`DiffEqBiological.add_hc_template!`

— Method```
add_hc_template(reaction_network)
Adds another hc template to the network. Having more HC templates might increase run time a little bit, but might give some additional certainity that all solutions are found (this should generally not be a problem anyway)
```

**args**

- reaction_network: a reaction network.

`DiffEqBiological.add_scale_noise_param!`

— Method`add_scale_noise_param!(network, scale_noise_name::String)`

Given an AbstractReaction network, add the parameter with the passed in string as its name to the network (if it is not already defined), and register it as the noise scaling coefficient.

`DiffEqBiological.add_scale_noise_param!`

— Method`add_scale_noise_param!(network, scale_noise::Symbol)`

Given an AbstractReaction network, add the parameter corresponding to the passed in symbol to the network (if it is not already defined), and register it as the noise scaling coefficient.

`DiffEqBiological.addjumps!`

— Method`addjumps!(network; build_jumps=true, build_regular_jumps=true, minimal_jumps=false)`

Extend an `AbstractReactionNetwork`

generated with the `@min_reaction_network`

or `@empty_reaction_network`

macros with everything needed to use jump SSA solvers.

Optional kwargs can be used to disable the construction of additional jump solver components.

Keyword arguments:

`build_jumps`

: if true jump rates and affects will be calculated for use in DiffEqJump SSAs.`build_regular_jumps`

: if true a`RegularJump`

representation of the stochastic chemical kinetics model will be calculated for use in τ-leaping methods.`minimal_jumps`

: if true`ConstantRate`

jumps are only constructed for non-mass action jumps. (Note, mass action jumps are still resolved within any jump simulation. This option simply speeds up the construction of the jump problem since it avoids building redundant`ConstantRate`

jumps that encode`MassActionJump`

s, which are subsequently ignored within jump simulations.)

`DiffEqBiological.addodes!`

— Method`addodes!(network; build_jac=true, build_symfuncs=true)`

Extend an `AbstractReactionNetwork`

generated with the `@min_reaction_network`

or `@empty_reaction_network`

macros with everything needed to use ODE solvers.

Optional kwargs can be used to disable the construction of additional ODE solver components.

`DiffEqBiological.addparam!`

— Method`addparam!(network, paramname::String)`

Given an AbstractReaction network, add the parameter with name given by the passed in string to the network (if it is not already defined).

`DiffEqBiological.addparam!`

— Method`addparam!(network, param::Symbol)`

Given an AbstractReaction network, add the parameter corresponding to the passed in symbol to the network (if it is not already defined).

`DiffEqBiological.addreaction!`

— Method`addreaction!(network, rateex::Union{Expr,Symbol,Int,Float64}, rxexpr::Expr)`

Given an AbstractReaction network, add a reaction with the passed in rate and reaction expressions. i.e. a reaction of the form

`k*X, 2X + Y --> 2W`

would have `rateex=:(k*X)`

and `rxexpr=:(2X + Y --> W)`

,

`10.5, 0 --> X`

would have `rateex=10.5`

and `rxexpr=:(0 --> X)`

, and

`k, X+X --> Z`

would have `rateex=:k`

and `rxexpr=:(X+X --> Z)`

. All normal DSL reaction definition notation should be supported.

`DiffEqBiological.addreaction!`

— Method`addreaction!(network, rateex::Union{Expr,Symbol,Int,Float64}, substrates, products)`

Given an AbstractReaction network, add a reaction with the passed in rate, `rateex`

, substrate stoichiometry, and product stoichiometry. Stoichiometries are represented as tuples of `Pair{Symbol,Int}`

. i.e. a reaction of the form

`k*X, 2X + Y --> 2W`

would have `rateex=:(k*X)`

, `substrates=(:X=>2, :Y=>2)`

`and`

products=(W=>2,)`,

`10.5, 0 --> X`

would have `rateex=10.5`

, `substrates=()`

and `products=(:X=>1,)`

, and

`k, X+X --> Z`

would have `rateex=:k`

, `substrates=(:X=>2,)`

and `products=(:Z=>2,)`

. All normal DSL reaction definition notation should be supported for the `rateex`

.

`DiffEqBiological.addsdes!`

— Method`addsdes!(network; build_jac=true, build_symfuncs=true)`

Extend an `AbstractReactionNetwork`

generated with the `@min_reaction_network`

or `@empty_reaction_network`

macros with everything needed to use SDE solvers.

Optional kwargs can be used to disable the construction of additional SDE solver components.

`DiffEqBiological.addspecies!`

— Method`addspecies!(network, speciesname::String)`

Given an AbstractReaction network, add the species with name given by the passed in string to the network (if it is not already defined.

`DiffEqBiological.addspecies!`

— Method`addspecies!(network, speciessym::Symbol)`

Given an AbstractReaction network, add the species corresponding to the passed in symbol to the network (if it is not already defined).

`DiffEqBiological.bifurcation_grid`

— Method```
bifurcation_grid(reaction_network, [solver], parameter_values, parameter_symbol, parameter_range; kwargs...)
Solves the steady states of a system for every parameter values in a given range of values. Returns a bifurcation grid type object (which can be plotted).
```

