strudel/packages/mini/test/mini.test.mjs
Alex McLean 68c9008019
Fix Bjorklund (#343)
* port Rohan Drape's Bjorklund implementation, add Toussaint's tests
* fix euclidLegato, simplifying a bit now that bjork results should always begin with an 'on'
* migrate euclid numbers in tunes
- 3,4 +1
- 5,8 -1
- 6,8 +3

Co-authored-by: Felix Roos <flix91@gmail.com>
2023-01-06 11:31:32 +00:00

171 lines
7.9 KiB
JavaScript

/*
mini.test.mjs - <short description TODO>
Copyright (C) 2022 Strudel contributors - see <https://github.com/tidalcycles/strudel/blob/main/packages/mini/test/mini.test.mjs>
This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License for more details. You should have received a copy of the GNU Affero General Public License along with this program. If not, see <https://www.gnu.org/licenses/>.
*/
import { mini } from '../mini.mjs';
import '@strudel.cycles/core/euclid.mjs';
import { describe, expect, it } from 'vitest';
describe('mini', () => {
const minV = (v) => mini(v).firstCycleValues;
const minS = (v) => mini(v).showFirstCycle;
it('supports single elements', () => {
expect(minV('a')).toEqual(['a']);
});
it('supports rest', () => {
expect(minV('~')).toEqual([]);
});
it('supports cat', () => {
expect(minS('a b')).toEqual(['a: 0 - 1/2', 'b: 1/2 - 1']);
expect(minS('a b c')).toEqual(['a: 0 - 1/3', 'b: 1/3 - 2/3', 'c: 2/3 - 1']);
});
it('supports fast', () => {
expect(minS('a*3 b')).toEqual(minS('[a a a] b'));
});
it('supports patterned fast', () => {
expect(minS('[a*<3 5>]*2')).toEqual(minS('[a a a] [a a a a a]'));
});
it('supports slow', () => {
expect(minS('[a a a]/3 b')).toEqual(minS('a b'));
});
it('supports patterned slow', () => {
expect(minS('[a a a a a a a a]/[2 4]')).toEqual(minS('[a a] a'));
});
it('supports patterned fast', () => {
expect(minS('[a*<3 5>]*2')).toEqual(minS('[a a a] [a a a a a]'));
});
it('supports slowcat', () => {
expect(minV('<a b>')).toEqual(['a']);
});
it('supports division', () => {
expect(minS('a/2')).toEqual(['a: 0 - 2']);
expect(minS('[c3 d3]/2')).toEqual(['c3: 0 - 1']);
});
it('supports multiplication', () => {
expect(minS('c3*2')).toEqual(['c3: 0 - 1/2', 'c3: 1/2 - 1']);
expect(minV('[c3 d3]*2')).toEqual(['c3', 'd3', 'c3', 'd3']);
});
it('supports brackets', () => {
expect(minS('c3 [d3 e3]')).toEqual(['c3: 0 - 1/2', 'd3: 1/2 - 3/4', 'e3: 3/4 - 1']);
expect(minS('c3 [d3 [e3 f3]]')).toEqual(['c3: 0 - 1/2', 'd3: 1/2 - 3/4', 'e3: 3/4 - 7/8', 'f3: 7/8 - 1']);
});
it('supports curly brackets', () => {
expect(minS('{a b, c d e}*3')).toEqual(minS('[a b a b a b, c d e c d e]'));
expect(minS('{a b, c [d e] f}*3')).toEqual(minS('[a b a b a b, c [d e] f c [d e] f]'));
expect(minS('{a b c, d e}*2')).toEqual(minS('[a b c a b c, d e d e d e]'));
});
it('supports curly brackets with explicit step-per-cycle', () => {
expect(minS('{a b, c d e}%3')).toEqual(minS('[a b a, c d e]'));
expect(minS('{a b, c d e}%5')).toEqual(minS('[a b a b a, c d e c d]'));
expect(minS('{a b, c d e}%6')).toEqual(minS('[a b a b a b, c d e c d e]'));
});
it('supports commas', () => {
expect(minS('c3,e3,g3')).toEqual(['c3: 0 - 1', 'e3: 0 - 1', 'g3: 0 - 1']);
expect(minS('[c3,e3,g3] f3')).toEqual(['c3: 0 - 1/2', 'e3: 0 - 1/2', 'g3: 0 - 1/2', 'f3: 1/2 - 1']);
});
it('supports elongation', () => {
expect(minS('a@3 b')).toEqual(['a: 0 - 3/4', 'b: 3/4 - 1']);
expect(minS('a@2 b@3')).toEqual(['a: 0 - 2/5', 'b: 2/5 - 1']);
});
it('supports replication', () => {
expect(minS('a!3 b')).toEqual(['a: 0 - 1/4', 'a: 1/4 - 1/2', 'a: 1/2 - 3/4', 'b: 3/4 - 1']);
expect(minS('[<a b c>]!3 d')).toEqual(minS('<a b c> <a b c> <a b c> d'));
});
it('supports euclidean rhythms', () => {
expect(minS('a(3, 8)')).toEqual(['a: 0 - 1/8', 'a: 3/8 - 1/2', 'a: 3/4 - 7/8']);
});
it('supports patterning euclidean rhythms', () => {
