/*
* Copyright © 2021 Google, Inc.
*
* This is part of HarfBuzz, a text shaping library.
*
* Permission is hereby granted, without written agreement and without
* license or royalty fees, to use, copy, modify, and distribute this
* software and its documentation for any purpose, provided that the
* above copyright notice and the following two paragraphs appear in
* all copies of this software.
*
* IN NO EVENT SHALL THE COPYRIGHT HOLDER BE LIABLE TO ANY PARTY FOR
* DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES
* ARISING OUT OF THE USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN
* IF THE COPYRIGHT HOLDER HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH
* DAMAGE.
*
* THE COPYRIGHT HOLDER SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING,
* BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND
* FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS
* ON AN "AS IS" BASIS, AND THE COPYRIGHT HOLDER HAS NO OBLIGATION TO
* PROVIDE MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
*
*/
#ifndef HB_OT_VAR_COMMON_HH
#define HB_OT_VAR_COMMON_HH
#include "hb-ot-layout-common.hh"
#include "hb-priority-queue.hh"
namespace OT {
template <typename MapCountT>
struct DeltaSetIndexMapFormat01
{
friend struct DeltaSetIndexMap;
unsigned get_size () const
{ return min_size + mapCount * get_width (); }
private:
DeltaSetIndexMapFormat01* copy (hb_serialize_context_t *c) const
{
TRACE_SERIALIZE (this);
return_trace (c->embed (this));
}
template <typename T>
bool serialize (hb_serialize_context_t *c, const T &plan)
{
unsigned int width = plan.get_width ();
unsigned int inner_bit_count = plan.get_inner_bit_count ();
const hb_array_t<const uint32_t> output_map = plan.get_output_map ();
TRACE_SERIALIZE (this);
if (unlikely (output_map.length && ((((inner_bit_count-1)&~0xF)!=0) || (((width-1)&~0x3)!=0))))
return_trace (false);
if (unlikely (!c->extend_min (this))) return_trace (false);
entryFormat = ((width-1)<<4)|(inner_bit_count-1);
mapCount = output_map.length;
HBUINT8 *p = c->allocate_size<HBUINT8> (width * output_map.length);
if (unlikely (!p)) return_trace (false);
for (unsigned int i = 0; i < output_map.length; i++)
{
unsigned int v = output_map.arrayZ[i];
if (v)
{
unsigned int outer = v >> 16;
unsigned int inner = v & 0xFFFF;
unsigned int u = (outer << inner_bit_count) | inner;
for (unsigned int w = width; w > 0;)
{
p[--w] = u;
u >>= 8;
}
}
p += width;
}
return_trace (true);
}
uint32_t map (unsigned int v) const /* Returns 16.16 outer.inner. */
{
/* If count is zero, pass value unchanged. This takes
* care of direct mapping for advance map. */
if (!mapCount)
return v;
if (v >= mapCount)
v = mapCount - 1;
unsigned int u = 0;
{ /* Fetch it. */
unsigned int w = get_width ();
const HBUINT8 *p = mapDataZ.arrayZ + w * v;
for (; w; w--)
u = (u << 8) + *p++;
}
{ /* Repack it. */
unsigned int n = get_inner_bit_count ();
unsigned int outer = u >> n;
unsigned int inner = u & ((1 << n) - 1);
u = (outer<<16) | inner;
}
return u;
}
unsigned get_map_count () const { return mapCount; }
unsigned get_width () const { return ((entryFormat >> 4) & 3) + 1; }
unsigned get_inner_bit_count () const { return (entryFormat & 0xF) + 1; }
bool sanitize (hb_sanitize_context_t *c) const
{
TRACE_SANITIZE (this);
return_trace (c->check_struct (this) &&
hb_barrier () &&
c->check_range (mapDataZ.arrayZ,
mapCount,
get_width ()));
}
protected:
HBUINT8 format; /* Format identifier--format = 0 */
HBUINT8 entryFormat; /* A packed field that describes the compressed
* representation of delta-set indices. */
MapCountT mapCount; /* The number of mapping entries. */
UnsizedArrayOf<HBUINT8>
mapDataZ; /* The delta-set index mapping data. */
public:
DEFINE_SIZE_ARRAY (2+MapCountT::static_size, mapDataZ);
};
struct DeltaSetIndexMap
{
template <typename T>
bool serialize (hb_serialize_context_t *c, const T &plan)
{
TRACE_SERIALIZE (this);
unsigned length = plan.get_output_map ().length;
u.format = length <= 0xFFFF ? 0 : 1;
switch (u.format) {
case 0: return_trace (u.format0.serialize (c, plan));
case 1: return_trace (u.format1.serialize (c, plan));
default:return_trace (false);
}
}
uint32_t map (unsigned v) const
{
switch (u.format) {
case 0: return (u.format0.map (v));
case 1: return (u.format1.map (v));
default:return v;
}
}
unsigned get_map_count () const
{
switch (u.format) {
case 0: return u.format0.get_map_count ();
case 1: return u.format1.get_map_count ();
default:return 0;
}
}
unsigned get_width () const
{
switch (u.format) {
case 0: return u.format0.get_width ();
case 1: return u.format1.get_width ();
default:return 0;
}
}
unsigned get_inner_bit_count () const
{
switch (u.format) {
case 0: return u.format0.get_inner_bit_count ();
case 1: return u.format1.get_inner_bit_count ();
default:return 0;
}
}
bool sanitize (hb_sanitize_context_t *c) const
{
TRACE_SANITIZE (this);
if (!u.format.sanitize (c)) return_trace (false);
hb_barrier ();
switch (u.format) {
case 0: return_trace (u.format0.sanitize (c));
case 1: return_trace (u.format1.sanitize (c));
default:return_trace (true);
}
}
DeltaSetIndexMap* copy (hb_serialize_context_t *c) const
{
TRACE_SERIALIZE (this);
switch (u.format) {
case 0: return_trace (reinterpret_cast<DeltaSetIndexMap *> (u.format0.copy (c)));
case 1: return_trace (reinterpret_cast<DeltaSetIndexMap *> (u.format1.copy (c)));
default:return_trace (nullptr);
}
}
protected:
union {
HBUINT8 format; /* Format identifier */
DeltaSetIndexMapFormat01<HBUINT16> format0;
DeltaSetIndexMapFormat01<HBUINT32> format1;
} u;
public:
DEFINE_SIZE_UNION (1, format);
};
struct VarStoreInstancer
{
VarStoreInstancer (const VariationStore *varStore,
const DeltaSetIndexMap *varIdxMap,
hb_array_t<int> coords) :
varStore (varStore), varIdxMap (varIdxMap), coords (coords) {}
operator bool () const { return varStore && bool (coords); }
/* according to the spec, if colr table has varStore but does not have
* varIdxMap, then an implicit identity mapping is used */
float operator() (uint32_t varIdx, unsigned short offset = 0) const
{ return coords ? varStore->get_delta (varIdxMap ? varIdxMap->map (VarIdx::add (varIdx, offset)) : varIdx + offset, coords) : 0; }
const VariationStore *varStore;
const DeltaSetIndexMap *varIdxMap;
hb_array_t<int> coords;
};
/* https://docs.microsoft.com/en-us/typography/opentype/spec/otvarcommonformats#tuplevariationheader */
struct TupleVariationHeader
{
friend struct tuple_delta_t;
unsigned get_size (unsigned axis_count) const
{ return min_size + get_all_tuples (axis_count).get_size (); }
unsigned get_data_size () const { return varDataSize; }
const TupleVariationHeader &get_next (unsigned axis_count) const
{ return StructAtOffset<TupleVariationHeader> (this, get_size (axis_count)); }
bool unpack_axis_tuples (unsigned axis_count,
const hb_array_t<const F2DOT14> shared_tuples,
const hb_map_t *axes_old_index_tag_map,
hb_hashmap_t<hb_tag_t, Triple>& axis_tuples /* OUT */) const
{
const F2DOT14 *peak_tuple = nullptr;
if (has_peak ())
peak_tuple = get_peak_tuple (axis_count).arrayZ;
else
{
unsigned int index = get_index ();
if (unlikely ((index + 1) * axis_count > shared_tuples.length))
return false;
peak_tuple = shared_tuples.sub_array (axis_count * index, axis_count).arrayZ;
}
const F2DOT14 *start_tuple = nullptr;
const F2DOT14 *end_tuple = nullptr;
bool has_interm = has_intermediate ();
if (has_interm)
{
start_tuple = get_start_tuple (axis_count).arrayZ;
end_tuple = get_end_tuple (axis_count).arrayZ;
}
for (unsigned i = 0; i < axis_count; i++)
{
float peak = peak_tuple[i].to_float ();
if (peak == 0.f) continue;
hb_tag_t *axis_tag;
if (!axes_old_index_tag_map->has (i, &axis_tag))
return false;
float start, end;
if (has_interm)
{
start = start_tuple[i].to_float ();
end = end_tuple[i].to_float ();
}
else
{
start = hb_min (peak, 0.f);
end = hb_max (peak, 0.f);
}