**args**

- reaction_network: a reaction network.
- solver (optional): a subtype of AbstractSteadyStateSolver that specifies how to solve the bifurcation diagram. Default is HCSteadyStateSolver (currently only solver avaiable).
- parameter_values: a vector which specifies the parameter values for which the steady states are to be found. Not required in case the reaction network lacks steady states.
- parameter_symbol: the parameter which is to be varried.
- parameter_range: a range with all the values of the parameter for which steady states are to be solved.

**kwargs**

- potential arguments for steady state solvers (however, only current solver does not have any such arguments).

`DiffEqBiological.bifurcation_grid_2d`

— Method```
bifurcation_grid_2d(reaction_network, [solver], parameter_values, parameter_symbol1, parameter_range1, parameter_symbol2, parameter_range2; kwargs...)
Ad bifurcation grid, but varries two different parameters. Returning a 2d grid with steady states in each grid point.
```

**args**

- reaction_network: a reaction network.
- solver (optional): a subtype of AbstractSteadyStateSolver that specifies how to solve the bifurcation diagram. Default is HCSteadyStateSolver (currently only solver avaiable).
- parameter_values: a vector which specifies the parameter values for which the steady states are to be found. Not required in case the reaction network lacks steady states.
- parameter_symbo1l: the first parameter which is to be varried.
- parameter_range1: a range with all the values of the first parameter for which steady states are to be solved.
- parameter_symbol2: the second parameter which is to be varried.
- parameter_range2: a range with all the values of the second parameter for which steady states are to be solved.

**kwargs**

- potential arguments for steady state solvers (however, only current solver does not have any such arguments).

`DiffEqBiological.bifurcation_grid_diagram`

— Method```
bifurcation_grid_diagram(reaction_network, [solver], parameter_values, parameter_symbol1, parameter_range1, parameter_symbol2, parameter_range2; kwargs...)
Varries a first parameter over a range of discrete values, for each values makes a bifurcation diagram over a second, continious range. Allows to vsiualise changes ins steady states over two parameters.
```

**args**

- reaction_network: a reaction network.
- solver (optional): a subtype of AbstractBifurcationSolver that specifies how to solve the bifurcation diagram. Default is HCBifurcationSolver.
- parameter_values: a vector which specifies the point in parameter space around which the bifurcation diagram is evaluated.
- parameter_symbol1: the first parameter which is varied, given as a symbol.
- parameter_range1: the range over which the first parameter is varied (this is a range of discrete numbers).
- parameter_symbol2: the second parameter which is varied, given as a symbol.
- parameter_rang21: the range over which the second parameter is varied (this is a tuple of two numbers).

**kwargs**

- stepsize = (parameter
*range[2] - parameter*range[1])/200: The maximum distance between two parameter values for which steady states are calculated. Smaller values will give a smoother diagram. - Δp = (parameter
*range[2] - parameter*range[1])/200: The distance to jump after finding a bifurcation. After discovering a bifurcation, the solver jumps ahead a distance`Δp`

and starts back-tracking. If this distance is too small, the method may error or cause visible artifiacts in the bifurcation diagram. If it is too large, then you might jump over another bifurcation and it will be missed (this should also be farily obvious in a plot). Only applicable for the HCBifurcationSolver. - Δu = 1e-7: (alternatively reduced to a tenth of the minimum value of any initial solutions) used by algorithm to determine if two points are identical. Set this to less than the expected minimum distance between two different solutions.

`DiffEqBiological.bifurcations`

— Method`bifurcations(reaction_network, [solver], parameter_values, parameter_symbol, parameter_range; kwargs...)`

Get a bifurcation diagram of the specified system.

