Catalyst.jl API

@reaction_network

Generates a ReactionSystem that encodes a chemical reaction network.

See the The Reaction DSL documentation for details on parameters to the macro.

Examples:

# a basic SIR model, with name SIR
sir_model = @reaction_network SIR begin
    c1, s + i --> 2i
    c2, i --> r
end c1 c2

# a basic SIR model, with random generated name
sir_model = @reaction_network begin
    c1, s + i --> 2i
    c2, i --> r
end c1 c2

# an empty network with name empty
emptyrn = @reaction_network empty

# an empty network with random generated name
emptyrn = @reaction_network 

make_empty_network(; iv=DEFAULT_IV, name=gensym(:ReactionSystem))

Construct an empty ReactionSystem. iv is the independent variable, usually time, and name is the name to give the ReactionSystem.

struct Reaction{S, T<:Number}

One chemical reaction.

Fields

• rate

  The rate function (excluding mass action terms).

• substrates

  Reaction substrates.

• products

  Reaction products.

• substoich

  The stoichiometric coefficients of the reactants.

• prodstoich

  The stoichiometric coefficients of the products.

• netstoich

  The net stoichiometric coefficients of all species changed by the reaction.

• only_use_rate

  false (default) if rate should be multiplied by mass action terms to give the rate law. true if rate represents the full reaction rate law.

Examples

using Catalyst
@parameters k[1:20]
@variables t A(t) B(t) C(t) D(t)
rxs = [Reaction(k[1], nothing, [A]),            # 0 -> A
       Reaction(k[2], [B], nothing),            # B -> 0
       Reaction(k[3],[A],[C]),                  # A -> C
       Reaction(k[4], [C], [A,B]),              # C -> A + B
       Reaction(k[5], [C], [A], [1], [2]),      # C -> A + A
       Reaction(k[6], [A,B], [C]),              # A + B -> C
       Reaction(k[7], [B], [A], [2], [1]),      # 2B -> A
       Reaction(k[8], [A,B], [A,C]),            # A + B -> A + C
       Reaction(k[9], [A,B], [C,D]),            # A + B -> C + D
       Reaction(k[10], [A], [C,D], [2], [1,1]), # 2A -> C + D
       Reaction(k[11], [A], [A,B], [2], [1,1]), # 2A -> A + B
       Reaction(k[12], [A,B,C], [C,D], [1,3,4], [2, 3]),          # A+3B+4C -> 2C + 3D
       Reaction(k[13], [A,B], nothing, [3,1], nothing),           # 3A+B -> 0
       Reaction(k[14], nothing, [A], nothing, [2]),               # 0 -> 2A
       Reaction(k[15]*A/(2+A), [A], nothing; only_use_rate=true), # A -> 0 with custom rate
       Reaction(k[16], [A], [B]; only_use_rate=true),             # A -> B with custom rate.
       Reaction(k[17]*A*exp(B), [C], [D], [2], [1]),              # 2C -> D with non constant rate.
       Reaction(k[18]*B, nothing, [B], nothing, [2]),             # 0 -> 2B with non constant rate.
       Reaction(k[19]*t, [A], [B]),                                # A -> B with non constant rate.
       Reaction(k[20]*t*A, [B,C], [D],[2,1],[2])                  # 2A +B -> 2C with non constant rate.
  ]

Notes:

• nothing can be used to indicate a reaction that has no reactants or no products. In this case the corresponding stoichiometry vector should also be set to nothing.
• The three-argument form assumes all reactant and product stoichiometric coefficients are one.

struct ReactionSystem{U<:Union{Nothing, ModelingToolkit.AbstractSystem}} <: AbstractTimeDependentSystem

A system of chemical reactions.

Fields

• eqs

  The reactions defining the system.

• iv

  Independent variable (usually time).

• states

  Dependent (state) variables representing amount of each species. Must not contain the independent variable.

• ps

  Parameter variables. Must not contain the independent variable.

• observed

  Equations for observed variables.

• name

  The name of the system

• systems

  Internal sub-systems

• defaults

  The default values to use when initial conditions and/or parameters are not supplied in ODEProblem.

