Improving Documentation

Author: s-baumann

src/1_MainFunctions.jl

@@ -106,7 +106,7 @@ A function for finding the fixed point of another function
  *  `quiet_errors` - If true the function will return everything already calculated as soon as an error occurs. The callstack that lead to the error is not returned however. If false an error will be thrown with a callstack.
  *  `other_outputs` - This allows you to pass in side products (as in Other_Output_ in a FixedPointResults struct). It is only used if the FixedPointResults that is input has already found a fixedpoint.
 ### Returns
- * A list containing the fixed_point, the Inputs and corresponding Outputs, and convergence values (which are computed under the "ConvergenceMetric").
+ * A `FixedPointResults` struct containing the fixed_point, the Inputs and corresponding Outputs, and convergence values (which are computed under the "ConvergenceMetric").
    The list will also include a "Finish" statement describing why it has finished. This is often going to be due to either MaxIter or ConvergenceMetricThreshold being
    reached. It may also terminate due to an error in generating a new input guess or using the function with that guess. If this occurs the function will terminate early
    and the "Finish" statement will describe the issue. In this event there will also be additional objects returned in the list "NewInputVector" and possibly
@@ -253,18 +253,18 @@ end
                                ConditionNumberThreshold::R = AbstractFloat(1000), PrintReports::Bool = false, ReplaceInvalids::InvalidReplacement = :NoAction) where R<:Real where S<:Real where T<:Real
 
 This function takes the previous inputs and outputs from the fixed_point function and determines what vector to try next in seeking a fixed point.
-### Takes
-*  Inputs - This is an N x A matrix of previous inputs for which corresponding outputs are available. In this case N is the dimensionality of the fixed point vector that is being sought (Hence each column is a matrix that is input to the "Function") and A is the number of previous Inputs/Outputs that are being provided to the fixed point.
-* Outputs - This is a matrix of Function values for the each column of the "Inputs" matrix.
-* Algorithm - This is the fixed point Algorithm to be used. It can be "Anderson", "Simple", "Aitken", "Newton", "MPE", "RRE", "VEA", "SEA".
-* MaxM - This is the number of saved iterates that are used in the Anderson algorithm. This has no role if another Algorithm is used.
-* SimpleStartIndex - This is the index for what column in the input/output matrices did the algorithm start doing simple iterates without jumps. This is used for all Algorithms except the simple and Anderson Algorithms where it has no effect.
-* ExtrapolationPeriod - This is the number of simple iterates to perform before extrapolating. This is used for the MPE, RRE, VEA and SEA Algorithms and has no effect if another Algorithm is chosen.
-* Dampening - This is the dampening parameter. By default it is 1 which means no dampening takes place. It can also be less than 1 (indicating dampening) or more than 1 (indicating extrapolation).
-* ConditionNumberThreshold - This is what threshold should be chosen to drop previous iterates if the matrix is ill conditioned. Only used in Anderson acceleration.
-* PrintReports - This is a boolean describing whether to print ongoing ConvergenceMetric values for each iterate.
+### Inputs
+* `Inputs` - This is an N x A matrix of previous inputs for which corresponding outputs are available. In this case N is the dimensionality of the fixed point vector that is being sought (Hence each column is a matrix that is input to the "Function") and A is the number of previous Inputs/Outputs that are being provided to the fixed point.
+* `Outputs` - This is a matrix of Function values for the each column of the `Inputs` matrix.
+* `Algorithm` - This is the fixed point Algorithm to be used. It can be "Anderson", "Simple", "Aitken", "Newton", "MPE", "RRE", "VEA", "SEA".
+* `MaxM` - This is the number of saved iterates that are used in the Anderson algorithm. This has no role if another Algorithm is used.
+* `SimpleStartIndex` - This is the index for what column in the input/output matrices did the algorithm start doing simple iterates without jumps. This is used for all Algorithms except the simple and Anderson Algorithms where it has no effect.
+* `ExtrapolationPeriod` - This is the number of simple iterates to perform before extrapolating. This is used for the MPE, RRE, VEA and SEA Algorithms and has no effect if another Algorithm is chosen.
+* `Dampening` - This is the dampening parameter. By default it is 1 which means no dampening takes place. It can also be less than 1 (indicating dampening) or more than 1 (indicating extrapolation).
+* `ConditionNumberThreshold` - This is what threshold should be chosen to drop previous iterates if the matrix is ill conditioned. Only used in Anderson acceleration.
+* `PrintReports` - This is a boolean describing whether to print ongoing ConvergenceMetric values for each iterate.
 ### Returns
- * A nicely formatted string version of the input number for printing to the console.
+ * A `Vector` of the next guess for the fixed point.
 ### Examples
     FPFunction = function(x){c(0.5*sqrt(abs(x[1] + x[2])), 1.5*x[1] + 0.5*x[2])}
     A = fixed_point( Function = FPFunction, Inputs = [0.3,900], MaxIter = 6, Algorithm = :Simple)