**args**

- reaction_network: a reaction network.
- solver (optional): a subtype of AbstractBifurcationSolver that specifies how to solve the bifurcation diagram. Default is HCBifurcationSolver.
- parameter_values: a vector which specifies the point in parameter space around which the bifurcation diagram is evaluated.
- parameter_symbol: the parameter which is varied, given as a symbol.
- parameter_range: the range over which the specified parameter is varied.

**kwargs**

- stepsize = (parameter
*range[2] - parameter*range[1])/200: The maximum distance between two parameter values for which steady states are calculated. Smaller values will give a smoother diagram. - Δp = (parameter
*range[2] - parameter*range[1])/200: The distance to jump after finding a bifurcation. After discovering a bifurcation, the solver jumps ahead a distance`Δp`

and starts back-tracking. If this distance is too small, the method may error or cause visible artifiacts in the bifurcation diagram. If it is too large, then you might jump over another bifurcation and it will be missed (this should also be farily obvious in a plot). Only applicable for the HCBifurcationSolver. - Δu = 1e-7: (alternatively reduced to a tenth of the minimum value of any initial solutions) used by algorithm to determine if two points are identical. Set this to less than the expected minimum distance between two different solutions.

`DiffEqBiological.dependants`

— Method`dependants(network, rxidx)`

See documentation for `dependents(network, rxidx)`

.

`DiffEqBiological.dependents`

— Method`dependents(network, rxidx)`

Given an `AbstractReactionNetwork`

and a reaction index, `rxidx`

, return a vector of symbols of species the *reaction rate law* depends on. i.e. for

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

the returned vector would be `[:W,:X,:Y]`

.

Non-allocating, returns underlying field within the reaction_network.

`DiffEqBiological.fix_parameters`

— Function`fix_parameters(reaction_network, [parameter_values]; t=get_polyvars(rn).t, kwargs...)`

Fixes certain parameters of a reaction network, preparing it for homotopy continuation.

In the polynomial needed to be solved by homotopy continuation to find steady states solutions, both varriables and parameters are initially represented as polynomial varriables. If a parameter exists in an exponent (e.g. X^n), that parameter might be needed to be fixed to a desired value before solving. Fixing is not required, but if you solve a polynomial several times, it might increase performance.

**args**

- reaction_network: a reaction network.
- parameter_values: An entire vector can be given, fixing all parameters. Generaly you do not want to do this.
- t=get_polyvars(rn).t: If you want to fix the time value.

**kwargs**

- How parameters generally are fixed. Write e.g. n=4 to fix the parameter value of n.

`DiffEqBiological.ismassaction`

— Method`ismassaction(network, rxidx)`

Given an `AbstractReactionNetwork`

and a reaction index, `rxidx`

, return a boolean indicating whether the given reaction is of mass action form. For example, the reaction

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

would return true, while reactions with state-dependent rates like

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

would return false.

Non-allocating, returns underlying field within the reaction_network.

`DiffEqBiological.jacfun`

— Method`jacfun(network)`

Given an `AbstractReactionNetwork`

, return a function, `jac!(J,u,p,t)`

, that evaluates the current Jacobian matrix, `J`

, of the ODE model, $du/dt = f(u,t)$. The Jacobian matrix has entries

$J_{i,j} = \partial f_i(u,t) / \partial u_j$.

*Note,* for a network generated with the `@min_reaction_network`

macro `addodes!`

must be called first.

`DiffEqBiological.jacobianexprs`

— Method`jacobianexprs(network)`

Given an `AbstractReactionNetwork`

, return a matrix with the ODE Jacobian expressions.

*Note,* for a network generated with the `@min_reaction_network`

macro `addodes!`

must be called first.

`DiffEqBiological.jumpexprs`

— Method`jumpexprs(network)`

Given an `AbstractReactionNetwork`

, return a tuple of the jump rates and affects expressions.

*Note,* for a network generated with the `@min_reaction_network`

macro `addjumps!`

must be called first.

`DiffEqBiological.jumps`

— Method`jumps(network)`

Given an `AbstractReactionNetwork`

, return a tuple of `AbstractJumps`

encoding a stochastical chemical kinetics representation for the reaction network.

*Note,* for a network generated with the `@min_reaction_network`

macro `addjumps!`

must be called first.

