diff options
Diffstat (limited to 'src/genome')
| -rw-r--r-- | src/genome/genome.js | 95 | ||||
| -rw-r--r-- | src/genome/genome.test.js | 185 |
2 files changed, 140 insertions, 140 deletions
diff --git a/src/genome/genome.js b/src/genome/genome.js index bc569ff..20974fc 100644 --- a/src/genome/genome.js +++ b/src/genome/genome.js @@ -5,38 +5,25 @@ import { network } from '../mind/topology.js'; // check if a given genome is valid and compute its size
-export function get_size(num_input, num_output, genome) {
- const [ max_index, max_weight ] = genome.reduce(
- ([max_index, max_weight ], [ source, sink, weight]) => [
- Math.max(max_index, source, sink),
- Math.max(max_weight, Math.abs(weight)),
- ],
- [ 0, 0 ]
+export function validate_genome(genome) {
+ const { n_input, n_internal, n_output } = genome;
+ console.log(n_input + n_internal);
+ return genome.genes.reduce(
+ (acc, [source, sink, weight]) => acc && (
+ (source < n_input+n_internal) &&
+ (sink >= n_input)
+ ),
+ true
);
-
- if (max_index < num_input + num_output - 1) {
- return -1;
- }
- else if (max_weight > 4.0) {
- return -1;
- }
- else {
- return max_index + 1;
- }
}
-
// parse a genome into a useable neural net
-export function parse_genome(num_input, num_output, genome) {
- const size = get_size(num_input, num_output, genome);
- if (size < 0) {
- // bad genome
- throw new Error('invalid genome sequence!');
- }
+export function parse_genome(genome) {
+ const { n_input, n_internal, n_output } = genome;
- const n = genome.reduce(
+ const n = genome.genes.reduce(
(acc, [source, sink, weight]) => acc.connect(source, sink, weight),
- network(num_input, size-num_input-num_output, num_output)
+ network(n_input, n_internal, n_output)
);
return n;
@@ -100,27 +87,26 @@ export function mut_gene_weight(weight_max, gene, r) { // expand the size of the neural net encoded by the genome
// relabels internal indices so that there is one extra internal neuron
-export function mut_genome_expand(
- [n_input, n_internal, n_output, genome], r
-) {
- const expand_index = Math.floor(n_internal * r) + n_input;
- const new_genome = genome.map(([source, sink, weight]) => [
+export function mut_genome_expand(genome, r) {
+ const expand_index = Math.floor(genome.n_internal * r) + genome.n_input;
+ const new_genes = genome.genes.map(([source, sink, weight]) => [
source >= expand_index ? source+1 : source,
sink >= expand_index ? sink+1 : sink,
weight,
]);
- return [
- n_input, n_internal+1, n_output, new_genome,
- ];
+ return {
+ ...genome,
+ n_internal: genome.n_internal+1,
+ genes: new_genes,
+ };
}
// contract the size of the neural net encoded by the genome
// relabels internal indices so that there is one less internal neuron
-export function mut_genome_contract(
- [n_input, n_internal, n_output, genome], r
-) {
+export function mut_genome_contract(genome, r) {
+ const { n_input, n_internal, n_output } = genome;
const contract_idx = Math.floor(n_internal * r) + n_input;
// decrement sources on the contract index too, to prevent invalid genomes
@@ -128,42 +114,39 @@ export function mut_genome_contract( // decrement sinks only after the contract index
const new_sink = (sink) => sink > contract_idx ? sink-1 : sink;
- const new_genome = genome.map(([source, sink, weight]) => [
+ const new_genes = genome.genes.map(([source, sink, weight]) => [
