text: // Copyright (c) 2012-2014 The Bitcoin developers
  // Copyright (c) 2017-2019 The PIVX developers
  // Copyright (c) 2021 The ENZO developers
  // Distributed under the MIT software license, see the accompanying
  // file COPYING or http://www.opensource.org/licenses/mit-license.php.
  
  #include "bloom.h"
  
  #include "hash.h"
  #include "primitives/transaction.h"
  #include "script/script.h"
  #include "script/standard.h"
  #include "random.h"
  #include "streams.h"
  
  #include <math.h>
  #include <stdlib.h>
  
  
  #define LN2SQUARED 0.4804530139182014246671025263266649717305529515945455
  #define LN2 0.6931471805599453094172321214581765680755001343602552
  
  
  CBloomFilter::CBloomFilter(unsigned int nElements, double nFPRate, unsigned int nTweakIn, unsigned char nFlagsIn) :
      /**
       * The ideal size for a bloom filter with a given number of elements and false positive rate is:
       * - nElements * log(fp rate) / ln(2)^2
       * We ignore filter parameters which will create a bloom filter larger than the protocol limits
       */
      vData(std::min((unsigned int)(-1 / LN2SQUARED * nElements * log(nFPRate)), MAX_BLOOM_FILTER_SIZE * 8) / 8),
      /**
       * The ideal number of hash functions is filter size * ln(2) / number of elements
       * Again, we ignore filter parameters which will create a bloom filter with more hash functions than the protocol limits
       * See https://en.wikipedia.org/wiki/Bloom_filter for an explanation of these formulas
       */
      isFull(false),
      isEmpty(false),
      nHashFuncs(std::min((unsigned int)(vData.size() * 8 / nElements * LN2), MAX_HASH_FUNCS)),
      nTweak(nTweakIn),
      nFlags(nFlagsIn)
  {
  }
  
  inline unsigned int CBloomFilter::Hash(unsigned int nHashNum, const std::vector<unsigned char>& vDataToHash) const
  {
      // 0xFBA4C795 chosen as it guarantees a reasonable bit difference between nHashNum values.
      return MurmurHash3(nHashNum * 0xFBA4C795 + nTweak, vDataToHash) % (vData.size() * 8);
  }
  
  void CBloomFilter::insert(const std::vector<unsigned char>& vKey)
  {
      if (isFull)
          return;
      for (unsigned int i = 0; i < nHashFuncs; i++) {
          unsigned int nIndex = Hash(i, vKey);
          // Sets bit nIndex of vData
          vData[nIndex >> 3] |= (1 << (7 & nIndex));
      }
      isEmpty = false;
  }
  
  void CBloomFilter::insert(const COutPoint& outpoint)
  {
      CDataStream stream(SER_NETWORK, PROTOCOL_VERSION);
      stream << outpoint;
      std::vector<unsigned char> data(stream.begin(), stream.end());
      insert(data);
  }
  
  void CBloomFilter::insert(const uint256& hash)
  {
      std::vector<unsigned char> data(hash.begin(), hash.end());
      insert(data);
  }
  
  bool CBloomFilter::contains(const std::vector<unsigned char>& vKey) const
  {
      if (isFull) {
          return true;
      }
      if (isEmpty) {
          return false;
      }
      for (unsigned int i = 0; i < nHashFuncs; i++) {
          unsigned int nIndex = Hash(i, vKey);
          // Checks bit nIndex of vData
          if (!(vData[nIndex >> 3] & (1 << (7 & nIndex))))
              return false;
      }
      return true;
  }
  
  bool CBloomFilter::contains(const COutPoint& outpoint) const
  {
      CDataStream stream(SER_NETWORK, PROTOCOL_VERSION);
      stream << outpoint;
      std::vector<unsigned char> data(stream.begin(), stream.end());
      return contains(data);
  }
  
  bool CBloomFilter::contains(const uint256& hash) const
  {
      std::vector<unsigned char> data(hash.begin(), hash.end());
      return contains(data);
  }
  
  void CBloomFilter::clear()
  {
      vData.assign(vData.size(), 0);
      isFull = false;
      isEmpty = true;
  }
  
  void CBloomFilter::reset(unsigned int nNewTweak)
  {
      clear();
      nTweak = nNewTweak;
  }
  
  bool CBloomFilter::IsWithinSizeConstraints() const
  {
      return vData.size() <= MAX_BLOOM_FILTER_SIZE && nHashFuncs <= MAX_HASH_FUNCS;
  }
  