`DiffEqBiological.make_hc_template!`

— Method```
make_hc_template(reaction_network)
Makes a template for solving for the given reaction networks steady states using homotopy continuation. Generally not needed as this is genrated automatically when netowkr is first solved *if one does not already exists). However, it can be sued to replace the current template, for whatever reason.
```

**args**

- reaction_network: a reaction network.

`DiffEqBiological.netstoich`

— Method`netstoich(network, rxidx)`

Given an `AbstractReactionNetwork`

and a reaction index, `rxidx`

, return a vector of pairs, mapping ids of species that change numbers due to the reaction to the net stoichiometric coefficient of the species (i.e. net change in the species due to the reaction).

Allocates a new vector to store the pairs.

`DiffEqBiological.noiseexprs`

— Method`noiseexprs(network)`

Given an `AbstractReactionNetwork`

, return a vector of the SDE noise expressions for each reaction.

*Note,* for a network generated with the `@min_reaction_network`

macro `addsdes!`

must be called first.

`DiffEqBiological.noisefun`

— Method`noisefun(network)`

Given an `AbstractReactionNetwork`

, return a function, `g(η,u,p,t)`

, that evaluates the current noise coefficients for each reaction in the Chemical Langevin Equation representation within `η`

.

*Note,* for a network generated with the `@min_reaction_network`

macro `addsdes!`

must be called first.

`DiffEqBiological.numparams`

— Method`numparams(network)`

Return the number of parameters within the given `AbstractReactionNetwork`

.

`DiffEqBiological.numreactions`

— Method`numreactions(network)`

Return the number of reactions within the given `AbstractReactionNetwork`

.

`DiffEqBiological.numspecies`

— Method`numspecies(network)`

Return the number of species within the given `AbstractReactionNetwork`

.

`DiffEqBiological.odeexprs`

— Method`odeexprs(network)`

Given an `AbstractReactionNetwork`

, return a vector of the ODE expressions.

*Note,* for a network generated with the `@min_reaction_network`

macro `addodes!`

must be called first.

`DiffEqBiological.odefun`

— Method`odefun(network)`

Given an `AbstractReactionNetwork`

, return a `DiffEqBase.ODEFunction`

encoding an ODE model for the reaction network.

*Note,* for a network generated with the `@min_reaction_network`

macro `addodes!`

must be called first.

`DiffEqBiological.oderatelawexpr`

— Method`oderatelawexpr(network, rxidx)`

Given an `AbstractReactionNetwork`

, return the reaction rate law expression used in generated ODEs for the reaction with index `rxidx`

. 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 * (X^2/2) * (Y^3/6))`

.

`DiffEqBiological.oderhsfun`

— Method`oderhsfun(network)`

Given an `AbstractReactionNetwork`

, return a function, `f!(du,u,p,t)`

, that evaluates the current value of the ODE model derivative functions, $du/dt = f(u,t)$, within `du`

.

*Note,* for a network generated with the `@min_reaction_network`

macro `addodes!`

must be called first.

`DiffEqBiological.paramjacfun`

— Method`paramjacfun(network)`

Given an `AbstractReactionNetwork`

, return a function, `pjac(pJ,u,p,t)`

, that evaluates the current parameter Jacobian matrix, `pJ`

, of the ODE model, $du/dt = f(u,t)$. The parameter Jacobian matrix has entries

$pJ_{i,j} = \partial f_i(u,t) / \partial p_j$.

*Note,* for a network generated with the `@min_reaction_network`

macro `addodes!`

must be called first.

`DiffEqBiological.params`

— Method`params(network)`

Given an `AbstractReactionNetwork`

, return a vector of parameter symbols.

`DiffEqBiological.paramsmap`

— Method`paramsmap(network)`

Given an `AbstractReactionNetwork`

