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Clean up and reformat

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This commit is contained in:
Lee Spector 2023-11-24 18:09:25 -05:00
parent 48658f455c
commit 91adcbf089
1 changed files with 53 additions and 33 deletions
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86
src/propeller/gp.cljc
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@ -50,8 +50,8 @@
(defn gp-loop
"Main GP loop."
[{:keys [population-size max-generations error-function instructions
max-initial-plushy-size solution-error-threshold ds-parent-rate ds-parent-gens dont-end ids-type downsample?]
[{:keys [population-size max-generations error-function instructions max-initial-plushy-size
solution-error-threshold ds-parent-rate ds-parent-gens dont-end ids-type downsample?]
:or {solution-error-threshold 0.0
dont-end false
ds-parent-rate 0
@ -59,9 +59,9 @@
ids-type :solved ; :solved or :elite or :soft
downsample? false}
:as argmap}]
;;
(prn {:starting-args (update (update argmap :error-function str)
:instructions
;; print starting args
(prn {:starting-args (update (update argmap :error-function str)
:instructions
(fn [instrs]
(utils/not-lazy (map #(if (fn? %) (str %) %) instrs))))})
(println)
@ -69,16 +69,19 @@
(loop [generation 0
evaluations 0
population (utils/pmapallv
(fn [_] {:plushy (genome/make-random-plushy instructions max-initial-plushy-size)})
(range population-size)
(fn [_] {:plushy (genome/make-random-plushy instructions max-initial-plushy-size)})
(range population-size)
argmap)
indexed-training-data (if downsample? (downsample/assign-indices-to-data (downsample/initialize-case-distances argmap) argmap) (:training-data argmap))]
indexed-training-data (if downsample?
(downsample/assign-indices-to-data (downsample/initialize-case-distances argmap) argmap)
(:training-data argmap))]
(let [training-data (if downsample?
(case (:ds-function argmap)
:case-maxmin (downsample/select-downsample-maxmin indexed-training-data argmap)
:case-maxmin-auto (downsample/select-downsample-maxmin-adaptive indexed-training-data argmap)
:case-rand (downsample/select-downsample-random indexed-training-data argmap)
(do (prn {:error "Invalid Downsample Function"}) (downsample/select-downsample-random indexed-training-data argmap)))
(do (prn {:error "Invalid Downsample Function"})
(downsample/select-downsample-random indexed-training-data argmap)))
indexed-training-data) ;defaults to full training set
parent-reps (if
(and downsample? ; if we are down-sampling
@ -106,46 +109,63 @@
(if (:custom-report argmap)
((:custom-report argmap) evaluations evaluated-pop generation argmap)
(report evaluations evaluated-pop generation argmap training-data))
;;did the indvidual pass all cases in ds?
;; Did the indvidual pass all cases in ds?
(when best-individual-passes-ds
(prn {:semi-success-generation generation}))
(cond
;; If either the best individual on the ds passes all training cases, or best individual on full sample passes all training cases
;; We verify success on test cases and end evolution
(if (or (and best-individual-passes-ds (<= (:total-error (error-function argmap indexed-training-data best-individual)) solution-error-threshold))
;; If either the best individual on the ds passes all training cases, or best individual on full
;; sample passes all training cases, we verify success on test cases and exit, succeeding
(if (or (and best-individual-passes-ds
(<= (:total-error (error-function argmap indexed-training-data best-individual))
solution-error-threshold))
(and (not downsample?)
(<= (:total-error best-individual) solution-error-threshold)))
(<= (:total-error best-individual)
solution-error-threshold)))
(do (prn {:success-generation generation})
(prn {:total-test-error
(:total-error (error-function argmap (:testing-data argmap) best-individual))})
(when (:simplification? argmap)
(let [simplified-plushy (simplification/auto-simplify-plushy (:plushy best-individual) error-function argmap)]
(prn {:total-test-error-simplified (:total-error (error-function argmap (:testing-data argmap) (hash-map :plushy simplified-plushy)))})))
(prn {:total-test-error-simplified
(:total-error (error-function argmap (:testing-data argmap) {:plushy simplified-plushy}))})))
(if dont-end false true))
false)
(cleanup)
;;
(and (not downsample?) (>= generation max-generations))
;; If we've evolved for as many generations as the parameters allow, exit without succeeding
(or (and (not downsample?)
(>= generation max-generations))
(and downsample?
(>= evaluations (* max-generations population-size (count indexed-training-data)))))
(cleanup)
;;
(and downsample? (>= evaluations (* max-generations population-size (count indexed-training-data))))
(cleanup)
;;
;; Otherwise, evolve for another generation
:else (recur (inc generation)
(+ evaluations (* population-size (count training-data)) ;every member evaluated on the current sample
(if (zero? (mod generation ds-parent-gens)) (* (count parent-reps) (- (count indexed-training-data) (count training-data))) 0) ; the parent-reps not evaluted already on down-sample
(if best-individual-passes-ds (- (count indexed-training-data) (count training-data)) 0)) ; if we checked for generalization or not
(if (:elitism argmap)
(conj (utils/pmapallv (fn [_] (variation/new-individual evaluated-pop argmap))
(range (dec population-size))
argmap)
(first evaluated-pop)) ;elitism maintains the most-fit individual
(utils/pmapallv (fn [_] (variation/new-individual evaluated-pop argmap))
(range population-size)
argmap))
(+ evaluations
(* population-size (count training-data)) ;every member evaluated on the current sample
(if (zero? (mod generation ds-parent-gens))
(* (count parent-reps)
(- (count indexed-training-data)
(count training-data)))
0) ; the parent-reps not evaluted already on down-sample
(if best-individual-passes-ds
(- (count indexed-training-data) (count training-data))
0)) ; if we checked for generalization or not
(if (:elitism argmap) ; elitism maintains the most-fit individual
(conj (utils/pmapallv (fn [_] (variation/new-individual evaluated-pop argmap))
(range (dec population-size))
argmap)
(first evaluated-pop))
(utils/pmapallv (fn [_] (variation/new-individual evaluated-pop argmap))
(range population-size)
argmap))
(if downsample?
(if (zero? (mod generation ds-parent-gens))
(downsample/update-case-distances rep-evaluated-pop indexed-training-data indexed-training-data ids-type (/ solution-error-threshold (count indexed-training-data))) ; update distances every ds-parent-gens generations
; update distances every ds-parent-gens generations
(downsample/update-case-distances rep-evaluated-pop
indexed-training-data
indexed-training-data
ids-type
(/ solution-error-threshold
(count indexed-training-data)))
indexed-training-data)
indexed-training-data))))))