1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
#![allow(dead_code)]
use super::bit_cost::BrotliPopulationCost;
use super::histogram::{
    CostAccessors, HistogramAddHistogram, HistogramClear, HistogramSelfAddHistogram,
};
use super::util::FastLog2;
use alloc::{Allocator, SliceWrapper, SliceWrapperMut};
use core::cmp::min;
#[derive(Clone, Copy)]
pub struct HistogramPair {
    pub idx1: u32,
    pub idx2: u32,
    pub cost_combo: super::util::floatX,
    pub cost_diff: super::util::floatX,
}

impl Default for HistogramPair {
    #[inline(always)]
    fn default() -> HistogramPair {
        HistogramPair {
            idx1: 0,
            idx2: 0,
            cost_combo: 0.0 as super::util::floatX,
            cost_diff: 0.0 as super::util::floatX,
        }
    }
}
/* Returns entropy reduction of the context map when we combine two clusters. */
#[inline(always)]
fn ClusterCostDiff(size_a: usize, size_b: usize) -> super::util::floatX {
    let size_c: usize = size_a.wrapping_add(size_b);
    size_a as (super::util::floatX) * FastLog2(size_a as u64)
        + size_b as (super::util::floatX) * FastLog2(size_b as u64)
        - size_c as (super::util::floatX) * FastLog2(size_c as u64)
}

#[inline(always)]
fn HistogramPairIsLess(p1: &HistogramPair, p2: &HistogramPair) -> bool {
    if p1.cost_diff != p2.cost_diff {
        p1.cost_diff > p2.cost_diff
    } else {
        p1.idx2.wrapping_sub(p1.idx1) > p2.idx2.wrapping_sub(p2.idx1)
    }
}

/* Computes the bit cost reduction by combining out[idx1] and out[idx2] and if
it is below a threshold, stores the pair (idx1, idx2) in the *pairs queue. */
fn BrotliCompareAndPushToQueue<
    HistogramType: SliceWrapperMut<u32> + SliceWrapper<u32> + CostAccessors + Clone,
>(
    out: &[HistogramType],
    cluster_size: &[u32],
    mut idx1: u32,
    mut idx2: u32,
    max_num_pairs: usize,
    scratch_space: &mut HistogramType::i32vec,
    pairs: &mut [HistogramPair],
    num_pairs: &mut usize,
) {
    let mut is_good_pair: i32 = 0i32;
    let mut p: HistogramPair = HistogramPair {
        idx1: 0,
        idx2: 0,
        cost_combo: 0.0,
        cost_diff: 0.0,
    };
    if idx1 == idx2 {
    } else {
        if idx2 < idx1 {
            core::mem::swap(&mut idx2, &mut idx1);
        }
        p.idx1 = idx1;
        p.idx2 = idx2;
        p.cost_diff = 0.5 as super::util::floatX
            * ClusterCostDiff(
                cluster_size[idx1 as usize] as usize,
                cluster_size[idx2 as usize] as usize,
            );
        p.cost_diff -= (out[idx1 as usize]).bit_cost();
        p.cost_diff -= (out[idx2 as usize]).bit_cost();
        if (out[idx1 as usize]).total_count() == 0usize {
            p.cost_combo = (out[idx2 as usize]).bit_cost();
            is_good_pair = 1i32;
        } else if (out[idx2 as usize]).total_count() == 0usize {
            p.cost_combo = (out[idx1 as usize]).bit_cost();
            is_good_pair = 1i32;
        } else {
            let threshold: super::util::floatX = if *num_pairs == 0usize {
                1e38 as super::util::floatX
            } else {
                pairs[0].cost_diff.max(0.0)
            };

            let mut combo: HistogramType = out[idx1 as usize].clone();
            HistogramAddHistogram(&mut combo, &out[idx2 as usize]);
            let cost_combo: super::util::floatX = BrotliPopulationCost(&combo, scratch_space);
            if cost_combo < threshold - p.cost_diff {
                p.cost_combo = cost_combo;
                is_good_pair = 1i32;
            }
        }
        if is_good_pair != 0 {
            p.cost_diff += p.cost_combo;
            if *num_pairs > 0usize && HistogramPairIsLess(&pairs[0], &p) {
                /* Replace the top of the queue if needed. */
                if *num_pairs < max_num_pairs {
                    pairs[*num_pairs] = pairs[0];
                    *num_pairs = num_pairs.wrapping_add(1);
                }
                pairs[0] = p;
            } else if *num_pairs < max_num_pairs {
                pairs[*num_pairs] = p;
                *num_pairs = num_pairs.wrapping_add(1);
            }
        }
    }
}