axis_tuples.set (*axis_tag, Triple (start, peak, end));
}
return true;
}
float calculate_scalar (hb_array_t<int> coords, unsigned int coord_count,
const hb_array_t<const F2DOT14> shared_tuples,
const hb_vector_t<hb_pair_t<int,int>> *shared_tuple_active_idx = nullptr) const
{
const F2DOT14 *peak_tuple;
unsigned start_idx = 0;
unsigned end_idx = coord_count;
unsigned step = 1;
if (has_peak ())
peak_tuple = get_peak_tuple (coord_count).arrayZ;
else
{
unsigned int index = get_index ();
if (unlikely ((index + 1) * coord_count > shared_tuples.length))
return 0.f;
peak_tuple = shared_tuples.sub_array (coord_count * index, coord_count).arrayZ;
if (shared_tuple_active_idx)
{
if (unlikely (index >= shared_tuple_active_idx->length))
return 0.f;
auto _ = (*shared_tuple_active_idx).arrayZ[index];
if (_.second != -1)
{
start_idx = _.first;
end_idx = _.second + 1;
step = _.second - _.first;
}
else if (_.first != -1)
{
start_idx = _.first;
end_idx = start_idx + 1;
}
}
}
const F2DOT14 *start_tuple = nullptr;
const F2DOT14 *end_tuple = nullptr;
bool has_interm = has_intermediate ();
if (has_interm)
{
start_tuple = get_start_tuple (coord_count).arrayZ;
end_tuple = get_end_tuple (coord_count).arrayZ;
}
float scalar = 1.f;
for (unsigned int i = start_idx; i < end_idx; i += step)
{
int peak = peak_tuple[i].to_int ();
if (!peak) continue;
int v = coords[i];
if (v == peak) continue;
if (has_interm)
{
int start = start_tuple[i].to_int ();
int end = end_tuple[i].to_int ();
if (unlikely (start > peak || peak > end ||
(start < 0 && end > 0 && peak))) continue;
if (v < start || v > end) return 0.f;
if (v < peak)
{ if (peak != start) scalar *= (float) (v - start) / (peak - start); }
else
{ if (peak != end) scalar *= (float) (end - v) / (end - peak); }
}
else if (!v || v < hb_min (0, peak) || v > hb_max (0, peak)) return 0.f;
else
scalar *= (float) v / peak;
}
return scalar;
}
bool has_peak () const { return tupleIndex & TuppleIndex::EmbeddedPeakTuple; }
bool has_intermediate () const { return tupleIndex & TuppleIndex::IntermediateRegion; }
bool has_private_points () const { return tupleIndex & TuppleIndex::PrivatePointNumbers; }
unsigned get_index () const { return tupleIndex & TuppleIndex::TupleIndexMask; }
protected:
struct TuppleIndex : HBUINT16
{
enum Flags {
EmbeddedPeakTuple = 0x8000u,
IntermediateRegion = 0x4000u,
PrivatePointNumbers = 0x2000u,
TupleIndexMask = 0x0FFFu
};
TuppleIndex& operator = (uint16_t i) { HBUINT16::operator= (i); return *this; }
DEFINE_SIZE_STATIC (2);
};
hb_array_t<const F2DOT14> get_all_tuples (unsigned axis_count) const
{ return StructAfter<UnsizedArrayOf<F2DOT14>> (tupleIndex).as_array ((has_peak () + has_intermediate () * 2) * axis_count); }
hb_array_t<const F2DOT14> get_peak_tuple (unsigned axis_count) const
{ return get_all_tuples (axis_count).sub_array (0, axis_count); }
hb_array_t<const F2DOT14> get_start_tuple (unsigned axis_count) const
{ return get_all_tuples (axis_count).sub_array (has_peak () * axis_count, axis_count); }
hb_array_t<const F2DOT14> get_end_tuple (unsigned axis_count) const
{ return get_all_tuples (axis_count).sub_array (has_peak () * axis_count + axis_count, axis_count); }
HBUINT16 varDataSize; /* The size in bytes of the serialized
* data for this tuple variation table. */
TuppleIndex tupleIndex; /* A packed field. The high 4 bits are flags (see below).
The low 12 bits are an index into a shared tuple
records array. */
/* UnsizedArrayOf<F2DOT14> peakTuple - optional */
/* Peak tuple record for this tuple variation table — optional,
* determined by flags in the tupleIndex value.
*
* Note that this must always be included in the 'cvar' table. */
/* UnsizedArrayOf<F2DOT14> intermediateStartTuple - optional */
/* Intermediate start tuple record for this tuple variation table — optional,
determined by flags in the tupleIndex value. */
/* UnsizedArrayOf<F2DOT14> intermediateEndTuple - optional */
/* Intermediate end tuple record for this tuple variation table — optional,
* determined by flags in the tupleIndex value. */
public:
DEFINE_SIZE_MIN (4);
};
enum packed_delta_flag_t
{
DELTAS_ARE_ZERO = 0x80,
DELTAS_ARE_WORDS = 0x40,
DELTA_RUN_COUNT_MASK = 0x3F
};
struct tuple_delta_t
{
static constexpr bool realloc_move = true; // Watch out when adding new members!
public:
hb_hashmap_t<hb_tag_t, Triple> axis_tuples;
/* indices_length = point_count, indice[i] = 1 means point i is referenced */
hb_vector_t<bool> indices;
hb_vector_t<float> deltas_x;
/* empty for cvar tuples */
hb_vector_t<float> deltas_y;
/* compiled data: header and deltas
* compiled point data is saved in a hashmap within tuple_variations_t cause
* some point sets might be reused by different tuple variations */
hb_vector_t<char> compiled_tuple_header;
hb_vector_t<char> compiled_deltas;
/* compiled peak coords, empty for non-gvar tuples */
hb_vector_t<char> compiled_peak_coords;
tuple_delta_t () = default;
tuple_delta_t (const tuple_delta_t& o) = default;
friend void swap (tuple_delta_t& a, tuple_delta_t& b)
{
hb_swap (a.axis_tuples, b.axis_tuples);
hb_swap (a.indices, b.indices);
hb_swap (a.deltas_x, b.deltas_x);
hb_swap (a.deltas_y, b.deltas_y);
hb_swap (a.compiled_tuple_header, b.compiled_tuple_header);
hb_swap (a.compiled_deltas, b.compiled_deltas);
hb_swap (a.compiled_peak_coords, b.compiled_peak_coords);
}
tuple_delta_t (tuple_delta_t&& o) : tuple_delta_t ()
{ hb_swap (*this, o); }
tuple_delta_t& operator = (tuple_delta_t&& o)
{
hb_swap (*this, o);
return *this;
}
void remove_axis (hb_tag_t axis_tag)
{ axis_tuples.del (axis_tag); }
bool set_tent (hb_tag_t axis_tag, Triple tent)
{ return axis_tuples.set (axis_tag, tent); }
tuple_delta_t& operator += (const tuple_delta_t& o)
{
unsigned num = indices.length;
for (unsigned i = 0; i < num; i++)
{
if (indices.arrayZ[i])
{
if (o.indices.arrayZ[i])
{
deltas_x[i] += o.deltas_x[i];
if (deltas_y && o.deltas_y)
deltas_y[i] += o.deltas_y[i];
}
}
else
{
if (!o.indices.arrayZ[i]) continue;
indices.arrayZ[i] = true;
deltas_x[i] = o.deltas_x[i];
if (deltas_y && o.deltas_y)
deltas_y[i] = o.deltas_y[i];
}
}
return *this;
}
tuple_delta_t& operator *= (float scalar)
{
if (scalar == 1.0f)
return *this;
unsigned num = indices.length;
if (deltas_y)
for (unsigned i = 0; i < num; i++)
{
if (!indices.arrayZ[i]) continue;
deltas_x[i] *= scalar;
deltas_y[i] *= scalar;
}
else
for (unsigned i = 0; i < num; i++)
{
if (!indices.arrayZ[i]) continue;
deltas_x[i] *= scalar;
}
return *this;
}
hb_vector_t<tuple_delta_t> change_tuple_var_axis_limit (hb_tag_t axis_tag, Triple axis_limit,
TripleDistances axis_triple_distances) const
{
hb_vector_t<tuple_delta_t> out;
Triple *tent;
if (!axis_tuples.has (axis_tag, &tent))
{
out.push (*this);
return out;
}
if ((tent->minimum < 0.f && tent->maximum > 0.f) ||
!(tent->minimum <= tent->middle && tent->middle <= tent->maximum))
return out;
if (tent->middle == 0.f)
{
out.push (*this);
return out;
}
result_t solutions = rebase_tent (*tent, axis_limit, axis_triple_distances);
for (auto t : solutions)
{
tuple_delta_t new_var = *this;
if (t.second == Triple ())
new_var.remove_axis (axis_tag);
else
new_var.set_tent (axis_tag, t.second);
new_var *= t.first;
out.push (std::move (new_var));
}
return out;
}
bool compile_peak_coords (const hb_map_t& axes_index_map,
const hb_map_t& axes_old_index_tag_map)
{
unsigned axis_count = axes_index_map.get_population ();
if (unlikely (!compiled_peak_coords.alloc (axis_count * F2DOT14::static_size)))
return false;
unsigned orig_axis_count = axes_old_index_tag_map.get_population ();
for (unsigned i = 0; i < orig_axis_count; i++)
{
if (!axes_index_map.has (i))
continue;
hb_tag_t axis_tag = axes_old_index_tag_map.get (i);
Triple *coords;
F2DOT14 peak_coord;
if (axis_tuples.has (axis_tag, &coords))
peak_coord.set_float (coords->middle);
else
peak_coord.set_int (0);
/* push F2DOT14 value into char vector */
