINDENT
.IP 3. 3
\fBdevice\-id\fP \-\-\- for selecting which device(s) to run on:
.INDENT 3.0
.INDENT 3.5
\fIint\fP | \fIstring\fP | \fBlocal\-rank\fP
.UNINDENT
.UNINDENT
.IP 4. 3
\fBgimmik\-max\-nnz\fP \-\-\- cutoff for GiMMiK in terms of the number of
non\-zero entires in a constant matrix:
.INDENT 3.0
.INDENT 3.5
\fIint\fP
.UNINDENT
.UNINDENT
.IP 5. 3
\fBlocal\-size\-1d\fP \-\-\- local work size for one dimensional pointwise
kernels:
.INDENT 3.0
.INDENT 3.5
\fIint\fP
.UNINDENT
.UNINDENT
.IP 6. 3
\fBlocal\-size\-2d\fP \-\-\- local work size for two dimensional pointwise
kernels:
.INDENT 3.0
.INDENT 3.5
\fIint\fP, \fIint\fP
.UNINDENT
.UNINDENT
.UNINDENT
.sp
Example:
.INDENT 0.0
.INDENT 3.5
.sp
.nf
.ft C
[backend\-opencl]
platform\-id = 0
device\-type = gpu
device\-id = local\-rank
gimmik\-max\-nnz = 512
local\-size\-1d = 16
local\-size\-2d = 128, 1
.ft P
.fi
.UNINDENT
.UNINDENT
.SS [backend\-openmp]
.sp
Parameterises the OpenMP backend with
.INDENT 0.0
.IP 1. 3
\fBcc\fP \-\-\- C compiler:
.INDENT 3.0
.INDENT 3.5
\fIstring\fP
.UNINDENT
.UNINDENT
.IP 2. 3
\fBcflags\fP \-\-\- additional C compiler flags:
.INDENT 3.0
.INDENT 3.5
\fIstring\fP
.UNINDENT
.UNINDENT
.IP 3. 3
\fBcblas\fP \-\-\- path to shared C BLAS library:
.INDENT 3.0
.INDENT 3.5
\fIstring\fP
.UNINDENT
.UNINDENT
.IP 4. 3
\fBcblas\-type\fP \-\-\- type of BLAS library:
.INDENT 3.0
.INDENT 3.5
\fBserial\fP | \fBparallel\fP
.UNINDENT
.UNINDENT
.UNINDENT
.sp
Example:
.INDENT 0.0
.INDENT 3.5
.sp
.nf
.ft C
[backend\-openmp]
cc = gcc
cblas= example/path/libBLAS.dylib
cblas\-type = parallel
.ft P
.fi
.UNINDENT
.UNINDENT
.SS [constants]
.sp
Sets constants used in the simulation with
.INDENT 0.0
.IP 1. 3
\fBgamma\fP \-\-\- ratio of specific heats:
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP
.UNINDENT
.UNINDENT
.IP 2. 3
\fBmu\fP \-\-\- dynamic viscosity:
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP
.UNINDENT
.UNINDENT
.IP 3. 3
\fBPr\fP \-\-\- Prandtl number:
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP
.UNINDENT
.UNINDENT
.IP 4. 3
\fBcpTref\fP \-\-\- product of specific heat at constant pressure and
reference temperature for Sutherland\(aqs Law:
.sp
\fIfloat\fP
.IP 5. 3
\fBcpTs\fP \-\-\- product of specific heat at constant pressure and
Sutherland temperature for Sutherland\(aqs Law:
.sp
\fIfloat\fP
.UNINDENT
.sp
Example:
.INDENT 0.0
.INDENT 3.5
.sp
.nf
.ft C
[constants]
gamma = 1.4
mu = 0.001
Pr = 0.72
.ft P
.fi
.UNINDENT
.UNINDENT
.SS [solver]
.sp
Parameterises the solver with
.INDENT 0.0
.IP 1. 3
\fBsystem\fP \-\-\- governing system:
.INDENT 3.0
.INDENT 3.5
\fBeuler\fP | \fBnavier\-stokes\fP
.UNINDENT
.UNINDENT
.IP 2. 3
\fBorder\fP \-\-\- order of polynomial solution basis:
.INDENT 3.0
.INDENT 3.5
\fIint\fP
.UNINDENT
.UNINDENT
.IP 3. 3
\fBanti\-alias\fP \-\-\- type of anti\-aliasing:
.INDENT 3.0
.INDENT 3.5
\fBflux\fP | \fBsurf\-flux\fP | \fBdiv\-flux\fP | \fBflux, surf\-flux\fP |
\fBflux, div\-flux\fP | \fBsurf\-flux, div\-flux\fP |
\fBflux, surf\-flux, div\-flux\fP
.UNINDENT
.UNINDENT
.IP 4. 3
\fBviscosity\-correction\fP \-\-\- viscosity correction:
.INDENT 3.0
.INDENT 3.5
\fBnone\fP | \fBsutherland\fP
.UNINDENT
.UNINDENT
.IP 5. 3
\fBshock\-capturing\fP \-\-\- shock capturing scheme:
.INDENT 3.0
.INDENT 3.5
\fBnone\fP | \fBartificial\-viscosity\fP
.UNINDENT
.UNINDENT
.UNINDENT
.sp
Example:
.INDENT 0.0
.INDENT 3.5
.sp
.nf
.ft C
[solver]
system = navier\-stokes
order = 3
anti\-alias = flux
viscosity\-correction = none
shock\-capturing = artificial\-viscosity
.ft P
.fi
.UNINDENT
.UNINDENT
.SS [solver\-time\-integrator]
.sp
Parameterises the time\-integration scheme used by the solver with
.INDENT 0.0
.IP 1. 3
\fBformulation\fP \-\-\- formulation:
.INDENT 3.0
.INDENT 3.5
\fBstd\fP | \fBdual\fP
.sp
where
.sp
\fBstd\fP requires
.INDENT 0.0
.INDENT 3.5
.INDENT 0.0
.IP \(bu 2
\fBscheme\fP \-\-\- time\-integration scheme
.INDENT 3.0
.INDENT 3.5
\fBeuler\fP | \fBrk34\fP | \fBrk4\fP | \fBrk45\fP | \fBtvd\-rk3\fP
.UNINDENT
.UNINDENT
.IP \(bu 2
\fBtstart\fP \-\-\- initial time
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP
.UNINDENT
.UNINDENT
.IP \(bu 2
\fBtend\fP \-\-\- final time
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP
.UNINDENT
.UNINDENT
.IP \(bu 2
\fBdt\fP \-\-\- time\-step
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP
.UNINDENT
.UNINDENT
.IP \(bu 2
\fBcontroller\fP \-\-\- time\-step controller
.INDENT 3.0
.INDENT 3.5
\fBnone\fP | \fBpi\fP
.sp
where
.sp
\fBpi\fP only works with \fBrk34\fP and \fBrk45\fP and requires
.INDENT 0.0
.INDENT 3.5
.INDENT 0.0
.IP \(bu 2
\fBatol\fP \-\-\- absolute error tolerance
.INDENT 2.0
.INDENT 3.5
\fIfloat\fP
.UNINDENT
.UNINDENT
.IP \(bu 2
\fBrtol\fP \-\-\- relative error tolerance
.INDENT 2.0
.INDENT 3.5
\fIfloat\fP
.UNINDENT
.UNINDENT
.IP \(bu 2
\fBerrest\-norm\fP \-\-\- norm to use for estimating the error
.INDENT 2.0
.INDENT 3.5
\fBuniform\fP | \fBl2\fP
.UNINDENT
.UNINDENT
.IP \(bu 2
\fBsafety\-fact\fP \-\-\- safety factor for step size adjustment
(suitable range 0.80\-0.95)
.INDENT 2.0
.INDENT 3.5
\fIfloat\fP
.UNINDENT
.UNINDENT
.IP \(bu 2
\fBmin\-fact\fP \-\-\- minimum factor that the time\-step can change
between iterations (suitable range 0.1\-0.5)
.INDENT 2.0
.INDENT 3.5
\fIfloat\fP
.UNINDENT
.UNINDENT
.IP \(bu 2
\fBmax\-fact\fP \-\-\- maximum factor that the time\-step can change
between iterations (suitable range 2.0\-6.0)
.INDENT 2.0
.INDENT 3.5
\fIfloat\fP
.UNINDENT
.UNINDENT
.UNINDENT
.UNINDENT
.UNINDENT
.UNINDENT
.UNINDENT
.UNINDENT
.UNINDENT
.UNINDENT
.sp
\fBdual\fP requires
.INDENT 0.0
.INDENT 3.5
.INDENT 0.0
.IP \(bu 2
\fBscheme\fP \-\-\- time\-integration scheme
.INDENT 3.0
.INDENT 3.5
\fBbackward\-euler\fP | \fBbdf2\fP | \fBbdf3\fP
.UNINDENT
.UNINDENT
.IP \(bu 2
\fBpseudo\-scheme\fP \-\-\- pseudo\-time\-integration scheme
.INDENT 3.0
.INDENT 3.5
\fBeuler\fP | \fBtvd\-rk3\fP | \fBrk4\fP
.UNINDENT
.UNINDENT
.IP \(bu 2
\fBtstart\fP \-\-\- initial time
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP
.UNINDENT
.UNINDENT
.IP \(bu 2
\fBtend\fP \-\-\- final time
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP
.UNINDENT
.UNINDENT
.IP \(bu 2
\fBdt\fP \-\-\- time\-step
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP
.UNINDENT
.UNINDENT
.IP \(bu 2
\fBpseudo\-dt\fP \-\-\- pseudo\-time\-step
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP
.UNINDENT
.UNINDENT
.IP \(bu 2
\fBcontroller\fP \-\-\- pseudo\-time\-step controller
.INDENT 3.0
.INDENT 3.5
\fBnone\fP
.sp
where
.sp
\fBnone\fP requires
.INDENT 0.0
.INDENT 3.5
.INDENT 0.0
.IP \(bu 2
\fBpseudo\-niters\-max\fP \-\-\- minimum number of iterations
.INDENT 2.0
.INDENT 3.5
\fIint\fP
.UNINDENT
.UNINDENT
.IP \(bu 2
\fBpseudo\-niters\-min\fP \-\-\- maximum number of iterations
.INDENT 2.0
.INDENT 3.5
\fIint\fP
.UNINDENT
.UNINDENT
.IP \(bu 2
\fBpseudo\-aresid\fP \-\-\- absolute residual tolerance
.INDENT 2.0
.INDENT 3.5
\fIfloat\fP
.UNINDENT
.UNINDENT
.IP \(bu 2
\fBpseudo\-rresid\fP \-\-\- relative residual tolerance
.INDENT 2.0
.INDENT 3.5
\fIfloat\fP
.UNINDENT
.UNINDENT
.UNINDENT
.UNINDENT
.UNINDENT
.UNINDENT
.UNINDENT
.UNINDENT
.UNINDENT
.UNINDENT
.UNINDENT
.UNINDENT
.UNINDENT
.sp
Example:
.INDENT 0.0
.INDENT 3.5
.sp
.nf
.ft C
[solver\-time\-integrator]
formulation = std
scheme = rk45
controller = pi
tstart = 0.0
tend = 10.0
dt = 0.001
atol = 0.00001
rtol = 0.00001
errest\-norm = l2
safety\-fact = 0.9
min\-fact = 0.3
max\-fact = 2.5
.ft P
.fi
.UNINDENT
.UNINDENT
.SS [solver\-interfaces]
.sp
Parameterises the interfaces with
.INDENT 0.0
.IP 1. 3
\fBriemann\-solver\fP \-\-\- type of Riemann solver:
.INDENT 3.0
.INDENT 3.5
\fBrusanov\fP | \fBhll\fP | \fBhllc\fP | \fBroe\fP | \fBroem\fP
.UNINDENT
.UNINDENT
.IP 2. 3
\fBldg\-beta\fP \-\-\- beta parameter used for LDG:
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP
.UNINDENT
.UNINDENT
.IP 3. 3
\fBldg\-tau\fP \-\-\- tau parameter used for LDG:
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP
.UNINDENT
.UNINDENT
.UNINDENT
.sp
Example:
.INDENT 0.0
.INDENT 3.5
.sp
.nf
.ft C
[solver\-interfaces]
riemann\-solver = rusanov
ldg\-beta = 0.5
ldg\-tau = 0.1
.ft P
.fi
.UNINDENT
.UNINDENT
.SS [solver\-interfaces\-line]
.sp
Parameterises the line interfaces with
.INDENT 0.0
.IP 1. 3
\fBflux\-pts\fP \-\-\- location of the flux points on a line interface:
.INDENT 3.0
.INDENT 3.5
\fBgauss\-legendre\fP | \fBgauss\-legendre\-lobatto\fP
.UNINDENT
.UNINDENT
.IP 2. 3
\fBquad\-deg\fP \-\-\- degree of quadrature rule for anti\-aliasing on a
line interface:
.INDENT 3.0
.INDENT 3.5
\fIint\fP
.UNINDENT
.UNINDENT
.IP 3. 3
\fBquad\-pts\fP \-\-\- name of quadrature rule for anti\-aliasing on a
line interface:
.INDENT 3.0
.INDENT 3.5
\fBgauss\-legendre\fP | \fBgauss\-legendre\-lobatto\fP
.UNINDENT
.UNINDENT
.UNINDENT
.sp
Example:
.INDENT 0.0
.INDENT 3.5
.sp
.nf
.ft C
[solver\-interfaces\-line]
flux\-pts = gauss\-legendre
quad\-deg = 10
quad\-pts = gauss\-legendre
.ft P
.fi
.UNINDENT
.UNINDENT
.SS [solver\-interfaces\-tri]
.sp
Parameterises the triangular interfaces with
.INDENT 0.0
.IP 1. 3
\fBflux\-pts\fP \-\-\- location of the flux points on a triangular
interface:
.INDENT 3.0
.INDENT 3.5
\fBwilliams\-shunn\fP
.UNINDENT
.UNINDENT
.IP 2. 3
\fBquad\-deg\fP \-\-\- degree of quadrature rule for anti\-aliasing on a
triangular interface:
.INDENT 3.0
.INDENT 3.5
\fIint\fP
.UNINDENT
.UNINDENT
.IP 3. 3
\fBquad\-pts\fP \-\-\- name of quadrature rule for anti\-aliasing on a
triangular interface:
.INDENT 3.0
.INDENT 3.5
\fBwilliams\-shunn\fP | \fBwitherden\-vincent\fP
.UNINDENT
.UNINDENT
.UNINDENT
.sp
Example:
.INDENT 0.0
.INDENT 3.5
.sp
.nf
.ft C
[solver\-interfaces\-tri]
flux\-pts = williams\-shunn
quad\-deg = 10
quad\-pts = williams\-shunn
.ft P
.fi
.UNINDENT
.UNINDENT
.SS [solver\-interfaces\-quad]
.sp
Parameterises the quadrilateral interfaces with
.INDENT 0.0
.IP 1. 3
\fBflux\-pts\fP \-\-\- location of the flux points on a quadrilateral
interface:
.INDENT 3.0
.INDENT 3.5
\fBgauss\-legendre\fP | \fBgauss\-legendre\-lobatto\fP
.UNINDENT
.UNINDENT
.IP 2. 3
\fBquad\-deg\fP \-\-\- degree of quadrature rule for anti\-aliasing on a