• connection_type

  Type of the system

• constraints

  Non-Reaction equations that further constrain the system

Example

Continuing from the example in the Reaction definition:

# simple constructor that infers species and parameters
@named rs = ReactionSystem(rxs, t)   

# allows specification of species and parameters
@named rs = ReactionSystem(rxs, t, [A,B,C,D], k) 

Keyword Arguments:

• observed::Vector{Equation}, equations specifying observed variables.
• systems::Vector{AbstractSystems}, vector of sub-systems. Can be ReactionSystems, ODESystems, or NonlinearSystems.
• name::Symbol, the name of the system (must be provided, or @named must be used).
• defaults::Dict, a dictionary mapping parameters to their default values and species to their default initial values.
• checks = true, boolean for whether to check units.
• constraints = nothing, a NonlinearSystem or ODESystem of coupled constraint equations.

Notes:

• ReactionSystems currently do rudimentary unit checking, requiring that all species have the same units, and all reactions have rate laws with units of (species units) / (time units). Unit checking can be disabled by passing the keyword argument checks=false.

species(network)

Given a ReactionSystem, return a vector of all species defined in the system and any subsystems that are of type ReactionSystem. To get the variables in the system and all subsystems, including non-ReactionSystem subsystems, uses states(network).

Notes:

• If ModelingToolkit.get_systems(network) is non-empty will allocate.

reactionparams(network)

Given a ReactionSystem, return a vector of all parameters defined within the system and any subsystems that are of type ReactionSystem. To get the parameters in the system and all subsystems, including non-ReactionSystem subsystems, use parameters(network).

Notes:

• If ModelingToolkit.get_systems(network) is non-empty will allocate.

reactions(network)

Given a ReactionSystem, return a vector of all Reactions in the system.

Notes:

• If ModelingToolkit.get_systems(network) is not empty, will allocate.

numspecies(network)

Return the total number of species within the given ReactionSystem and subsystems that are ReactionSystems.

Notes

• If there are no subsystems this will be fast.
• As this calls species, it can be slow and will allocate if there are any subsystems.

numreactions(network)

Return the total number of reactions within the given ReactionSystem and subsystems that are ReactionSystems.

numreactionparams(network)

Return the total number of parameters within the given ReactionSystem and subsystems that are ReactionSystems.

Notes

• If there are no subsystems this will be fast.
• As this calls reactionparams, it can be slow and will allocate if there are any subsystems.

speciesmap(network)

Given a ReactionSystem, return a Dictionary mapping species that participate in Reactions to their index within species(network).

paramsmap(network)

Given a ReactionSystem, return a Dictionary mapping from all parameters that appear within the system to their index within parameters(network).

reactionparamsmap(network)

Given a ReactionSystem, return a Dictionary mapping from parameters that appear within Reactions to their index within reactionparams(network).

ismassaction(rx, rs; rxvars = get_variables(rx.rate),
                              haveivdep = any(var -> isequal(get_iv(rs),var), rxvars),
                              stateset = Set(states(rs)))

True if a given reaction is of mass action form, i.e. rx.rate does not depend on any chemical species that correspond to states of the system, and does not depend explicitly on the independent variable (usually time).

Arguments

• rx, the Reaction.
• rs, a ReactionSystem containing the reaction.
• Optional: rxvars, Variables which are not in rxvars are ignored as possible dependencies.
• Optional: haveivdep, true if the Reaction rate field explicitly depends on the independent variable.
• Optional: stateset, set of states which if the rxvars are within mean rx is non-mass action.

dependents(rx, network)

Given a Reaction and a ReactionSystem, return a vector of ModelingToolkit.Nums corresponding to species the reaction rate law depends on. E.g., for

k*W, 2X + 3Y --> 5Z + W

the returned vector would be [W(t),X(t),Y(t)].

Notes:

• Allocates
• Does not check for dependents within any subsystems.

dependents(rx, network)

See documentation for dependents.

substoichmat(rn; sparse=false, smap=speciesmap(rn))

Returns the substrate stoichiometry matrix, $S$, with $S_{i j}$ the stoichiometric coefficient of the ith substrate within the jth reaction.

Note:

• Set sparse=true for a sparse matrix representation

prodstoichmat(rn; sparse=false, smap=speciesmap(rn))

Returns the product stoichiometry matrix, $P$, with $P_{i j}$ the stoichiometric coefficient of the ith product within the jth reaction.

Note:

• Set sparse=true for a sparse matrix representation

netstoichmat(rn, sparse=false; smap=speciesmap(rn))

Returns the net stoichiometry matrix, $N$, with $N_{i j}$ the net stoichiometric coefficient of the ith species within the jth reaction.

Note:

• Set sparse=true for a sparse matrix representation

reactionrates(network)

Given a ReactionSystem, returns a vector of the symbolic reaction rates for each reaction.