int16_t val = peak_coord.to_int ();
compiled_peak_coords.push (static_cast<char> (val >> 8));
compiled_peak_coords.push (static_cast<char> (val & 0xFF));
}
return !compiled_peak_coords.in_error ();
}
/* deltas should be compiled already before we compile tuple
* variation header cause we need to fill in the size of the
* serialized data for this tuple variation */
bool compile_tuple_var_header (const hb_map_t& axes_index_map,
unsigned points_data_length,
const hb_map_t& axes_old_index_tag_map,
const hb_hashmap_t<const hb_vector_t<char>*, unsigned>* shared_tuples_idx_map)
{
if (!compiled_deltas) return false;
unsigned cur_axis_count = axes_index_map.get_population ();
/* allocate enough memory: 1 peak + 2 intermediate coords + fixed header size */
unsigned alloc_len = 3 * cur_axis_count * (F2DOT14::static_size) + 4;
if (unlikely (!compiled_tuple_header.resize (alloc_len))) return false;
unsigned flag = 0;
/* skip the first 4 header bytes: variationDataSize+tupleIndex */
F2DOT14* p = reinterpret_cast<F2DOT14 *> (compiled_tuple_header.begin () + 4);
F2DOT14* end = reinterpret_cast<F2DOT14 *> (compiled_tuple_header.end ());
hb_array_t<F2DOT14> coords (p, end - p);
/* encode peak coords */
unsigned peak_count = 0;
unsigned *shared_tuple_idx;
if (shared_tuples_idx_map &&
shared_tuples_idx_map->has (&compiled_peak_coords, &shared_tuple_idx))
{
flag = *shared_tuple_idx;
}
else
{
peak_count = encode_peak_coords(coords, flag, axes_index_map, axes_old_index_tag_map);
if (!peak_count) return false;
}
/* encode interim coords, it's optional so returned num could be 0 */
unsigned interim_count = encode_interm_coords (coords.sub_array (peak_count), flag, axes_index_map, axes_old_index_tag_map);
/* pointdata length = 0 implies "use shared points" */
if (points_data_length)
flag |= TupleVariationHeader::TuppleIndex::PrivatePointNumbers;
unsigned serialized_data_size = points_data_length + compiled_deltas.length;
TupleVariationHeader *o = reinterpret_cast<TupleVariationHeader *> (compiled_tuple_header.begin ());
o->varDataSize = serialized_data_size;
o->tupleIndex = flag;
unsigned total_header_len = 4 + (peak_count + interim_count) * (F2DOT14::static_size);
return compiled_tuple_header.resize (total_header_len);
}
unsigned encode_peak_coords (hb_array_t<F2DOT14> peak_coords,
unsigned& flag,
const hb_map_t& axes_index_map,
const hb_map_t& axes_old_index_tag_map) const
{
unsigned orig_axis_count = axes_old_index_tag_map.get_population ();
auto it = peak_coords.iter ();
unsigned count = 0;
for (unsigned i = 0; i < orig_axis_count; i++)
{
if (!axes_index_map.has (i)) /* axis pinned */
continue;
hb_tag_t axis_tag = axes_old_index_tag_map.get (i);
Triple *coords;
if (!axis_tuples.has (axis_tag, &coords))
(*it).set_int (0);
else
(*it).set_float (coords->middle);
it++;
count++;
}
flag |= TupleVariationHeader::TuppleIndex::EmbeddedPeakTuple;
return count;
}
/* if no need to encode intermediate coords, then just return p */
unsigned encode_interm_coords (hb_array_t<F2DOT14> coords,
unsigned& flag,
const hb_map_t& axes_index_map,
const hb_map_t& axes_old_index_tag_map) const
{
unsigned orig_axis_count = axes_old_index_tag_map.get_population ();
unsigned cur_axis_count = axes_index_map.get_population ();
auto start_coords_iter = coords.sub_array (0, cur_axis_count).iter ();
auto end_coords_iter = coords.sub_array (cur_axis_count).iter ();
bool encode_needed = false;
unsigned count = 0;
for (unsigned i = 0; i < orig_axis_count; i++)
{
if (!axes_index_map.has (i)) /* axis pinned */
continue;
hb_tag_t axis_tag = axes_old_index_tag_map.get (i);
Triple *coords;
float min_val = 0.f, val = 0.f, max_val = 0.f;
if (axis_tuples.has (axis_tag, &coords))
{
min_val = coords->minimum;
val = coords->middle;
max_val = coords->maximum;
}
(*start_coords_iter).set_float (min_val);
(*end_coords_iter).set_float (max_val);
start_coords_iter++;
end_coords_iter++;
count += 2;
if (min_val != hb_min (val, 0.f) || max_val != hb_max (val, 0.f))
encode_needed = true;
}
if (encode_needed)
{
flag |= TupleVariationHeader::TuppleIndex::IntermediateRegion;
return count;
}
return 0;
}
bool compile_deltas ()
{
hb_vector_t<int> rounded_deltas;
if (unlikely (!rounded_deltas.alloc (indices.length)))
return false;
for (unsigned i = 0; i < indices.length; i++)
{
if (!indices[i]) continue;
int rounded_delta = (int) roundf (deltas_x[i]);
rounded_deltas.push (rounded_delta);
}
if (!rounded_deltas) return false;
/* allocate enough memories 3 * num_deltas */
unsigned alloc_len = 3 * rounded_deltas.length;
if (deltas_y)
alloc_len *= 2;
if (unlikely (!compiled_deltas.resize (alloc_len))) return false;
unsigned i = 0;
unsigned encoded_len = encode_delta_run (i, compiled_deltas.as_array (), rounded_deltas);
if (deltas_y)
{
/* reuse the rounded_deltas vector, check that deltas_y have the same num of deltas as deltas_x */
unsigned j = 0;
for (unsigned idx = 0; idx < indices.length; idx++)
{
if (!indices[idx]) continue;
int rounded_delta = (int) roundf (deltas_y[idx]);
if (j >= rounded_deltas.length) return false;
rounded_deltas[j++] = rounded_delta;
}
if (j != rounded_deltas.length) return false;
/* reset i because we reuse rounded_deltas for deltas_y */
i = 0;
encoded_len += encode_delta_run (i, compiled_deltas.as_array ().sub_array (encoded_len), rounded_deltas);
}
return compiled_deltas.resize (encoded_len);
}
unsigned encode_delta_run (unsigned& i,
hb_array_t<char> encoded_bytes,
const hb_vector_t<int>& deltas) const
{
unsigned num_deltas = deltas.length;
unsigned encoded_len = 0;
while (i < num_deltas)
{
int val = deltas.arrayZ[i];
if (val == 0)
encoded_len += encode_delta_run_as_zeroes (i, encoded_bytes.sub_array (encoded_len), deltas);
else if (val >= -128 && val <= 127)
encoded_len += encode_delta_run_as_bytes (i, encoded_bytes.sub_array (encoded_len), deltas);
else
encoded_len += encode_delta_run_as_words (i, encoded_bytes.sub_array (encoded_len), deltas);
}
return encoded_len;
}
unsigned encode_delta_run_as_zeroes (unsigned& i,
hb_array_t<char> encoded_bytes,
const hb_vector_t<int>& deltas) const
{
unsigned num_deltas = deltas.length;
unsigned run_length = 0;
auto it = encoded_bytes.iter ();
unsigned encoded_len = 0;
while (i < num_deltas && deltas.arrayZ[i] == 0)
{
i++;
run_length++;
}
while (run_length >= 64)
{
*it++ = char (DELTAS_ARE_ZERO | 63);
run_length -= 64;
encoded_len++;
}
if (run_length)
{
*it++ = char (DELTAS_ARE_ZERO | (run_length - 1));
encoded_len++;
}
return encoded_len;
}
unsigned encode_delta_run_as_bytes (unsigned &i,
hb_array_t<char> encoded_bytes,
const hb_vector_t<int>& deltas) const
{
unsigned start = i;
unsigned num_deltas = deltas.length;
while (i < num_deltas)
{
int val = deltas.arrayZ[i];
if (val > 127 || val < -128)
break;
/* from fonttools: if there're 2 or more zeros in a sequence,
* it is better to start a new run to save bytes. */
if (val == 0 && i + 1 < num_deltas && deltas.arrayZ[i+1] == 0)
break;
i++;
}
unsigned run_length = i - start;
unsigned encoded_len = 0;
auto it = encoded_bytes.iter ();
while (run_length >= 64)
{
*it++ = 63;
encoded_len++;
for (unsigned j = 0; j < 64; j++)
{
*it++ = static_cast<char> (deltas.arrayZ[start + j]);
encoded_len++;
}
start += 64;
run_length -= 64;
}
if (run_length)
{
*it++ = run_length - 1;
encoded_len++;
while (start < i)
{
*it++ = static_cast<char> (deltas.arrayZ[start++]);
encoded_len++;
}
}
return encoded_len;
}
unsigned encode_delta_run_as_words (unsigned &i,
hb_array_t<char> encoded_bytes,
const hb_vector_t<int>& deltas) const
{
unsigned start = i;
unsigned num_deltas = deltas.length;
while (i < num_deltas)
{
int val = deltas.arrayZ[i];
/* start a new run for a single zero value*/
if (val == 0) break;
/* from fonttools: continue word-encoded run if there's only one
* single value in the range [-128, 127] because it is more compact.