quadrilateral interface:
.INDENT 3.0
.INDENT 3.5
\fIint\fP
.UNINDENT
.UNINDENT
.IP 3. 3
\fBquad\-pts\fP \-\-\- name of quadrature rule for anti\-aliasing on a
quadrilateral interface:
.INDENT 3.0
.INDENT 3.5
\fBgauss\-legendre\fP | \fBgauss\-legendre\-lobatto\fP |
\fBwitherden\-vincent\fP
.UNINDENT
.UNINDENT
.UNINDENT
.sp
Example:
.INDENT 0.0
.INDENT 3.5
.sp
.nf
.ft C
[solver\-interfaces\-quad]
flux\-pts = gauss\-legendre
quad\-deg = 10
quad\-pts = gauss\-legendre
.ft P
.fi
.UNINDENT
.UNINDENT
.SS [solver\-elements\-tri]
.sp
Parameterises the triangular elements with
.INDENT 0.0
.IP 1. 3
\fBsoln\-pts\fP \-\-\- location of the solution points in a triangular
element:
.INDENT 3.0
.INDENT 3.5
\fBwilliams\-shunn\fP
.UNINDENT
.UNINDENT
.IP 2. 3
\fBquad\-deg\fP \-\-\- degree of quadrature rule for anti\-aliasing in a
triangular element:
.INDENT 3.0
.INDENT 3.5
\fIint\fP
.UNINDENT
.UNINDENT
.IP 3. 3
\fBquad\-pts\fP \-\-\- name of quadrature rule for anti\-aliasing in a
triangular element:
.INDENT 3.0
.INDENT 3.5
\fBwilliams\-shunn\fP | \fBwitherden\-vincent\fP
.UNINDENT
.UNINDENT
.UNINDENT
.sp
Example:
.INDENT 0.0
.INDENT 3.5
.sp
.nf
.ft C
[solver\-elements\-tri]
soln\-pts = williams\-shunn
quad\-deg = 10
quad\-pts = williams\-shunn
.ft P
.fi
.UNINDENT
.UNINDENT
.SS [solver\-elements\-quad]
.sp
Parameterises the quadrilateral elements with
.INDENT 0.0
.IP 1. 3
\fBsoln\-pts\fP \-\-\- location of the solution points in a quadrilateral
element:
.INDENT 3.0
.INDENT 3.5
\fBgauss\-legendre\fP | \fBgauss\-legendre\-lobatto\fP
.UNINDENT
.UNINDENT
.IP 2. 3
\fBquad\-deg\fP \-\-\- degree of quadrature rule for anti\-aliasing in a
quadrilateral element:
.INDENT 3.0
.INDENT 3.5
\fIint\fP
.UNINDENT
.UNINDENT
.IP 3. 3
\fBquad\-pts\fP \-\-\- name of quadrature rule for anti\-aliasing in a
quadrilateral element:
.INDENT 3.0
.INDENT 3.5
\fBgauss\-legendre\fP | \fBgauss\-legendre\-lobatto\fP |
\fBwitherden\-vincent\fP
.UNINDENT
.UNINDENT
.UNINDENT
.sp
Example:
.INDENT 0.0
.INDENT 3.5
.sp
.nf
.ft C
[solver\-elements\-quad]
soln\-pts = gauss\-legendre
quad\-deg = 10
quad\-pts = gauss\-legendre
.ft P
.fi
.UNINDENT
.UNINDENT
.SS [solver\-elements\-hex]
.sp
Parameterises the hexahedral elements with
.INDENT 0.0
.IP 1. 3
\fBsoln\-pts\fP \-\-\- location of the solution points in a hexahedral
element:
.INDENT 3.0
.INDENT 3.5
\fBgauss\-legendre\fP | \fBgauss\-legendre\-lobatto\fP
.UNINDENT
.UNINDENT
.IP 2. 3
\fBquad\-deg\fP \-\-\- degree of quadrature rule for anti\-aliasing in a
hexahedral element:
.INDENT 3.0
.INDENT 3.5
\fIint\fP
.UNINDENT
.UNINDENT
.IP 3. 3
\fBquad\-pts\fP \-\-\- name of quadrature rule for anti\-aliasing in a
hexahedral element:
.INDENT 3.0
.INDENT 3.5
\fBgauss\-legendre\fP | \fBgauss\-legendre\-lobatto\fP |
\fBwitherden\-vincent\fP
.UNINDENT
.UNINDENT
.UNINDENT
.sp
Example:
.INDENT 0.0
.INDENT 3.5
.sp
.nf
.ft C
[solver\-elements\-hex]
soln\-pts = gauss\-legendre
quad\-deg = 10
quad\-pts = gauss\-legendre
.ft P
.fi
.UNINDENT
.UNINDENT
.SS [solver\-elements\-tet]
.sp
Parameterises the tetrahedral elements with
.INDENT 0.0
.IP 1. 3
\fBsoln\-pts\fP \-\-\- location of the solution points in a tetrahedral
element:
.INDENT 3.0
.INDENT 3.5
\fBshunn\-ham\fP
.UNINDENT
.UNINDENT
.IP 2. 3
\fBquad\-deg\fP \-\-\- degree of quadrature rule for anti\-aliasing in a
tetrahedral element:
.INDENT 3.0
.INDENT 3.5
\fIint\fP
.UNINDENT
.UNINDENT
.IP 3. 3
\fBquad\-pts\fP \-\-\- name of quadrature rule for anti\-aliasing in a
tetrahedral element:
.INDENT 3.0
.INDENT 3.5
\fBshunn\-ham\fP | \fBwitherden\-vincent\fP
.UNINDENT
.UNINDENT
.UNINDENT
.sp
Example:
.INDENT 0.0
.INDENT 3.5
.sp
.nf
.ft C
[solver\-elements\-tet]
soln\-pts = shunn\-ham
quad\-deg = 10
quad\-pts = shunn\-ham
.ft P
.fi
.UNINDENT
.UNINDENT
.SS [solver\-elements\-pri]
.sp
Parameterises the prismatic elements with
.INDENT 0.0
.IP 1. 3
\fBsoln\-pts\fP \-\-\- location of the solution points in a prismatic
element:
.INDENT 3.0
.INDENT 3.5
\fBwilliams\-shunn~gauss\-legendre\fP |
\fBwilliams\-shunn~gauss\-legendre\-lobatto\fP
.UNINDENT
.UNINDENT
.IP 2. 3
\fBquad\-deg\fP \-\-\- degree of quadrature rule for anti\-aliasing in a
prismatic element:
.INDENT 3.0
.INDENT 3.5
\fIint\fP
.UNINDENT
.UNINDENT
.IP 3. 3
\fBquad\-pts\fP \-\-\- name of quadrature rule for anti\-aliasing in a
prismatic element:
.INDENT 3.0
.INDENT 3.5
\fBwilliams\-shunn~gauss\-legendre\fP |
\fBwilliams\-shunn~gauss\-legendre\-lobatto\fP | \fBwitherden\-vincent\fP
.UNINDENT
.UNINDENT
.UNINDENT
.sp
Example:
.INDENT 0.0
.INDENT 3.5
.sp
.nf
.ft C
[solver\-elements\-pri]
soln\-pts = williams\-shunn~gauss\-legendre
quad\-deg = 10
quad\-pts = williams\-shunn~gauss\-legendre
.ft P
.fi
.UNINDENT
.UNINDENT
.SS [solver\-elements\-pyr]
.sp
Parameterises the pyramidal elements with
.INDENT 0.0
.IP 1. 3
\fBsoln\-pts\fP \-\-\- location of the solution points in a pyramidal
element:
.INDENT 3.0
.INDENT 3.5
\fBgauss\-legendre\fP | \fBgauss\-legendre\-lobatto\fP
.UNINDENT
.UNINDENT
.IP 2. 3
\fBquad\-deg\fP \-\-\- degree of quadrature rule for anti\-aliasing in a
pyramidal element:
.INDENT 3.0
.INDENT 3.5
\fIint\fP
.UNINDENT
.UNINDENT
.IP 3. 3
\fBquad\-pts\fP \-\-\- name of quadrature rule for anti\-aliasing in a
pyramidal element:
.INDENT 3.0
.INDENT 3.5
\fBwitherden\-vincent\fP
.UNINDENT
.UNINDENT
.UNINDENT
.sp
Example:
.INDENT 0.0
.INDENT 3.5
.sp
.nf
.ft C
[solver\-elements\-pyr]
soln\-pts = gauss\-legendre
quad\-deg = 10
quad\-pts = witherden\-vincent
.ft P
.fi
.UNINDENT
.UNINDENT
.SS [solver\-source\-terms]
.sp
Parameterises solution, space (x, y, [z]), and time (t) dependent
source terms with
.INDENT 0.0
.IP 1. 3
\fBrho\fP \-\-\- density source term:
.INDENT 3.0
.INDENT 3.5
\fIstring\fP
.UNINDENT
.UNINDENT
.IP 2. 3
\fBrhou\fP \-\-\- x\-momentum source term:
.INDENT 3.0
.INDENT 3.5
\fIstring\fP
.UNINDENT
.UNINDENT
.IP 3. 3
\fBrhov\fP \-\-\- y\-momentum source term:
.INDENT 3.0
.INDENT 3.5
\fIstring\fP
.UNINDENT
.UNINDENT
.IP 4. 3
\fBrhow\fP \-\-\- z\-momentum source term:
.INDENT 3.0
.INDENT 3.5
\fIstring\fP
.UNINDENT
.UNINDENT
.IP 5. 3
\fBE\fP \-\-\- energy source term:
.INDENT 3.0
.INDENT 3.5
\fIstring\fP
.UNINDENT
.UNINDENT
.UNINDENT
.sp
Example:
.INDENT 0.0
.INDENT 3.5
.sp
.nf
.ft C
[solver\-source\-terms]
rho = t
rhou = x*y*sin(y)
rhov = z*rho
rhow = 1.0
E = 1.0/(1.0+x)
.ft P
.fi
.UNINDENT
.UNINDENT
.SS [solver\-artificial\-viscosity]
.sp
Parameterises artificial viscosity for shock capturing with
.INDENT 0.0
.IP 1. 3
\fBmax\-artvisc\fP \-\-\- maximum artificial viscosity:
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP
.UNINDENT
.UNINDENT
.IP 2. 3
\fBs0\fP \-\-\- sensor cut\-off:
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP
.UNINDENT
.UNINDENT
.IP 3. 3
\fBkappa\fP \-\-\- sensor range:
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP
.UNINDENT
.UNINDENT
.UNINDENT
.sp
Example:
.INDENT 0.0
.INDENT 3.5
.sp
.nf
.ft C
[solver\-artificial\-viscosity]
max\-artvisc = 0.01
s0 = 0.01
kappa = 5.0
.ft P
.fi
.UNINDENT
.UNINDENT
.SS [soln\-filter]
.sp
Parameterises an exponential solution filter with
.INDENT 0.0
.IP 1. 3
\fBnsteps\fP \-\-\- apply filter every \fBnsteps\fP:
.INDENT 3.0
.INDENT 3.5
\fIint\fP
.UNINDENT
.UNINDENT
.IP 2. 3
\fBalpha\fP \-\-\- strength of filter:
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP
.UNINDENT
.UNINDENT
.IP 3. 3
\fBorder\fP \-\-\- order of filter:
.INDENT 3.0
.INDENT 3.5
\fIint\fP
.UNINDENT
.UNINDENT
.IP 4. 3
\fBcutoff\fP \-\-\- cutoff frequency below which no filtering is applied:
.INDENT 3.0
.INDENT 3.5
\fIint\fP
.UNINDENT
.UNINDENT
.UNINDENT
.sp
Example:
.INDENT 0.0
.INDENT 3.5
.sp
.nf
.ft C
[soln\-filter]
nsteps = 10
alpha = 36.0
order = 16
cutoff = 1
.ft P
.fi
.UNINDENT
.UNINDENT
.SS [soln\-plugin\-writer]
.sp
Periodically write the solution to disk in the pyfrs format.
Parameterised with
.INDENT 0.0
.IP 1. 3
\fBdt\-out\fP \-\-\- write to disk every \fBdt\-out\fP time units:
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP
.UNINDENT
.UNINDENT
.IP 2. 3
\fBbasedir\fP \-\-\- relative path to directory where outputs will be
written:
.INDENT 3.0
.INDENT 3.5
\fIstring\fP
.UNINDENT
.UNINDENT
.IP 3. 3
\fBbasename\fP \-\-\- pattern of output names:
.INDENT 3.0
.INDENT 3.5
\fIstring\fP
.UNINDENT
.UNINDENT
.IP 4. 3
\fBpost\-action\fP \-\-\- command to execute after writing the file:
.INDENT 3.0
.INDENT 3.5
\fIstring\fP
.UNINDENT
.UNINDENT
.IP 5. 3
\fBpost\-action\-mode\fP \-\-\- how the post\-action command should be
executed:
.INDENT 3.0
.INDENT 3.5
\fBblocking\fP | \fBnon\-blocking\fP
.UNINDENT
.UNINDENT
.UNINDENT
.sp
Example:
.INDENT 0.0
.INDENT 3.5
.sp
.nf
.ft C
[soln\-plugin\-writer]
dt\-out = 0.01
basedir = .
basename = files\-{t:.2f}
post\-action = echo "Wrote file {soln} at time {t} for mesh {mesh}."
post\-action\-mode = blocking
.ft P
.fi
.UNINDENT
.UNINDENT
.SS [soln\-plugin\-fluidforce\-name]
.sp
Periodically integrates the pressure and viscous stress on the boundary
labelled \fBname\fP and writes out the resulting force vectors to a CSV
file. Parameterised with
.INDENT 0.0
.IP 1. 3
\fBnsteps\fP \-\-\- integrate every \fBnsteps\fP:
.INDENT 3.0
.INDENT 3.5
\fIint\fP
.UNINDENT
.UNINDENT
.IP 2. 3
\fBfile\fP \-\-\- output file path; should the file already exist it
will be appended to:
.INDENT 3.0
.INDENT 3.5
\fIstring\fP
.UNINDENT
.UNINDENT
.IP 3. 3
\fBheader\fP \-\-\- if to output a header row or not:
.INDENT 3.0
.INDENT 3.5
\fIboolean\fP
.UNINDENT
.UNINDENT
.UNINDENT
.sp
Example:
.INDENT 0.0
.INDENT 3.5
.sp
.nf
.ft C
[soln\-plugin\-fluidforce\-wing]
nsteps = 10
file = wing\-forces.csv
header = true
.ft P
.fi
.UNINDENT
.UNINDENT
.SS [soln\-plugin\-nancheck]
.sp
Periodically checks the solution for NaN values. Parameterised with
.INDENT 0.0
.IP 1. 3
\fBnsteps\fP \-\-\- check every \fBnsteps\fP:
.INDENT 3.0
.INDENT 3.5
\fIint\fP
.UNINDENT
.UNINDENT
.UNINDENT
.sp
Example:
.INDENT 0.0
.INDENT 3.5
.sp
.nf
.ft C
[soln\-plugin\-nancheck]
nsteps = 10
.ft P
.fi
.UNINDENT
.UNINDENT
.SS [soln\-plugin\-residual]
.sp
Periodically calculates the residual and writes it out to a CSV file.
