'use strict';

// genome structure
// {
//   genes: gene[]
//   n_input, n_internal, n_output
// }


import { 
  validate_genome,
  parse_genome,
  mut_gene_source,
  mut_gene_sink,
  mut_gene_weight,
  mut_genome_expand,
  mut_genome_contract,
  mut_genome_insert,
  mut_genome_delete,
} from './genome';


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({
    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);
	expect(n.compute([2], [-1])).toEqual([
		[ Math.tanh( Math.tanh( 2-1 ) ) ],
		[ Math.tanh( 2-1 ) ],
	]);
});


test('mutate gene source', () => {
  const n_input = 3;
  const n_internal = 4;
  const n_output = 5;

  expect(mut_gene_source(
    n_input, n_internal, n_output, 
    [0, 4, 0],
    0.0
  )).toEqual([0, 4, 0]);

  expect(mut_gene_source(
    n_input, n_internal, n_output, 
    [0, 4, 0],
    1.0
  )).toEqual([1, 4, 0]);

  expect(mut_gene_source(
    n_input, n_internal, n_output, 
    [6, 4, 0],
    0.0
  )).toEqual([5, 4, 0]);

  expect(mut_gene_source(
    n_input, n_internal, n_output, 
    [6, 4, 0],
    1.0
  )).toEqual([6, 4, 0]);
});


test('mutate gene sink', () => {
  const n_input = 3;
  const n_internal = 4;
  const n_output = 5;

  expect(mut_gene_sink(
    n_input, n_internal, n_output, 
    [0, 7, 0],
    0.0
  )).toEqual([0, 7, 0]);

  expect(mut_gene_sink(
    n_input, n_internal, n_output, 
    [0, 7, 0],
    1.0
  )).toEqual([0, 8, 0]);

  expect(mut_gene_sink(
    n_input, n_internal, n_output, 
    [6, 11, 0],
    0.0
  )).toEqual([6, 10, 0]);

  expect(mut_gene_sink(
    n_input, n_internal, n_output, 
    [6, 11, 0],
    1.0
  )).toEqual([6, 11, 0]);
});


test('mutate gene weight', () => {
  const weight_max = 4.0;

  expect(mut_gene_weight(
    weight_max, [0, 0, 1], 0.0
  )).toEqual([0, 0, (2 - 4)/3]);

  expect(mut_gene_weight(
    weight_max, [0, 0, -4], 1.0
  )).toEqual([0, 0, (-8 + 4)/3]);

  expect(mut_gene_weight(
    weight_max, [0, 0, 3], 0.5
  )).toEqual([0, 0, (6+0)/3]);
});


test('expand genome', () => {
  const n_input = 1;
  const n_internal = 3;
  const n_output = 1;

  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(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(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],
    ],
  });
});


test('contract genome', () => {
  const n_input = 1;
  const n_internal = 3;
  const n_output = 1;

  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(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(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],
    ],
  });
});



test('insert new genes', () => {
  const n_input = 1;
  const n_internal = 2;
  const n_output = 1;
  const weight_max = 4;

  expect(mut_genome_insert({
    n_input, n_internal, n_output,
    genes: []
  }, weight_max, 0, 0.5, 0)).toEqual({
    n_input, n_internal, n_output,
    genes: [[0, 2, -4]]
  });

  expect(mut_genome_insert({
    n_input, n_internal, n_output,
    genes: [[0, 2, -4]]
  }, weight_max, 0.99, 0, 1)).toEqual({
    n_input, n_internal, n_output,
    genes: [[0, 2, -4], [2, 1, 4]]
  });
});


test('remove genes', () => {
  const n_input = 0;
  const n_output = 0;
  const n_internal = 3;
  const genome = {
    n_input, n_internal, n_output,
    genes: [[0, 1, 0], [1, 2, 0]],
  };

  expect(mut_genome_delete(genome, 0.0)).toEqual({
    n_input, n_internal, n_output, 
    genes: [[1, 2, 0]],
  });

  expect(mut_genome_delete(genome, 0.99)).toEqual({
    n_input, n_internal, n_output, 
    genes: [[0, 1, 0]],
  });
});