* Only start a new run when there're 2 continuous such values. */
if (val >= -128 && val <= 127 &&
i + 1 < num_deltas &&
deltas.arrayZ[i+1] >= -128 && deltas.arrayZ[i+1] <= 127)
break;
i++;
}
unsigned run_length = i - start;
auto it = encoded_bytes.iter ();
unsigned encoded_len = 0;
while (run_length >= 64)
{
*it++ = (DELTAS_ARE_WORDS | 63);
encoded_len++;
for (unsigned j = 0; j < 64; j++)
{
int16_t delta_val = deltas.arrayZ[start + j];
*it++ = static_cast<char> (delta_val >> 8);
*it++ = static_cast<char> (delta_val & 0xFF);
encoded_len += 2;
}
start += 64;
run_length -= 64;
}
if (run_length)
{
*it++ = (DELTAS_ARE_WORDS | (run_length - 1));
encoded_len++;
while (start < i)
{
int16_t delta_val = deltas.arrayZ[start++];
*it++ = static_cast<char> (delta_val >> 8);
*it++ = static_cast<char> (delta_val & 0xFF);
encoded_len += 2;
}
}
return encoded_len;
}
bool calc_inferred_deltas (const contour_point_vector_t& orig_points)
{
unsigned point_count = orig_points.length;
if (point_count != indices.length)
return false;
unsigned ref_count = 0;
hb_vector_t<unsigned> end_points;
for (unsigned i = 0; i < point_count; i++)
{
if (indices.arrayZ[i])
ref_count++;
if (orig_points.arrayZ[i].is_end_point)
end_points.push (i);
}
/* all points are referenced, nothing to do */
if (ref_count == point_count)
return true;
if (unlikely (end_points.in_error ())) return false;
hb_set_t inferred_idxes;
unsigned start_point = 0;
for (unsigned end_point : end_points)
{
/* Check the number of unreferenced points in a contour. If no unref points or no ref points, nothing to do. */
unsigned unref_count = 0;
for (unsigned i = start_point; i < end_point + 1; i++)
unref_count += indices.arrayZ[i];
unref_count = (end_point - start_point + 1) - unref_count;
unsigned j = start_point;
if (unref_count == 0 || unref_count > end_point - start_point)
goto no_more_gaps;
for (;;)
{
/* Locate the next gap of unreferenced points between two referenced points prev and next.
* Note that a gap may wrap around at left (start_point) and/or at right (end_point).
*/
unsigned int prev, next, i;
for (;;)
{
i = j;
j = next_index (i, start_point, end_point);
if (indices.arrayZ[i] && !indices.arrayZ[j]) break;
}
prev = j = i;
for (;;)
{
i = j;
j = next_index (i, start_point, end_point);
if (!indices.arrayZ[i] && indices.arrayZ[j]) break;
}
next = j;
/* Infer deltas for all unref points in the gap between prev and next */
i = prev;
for (;;)
{
i = next_index (i, start_point, end_point);
if (i == next) break;
deltas_x.arrayZ[i] = infer_delta (orig_points.arrayZ[i].x, orig_points.arrayZ[prev].x, orig_points.arrayZ[next].x,
deltas_x.arrayZ[prev], deltas_x.arrayZ[next]);
deltas_y.arrayZ[i] = infer_delta (orig_points.arrayZ[i].y, orig_points.arrayZ[prev].y, orig_points.arrayZ[next].y,
deltas_y.arrayZ[prev], deltas_y.arrayZ[next]);
inferred_idxes.add (i);
if (--unref_count == 0) goto no_more_gaps;
}
}
no_more_gaps:
start_point = end_point + 1;
}
for (unsigned i = 0; i < point_count; i++)
{
/* if points are not referenced and deltas are not inferred, set to 0.
* reference all points for gvar */
if ( !indices[i])
{
if (!inferred_idxes.has (i))
{
deltas_x.arrayZ[i] = 0.f;
deltas_y.arrayZ[i] = 0.f;
}
indices[i] = true;
}
}
return true;
}
static float infer_delta (float target_val, float prev_val, float next_val, float prev_delta, float next_delta)
{
if (prev_val == next_val)
return (prev_delta == next_delta) ? prev_delta : 0.f;
else if (target_val <= hb_min (prev_val, next_val))
return (prev_val < next_val) ? prev_delta : next_delta;
else if (target_val >= hb_max (prev_val, next_val))
return (prev_val > next_val) ? prev_delta : next_delta;
float r = (target_val - prev_val) / (next_val - prev_val);
return prev_delta + r * (next_delta - prev_delta);
}
static unsigned int next_index (unsigned int i, unsigned int start, unsigned int end)
{ return (i >= end) ? start : (i + 1); }
};
struct TupleVariationData
{
bool sanitize (hb_sanitize_context_t *c) const
{
TRACE_SANITIZE (this);
// here check on min_size only, TupleVariationHeader and var data will be
// checked while accessing through iterator.
return_trace (c->check_struct (this));
}
unsigned get_size (unsigned axis_count) const
{
unsigned total_size = min_size;
unsigned count = tupleVarCount.get_count ();
const TupleVariationHeader *tuple_var_header = &(get_tuple_var_header());
for (unsigned i = 0; i < count; i++)
{
total_size += tuple_var_header->get_size (axis_count) + tuple_var_header->get_data_size ();
tuple_var_header = &tuple_var_header->get_next (axis_count);
}
return total_size;
}
const TupleVariationHeader &get_tuple_var_header (void) const
{ return StructAfter<TupleVariationHeader> (data); }
struct tuple_iterator_t;
struct tuple_variations_t
{
hb_vector_t<tuple_delta_t> tuple_vars;
private:
/* referenced point set->compiled point data map */
hb_hashmap_t<const hb_vector_t<bool>*, hb_bytes_t> point_data_map;
/* referenced point set-> count map, used in finding shared points */
hb_hashmap_t<const hb_vector_t<bool>*, unsigned> point_set_count_map;
/* empty for non-gvar tuples.