Parameterised with
.INDENT 0.0
.IP 1. 3
\fBnsteps\fP \-\-\- calculate every \fBnsteps\fP:
.INDENT 3.0
.INDENT 3.5
\fIint\fP
.UNINDENT
.UNINDENT
.IP 2. 3
\fBfile\fP \-\-\- output file path; should the file already exist it
will be appended to:
.INDENT 3.0
.INDENT 3.5
\fIstring\fP
.UNINDENT
.UNINDENT
.IP 3. 3
\fBheader\fP \-\-\- if to output a header row or not:
.INDENT 3.0
.INDENT 3.5
\fIboolean\fP
.UNINDENT
.UNINDENT
.UNINDENT
.sp
Example:
.INDENT 0.0
.INDENT 3.5
.sp
.nf
.ft C
[soln\-plugin\-residual]
nsteps = 10
file = residual.csv
header = true
.ft P
.fi
.UNINDENT
.UNINDENT
.SS [soln\-plugin\-dtstats]
.sp
Write time\-step statistics out to a CSV file. Parameterised with
.INDENT 0.0
.IP 1. 3
\fBflushsteps\fP \-\-\- flush to disk every \fBflushsteps\fP:
.INDENT 3.0
.INDENT 3.5
\fIint\fP
.UNINDENT
.UNINDENT
.IP 2. 3
\fBfile\fP \-\-\- output file path; should the file already exist it
will be appended to:
.INDENT 3.0
.INDENT 3.5
\fIstring\fP
.UNINDENT
.UNINDENT
.IP 3. 3
\fBheader\fP \-\-\- if to output a header row or not:
.INDENT 3.0
.INDENT 3.5
\fIboolean\fP
.UNINDENT
.UNINDENT
.UNINDENT
.sp
Example:
.INDENT 0.0
.INDENT 3.5
.sp
.nf
.ft C
[soln\-plugin\-dtstats]
flushsteps = 100
file = dtstats.csv
header = true
.ft P
.fi
.UNINDENT
.UNINDENT
.SS [soln\-plugin\-sampler]
.sp
Periodically samples specific points in the volume and writes them out
to a CSV file.  The plugin actually samples the solution point
closest to each sample point, hence a slight discrepancy in the output
sampling locations is to be expected.  A nearest\-neighbour search is
used to locate the closest solution point to the sample point.  The
location process automatically takes advantage of
\fI\%scipy.spatial.cKDTree\fP
where available.  Parameterised with
.INDENT 0.0
.IP 1. 3
\fBnsteps\fP \-\-\- sample every \fBnsteps\fP:
.INDENT 3.0
.INDENT 3.5
\fIint\fP
.UNINDENT
.UNINDENT
.IP 2. 3
\fBsamp\-pts\fP \-\-\- list of points to sample:
.INDENT 3.0
.INDENT 3.5
\fB[(x, y), (x, y), ...]\fP | \fB[(x, y, z), (x, y, z), ...]\fP
.UNINDENT
.UNINDENT
.IP 3. 3
\fBformat\fP \-\-\- output variable format:
.INDENT 3.0
.INDENT 3.5
\fBprimitive\fP | \fBconservative\fP
.UNINDENT
.UNINDENT
.IP 4. 3
\fBfile\fP \-\-\- output file path; should the file already exist it
will be appended to:
.INDENT 3.0
.INDENT 3.5
\fIstring\fP
.UNINDENT
.UNINDENT
.IP 5. 3
\fBheader\fP \-\-\- if to output a header row or not:
.INDENT 3.0
.INDENT 3.5
\fIboolean\fP
.UNINDENT
.UNINDENT
.UNINDENT
.sp
Example:
.INDENT 0.0
.INDENT 3.5
.sp
.nf
.ft C
[soln\-plugin\-sampler]
nsteps = 10
samp\-pts = [(1.0, 0.7, 0.0), (1.0, 0.8, 0.0)]
format = primative
file = point\-data.csv
header = true
.ft P
.fi
.UNINDENT
.UNINDENT
.SS [soln\-plugin\-tavg]
.sp
Time average quantities. Parameterised with
.INDENT 0.0
.IP 1. 3
\fBnsteps\fP \-\-\- accumulate the average every \fBnsteps\fP time steps:
.INDENT 3.0
.INDENT 3.5
\fIint\fP
.UNINDENT
.UNINDENT
.IP 2. 3
\fBdt\-out\fP \-\-\- write to disk every \fBdt\-out\fP time units:
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP
.UNINDENT
.UNINDENT
.IP 3. 3
\fBbasedir\fP \-\-\- relative path to directory where outputs will be
written:
.INDENT 3.0
.INDENT 3.5
\fIstring\fP
.UNINDENT
.UNINDENT
.IP 4. 3
\fBbasename\fP \-\-\- pattern of output names:
.INDENT 3.0
.INDENT 3.5
\fIstring\fP
.UNINDENT
.UNINDENT
.IP 5. 3
\fBavg\-name\fP \-\-\- expression as a function of the primitive variables,
time (t), and space (x, y, [z]) to time average; multiple
expressions, each with their own \fIname\fP, may be specified:
.INDENT 3.0
.INDENT 3.5
\fIstring\fP
.UNINDENT
.UNINDENT
.UNINDENT
.sp
Example:
.INDENT 0.0
.INDENT 3.5
.sp
.nf
.ft C
[soln\-plugin\-tavg]
nsteps = 10
dt\-out = 2.0
basedir = .
basename = files\-{t:06.2f}

avg\-p = p
avg\-p2 = p*p
avg\-vel = sqrt(u*u + v*v)
.ft P
.fi
.UNINDENT
.UNINDENT
.SS [soln\-bcs\-name]
.sp
Parameterises constant, or if available space (x, y, [z]) and time (t)
dependent, boundary condition labelled \fBname\fP in the .pyfrm file
with
.INDENT 0.0
.IP 1. 3
\fBtype\fP \-\-\- type of boundary condition:
.INDENT 3.0
.INDENT 3.5
\fBchar\-riem\-inv\fP | \fBno\-slp\-adia\-wall\fP | \fBno\-slp\-isot\-wall\fP |
\fBslp\-adia\-wall\fP | \fBsub\-in\-frv\fP | \fBsub\-in\-ftpttang\fP |
\fBsub\-out\-fp\fP | \fBsup\-in\-fa\fP | \fBsup\-out\-fn\fP
.sp
where
.sp
\fBchar\-riem\-inv\fP requires
.INDENT 0.0
.INDENT 3.5
.INDENT 0.0
.IP \(bu 2
\fBrho\fP \-\-\- density
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP | \fIstring\fP
.UNINDENT
.UNINDENT
.IP \(bu 2
\fBu\fP \-\-\- x\-velocity
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP | \fIstring\fP
.UNINDENT
.UNINDENT
.IP \(bu 2
\fBv\fP \-\-\- y\-velocity
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP | \fIstring\fP
.UNINDENT
.UNINDENT
.IP \(bu 2
\fBw\fP \-\-\- z\-velocity
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP | \fIstring\fP
.UNINDENT
.UNINDENT
.IP \(bu 2
\fBp\fP \-\-\- static pressure
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP | \fIstring\fP
.UNINDENT
.UNINDENT
.UNINDENT
.UNINDENT
.UNINDENT
.sp
\fBno\-slp\-isot\-wall\fP requires
.INDENT 0.0
.INDENT 3.5
.INDENT 0.0
.IP \(bu 2
\fBu\fP \-\-\- x\-velocity of wall
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP
.UNINDENT
.UNINDENT
.IP \(bu 2
\fBv\fP \-\-\- y\-velocity of wall
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP
.UNINDENT
.UNINDENT
.IP \(bu 2
\fBw\fP \-\-\- z\-velocity of wall
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP
.UNINDENT
.UNINDENT
.IP \(bu 2
\fBcpTw\fP \-\-\- product of specific heat capacity at constant
pressure and temperature of wall
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP
.UNINDENT
.UNINDENT
.UNINDENT
.UNINDENT
.UNINDENT
.sp
\fBsub\-in\-frv\fP requires
.INDENT 0.0
.INDENT 3.5
.INDENT 0.0
.IP \(bu 2
\fBrho\fP \-\-\- density
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP | \fIstring\fP
.UNINDENT
.UNINDENT
.IP \(bu 2
\fBu\fP \-\-\- x\-velocity
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP | \fIstring\fP
.UNINDENT
.UNINDENT
.IP \(bu 2
\fBv\fP \-\-\- y\-velocity
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP | \fIstring\fP
.UNINDENT
.UNINDENT
.IP \(bu 2
\fBw\fP \-\-\- z\-velocity
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP | \fIstring\fP
.UNINDENT
.UNINDENT
.UNINDENT
.UNINDENT
.UNINDENT
.sp
\fBsub\-in\-ftpttang\fP requires
.INDENT 0.0
.INDENT 3.5
.INDENT 0.0
.IP \(bu 2
\fBpt\fP \-\-\- total pressure
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP
.UNINDENT
.UNINDENT
.IP \(bu 2
\fBcpTt\fP \-\-\- product of specific heat capacity at constant
pressure and total temperature
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP
.UNINDENT
.UNINDENT
.IP \(bu 2
\fBtheta\fP \-\-\- azimuth angle (in degrees) of inflow measured
in the x\-y plane relative to the positive x\-axis
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP
.UNINDENT
.UNINDENT
.IP \(bu 2
\fBphi\fP \-\-\- inclination angle (in degrees) of inflow measured
relative to the positive z\-axis
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP
.UNINDENT
.UNINDENT
.UNINDENT
.UNINDENT
.UNINDENT
.sp
\fBsub\-out\-fp\fP requires
.INDENT 0.0
.INDENT 3.5
.INDENT 0.0
.IP \(bu 2
\fBp\fP \-\-\- static pressure
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP | \fIstring\fP
.UNINDENT
.UNINDENT
.UNINDENT
.UNINDENT
.UNINDENT
.sp
\fBsup\-in\-fa\fP requires
.INDENT 0.0
.INDENT 3.5
.INDENT 0.0
.IP \(bu 2
\fBrho\fP \-\-\- density
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP | \fIstring\fP
.UNINDENT
.UNINDENT
.IP \(bu 2
\fBu\fP \-\-\- x\-velocity
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP | \fIstring\fP
.UNINDENT
.UNINDENT
.IP \(bu 2
\fBv\fP \-\-\- y\-velocity
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP | \fIstring\fP
.UNINDENT
.UNINDENT
.IP \(bu 2
\fBw\fP \-\-\- z\-velocity
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP | \fIstring\fP
.UNINDENT
.UNINDENT
.IP \(bu 2
\fBp\fP \-\-\- static pressure
.INDENT 3.0
.INDENT 3.5
\fIfloat\fP | \fIstring\fP
.UNINDENT
.UNINDENT
.UNINDENT
.UNINDENT
.UNINDENT
.UNINDENT
.UNINDENT
.UNINDENT
.sp
Example:
.INDENT 0.0
.INDENT 3.5
.sp
.nf
.ft C
[soln\-bcs\-bcwallupper]
type = no\-slp\-isot\-wall
cpTw = 10.0
u = 1.0
.ft P
.fi
.UNINDENT
.UNINDENT
.SS [soln\-ics]
.sp
Parameterises space (x, y, [z]) dependent initial conditions with
.INDENT 0.0
.IP 1. 3
\fBrho\fP \-\-\- initial density distribution:
.INDENT 3.0
.INDENT 3.5
\fIstring\fP
.UNINDENT
.UNINDENT
.IP 2. 3
\fBu\fP \-\-\- initial x\-velocity distribution:
.INDENT 3.0
.INDENT 3.5
\fIstring\fP
.UNINDENT
.UNINDENT
.IP 3. 3
\fBv\fP \-\-\- initial y\-velocity distribution:
.INDENT 3.0
.INDENT 3.5
\fIstring\fP
.UNINDENT
.UNINDENT
.IP 4. 3
\fBw\fP \-\-\- initial z\-velocity distribution:
.INDENT 3.0
.INDENT 3.5
\fIstring\fP
.UNINDENT
.UNINDENT
.IP 5. 3
\fBp\fP \-\-\- initial static pressure distribution:
.INDENT 3.0
.INDENT 3.5
\fIstring\fP
.UNINDENT
.UNINDENT
.UNINDENT
.sp
Example:
.INDENT 0.0
.INDENT 3.5
.sp
.nf
.ft C
[soln\-ics]
rho = 1.0
u = x*y*sin(y)
v = z
w = 1.0
p = 1.0/(1.0+x)
.ft P
.fi
.UNINDENT
.UNINDENT
.SS Example \-\-\- 2D Couette Flow
.sp
Proceed with the following steps to run a serial 2D Couette flow
simulation on a mixed unstructured mesh:
.INDENT 0.0
.IP 1. 3
Create a working directory called \fBcouette_flow_2d/\fP
.IP 2. 3
Copy the configuration file
\fBPyFR/examples/couette_flow_2d/couette_flow_2d.ini\fP into
\fBcouette_flow_2d/\fP
.IP 3. 3
Copy the \fI\%Gmsh\fP mesh file
\fBPyFR/examples/couette_flow_2d/couette_flow_2d.msh\fP into
\fBcouette_flow_2d/\fP
.IP 4. 3
Run pyfr to covert the \fI\%Gmsh\fP
mesh file into a PyFR mesh file called \fBcouette_flow_2d.pyfrm\fP:
.INDENT 3.0
.INDENT 3.5
.sp
.nf
.ft C
pyfr import couette_flow_2d.msh couette_flow_2d.pyfrm
.ft P
.fi
.UNINDENT
.UNINDENT
.IP 5. 3
Run pyfr to solve the Navier\-Stokes equations on the mesh,
generating a series of PyFR solution files called
\fBcouette_flow_2d\-*.pyfrs\fP:
.INDENT 3.0
.INDENT 3.5
.sp
.nf
.ft C
pyfr run \-b cuda \-p couette_flow_2d.pyfrm couette_flow_2d.ini
.ft P
.fi
.UNINDENT
.UNINDENT
.IP 6. 3
Run pyfr on the solution file \fBcouette_flow_2d\-040.pyfrs\fP
converting it into an unstructured VTK file called
\fBcouette_flow_2d\-040.vtu\fP\&. Note that in order to visualise the
high\-order data, each high\-order element is sub\-divided into smaller
linear elements. The level of sub\-division is controlled by the
integer at the end of the command:
.INDENT 3.0
.INDENT 3.5
.sp
.nf
.ft C
pyfr export couette_flow_2d.pyfrm couette_flow_2d\-040.pyfrs couette_flow_2d\-040.vtu \-d 4
.ft P
.fi
.UNINDENT
.UNINDENT
.IP 7. 3
Visualise the unstructured VTK file in \fI\%Paraview\fP
.UNINDENT
.INDENT 0.0
.INDENT 2.5
[image: couette flow]
[image]
Colour map of steady\-state density distribution..UNINDENT
.UNINDENT
.SS Example \-\-\- 2D Euler Vortex
.sp
Proceed with the following steps to run a parallel 2D Euler vortex
simulation on a structured mesh:
.INDENT 0.0
.IP 1. 3
Create a working directory called \fBeuler_vortex_2d/\fP
.IP 2. 3
Copy the configuration file
\fBPyFR/examples/euler_vortex_2d/euler_vortex_2d.ini\fP into
\fBeuler_vortex_2d/\fP
.IP 3. 3
Copy the \fI\%Gmsh\fP file
\fBPyFR/examples/euler_vortex_2d/euler_vortex_2d.msh\fP into
\fBeuler_vortex_2d/\fP
.IP 4. 3
Run pyfr to convert the \fI\%Gmsh\fP
mesh file into a PyFR mesh file called \fBeuler_vortex_2d.pyfrm\fP:
.INDENT 3.0
.INDENT 3.5
.sp
.nf
.ft C
pyfr import euler_vortex_2d.msh euler_vortex_2d.pyfrm
.ft P
.fi
.UNINDENT
.UNINDENT
.IP 5. 3
Run pyfr to partition the PyFR mesh file into two pieces:
.INDENT 3.0
.INDENT 3.5
.sp
.nf
.ft C
pyfr partition 2 euler_vortex_2d.pyfrm .