expect(minS('[a(<3 5>, <8 16>)]*2')).toEqual(minS('a(3,8) a(5,16)'));
});
it("reproduces Toussaint's example euclidean algorithms", () => {
const checkEuclid = function (spec, target) {
expect(minS(`x(${spec[0]},${spec[1]})`)).toEqual(minS(target));
};
checkEuclid([1, 2], 'x ~');
checkEuclid([1, 3], 'x ~ ~');
checkEuclid([1, 4], 'x ~ ~ ~');
checkEuclid([4, 12], 'x ~ ~ x ~ ~ x ~ ~ x ~ ~');
checkEuclid([2, 5], 'x ~ x ~ ~');
// checkEuclid([3, 4], "x ~ x x"); // Toussaint is wrong..
checkEuclid([3, 4], 'x x x ~'); // correction
checkEuclid([3, 5], 'x ~ x ~ x');
checkEuclid([3, 7], 'x ~ x ~ x ~ ~');
checkEuclid([3, 8], 'x ~ ~ x ~ ~ x ~');
checkEuclid([4, 7], 'x ~ x ~ x ~ x');
checkEuclid([4, 9], 'x ~ x ~ x ~ x ~ ~');
checkEuclid([4, 11], 'x ~ ~ x ~ ~ x ~ ~ x ~');
// checkEuclid([5, 6], "x ~ x x x x"); // Toussaint is wrong..
checkEuclid([5, 6], 'x x x x x ~'); // correction
checkEuclid([5, 7], 'x ~ x x ~ x x');
checkEuclid([5, 8], 'x ~ x x ~ x x ~');
checkEuclid([5, 9], 'x ~ x ~ x ~ x ~ x');
checkEuclid([5, 11], 'x ~ x ~ x ~ x ~ x ~ ~');
checkEuclid([5, 12], 'x ~ ~ x ~ x ~ ~ x ~ x ~');
// checkEuclid([5, 16], "x ~ ~ x ~ ~ x ~ ~ x ~ ~ x ~ ~ ~ ~"); // Toussaint is wrong..
checkEuclid([5, 16], 'x ~ ~ x ~ ~ x ~ ~ x ~ ~ x ~ ~ ~'); // correction
// checkEuclid([7, 8], "x ~ x x x x x x"); // Toussaint is wrong..
checkEuclid([7, 8], 'x x x x x x x ~'); // Correction
checkEuclid([7, 12], 'x ~ x x ~ x ~ x x ~ x ~');
checkEuclid([7, 16], 'x ~ ~ x ~ x ~ x ~ ~ x ~ x ~ x ~');
checkEuclid([9, 16], 'x ~ x x ~ x ~ x ~ x x ~ x ~ x ~');
checkEuclid([11, 24], 'x ~ ~ x ~ x ~ x ~ x ~ x ~ ~ x ~ x ~ x ~ x ~ x ~');
checkEuclid([13, 24], 'x ~ x x ~ x ~ x ~ x ~ x ~ x x ~ x ~ x ~ x ~ x ~');
});
it('supports the ? operator', () => {
expect(
mini('a?')
.queryArc(0, 20)
.map((hap) => hap.whole.begin),
).toEqual(
mini('a')
.degradeBy(0.5)
.queryArc(0, 20)
.map((hap) => hap.whole.begin),
);
});
// testing things that involve pseudo-randomness, so there's a probability we could fail by chance.
// these next few tests work with the current PRNG, and are intended to succeed with p > 0.99 even if the PRNG changes
// (as long as the PRNG has a relatively-uniform distribution of values)
it('supports degradeBy with default of 50%', () => {
const haps = mini('a?').queryArc(0, 1000);
expect(459 <= haps.length && haps.length <= 541).toBe(true);
// 'Number of elements did not fall in 99% confidence interval for binomial with p=0.5',
});
it('supports degradeBy with an argument', () => {
const haps = mini('a?0.8').queryArc(0, 1000);
expect(haps.length > 0).toBe(true);
// 'Should have had at least one element when degradeBy was set at 0.8');
expect(haps.length < 230).toBe(true);
// 'Had too many cycles remaining after degradeBy 0.8');
});
/*it('supports the random choice operator ("|") with nesting', () => {
const numCycles = 900;
const haps = mini('a | [b | c] | [d | e | f]').queryArc(0, numCycles);
// Should have about 1/3 a, 1/6 each of b | c, and 1/9 each of d | e | f.
// Evaluating this distribution with a chi-squared test.
// Note: this just evaluates the overall distribution, not things like correlation/runs of values
const observed = haps.reduce((acc, hap) => {
acc[hap.value] = (acc[hap.value] || 0) + 1;
return acc;
}, {});
const expected = {
a: numCycles / 3,
b: numCycles / 6,
c: numCycles / 6,
d: numCycles / 9,
e: numCycles / 9,
f: numCycles / 9,
};
let chisq = -numCycles;
for (let k in expected) {
chisq += (observed[k] * observed[k]) / expected[k];
}
// 15.086 is the chisq for 5 degrees of freedom at 99%, so for 99% of uniformly-distributed
// PRNG, this test should succeed
expect(chisq <= 15.086).toBe(true);
// assert(chisq <= 15.086, chisq + ' was expected to be less than 15.086 under chi-squared test');
});*/
});