* shared_points_bytes is just a copy of some value in the point_data_map,
* which will be freed during map destruction. Save it for serialization, so
* no need to do find_shared_points () again */
hb_bytes_t shared_points_bytes;
/* total compiled byte size as TupleVariationData format, initialized to its
* min_size: 4 */
unsigned compiled_byte_size = 4;
public:
tuple_variations_t () = default;
tuple_variations_t (const tuple_variations_t&) = delete;
tuple_variations_t& operator=(const tuple_variations_t&) = delete;
tuple_variations_t (tuple_variations_t&&) = default;
tuple_variations_t& operator=(tuple_variations_t&&) = default;
~tuple_variations_t () { fini (); }
void fini ()
{
for (auto _ : point_data_map.values ())
_.fini ();
point_set_count_map.fini ();
tuple_vars.fini ();
}
explicit operator bool () const { return bool (tuple_vars); }
unsigned get_var_count () const
{
unsigned count = tuple_vars.length;
if (shared_points_bytes.length)
count |= TupleVarCount::SharedPointNumbers;
return count;
}
unsigned get_compiled_byte_size () const
{ return compiled_byte_size; }
bool create_from_tuple_var_data (tuple_iterator_t iterator,
unsigned tuple_var_count,
unsigned point_count,
bool is_gvar,
const hb_map_t *axes_old_index_tag_map,
const hb_vector_t<unsigned> &shared_indices,
const hb_array_t<const F2DOT14> shared_tuples)
{
do
{
const HBUINT8 *p = iterator.get_serialized_data ();
unsigned int length = iterator.current_tuple->get_data_size ();
if (unlikely (!iterator.var_data_bytes.check_range (p, length)))
{ fini (); return false; }
hb_hashmap_t<hb_tag_t, Triple> axis_tuples;
if (!iterator.current_tuple->unpack_axis_tuples (iterator.get_axis_count (), shared_tuples, axes_old_index_tag_map, axis_tuples)
|| axis_tuples.is_empty ())
{ fini (); return false; }
hb_vector_t<unsigned> private_indices;
bool has_private_points = iterator.current_tuple->has_private_points ();
const HBUINT8 *end = p + length;
if (has_private_points &&
!TupleVariationData::unpack_points (p, private_indices, end))
{ fini (); return false; }
const hb_vector_t<unsigned> &indices = has_private_points ? private_indices : shared_indices;
bool apply_to_all = (indices.length == 0);
unsigned num_deltas = apply_to_all ? point_count : indices.length;
hb_vector_t<int> deltas_x;
if (unlikely (!deltas_x.resize (num_deltas, false) ||
!TupleVariationData::unpack_deltas (p, deltas_x, end)))
{ fini (); return false; }
hb_vector_t<int> deltas_y;
if (is_gvar)
{
if (unlikely (!deltas_y.resize (num_deltas, false) ||
!TupleVariationData::unpack_deltas (p, deltas_y, end)))
{ fini (); return false; }
}
tuple_delta_t var;
var.axis_tuples = std::move (axis_tuples);
if (unlikely (!var.indices.resize (point_count) ||
!var.deltas_x.resize (point_count, false)))
{ fini (); return false; }
if (is_gvar && unlikely (!var.deltas_y.resize (point_count, false)))
{ fini (); return false; }
for (unsigned i = 0; i < num_deltas; i++)
{
unsigned idx = apply_to_all ? i : indices[i];
if (idx >= point_count) continue;
var.indices[idx] = true;
var.deltas_x[idx] = static_cast<float> (deltas_x[i]);
if (is_gvar)
var.deltas_y[idx] = static_cast<float> (deltas_y[i]);
}
tuple_vars.push (std::move (var));
} while (iterator.move_to_next ());
return true;
}
bool create_from_item_var_data (const VarData &var_data,
const hb_vector_t<hb_hashmap_t<hb_tag_t, Triple>>& regions,
const hb_map_t& axes_old_index_tag_map,
unsigned& item_count,
const hb_inc_bimap_t* inner_map = nullptr)
{
/* NULL offset, to keep original varidx valid, just return */
if (&var_data == &Null (VarData))
return true;
unsigned num_regions = var_data.get_region_index_count ();
if (!tuple_vars.alloc (num_regions)) return false;
item_count = inner_map ? inner_map->get_population () : var_data.get_item_count ();
if (!item_count) return true;
unsigned row_size = var_data.get_row_size ();
const HBUINT8 *delta_bytes = var_data.get_delta_bytes ();
for (unsigned r = 0; r < num_regions; r++)
{
/* In VarData, deltas are organized in rows, convert them into
* column(region) based tuples, resize deltas_x first */
tuple_delta_t tuple;
if (!tuple.deltas_x.resize (item_count, false) ||
!tuple.indices.resize (item_count, false))
return false;
for (unsigned i = 0; i < item_count; i++)
{
tuple.indices.arrayZ[i] = true;
tuple.deltas_x.arrayZ[i] = var_data.get_item_delta_fast (inner_map ? inner_map->backward (i) : i,
r, delta_bytes, row_size);
}
unsigned region_index = var_data.get_region_index (r);
if (region_index >= regions.length) return false;
tuple.axis_tuples = regions.arrayZ[region_index];
tuple_vars.push (std::move (tuple));
}
return !tuple_vars.in_error ();
}
private:
static int _cmp_axis_tag (const void *pa, const void *pb)
{
const hb_tag_t *a = (const hb_tag_t*) pa;
const hb_tag_t *b = (const hb_tag_t*) pb;
return (int)(*a) - (int)(*b);
}
bool change_tuple_variations_axis_limits (const hb_hashmap_t<hb_tag_t, Triple>& normalized_axes_location,
const hb_hashmap_t<hb_tag_t, TripleDistances>& axes_triple_distances)
{
/* sort axis_tag/axis_limits, make result deterministic */
hb_vector_t<hb_tag_t> axis_tags;
if (!axis_tags.alloc (normalized_axes_location.get_population ()))
return false;
for (auto t : normalized_axes_location.keys ())
axis_tags.push (t);
axis_tags.qsort (_cmp_axis_tag);
for (auto axis_tag : axis_tags)
{
Triple *axis_limit;
if (!normalized_axes_location.has (axis_tag, &axis_limit))
return false;
TripleDistances axis_triple_distances{1.f, 1.f};
if (axes_triple_distances.has (axis_tag))
axis_triple_distances = axes_triple_distances.get (axis_tag);
hb_vector_t<tuple_delta_t> new_vars;
for (const tuple_delta_t& var : tuple_vars)
{
hb_vector_t<tuple_delta_t> out = var.change_tuple_var_axis_limit (axis_tag, *axis_limit, axis_triple_distances);
if (!out) continue;
unsigned new_len = new_vars.length + out.length;
if (unlikely (!new_vars.alloc (new_len, false)))
{ fini (); return false;}
for (unsigned i = 0; i < out.length; i++)
new_vars.push (std::move (out[i]));
}
tuple_vars.fini ();
tuple_vars = std::move (new_vars);
}
return true;
}
/* merge tuple variations with overlapping tents */
void merge_tuple_variations ()
{
hb_vector_t<tuple_delta_t> new_vars;
hb_hashmap_t<const hb_hashmap_t<hb_tag_t, Triple>*, unsigned> m;
unsigned i = 0;
for (const tuple_delta_t& var : tuple_vars)
{
/* if all axes are pinned, drop the tuple variation */
if (var.axis_tuples.is_empty ()) continue;
unsigned *idx;
if (m.has (&(var.axis_tuples), &idx))
{
new_vars[*idx] += var;
}
else
{
new_vars.push (var);
m.set (&(var.axis_tuples), i);
i++;
}
}
tuple_vars.fini ();
tuple_vars = std::move (new_vars);
}
hb_bytes_t compile_point_set (const hb_vector_t<bool> &point_indices)
{
unsigned num_points = 0;
for (bool i : point_indices)
if (i) num_points++;
unsigned indices_length = point_indices.length;
/* If the points set consists of all points in the glyph, it's encoded with a
* single zero byte */
if (num_points == indices_length)
{
char *p = (char *) hb_calloc (1, sizeof (char));
if (unlikely (!p)) return hb_bytes_t ();
return hb_bytes_t (p, 1);
}
/* allocate enough memories: 2 bytes for count + 3 bytes for each point */
unsigned num_bytes = 2 + 3 *num_points;
char *p = (char *) hb_calloc (num_bytes, sizeof (char));
if (unlikely (!p)) return hb_bytes_t ();
unsigned pos = 0;
/* binary data starts with the total number of reference points */
if (num_points < 0x80)
p[pos++] = num_points;
else
{
p[pos++] = ((num_points >> 8) | 0x80);
p[pos++] = num_points & 0xFF;
}
const unsigned max_run_length = 0x7F;
unsigned i = 0;
unsigned last_value = 0;
unsigned num_encoded = 0;
while (i < indices_length && num_encoded < num_points)
{
unsigned run_length = 0;
unsigned header_pos = pos;
p[pos++] = 0;
bool use_byte_encoding = false;
bool new_run = true;
while (i < indices_length && num_encoded < num_points &&
run_length <= max_run_length)
{
// find out next referenced point index
while (i < indices_length && !point_indices[i])