.ft P
.fi
.UNINDENT
.UNINDENT
.IP 6. 3
Run pyfr to solve the Euler equations on the mesh, generating a
series of PyFR solution files called \fBeuler_vortex_2d*.pyfrs\fP:
.INDENT 3.0
.INDENT 3.5
.sp
.nf
.ft C
mpirun \-n 2 pyfr run \-b cuda \-p euler_vortex_2d.pyfrm euler_vortex_2d.ini
.ft P
.fi
.UNINDENT
.UNINDENT
.IP 7. 3
Run pyfr on the solution file \fBeuler_vortex_2d\-100.0.pyfrs\fP
converting it into an unstructured VTK file called
\fBeuler_vortex_2d\-100.0.vtu\fP\&. Note that in order to visualise the
high\-order data, each high\-order element is sub\-divided into smaller
linear elements. The level of sub\-division is controlled by the
integer at the end of the command:
.INDENT 3.0
.INDENT 3.5
.sp
.nf
.ft C
pyfr export euler_vortex_2d.pyfrm euler_vortex_2d\-100.0.pyfrs euler_vortex_2d\-100.0.vtu \-d 4
.ft P
.fi
.UNINDENT
.UNINDENT
.IP 8. 3
Visualise the unstructured VTK file in \fI\%Paraview\fP
.UNINDENT
.INDENT 0.0
.INDENT 2.5
[image: euler vortex]
[image]
Colour map of density distribution at 100 time units..UNINDENT
.UNINDENT
.SH DEVELOPER GUIDE
.SS A Brief Overview of the PyFR Framework
.SS Where to Start
.sp
The symbolic link \fBpyfr.scripts.pyfr\fP points to the script
\fBpyfr.scripts.main\fP, which is where it all starts! Specifically,
the function \fBprocess_run\fP calls the function
\fB_process_common\fP, which in turn calls the function
\fBget_solver\fP, returning an Integrator \-\- a composite of a
\fI\%Controller\fP and a \fI\%Stepper\fP\&. The Integrator has a method named
\fBrun\fP, which is then called to run the simulation.
.SS Controller
.sp
A \fI\%Controller\fP acts to advance the simulation in time. Specifically, a
\fI\%Controller\fP has a method named \fBadvance_to\fP which advances a
\fI\%System\fP to a specified time. There are three types of \fI\%Controller\fP
available in PyFR 1.5.0:
.INDENT 0.0
.TP
.B class pyfr.integrators.std.controllers.StdNoneController(*args, **kwargs)
.INDENT 7.0
.TP
.B _abc_impl = <_abc_data object>
.UNINDENT
.INDENT 7.0
.TP
.B _accept_step(dt, idxcurr, err=None)
.UNINDENT
.INDENT 7.0
.TP
.B _add(*args)
.UNINDENT
.INDENT 7.0
.TP
.B _controller_needs_errest
.UNINDENT
.INDENT 7.0
.TP
.B _get_axnpby_kerns(n, subdims=None)
.UNINDENT
.INDENT 7.0
.TP
.B _get_gndofs()
.UNINDENT
.INDENT 7.0
.TP
.B _get_kernels(name, nargs, **kwargs)
.UNINDENT
.INDENT 7.0
.TP
.B _get_plugins()
.UNINDENT
.INDENT 7.0
.TP
.B _get_reg_banks(nreg)
.UNINDENT
.INDENT 7.0
.TP
.B _prepare_reg_banks(*bidxes)
.UNINDENT
.INDENT 7.0
.TP
.B _reject_step(dt, idxold, err=None)
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_has_errest
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_nfevals
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_nregs
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_order
.UNINDENT
.INDENT 7.0
.TP
.B advance_to(t)
.UNINDENT
.INDENT 7.0
.TP
.B call_plugin_dt(dt)
.UNINDENT
.INDENT 7.0
.TP
.B cfgmeta
.UNINDENT
.INDENT 7.0
.TP
.B collect_stats(stats)
.UNINDENT
.INDENT 7.0
.TP
.B controller_name = \(aqnone\(aq
.UNINDENT
.INDENT 7.0
.TP
.B formulation = \(aqstd\(aq
.UNINDENT
.INDENT 7.0
.TP
.B nsteps
.UNINDENT
.INDENT 7.0
.TP
.B run()
.UNINDENT
.INDENT 7.0
.TP
.B soln
.UNINDENT
.INDENT 7.0
.TP
.B step(t, dt)
.UNINDENT
.UNINDENT
.INDENT 0.0
.TP
.B class pyfr.integrators.std.controllers.StdPIController(*args, **kwargs)
.INDENT 7.0
.TP
.B _abc_impl = <_abc_data object>
.UNINDENT
.INDENT 7.0
.TP
.B _accept_step(dt, idxcurr, err=None)
.UNINDENT
.INDENT 7.0
.TP
.B _add(*args)
.UNINDENT
.INDENT 7.0
.TP
.B _controller_needs_errest
.UNINDENT
.INDENT 7.0
.TP
.B _errest(x, y, z)
.UNINDENT
.INDENT 7.0
.TP
.B _get_axnpby_kerns(n, subdims=None)
.UNINDENT
.INDENT 7.0
.TP
.B _get_errest_kerns()
.UNINDENT
.INDENT 7.0
.TP
.B _get_gndofs()
.UNINDENT
.INDENT 7.0
.TP
.B _get_kernels(name, nargs, **kwargs)
.UNINDENT
.INDENT 7.0
.TP
.B _get_plugins()
.UNINDENT
.INDENT 7.0
.TP
.B _get_reg_banks(nreg)
.UNINDENT
.INDENT 7.0
.TP
.B _prepare_reg_banks(*bidxes)
.UNINDENT
.INDENT 7.0
.TP
.B _reject_step(dt, idxold, err=None)
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_has_errest
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_nfevals
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_nregs
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_order
.UNINDENT
.INDENT 7.0
.TP
.B advance_to(t)
.UNINDENT
.INDENT 7.0
.TP
.B call_plugin_dt(dt)
.UNINDENT
.INDENT 7.0
.TP
.B cfgmeta
.UNINDENT
.INDENT 7.0
.TP
.B collect_stats(stats)
.UNINDENT
.INDENT 7.0
.TP
.B controller_name = \(aqpi\(aq
.UNINDENT
.INDENT 7.0
.TP
.B formulation = \(aqstd\(aq
.UNINDENT
.INDENT 7.0
.TP
.B nsteps
.UNINDENT
.INDENT 7.0
.TP
.B run()
.UNINDENT
.INDENT 7.0
.TP
.B soln
.UNINDENT
.INDENT 7.0
.TP
.B step(t, dt)
.UNINDENT
.UNINDENT
.INDENT 0.0
.TP
.B class pyfr.integrators.dual.controllers.DualNoneController(*args, **kwargs)
.INDENT 7.0
.TP
.B _abc_impl = <_abc_data object>
.UNINDENT
.INDENT 7.0
.TP
.B _accept_step(dt, idxcurr)
.UNINDENT
.INDENT 7.0
.TP
.B _add(*args)
.UNINDENT
.INDENT 7.0
.TP
.B _dual_time_source()
.UNINDENT
.INDENT 7.0
.TP
.B _get_axnpby_kerns(n, subdims=None)
.UNINDENT
.INDENT 7.0
.TP
.B _get_errest_kerns()
.UNINDENT
.INDENT 7.0
.TP
.B _get_gndofs()
.UNINDENT
.INDENT 7.0
.TP
.B _get_kernels(name, nargs, **kwargs)
.UNINDENT
.INDENT 7.0
.TP
.B _get_plugins()
.UNINDENT
.INDENT 7.0
.TP
.B _get_reg_banks(nreg)
.UNINDENT
.INDENT 7.0
.TP
.B _prepare_reg_banks(*bidxes)
.UNINDENT
.INDENT 7.0
.TP
.B _resid(x, y)
.UNINDENT
.INDENT 7.0
.TP
.B _source_regidx
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_nfevals
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_nregs
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_order
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_regidx
.UNINDENT
.INDENT 7.0
.TP
.B advance_to(t)
.UNINDENT
.INDENT 7.0
.TP
.B call_plugin_dt(dt)
.UNINDENT
.INDENT 7.0
.TP
.B cfgmeta
.UNINDENT
.INDENT 7.0
.TP
.B collect_stats(stats)
.UNINDENT
.INDENT 7.0
.TP
.B controller_name = \(aqnone\(aq
.UNINDENT
.INDENT 7.0
.TP
.B finalise_step(currsoln)
.UNINDENT
.INDENT 7.0
.TP
.B formulation = \(aqdual\(aq
.UNINDENT
.INDENT 7.0
.TP
.B nsteps
.UNINDENT
.INDENT 7.0
.TP
.B run()
.UNINDENT
.INDENT 7.0
.TP
.B soln
.UNINDENT
.INDENT 7.0
.TP
.B step(t, dt)
.UNINDENT
.UNINDENT
.sp
Types of \fI\%Controller\fP are related via the following inheritance
diagram:
.SS Stepper
.sp
A \fI\%Stepper\fP acts to advance the simulation by a single time\-step.
Specifically, a \fI\%Stepper\fP has a method named \fBstep\fP which
advances a \fI\%System\fP by a single time\-step. There are 11 types of
\fI\%Stepper\fP available in PyFR 1.5.0:
.INDENT 0.0
.TP
.B class pyfr.integrators.std.steppers.StdEulerStepper(*args, **kwargs)
.INDENT 7.0
.TP
.B _abc_impl = <_abc_data object>
.UNINDENT
.INDENT 7.0
.TP
.B _add(*args)
.UNINDENT
.INDENT 7.0
.TP
.B _controller_needs_errest
.UNINDENT
.INDENT 7.0
.TP
.B _get_axnpby_kerns(n, subdims=None)
.UNINDENT
.INDENT 7.0
.TP
.B _get_gndofs()
.UNINDENT
.INDENT 7.0
.TP
.B _get_kernels(name, nargs, **kwargs)
.UNINDENT
.INDENT 7.0
.TP
.B _get_plugins()
.UNINDENT
.INDENT 7.0
.TP
.B _get_reg_banks(nreg)
.UNINDENT
.INDENT 7.0
.TP
.B _prepare_reg_banks(*bidxes)
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_has_errest
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_nfevals
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_nregs
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_order
.UNINDENT
.INDENT 7.0
.TP
.B advance_to(t)
.UNINDENT
.INDENT 7.0
.TP
.B call_plugin_dt(dt)
.UNINDENT
.INDENT 7.0
.TP
.B cfgmeta
.UNINDENT
.INDENT 7.0
.TP
.B collect_stats(stats)
.UNINDENT
.INDENT 7.0
.TP
.B formulation = \(aqstd\(aq
.UNINDENT
.INDENT 7.0
.TP
.B nsteps
.UNINDENT
.INDENT 7.0
.TP
.B run()
.UNINDENT
.INDENT 7.0
.TP
.B soln
.UNINDENT
.INDENT 7.0
.TP
.B step(t, dt)
.UNINDENT
.INDENT 7.0
.TP
.B stepper_name = \(aqeuler\(aq
.UNINDENT
.UNINDENT
.INDENT 0.0
.TP
.B class pyfr.integrators.std.steppers.StdRK4Stepper(*args, **kwargs)
.INDENT 7.0
.TP
.B _abc_impl = <_abc_data object>
.UNINDENT
.INDENT 7.0
.TP
.B _add(*args)
.UNINDENT
.INDENT 7.0
.TP
.B _controller_needs_errest
.UNINDENT
.INDENT 7.0
.TP
.B _get_axnpby_kerns(n, subdims=None)
.UNINDENT
.INDENT 7.0
.TP
.B _get_gndofs()
.UNINDENT
.INDENT 7.0
.TP
.B _get_kernels(name, nargs, **kwargs)
.UNINDENT
.INDENT 7.0
.TP
.B _get_plugins()
.UNINDENT
.INDENT 7.0
.TP
.B _get_reg_banks(nreg)
.UNINDENT
.INDENT 7.0
.TP
.B _prepare_reg_banks(*bidxes)
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_has_errest
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_nfevals
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_nregs
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_order
.UNINDENT
.INDENT 7.0
.TP
.B advance_to(t)
.UNINDENT
.INDENT 7.0
.TP
.B call_plugin_dt(dt)
.UNINDENT
.INDENT 7.0
.TP
.B cfgmeta
.UNINDENT
.INDENT 7.0
.TP
.B collect_stats(stats)
.UNINDENT
.INDENT 7.0
.TP
.B formulation = \(aqstd\(aq
.UNINDENT
.INDENT 7.0
.TP
.B nsteps
.UNINDENT
.INDENT 7.0
.TP
.B run()
.UNINDENT
.INDENT 7.0
.TP
.B soln
.UNINDENT
.INDENT 7.0
.TP
.B step(t, dt)
.UNINDENT
.INDENT 7.0
.TP
.B stepper_name = \(aqrk4\(aq
.UNINDENT
.UNINDENT
.INDENT 0.0
.TP
.B class pyfr.integrators.std.steppers.StdRK34Stepper(*args, **kwargs)
.INDENT 7.0
.TP
.B _abc_impl = <_abc_data object>
.UNINDENT
.INDENT 7.0
.TP
.B _add(*args)
.UNINDENT
.INDENT 7.0
.TP
.B _controller_needs_errest
.UNINDENT
.INDENT 7.0
.TP
.B _get_axnpby_kerns(n, subdims=None)
.UNINDENT
.INDENT 7.0
.TP
.B _get_gndofs()
.UNINDENT
.INDENT 7.0
.TP
.B _get_kernels(name, nargs, **kwargs)
.UNINDENT
.INDENT 7.0
.TP
.B _get_plugins()
.UNINDENT
.INDENT 7.0
.TP
.B _get_reg_banks(nreg)
.UNINDENT
.INDENT 7.0
.TP
.B _prepare_reg_banks(*bidxes)
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_has_errest
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_nfevals
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_nregs
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_order
