2249 lines
72 KiB
C++
2249 lines
72 KiB
C++
/*
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* Copyright © 2021 Google, Inc.
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*
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* This is part of HarfBuzz, a text shaping library.
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*
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* Permission is hereby granted, without written agreement and without
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* license or royalty fees, to use, copy, modify, and distribute this
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* software and its documentation for any purpose, provided that the
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* above copyright notice and the following two paragraphs appear in
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* all copies of this software.
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*
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* IN NO EVENT SHALL THE COPYRIGHT HOLDER BE LIABLE TO ANY PARTY FOR
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* DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES
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* ARISING OUT OF THE USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN
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* IF THE COPYRIGHT HOLDER HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH
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* DAMAGE.
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*
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* THE COPYRIGHT HOLDER SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING,
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* BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND
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* FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS
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* ON AN "AS IS" BASIS, AND THE COPYRIGHT HOLDER HAS NO OBLIGATION TO
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* PROVIDE MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
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*
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*/
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#ifndef HB_OT_VAR_COMMON_HH
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#define HB_OT_VAR_COMMON_HH
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#include "hb-ot-layout-common.hh"
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#include "hb-priority-queue.hh"
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namespace OT {
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template <typename MapCountT>
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struct DeltaSetIndexMapFormat01
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{
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friend struct DeltaSetIndexMap;
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unsigned get_size () const
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{ return min_size + mapCount * get_width (); }
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private:
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DeltaSetIndexMapFormat01* copy (hb_serialize_context_t *c) const
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{
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TRACE_SERIALIZE (this);
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return_trace (c->embed (this));
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}
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template <typename T>
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bool serialize (hb_serialize_context_t *c, const T &plan)
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{
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unsigned int width = plan.get_width ();
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unsigned int inner_bit_count = plan.get_inner_bit_count ();
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const hb_array_t<const uint32_t> output_map = plan.get_output_map ();
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TRACE_SERIALIZE (this);
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if (unlikely (output_map.length && ((((inner_bit_count-1)&~0xF)!=0) || (((width-1)&~0x3)!=0))))
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return_trace (false);
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if (unlikely (!c->extend_min (this))) return_trace (false);
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entryFormat = ((width-1)<<4)|(inner_bit_count-1);
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mapCount = output_map.length;
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HBUINT8 *p = c->allocate_size<HBUINT8> (width * output_map.length);
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if (unlikely (!p)) return_trace (false);
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for (unsigned int i = 0; i < output_map.length; i++)
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{
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unsigned int v = output_map.arrayZ[i];
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if (v)
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{
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unsigned int outer = v >> 16;
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unsigned int inner = v & 0xFFFF;
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unsigned int u = (outer << inner_bit_count) | inner;
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for (unsigned int w = width; w > 0;)
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{
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p[--w] = u;
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u >>= 8;
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}
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}
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p += width;
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}
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return_trace (true);
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}
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uint32_t map (unsigned int v) const /* Returns 16.16 outer.inner. */
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{
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/* If count is zero, pass value unchanged. This takes
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* care of direct mapping for advance map. */
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if (!mapCount)
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return v;
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if (v >= mapCount)
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v = mapCount - 1;
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unsigned int u = 0;
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{ /* Fetch it. */
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unsigned int w = get_width ();
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const HBUINT8 *p = mapDataZ.arrayZ + w * v;
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for (; w; w--)
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u = (u << 8) + *p++;
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}
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{ /* Repack it. */
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unsigned int n = get_inner_bit_count ();
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unsigned int outer = u >> n;
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unsigned int inner = u & ((1 << n) - 1);
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u = (outer<<16) | inner;
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}
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return u;
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}
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unsigned get_map_count () const { return mapCount; }
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unsigned get_width () const { return ((entryFormat >> 4) & 3) + 1; }
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unsigned get_inner_bit_count () const { return (entryFormat & 0xF) + 1; }
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bool sanitize (hb_sanitize_context_t *c) const
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{
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TRACE_SANITIZE (this);
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return_trace (c->check_struct (this) &&
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hb_barrier () &&
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c->check_range (mapDataZ.arrayZ,
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mapCount,
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get_width ()));
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}
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protected:
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HBUINT8 format; /* Format identifier--format = 0 */
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HBUINT8 entryFormat; /* A packed field that describes the compressed
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* representation of delta-set indices. */
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MapCountT mapCount; /* The number of mapping entries. */
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UnsizedArrayOf<HBUINT8>
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mapDataZ; /* The delta-set index mapping data. */
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public:
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DEFINE_SIZE_ARRAY (2+MapCountT::static_size, mapDataZ);
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};
