SOS i keep getting errors in the loop solving by finite difference method.
I either get the following error when i start with i = 2 : N :
diffusion: A(I,J): row index out of bounds; value 2 out of bound 1
error: called from
diffusion at line 37 column 10 % note line change due to edit!
or, I get the following error when i do i = 2 : N :
subscript indices must be either positive integers less than 2^31 or logicals
error: called from
diffusion at line 37 column 10 % note line change due to edit!
Please help
clear all; close all;
% mesh in space
dx = 0.1;
x = 0 : dx : 1;
% mesh in time
dt = 1 / 50;
t0 = 0;
tf = 10;
t = t0 : dt : tf;
% diffusivity
D = 0.5;
% number of nodes
N = 11;
% number of iterations
M = 10;
% initial conditions
if x <= .5 && x >= 0 % note, in octave, you don't need parentheses around the test expression
u0 = x;
elseif
u0 = 1-x;
endif
u = u0;
alpha = D * dt / (dx^2);
for j = 1 : M
for i = 1 : N
u(i, j+1) = u(i, j ) ...
+ alpha ...
* ( u(i-1, j) ...
+ u(i+1, j) ...
- 2 ...
* u(i, j) ...
) ;
end
u(N+1, j+1) = u(N+1, j) ...
+ alpha ...
* ( ...
u(N, j) ...
- 2 ...
* u(N+1, j) ...
+ u(N, j) ...
) ;
% boundary conditions
u(0, :) = u0;
u(1, :) = u1;
u1 = u0;
u0 = 0;
end
% exact solution with 14 terms
%k=14 % COMMENTED OUT
v = (4 / ((k * pi) .^ 2)) ...
* sin( (k * pi) / 2 ) ...
* sin( k * pi * x ) ...
* exp .^ (D * ((k * pi) ^ 2) * t) ;
exact = symsum( v, k, 1, 14 );
error = exact - u;
% plot stuff
plot( t, error );
xlabel( 'time' );
ylabel( 'error' );
legend( 't = 1 / 50' );
Have a look at the edited code I cleaned up for you above and study it.
Don't underestimate the importance of clean, readable code when hunting for bugs.
It will save you more time than it will cost. Especially a week from now when you will need to revisit this code and you will not remember at all what you were trying to do.
Now regarding your errors. (all line references are with respect to the cleaned up code above)
Scenario 1:
In line 29 you initialise u as a single value.
If you start your loop in line 35 starting with i = 2, then as soon as you try to do u(i, j+1), i.e. u(2,2) in the next line, octave will complain that you're trying to index the second row, in an array that so far only contains one row. (in fact, the same will apply for j at this point, since at this point you only have one column as well)
Scenario 2:
I assume the second scenario was a typo and you meant to say i = 1 : N.
If you start with i=1 in the loop, then have a look at line 38: you are trying to get element u(i-1, j), i.e. u(0,1). Therefore octave will complain that you're trying to get the zero element, but in octave arrays start from one and zero is not defined. Attempting to access any array with a zero will result in the error you see (try it in a terminal!).
UPDATE
Also, now that the code is clean, you can spot another bug, which octave helpfully warns you about if you try to run the code.
Look at line 26. There is NO condition in the elseif leg, so octave looks for the next statement as the test condition.
This means that the elseif condition will always succeed as long as the result of u0 = 1-x is non-zero.
This is clearly a bug. Either you forgot to put the condition for the elseif, or more likely, you probably just meant to say else, rather than elseif.
I'm looking for algorithm working in loop which will generate any natural number n with using only incrementation and multiplication by 2 well trivial way is known (increment number n times) but I'm looking for something a little bit faster. Honestly I don't even know how I should start this.
Basically, what you want to do is shift in the bits of the number from the right, starting with the MSB.
For example, if your number is 70, then the binary of it is 0b1000110. So, you want to "shift in" the bits 1, 0, 0, 0, 1, 1, 0.
To shift in a zero, you simply double the number. To shift in a one, you double the number, then increment it.
if (bit_to_be_shifted_in != 0)
x = (x * 2) + 1;
else
x = x * 2;
So, if you're given an array of bits from MSB to LSB (i.e. from left to right), then the C code looks like this:
x = 0;
for (i = 0; i < number_of_bits; i++)
{
if (bits[i] != 0)
x = x * 2 + 1;
else
x = x * 2;
}
One way of doing this is to go backwards. If it's an odd number, subtract one. If it's even, divide by 2.
while(n > 0) {
n & 1 ? n &= ~1 : n >>= 1;
}
I am trying to do a fast exponentiation. But the result does not seem to produce the correct result. Any help would be appreciated.