  /**
   * Returns true if this filter will match anything. See {@link org.enzoj.core.BloomFilter#setMatchAll()}
   * for when this can be a useful thing to do.
   */
  bool CBloomFilter::MatchesAll() const {
      for (unsigned char b : vData)
          if (b !=  0xff)
              return false;
      return true;
  }
  
  /**
   * Copies filter into this. Filter must have the same size, hash function count and nTweak or an
   * IllegalArgumentException will be thrown.
   */
  bool CBloomFilter::Merge(const CBloomFilter& filter) {
      if (!this->MatchesAll() && !filter.MatchesAll()) {
          if(! (filter.vData.size() == this->vData.size() &&
                  filter.nHashFuncs == this->nHashFuncs &&
                  filter.nTweak == this->nTweak)){
              return false;
          }
          for (unsigned int i = 0; i < vData.size(); i++)
              this->vData[i] |= filter.vData[i];
      } else {
          // TODO: Check this.
          this->vData.clear();
          this->vData[0] = 0xff;
      }
      return true;
  }
  
  bool CBloomFilter::IsRelevantAndUpdate(const CTransaction& tx)
  {
      bool fFound = false;
      // Match if the filter contains the hash of tx
      //  for finding tx when they appear in a block
      if (isFull)
          return true;
      if (isEmpty)
          return false;
      const uint256& hash = tx.GetHash();
      if (contains(hash))
          fFound = true;
  
      for (unsigned int i = 0; i < tx.vout.size(); i++) {
          const CTxOut& txout = tx.vout[i];
          // Match if the filter contains any arbitrary script data element in any scriptPubKey in tx
          // If this matches, also add the specific output that was matched.
          // This means clients don't have to update the filter themselves when a new relevant tx
          // is discovered in order to find spending transactions, which avoids round-tripping and race conditions.
          CScript::const_iterator pc = txout.scriptPubKey.begin();
          std::vector<unsigned char> data;
          while (pc < txout.scriptPubKey.end()) {
              opcodetype opcode;
              if (!txout.scriptPubKey.GetOp(pc, opcode, data)){
                  break;
              }
  
              if (data.size() != 0 && contains(data)) {
                  fFound = true;
                  if ((nFlags & BLOOM_UPDATE_MASK) == BLOOM_UPDATE_ALL)
                      insert(COutPoint(hash, i));
                  else if ((nFlags & BLOOM_UPDATE_MASK) == BLOOM_UPDATE_P2PUBKEY_ONLY) {
                      txnouttype type;
                      std::vector<std::vector<unsigned char> > vSolutions;
                      if (Solver(txout.scriptPubKey, type, vSolutions) &&
                          (type == TX_PUBKEY || type == TX_MULTISIG))
                          insert(COutPoint(hash, i));
                  }
                  break;
              }
          }
      }
  
      if (fFound)
          return true;
  
      for (const CTxIn& txin : tx.vin) {
          // Match if the filter contains an outpoint tx spends
          if (contains(txin.prevout))
              return true;
  
          // Match if the filter contains any arbitrary script data element in any scriptSig in tx
          CScript::const_iterator pc = txin.scriptSig.begin();
          std::vector<unsigned char> data;
          while (pc < txin.scriptSig.end()) {
              opcodetype opcode;
              if (!txin.scriptSig.GetOp(pc, opcode, data))
                  break;
              if (data.size() != 0 && contains(data)) {
                  return true;
              }
          }
      }
  
      return false;
  }
  
  void CBloomFilter::UpdateEmptyFull()
  {
      bool full = true;
      bool empty = true;
      for (unsigned int i = 0; i < vData.size(); i++) {
          full &= vData[i] == 0xff;
          empty &= vData[i] == 0;
      }
      isFull = full;
      isEmpty = empty;
  }
  