i++;
if (i >= indices_length) break;
unsigned cur_value = i;
unsigned delta = cur_value - last_value;
if (new_run)
{
use_byte_encoding = (delta <= 0xFF);
new_run = false;
}
if (use_byte_encoding && delta > 0xFF)
break;
if (use_byte_encoding)
p[pos++] = delta;
else
{
p[pos++] = delta >> 8;
p[pos++] = delta & 0xFF;
}
i++;
last_value = cur_value;
run_length++;
num_encoded++;
}
if (use_byte_encoding)
p[header_pos] = run_length - 1;
else
p[header_pos] = (run_length - 1) | 0x80;
}
return hb_bytes_t (p, pos);
}
/* compile all point set and store byte data in a point_set->hb_bytes_t hashmap,
* also update point_set->count map, which will be used in finding shared
* point set*/
bool compile_all_point_sets ()
{
for (const auto& tuple: tuple_vars)
{
const hb_vector_t<bool>* points_set = &(tuple.indices);
if (point_data_map.has (points_set))
{
unsigned *count;
if (unlikely (!point_set_count_map.has (points_set, &count) ||
!point_set_count_map.set (points_set, (*count) + 1)))
return false;
continue;
}
hb_bytes_t compiled_data = compile_point_set (*points_set);
if (unlikely (compiled_data == hb_bytes_t ()))
return false;
if (!point_data_map.set (points_set, compiled_data) ||
!point_set_count_map.set (points_set, 1))
return false;
}
return true;
}
/* find shared points set which saves most bytes */
hb_bytes_t find_shared_points ()
{
unsigned max_saved_bytes = 0;
hb_bytes_t res{};
for (const auto& _ : point_data_map.iter ())
{
const hb_vector_t<bool>* points_set = _.first;
unsigned data_length = _.second.length;
unsigned *count;
if (unlikely (!point_set_count_map.has (points_set, &count) ||
*count <= 1))
return hb_bytes_t ();
unsigned saved_bytes = data_length * ((*count) -1);
if (saved_bytes > max_saved_bytes)
{
max_saved_bytes = saved_bytes;
res = _.second;
}
}
return res;
}
bool calc_inferred_deltas (contour_point_vector_t& contour_points)
{
for (tuple_delta_t& var : tuple_vars)
if (!var.calc_inferred_deltas (contour_points))
return false;
return true;
}
public:
bool instantiate (const hb_hashmap_t<hb_tag_t, Triple>& normalized_axes_location,
const hb_hashmap_t<hb_tag_t, TripleDistances>& axes_triple_distances,
contour_point_vector_t* contour_points = nullptr)
{
if (!tuple_vars) return true;
if (!change_tuple_variations_axis_limits (normalized_axes_location, axes_triple_distances))
return false;
/* compute inferred deltas only for gvar */
if (contour_points)
if (!calc_inferred_deltas (*contour_points))
return false;
merge_tuple_variations ();
return !tuple_vars.in_error ();
}
bool compile_bytes (const hb_map_t& axes_index_map,
const hb_map_t& axes_old_index_tag_map,
bool use_shared_points,
const hb_hashmap_t<const hb_vector_t<char>*, unsigned>* shared_tuples_idx_map = nullptr)
{
// compile points set and store data in hashmap
if (!compile_all_point_sets ())
return false;
if (use_shared_points)
{
shared_points_bytes = find_shared_points ();
compiled_byte_size += shared_points_bytes.length;
}
// compile delta and tuple var header for each tuple variation
for (auto& tuple: tuple_vars)
{
const hb_vector_t<bool>* points_set = &(tuple.indices);
hb_bytes_t *points_data;
if (unlikely (!point_data_map.has (points_set, &points_data)))
return false;
if (!tuple.compile_deltas ())
return false;
unsigned points_data_length = (*points_data != shared_points_bytes) ? points_data->length : 0;
if (!tuple.compile_tuple_var_header (axes_index_map, points_data_length, axes_old_index_tag_map,
shared_tuples_idx_map))
return false;
compiled_byte_size += tuple.compiled_tuple_header.length + points_data_length + tuple.compiled_deltas.length;
}
return true;
}
bool serialize_var_headers (hb_serialize_context_t *c, unsigned& total_header_len) const
{
TRACE_SERIALIZE (this);
for (const auto& tuple: tuple_vars)
{
tuple.compiled_tuple_header.as_array ().copy (c);
if (c->in_error ()) return_trace (false);
total_header_len += tuple.compiled_tuple_header.length;
}
return_trace (true);
}
bool serialize_var_data (hb_serialize_context_t *c, bool is_gvar) const
{
TRACE_SERIALIZE (this);
if (is_gvar)
shared_points_bytes.copy (c);
for (const auto& tuple: tuple_vars)
{
const hb_vector_t<bool>* points_set = &(tuple.indices);
hb_bytes_t *point_data;
if (!point_data_map.has (points_set, &point_data))
return_trace (false);
if (!is_gvar || *point_data != shared_points_bytes)
point_data->copy (c);
tuple.compiled_deltas.as_array ().copy (c);
if (c->in_error ()) return_trace (false);
}
/* padding for gvar */
if (is_gvar && (compiled_byte_size % 2))
{
HBUINT8 pad;
pad = 0;
if (!c->embed (pad)) return_trace (false);
}
return_trace (true);
}
};
struct tuple_iterator_t
{
unsigned get_axis_count () const { return axis_count; }
void init (hb_bytes_t var_data_bytes_, unsigned int axis_count_, const void *table_base_)
{
var_data_bytes = var_data_bytes_;
var_data = var_data_bytes_.as<TupleVariationData> ();
index = 0;
axis_count = axis_count_;
current_tuple = &var_data->get_tuple_var_header ();
data_offset = 0;
table_base = table_base_;
}
bool get_shared_indices (hb_vector_t<unsigned int> &shared_indices /* OUT */)
{
if (var_data->has_shared_point_numbers ())
{
const HBUINT8 *base = &(table_base+var_data->data);
const HBUINT8 *p = base;
if (!unpack_points (p, shared_indices, (const HBUINT8 *) (var_data_bytes.arrayZ + var_data_bytes.length))) return false;
data_offset = p - base;
}
return true;
}
bool is_valid () const
{
return (index < var_data->tupleVarCount.get_count ()) &&
var_data_bytes.check_range (current_tuple, TupleVariationHeader::min_size) &&
var_data_bytes.check_range (current_tuple, hb_max (current_tuple->get_data_size (),
current_tuple->get_size (axis_count)));
}
bool move_to_next ()
{
data_offset += current_tuple->get_data_size ();
current_tuple = ¤t_tuple->get_next (axis_count);
index++;
return is_valid ();
}
const HBUINT8 *get_serialized_data () const
{ return &(table_base+var_data->data) + data_offset; }
private:
const TupleVariationData *var_data;
unsigned int index;
unsigned int axis_count;
unsigned int data_offset;
const void *table_base;
public:
hb_bytes_t var_data_bytes;
const TupleVariationHeader *current_tuple;
};
static bool get_tuple_iterator (hb_bytes_t var_data_bytes, unsigned axis_count,
const void *table_base,
hb_vector_t<unsigned int> &shared_indices /* OUT */,
tuple_iterator_t *iterator /* OUT */)
{
iterator->init (var_data_bytes, axis_count, table_base);
if (!iterator->get_shared_indices (shared_indices))
return false;
return iterator->is_valid ();
}
bool has_shared_point_numbers () const { return tupleVarCount.has_shared_point_numbers (); }
static bool unpack_points (const HBUINT8 *&p /* IN/OUT */,
hb_vector_t<unsigned int> &points /* OUT */,
const HBUINT8 *end)
{
enum packed_point_flag_t
{
POINTS_ARE_WORDS = 0x80,
POINT_RUN_COUNT_MASK = 0x7F
};
if (unlikely (p + 1 > end)) return false;
unsigned count = *p++;
if (count & POINTS_ARE_WORDS)
{
if (unlikely (p + 1 > end)) return false;
count = ((count & POINT_RUN_COUNT_MASK) << 8) | *p++;
}
if (unlikely (!points.resize (count, false))) return false;
unsigned n = 0;
unsigned i = 0;
while (i < count)
{
if (unlikely (p + 1 > end)) return false;
unsigned control = *p++;
unsigned run_count = (control & POINT_RUN_COUNT_MASK) + 1;
unsigned stop = i + run_count;
if (unlikely (stop > count)) return false;
if (control & POINTS_ARE_WORDS)
{
if (unlikely (p + run_count * HBUINT16::static_size > end)) return false;
for (; i < stop; i++)
{
n += *(const HBUINT16 *)p;
points.arrayZ[i] = n;
p += HBUINT16::static_size;
}
}
else
{
if (unlikely (p + run_count > end)) return false;
for (; i < stop; i++)
{
n += *p++;
points.arrayZ[i] = n;
}
}
}
return true;
}
static bool unpack_deltas (const HBUINT8 *&p /* IN/OUT */,
hb_vector_t<int> &deltas /* IN/OUT */,
const HBUINT8 *end)
{
unsigned i = 0;
unsigned count = deltas.length;
while (i < count)
{
if (unlikely (p + 1 > end)) return false;
unsigned control = *p++;
unsigned run_count = (control & DELTA_RUN_COUNT_MASK) + 1;
