Commit 5c012c87 authored by René Fritze's avatar René Fritze Committed by René Fritze

[demos] format module docstrings so that sphinx does not complain

parent 9c75001f
......@@ -12,6 +12,7 @@ Arguments:
PROBLEM-NUMBER {0,1}, selects the problem to solve
DIRICHLET-NUMBER {0,1,2}, selects the Dirichlet data function
NEUMANN-NUMBER {0,1}, selects the Neumann data function
NEUMANN-COUNT 0: no neumann boundary
1: right edge is neumann boundary
2: right+top edges are neumann boundary
......
......@@ -10,10 +10,13 @@ Usage:
Arguments:
BACKEND Discretization toolkit to use (pymor, fenics).
ALG The model reduction algorithm to use
(greedy, adaptive_greedy, pod).
SNAPSHOTS greedy/pod: number of training set parameters
adaptive_greedy: size of validation set.
RBSIZE Size of the reduced basis.
TEST Number of test parameters for reduction error estimation.
"""
......
......@@ -13,43 +13,47 @@ Usage:
Arguments:
XBLOCKS Number of blocks in x direction.
YBLOCKS Number of blocks in y direction.
SNAPSHOTS naive: ignored
greedy/pod: Number of training_set parameters per block
(in total SNAPSHOTS^(XBLOCKS * YBLOCKS)
parameters).
adaptive_greedy: size of validation set.
RBSIZE Size of the reduced basis
Options:
--adaptive-greedy-rho=RHO See pymor.algorithms.adaptivegreedy [default: 1.1].
--adaptive-greedy-gamma=GAMMA See pymor.algorithms.adaptivegreedy [default: 0.2].
--adaptive-greedy-theta=THETA See pymor.algorithms.adaptivegreedy [default: 0.]
--alg=ALG The model reduction algorithm to use
--alg=ALG The model reduction algorithm to use \
(naive, greedy, adaptive_greedy, pod) [default: greedy].
--cache-region=REGION Name of cache region to use for caching solution snapshots
--cache-region=REGION Name of cache region to use for caching solution snapshots \
(none, memory, disk, persistent) [default: none].
--extension-alg=ALG Basis extension algorithm (trivial, gram_schmidt)
--extension-alg=ALG Basis extension algorithm (trivial, gram_schmidt) \
to be used [default: gram_schmidt].
--fenics Use FEniCS model.
--grid=NI Use grid with 4*NI*NI elements [default: 100].
-h, --help Show this message.
--ipython-engines=COUNT If positive, the number of IPython cluster engines to use for
parallel greedy search. If zero, no parallelization is performed.
--ipython-engines=COUNT If positive, the number of IPython cluster engines to use for \
parallel greedy search. If zero, no parallelization is performed. \
[default: 0]
--ipython-profile=PROFILE IPython profile to use for parallelization.
--list-vector-array Solve using ListVectorArray[NumpyVector] instead of NumpyVectorArray.
--order=ORDER Polynomial order of the Lagrange finite elements to use in FEniCS
--order=ORDER Polynomial order of the Lagrange finite elements to use in FEniCS \
model [default: 1].
--pickle=PREFIX Pickle reduced model, as well as reductor and high-dimensional
--pickle=PREFIX Pickle reduced model, as well as reductor and high-dimensional \
model to files with this prefix.
--plot-err Plot error.
--plot-solutions Plot some example solutions.
--plot-error-sequence Plot reduction error vs. basis size.
--product=PROD Product (euclidean, h1) w.r.t. which to orthonormalize
--product=PROD Product (euclidean, h1) w.r.t. which to orthonormalize \
and calculate Riesz representatives [default: h1].
--reductor=RED Reductor (error estimator) to choose (traditional, residual_basis)
--reductor=RED Reductor (error estimator) to choose (traditional, residual_basis) \
[default: residual_basis]
--test=COUNT Use COUNT snapshots for stochastic error estimation
--test=COUNT Use COUNT snapshots for stochastic error estimation \
[default: 10].
--greedy-without-estimator Do not use error estimator for basis generation.
"""
......
......@@ -13,14 +13,16 @@ Usage:
Arguments:
XBLOCKS Number of blocks in x direction.
YBLOCKS Number of blocks in y direction.
SNAPSHOTS Number of snapshots for basis generation per component.
In total SNAPSHOTS^(XBLOCKS * YBLOCKS).
RBSIZE Size of the reduced basis
Options:
--grid=NI Use grid with 2*NI*NI elements [default: 60].
--product=PROD Product (euclidean, h1) w.r.t. which to orthonormalize
--product=PROD Product (euclidean, h1) w.r.t. which to orthonormalize \
and calculate Riesz representatives [default: h1].
--testing load the gui and exit right away (for functional testing)
-h, --help Show this message.
......
......@@ -10,13 +10,16 @@ Usage:
Arguments:
MODEL High-dimensional model (pymor, fenics, ngsolve, pymor-text).
ALG The model reduction algorithm to use
(naive, greedy, adaptive_greedy, pod).
ALG The model reduction algorithm to use (naive, greedy, adaptive_greedy, pod).
SNAPSHOTS naive: ignored
greedy/pod: Number of training_set parameters per block
(in total SNAPSHOTS^(XBLOCKS * YBLOCKS)
parameters).
adaptive_greedy: size of validation set.
RBSIZE Size of the reduced basis.
TEST Number of parameters for stochastic error estimation.
"""
......
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