  CRollingBloomFilter::CRollingBloomFilter(unsigned int nElements, double fpRate)
  {
      double logFpRate = log(fpRate);
      /* The optimal number of hash functions is log(fpRate) / log(0.5), but
       * restrict it to the range 1-50. */
      nHashFuncs = std::max(1, std::min((int)round(logFpRate / log(0.5)), 50));
      /* In this rolling bloom filter, we'll store between 2 and 3 generations of nElements / 2 entries. */
      nEntriesPerGeneration = (nElements + 1) / 2;
      uint32_t nMaxElements = nEntriesPerGeneration * 3;
      /* The maximum fpRate = pow(1.0 - exp(-nHashFuncs * nMaxElements / nFilterBits), nHashFuncs)
       * =>          pow(fpRate, 1.0 / nHashFuncs) = 1.0 - exp(-nHashFuncs * nMaxElements / nFilterBits)
       * =>          1.0 - pow(fpRate, 1.0 / nHashFuncs) = exp(-nHashFuncs * nMaxElements / nFilterBits)
       * =>          log(1.0 - pow(fpRate, 1.0 / nHashFuncs)) = -nHashFuncs * nMaxElements / nFilterBits
       * =>          nFilterBits = -nHashFuncs * nMaxElements / log(1.0 - pow(fpRate, 1.0 / nHashFuncs))
       * =>          nFilterBits = -nHashFuncs * nMaxElements / log(1.0 - exp(logFpRate / nHashFuncs))
       */
      uint32_t nFilterBits = (uint32_t)ceil(-1.0 * nHashFuncs * nMaxElements / log(1.0 - exp(logFpRate / nHashFuncs)));
      data.clear();
      /* We store up to 16 'bits' per data element. */
      data.resize((nFilterBits + 15) / 16);
      reset();
  }
  
  /* Similar to CBloomFilter::Hash */
  inline unsigned int CRollingBloomFilter::Hash(unsigned int nHashNum, const std::vector<unsigned char>& vDataToHash) const {
      return MurmurHash3(nHashNum * 0xFBA4C795 + nTweak, vDataToHash) % (data.size() * 16);
  }
  
  void CRollingBloomFilter::insert(const std::vector<unsigned char>& vKey)
  {
      if (nEntriesThisGeneration == nEntriesPerGeneration) {
          nEntriesThisGeneration = 0;
          nGeneration++;
          if (nGeneration == 4) {
              nGeneration = 1;
          }
          /* Wipe old entries that used this generation number. */
          for (uint32_t p = 0; p < data.size() * 16; p++) {
              if (get(p) == nGeneration) {
                  put(p, 0);
              }
          }
      }
      nEntriesThisGeneration++;
  
      for (int n = 0; n < nHashFuncs; n++) {
          uint32_t h = Hash(n, vKey);
          put(h, nGeneration);
      }
  }
  
  void CRollingBloomFilter::insert(const uint256& hash)
  {
      std::vector<unsigned char> data(hash.begin(), hash.end());
      insert(data);
  }
  
  bool CRollingBloomFilter::contains(const std::vector<unsigned char>& vKey) const
  {
      for (int n = 0; n < nHashFuncs; n++) {
          uint32_t h = Hash(n, vKey);
          if (get(h) == 0) {
              return false;
          }
      }
      return true;
  }
  
  bool CRollingBloomFilter::contains(const uint256& hash) const
  {
      std::vector<unsigned char> data(hash.begin(), hash.end());
      return contains(data);
  }
  
  void CRollingBloomFilter::reset()
  {
      nTweak = GetRand(std::numeric_limits<unsigned int>::max());
      nEntriesThisGeneration = 0;
      nGeneration = 1;
      for (std::vector<uint32_t>::iterator it = data.begin(); it != data.end(); it++) {
          *it = 0;
      }
  }
  