pub fn BrotliHistogramCombine<
    HistogramType: SliceWrapperMut<u32> + SliceWrapper<u32> + CostAccessors + Clone,
>(
    out: &mut [HistogramType],
    cluster_size: &mut [u32],
    symbols: &mut [u32],
    clusters: &mut [u32],
    pairs: &mut [HistogramPair],
    mut num_clusters: usize,
    symbols_size: usize,
    max_clusters: usize,
    max_num_pairs: usize,
    scratch_space: &mut HistogramType::i32vec,
) -> usize {
    let mut cost_diff_threshold: super::util::floatX = 0.0 as super::util::floatX;
    let mut min_cluster_size: usize = 1;
    let mut num_pairs: usize = 0usize;
    {
        /* We maintain a vector of histogram pairs, with the property that the pair
        with the maximum bit cost reduction is the first. */
        for idx1 in 0..num_clusters {
            for idx2 in idx1 + 1..num_clusters {
                BrotliCompareAndPushToQueue(
                    out,
                    cluster_size,
                    clusters[idx1],
                    clusters[idx2],
                    max_num_pairs,
                    scratch_space,
                    pairs,
                    &mut num_pairs,
                );
            }
        }
    }
    while num_clusters > min_cluster_size {
        let mut i: usize;
        if (pairs[0]).cost_diff >= cost_diff_threshold {
            cost_diff_threshold = 1e38 as super::util::floatX;
            min_cluster_size = max_clusters;
            {
                continue;
            }
        }
        /* Take the best pair from the top of heap. */
        let best_idx1: u32 = (pairs[0]).idx1;
        let best_idx2: u32 = (pairs[0]).idx2;
        HistogramSelfAddHistogram(out, (best_idx1 as usize), (best_idx2 as usize));
        (out[(best_idx1 as usize)]).set_bit_cost((pairs[0]).cost_combo);
        {
            let _rhs = cluster_size[(best_idx2 as usize)];
            let _lhs = &mut cluster_size[(best_idx1 as usize)];
            *_lhs = (*_lhs).wrapping_add(_rhs);
        }
        for i in 0usize..symbols_size {
            if symbols[i] == best_idx2 {
                symbols[i] = best_idx1;
            }
        }
        i = 0usize;
        'break9: while i < num_clusters {
            {
                if clusters[i] == best_idx2 {
                    for offset in 0..(num_clusters - i - 1) {
                        clusters[i + offset] = clusters[i + 1 + offset];
                    }
                    break 'break9;
                }
            }
            i = i.wrapping_add(1);
        }
        num_clusters = num_clusters.wrapping_sub(1);
        {
            /* Remove pairs intersecting the just combined best pair. */
            let mut copy_to_idx: usize = 0usize;
            i = 0usize;
            while i < num_pairs {
                'continue12: loop {
                    {
                        let p: HistogramPair = pairs[i];
                        if (p).idx1 == best_idx1
                            || (p).idx2 == best_idx1
                            || (p).idx1 == best_idx2
                            || (p).idx2 == best_idx2
                        {
                            /* Remove invalid pair from the queue. */
                            break 'continue12;
                        }
                        if HistogramPairIsLess(&pairs[0], &p) {
                            /* Replace the top of the queue if needed. */
                            let front: HistogramPair = pairs[0];
                            pairs[0] = p;
                            pairs[copy_to_idx] = front;
                        } else {
                            pairs[copy_to_idx] = p;
                        }
                        copy_to_idx = copy_to_idx.wrapping_add(1);
                    }
                    break;
                }
                i = i.wrapping_add(1);
            }
            num_pairs = copy_to_idx;
        }
        for i in 0usize..num_clusters {
            BrotliCompareAndPushToQueue(
                out,
                cluster_size,
                best_idx1,
                clusters[i],
                max_num_pairs,
                scratch_space,
                pairs,
                &mut num_pairs,
            );
        }
    }
    num_clusters
}

/* What is the bit cost of moving histogram from cur_symbol to candidate. */
#[inline(always)]
pub fn BrotliHistogramBitCostDistance<
    HistogramType: SliceWrapperMut<u32> + SliceWrapper<u32> + CostAccessors + Clone,
>(
    histogram: &HistogramType,
    candidate: &HistogramType,
    scratch_space: &mut HistogramType::i32vec,
) -> super::util::floatX {
    if histogram.total_count() == 0usize {
        0.0 as super::util::floatX
    } else {
        let mut tmp: HistogramType = histogram.clone();
        HistogramAddHistogram(&mut tmp, candidate);
        BrotliPopulationCost(&tmp, scratch_space) - candidate.bit_cost()
    }
}