, return a Dictionary mapping from parameter symbol to parameter index.

`DiffEqBiological.products`

— Method`products(network, rxidx)`

Given an `AbstractReactionNetwork`

and a reaction index, `rxidx`

, return a vector of symbols of species that correspond to products in the reaction. i.e. for

`k*W, X + 3Y --> X + W`

the returned vector would be `[:X,:W]`

.

Allocates a new vector to store the symbols.

`DiffEqBiological.productstoich`

— Method`productstoich(network, rxidx)`

Given an `AbstractReactionNetwork`

and a reaction index, `rxidx`

, return a vector of pairs, mapping ids of species that are products in the reaction to the corresponding stoichiometric coefficient as a product.

Allocates a new vector to store the pairs.

`DiffEqBiological.productsymstoich`

— Method`productsymstoich(network, rxidx)`

Given an `AbstractReactionNetwork`

and a reaction index, `rxidx`

, return a Vector of `ReactantStruct`

s, mapping the symbols of species that are products in the reaction to the corresponding stoichiometric coefficient as a product.

Non-allocating, returns underlying field within the reaction_network.

`DiffEqBiological.rateexpr`

— Method`rateexpr(network, rxidx)`

Given an `AbstractReactionNetwork`

, return the reaction rate expression for the reaction with index `rxidx`

. Note, for a reaction defined by

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

the expression that is returned will be `:(k*X*Y)`

, while the *rate law* used in ODEs and SDEs would be `k*X^2*Y*Z`

.

`DiffEqBiological.regularjumps`

— Method`regularjumps(network)`

Given an `AbstractReactionNetwork`

, return a `RegularJump`

encoding a stochastical chemical kinetics representation of the reaction network for use in $\tau$-leaping approximations.

*Note,* for a network generated with the `@min_reaction_network`

macro `addjumps!`

must be called first.

`DiffEqBiological.rxtorx_depgraph`

— Function`rxtorx_depgraph(network)`

Given an `AbstractReactionNetwork`

, returns a `Vector{Vector{Int}}`

mapping each reaction index to the indices of reactions that depend on it.

`DiffEqBiological.rxtospecies_depgraph`

— Method`rxtospecies_depgraph(network)`

Given an `AbstractReactionNetwork`

, returns a `Vector{Vector{Int}}`

mapping each reaction index to the indices of species that depend on it.

`DiffEqBiological.sdefun`

— Method`sdefun(network)`

Given an `AbstractReactionNetwork`

, return a `DiffEqBase.SDEFunction`

encoding a Chemical Langevin Equation SDE model for the reaction network.

*Note,* for a network generated with the `@min_reaction_network`

macro `addsdes!`

must be called first.

`DiffEqBiological.species`

— Method`species(network)`

Given an `AbstractReactionNetwork`

, return a vector of species symbols.

`DiffEqBiological.speciesmap`

— Method`speciesmap(network)`

Given an `AbstractReactionNetwork`

, return a Dictionary mapping from species symbol to species index.

`DiffEqBiological.speciestorx_depgraph`

— Method`speciestorx_depgraph(network)`

Given an `AbstractReactionNetwork`

, returns a `Vector{Vector{Int}}`

mapping each species index to the indices of reactions that depend on it.

`DiffEqBiological.ssaratelawexpr`

— Method`ssaratelawexpr(network, rxidx)`

Given an `AbstractReactionNetwork`

, return the reaction rate law expression used in generated stochastic chemical kinetic model SSAs for the reaction with index `rxidx`

. 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))`

.

`DiffEqBiological.stability`

— Function```
stability(solution,reaction_network, parameter_values, t=0.)
Gives the steady stability of the steady state of a certain network. Returns true if the point is stable, false if it is not.
```