.UNINDENT
.INDENT 7.0
.TP
.B a = [0.32416573882874605, 0.5570978645055429, \-0.08605491431272755]
.UNINDENT
.INDENT 7.0
.TP
.B advance_to(t)
.UNINDENT
.INDENT 7.0
.TP
.B b = [0.10407986927510238, 0.6019391368822611, 2.9750900268840206, \-2.681109033041384]
.UNINDENT
.INDENT 7.0
.TP
.B bhat = [0.3406814840808433, 0.09091523008632837, 2.866496742725443, \-2.298093456892615]
.UNINDENT
.INDENT 7.0
.TP
.B call_plugin_dt(dt)
.UNINDENT
.INDENT 7.0
.TP
.B cfgmeta
.UNINDENT
.INDENT 7.0
.TP
.B collect_stats(stats)
.UNINDENT
.INDENT 7.0
.TP
.B formulation = \(aqstd\(aq
.UNINDENT
.INDENT 7.0
.TP
.B nsteps
.UNINDENT
.INDENT 7.0
.TP
.B run()
.UNINDENT
.INDENT 7.0
.TP
.B soln
.UNINDENT
.INDENT 7.0
.TP
.B step(t, dt)
.UNINDENT
.INDENT 7.0
.TP
.B stepper_name = \(aqrk34\(aq
.UNINDENT
.UNINDENT
.INDENT 0.0
.TP
.B class pyfr.integrators.std.steppers.StdRK45Stepper(*args, **kwargs)
.INDENT 7.0
.TP
.B _abc_impl = <_abc_data object>
.UNINDENT
.INDENT 7.0
.TP
.B _add(*args)
.UNINDENT
.INDENT 7.0
.TP
.B _controller_needs_errest
.UNINDENT
.INDENT 7.0
.TP
.B _get_axnpby_kerns(n, subdims=None)
.UNINDENT
.INDENT 7.0
.TP
.B _get_gndofs()
.UNINDENT
.INDENT 7.0
.TP
.B _get_kernels(name, nargs, **kwargs)
.UNINDENT
.INDENT 7.0
.TP
.B _get_plugins()
.UNINDENT
.INDENT 7.0
.TP
.B _get_reg_banks(nreg)
.UNINDENT
.INDENT 7.0
.TP
.B _prepare_reg_banks(*bidxes)
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_has_errest
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_nfevals
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_nregs
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_order
.UNINDENT
.INDENT 7.0
.TP
.B a = [0.22502245872571303, 0.5440433129514047, 0.14456824349399464, 0.7866643421983568]
.UNINDENT
.INDENT 7.0
.TP
.B advance_to(t)
.UNINDENT
.INDENT 7.0
.TP
.B b = [0.05122930664033915, 0.3809548257264019, \-0.3733525963923833, 0.5925012850263623, 0.34866717899927996]
.UNINDENT
.INDENT 7.0
.TP
.B bhat = [0.13721732210321927, 0.19188076232938728, \-0.2292067211595315, 0.6242946765438954, 0.27581396018302956]
.UNINDENT
.INDENT 7.0
.TP
.B call_plugin_dt(dt)
.UNINDENT
.INDENT 7.0
.TP
.B cfgmeta
.UNINDENT
.INDENT 7.0
.TP
.B collect_stats(stats)
.UNINDENT
.INDENT 7.0
.TP
.B formulation = \(aqstd\(aq
.UNINDENT
.INDENT 7.0
.TP
.B nsteps
.UNINDENT
.INDENT 7.0
.TP
.B run()
.UNINDENT
.INDENT 7.0
.TP
.B soln
.UNINDENT
.INDENT 7.0
.TP
.B step(t, dt)
.UNINDENT
.INDENT 7.0
.TP
.B stepper_name = \(aqrk45\(aq
.UNINDENT
.UNINDENT
.INDENT 0.0
.TP
.B class pyfr.integrators.std.steppers.StdTVDRK3Stepper(*args, **kwargs)
.INDENT 7.0
.TP
.B _abc_impl = <_abc_data object>
.UNINDENT
.INDENT 7.0
.TP
.B _add(*args)
.UNINDENT
.INDENT 7.0
.TP
.B _controller_needs_errest
.UNINDENT
.INDENT 7.0
.TP
.B _get_axnpby_kerns(n, subdims=None)
.UNINDENT
.INDENT 7.0
.TP
.B _get_gndofs()
.UNINDENT
.INDENT 7.0
.TP
.B _get_kernels(name, nargs, **kwargs)
.UNINDENT
.INDENT 7.0
.TP
.B _get_plugins()
.UNINDENT
.INDENT 7.0
.TP
.B _get_reg_banks(nreg)
.UNINDENT
.INDENT 7.0
.TP
.B _prepare_reg_banks(*bidxes)
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_has_errest
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_nfevals
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_nregs
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_order
.UNINDENT
.INDENT 7.0
.TP
.B advance_to(t)
.UNINDENT
.INDENT 7.0
.TP
.B call_plugin_dt(dt)
.UNINDENT
.INDENT 7.0
.TP
.B cfgmeta
.UNINDENT
.INDENT 7.0
.TP
.B collect_stats(stats)
.UNINDENT
.INDENT 7.0
.TP
.B formulation = \(aqstd\(aq
.UNINDENT
.INDENT 7.0
.TP
.B nsteps
.UNINDENT
.INDENT 7.0
.TP
.B run()
.UNINDENT
.INDENT 7.0
.TP
.B soln
.UNINDENT
.INDENT 7.0
.TP
.B step(t, dt)
.UNINDENT
.INDENT 7.0
.TP
.B stepper_name = \(aqtvd\-rk3\(aq
.UNINDENT
.UNINDENT
.INDENT 0.0
.TP
.B class pyfr.integrators.dual.steppers.DualBDF2Stepper(*args, **kwargs)
.INDENT 7.0
.TP
.B _abc_impl = <_abc_data object>
.UNINDENT
.INDENT 7.0
.TP
.B _add(*args)
.UNINDENT
.INDENT 7.0
.TP
.B _dual_time_source
.UNINDENT
.INDENT 7.0
.TP
.B _get_axnpby_kerns(n, subdims=None)
.UNINDENT
.INDENT 7.0
.TP
.B _get_gndofs()
.UNINDENT
.INDENT 7.0
.TP
.B _get_kernels(name, nargs, **kwargs)
.UNINDENT
.INDENT 7.0
.TP
.B _get_plugins()
.UNINDENT
.INDENT 7.0
.TP
.B _get_reg_banks(nreg)
.UNINDENT
.INDENT 7.0
.TP
.B _prepare_reg_banks(*bidxes)
.UNINDENT
.INDENT 7.0
.TP
.B _source_regidx
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_nfevals
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_nregs
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_order
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_regidx
.UNINDENT
.INDENT 7.0
.TP
.B advance_to(t)
.UNINDENT
.INDENT 7.0
.TP
.B call_plugin_dt(dt)
.UNINDENT
.INDENT 7.0
.TP
.B cfgmeta
.UNINDENT
.INDENT 7.0
.TP
.B collect_stats(stats)
.UNINDENT
.INDENT 7.0
.TP
.B finalise_step(currsoln)
.UNINDENT
.INDENT 7.0
.TP
.B formulation = \(aqdual\(aq
.UNINDENT
.INDENT 7.0
.TP
.B nsteps
.UNINDENT
.INDENT 7.0
.TP
.B run()
.UNINDENT
.INDENT 7.0
.TP
.B soln
.UNINDENT
.INDENT 7.0
.TP
.B step(t, dt)
.UNINDENT
.INDENT 7.0
.TP
.B stepper_name = \(aqbdf2\(aq
.UNINDENT
.UNINDENT
.INDENT 0.0
.TP
.B class pyfr.integrators.dual.steppers.DualBDF3Stepper(*args, **kwargs)
.INDENT 7.0
.TP
.B _abc_impl = <_abc_data object>
.UNINDENT
.INDENT 7.0
.TP
.B _add(*args)
.UNINDENT
.INDENT 7.0
.TP
.B _dual_time_source
.UNINDENT
.INDENT 7.0
.TP
.B _get_axnpby_kerns(n, subdims=None)
.UNINDENT
.INDENT 7.0
.TP
.B _get_gndofs()
.UNINDENT
.INDENT 7.0
.TP
.B _get_kernels(name, nargs, **kwargs)
.UNINDENT
.INDENT 7.0
.TP
.B _get_plugins()
.UNINDENT
.INDENT 7.0
.TP
.B _get_reg_banks(nreg)
.UNINDENT
.INDENT 7.0
.TP
.B _prepare_reg_banks(*bidxes)
.UNINDENT
.INDENT 7.0
.TP
.B _source_regidx
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_nfevals
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_nregs
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_order
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_regidx
.UNINDENT
.INDENT 7.0
.TP
.B advance_to(t)
.UNINDENT
.INDENT 7.0
.TP
.B call_plugin_dt(dt)
.UNINDENT
.INDENT 7.0
.TP
.B cfgmeta
.UNINDENT
.INDENT 7.0
.TP
.B collect_stats(stats)
.UNINDENT
.INDENT 7.0
.TP
.B finalise_step(currsoln)
.UNINDENT
.INDENT 7.0
.TP
.B formulation = \(aqdual\(aq
.UNINDENT
.INDENT 7.0
.TP
.B nsteps
.UNINDENT
.INDENT 7.0
.TP
.B run()
.UNINDENT
.INDENT 7.0
.TP
.B soln
.UNINDENT
.INDENT 7.0
.TP
.B step(t, dt)
.UNINDENT
.INDENT 7.0
.TP
.B stepper_name = \(aqbdf3\(aq
.UNINDENT
.UNINDENT
.INDENT 0.0
.TP
.B class pyfr.integrators.dual.steppers.DualBackwardEulerStepper(*args, **kwargs)
.INDENT 7.0
.TP
.B _abc_impl = <_abc_data object>
.UNINDENT
.INDENT 7.0
.TP
.B _add(*args)
.UNINDENT
.INDENT 7.0
.TP
.B _dual_time_source
.UNINDENT
.INDENT 7.0
.TP
.B _get_axnpby_kerns(n, subdims=None)
.UNINDENT
.INDENT 7.0
.TP
.B _get_gndofs()
.UNINDENT
.INDENT 7.0
.TP
.B _get_kernels(name, nargs, **kwargs)
.UNINDENT
.INDENT 7.0
.TP
.B _get_plugins()
.UNINDENT
.INDENT 7.0
.TP
.B _get_reg_banks(nreg)
.UNINDENT
.INDENT 7.0
.TP
.B _prepare_reg_banks(*bidxes)
.UNINDENT
.INDENT 7.0
.TP
.B _source_regidx
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_nfevals
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_nregs
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_order
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_regidx
.UNINDENT
.INDENT 7.0
.TP
.B advance_to(t)
.UNINDENT
.INDENT 7.0
.TP
.B call_plugin_dt(dt)
.UNINDENT
.INDENT 7.0
.TP
.B cfgmeta
.UNINDENT
.INDENT 7.0
.TP
.B collect_stats(stats)
.UNINDENT
.INDENT 7.0
.TP
.B finalise_step(currsoln)
.UNINDENT
.INDENT 7.0
.TP
.B formulation = \(aqdual\(aq
.UNINDENT
.INDENT 7.0
.TP
.B nsteps
.UNINDENT
.INDENT 7.0
.TP
.B run()
.UNINDENT
.INDENT 7.0
.TP
.B soln
.UNINDENT
.INDENT 7.0
.TP
.B step(t, dt)
.UNINDENT
.INDENT 7.0
.TP
.B stepper_name = \(aqbackward\-euler\(aq
.UNINDENT
.UNINDENT
.INDENT 0.0
.TP
.B class pyfr.integrators.dual.pseudosteppers.DualPseudoRK4Stepper(*args, **kwargs)
.INDENT 7.0
.TP
.B _abc_impl = <_abc_data object>
.UNINDENT
.INDENT 7.0
.TP
.B _add(*args)
.UNINDENT
.INDENT 7.0
.TP
.B _add_with_dts(*args, c)
.UNINDENT
.INDENT 7.0
.TP
.B _dual_time_source()
.UNINDENT
.INDENT 7.0
.TP
.B _get_axnpby_kerns(n, subdims=None)
.UNINDENT
.INDENT 7.0
.TP
.B _get_gndofs()
.UNINDENT
.INDENT 7.0
.TP
.B _get_kernels(name, nargs, **kwargs)
.UNINDENT
.INDENT 7.0
.TP
.B _get_plugins()
.UNINDENT
.INDENT 7.0
.TP
.B _get_reg_banks(nreg)
.UNINDENT
.INDENT 7.0
.TP
.B _prepare_reg_banks(*bidxes)
.UNINDENT
.INDENT 7.0
.TP
.B _pseudo_stepper_nregs
.UNINDENT
.INDENT 7.0
.TP
.B _pseudo_stepper_order
.UNINDENT
.INDENT 7.0
.TP
.B _source_regidx
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_nfevals
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_nregs
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_order
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_regidx
.UNINDENT
.INDENT 7.0
.TP
.B advance_to(t)
.UNINDENT
.INDENT 7.0
.TP
.B call_plugin_dt(dt)
.UNINDENT
.INDENT 7.0
.TP
.B cfgmeta
.UNINDENT
.INDENT 7.0
.TP
.B collect_stats(stats)
.UNINDENT
.INDENT 7.0
.TP
.B finalise_step(currsoln)
.UNINDENT
.INDENT 7.0
.TP
.B formulation = \(aqdual\(aq
.UNINDENT
.INDENT 7.0
.TP
.B nsteps
.UNINDENT
.INDENT 7.0
.TP
.B pseudo_stepper_name = \(aqrk4\(aq
.UNINDENT
.INDENT 7.0
.TP
.B run()
.UNINDENT
.INDENT 7.0
.TP
.B soln
.UNINDENT
.INDENT 7.0
.TP
.B step(t, dt, dtau)
.UNINDENT
.UNINDENT
.INDENT 0.0
.TP
.B class pyfr.integrators.dual.pseudosteppers.DualPseudoTVDRK3Stepper(*args, **kwargs)
.INDENT 7.0
.TP
.B _abc_impl = <_abc_data object>
.UNINDENT
.INDENT 7.0
.TP
.B _add(*args)
.UNINDENT
.INDENT 7.0
.TP
.B _add_with_dts(*args, c)
.UNINDENT
.INDENT 7.0
.TP
.B _dual_time_source()
.UNINDENT
.INDENT 7.0
.TP
.B _get_axnpby_kerns(n, subdims=None)
.UNINDENT
.INDENT 7.0
.TP
.B _get_gndofs()
.UNINDENT
.INDENT 7.0
.TP
.B _get_kernels(name, nargs, **kwargs)
.UNINDENT
.INDENT 7.0
.TP
.B _get_plugins()
.UNINDENT
.INDENT 7.0
.TP
.B _get_reg_banks(nreg)
.UNINDENT
.INDENT 7.0