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struct DeltaSetIndexMap
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{
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template <typename T>
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bool serialize (hb_serialize_context_t *c, const T &plan)
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{
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TRACE_SERIALIZE (this);
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unsigned length = plan.get_output_map ().length;
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u.format = length <= 0xFFFF ? 0 : 1;
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switch (u.format) {
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case 0: return_trace (u.format0.serialize (c, plan));
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case 1: return_trace (u.format1.serialize (c, plan));
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default:return_trace (false);
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}
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}
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uint32_t map (unsigned v) const
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{
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switch (u.format) {
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case 0: return (u.format0.map (v));
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case 1: return (u.format1.map (v));
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default:return v;
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}
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}
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unsigned get_map_count () const
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{
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switch (u.format) {
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case 0: return u.format0.get_map_count ();
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case 1: return u.format1.get_map_count ();
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default:return 0;
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}
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}
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unsigned get_width () const
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{
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switch (u.format) {
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case 0: return u.format0.get_width ();
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case 1: return u.format1.get_width ();
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default:return 0;
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}
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}
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unsigned get_inner_bit_count () const
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{
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switch (u.format) {
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case 0: return u.format0.get_inner_bit_count ();
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case 1: return u.format1.get_inner_bit_count ();
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default:return 0;
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}
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}
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bool sanitize (hb_sanitize_context_t *c) const
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{
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TRACE_SANITIZE (this);
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if (!u.format.sanitize (c)) return_trace (false);
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hb_barrier ();
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switch (u.format) {
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case 0: return_trace (u.format0.sanitize (c));
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case 1: return_trace (u.format1.sanitize (c));
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default:return_trace (true);
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}
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}
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DeltaSetIndexMap* copy (hb_serialize_context_t *c) const
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{
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TRACE_SERIALIZE (this);
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switch (u.format) {
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case 0: return_trace (reinterpret_cast<DeltaSetIndexMap *> (u.format0.copy (c)));
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case 1: return_trace (reinterpret_cast<DeltaSetIndexMap *> (u.format1.copy (c)));
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default:return_trace (nullptr);
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}
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}
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protected:
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union {
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HBUINT8 format; /* Format identifier */
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DeltaSetIndexMapFormat01<HBUINT16> format0;
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DeltaSetIndexMapFormat01<HBUINT32> format1;
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} u;
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public:
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DEFINE_SIZE_UNION (1, format);
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};
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struct VarStoreInstancer
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{
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VarStoreInstancer (const VariationStore *varStore,
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const DeltaSetIndexMap *varIdxMap,
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hb_array_t<int> coords) :
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varStore (varStore), varIdxMap (varIdxMap), coords (coords) {}
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operator bool () const { return varStore && bool (coords); }
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/* according to the spec, if colr table has varStore but does not have
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* varIdxMap, then an implicit identity mapping is used */
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float operator() (uint32_t varIdx, unsigned short offset = 0) const
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{ return coords ? varStore->get_delta (varIdxMap ? varIdxMap->map (VarIdx::add (varIdx, offset)) : varIdx + offset, coords) : 0; }
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const VariationStore *varStore;
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const DeltaSetIndexMap *varIdxMap;
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hb_array_t<int> coords;
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};
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/* https://docs.microsoft.com/en-us/typography/opentype/spec/otvarcommonformats#tuplevariationheader */
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struct TupleVariationHeader
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{
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friend struct tuple_delta_t;
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unsigned get_size (unsigned axis_count) const
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{ return min_size + get_all_tuples (axis_count).get_size (); }
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unsigned get_data_size () const { return varDataSize; }
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const TupleVariationHeader &get_next (unsigned axis_count) const
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{ return StructAtOffset<TupleVariationHeader> (this, get_size (axis_count)); }
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bool unpack_axis_tuples (unsigned axis_count,
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const hb_array_t<const F2DOT14> shared_tuples,
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const hb_map_t *axes_old_index_tag_map,
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hb_hashmap_t<hb_tag_t, Triple>& axis_tuples /* OUT */) const
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{
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const F2DOT14 *peak_tuple = nullptr;
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if (has_peak ())
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peak_tuple = get_peak_tuple (axis_count).arrayZ;
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else
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{
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unsigned int index = get_index ();
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if (unlikely ((index + 1) * axis_count > shared_tuples.length))
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return false;
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peak_tuple = shared_tuples.sub_array (axis_count * index, axis_count).arrayZ;
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}
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const F2DOT14 *start_tuple = nullptr;
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const F2DOT14 *end_tuple = nullptr;
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bool has_interm = has_intermediate ();
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if (has_interm)
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{
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start_tuple = get_start_tuple (axis_count).arrayZ;