new_source(source),
new_sink(sink),
weight,
]);
- return [
- n_input, n_internal-1, n_output, new_genome
- ];
+ return {
+ ...genome,
+ n_internal: n_internal-1,
+ genes: new_genes,
+ };
}
// append a newly generated gene to the end of the genome
-export function mut_genome_insert(
- [n_input, n_internal, n_output, genome],
- weight_max,
- r1, r2, r3
-) {
+export function mut_genome_insert(genome, weight_max, r1=Math.random(), r2=Math.random(), r3=Math.random()) {
+ const { n_input, n_internal, n_output } = genome;
const source = Math.floor((n_input + n_internal) * r1);
const sink = Math.floor((n_internal + n_output) * r2) + n_input;
const weight = weight_max * ((2*r3)-1);
- return [
- n_input, n_internal, n_output,
- [...genome, [source, sink, weight]],
- ];
+ return {
+ ...genome,
+ genes: [...genome.genes, [source, sink, weight]],
+ };
}
// delete a gene from the genome
-export function mut_genome_delete(
- [n_input, n_internal, n_output, genome], r
-) {
- const del_idx = Math.floor(r * genome.length);
- const new_genome = genome.filter((_, idx) => idx != del_idx);
- return [n_input, n_internal, n_output, new_genome];
+export function mut_genome_delete(genome, r) {
+ const del_idx = Math.floor(r * genome.genes.length);
+ const genes = genome.genes.filter((_, idx) => idx != del_idx);
+ return { ...genome, genes };
}
diff --git a/src/genome/genome.test.js b/src/genome/genome.test.js index 37bdacc..bc64e4e 100644 --- a/src/genome/genome.test.js +++ b/src/genome/genome.test.js @@ -1,7 +1,14 @@ 'use strict';
+// genome structure
+// {
+// genes: gene[]
+// n_input, n_internal, n_output
+// }
+
+
import {
- get_size,
+ validate_genome,
parse_genome,
mut_gene_source,
mut_gene_sink,
@@ -13,20 +20,39 @@ import { } from './genome';
-test('genome validation and size', () => {
- expect(get_size(0, 0, [ [ 0, 0, 1.0 ] ])).toBe(1);
- expect(get_size(2, 1, [ [ 0, 2, 1 ] ])).toBe(3);
- expect(get_size(2, 1, [ [ 0, 1, 1 ] ])).toBe(-1);
- expect(get_size(2, 1, [ [ 0, 2, 5 ] ])).toBe(-1);
+test('genome validation', () => {
+ expect(validate_genome({
+ n_input: 0, n_internal: 1, n_output: 0,
+ genes: [[0, 0, 1.0]],
+ })).toBe(true);
+ expect(validate_genome({
+ n_input: 2, n_internal: 0, n_output: 1,
+ genes: [[0, 2, 1]],
+ })).toBe(true);
+ expect(validate_genome({
+ n_input: 2, n_internal: 0, n_output: 1,
+ genes: [[2, 0, 1]],
+ })).toBe(false);
+ expect(validate_genome({
+ n_input: 2, n_internal: 0, n_output: 1,
+ genes: [[2, 2, 1]],
+ })).toBe(false);
+ expect(validate_genome({
+ n_input: 2, n_internal: 1, n_output: 1,
+ genes: [[3, 2, 1]],
+ })).toBe(false);
});
test('parse a genome into a neural net', () => {
- const n = parse_genome(1, 1, [
- [0, 1, 1],
- [1, 1, 1],
- [1, 2, 1]
- ]);
+ const n = parse_genome({
+ n_input: 1, n_internal: 1, n_output: 1,
+ genes: [
+ [0, 1, 1],
+ [1, 1, 1],
+ [1, 2, 1]
+ ]
+ });
expect(n.input_count).toBe(1);
expect(n.output_count).toBe(1);
@@ -121,48 +147,45 @@ test('expand genome', () => { const n_internal = 3;
const n_output = 1;
- const genome = [
- [0, 1, 0],
- [1, 2, 0],
- [2, 3, 0],
- [3, 4, 0],
- ];
-
- expect(mut_genome_expand([
- n_input, n_internal, n_output, genome
- ], 0.0)).toEqual([
- n_input, n_internal+1, n_output,
- [
+ const genome = {
+ n_input, n_internal, n_output,
+ genes: [
+ [0, 1, 0],
+ [1, 2, 0],
+ [2, 3, 0],
+ [3, 4, 0],
+ ],
+ };
+