.TP
.B _prepare_reg_banks(*bidxes)
.UNINDENT
.INDENT 7.0
.TP
.B _pseudo_stepper_nregs
.UNINDENT
.INDENT 7.0
.TP
.B _pseudo_stepper_order
.UNINDENT
.INDENT 7.0
.TP
.B _source_regidx
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_nfevals
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_nregs
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_order
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_regidx
.UNINDENT
.INDENT 7.0
.TP
.B advance_to(t)
.UNINDENT
.INDENT 7.0
.TP
.B call_plugin_dt(dt)
.UNINDENT
.INDENT 7.0
.TP
.B cfgmeta
.UNINDENT
.INDENT 7.0
.TP
.B collect_stats(stats)
.UNINDENT
.INDENT 7.0
.TP
.B finalise_step(currsoln)
.UNINDENT
.INDENT 7.0
.TP
.B formulation = \(aqdual\(aq
.UNINDENT
.INDENT 7.0
.TP
.B nsteps
.UNINDENT
.INDENT 7.0
.TP
.B pseudo_stepper_name = \(aqtvd\-rk3\(aq
.UNINDENT
.INDENT 7.0
.TP
.B run()
.UNINDENT
.INDENT 7.0
.TP
.B soln
.UNINDENT
.INDENT 7.0
.TP
.B step(t, dt, dtau)
.UNINDENT
.UNINDENT
.INDENT 0.0
.TP
.B class pyfr.integrators.dual.pseudosteppers.DualPseudoEulerStepper(*args, **kwargs)
.INDENT 7.0
.TP
.B _abc_impl = <_abc_data object>
.UNINDENT
.INDENT 7.0
.TP
.B _add(*args)
.UNINDENT
.INDENT 7.0
.TP
.B _add_with_dts(*args, c)
.UNINDENT
.INDENT 7.0
.TP
.B _dual_time_source()
.UNINDENT
.INDENT 7.0
.TP
.B _get_axnpby_kerns(n, subdims=None)
.UNINDENT
.INDENT 7.0
.TP
.B _get_gndofs()
.UNINDENT
.INDENT 7.0
.TP
.B _get_kernels(name, nargs, **kwargs)
.UNINDENT
.INDENT 7.0
.TP
.B _get_plugins()
.UNINDENT
.INDENT 7.0
.TP
.B _get_reg_banks(nreg)
.UNINDENT
.INDENT 7.0
.TP
.B _prepare_reg_banks(*bidxes)
.UNINDENT
.INDENT 7.0
.TP
.B _pseudo_stepper_nregs
.UNINDENT
.INDENT 7.0
.TP
.B _pseudo_stepper_order
.UNINDENT
.INDENT 7.0
.TP
.B _source_regidx
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_nfevals
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_nregs
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_order
.UNINDENT
.INDENT 7.0
.TP
.B _stepper_regidx
.UNINDENT
.INDENT 7.0
.TP
.B advance_to(t)
.UNINDENT
.INDENT 7.0
.TP
.B call_plugin_dt(dt)
.UNINDENT
.INDENT 7.0
.TP
.B cfgmeta
.UNINDENT
.INDENT 7.0
.TP
.B collect_stats(stats)
.UNINDENT
.INDENT 7.0
.TP
.B finalise_step(currsoln)
.UNINDENT
.INDENT 7.0
.TP
.B formulation = \(aqdual\(aq
.UNINDENT
.INDENT 7.0
.TP
.B nsteps
.UNINDENT
.INDENT 7.0
.TP
.B pseudo_stepper_name = \(aqeuler\(aq
.UNINDENT
.INDENT 7.0
.TP
.B run()
.UNINDENT
.INDENT 7.0
.TP
.B soln
.UNINDENT
.INDENT 7.0
.TP
.B step(t, dt, dtau)
.UNINDENT
.UNINDENT
.sp
Types of \fI\%Stepper\fP are related via the following inheritance diagram:
.SS System
.sp
A \fI\%System\fP holds information/data for the system, including
\fI\%Elements\fP, \fI\%Interfaces\fP, and the \fI\%Backend\fP with which the
simulation is to run. A \fI\%System\fP has a method named \fBrhs\fP, which
obtains the divergence of the flux (the \(aqright\-hand\-side\(aq) at each
solution point. The method \fBrhs\fP invokes various kernels which
have been pre\-generated and loaded into queues. A \fI\%System\fP also has a
method named \fB_gen_kernels\fP which acts to generate all the
kernels required by a particular \fI\%System\fP\&. A kernel is an instance of
a \(aqone\-off\(aq class with a method named \fBrun\fP that implements the
required kernel functionality. Individual kernels are produced by a
kernel provider. PyFR 1.5.0 has various types of kernel provider. A
\fI\%Pointwise Kernel Provider\fP produces point\-wise kernels such as
Riemann solvers and flux functions etc. These point\-wise kernels are
specified using an in\-built platform\-independent templating language
derived from \fI\%Mako\fP, henceforth
referred to as \fI\%PyFR\-Mako\fP\&. There are two types of \fI\%System\fP available
in PyFR 1.5.0:
.INDENT 0.0
.TP
.B class pyfr.solvers.euler.system.EulerSystem(backend, rallocs, mesh, initsoln, nreg, cfg)
.INDENT 7.0
.TP
.B _abc_impl = <_abc_data object>
.UNINDENT
.INDENT 7.0
.TP
.B _gen_kernels(eles, iint, mpiint, bcint)
.UNINDENT
.INDENT 7.0
.TP
.B _gen_queues()
.UNINDENT
.INDENT 7.0
.TP
.B _load_bc_inters(rallocs, mesh, elemap)
.UNINDENT
.INDENT 7.0
.TP
.B _load_eles(rallocs, mesh, initsoln, nreg, nonce)
.UNINDENT
.INDENT 7.0
.TP
.B _load_int_inters(rallocs, mesh, elemap)
.UNINDENT
.INDENT 7.0
.TP
.B _load_mpi_inters(rallocs, mesh, elemap)
.UNINDENT
.INDENT 7.0
.TP
.B _nonce_seq = count(0)
.UNINDENT
.INDENT 7.0
.TP
.B _nqueues = 2
.UNINDENT
.INDENT 7.0
.TP
.B bbcinterscls
alias of \fBpyfr.solvers.euler.inters.EulerBaseBCInters\fP
.UNINDENT
.INDENT 7.0
.TP
.B ele_scal_upts(idx)
.UNINDENT
.INDENT 7.0
.TP
.B elementscls
alias of \fI\%pyfr.solvers.euler.elements.EulerElements\fP
.UNINDENT
.INDENT 7.0
.TP
.B filt(uinoutbank)
.UNINDENT
.INDENT 7.0
.TP
.B intinterscls
alias of \fI\%pyfr.solvers.euler.inters.EulerIntInters\fP
.UNINDENT
.INDENT 7.0
.TP
.B mpiinterscls
alias of \fI\%pyfr.solvers.euler.inters.EulerMPIInters\fP
.UNINDENT
.INDENT 7.0
.TP
.B name = \(aqeuler\(aq
.UNINDENT
.INDENT 7.0
.TP
.B rhs(t, uinbank, foutbank)
.UNINDENT
.UNINDENT
.INDENT 0.0
.TP
.B class pyfr.solvers.navstokes.system.NavierStokesSystem(backend, rallocs, mesh, initsoln, nreg, cfg)
.INDENT 7.0
.TP
.B _abc_impl = <_abc_data object>
.UNINDENT
.INDENT 7.0
.TP
.B _gen_kernels(eles, iint, mpiint, bcint)
.UNINDENT
.INDENT 7.0
.TP
.B _gen_queues()
.UNINDENT
.INDENT 7.0
.TP
.B _load_bc_inters(rallocs, mesh, elemap)
.UNINDENT
.INDENT 7.0
.TP
.B _load_eles(rallocs, mesh, initsoln, nreg, nonce)
.UNINDENT
.INDENT 7.0
.TP
.B _load_int_inters(rallocs, mesh, elemap)
.UNINDENT
.INDENT 7.0
.TP
.B _load_mpi_inters(rallocs, mesh, elemap)
.UNINDENT
.INDENT 7.0
.TP
.B _nonce_seq = count(0)
.UNINDENT
.INDENT 7.0
.TP
.B _nqueues = 2
.UNINDENT
.INDENT 7.0
.TP
.B bbcinterscls
alias of \fBpyfr.solvers.navstokes.inters.NavierStokesBaseBCInters\fP
.UNINDENT
.INDENT 7.0
.TP
.B ele_scal_upts(idx)
.UNINDENT
.INDENT 7.0
.TP
.B elementscls
alias of \fI\%pyfr.solvers.navstokes.elements.NavierStokesElements\fP
.UNINDENT
.INDENT 7.0
.TP
.B filt(uinoutbank)
.UNINDENT
.INDENT 7.0
.TP
.B intinterscls
alias of \fI\%pyfr.solvers.navstokes.inters.NavierStokesIntInters\fP
.UNINDENT
.INDENT 7.0
.TP
.B mpiinterscls
alias of \fI\%pyfr.solvers.navstokes.inters.NavierStokesMPIInters\fP
.UNINDENT
.INDENT 7.0
.TP
.B name = \(aqnavier\-stokes\(aq
.UNINDENT
.INDENT 7.0
.TP
.B rhs(t, uinbank, foutbank)
.UNINDENT
.UNINDENT
.sp
Types of \fI\%System\fP are related via the following inheritance diagram:
.SS Elements
.sp
An \fI\%Elements\fP holds information/data for a group of elements. There are
two types of \fI\%Elements\fP available in PyFR 1.5.0:
.INDENT 0.0
.TP
.B class pyfr.solvers.euler.elements.EulerElements(basiscls, eles, cfg)
.INDENT 7.0
.TP
.B _abc_impl = <_abc_data object>
.UNINDENT
.INDENT 7.0
.TP
.B _gen_pnorm_fpts()
.UNINDENT
.INDENT 7.0
.TP
.B _mag_pnorm_fpts = None
.UNINDENT
.INDENT 7.0
.TP
.B _norm_pnorm_fpts = None
.UNINDENT
.INDENT 7.0
.TP
.B _ploc_in_src_exprs = None
.UNINDENT
.INDENT 7.0
.TP
.B _scratch_bufs
.UNINDENT
.INDENT 7.0
.TP
.B _smats_djacs_mpts = None
.UNINDENT
.INDENT 7.0
.TP
.B _soln_in_src_exprs = None
.UNINDENT
.INDENT 7.0
.TP
.B _src_exprs = None
.UNINDENT
.INDENT 7.0
.TP
.B _srtd_face_fpts = None
.UNINDENT
.INDENT 7.0
.TP
.B static con_to_pri(cons, cfg)
.UNINDENT
.INDENT 7.0
.TP
.B convarmap = {2: [\(aqrho\(aq, \(aqrhou\(aq, \(aqrhov\(aq, \(aqE\(aq], 3: [\(aqrho\(aq, \(aqrhou\(aq, \(aqrhov\(aq, \(aqrhow\(aq, \(aqE\(aq]}
.UNINDENT
.INDENT 7.0
.TP
.B dualcoeffs = {2: [\(aqrho\(aq, \(aqrhou\(aq, \(aqrhov\(aq, \(aqE\(aq], 3: [\(aqrho\(aq, \(aqrhou\(aq, \(aqrhov\(aq, \(aqrhow\(aq, \(aqE\(aq]}
.UNINDENT
.INDENT 7.0
.TP
.B formulations = [\(aqstd\(aq, \(aqdual\(aq]
.UNINDENT
.INDENT 7.0
.TP
.B get_mag_pnorms(eidx, fidx)
.UNINDENT
.INDENT 7.0
.TP
.B get_mag_pnorms_for_inter(eidx, fidx)
.UNINDENT
.INDENT 7.0
.TP
.B get_norm_pnorms(eidx, fidx)
.UNINDENT
.INDENT 7.0
.TP
.B get_norm_pnorms_for_inter(eidx, fidx)
.UNINDENT
.INDENT 7.0
.TP
.B get_ploc_for_inter(eidx, fidx)
.UNINDENT
.INDENT 7.0
.TP
.B get_scal_fpts_for_inter(eidx, fidx)
.UNINDENT
.INDENT 7.0
.TP
.B get_vect_fpts_for_inter(eidx, fidx)
.UNINDENT
.INDENT 7.0
.TP
.B opmat(expr)
.UNINDENT
.INDENT 7.0
.TP
.B ploc_at(name)
.UNINDENT
.INDENT 7.0
.TP
.B ploc_at_np(name)
.UNINDENT
.INDENT 7.0
.TP
.B plocfpts = None
.UNINDENT
.INDENT 7.0
.TP
.B static pri_to_con(pris, cfg)
.UNINDENT
.INDENT 7.0
.TP
.B privarmap = {2: [\(aqrho\(aq, \(aqu\(aq, \(aqv\(aq, \(aqp\(aq], 3: [\(aqrho\(aq, \(aqu\(aq, \(aqv\(aq, \(aqw\(aq, \(aqp\(aq]}
.UNINDENT
.INDENT 7.0
.TP
.B rcpdjac_at(name)
.UNINDENT
.INDENT 7.0
.TP
.B rcpdjac_at_np(name)
.UNINDENT
.INDENT 7.0
.TP
.B set_backend(backend, nscalupts, nonce)
.UNINDENT
.INDENT 7.0
.TP
.B set_ics_from_cfg()
.UNINDENT
.INDENT 7.0
.TP
.B set_ics_from_soln(solnmat, solncfg)
.UNINDENT
.INDENT 7.0
.TP
.B smat_at(name)
.UNINDENT
.INDENT 7.0
.TP
.B smat_at_np(name)
.UNINDENT
.INDENT 7.0
.TP
.B visvarmap = {2: {\(aqdensity\(aq: [\(aqrho\(aq], \(aqpressure\(aq: [\(aqp\(aq], \(aqvelocity\(aq: [\(aqu\(aq, \(aqv\(aq]}, 3: {\(aqdensity\(aq: [\(aqrho\(aq], \(aqpressure\(aq: [\(aqp\(aq], \(aqvelocity\(aq: [\(aqu\(aq, \(aqv\(aq, \(aqw\(aq]}}
.UNINDENT
.UNINDENT
.INDENT 0.0
.TP
.B class pyfr.solvers.navstokes.elements.NavierStokesElements(basiscls, eles, cfg)
.INDENT 7.0
.TP
.B _abc_impl = <_abc_data object>
.UNINDENT
.INDENT 7.0
.TP
.B _gen_pnorm_fpts()
.UNINDENT
.INDENT 7.0
.TP
.B _mag_pnorm_fpts = None
.UNINDENT
.INDENT 7.0
.TP
.B _norm_pnorm_fpts = None
.UNINDENT
.INDENT 7.0
.TP
.B _ploc_in_src_exprs = None
.UNINDENT
.INDENT 7.0
.TP
.B _scratch_bufs
.UNINDENT
.INDENT 7.0
.TP
.B _smats_djacs_mpts = None
.UNINDENT
.INDENT 7.0
.TP
.B _soln_in_src_exprs = None
.UNINDENT
.INDENT 7.0
.TP
.B _src_exprs = None
.UNINDENT
.INDENT 7.0
.TP
.B _srtd_face_fpts = None
.UNINDENT
.INDENT 7.0
.TP
.B static con_to_pri(cons, cfg)
.UNINDENT
.INDENT 7.0
.TP
.B convarmap = {2: [\(aqrho\(aq, \(aqrhou\(aq, \(aqrhov\(aq, \(aqE\(aq], 3: [\(aqrho\(aq, \(aqrhou\(aq, \(aqrhov\(aq, \(aqrhow\(aq, \(aqE\(aq]}
