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fix: detect observed variables and dependent parameters dependent on discrete parameters #3106

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fix: detect observed variables and dependent parameters dependent on discrete parameters #3106

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95154e2
fix: detect observed variables and dependent parameters dependent on …
AayushSabharwal Oct 8, 2024
a126bf9
fix: fix timeseries detection for shifted variables in DDEs
AayushSabharwal Oct 28, 2024
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17 changes: 13 additions & 4 deletions src/systems/abstractsystem.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -731,7 +731,7 @@ end
function has_observed_with_lhs(sys, sym)
has_observed(sys) || return false
if has_index_cache(sys) && (ic = get_index_cache(sys)) !== nothing
return any(isequal(sym), ic.observed_syms)
return haskey(ic.observed_syms_to_timeseries, sym)
else
return any(isequal(sym), [eq.lhs for eq in observed(sys)])
end
Expand All @@ -740,7 +740,7 @@ end
function has_parameter_dependency_with_lhs(sys, sym)
has_parameter_dependencies(sys) || return false
if has_index_cache(sys) && (ic = get_index_cache(sys)) !== nothing
return any(isequal(sym), ic.dependent_pars)
return haskey(ic.dependent_pars_to_timeseries, unwrap(sym))
else
return any(isequal(sym), [eq.lhs for eq in parameter_dependencies(sys)])
end
Expand All @@ -762,11 +762,20 @@ for traitT in [
allsyms = vars(sym; op = Symbolics.Operator)
for s in allsyms
s = unwrap(s)
if is_variable(sys, s) || is_independent_variable(sys, s) ||
has_observed_with_lhs(sys, s)
if is_variable(sys, s) || is_independent_variable(sys, s)
push!(ts_idxs, ContinuousTimeseries())
elseif is_timeseries_parameter(sys, s)
push!(ts_idxs, timeseries_parameter_index(sys, s).timeseries_idx)
elseif is_time_dependent(sys) && iscall(s) && issym(operation(s)) &&
is_variable(sys, operation(s)(get_iv(sys)))
# DDEs case, to detect x(t - k)
push!(ts_idxs, ContinuousTimeseries())
elseif has_index_cache(sys) && (ic = get_index_cache(sys)) !== nothing
if (ts = get(ic.observed_syms_to_timeseries, s, nothing)) !== nothing
union!(ts_idxs, ts)
elseif (ts = get(ic.dependent_pars_to_timeseries, s, nothing)) !== nothing
union!(ts_idxs, ts)
end
end
end
end
Expand Down
11 changes: 10 additions & 1 deletion src/systems/diffeqs/odesystem.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -448,7 +448,16 @@ function build_explicit_observed_function(sys, ts;
ivs = independent_variables(sys)
dep_vars = scalarize(setdiff(vars, ivs))

obs = param_only ? Equation[] : observed(sys)
obs = observed(sys)
if param_only
if has_index_cache(sys) && (ic = get_index_cache(sys)) !== nothing
obs = filter(obs) do eq
!(ContinuousTimeseries() in ic.observed_syms_to_timeseries[eq.lhs])
end
else
obs = Equation[]
end
end

cs = collect_constants(obs)
if !isempty(cs) > 0
Expand Down
87 changes: 58 additions & 29 deletions src/systems/index_cache.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -38,6 +38,7 @@ const UnknownIndexMap = Dict{
BasicSymbolic, Union{Int, UnitRange{Int}, AbstractArray{Int}}}
const TunableIndexMap = Dict{BasicSymbolic,
Union{Int, UnitRange{Int}, Base.ReshapedArray{Int, N, UnitRange{Int}} where {N}}}
const TimeseriesSetType = Set{Union{ContinuousTimeseries, Int}}

struct IndexCache
unknown_idx::UnknownIndexMap
Expand All @@ -48,8 +49,9 @@ struct IndexCache
tunable_idx::TunableIndexMap
constant_idx::ParamIndexMap
nonnumeric_idx::NonnumericMap
observed_syms::Set{BasicSymbolic}
dependent_pars::Set{Union{BasicSymbolic, CallWithMetadata}}
observed_syms_to_timeseries::Dict{BasicSymbolic, TimeseriesSetType}
dependent_pars_to_timeseries::Dict{
Union{BasicSymbolic, CallWithMetadata}, TimeseriesSetType}
discrete_buffer_sizes::Vector{Vector{BufferTemplate}}
tunable_buffer_size::BufferTemplate
constant_buffer_sizes::Vector{BufferTemplate}
Expand Down Expand Up @@ -91,20 +93,6 @@ function IndexCache(sys::AbstractSystem)
end
end

observed_syms = Set{BasicSymbolic}()
for eq in observed(sys)
if symbolic_type(eq.lhs) != NotSymbolic()
sym = eq.lhs
ttsym = default_toterm(sym)
rsym = renamespace(sys, sym)
rttsym = renamespace(sys, ttsym)
push!(observed_syms, sym)
push!(observed_syms, ttsym)
push!(observed_syms, rsym)
push!(observed_syms, rttsym)
end
end

tunable_buffers = Dict{Any, Set{BasicSymbolic}}()
constant_buffers = Dict{Any, Set{BasicSymbolic}}()
nonnumeric_buffers = Dict{Any, Set{Union{BasicSymbolic, CallWithMetadata}}}()
Expand Down Expand Up @@ -267,38 +255,79 @@ function IndexCache(sys::AbstractSystem)
end
end