@add_reactions

Adds the reactions declared to a preexisting ReactionSystem. All parameters used in the added reactions need to be declared after the reactions.

See the Catalyst.jl for Reaction Models documentation for details on parameters to the macro.

addspecies!(network::ReactionSystem, s::Symbolic; disablechecks=false)

Given a ReactionSystem, add the species corresponding to the variable s to the network (if it is not already defined). Returns the integer id of the species within the system.

Notes:

• disablechecks will disable checking for whether the passed in variable is already defined, which is useful when adding many new variables to the system. Do not disable checks unless you are sure the passed in variable is a new variable, as this will potentially leave the system in an undefined state.

addspecies!(network::ReactionSystem, s::Num; disablechecks=false)

Given a ReactionSystem, add the species corresponding to the variable s to the network (if it is not already defined). Returns the integer id of the species within the system.

• disablechecks will disable checking for whether the passed in variable is already defined, which is useful when adding many new variables to the system. Do not disable checks unless you are sure the passed in variable is a new variable, as this will potentially leave the system in an undefined state.

reorder_states!(rn, neworder)

Given a ReactionSystem and a vector neworder, orders the states of rn accordingly to neworder.

Notes:

• Currently only supports ReactionSystems without constraints or subsystems.

addparam!(network::ReactionSystem, p::Symbolic; disablechecks=false)

Given a ReactionSystem, add the parameter corresponding to the variable p to the network (if it is not already defined). Returns the integer id of the parameter within the system.

• disablechecks will disable checking for whether the passed in variable is already defined, which is useful when adding many new variables to the system. Do not disable checks unless you are sure the passed in variable is a new variable, as this will potentially leave the system in an undefined state.

addparam!(network::ReactionSystem, p::Num; disablechecks=false)

Given a ReactionSystem, add the parameter corresponding to the variable p to the network (if it is not already defined). Returns the integer id of the parameter within the system.

• disablechecks will disable checking for whether the passed in variable is already defined, which is useful when adding many new variables to the system. Do not disable checks unless you are sure the passed in variable is a new variable, as this will potentially leave the system in an undefined state.

addreaction!(network::ReactionSystem, rx::Reaction)

Add the passed in reaction to the ReactionSystem. Returns the integer id of rx in the list of Reactions within network.

Notes:

• Any new species or parameters used in rx should be separately added to network using addspecies! and addparam!.

ModelingToolkit.extend(sys::Union{NonlinearSystem,ODESystem}, rs::ReactionSystem; name::Symbol=nameof(sys))

Extends the indicated ReactionSystem with a ModelingToolkit.NonlinearSystem or ModelingToolkit.ODESystem, which will be stored internally as constraint equations.

Notes:

• Returns a new ReactionSystem and does not modify rs.
• By default, the new ReactionSystem will have the same name as sys.

ModelingToolkit.extend(sys::ReactionSystem, rs::ReactionSystem; name::Symbol=nameof(sys))

Extends the indicated ReactionSystem with another ReactionSystem. Similar to calling merge! except constraint systems are allowed (and will also be merged together).

Notes:

• Returns a new ReactionSystem and does not modify rs.
• By default, the new ReactionSystem will have the same name as sys.

extend(sys::ModelingToolkit.AbstractSystem, basesys::ModelingToolkit.AbstractSystem; name) -> ReactionSystem

entend the basesys with sys, the resulting system would inherit sys's name by default.

compose(sys, systems; name)

compose multiple systems together. The resulting system would inherit the first system's name.

Catalyst.flatten(rs::ReactionSystem)

Merges all subsystems of the given ReactionSystem up into rs.

Notes:

• Returns a new ReactionSystem that represents the flattened system.
• All Reactions within subsystems are namespaced and merged into the list of Reactions of rs. The merged list is then available as reactions(rs) or get_eqs(rs).
• All algebraic equations are merged into a NonlinearSystem or ODESystem stored as get_constraints(rs). If get_constraints !== nothing then the algebraic equations are merged with the current constraints in a system of the same type as the current constraints, otherwise the new constraint system is an ODESystem.
• Currently only ReactionSystems, NonlinearSystems and ODESystems are supported as sub-systems when flattening.

merge!(network1::ReactionSystem, network2::ReactionSystem)

Merge network2 into network1.