.UNINDENT
.INDENT 7.0
.TP
.B dualcoeffs = {2: [\(aqrho\(aq, \(aqrhou\(aq, \(aqrhov\(aq, \(aqE\(aq], 3: [\(aqrho\(aq, \(aqrhou\(aq, \(aqrhov\(aq, \(aqrhow\(aq, \(aqE\(aq]}
.UNINDENT
.INDENT 7.0
.TP
.B formulations = [\(aqstd\(aq, \(aqdual\(aq]
.UNINDENT
.INDENT 7.0
.TP
.B get_artvisc_fpts_for_inter(eidx, fidx)
.UNINDENT
.INDENT 7.0
.TP
.B get_mag_pnorms(eidx, fidx)
.UNINDENT
.INDENT 7.0
.TP
.B get_mag_pnorms_for_inter(eidx, fidx)
.UNINDENT
.INDENT 7.0
.TP
.B get_norm_pnorms(eidx, fidx)
.UNINDENT
.INDENT 7.0
.TP
.B get_norm_pnorms_for_inter(eidx, fidx)
.UNINDENT
.INDENT 7.0
.TP
.B get_ploc_for_inter(eidx, fidx)
.UNINDENT
.INDENT 7.0
.TP
.B get_scal_fpts_for_inter(eidx, fidx)
.UNINDENT
.INDENT 7.0
.TP
.B get_vect_fpts_for_inter(eidx, fidx)
.UNINDENT
.INDENT 7.0
.TP
.B opmat(expr)
.UNINDENT
.INDENT 7.0
.TP
.B ploc_at(name)
.UNINDENT
.INDENT 7.0
.TP
.B ploc_at_np(name)
.UNINDENT
.INDENT 7.0
.TP
.B plocfpts = None
.UNINDENT
.INDENT 7.0
.TP
.B static pri_to_con(pris, cfg)
.UNINDENT
.INDENT 7.0
.TP
.B privarmap = {2: [\(aqrho\(aq, \(aqu\(aq, \(aqv\(aq, \(aqp\(aq], 3: [\(aqrho\(aq, \(aqu\(aq, \(aqv\(aq, \(aqw\(aq, \(aqp\(aq]}
.UNINDENT
.INDENT 7.0
.TP
.B rcpdjac_at(name)
.UNINDENT
.INDENT 7.0
.TP
.B rcpdjac_at_np(name)
.UNINDENT
.INDENT 7.0
.TP
.B set_backend(backend, nscalupts, nonce)
.UNINDENT
.INDENT 7.0
.TP
.B set_ics_from_cfg()
.UNINDENT
.INDENT 7.0
.TP
.B set_ics_from_soln(solnmat, solncfg)
.UNINDENT
.INDENT 7.0
.TP
.B shockvar = \(aqrho\(aq
.UNINDENT
.INDENT 7.0
.TP
.B smat_at(name)
.UNINDENT
.INDENT 7.0
.TP
.B smat_at_np(name)
.UNINDENT
.INDENT 7.0
.TP
.B visvarmap = {2: {\(aqdensity\(aq: [\(aqrho\(aq], \(aqpressure\(aq: [\(aqp\(aq], \(aqvelocity\(aq: [\(aqu\(aq, \(aqv\(aq]}, 3: {\(aqdensity\(aq: [\(aqrho\(aq], \(aqpressure\(aq: [\(aqp\(aq], \(aqvelocity\(aq: [\(aqu\(aq, \(aqv\(aq, \(aqw\(aq]}}
.UNINDENT
.UNINDENT
.sp
Types of \fI\%Elements\fP are related via the following inheritance diagram:
.SS Interfaces
.sp
An \fI\%Interfaces\fP holds information/data for a group of interfaces. There
are four types of (non\-boundary) \fI\%Interfaces\fP available in PyFR
1.5.0:
.INDENT 0.0
.TP
.B class pyfr.solvers.euler.inters.EulerIntInters(*args, **kwargs)
.INDENT 7.0
.TP
.B _const_mat(inter, meth)
.UNINDENT
.INDENT 7.0
.TP
.B _gen_perm(lhs, rhs)
.UNINDENT
.INDENT 7.0
.TP
.B _scal_view(inter, meth)
.UNINDENT
.INDENT 7.0
.TP
.B _scal_xchg_view(inter, meth)
.UNINDENT
.INDENT 7.0
.TP
.B _vect_view(inter, meth)
.UNINDENT
.INDENT 7.0
.TP
.B _vect_xchg_view(inter, meth)
.UNINDENT
.INDENT 7.0
.TP
.B _view(inter, meth, vshape=())
.UNINDENT
.INDENT 7.0
.TP
.B _xchg_view(inter, meth, vshape=())
.UNINDENT
.UNINDENT
.INDENT 0.0
.TP
.B class pyfr.solvers.euler.inters.EulerMPIInters(*args, **kwargs)
.INDENT 7.0
.TP
.B MPI_TAG = 2314
.UNINDENT
.INDENT 7.0
.TP
.B _const_mat(inter, meth)
.UNINDENT
.INDENT 7.0
.TP
.B _scal_view(inter, meth)
.UNINDENT
.INDENT 7.0
.TP
.B _scal_xchg_view(inter, meth)
.UNINDENT
.INDENT 7.0
.TP
.B _vect_view(inter, meth)
.UNINDENT
.INDENT 7.0
.TP
.B _vect_xchg_view(inter, meth)
.UNINDENT
.INDENT 7.0
.TP
.B _view(inter, meth, vshape=())
.UNINDENT
.INDENT 7.0
.TP
.B _xchg_view(inter, meth, vshape=())
.UNINDENT
.UNINDENT
.INDENT 0.0
.TP
.B class pyfr.solvers.navstokes.inters.NavierStokesIntInters(be, lhs, rhs, elemap, cfg)
.INDENT 7.0
.TP
.B _const_mat(inter, meth)
.UNINDENT
.INDENT 7.0
.TP
.B _gen_perm(lhs, rhs)
.UNINDENT
.INDENT 7.0
.TP
.B _scal_view(inter, meth)
.UNINDENT
.INDENT 7.0
.TP
.B _scal_xchg_view(inter, meth)
.UNINDENT
.INDENT 7.0
.TP
.B _vect_view(inter, meth)
.UNINDENT
.INDENT 7.0
.TP
.B _vect_xchg_view(inter, meth)
.UNINDENT
.INDENT 7.0
.TP
.B _view(inter, meth, vshape=())
.UNINDENT
.INDENT 7.0
.TP
.B _xchg_view(inter, meth, vshape=())
.UNINDENT
.UNINDENT
.INDENT 0.0
.TP
.B class pyfr.solvers.navstokes.inters.NavierStokesMPIInters(be, lhs, rhsrank, rallocs, elemap, cfg)
.INDENT 7.0
.TP
.B MPI_TAG = 2314
.UNINDENT
.INDENT 7.0
.TP
.B _const_mat(inter, meth)
.UNINDENT
.INDENT 7.0
.TP
.B _scal_view(inter, meth)
.UNINDENT
.INDENT 7.0
.TP
.B _scal_xchg_view(inter, meth)
.UNINDENT
.INDENT 7.0
.TP
.B _vect_view(inter, meth)
.UNINDENT
.INDENT 7.0
.TP
.B _vect_xchg_view(inter, meth)
.UNINDENT
.INDENT 7.0
.TP
.B _view(inter, meth, vshape=())
.UNINDENT
.INDENT 7.0
.TP
.B _xchg_view(inter, meth, vshape=())
.UNINDENT
.UNINDENT
.sp
Types of (non\-boundary) \fI\%Interfaces\fP are related via the following
inheritance diagram:
.SS Backend
.sp
A \fI\%Backend\fP holds information/data for a backend. There are four types
of \fI\%Backend\fP available in PyFR 1.5.0:
.INDENT 0.0
.TP
.B class pyfr.backends.cuda.base.CUDABackend(cfg)
.INDENT 7.0
.TP
.B _abc_impl = <_abc_data object>
.UNINDENT
.INDENT 7.0
.TP
.B _malloc_impl(nbytes)
.UNINDENT
.INDENT 7.0
.TP
.B alias(obj, aobj)
.UNINDENT
.INDENT 7.0
.TP
.B commit()
.UNINDENT
.INDENT 7.0
.TP
.B const_matrix(initval, extent=None, tags={})
.UNINDENT
.INDENT 7.0
.TP
.B kernel(name, *args, **kwargs)
.UNINDENT
.INDENT 7.0
.TP
.B lookup = None
.UNINDENT
.INDENT 7.0
.TP
.B malloc(obj, extent)
.UNINDENT
.INDENT 7.0
.TP
.B matrix(ioshape, initval=None, extent=None, aliases=None, tags={})
.UNINDENT
.INDENT 7.0
.TP
.B matrix_bank(mats, initbank=0, tags={})
.UNINDENT
.INDENT 7.0
.TP
.B matrix_rslice(mat, p, q)
.UNINDENT
.INDENT 7.0
.TP
.B name = \(aqcuda\(aq
.UNINDENT
.INDENT 7.0
.TP
.B queue()
.UNINDENT
.INDENT 7.0
.TP
.B runall(sequence)
.UNINDENT
.INDENT 7.0
.TP
.B view(matmap, rmap, cmap, rstridemap=None, vshape=(), tags={})
.UNINDENT
.INDENT 7.0
.TP
.B xchg_matrix(ioshape, initval=None, extent=None, aliases=None, tags={})
.UNINDENT
.INDENT 7.0
.TP
.B xchg_matrix_for_view(view, tags={})
.UNINDENT
.INDENT 7.0
.TP
.B xchg_view(matmap, rmap, cmap, rstridemap=None, vshape=(), tags={})
.UNINDENT
.UNINDENT
.INDENT 0.0
.TP
.B class pyfr.backends.mic.base.MICBackend(cfg)
.INDENT 7.0
.TP
.B _abc_impl = <_abc_data object>
.UNINDENT
.INDENT 7.0
.TP
.B _malloc_impl(nbytes)
.UNINDENT
.INDENT 7.0
.TP
.B alias(obj, aobj)
.UNINDENT
.INDENT 7.0
.TP
.B commit()
.UNINDENT
.INDENT 7.0
.TP
.B const_matrix(initval, extent=None, tags={})
.UNINDENT
.INDENT 7.0
.TP
.B kernel(name, *args, **kwargs)
.UNINDENT
.INDENT 7.0
.TP
.B lookup = None
.UNINDENT
.INDENT 7.0
.TP
.B malloc(obj, extent)
.UNINDENT
.INDENT 7.0
.TP
.B matrix(ioshape, initval=None, extent=None, aliases=None, tags={})
.UNINDENT
.INDENT 7.0
.TP
.B matrix_bank(mats, initbank=0, tags={})
.UNINDENT
.INDENT 7.0
.TP
.B matrix_rslice(mat, p, q)
.UNINDENT
.INDENT 7.0
.TP
.B name = \(aqmic\(aq
.UNINDENT
.INDENT 7.0
.TP
.B queue()
.UNINDENT
.INDENT 7.0
.TP
.B runall(sequence)
.UNINDENT
.INDENT 7.0
.TP
.B view(matmap, rmap, cmap, rstridemap=None, vshape=(), tags={})
.UNINDENT
.INDENT 7.0
.TP
.B xchg_matrix(ioshape, initval=None, extent=None, aliases=None, tags={})
.UNINDENT
.INDENT 7.0
.TP
.B xchg_matrix_for_view(view, tags={})
.UNINDENT
.INDENT 7.0
.TP
.B xchg_view(matmap, rmap, cmap, rstridemap=None, vshape=(), tags={})
.UNINDENT
.UNINDENT
.INDENT 0.0
.TP
.B class pyfr.backends.opencl.base.OpenCLBackend(cfg)
.INDENT 7.0
.TP
.B _abc_impl = <_abc_data object>
.UNINDENT
.INDENT 7.0
.TP
.B _malloc_impl(nbytes)
.UNINDENT
.INDENT 7.0
.TP
.B alias(obj, aobj)
.UNINDENT
.INDENT 7.0
.TP
.B commit()
.UNINDENT
.INDENT 7.0
.TP
.B const_matrix(initval, extent=None, tags={})
.UNINDENT
.INDENT 7.0
.TP
.B kernel(name, *args, **kwargs)
.UNINDENT
.INDENT 7.0
.TP
.B lookup = None
.UNINDENT
.INDENT 7.0
.TP
.B malloc(obj, extent)
.UNINDENT
.INDENT 7.0
.TP
.B matrix(ioshape, initval=None, extent=None, aliases=None, tags={})
.UNINDENT
.INDENT 7.0
.TP
.B matrix_bank(mats, initbank=0, tags={})
.UNINDENT
.INDENT 7.0
.TP
.B matrix_rslice(mat, p, q)
.UNINDENT
.INDENT 7.0
.TP
.B name = \(aqopencl\(aq
.UNINDENT
.INDENT 7.0
.TP
.B queue()
.UNINDENT
.INDENT 7.0
.TP
.B runall(sequence)
.UNINDENT
.INDENT 7.0
.TP
.B view(matmap, rmap, cmap, rstridemap=None, vshape=(), tags={})
.UNINDENT
.INDENT 7.0
.TP
.B xchg_matrix(ioshape, initval=None, extent=None, aliases=None, tags={})
.UNINDENT
.INDENT 7.0
.TP
.B xchg_matrix_for_view(view, tags={})
.UNINDENT
.INDENT 7.0
.TP
.B xchg_view(matmap, rmap, cmap, rstridemap=None, vshape=(), tags={})
.UNINDENT
.UNINDENT
.INDENT 0.0
.TP
.B class pyfr.backends.openmp.base.OpenMPBackend(cfg)
.INDENT 7.0
.TP
.B _abc_impl = <_abc_data object>
.UNINDENT
.INDENT 7.0
.TP
.B _malloc_impl(nbytes)
.UNINDENT
.INDENT 7.0
.TP
.B alias(obj, aobj)
.UNINDENT
.INDENT 7.0
.TP
.B commit()
.UNINDENT
.INDENT 7.0
.TP
.B const_matrix(initval, extent=None, tags={})
.UNINDENT
.INDENT 7.0
.TP
.B kernel(name, *args, **kwargs)
.UNINDENT
.INDENT 7.0
.TP
.B lookup = None
.UNINDENT
.INDENT 7.0
.TP
.B malloc(obj, extent)
.UNINDENT
.INDENT 7.0
.TP
.B matrix(ioshape, initval=None, extent=None, aliases=None, tags={})
.UNINDENT
.INDENT 7.0
.TP
.B matrix_bank(mats, initbank=0, tags={})
.UNINDENT
.INDENT 7.0
.TP
.B matrix_rslice(mat, p, q)
.UNINDENT
.INDENT 7.0
.TP
.B name = \(aqopenmp\(aq
.UNINDENT
.INDENT 7.0
.TP
.B queue()
.UNINDENT
.INDENT 7.0
.TP
.B runall(sequence)
.UNINDENT
.INDENT 7.0
.TP
.B view(matmap, rmap, cmap, rstridemap=None, vshape=(), tags={})
.UNINDENT
.INDENT 7.0
.TP
.B xchg_matrix(ioshape, initval=None, extent=None, aliases=None, tags={})
.UNINDENT
.INDENT 7.0
.TP
.B xchg_matrix_for_view(view, tags={})
.UNINDENT
.INDENT 7.0
.TP
.B xchg_view(matmap, rmap, cmap, rstridemap=None, vshape=(), tags={})
.UNINDENT
.UNINDENT
.sp
Types of \fI\%Backend\fP are related via the following inheritance diagram:
.SS Pointwise Kernel Provider
.sp
A \fI\%Pointwise Kernel Provider\fP produces point\-wise kernels.
Specifically, a \fI\%Pointwise Kernel Provider\fP has a method named
\fBregister\fP, which adds a new method to an instance of a
\fI\%Pointwise Kernel Provider\fP\&. This new method, when called, returns a
kernel. A kernel is an instance of a \(aqone\-off\(aq class with a method
named \fBrun\fP that implements the required kernel functionality.
