//
// I(k) = k * d->span + d->span / 2 (1)
- // First step is to get the 'k' of the I(k) nearest to our idx, using defintion (1)
+ // First step is to get the 'k' of the I(k) nearest to our idx, using definition (1)
uint32_t k = idx / d->span;
// Then we read the corresponding SparseIndex[] entry
uint32_t block = number<uint32_t, LittleEndian>(&d->sparseIndex[k].block);
int offset = number<uint16_t, LittleEndian>(&d->sparseIndex[k].offset);
- // Now compute the difference idx - I(k). From defintion of k we know that
+ // Now compute the difference idx - I(k). From definition of k we know that
//
// idx = k * d->span + idx % d->span (2)
//
// idx = Binomial[1][s1] + Binomial[2][s2] + ... + Binomial[k][sk]
//
template<typename Entry, typename T = typename Ret<Entry>::type>
-T do_probe_table(const Position& pos, Entry* entry, WDLScore wdl, ProbeState* result) {
+T do_probe_table(const Position& pos, Entry* entry, WDLScore wdl, ProbeState* result) {
const bool IsWDL = std::is_same<Entry, WDLEntry>::value;
for (File f = FILE_A; f <= MaxFile; ++f)
for (int i = 0; i < Sides; i++) {
(d = item(p, i, f).precomp)->sparseIndex = (SparseEntry*)data;
- data += d->sparseIndexSize * sizeof(SparseEntry) ;
+ data += d->sparseIndexSize * sizeof(SparseEntry);
}
for (File f = FILE_A; f <= MaxFile; ++f)