@gmod/cram
Version:
read CRAM files with pure Javascript
118 lines • 4.39 kB
JavaScript
/* eslint-disable no-var */
// @ts-nocheck
/*
* Copyright (c) 2019 Genome Research Ltd.
* Author(s): James Bonfield
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are met:
*
* 1. Redistributions of source code must retain the above copyright notice,
* this list of conditions and the following disclaimer.
*
* 2. Redistributions in binary form must reproduce the above
* copyright notice, this list of conditions and the following
* disclaimer in the documentation and/or other materials provided
* with the distribution.
*
* 3. Neither the names Genome Research Ltd and Wellcome Trust Sanger
* Institute nor the names of its contributors may be used to endorse
* or promote products derived from this software without specific
* prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY GENOME RESEARCH LTD AND CONTRIBUTORS "AS
* IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED
* TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A
* PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL GENOME RESEARCH
* LTD OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
* SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
* LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
* DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
* THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
// An adaptive probability model for encoding and decoding of symbols
// within a given alphabet, using the range coder to get/put the
// compressed data.
const MAX_FREQ = (1 << 16) - 17;
const STEP = 16;
export default class ByteModel {
constructor(max_sym = 256) {
this.total_freq = max_sym;
this.max_sym = max_sym - 1;
this.S = [];
this.F = [];
for (let i = 0; i <= this.max_sym; i++) {
this.S[i] = i;
this.F[i] = 1;
}
}
ModelDecode(src, rc) {
// Find symbol
const freq = rc.RangeGetFrequency(this.total_freq);
// Linear scan to find cumulative frequency 'freq'
let acc = 0;
let x = 0;
while (acc + this.F[x] <= freq) {
acc += this.F[x++];
}
// for (var acc = 0; (acc += this.F[x]) <= freq; x++)
// ;
// acc -= this.F[x];
// Update range coder
rc.RangeDecode(src, acc, this.F[x], this.total_freq);
// Update model
this.F[x] += STEP;
this.total_freq += STEP;
if (this.total_freq > MAX_FREQ) {
this.ModelRenormalise();
}
// Keep symbols approximately frequency sorted
const sym = this.S[x];
if (x > 0 && this.F[x] > this.F[x - 1]) {
let tmp = this.F[x];
this.F[x] = this.F[x - 1];
this.F[x - 1] = tmp;
tmp = this.S[x];
this.S[x] = this.S[x - 1];
this.S[x - 1] = tmp;
}
return sym;
}
ModelRenormalise() {
// Halve all the frequencies, being careful not to hit zero
this.total_freq = 0;
for (let i = 0; i <= this.max_sym; i++) {
this.F[i] -= Math.floor(this.F[i] / 2);
this.total_freq += this.F[i];
}
}
ModelEncode(dst, rc, sym) {
// Find cumulative frequency
let acc = 0;
for (var x = 0; this.S[x] != sym; x++) {
acc += this.F[x];
}
// Encode
rc.RangeEncode(dst, acc, this.F[x], this.total_freq);
// Update model
this.F[x] += STEP;
this.total_freq += STEP;
if (this.total_freq > MAX_FREQ) {
// FIXME x2
this.ModelRenormalise();
}
// Keep symbols approximately frequency sorted
var sym = this.S[x];
if (x > 0 && this.F[x] > this.F[x - 1]) {
let tmp = this.F[x];
this.F[x] = this.F[x - 1];
this.F[x - 1] = tmp;
tmp = this.S[x];
this.S[x] = this.S[x - 1];
this.S[x - 1] = tmp;
}
}
}
//# sourceMappingURL=byte_model.js.map