Notes:

• Duplicate reactions between the two networks are not filtered out.
• Reactions are not deepcopied to minimize allocations, so both networks will share underlying data arrays.
• Subsystems are not deepcopied between the two networks and will hence be shared.
• Returns network1.

conservationlaws(netstoichmat::AbstractMatrix)::Matrix

Given the net stoichiometry matrix of a reaction system, computes a matrix of conservation laws, each represented as a row in the output.

conservedquantities(state, cons_laws)

Compute conserved quantities for a system with the given conservation laws.

struct ReactionComplexElement{T}

One reaction complex element

Fields

• speciesid

  The integer id of the species representing this element.

• speciesstoich

  The stoichiometric coefficient of this species.

struct ReactionComplex{V<:Integer} <: AbstractArray{Catalyst.ReactionComplexElement{V<:Integer}, 1}

One reaction complex.

Fields

• speciesids

  The integer ids of all species participating in this complex.

• speciesstoichs

  The stoichiometric coefficients of all species participating in this complex.

reactioncomplexmap(rn::ReactionSystem; smap=speciesmap(rn))

Find each ReactionComplex within the specified system, constructing a mapping from the complex to vectors that indicate which reactions it appears in as substrates and products.

Notes:

• Each ReactionComplex is mapped to a vector of pairs, with each pair having the form reactionidx => ± 1, where -1 indicates the complex appears as a substrate and +1 as a product in the reaction with integer label reactionidx.

reactioncomplexes(network::ReactionSystem; sparse=false, smap=speciesmap(rn), 
                  complextorxsmap=reactioncomplexmap(rn; smap=smap))

Calculate the reaction complexes and complex incidence matrix for the given ReactionSystem.

Notes:

• returns a pair of a vector of ReactionComplexs and the complex incidence matrix.
• An empty ReactionComplex denotes the null (∅) state (from reactions like ∅ -> A or A -> ∅).
• The complex incidence matrix, $B$, is number of complexes by number of reactions with

\[B_{i j} = \begin{cases} -1, &\text{if the i'th complex is the substrate of the j'th reaction},\\ 1, &\text{if the i'th complex is the product of the j'th reaction},\\ 0, &\text{otherwise.} \end{cases}\]

• Set sparse=true for a sparse matrix representation of the incidence matrix

complexstoichmat(network::ReactionSystem; sparse=false, rcs=keys(reactioncomplexmap(rn)))

Given a ReactionSystem and vector of reaction complexes, return a matrix with positive entries of size number of species by number of complexes, where the non-zero positive entries in the kth column denote stoichiometric coefficients of the species participating in the kth reaction complex.

Notes:

• rcs correspond to an iterable of the ReactionComplexes, i.e. rcs=keys(reactioncomplexmap(rn)) or reactioncomplexes(rn)[1].
• Set sparse=true for a sparse matrix representation

complexoutgoingmat(network; sparse=false, B=reactioncomplexes(rn)[2])

Given a ReactionSystem and complex incidence matrix, $B$, return a matrix of size num of complexes by num of reactions that identifies substrate complexes.

Notes:

• The complex outgoing matrix, $\Delta$, is defined by

\[\Delta_{i j} = \begin{cases} = 0, &\text{if } B_{i j} = 1, \\ = B_{i j}, &\text{otherwise.} \end{cases}\]

• Set sparse=true for a sparse matrix representation

incidencematgraph(incidencemat)

Given an incidence matrix of a reaction-network, construct a directed simple graph where nodes correspond to reaction complexes and directed edges to reactions converting between two complexes.

For example,

sir = @reaction_network SIR begin
    β, S + I --> 2I
    ν, I --> R
end β ν
rcs,incidencemat = reactioncomplexes(sir)
incidencegraph   = incidencematgraph(incidencemat)

linkageclasses(incidencegraph)

Given the incidence graph of a reaction network, return a vector of the connected components of the graph (i.e. sub-groups of reaction complexes that are connected in the incidence graph).

For example, continuing the example from incidencematgraph

julia> linkageclasses(incidencegraph)
2-element Vector{Vector{Int64}}:
 [1, 2]
 [3, 4]

deficiency(netstoich_mat, incidence_graph, linkage_classes)

Calculate the deficiency of a reaction network.