/* Find the best 'out' histogram for each of the 'in' histograms.
When called, clusters[0..num_clusters) contains the unique values from
symbols[0..in_size), but this property is not preserved in this function.
Note: we assume that out[]->bit_cost_ is already up-to-date. */

pub fn BrotliHistogramRemap<
    HistogramType: SliceWrapperMut<u32> + SliceWrapper<u32> + CostAccessors + Clone,
>(
    inp: &[HistogramType],
    in_size: usize,
    clusters: &[u32],
    num_clusters: usize,
    scratch_space: &mut HistogramType::i32vec,
    out: &mut [HistogramType],
    symbols: &mut [u32],
) {
    for i in 0usize..in_size {
        let mut best_out: u32 = if i == 0usize {
            symbols[0]
        } else {
            symbols[i.wrapping_sub(1)]
        };
        let mut best_bits: super::util::floatX =
            BrotliHistogramBitCostDistance(&inp[i], &mut out[(best_out as usize)], scratch_space);
        for j in 0usize..num_clusters {
            let cur_bits: super::util::floatX = BrotliHistogramBitCostDistance(
                &inp[i],
                &mut out[(clusters[j] as usize)],
                scratch_space,
            );
            if cur_bits < best_bits {
                best_bits = cur_bits;
                best_out = clusters[j];
            }
        }
        symbols[i] = best_out;
    }
    for i in 0usize..num_clusters {
        HistogramClear(&mut out[(clusters[i] as usize)]);
    }
    for i in 0usize..in_size {
        HistogramAddHistogram(&mut out[(symbols[i] as usize)], &inp[i]);
    }
}

/* Reorders elements of the out[0..length) array and changes values in
symbols[0..length) array in the following way:
  * when called, symbols[] contains indexes into out[], and has N unique
    values (possibly N < length)
  * on return, symbols'[i] = f(symbols[i]) and
               out'[symbols'[i]] = out[symbols[i]], for each 0 <= i < length,
    where f is a bijection between the range of symbols[] and [0..N), and
    the first occurrences of values in symbols'[i] come in consecutive
    increasing order.
Returns N, the number of unique values in symbols[]. */
pub fn BrotliHistogramReindex<
    HistogramType: SliceWrapperMut<u32> + SliceWrapper<u32> + CostAccessors + Clone,
    Alloc: alloc::Allocator<u32> + alloc::Allocator<HistogramType>,
>(
    alloc: &mut Alloc,
    out: &mut [HistogramType],
    symbols: &mut [u32],
    length: usize,
) -> usize {
    static kInvalidIndex: u32 = !(0u32);
    let mut new_index = if length != 0 {
        <Alloc as Allocator<u32>>::alloc_cell(alloc, length)
    } else {
        <Alloc as Allocator<u32>>::AllocatedMemory::default()
    };
    let mut next_index: u32;
    let mut tmp: <Alloc as Allocator<HistogramType>>::AllocatedMemory;
    for i in 0usize..length {
        new_index.slice_mut()[i] = kInvalidIndex;
    }
    next_index = 0u32;
    for i in 0usize..length {
        if new_index.slice()[(symbols[i] as usize)] == kInvalidIndex {
            new_index.slice_mut()[(symbols[i] as usize)] = next_index;
            next_index = next_index.wrapping_add(1);
        }
    }
    tmp = if next_index != 0 {
        <Alloc as Allocator<HistogramType>>::alloc_cell(alloc, next_index as usize)
    } else {
        <Alloc as Allocator<HistogramType>>::AllocatedMemory::default()
    };
    next_index = 0u32;
    for i in 0usize..length {
        if new_index.slice()[(symbols[i] as usize)] == next_index {
            tmp.slice_mut()[(next_index as usize)] = out[(symbols[i] as usize)].clone();
            next_index = next_index.wrapping_add(1);
        }
        symbols[i] = new_index.slice()[(symbols[i] as usize)];
    }
    {
        <Alloc as Allocator<u32>>::free_cell(alloc, new_index);
    }
    for i in 0usize..next_index as usize {
        out[i] = tmp.slice()[i].clone();
    }
    {
        <Alloc as Allocator<HistogramType>>::free_cell(alloc, tmp)
    }
    next_index as usize
}

