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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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66
src/propeller/gp.cljc
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@ -50,8 +50,8 @@
(defn gp-loop (defn gp-loop
"Main GP loop." "Main GP loop."
[{:keys [population-size max-generations error-function instructions [{:keys [population-size max-generations error-function instructions max-initial-plushy-size
max-initial-plushy-size solution-error-threshold ds-parent-rate ds-parent-gens dont-end ids-type downsample?] solution-error-threshold ds-parent-rate ds-parent-gens dont-end ids-type downsample?]
:or {solution-error-threshold 0.0 :or {solution-error-threshold 0.0
dont-end false dont-end false
ds-parent-rate 0 ds-parent-rate 0
@ -59,7 +59,7 @@
ids-type :solved ; :solved or :elite or :soft ids-type :solved ; :solved or :elite or :soft
downsample? false} downsample? false}
:as argmap}] :as argmap}]
;; ;; print starting args
(prn {:starting-args (update (update argmap :error-function str) (prn {:starting-args (update (update argmap :error-function str)
:instructions :instructions
(fn [instrs] (fn [instrs]
@ -72,13 +72,16 @@
(fn [_] {:plushy (genome/make-random-plushy instructions max-initial-plushy-size)}) (fn [_] {:plushy (genome/make-random-plushy instructions max-initial-plushy-size)})
(range population-size) (range population-size)
argmap) 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? (let [training-data (if downsample?
(case (:ds-function argmap) (case (:ds-function argmap)
:case-maxmin (downsample/select-downsample-maxmin indexed-training-data argmap) :case-maxmin (downsample/select-downsample-maxmin indexed-training-data argmap)
:case-maxmin-auto (downsample/select-downsample-maxmin-adaptive 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) :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 indexed-training-data) ;defaults to full training set
parent-reps (if parent-reps (if
(and downsample? ; if we are down-sampling (and downsample? ; if we are down-sampling
@ -106,46 +109,63 @@
(if (:custom-report argmap) (if (:custom-report argmap)
((:custom-report argmap) evaluations evaluated-pop generation argmap) ((:custom-report argmap) evaluations evaluated-pop generation argmap)
(report evaluations evaluated-pop generation argmap training-data)) (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 (when best-individual-passes-ds
(prn {:semi-success-generation generation})) (prn {:semi-success-generation generation}))
(cond (cond
;; If either the best individual on the ds passes all training cases, or best individual on full sample passes all training cases ;; If either the best individual on the ds passes all training cases, or best individual on full
;; We verify success on test cases and end evolution ;; 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)) (if (or (and best-individual-passes-ds
(<= (:total-error (error-function argmap indexed-training-data best-individual))
solution-error-threshold))
(and (not downsample?) (and (not downsample?)
(<= (:total-error best-individual) solution-error-threshold))) (<= (:total-error best-individual)
solution-error-threshold)))
(do (prn {:success-generation generation}) (do (prn {:success-generation generation})
(prn {:total-test-error (prn {:total-test-error
(:total-error (error-function argmap (:testing-data argmap) best-individual))}) (:total-error (error-function argmap (:testing-data argmap) best-individual))})
(when (:simplification? argmap) (when (:simplification? argmap)
(let [simplified-plushy (simplification/auto-simplify-plushy (:plushy best-individual) error-function 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)) (if dont-end false true))
false) false)
(cleanup) (cleanup)
;; ;; If we've evolved for as many generations as the parameters allow, exit without succeeding
(and (not downsample?) (>= generation max-generations)) (or (and (not downsample?)
(>= generation max-generations))
(and downsample?
(>= evaluations (* max-generations population-size (count indexed-training-data)))))
(cleanup) (cleanup)
;; ;; Otherwise, evolve for another generation
(and downsample? (>= evaluations (* max-generations population-size (count indexed-training-data))))
(cleanup)
;;
:else (recur (inc generation) :else (recur (inc generation)
(+ evaluations (* population-size (count training-data)) ;every member evaluated on the current sample (+ evaluations
(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 (* population-size (count training-data)) ;every member evaluated on the current sample
(if best-individual-passes-ds (- (count indexed-training-data) (count training-data)) 0)) ; if we checked for generalization or not (if (zero? (mod generation ds-parent-gens))
(if (:elitism argmap) (* (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)) (conj (utils/pmapallv (fn [_] (variation/new-individual evaluated-pop argmap))
(range (dec population-size)) (range (dec population-size))
argmap) argmap)
(first evaluated-pop)) ;elitism maintains the most-fit individual (first evaluated-pop))
(utils/pmapallv (fn [_] (variation/new-individual evaluated-pop argmap)) (utils/pmapallv (fn [_] (variation/new-individual evaluated-pop argmap))
(range population-size) (range population-size)
argmap)) argmap))
(if downsample? (if downsample?
(if (zero? (mod generation ds-parent-gens)) (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)
indexed-training-data)))))) indexed-training-data))))))