Here the deficiency, $\delta$, of a network with $n$ reaction complexes, $\ell$ linkage classes and a rank $s$ stoichiometric matrix is

\[\delta = n - \ell - s\]

For example,

sir = @reaction_network SIR begin
    β, S + I --> 2I
    ν, I --> R
end β ν
rcs,incidencemat = reactioncomplexes(sir)
incidence_graph  = incidencematgraph(incidencemat)
linkage_classes   = linkageclasses(incidence_graph)
netstoich_mat    = netstoichmat(sir)
δ = deficiency(netstoich_mat, incidence_graph, linkage_classes)

subnetworks(network, linkage_classes ; rxs = reactions(network),
              complextorxmap = collect(values(reactioncomplexmap(network))),
              p = parameters(network))

Find subnetworks corresponding to the each linkage class of reaction network

For example, continuing the example from deficiency

   subnets = subnetworks(sir, linkage_classes)

linkagedeficiencies(subnetworks::AbstractVector, linkage_classes::AbstractVector)

Calculates the deficiency of each sub-reaction network defined by a collection of linkage_classes.

For example, continuing the example from deficiency

subnets = subnetworks(sir, linkage_classes)
linkage_deficiencies = linkagedeficiency(subnets, linkage_classes)

isreversible(incidencegraph)

Given an incidence graph of the reaction network, returns if the network is reversible or not. For example, continuing the example from linkagedeficiencies

isreversible(incidence_graph)

isweaklyreversible(subnetworks)

Given the subnetworks corresponding to the each linkage class of reaction network, determines if the reaction network is weakly reversible or not. For example, continuing the example from isreversible

isweaklyreversible(subnets)

==(rx1::Reaction, rx2::Reaction)

Tests whether two Reactions are identical.

Notes:

• Ignores the order in which stoichiometry components are listed.
• Does not currently simplify rates, so a rate of A^2+2*A+1 would be considered different than (A+1)^2.

isequal_ignore_names(rn1::ReactionSystem, rn2::ReactionSystem)

Tests whether the underlying species, parameters and reactions are the same in the two ReactionSystems. Ignores the names of the systems in testing equality.

Notes:

• Does not currently simplify rates, so a rate of A^2+2*A+1 would be considered different than (A+1)^2.
• Does not include defaults in determining equality.

==(rn1::ReactionSystem, rn2::ReactionSystem)

Tests whether the underlying species, parameters and reactions are the same in the two ReactionSystems. Requires the systems to have the same names too.

Notes:

• Does not currently simplify rates, so a rate of A^2+2*A+1 would be considered different than (A+1)^2.
• Does not include defaults in determining equality.

Graph(rn::ReactionSystem)

Converts a ReactionSystem into a Graphviz graph. Reactions correspond to small green circles, and species to blue circles.

Notes:

• Black arrows from species to reactions indicate reactants, and are labelled with their input stoichiometry.
• Black arrows from reactions to species indicate products, and are labelled with their output stoichiometry.
• Red arrows from species to reactions indicate that species is used within the rate expression. For example, in the reaction k*A, B --> C, there would be a red arrow from A to the reaction node. In k*A, A+B --> C, there would be red and black arrows from A to the reaction node.
• Requires the Graphviz jll to be installed, or Graphviz to be installed and commandline accessible.

complexgraph(rn::ReactionSystem; complexdata=reactioncomplexes(rn))

Creates a Graphviz graph of the ReactionComplexs in rn. Reactions correspond to arrows and reaction complexes to blue circles.

Notes:

• Black arrows from complexes to complexes indicate reactions whose rate is a parameter or a Number. i.e. k, A --> B.
• Red dashed arrows from complexes to complexes indicate reactions whose rate depends on species. i.e. k*C, A --> B for C a species.
• Requires the Graphviz jll to be installed, or Graphviz to be installed and commandline accessible.

savegraph(g::Graph, fname, fmt="png")

Given a Graph generated by Graph, save the graph to the file with name fname and extension fmt.

Notes:

• fmt="png" is the default output format.
• Requires the Graphviz jll to be installed, or Graphviz to be installed and commandline accessible.

oderatelaw(rx; combinatoric_ratelaw=true)

Given a Reaction, return the symbolic reaction rate law used in generated ODEs for the reaction. Note, for a reaction defined by

k*X*Y, X+Z --> 2X + Y

the expression that is returned will be k*X(t)^2*Y(t)*Z(t). For a reaction of the form

k, 2X+3Y --> Z

the expression that is returned will be k * (X(t)^2/2) * (Y(t)^3/6).