**args**

- solution: the values of the reactants in the steady state.
- parameter_values: the parameter values in for which the steady state was calculated.
- reaction_network: a reaction network.
- t (optional): the value of t, for which the stability is calculated.

`DiffEqBiological.stability`

— Function```
stability(solutions,reaction_network, parameter_values, t=0.)
Gives the steady stability of the steady state of a certain network.
```

**args**

- solutions: An array of steady states (which each in turn, is an array of reactant concentrations in the steady state).
- parameter_values: the parameter values in for which the steady state was calculated.
- reaction_network: a reaction network.
- t (optional): the value of t, for which the stability is calculated.

`DiffEqBiological.steady_states`

— Method`steady_states(reaction_network, [solver], [parameter_values]; kwargs...)`

Finds the steady states of a given reaction network, at given parameter values.

**args**

- reaction_network: a reaction network.
- solver (optional): a subtype of AbstractSteadyStateSolver that specifies how to solve the bifurcation diagram. Default is HCSteadyStateSolver (currently only solver avaiable).
- parameter_values: a vector which specifies the parameter values for which the steady states are to be found. Not required in case the reaction network lacks steady states.

**kwargs**

- potential arguments for steady state solvers (however, only current solver does not have any such arguments).

`DiffEqBiological.substrates`

— Method`substrates(network, rxidx)`

Given an `AbstractReactionNetwork`

and a reaction index, `rxidx`

, return a vector of symbols of species that correspond to substrates in the reaction. i.e. for

`k*W, X + 3Y --> X + W`

the returned vector would be `[:X,:Y]`

.

Allocates a new vector to store the symbols.

`DiffEqBiological.substratestoich`

— Method`substratestoich(network, rxidx)`

Given an `AbstractReactionNetwork`

and a reaction index, `rxidx`

, return a vector of pairs, mapping ids of species that serve as substrates in the reaction to the corresponding stoichiometric coefficient as a substrate.

Allocates a new vector to store the pairs.

`DiffEqBiological.substratesymstoich`

— Method`substratesymstoich(network, rxidx)`

Given an `AbstractReactionNetwork`

and a reaction index, `rxidx`

, return a Vector of `ReactantStruct`

s, mapping the symbols of species that serve as substrates in the reaction to the corresponding stoichiometric coefficient as a substrate.

Non-allocating, returns underlying field within the reaction_network.

`DiffEqBiological.@add_constraint`

— Macro`@add_contraint(reaction_network, constraints)`

Some networks (like X ↔ Y) have an infinite number of potential steady states, depending on initial conditions. For these some additional contraint(s) is required. Typically in the form of fixed concentrations.

**args**

- reaction_network: a reaction network.
- constraints: Constraints, typically given as X + Y = C. Both parameters, varriables, and numbers can be given. However, parameters much be declared previously in the reaction network.

`DiffEqBiological.@add_constraints`

— Macro`@add_contraints(reaction_network, constraints)`

Same as @add*constraint, but a more natural way of adding several contraints such as: @add*contraints rn begin X1 + Y1 = C1 X2 + Y2 = C2 end

**args**

- reaction_network: a reaction network.
- constraints: Constraints, typically given as X + Y = C. Both parameters, varriables, and numbers can be given. However, parameters much be declared previously in the reaction network.

`DiffEqBiological.@add_hc_template`

— Macro```
@make_hc_template(reaction_network)
Calls the "add_hc_template function on the given reaction network."
```

**args**

- reaction_network: a reaction network.

`DiffEqBiological.@empty_reaction_network`

— Macro`@empty_reaction_network networktype`

Generates a subtype of an `AbstractReactionNetwork`

that encodes an empty chemical reaction network. `networktype`

is an optional parameter that specifies the type of the generated network. Use `addspecies!`

, `addparam!`

and `addreaction!`

to extend the network. Use `addodes!`

, `addsdes!`

or `addjumps!`

to complete the network for specific problem types.

`DiffEqBiological.@make_hc_template`

— Macro```
@make_hc_template(reaction_network)
Calls the "make_hc_template function on the given reaction network."
```

**args**

- reaction_network: a reaction network.

`DiffEqBiological.@min_reaction_network`

— Macro`@min_reaction_network`

Generates a subtype of an `AbstractReactionNetwork`

that only encodes a chemical reaction network. Use `addodes!`

, `addsdes!`

or `addjumps!`

to complete the network for specific problem types. It accepts the same arguments as `@reaction_network`

.

`DiffEqBiological.@reaction_network`

— Macro`@reaction_network`

Generates a subtype of an `AbstractReactionNetwork`

that encodes a chemical reaction network, and complete ODE, SDE and jump representations of the system. See the Chemical Reaction Model docs for details on parameters to the macro.

`Base.:==`

— Method`==(rn1::DiffEqBase.AbstractReactionNetwork, rn2::DiffEqBase.AbstractReactionNetwork)`

Tests whether the underlying species symbols, parameter symbols and reactions are the same in the two networks. Ignores order network components were defined, so the integer id of any individual species/parameters/reactions may be different between the two networks. *Does not* currently account for different reaction definitions, so "k, X+Y –> Y + Z" will not be the same as "k, Y+X –> Y + Z"

`DiffEqBiological.clean_subtractions`

— Methodclean_subtractions(ex::Expr) Replace additions of negative terms with subtractions. This is a fairly stupid function which is designed for a specific problem with reaction networks. It is neither recursive nor very general. Return :: cleaned out expression

From Latexify.jl with permission: see

`DiffEqBiological.netsymstoich`

— Method`netsymstoich(network, rxidx)`

Given an `AbstractReactionNetwork`

and a reaction index, `rxidx`

, return a Vector of `ReactantStruct`

s, mapping the symbols of species that change numbers due to the reaction to the net stoichiometric coefficient of the species (i.e. net change in the species due to the reaction).

Non-allocating, returns underlying field within the reaction_network.