data structures, new testing concept

This commit is contained in:
Jukka Aho
2015-11-01 18:44:50 +02:00
parent cd1023cf08
commit 3cac7d9b83
16 changed files with 867 additions and 847 deletions
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# This file is a part of JuliaFEM.
# License is MIT: see https://github.com/JuliaFEM/JuliaFEM.jl/blob/master/LICENSE.md
abstract AbstractBasis
""" Defined to dimensionless coordinate ξ∈[-1,1]^n. """
type SpatialBasis <: AbstractBasis
basis :: Function
dbasisdxi :: Function
end
typealias Basis SpatialBasis
""" Defined to to interval t∈[0, 1]. """
type TemporalBasis <: AbstractBasis
basis :: Function
dbasisdt :: Function
end
function TemporalBasis()
basis(t) = [1-t, t]
dbasis(t) = [-1, 1]
return TemporalBasis(basis, dbasis)
end
function call(b::TemporalBasis, value::Number)
b.basis(value)
end
function call(b::SpatialBasis, value::Vector)
b.basis(value)
end
### INTERPOLATION IN TIME DOMAIN ###
function Base.call(field::Field, basis::TemporalBasis, time)
# FieldSet -> Field -> TimeStep -> Increment -> data
# special cases, -Inf, +Inf and ~0.0
if time > field[end].time
return field[end][end]
end
if (time < field[1].time) || abs(time-field[1].time) < 1.0e-12
return field[1][end]
end
i = length(field)
while field[i].time >= time
i -= 1
end
field[i].time == time && return field[i][end]
t1 = field[i].time
t2 = field[i+1].time
inc1 = field[i][end]
inc2 = field[i+1][end]
# TODO: may there be some reasons for "unphysical" jumps in
# fields w.r.t time which should be taken account in some way?
# i.e. dt between two fields → 0
dt = t2 - t1
b = basis.basis((time-t1)/dt)
r = Increment[inc1, inc2]
return dot(b, r)
end
function Base.call(field::DiscreteField, time)
return Base.call(field, TemporalBasis(), time)
end
function Base.call(field::Field, basis::TemporalBasis, time,
derivative::Type{Val{:derivative}})
# FieldSet -> Field -> TimeStep -> Increment -> data
if length(field) == 1
# just one timestep, time derivative cannot be evaluated.
error("Field length = $(length(field)), cannot evaluate time derivative")
end
function eval_field(i, j)
timesteps = TimeStep[field[i], field[j]]
increments = Increment[timesteps[1][end], timesteps[2][end]]
J = norm(timesteps[2].time - timesteps[1].time)
dbasisdt = basis.dbasisdt( (time-timesteps[1].time)/J )
return dot(dbasisdt, increments)/J
end
# special cases, +Inf, -Inf, ~0.0
if (time > field[end].time) || isapprox(time, field[end].time)
return eval_field(endof(field)-1, endof(field))
end
if (time < field[1].time) || isapprox(time, field[1].time)
return eval_field(1, 2)
end
# search for a correct "bin" between time steps
i = length(field)
while (field[i].time > time) && !isapprox(field[i].time, time)
i -= 1
end
if isapprox(field[i].time, time)
# This is the hard case, maybe discontinuous time
# derivative if linear approximation.
# we are on the "mid node" in time axis
field1 = eval_field(i-1,i)
field2 = eval_field(i,i+1)
return 1/2*(field1 + field2)
end
return eval_field(i, i+1)
end
### INTERPOLATION IN SPATIAL DOMAIN ###
function Base.call(increment::Increment, basis::SpatialBasis, xi::Vector)
basis = basis.basis(xi)
sum([basis[i]*increment[i] for i=1:length(increment)])
end
function Base.call(increment::Increment, basis::SpatialBasis, xi::Vector,
geometry::Increment, gradient::Type{Val{:gradient}})
dbasis = basis.dbasisdxi(xi)
J = sum([dbasis[:,i]*geometry[i]' for i=1:length(geometry)])
grad = inv(J)*dbasis
gradf = sum([grad[:,i]*increment[i]' for i=1:length(increment)])'
return gradf
end