unsigned stop = i + run_count;
if (unlikely (stop > count)) return false;
if (control & DELTAS_ARE_ZERO)
{
for (; i < stop; i++)
deltas.arrayZ[i] = 0;
}
else if (control & DELTAS_ARE_WORDS)
{
if (unlikely (p + run_count * HBUINT16::static_size > end)) return false;
for (; i < stop; i++)
{
deltas.arrayZ[i] = * (const HBINT16 *) p;
p += HBUINT16::static_size;
}
}
else
{
if (unlikely (p + run_count > end)) return false;
for (; i < stop; i++)
{
deltas.arrayZ[i] = * (const HBINT8 *) p++;
}
}
}
return true;
}
bool has_data () const { return tupleVarCount; }
bool decompile_tuple_variations (unsigned point_count,
bool is_gvar,
tuple_iterator_t iterator,
const hb_map_t *axes_old_index_tag_map,
const hb_vector_t<unsigned> &shared_indices,
const hb_array_t<const F2DOT14> shared_tuples,
tuple_variations_t& tuple_variations /* OUT */) const
{
return tuple_variations.create_from_tuple_var_data (iterator, tupleVarCount,
point_count, is_gvar,
axes_old_index_tag_map,
shared_indices,
shared_tuples);
}
bool serialize (hb_serialize_context_t *c,
bool is_gvar,
const tuple_variations_t& tuple_variations) const
{
TRACE_SERIALIZE (this);
/* empty tuple variations, just return and skip serialization. */
if (!tuple_variations) return_trace (true);
auto *out = c->start_embed (this);
if (unlikely (!c->extend_min (out))) return_trace (false);
if (!c->check_assign (out->tupleVarCount, tuple_variations.get_var_count (),
HB_SERIALIZE_ERROR_INT_OVERFLOW)) return_trace (false);
unsigned total_header_len = 0;
if (!tuple_variations.serialize_var_headers (c, total_header_len))
return_trace (false);
unsigned data_offset = min_size + total_header_len;
if (!is_gvar) data_offset += 4;
if (!c->check_assign (out->data, data_offset, HB_SERIALIZE_ERROR_INT_OVERFLOW)) return_trace (false);
return tuple_variations.serialize_var_data (c, is_gvar);
}
protected:
struct TupleVarCount : HBUINT16
{
friend struct tuple_variations_t;
bool has_shared_point_numbers () const { return ((*this) & SharedPointNumbers); }
unsigned int get_count () const { return (*this) & CountMask; }
TupleVarCount& operator = (uint16_t i) { HBUINT16::operator= (i); return *this; }
explicit operator bool () const { return get_count (); }
protected:
enum Flags
{
SharedPointNumbers= 0x8000u,
CountMask = 0x0FFFu
};
public:
DEFINE_SIZE_STATIC (2);
};
TupleVarCount tupleVarCount; /* A packed field. The high 4 bits are flags, and the
* low 12 bits are the number of tuple variation tables
* for this glyph. The number of tuple variation tables
* can be any number between 1 and 4095. */
Offset16To<HBUINT8>
data; /* Offset from the start of the base table
* to the serialized data. */
/* TupleVariationHeader tupleVariationHeaders[] *//* Array of tuple variation headers. */
public:
DEFINE_SIZE_MIN (4);
};
using tuple_variations_t = TupleVariationData::tuple_variations_t;
struct item_variations_t
{
using region_t = const hb_hashmap_t<hb_tag_t, Triple>*;
private:
/* each subtable is decompiled into a tuple_variations_t, in which all tuples
* have the same num of deltas (rows) */
hb_vector_t<tuple_variations_t> vars;
/* num of retained rows for each subtable, there're 2 cases when var_data is empty:
* 1. retained item_count is zero
* 2. regions is empty and item_count is non-zero.
* when converting to tuples, both will be dropped because the tuple is empty,
* however, we need to retain 2. as all-zero rows to keep original varidx
* valid, so we need a way to remember the num of rows for each subtable */
hb_vector_t<unsigned> var_data_num_rows;
/* original region list, decompiled from item varstore, used when rebuilding
* region list after instantiation */
hb_vector_t<hb_hashmap_t<hb_tag_t, Triple>> orig_region_list;
/* region list: vector of Regions, maintain the original order for the regions
* that existed before instantiate (), append the new regions at the end.
* Regions are stored in each tuple already, save pointers only.
* When converting back to item varstore, unused regions will be pruned */
hb_vector_t<region_t> region_list;
/* region -> idx map after instantiation and pruning unused regions */
hb_hashmap_t<region_t, unsigned> region_map;
/* all delta rows after instantiation */
hb_vector_t<hb_vector_t<int>> delta_rows;
/* final optimized vector of encoding objects used to assemble the varstore */
hb_vector_t<delta_row_encoding_t> encodings;
/* old varidxes -> new var_idxes map */
hb_map_t varidx_map;
/* has long words */
bool has_long = false;
public:
bool has_long_word () const
{ return has_long; }
const hb_vector_t<region_t>& get_region_list () const
{ return region_list; }
const hb_vector_t<delta_row_encoding_t>& get_vardata_encodings () const
{ return encodings; }
const hb_map_t& get_varidx_map () const
{ return varidx_map; }
bool instantiate (const VariationStore& varStore,
const hb_subset_plan_t *plan,
bool optimize=true,
bool use_no_variation_idx=true,
const hb_array_t <const hb_inc_bimap_t> inner_maps = hb_array_t<const hb_inc_bimap_t> ())
{
if (!create_from_item_varstore (varStore, plan->axes_old_index_tag_map, inner_maps))
return false;
if (!instantiate_tuple_vars (plan->axes_location, plan->axes_triple_distances))
return false;
return as_item_varstore (optimize, use_no_variation_idx);
}
/* keep below APIs public only for unit test: test-item-varstore */
bool create_from_item_varstore (const VariationStore& varStore,
const hb_map_t& axes_old_index_tag_map,
const hb_array_t <const hb_inc_bimap_t> inner_maps = hb_array_t<const hb_inc_bimap_t> ())
{
const VarRegionList& regionList = varStore.get_region_list ();
if (!regionList.get_var_regions (axes_old_index_tag_map, orig_region_list))
return false;
unsigned num_var_data = varStore.get_sub_table_count ();
if (inner_maps && inner_maps.length != num_var_data) return false;
if (!vars.alloc (num_var_data) ||
!var_data_num_rows.alloc (num_var_data)) return false;
for (unsigned i = 0; i < num_var_data; i++)
{
if (inner_maps && !inner_maps.arrayZ[i].get_population ())
continue;
tuple_variations_t var_data_tuples;
unsigned item_count = 0;
if (!var_data_tuples.create_from_item_var_data (varStore.get_sub_table (i),
orig_region_list,
axes_old_index_tag_map,
item_count,
inner_maps ? &(inner_maps.arrayZ[i]) : nullptr))
return false;
var_data_num_rows.push (item_count);
vars.push (std::move (var_data_tuples));
}
return !vars.in_error () && !var_data_num_rows.in_error () && vars.length == var_data_num_rows.length;
}
bool instantiate_tuple_vars (const hb_hashmap_t<hb_tag_t, Triple>& normalized_axes_location,
const hb_hashmap_t<hb_tag_t, TripleDistances>& axes_triple_distances)
{
for (tuple_variations_t& tuple_vars : vars)
if (!tuple_vars.instantiate (normalized_axes_location, axes_triple_distances))
return false;
if (!build_region_list ()) return false;
return true;
}
bool build_region_list ()
{
/* scan all tuples and collect all unique regions, prune unused regions */
hb_hashmap_t<region_t, unsigned> all_regions;
hb_hashmap_t<region_t, unsigned> used_regions;
/* use a vector when inserting new regions, make result deterministic */
hb_vector_t<region_t> all_unique_regions;
for (const tuple_variations_t& sub_table : vars)
{
for (const tuple_delta_t& tuple : sub_table.tuple_vars)
{
region_t r = &(tuple.axis_tuples);
if (!used_regions.has (r))
{
bool all_zeros = true;
for (float d : tuple.deltas_x)
{
int delta = (int) roundf (d);
if (delta != 0)
{
all_zeros = false;
break;
}
}
if (!all_zeros)
{
if (!used_regions.set (r, 1))
return false;
}
}
if (all_regions.has (r))
continue;
if (!all_regions.set (r, 1))
return false;
all_unique_regions.push (r);
}
}
if (!all_regions || !all_unique_regions) return false;
if (!region_list.alloc (all_regions.get_population ()))
return false;
unsigned idx = 0;
/* append the original regions that pre-existed */
for (const auto& r : orig_region_list)
{
if (!all_regions.has (&r) || !used_regions.has (&r))
continue;
region_list.push (&r);
if (!region_map.set (&r, idx))