for sym in Iterators.flatten((keys(unk_idxs), keys(disc_idxs), keys(tunable_idxs),
keys(const_idxs), keys(nonnumeric_idxs),
observed_syms, independent_variable_symbols(sys)))
if hasname(sym) && (!iscall(sym) || operation(sym) !== getindex)
symbol_to_variable[getname(sym)] = sym
end
end

dependent_pars = Set{Union{BasicSymbolic, CallWithMetadata}}()
dependent_pars_to_timeseries = Dict{
Union{BasicSymbolic, CallWithMetadata}, TimeseriesSetType}()

for eq in parameter_dependencies(sys)
sym = eq.lhs
vs = vars(eq.rhs)
timeseries = TimeseriesSetType()
if is_time_dependent(sys)
for v in vs
if (idx = get(disc_idxs, v, nothing)) !== nothing
push!(timeseries, idx.clock_idx)
end
end
end
ttsym = default_toterm(sym)
rsym = renamespace(sys, sym)
rttsym = renamespace(sys, ttsym)
for s in [sym, ttsym, rsym, rttsym]
push!(dependent_pars, s)
for s in (sym, ttsym, rsym, rttsym)
dependent_pars_to_timeseries[s] = timeseries
if hasname(s) && (!iscall(s) || operation(s) != getindex)
symbol_to_variable[getname(s)] = sym
end
end
end

observed_syms_to_timeseries = Dict{BasicSymbolic, TimeseriesSetType}()
for eq in observed(sys)
if symbolic_type(eq.lhs) != NotSymbolic()
sym = eq.lhs
vs = vars(eq.rhs)
timeseries = TimeseriesSetType()
if is_time_dependent(sys)
for v in vs
if (idx = get(disc_idxs, v, nothing)) !== nothing
push!(timeseries, idx.clock_idx)
elseif haskey(unk_idxs, v)
push!(timeseries, ContinuousTimeseries())
elseif haskey(observed_syms_to_timeseries, v)
union!(timeseries, observed_syms_to_timeseries[v])
elseif haskey(dependent_pars_to_timeseries, v)
union!(timeseries, dependent_pars_to_timeseries[v])
elseif iscall(v) && issym(operation(v)) &&
is_variable(sys, operation(v)(get_iv(sys)))
push!(timeseries, ContinuousTimeseries())
end
end
end
ttsym = default_toterm(sym)
rsym = renamespace(sys, sym)
rttsym = renamespace(sys, ttsym)
for s in (sym, ttsym, rsym, rttsym)
observed_syms_to_timeseries[s] = timeseries
end
end
end

for sym in Iterators.flatten((keys(unk_idxs), keys(disc_idxs), keys(tunable_idxs),
keys(const_idxs), keys(nonnumeric_idxs),
keys(observed_syms_to_timeseries), independent_variable_symbols(sys)))
if hasname(sym) && (!iscall(sym) || operation(sym) !== getindex)
symbol_to_variable[getname(sym)] = sym
end
end

return IndexCache(
unk_idxs,
disc_idxs,
callback_to_clocks,
tunable_idxs,
const_idxs,
nonnumeric_idxs,
observed_syms,
dependent_pars,
observed_syms_to_timeseries,
dependent_pars_to_timeseries,
disc_buffer_templates,
BufferTemplate(Real, tunable_buffer_size),
const_buffer_sizes,
Expand Down
11 changes: 11 additions & 0 deletions test/odesystem.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -1467,3 +1467,14 @@ end
obsfn(buf, prob.u0, prob.p, 0.0)
@test buf ≈ [1.0, 1.0, 2.0]
end

# https://github.com/SciML/SciMLBase.jl/issues/786
@testset "Observed variables dependent on discrete parameters" begin
@variables x(t) obs(t)
@parameters c(t)
@mtkbuild sys = ODESystem(
[D(x) ~ c * cos(x), obs ~ c], t, [x], [c]; discrete_events = [1.0 => [c ~ c + 1]])
prob = ODEProblem(sys, [x => 0.0], (0.0, 2pi), [c => 1.0])
sol = solve(prob, Tsit5())
@test sol[obs] ≈ 1:7
end
Comment on lines +1472 to +1480
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I think this MWE I provided in the issue is not a sufficient testcase. I'd propose the following

    @variables x1(t)=0 x2(t)=0 obs1(t) obs2(t)
    @parameters c1(t)=1 c2=1
    @mtkbuild sys = ODESystem(
        [D(x1) ~ c1,
        D(x2) ~ c2,
        obs1 ~ x1*c1,
        obs2 ~ x2*c2], t; discrete_events = [[1.0] => [c1 ~ 0, c2 ~ 0]])
    prob = ODEProblem(sys, [x1=>0, x2=>0], (0.0, 2))
    sol = solve(prob, Tsit5())

    # tests that should pass (?)
    @test sol([0,2], idxs=c1) == [1.0, 0.0]
    @test sol([0,0.9,1.1,2], idxs=obs1) ≈ [0, 0.9, 0, 0]
    @test sol[obs1] == sol(sol.t, idxs=obs1) # errors because of mixed timeseries

    # the following tests check an observable which depends on a parameter which is not declared time dependent, which is done in the docs on discrete events
    # i don't know how this should be handled. Personally, as a user i'd expect all parameters to be discrete timeseries implicitly
    # Depending on your API design, those failures might be by design and don't need fixing.
    @test sol([0,2], idxs=c2) == [1.0, 0.0]
    @test sol([0,0.9,1.1,2], idxs=obs2) ≈ [0, 0.9, 0, 0]
    @test sol[obs2] == sol(sol.t, idxs=obs2)

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