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end_tuple = get_end_tuple (axis_count).arrayZ;
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}
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for (unsigned i = 0; i < axis_count; i++)
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{
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float peak = peak_tuple[i].to_float ();
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if (peak == 0.f) continue;
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hb_tag_t *axis_tag;
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if (!axes_old_index_tag_map->has (i, &axis_tag))
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return false;
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float start, end;
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if (has_interm)
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{
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start = start_tuple[i].to_float ();
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end = end_tuple[i].to_float ();
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}
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else
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{
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start = hb_min (peak, 0.f);
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end = hb_max (peak, 0.f);
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}
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axis_tuples.set (*axis_tag, Triple (start, peak, end));
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}
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return true;
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}
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float calculate_scalar (hb_array_t<int> coords, unsigned int coord_count,
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const hb_array_t<const F2DOT14> shared_tuples,
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const hb_vector_t<hb_pair_t<int,int>> *shared_tuple_active_idx = nullptr) const
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{
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const F2DOT14 *peak_tuple;
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unsigned start_idx = 0;
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unsigned end_idx = coord_count;
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unsigned step = 1;
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if (has_peak ())
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peak_tuple = get_peak_tuple (coord_count).arrayZ;
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else
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{
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unsigned int index = get_index ();
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if (unlikely ((index + 1) * coord_count > shared_tuples.length))
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return 0.f;
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peak_tuple = shared_tuples.sub_array (coord_count * index, coord_count).arrayZ;
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if (shared_tuple_active_idx)
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{
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if (unlikely (index >= shared_tuple_active_idx->length))
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return 0.f;
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auto _ = (*shared_tuple_active_idx).arrayZ[index];
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if (_.second != -1)
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{
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start_idx = _.first;
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end_idx = _.second + 1;
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step = _.second - _.first;
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}
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else if (_.first != -1)
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{
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start_idx = _.first;
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end_idx = start_idx + 1;
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}
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}
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}
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const F2DOT14 *start_tuple = nullptr;
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const F2DOT14 *end_tuple = nullptr;
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bool has_interm = has_intermediate ();
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if (has_interm)
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{
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start_tuple = get_start_tuple (coord_count).arrayZ;
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end_tuple = get_end_tuple (coord_count).arrayZ;
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}
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float scalar = 1.f;
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for (unsigned int i = start_idx; i < end_idx; i += step)
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{
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int peak = peak_tuple[i].to_int ();
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if (!peak) continue;
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int v = coords[i];
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if (v == peak) continue;
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if (has_interm)
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{
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int start = start_tuple[i].to_int ();
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int end = end_tuple[i].to_int ();
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if (unlikely (start > peak || peak > end ||
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(start < 0 && end > 0 && peak))) continue;
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if (v < start || v > end) return 0.f;
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if (v < peak)
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{ if (peak != start) scalar *= (float) (v - start) / (peak - start); }
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else
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{ if (peak != end) scalar *= (float) (end - v) / (end - peak); }
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}
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else if (!v || v < hb_min (0, peak) || v > hb_max (0, peak)) return 0.f;
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else
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scalar *= (float) v / peak;
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}
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return scalar;
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}
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bool has_peak () const { return tupleIndex & TuppleIndex::EmbeddedPeakTuple; }
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bool has_intermediate () const { return tupleIndex & TuppleIndex::IntermediateRegion; }
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bool has_private_points () const { return tupleIndex & TuppleIndex::PrivatePointNumbers; }
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unsigned get_index () const { return tupleIndex & TuppleIndex::TupleIndexMask; }
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protected:
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struct TuppleIndex : HBUINT16
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{
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enum Flags {
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EmbeddedPeakTuple = 0x8000u,
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IntermediateRegion = 0x4000u,
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PrivatePointNumbers = 0x2000u,
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TupleIndexMask = 0x0FFFu
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};
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TuppleIndex& operator = (uint16_t i) { HBUINT16::operator= (i); return *this; }
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DEFINE_SIZE_STATIC (2);
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};
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hb_array_t<const F2DOT14> get_all_tuples (unsigned axis_count) const
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{ return StructAfter<UnsizedArrayOf<F2DOT14>> (tupleIndex).as_array ((has_peak () + has_intermediate () * 2) * axis_count); }
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hb_array_t<const F2DOT14> get_peak_tuple (unsigned axis_count) const
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{ return get_all_tuples (axis_count).sub_array (0, axis_count); }
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hb_array_t<const F2DOT14> get_start_tuple (unsigned axis_count) const
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{ return get_all_tuples (axis_count).sub_array (has_peak () * axis_count, axis_count); }
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hb_array_t<const F2DOT14> get_end_tuple (unsigned axis_count) const
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{ return get_all_tuples (axis_count).sub_array (has_peak () * axis_count + axis_count, axis_count); }
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HBUINT16 varDataSize; /* The size in bytes of the serialized
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* data for this tuple variation table. */
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TuppleIndex tupleIndex; /* A packed field. The high 4 bits are flags (see below).
