update docs site

src/docs_src/Adding_Selection_Method.md

@@ -3,18 +3,17 @@
 1. Define a selection method function in `propeller.selection` that selects an individual from the population
 2. Add the selection method in `propeller.selection/select-parent` under the `case` call:
 
-```clojure
+   ```clojure
-(defn select-parent
+    (defn select-parent
-  "Selects a parent from the population using the specified method."
+    "Selects a parent from the population using the specified method."
-  [pop argmap]
+    [pop argmap]
-  (case (:parent-selection argmap)
+    (case (:parent-selection argmap)
     :new-selection-method (new-selection-method )))
-```
+    ```
-
 3. When runnning a problem, specify the selection method in `:parent-selection`. 
 For example:
-```
+    ```
-lein run -m propeller.problems.simple-regression :parent-selection :new-selection-method"
+    lein run -m propeller.problems.simple-regression :parent-selection :new-selection-method"
-```
+    ```
 
 

src/propeller/core.cljc

@@ -1,4 +1,4 @@
-(ns propeller.core
+(ns ^:no-doc propeller.core
   #?(:clj (:gen-class)))
 
 (defn -main

src/propeller/genome.cljc

@@ -13,7 +13,12 @@ They hold the genetic material for an `individual`. In the initial population, w
     #(utils/random-instruction instructions)))
 
 (defn plushy->push
-  "Returns the Push program expressed by the given plushy representation."
+  "Returns the Push program expressed by the given plushy representation.
+
+  The function takes in a plushy representation as input and converts it into a Push program by iteratively processing
+  the plushy elements and adding instructions to the push program.
+  It also handles the case where there are open instructions that need to be closed before the end of the program.
+  "
   ([plushy] (plushy->push plushy {}))
   ([plushy argmap]
    (let [plushy (if (:diploid argmap) (map first (partition 2 plushy)) plushy)

src/propeller/gp.cljc

@@ -15,7 +15,7 @@
             [propeller.selection :as selection]))
 
 (defn report
-  "Reports information each generation."
+  "Reports information for each generation."
   [pop generation argmap]
   (let [best (first pop)]
     (clojure.pprint/pprint {:generation            generation
@@ -31,7 +31,25 @@
     (println)))
 
 (defn gp
-  "Main GP loop."
+  "Main GP loop.
+
+On each iteration, it creates a population of random plushies using a mapper
+function and genome/make-random-plushy function,
+then it sorts the population by the total error using the error-function
+and sort-by function. It then takes the best individual from the sorted population,
+and if the parent selection is set to epsilon-lexicase, it adds the epsilons to the argmap.
+
+The function then checks if the custom-report argument is set,
+if so it calls that function passing the evaluated population,
+current generation and argmap. If not, it calls the report function
+passing the evaluated population, current generation and argmap.
+
+Then, it checks if the total error of the best individual is less than or equal
+to the solution-error-threshold or if the current generation is greater than or
+equal to the max-generations specified. If either is true, the function
+exits with the best individual or nil. If not, it creates new individuals
+for the next generation using the variation/new-individual function and the
+repeatedly function, and then continues to the next iteration of the loop. "
   [{:keys [population-size max-generations error-function instructions
            max-initial-plushy-size solution-error-threshold mapper]
     :or   {solution-error-threshold 0.0
@@ -79,26 +97,3 @@
                        (repeatedly population-size
                                    #(variation/new-individual evaluated-pop argmap))))))))
 
-; This code is defining a function called "gp" (short for genetic programming) that takes in a map of parameters as its argument.
-; The map contains keys such as "population-size", "max-generations", "error-function", "instructions", "max-initial-plushy-size",
-; "solution-error-threshold", and "mapper", with default values specified for some of them.
-;
-;The function starts by printing some information about the starting arguments using
-; the prn function and then uses a loop to iterate over generations.
-; On each iteration, it creates a population of random plushies using a mapper
-; function and genome/make-random-plushy function,
-; then it sorts the population by the total error using the error-function
-; and sort-by function. It then takes the best individual from the sorted population,
-; and if the parent selection is set to epsilon-lexicase, it adds the epsilons to the argmap.
-;
-;The function then checks if the custom-report argument is set,
-; if so it calls that function passing the evaluated population,
-; current generation and argmap. If not, it calls the report function
-; passing the evaluated population, current generation and argmap.
-;
-;Then, it checks if the total error of the best individual is less than or equal
-; to the solution-error-threshold or if the current generation is greater than or
-; equal to the max-generations specified. If either is true, the function
-; exits with the best individual or nil. If not, it creates new individuals
-; for the next generation using the variation/new-individual function and the
-; repeatedly function, and then continues to the next iteration of the loop.

src/propeller/main.cljs

@@ -1,4 +1,4 @@
-(ns propeller.main
+(ns ^:no-doc propeller.main
   (:require [propeller.core :as propeller]))
 
 (defn main! []

src/propeller/session.cljc

@@ -5,7 +5,7 @@
 ; The commented-out stuff is a reminder of how to do some basic things.
 
 
-(ns propeller.session
+(ns ^:no-doc propeller.session
   "The \"session\" namespace is for trying things out interactively.
   For example, you can use it to test a new Push instruction by running a program that uses it and seeing the result.
   You might just want to do this interactively in the REPL, but the session file makes it a little easier since it already