pub fn BrotliClusterHistograms<
    HistogramType: SliceWrapperMut<u32> + SliceWrapper<u32> + CostAccessors + Clone,
    Alloc: alloc::Allocator<u32> + alloc::Allocator<HistogramPair> + alloc::Allocator<HistogramType>,
>(
    alloc: &mut Alloc,
    inp: &[HistogramType],
    in_size: usize,
    max_histograms: usize,
    scratch_space: &mut HistogramType::i32vec,
    out: &mut [HistogramType],
    out_size: &mut usize,
    histogram_symbols: &mut [u32],
) {
    let mut cluster_size = if in_size != 0 {
        <Alloc as Allocator<u32>>::alloc_cell(alloc, in_size)
    } else {
        <Alloc as Allocator<u32>>::AllocatedMemory::default()
    };
    let mut clusters = if in_size != 0 {
        <Alloc as Allocator<u32>>::alloc_cell(alloc, in_size)
    } else {
        <Alloc as Allocator<u32>>::AllocatedMemory::default()
    };
    let mut num_clusters: usize = 0usize;
    let max_input_histograms: usize = 64usize;
    let pairs_capacity: usize = max_input_histograms
        .wrapping_mul(max_input_histograms)
        .wrapping_div(2);
    let mut pairs =
        <Alloc as Allocator<HistogramPair>>::alloc_cell(alloc, pairs_capacity.wrapping_add(1));
    let mut i: usize;
    for i in 0usize..in_size {
        cluster_size.slice_mut()[i] = 1u32;
    }
    for i in 0usize..in_size {
        out[i] = inp[i].clone();
        (out[i]).set_bit_cost(BrotliPopulationCost(&inp[i], scratch_space));
        histogram_symbols[i] = i as u32;
    }
    i = 0usize;
    while i < in_size {
        {
            let num_to_combine: usize = min(in_size.wrapping_sub(i), max_input_histograms);

            for j in 0usize..num_to_combine {
                clusters.slice_mut()[num_clusters.wrapping_add(j)] = i.wrapping_add(j) as u32;
            }
            let num_new_clusters: usize = BrotliHistogramCombine(
                out,
                cluster_size.slice_mut(),
                &mut histogram_symbols[i..],
                &mut clusters.slice_mut()[num_clusters..],
                pairs.slice_mut(),
                num_to_combine,
                num_to_combine,
                max_histograms,
                pairs_capacity,
                scratch_space,
            );
            num_clusters = num_clusters.wrapping_add(num_new_clusters);
        }
        i = i.wrapping_add(max_input_histograms);
    }
    {
        let max_num_pairs: usize = min(
            (64usize).wrapping_mul(num_clusters),
            num_clusters.wrapping_div(2).wrapping_mul(num_clusters),
        );
        {
            if pairs_capacity < max_num_pairs.wrapping_add(1) {
                let mut _new_size: usize = if pairs_capacity == 0usize {
                    max_num_pairs.wrapping_add(1)
                } else {
                    pairs_capacity
                };
                let mut new_array: <Alloc as Allocator<HistogramPair>>::AllocatedMemory;
                while _new_size < max_num_pairs.wrapping_add(1) {
                    _new_size = _new_size.wrapping_mul(2);
                }
                new_array = if _new_size != 0 {
                    <Alloc as Allocator<HistogramPair>>::alloc_cell(alloc, _new_size)
                } else {
                    <Alloc as Allocator<HistogramPair>>::AllocatedMemory::default()
                };
                new_array.slice_mut()[..pairs_capacity]
                    .clone_from_slice(&pairs.slice()[..pairs_capacity]);
                <Alloc as Allocator<HistogramPair>>::free_cell(
                    alloc,
                    core::mem::replace(&mut pairs, new_array),
                );
            }
        }
        num_clusters = BrotliHistogramCombine(
            out,
            cluster_size.slice_mut(),
            histogram_symbols,
            clusters.slice_mut(),
            pairs.slice_mut(),
            num_clusters,
            in_size,
            max_histograms,
            max_num_pairs,
            scratch_space,
        );
    }
    <Alloc as Allocator<HistogramPair>>::free_cell(alloc, pairs);
    <Alloc as Allocator<u32>>::free_cell(alloc, cluster_size);
    BrotliHistogramRemap(
        inp,
        in_size,
        clusters.slice(),
        num_clusters,
        scratch_space,
        out,
        histogram_symbols,
    );
    <Alloc as Allocator<u32>>::free_cell(alloc, clusters);
    *out_size = BrotliHistogramReindex(alloc, out, histogram_symbols, in_size);
}

/////////// DONE //////////////////////////