+ expect(mut_genome_expand(genome, 0.0)).toEqual({
+ n_input, n_internal: n_internal+1, n_output,
+ genes: [
[0, 2, 0],
[2, 3, 0],
[3, 4, 0],
[4, 5, 0],
],
- ]);
+ });
- expect(mut_genome_expand([
- n_input, n_internal, n_output, genome
- ], 0.5)).toEqual([
- n_input, n_internal+1, n_output,
- [
+ expect(mut_genome_expand(genome, 0.5)).toEqual({
+ n_input, n_internal: n_internal+1, n_output,
+ genes: [
[0, 1, 0],
[1, 3, 0],
[3, 4, 0],
[4, 5, 0],
],
- ]);
+ });
- expect(mut_genome_expand([
- n_input, n_internal, n_output, genome
- ], 0.99)).toEqual([
- n_input, n_internal+1, n_output,
- [
+ expect(mut_genome_expand(genome, 0.99)).toEqual({
+ n_input, n_internal: n_internal+1, n_output,
+ genes: [
[0, 1, 0],
[1, 2, 0],
[2, 4, 0],
[4, 5, 0],
],
- ]);
+ });
});
@@ -171,48 +194,45 @@ test('contract genome', () => { const n_internal = 3;
const n_output = 1;
- const genome = [
- [0, 1, 0],
- [1, 2, 1],
- [2, 3, 2],
- [3, 4, 3],
- ];
-
- expect(mut_genome_contract([
- n_input, n_internal, n_output, genome
- ], 0.0)).toEqual([
- n_input, n_internal-1, n_output,
- [
+ const genome = {
+ n_input, n_internal, n_output,
+ genes: [
+ [0, 1, 0],
+ [1, 2, 1],
+ [2, 3, 2],
+ [3, 4, 3],
+ ],
+ };
+
+ expect(mut_genome_contract(genome, 0.0)).toEqual({
+ n_input, n_internal: n_internal-1, n_output,
+ genes: [
[0, 1, 0],
[0, 1, 1],
[1, 2, 2],
[2, 3, 3],
],
- ]);
+ });
- expect(mut_genome_contract([
- n_input, n_internal, n_output, genome
- ], 0.5)).toEqual([
- n_input, n_internal-1, n_output,
- [
+ expect(mut_genome_contract(genome, 0.5)).toEqual({
+ n_input, n_internal: n_internal-1, n_output,
+ genes: [
[0, 1, 0],
[1, 2, 1],
[1, 2, 2],
[2, 3, 3],
],
- ]);
+ });
- expect(mut_genome_contract([
- n_input, n_internal, n_output, genome
- ], 0.99)).toEqual([
- n_input, n_internal-1, n_output,
- [
+ expect(mut_genome_contract(genome, 0.99)).toEqual({
+ n_input, n_internal: n_internal-1, n_output,
+ genes: [
[0, 1, 0],
[1, 2, 1],
[2, 3, 2],
[2, 3, 3],
],
- ]);
+ });
});
@@ -223,21 +243,21 @@ test('insert new genes', () => { const n_output = 1;
const weight_max = 4;
- expect(mut_genome_insert([
+ expect(mut_genome_insert({
n_input, n_internal, n_output,
- []
- ], weight_max, 0, 0.5, 0)).toEqual([
+ genes: []
+ }, weight_max, 0, 0.5, 0)).toEqual({
n_input, n_internal, n_output,
- [[0, 2, -4]]
- ]);
+ genes: [[0, 2, -4]]
+ });
- expect(mut_genome_insert([
+ expect(mut_genome_insert({
n_input, n_internal, n_output,
- [[0, 2, -4]]
- ], weight_max, 0.99, 0, 1)).toEqual([
+ genes: [[0, 2, -4]]
+ }, weight_max, 0.99, 0, 1)).toEqual({
n_input, n_internal, n_output,
- [[0, 2, -4], [2, 1, 4]]
- ]);
+ genes: [[0, 2, -4], [2, 1, 4]]
+ });
});
@@ -245,21 +265,18 @@ test('remove genes', () => { const n_input = 0;
const n_output = 0;
const n_internal = 3;
- const genome = [
- [0, 1, 0], [1, 2, 0],
- ];
+ const genome = {
+ n_input, n_internal, n_output,
+ genes: [[0, 1, 0], [1, 2, 0]],
+ };
- expect(mut_genome_delete([
- n_input, n_internal, n_output, genome
- ], 0.0)).toEqual([
+ expect(mut_genome_delete(genome, 0.0)).toEqual({
n_input, n_internal, n_output,
- [[1, 2, 0]],
- ]);
+ genes: [[1, 2, 0]],
+ });
- expect(mut_genome_delete([
- n_input, n_internal, n_output, genome
- ], 0.99)).toEqual([
+ expect(mut_genome_delete(genome, 0.99)).toEqual({
n_input, n_internal, n_output,
- [[0, 1, 0]],
- ]);
+ genes: [[0, 1, 0]],
+ });
});
|