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Conflicts: doc/tut1.txt lib/core/locks.nim lib/pure/collections/tables.nim lib/pure/selectors.nim
133 lines
4.4 KiB
Nim
133 lines
4.4 KiB
Nim
#
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#
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# Nim's Runtime Library
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# (c) Copyright 2015 Andreas Rumpf
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#
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# See the file "copying.txt", included in this
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# distribution, for details about the copyright.
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#
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## An ``include`` file for the different table implementations.
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# hcode for real keys cannot be zero. hcode==0 signifies an empty slot. These
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# two procs retain clarity of that encoding without the space cost of an enum.
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proc isEmpty(hcode: Hash): bool {.inline.} =
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result = hcode == 0
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proc isFilled(hcode: Hash): bool {.inline.} =
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result = hcode != 0
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const
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growthFactor = 2
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proc mustRehash(length, counter: int): bool {.inline.} =
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assert(length > counter)
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result = (length * 2 < counter * 3) or (length - counter < 4)
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proc nextTry(h, maxHash: Hash): Hash {.inline.} =
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result = (h + 1) and maxHash
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template rawGetKnownHCImpl() {.dirty.} =
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var h: Hash = hc and maxHash(t) # start with real hash value
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while isFilled(t.data[h].hcode):
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# Compare hc THEN key with boolean short circuit. This makes the common case
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# zero ==key's for missing (e.g.inserts) and exactly one ==key for present.
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# It does slow down succeeding lookups by one extra Hash cmp&and..usually
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# just a few clock cycles, generally worth it for any non-integer-like A.
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if t.data[h].hcode == hc and t.data[h].key == key:
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return h
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h = nextTry(h, maxHash(t))
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result = -1 - h # < 0 => MISSING; insert idx = -1 - result
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template rawGetImpl() {.dirty.} =
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hc = hash(key)
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if hc == 0: # This almost never taken branch should be very predictable.
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hc = 314159265 # Value doesn't matter; Any non-zero favorite is fine.
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rawGetKnownHCImpl()
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template rawGetDeepImpl() {.dirty.} = # Search algo for unconditional add
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hc = hash(key)
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if hc == 0:
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hc = 314159265
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var h: Hash = hc and maxHash(t)
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while isFilled(t.data[h].hcode):
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h = nextTry(h, maxHash(t))
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result = h
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template rawInsertImpl() {.dirty.} =
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data[h].key = key
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data[h].val = val
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data[h].hcode = hc
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proc rawGetKnownHC[X, A](t: X, key: A, hc: Hash): int {.inline.} =
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rawGetKnownHCImpl()
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proc rawGetDeep[X, A](t: X, key: A, hc: var Hash): int {.inline.} =
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rawGetDeepImpl()
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proc rawGet[X, A](t: X, key: A, hc: var Hash): int {.inline.} =
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rawGetImpl()
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proc rawInsert[X, A, B](t: var X, data: var KeyValuePairSeq[A, B],
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key: A, val: B, hc: Hash, h: Hash) =
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rawInsertImpl()
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template addImpl(enlarge) {.dirty, immediate.} =
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if mustRehash(t.dataLen, t.counter): enlarge(t)
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var hc: Hash
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var j = rawGetDeep(t, key, hc)
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rawInsert(t, t.data, key, val, hc, j)
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inc(t.counter)
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template maybeRehashPutImpl(enlarge) {.dirty, immediate.} =
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if mustRehash(t.dataLen, t.counter):
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enlarge(t)
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index = rawGetKnownHC(t, key, hc)
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index = -1 - index # important to transform for mgetOrPutImpl
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rawInsert(t, t.data, key, val, hc, index)
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inc(t.counter)
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template putImpl(enlarge) {.dirty, immediate.} =
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var hc: Hash
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var index = rawGet(t, key, hc)
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if index >= 0: t.data[index].val = val
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else: maybeRehashPutImpl(enlarge)
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template mgetOrPutImpl(enlarge) {.dirty, immediate.} =
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var hc: Hash
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var index = rawGet(t, key, hc)
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if index < 0:
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# not present: insert (flipping index)
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maybeRehashPutImpl(enlarge)
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# either way return modifiable val
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result = t.data[index].val
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template hasKeyOrPutImpl(enlarge) {.dirty, immediate.} =
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var hc: Hash
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var index = rawGet(t, key, hc)
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if index < 0:
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result = false
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maybeRehashPutImpl(enlarge)
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else: result = true
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template delImpl() {.dirty, immediate.} =
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var hc: Hash
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var i = rawGet(t, key, hc)
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let msk = maxHash(t)
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if i >= 0:
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t.data[i].hcode = 0
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dec(t.counter)
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block outer:
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while true: # KnuthV3 Algo6.4R adapted for i=i+1 instead of i=i-1
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var j = i # The correctness of this depends on (h+1) in nextTry,
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var r = j # though may be adaptable to other simple sequences.
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t.data[i].hcode = 0 # mark current EMPTY
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while true:
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i = (i + 1) and msk # increment mod table size
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if isEmpty(t.data[i].hcode): # end of collision cluster; So all done
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break outer
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r = t.data[i].hcode and msk # "home" location of key@i
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if not ((i >= r and r > j) or (r > j and j > i) or (j > i and i >= r)):
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break
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shallowCopy(t.data[j], t.data[i]) # data[j] will be marked EMPTY next loop
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