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The low 12 bits are an index into a shared tuple
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records array. */
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/* UnsizedArrayOf<F2DOT14> peakTuple - optional */
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/* Peak tuple record for this tuple variation table — optional,
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* determined by flags in the tupleIndex value.
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*
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* Note that this must always be included in the 'cvar' table. */
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/* UnsizedArrayOf<F2DOT14> intermediateStartTuple - optional */
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/* Intermediate start tuple record for this tuple variation table — optional,
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determined by flags in the tupleIndex value. */
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/* UnsizedArrayOf<F2DOT14> intermediateEndTuple - optional */
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/* Intermediate end tuple record for this tuple variation table — optional,
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* determined by flags in the tupleIndex value. */
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public:
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DEFINE_SIZE_MIN (4);
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};
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enum packed_delta_flag_t
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{
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DELTAS_ARE_ZERO = 0x80,
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DELTAS_ARE_WORDS = 0x40,
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DELTA_RUN_COUNT_MASK = 0x3F
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};
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struct tuple_delta_t
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{
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static constexpr bool realloc_move = true; // Watch out when adding new members!
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public:
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hb_hashmap_t<hb_tag_t, Triple> axis_tuples;
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/* indices_length = point_count, indice[i] = 1 means point i is referenced */
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hb_vector_t<bool> indices;
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hb_vector_t<float> deltas_x;
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/* empty for cvar tuples */
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hb_vector_t<float> deltas_y;
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/* compiled data: header and deltas
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* compiled point data is saved in a hashmap within tuple_variations_t cause
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* some point sets might be reused by different tuple variations */
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hb_vector_t<char> compiled_tuple_header;
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hb_vector_t<char> compiled_deltas;
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/* compiled peak coords, empty for non-gvar tuples */
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hb_vector_t<char> compiled_peak_coords;
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tuple_delta_t () = default;
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tuple_delta_t (const tuple_delta_t& o) = default;
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friend void swap (tuple_delta_t& a, tuple_delta_t& b)
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{
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hb_swap (a.axis_tuples, b.axis_tuples);
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hb_swap (a.indices, b.indices);
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hb_swap (a.deltas_x, b.deltas_x);
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hb_swap (a.deltas_y, b.deltas_y);
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hb_swap (a.compiled_tuple_header, b.compiled_tuple_header);
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hb_swap (a.compiled_deltas, b.compiled_deltas);
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hb_swap (a.compiled_peak_coords, b.compiled_peak_coords);
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}
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tuple_delta_t (tuple_delta_t&& o) : tuple_delta_t ()
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{ hb_swap (*this, o); }
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tuple_delta_t& operator = (tuple_delta_t&& o)
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{
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hb_swap (*this, o);
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return *this;
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}
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void remove_axis (hb_tag_t axis_tag)
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{ axis_tuples.del (axis_tag); }
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bool set_tent (hb_tag_t axis_tag, Triple tent)
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{ return axis_tuples.set (axis_tag, tent); }
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|
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tuple_delta_t& operator += (const tuple_delta_t& o)
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{
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unsigned num = indices.length;
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for (unsigned i = 0; i < num; i++)
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{
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|
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 */
|