Notes:

• Allocates
• combinatoric_ratelaw=true uses factorial scaling factors in calculating the rate law, i.e. for 2S -> 0 at rate k the ratelaw would be k*S^2/2!. If combinatoric_ratelaw=false then the ratelaw is k*S^2, i.e. the scaling factor is ignored.

jumpratelaw(rx; rxvars=get_variables(rx.rate), combinatoric_ratelaw=true)

Given a Reaction, return the symbolic reaction rate law used in generated stochastic chemical kinetics model SSAs for the reaction. Note, for a reaction defined by

k*X*Y, X+Z --> 2X + Y

the expression that is returned will be k*X^2*Y*Z. For a reaction of the form

k, 2X+3Y --> Z

the expression that is returned will be k * binomial(X,2) * binomial(Y,3).

Notes:

• rxvars should give the Variables, i.e. species and parameters, the rate depends on.
• Allocates
• combinatoric_ratelaw=true uses binomials in calculating the rate law, i.e. for 2S -> 0 at rate k the ratelaw would be k*S*(S-1)/2. If combinatoric_ratelaw=false then the ratelaw is k*S*(S-1), i.e. the rate law is not normalized by the scaling factor.

mm(X,v,K) = v*X / (X + K)

A Michaelis-Menten rate function.

mmr(X,v,K) = v*K / (X + K)

A repressive Michaelis-Menten rate function.

hill(X,v,K,n) = v*(X^n) / (X^n + K^n)

A Hill rate function.

hillr(X,v,K,n) = v*(K^n) / (X^n + K^n)

A repressive Hill rate function.

hillar(X,Y,v,K,n) = v*(X^n) / (X^n + Y^n + K^n)

An activation/repressing Hill rate function.

Base.convert(::Type{<:ODESystem},rs::ReactionSystem)

Convert a ReactionSystem to an ModelingToolkit.ODESystem.

Notes:

• combinatoric_ratelaws=true uses factorial scaling factors in calculating the rate

law, i.e. for 2S -> 0 at rate k the ratelaw would be k*S^2/2!. If combinatoric_ratelaws=false then the ratelaw is k*S^2, i.e. the scaling factor is ignored.

Base.convert(::Type{<:NonlinearSystem},rs::ReactionSystem)

Convert a ReactionSystem to an ModelingToolkit.NonlinearSystem.

Notes:

• combinatoric_ratelaws=true uses factorial scaling factors in calculating the rate

law, i.e. for 2S -> 0 at rate k the ratelaw would be k*S^2/2!. If combinatoric_ratelaws=false then the ratelaw is k*S^2, i.e. the scaling factor is ignored.

Base.convert(::Type{<:SDESystem},rs::ReactionSystem)

Convert a ReactionSystem to an ModelingToolkit.SDESystem.

Notes:

• combinatoric_ratelaws=true uses factorial scaling factors in calculating the rate

law, i.e. for 2S -> 0 at rate k the ratelaw would be k*S^2/2!. If combinatoric_ratelaws=false then the ratelaw is k*S^2, i.e. the scaling factor is ignored.

• noise_scaling=nothing::Union{Vector{Num},Num,Nothing} allows for linear

scaling of the noise in the chemical Langevin equations. If nothing is given, the default value as in Gillespie 2000 is used. Alternatively, a Num can be given, this is added as a parameter to the system (at the end of the parameter array). All noise terms are linearly scaled with this value. The parameter may be one already declared in the ReactionSystem. Finally, a Vector{Num} can be provided (the length must be equal to the number of reactions). Here the noise for each reaction is scaled by the corresponding parameter in the input vector. This input may contain repeat parameters.

Base.convert(::Type{<:JumpSystem},rs::ReactionSystem; combinatoric_ratelaws=true)

Convert a ReactionSystem to an ModelingToolkit.JumpSystem.

Notes:

• combinatoric_ratelaws=true uses binomials in calculating the rate law, i.e. for 2S -> 0 at rate k the ratelaw would be k*S*(S-1)/2. If combinatoric_ratelaws=false then the ratelaw is k*S*(S-1), i.e. the rate law is not normalized by the scaling factor.

structural_simplify(sys; simplify)

Structurally simplify algebraic equations in a system and compute the topological sort of the observed equations. When simplify=true, the simplify function will be applied during the tearing process.

validate(rx::Reaction; info::String = "")

Check that all substrates and products within the given Reaction have the same units, and that the units of the reaction's rate expression are internally consistent (i.e. if the rate involves sums, each term in the sum has the same units).

validate(rs::ReactionSystem, info::String="")

Check that all species in the ReactionSystem have the same units, and that the rate laws of all reactions reduce to units of (species units) / (time units).

Notes:

• Does not check subsystems too.