The kernel functionality itself is specified using \fI\%PyFR\-Mako\fP\&. Hence,
a \fI\%Pointwise Kernel Provider\fP also has a method named
\fB_render_kernel\fP, which renders \fI\%PyFR\-Mako\fP into low\-level
platform\-specific code. The \fB_render_kernel\fP method first sets
the context for Mako (i.e. details about the \fI\%Backend\fP etc.) and then
uses Mako to begin rendering the \fI\%PyFR\-Mako\fP specification. When Mako
encounters a \fBpyfr:kernel\fP an instance of a \fI\%Kernel Generator\fP
is created, which is used to render the body of the
\fBpyfr:kernel\fP\&. There are four types of \fI\%Pointwise Kernel
Provider\fP available in PyFR 1.5.0:
.INDENT 0.0
.TP
.B class pyfr.backends.cuda.provider.CUDAPointwiseKernelProvider(backend)
.INDENT 7.0
.TP
.B _abc_impl = <_abc_data object>
.UNINDENT
.INDENT 7.0
.TP
.B _build_arglst(dims, argn, argt, argdict)
.UNINDENT
.INDENT 7.0
.TP
.B _build_kernel(name, src, argtypes)
.UNINDENT
.INDENT 7.0
.TP
.B _instantiate_kernel(dims, fun, arglst)
.UNINDENT
.INDENT 7.0
.TP
.B _render_kernel(name, mod, tplargs)
.UNINDENT
.INDENT 7.0
.TP
.B kernel_generator_cls
alias of \fI\%pyfr.backends.cuda.generator.CUDAKernelGenerator\fP
.UNINDENT
.INDENT 7.0
.TP
.B register(mod)
.UNINDENT
.UNINDENT
.INDENT 0.0
.TP
.B class pyfr.backends.mic.provider.MICPointwiseKernelProvider(backend)
.INDENT 7.0
.TP
.B _abc_impl = <_abc_data object>
.UNINDENT
.INDENT 7.0
.TP
.B _build_arglst(dims, argn, argt, argdict)
.UNINDENT
.INDENT 7.0
.TP
.B _build_kernel(name, src, argtypes, restype=None)
.UNINDENT
.INDENT 7.0
.TP
.B _instantiate_kernel(dims, fun, arglst)
.UNINDENT
.INDENT 7.0
.TP
.B _render_kernel(name, mod, tplargs)
.UNINDENT
.INDENT 7.0
.TP
.B kernel_generator_cls
alias of \fI\%pyfr.backends.mic.generator.MICKernelGenerator\fP
.UNINDENT
.INDENT 7.0
.TP
.B register(mod)
.UNINDENT
.UNINDENT
.INDENT 0.0
.TP
.B class pyfr.backends.opencl.provider.OpenCLPointwiseKernelProvider(backend)
.INDENT 7.0
.TP
.B _abc_impl = <_abc_data object>
.UNINDENT
.INDENT 7.0
.TP
.B _build_arglst(dims, argn, argt, argdict)
.UNINDENT
.INDENT 7.0
.TP
.B _build_kernel(name, src, argtypes)
.UNINDENT
.INDENT 7.0
.TP
.B _instantiate_kernel(dims, fun, arglst)
.UNINDENT
.INDENT 7.0
.TP
.B _render_kernel(name, mod, tplargs)
.UNINDENT
.INDENT 7.0
.TP
.B kernel_generator_cls
alias of \fI\%pyfr.backends.opencl.generator.OpenCLKernelGenerator\fP
.UNINDENT
.INDENT 7.0
.TP
.B register(mod)
.UNINDENT
.UNINDENT
.INDENT 0.0
.TP
.B class pyfr.backends.openmp.provider.OpenMPPointwiseKernelProvider(backend)
.INDENT 7.0
.TP
.B _abc_impl = <_abc_data object>
.UNINDENT
.INDENT 7.0
.TP
.B _build_arglst(dims, argn, argt, argdict)
.UNINDENT
.INDENT 7.0
.TP
.B _build_kernel(name, src, argtypes, restype=None)
.UNINDENT
.INDENT 7.0
.TP
.B _instantiate_kernel(dims, fun, arglst)
.UNINDENT
.INDENT 7.0
.TP
.B _render_kernel(name, mod, tplargs)
.UNINDENT
.INDENT 7.0
.TP
.B kernel_generator_cls
alias of \fI\%pyfr.backends.openmp.generator.OpenMPKernelGenerator\fP
.UNINDENT
.INDENT 7.0
.TP
.B register(mod)
.UNINDENT
.UNINDENT
.sp
Types of \fI\%Pointwise Kernel Provider\fP are related via the following
inheritance diagram:
.SS Kernel Generator
.sp
A \fI\%Kernel Generator\fP renders the \fI\%PyFR\-Mako\fP in a \fBpyfr:kernel\fP
into low\-level platform\-specific code. Specifically, a \fI\%Kernel
Generator\fP has a method named \fBrender\fP, which applies \fI\%Backend\fP
specific regex and adds \fI\%Backend\fP specific \(aqboiler plate\(aq code to
produce the low\-level platform\-specific source \-\- which is compiled,
linked, and loaded. There are four types of \fI\%Kernel Generator\fP
available in PyFR 1.5.0:
.INDENT 0.0
.TP
.B class pyfr.backends.cuda.generator.CUDAKernelGenerator(*args, **kwargs)
.INDENT 7.0
.TP
.B _abc_impl = <_abc_data object>
.UNINDENT
.INDENT 7.0
.TP
.B _deref_arg_array_1d(arg)
.UNINDENT
.INDENT 7.0
.TP
.B _deref_arg_array_2d(arg)
.UNINDENT
.INDENT 7.0
.TP
.B _deref_arg_view(arg)
.UNINDENT
.INDENT 7.0
.TP
.B _render_body(body)
.UNINDENT
.INDENT 7.0
.TP
.B _render_spec()
.UNINDENT
.INDENT 7.0
.TP
.B argspec()
.UNINDENT
.INDENT 7.0
.TP
.B needs_ldim(arg)
.UNINDENT
.INDENT 7.0
.TP
.B render()
.UNINDENT
.UNINDENT
.INDENT 0.0
.TP
.B class pyfr.backends.mic.generator.MICKernelGenerator(name, ndim, args, body, fpdtype)
.INDENT 7.0
.TP
.B _abc_impl = <_abc_data object>
.UNINDENT
.INDENT 7.0
.TP
.B _deref_arg_array_1d(arg)
.UNINDENT
.INDENT 7.0
.TP
.B _deref_arg_array_2d(arg)
.UNINDENT
.INDENT 7.0
.TP
.B _deref_arg_view(arg)
.UNINDENT
.INDENT 7.0
.TP
.B _render_body(body)
.UNINDENT
.INDENT 7.0
.TP
.B _render_spec_unpack()
.UNINDENT
.INDENT 7.0
.TP
.B argspec()
.UNINDENT
.INDENT 7.0
.TP
.B needs_ldim(arg)
.UNINDENT
.INDENT 7.0
.TP
.B render()
.UNINDENT
.UNINDENT
.INDENT 0.0
.TP
.B class pyfr.backends.opencl.generator.OpenCLKernelGenerator(*args, **kwargs)
.INDENT 7.0
.TP
.B _abc_impl = <_abc_data object>
.UNINDENT
.INDENT 7.0
.TP
.B _deref_arg_array_1d(arg)
.UNINDENT
.INDENT 7.0
.TP
.B _deref_arg_array_2d(arg)
.UNINDENT
.INDENT 7.0
.TP
.B _deref_arg_view(arg)
.UNINDENT
.INDENT 7.0
.TP
.B _render_body(body)
.UNINDENT
.INDENT 7.0
.TP
.B _render_spec()
.UNINDENT
.INDENT 7.0
.TP
.B argspec()
.UNINDENT
.INDENT 7.0
.TP
.B needs_ldim(arg)
.UNINDENT
.INDENT 7.0
.TP
.B render()
.UNINDENT
.UNINDENT
.INDENT 0.0
.TP
.B class pyfr.backends.openmp.generator.OpenMPKernelGenerator(name, ndim, args, body, fpdtype)
.INDENT 7.0
.TP
.B _abc_impl = <_abc_data object>
.UNINDENT
.INDENT 7.0
.TP
.B _deref_arg_array_1d(arg)
.UNINDENT
.INDENT 7.0
.TP
.B _deref_arg_array_2d(arg)
.UNINDENT
.INDENT 7.0
.TP
.B _deref_arg_view(arg)
.UNINDENT
.INDENT 7.0
.TP
.B _render_body(body)
.UNINDENT
.INDENT 7.0
.TP
.B _render_spec()
.UNINDENT
.INDENT 7.0
.TP
.B argspec()
.UNINDENT
.INDENT 7.0
.TP
.B needs_ldim(arg)
.UNINDENT
.INDENT 7.0
.TP
.B render()
.UNINDENT
.UNINDENT
.sp
Types of \fI\%Kernel Generator\fP are related via the following inheritance diagram:
.SS PyFR\-Mako
.SS PyFR\-Mako Kernels
.sp
PyFR\-Mako kernels are specifications of point\-wise functionality that
can be invoked directly from within PyFR. They are opened with a header
of the form:
.INDENT 0.0
.INDENT 3.5
.sp
.nf
.ft C
<%pyfr:kernel name=\(aqkernel\-name\(aq ndim=\(aqdata\-dimensionality\(aq [argument\-name=\(aqargument\-intent argument\-attribute argument\-data\-type\(aq ...]>
.ft P
.fi
.UNINDENT
.UNINDENT
.sp
where
.INDENT 0.0
.IP 1. 3
\fBkernel\-name\fP \-\-\- name of kernel
.INDENT 3.0
.INDENT 3.5
\fIstring\fP
.UNINDENT
.UNINDENT
.IP 2. 3
\fBdata\-dimensionality\fP \-\-\- dimensionality of data
.INDENT 3.0
.INDENT 3.5
\fIint\fP
.UNINDENT
.UNINDENT
.IP 3. 3
\fBargument\-name\fP \-\-\- name of argument
.INDENT 3.0
.INDENT 3.5
\fIstring\fP
.UNINDENT
.UNINDENT
.IP 4. 3
\fBargument\-intent\fP \-\-\- intent of argument
.INDENT 3.0
.INDENT 3.5
\fBin\fP | \fBout\fP | \fBinout\fP
.UNINDENT
.UNINDENT
.IP 5. 3
\fBargument\-attribute\fP \-\-\- attribute of argument
.INDENT 3.0
.INDENT 3.5
\fBmpi\fP | \fBscalar\fP | \fBview\fP
.UNINDENT
.UNINDENT
.IP 6. 3
\fBargument\-data\-type\fP \-\-\- data type of argument
.INDENT 3.0
.INDENT 3.5
\fIstring\fP
.UNINDENT
.UNINDENT
.UNINDENT
.sp
and are closed with a footer of the form:
.INDENT 0.0
.INDENT 3.5
.sp
.nf
.ft C
</%pyfr:kernel>
.ft P
.fi
.UNINDENT
.UNINDENT
.SS PyFR\-Mako Macros
.sp
PyFR\-Mako macros are specifications of point\-wise functionality that
cannot be invoked directly from within PyFR, but can be embedded into
PyFR\-Mako kernels. PyFR\-Mako macros can be viewed as building blocks
for PyFR\-mako kernels. They are opened with a header of the form:
.INDENT 0.0
.INDENT 3.5
.sp
.nf
.ft C
<%pyfr:macro name=\(aqmacro\-name\(aq params=\(aq[parameter\-name, ...]\(aq>
.ft P
.fi
.UNINDENT
.UNINDENT
.sp
where
.INDENT 0.0
.IP 1. 3
\fBmacro\-name\fP \-\-\- name of macro
.INDENT 3.0
.INDENT 3.5
\fIstring\fP
.UNINDENT
.UNINDENT
.IP 2. 3
\fBparameter\-name\fP \-\-\- name of parameter
.INDENT 3.0
.INDENT 3.5
\fIstring\fP
.UNINDENT
.UNINDENT
.UNINDENT
.sp
and are closed with a footer of the form:
.INDENT 0.0
.INDENT 3.5
.sp
.nf
.ft C
</%pyfr:macro>
.ft P
.fi
.UNINDENT
.UNINDENT
.sp
PyFR\-Mako macros are embedded within a kernel using an expression of
the following form:
.INDENT 0.0
.INDENT 3.5
.sp
.nf
.ft C
${pyfr.expand(\(aqmacro\-name\(aq, [\(aqparameter\-name\(aq, ...])};
.ft P
.fi
.UNINDENT
.UNINDENT
.sp
where
.INDENT 0.0
.IP 1. 3
\fBmacro\-name\fP \-\-\- name of the macro
.INDENT 3.0
.INDENT 3.5
\fIstring\fP
.UNINDENT
.UNINDENT
.IP 2. 3
\fBparameter\-name\fP \-\-\- name of parameter
.INDENT 3.0
.INDENT 3.5
\fIstring\fP
.UNINDENT
.UNINDENT
.UNINDENT
.SS Syntax
.SS Basic Functionality
.sp
Basic functionality can be expressed using a restricted subset of the C
programming language. Specifically, use of the following is allowed:
.INDENT 0.0
.IP 1. 3
\fB+,\-,*,/\fP \-\-\- basic arithmetic
.IP 2. 3
\fBsin, cos, tan\fP \-\-\- basic trigonometric functions
.IP 3. 3
\fBexp\fP \-\-\- exponential
.IP 4. 3
\fBpow\fP \-\-\- power
.IP 5. 3
\fBfabs\fP \-\-\- absolute value
.IP 6. 3
\fBoutput = ( condition ? satisfied : unsatisfied )\fP \-\-\- ternary if
.IP 7. 3
\fBmin\fP \-\-\- minimum
.IP 8. 3
\fBmax\fP \-\-\- maximum
.UNINDENT
.sp
However, conditional if statements, as well as for/while loops, are
not allowed.
.SS Expression Substitution
.sp
Mako expression substitution can be used to facilitate PyFR\-Mako kernel
specification. A Python expression \fBexpression\fP prescribed thus
\fB${expression}\fP is substituted for the result when the PyFR\-Mako
kernel specification is interpreted at runtime.
.sp
Example:
.INDENT 0.0
.INDENT 3.5
.sp
.nf
.ft C
E = s[${ndims \- 1}]
.ft P
.fi
.UNINDENT
.UNINDENT
.SS Conditionals
.sp
Mako conditionals can be used to facilitate PyFR\-Mako kernel
specification. Conditionals are opened with \fB% if condition:\fP and
closed with \fB% endif\fP\&. Note that such conditionals are evaluated
when the PyFR\-Mako kernel specification is interpreted at runtime, they
are not embedded into the low\-level kernel.
.sp
Example:
.INDENT 0.0
.INDENT 3.5
.sp
.nf
.ft C
% if ndims == 2:
    fout[0][1] += t_xx;     fout[1][1] += t_xy;
    fout[0][2] += t_xy;     fout[1][2] += t_yy;
    fout[0][3] += u*t_xx + v*t_xy + ${\-c[\(aqmu\(aq]*c[\(aqgamma\(aq]/c[\(aqPr\(aq]}*T_x;
    fout[1][3] += u*t_xy + v*t_yy + ${\-c[\(aqmu\(aq]*c[\(aqgamma\(aq]/c[\(aqPr\(aq]}*T_y;
% endif
.ft P
.fi
.UNINDENT
.UNINDENT
.SS Loops
.sp
Mako loops can be used to facilitate PyFR\-Mako kernel specification.
Loops are opened with \fB% for condition:\fP and closed with \fB%
endfor\fP\&. Note that such loops are unrolled when the PyFR\-Mako kernel
specification is interpreted at runtime, they are not embedded into the
low\-level kernel.
.sp
Example:
.INDENT 0.0
.INDENT 3.5
.sp
.nf
.ft C
% for i in range(ndims):
    rhov[${i}] = s[${i + 1}];
    v[${i}] = invrho*rhov[${i}];
% endfor
.ft P
.fi
.UNINDENT
.UNINDENT
.SH INDICES AND TABLES
.INDENT 0.0
.IP \(bu 2
genindex
.IP \(bu 2
modindex
.IP \(bu 2
search
.UNINDENT
.SH AUTHOR
Imperial College London
.SH COPYRIGHT
2013-2019, Imperial College London
.\" Generated by docutils manpage writer.
.