使用掩码交错位
输入:
arbitrary bitset, e.g. bit positions 012345
arbitrary bit mask, e.g. (x=1) xx0x0x
输出:
xx0x1x2345
也就是说,我希望将位集的第一位放置在掩码的第一个 0 中。同样,第二位被放置在掩码的第二个 0 中。
示例:
mask = 1001001
bits = 1101
result = 1111011
我知道这可以通过循环来完成,但我想主要使用位操作来完成。我知道您可以仅使用掩码和位运算符来执行任意位排列。我愿意花费大量时间来设置排列掩码,因为输入掩码将被多次使用。
编辑:我查看了 http://graphics.stanford.edu/~ 的算法seander/bithacks.html 和 http://www.hackersdelight.org/HDcode.htm< /a>,但还没有找到确切的方法。
inputs:
arbitrary bitset, e.g. bit positions 012345
arbitrary bit mask, e.g. (x=1) xx0x0x
output:
xx0x1x2345
That is, I want the first bit of the bitset to be placed in the first 0 of the mask. Likewise, the second bit is placed in the second 0 of the mask.
example:
mask = 1001001
bits = 1101
result = 1111011
I know that this can be done with a loop, but I'd like do it using primarily bit operations. I know you can perform arbitrary bit permutations using only masking and bit operators. I'm willing to spend a good amount of time setting up the permutation masks since the input mask will be used many times.
edit: I've looked at the algorithms at http://graphics.stanford.edu/~seander/bithacks.html and http://www.hackersdelight.org/HDcode.htm, but haven't found the exact method yet.
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我认为 012345 旨在成为一个 BITSET,他使用 0..5 来指示 0 和 1 的混合。
然而,这似乎不是按位运算。我会坚持循环..
I think the 012345 is intended to be a BITSET and he used 0..5 to indiccate a mix of 0's and 1s.
However, this does not appear to be a bitwise operation. I'd stick to a loop..
如果我没有理解错的话,你需要一个函数 f(bitmask, bitset) ,例如:
其中第一个参数(位掩码)相对固定。
我认为您必须循环位掩码,并且在该循环内您可以使用按位运算。当然,您可以预先编译位掩码并保留 0 的位置,如 {1, 3, 6, 7, ...},并通过循环序列来节省一些周期。
If I didn't get it wrong, you want a function f(bitmask, bitset) like:
in which the first argument (the bit mask) is relatively fixed.
I think you'll have to loop over the bit mask, and inside that loop you could use bitwise operation. Of course you can compile the bit mask beforehand and keep the positions of 0's like {1, 3, 6, 7, ...}, and save some cycles by looping over the sequence instead.
你确定你不需要循环吗?如果您知道位数,则可以跳过开销,只需执行 16 或 32 行位移即可,但循环会更简单。我认为确实没有其他方法可以做到这一点,但你现在让我开始思考它
are you sure you don't need a loop? If you know the number of bits you could skip the overhead and just do like 16 or 32 lines of bit shifts, but a loop would be simpler. I don't think there's really another way to do it but you got me thinking about it now
我认为您想要实现的效果是(使用您的示例数据,但以不同的方式布置信息):
现在,如果我们将其描述为从右到左工作(首先是最低有效位),那么最后的 1 bitset 表示需要设置位掩码最右边的 0。位集中的 0 表示位掩码的下一个 0 不变;接下来的1表示将第三个0转换为1;最重要的 1 意味着第四个零转换为 1。由于位集中没有更多的 1,因此这是最终的更改。请注意,这种算法的表述避免了位集或位掩码中有多少位的问题 - 而从左到右的解释会导致大问题。
让我们回顾一些其他示例:
如果此解释正确,则位集的含义会根据位掩码而变化。如果位掩码和位集限制为 8 位,那么对于每个位集,您可能最终会计算一组 256 个值,这些值可以与原始位掩码值进行或运算以产生结果。另一方面,您可以轻松地将结果计算为与主数据进行“或”运算的值。
I think that the effect you are trying to achieve is (using your example data, but laying the information out somewhat differently):
Now, if we describe this as working from right to left (least significant bit first), then the final 1 of the bitset means that the rightmost 0 of the bitmask needs to be set. The zero in the bitset means that the next 0 of the bitmask is unchanged; the next 1 means that the third zero is converted to a one; and the most significant 1 means that the fourth zero is converted to a 1. Since there are no more ones in the bitset, that is the final change. Note that this formulation of the algorithm avoid issues with how many bits there are in the bitset or bitmask - whereas a left to right interpretation leads to big problems.
Let's review some other examples:
If this interpretation is correct, then the meaning of the bitset varies depending on the bitmask. If the bitmask and bitset are limited to 8 bits, then for each bitset, you probably end up computing a set of 256 values that can be OR'd with the original bitmask value to produce the result. On the other hand, you can just as easily compute the result as a value to be OR'd into the main data.
大多数交错位或通用聚合位函数都会循环,但以不明显的方式循环。
即使是计数位函数也具有 O(log2(整数位)) 复杂度。
因此,如果您愿意接受 O(掩码中的零数) 循环,那么这可能是您最好的选择。 (您必须有一个算法,无论如何都可以在没有本机 插入位的情况下执行此操作说明。):
Most of the interleave bits or general aggregate bits functions do loop, but in a non-obvious way.
Even the count bits function has an O(log2(bits in integer)) complexity.
So if you are willing to accept an O(# of zeroes in mask) loop, then that will probably be your best bet. (You'd have to have an algorithm that does that anyway without a native insert bits instruction.):