return false;
all_regions.del (&r);
idx++;
}
/* append the new regions at the end */
for (const auto& r: all_unique_regions)
{
if (!all_regions.has (r) || !used_regions.has (r))
continue;
region_list.push (r);
if (!region_map.set (r, idx))
return false;
all_regions.del (r);
idx++;
}
return (!region_list.in_error ()) && (!region_map.in_error ());
}
/* main algorithm ported from fonttools VarStore_optimize() method, optimize
* varstore by default */
struct combined_gain_idx_tuple_t
{
int gain;
unsigned idx_1;
unsigned idx_2;
combined_gain_idx_tuple_t () = default;
combined_gain_idx_tuple_t (int gain_, unsigned i, unsigned j)
:gain (gain_), idx_1 (i), idx_2 (j) {}
bool operator < (const combined_gain_idx_tuple_t& o)
{
if (gain != o.gain)
return gain < o.gain;
if (idx_1 != o.idx_1)
return idx_1 < o.idx_1;
return idx_2 < o.idx_2;
}
bool operator <= (const combined_gain_idx_tuple_t& o)
{
if (*this < o) return true;
return gain == o.gain && idx_1 == o.idx_1 && idx_2 == o.idx_2;
}
};
bool as_item_varstore (bool optimize=true, bool use_no_variation_idx=true)
{
if (!region_list) return false;
unsigned num_cols = region_list.length;
/* pre-alloc a 2D vector for all sub_table's VarData rows */
unsigned total_rows = 0;
for (unsigned major = 0; major < var_data_num_rows.length; major++)
total_rows += var_data_num_rows[major];
if (!delta_rows.resize (total_rows)) return false;
/* init all rows to [0]*num_cols */
for (unsigned i = 0; i < total_rows; i++)
if (!(delta_rows[i].resize (num_cols))) return false;
/* old VarIdxes -> full encoding_row mapping */
hb_hashmap_t<unsigned, const hb_vector_t<int>*> front_mapping;
unsigned start_row = 0;
hb_vector_t<delta_row_encoding_t> encoding_objs;
hb_hashmap_t<hb_vector_t<uint8_t>, unsigned> chars_idx_map;
/* delta_rows map, used for filtering out duplicate rows */
hb_hashmap_t<const hb_vector_t<int>*, unsigned> delta_rows_map;
for (unsigned major = 0; major < vars.length; major++)
{
/* deltas are stored in tuples(column based), convert them back into items
* (row based) delta */
const tuple_variations_t& tuples = vars[major];
unsigned num_rows = var_data_num_rows[major];
for (const tuple_delta_t& tuple: tuples.tuple_vars)
{
if (tuple.deltas_x.length != num_rows)
return false;
/* skip unused regions */
unsigned *col_idx;
if (!region_map.has (&(tuple.axis_tuples), &col_idx))
continue;
for (unsigned i = 0; i < num_rows; i++)
{
int rounded_delta = roundf (tuple.deltas_x[i]);
delta_rows[start_row + i][*col_idx] += rounded_delta;
if ((!has_long) && (rounded_delta < -65536 || rounded_delta > 65535))
has_long = true;
}
}
if (!optimize)
{
/* assemble a delta_row_encoding_t for this subtable, skip optimization so
* chars is not initialized, we only need delta rows for serialization */
delta_row_encoding_t obj;
for (unsigned r = start_row; r < start_row + num_rows; r++)
obj.add_row (&(delta_rows.arrayZ[r]));
encodings.push (std::move (obj));
start_row += num_rows;
continue;
}
for (unsigned minor = 0; minor < num_rows; minor++)
{
const hb_vector_t<int>& row = delta_rows[start_row + minor];
if (use_no_variation_idx)
{
bool all_zeros = true;
for (int delta : row)
{
if (delta != 0)
{
all_zeros = false;
break;
}
}
if (all_zeros)
continue;
}
if (!front_mapping.set ((major<<16) + minor, &row))
return false;
hb_vector_t<uint8_t> chars = delta_row_encoding_t::get_row_chars (row);
if (!chars) return false;
if (delta_rows_map.has (&row))
continue;
delta_rows_map.set (&row, 1);
unsigned *obj_idx;
if (chars_idx_map.has (chars, &obj_idx))
{
delta_row_encoding_t& obj = encoding_objs[*obj_idx];
if (!obj.add_row (&row))
return false;
}
else
{
if (!chars_idx_map.set (chars, encoding_objs.length))
return false;
delta_row_encoding_t obj (std::move (chars), &row);
encoding_objs.push (std::move (obj));
}
}
start_row += num_rows;
}
/* return directly if no optimization, maintain original VariationIndex so
* varidx_map would be empty */
if (!optimize) return !encodings.in_error ();
/* sort encoding_objs */
encoding_objs.qsort ();
/* main algorithm: repeatedly pick 2 best encodings to combine, and combine
* them */
hb_priority_queue_t<combined_gain_idx_tuple_t> queue;
unsigned num_todos = encoding_objs.length;
for (unsigned i = 0; i < num_todos; i++)
{
for (unsigned j = i + 1; j < num_todos; j++)
{
int combining_gain = encoding_objs.arrayZ[i].gain_from_merging (encoding_objs.arrayZ[j]);
if (combining_gain > 0)
queue.insert (combined_gain_idx_tuple_t (-combining_gain, i, j), 0);
}
}
hb_set_t removed_todo_idxes;
while (queue)
{
auto t = queue.pop_minimum ().first;
unsigned i = t.idx_1;
unsigned j = t.idx_2;
if (removed_todo_idxes.has (i) || removed_todo_idxes.has (j))
continue;
delta_row_encoding_t& encoding = encoding_objs.arrayZ[i];
delta_row_encoding_t& other_encoding = encoding_objs.arrayZ[j];
removed_todo_idxes.add (i);
removed_todo_idxes.add (j);
hb_vector_t<uint8_t> combined_chars;
if (!combined_chars.alloc (encoding.chars.length))
return false;
for (unsigned idx = 0; idx < encoding.chars.length; idx++)
{
uint8_t v = hb_max (encoding.chars.arrayZ[idx], other_encoding.chars.arrayZ[idx]);
combined_chars.push (v);
}
delta_row_encoding_t combined_encoding_obj (std::move (combined_chars));
for (const auto& row : hb_concat (encoding.items, other_encoding.items))
combined_encoding_obj.add_row (row);
for (unsigned idx = 0; idx < encoding_objs.length; idx++)
{
if (removed_todo_idxes.has (idx)) continue;
const delta_row_encoding_t& obj = encoding_objs.arrayZ[idx];
if (obj.chars == combined_chars)
{
for (const auto& row : obj.items)
combined_encoding_obj.add_row (row);
removed_todo_idxes.add (idx);
continue;
}
int combined_gain = combined_encoding_obj.gain_from_merging (obj);
if (combined_gain > 0)
queue.insert (combined_gain_idx_tuple_t (-combined_gain, idx, encoding_objs.length), 0);
}
encoding_objs.push (std::move (combined_encoding_obj));
}
int num_final_encodings = (int) encoding_objs.length - (int) removed_todo_idxes.get_population ();
if (num_final_encodings <= 0) return false;
if (!encodings.alloc (num_final_encodings)) return false;
for (unsigned i = 0; i < encoding_objs.length; i++)
{
if (removed_todo_idxes.has (i)) continue;
encodings.push (std::move (encoding_objs.arrayZ[i]));
}
/* sort again based on width, make result deterministic */
encodings.qsort (delta_row_encoding_t::cmp_width);
return compile_varidx_map (front_mapping);
}
private:
/* compile varidx_map for one VarData subtable (index specified by major) */
bool compile_varidx_map (const hb_hashmap_t<unsigned, const hb_vector_t<int>*>& front_mapping)
{
/* full encoding_row -> new VarIdxes mapping */
hb_hashmap_t<const hb_vector_t<int>*, unsigned> back_mapping;
for (unsigned major = 0; major < encodings.length; major++)
{
delta_row_encoding_t& encoding = encodings[major];
/* just sanity check, this shouldn't happen */
if (encoding.is_empty ())
return false;
unsigned num_rows = encoding.items.length;
/* sort rows, make result deterministic */
encoding.items.qsort (_cmp_row);
/* compile old to new var_idxes mapping */
for (unsigned minor = 0; minor < num_rows; minor++)
{
unsigned new_varidx = (major << 16) + minor;
back_mapping.set (encoding.items.arrayZ[minor], new_varidx);
}
}
for (auto _ : front_mapping.iter ())
{
unsigned old_varidx = _.first;
unsigned *new_varidx;
if (back_mapping.has (_.second, &new_varidx))
varidx_map.set (old_varidx, *new_varidx);
else
varidx_map.set (old_varidx, HB_OT_LAYOUT_NO_VARIATIONS_INDEX);
}
return !varidx_map.in_error ();
}
static int _cmp_row (const void *pa, const void *pb)
{
/* compare pointers of vectors(const hb_vector_t<int>*) that represent a row */
const hb_vector_t<int>** a = (const hb_vector_t<int>**) pa;
const hb_vector_t<int>** b = (const hb_vector_t<int>**) pb;
for (unsigned i = 0; i < (*b)->length; i++)
{
int va = (*a)->arrayZ[i];
int vb = (*b)->arrayZ[i];
if (va != vb)
return va < vb ? -1 : 1;
}
return 0;
}
};
} /* namespace OT */
#endif /* HB_OT_VAR_COMMON_HH */