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+/*
+ * 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 = &current_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 */