EDIT: Manage to solve it thanks for all the help.
if (content[i] == '1')
s1 = (int)(po1 * (Math.pow(po1, 2)));
else
s1 = po1 * po1;
final_result *= temp;
Check out this Exponation by squaring
You probably want to bit-shift right and square your base each time you encounter a 1 bit in the exponent
int pow(int base, int e)
{
int retVal = 1;
while (e)
{
if (e % 2 == 1)//i.e. last bit of exponent is 1
retVal *= base;
e >>= 1; //bitshift exponent to the right.
base *= base; // square base since we shifted 1 bit in our exponent
}
return retVal ;
}
A good way of thinking about it is that your exponent is being broken down: say, 6^7 (exponent in bits is 1, 1, 1) = 6^1 * 6^2 * 6^4 = 6 * 36 * 36^2 = 6 * 36 * 1296. Your base is always squaring itself.
temp = (int)(g1 * (Math.pow(g1, 2)));
This basically just boils down to g13. I'm not familiar with this algorithm but this can't be right.
Also, as a side note, don't ever call Math.pow(<var>, 2), just write <var> * <var>.
There are several problems with your code, starting with the fact that you are reading the exp string in the wrong direction, adding extra multiplications by the base, and not considering the rank of the 1 when raising the powers of 2.
Here is a python quick sketch of what you are trying to achieve:
a = int(raw_input("base"))
b = "{0:b}".format(int(raw_input("exp")))
res = 1
for index, i in enumerate(b[::-1]):
if i == '1':
res *= a**(2**index)
print res
Alternatively, you could square a at every iteration instead:
for index, i in enumerate(b[::-1]):
if i == '1':
res *= a
a *= a
I am currently reading "Linux Kernel Development" by Robert Love, and I got a few questions about the CFS.
My question is how calc_delta_mine calculates :
delta_exec_weighted= (delta_exec * weight)/lw->weight
I guess it is done by two steps :
calculation the (delta_exec * 1024) :
if (likely(weight > (1UL << SCHED_LOAD_RESOLUTION)))
tmp = (u64)delta_exec * scale_load_down(weight);
else
tmp = (u64)delta_exec;
calculate the /lw->weight ( or * lw->inv_weight ) :
if (!lw->inv_weight) {
unsigned long w = scale_load_down(lw->weight);
if (BITS_PER_LONG > 32 && unlikely(w >= WMULT_CONST))
lw->inv_weight = 1;
else if (unlikely(!w))
lw->inv_weight = WMULT_CONST;
else
lw->inv_weight = WMULT_CONST / w;
}
/*
* Check whether we'd overflow the 64-bit multiplication:
*/
if (unlikely(tmp > WMULT_CONST))
tmp = SRR(SRR(tmp, WMULT_SHIFT/2) * lw->inv_weight,
WMULT_SHIFT/2);
else
tmp = SRR(tmp * lw->inv_weight, WMULT_SHIFT);
return (unsigned long)min(tmp, (u64)(unsigned long)LONG_MAX);
The SRR (Shift right and round) macro is defined via :
#define SRR(x, y) (((x) + (1UL << ((y) - 1))) >> (y))
And the other MACROS are defined :
#if BITS_PER_LONG == 32
# define WMULT_CONST (~0UL)
#else
# define WMULT_CONST (1UL << 32)
#endif
#define WMULT_SHIFT 32
Can someone please explain how exactly the SRR works and how does this check the 64-bit multiplication overflow?
And please explain the definition of the MACROS in this function((~0UL) ,(1UL << 32))?
The code you posted is basically doing calculations using 32.32 fixed-point arithmetic, where a single 64-bit quantity holds the integer part of the number in the high 32 bits, and the decimal part of the number in the low 32 bits (so, for example, 1.5 is 0x0000000180000000 in this system). WMULT_CONST is thus an approximation of 1.0 (using a value that can fit in a long for platform efficiency considerations), and so dividing WMULT_CONST by w computes 1/w as a 32.32 value.
Note that multiplying two 32.32 values together as integers produces a result that is 232 times too large; thus, WMULT_SHIFT (=32) is the right shift value needed to normalize the result of multiplying two 32.32 values together back down to 32.32.
The necessity of using this improved precision for scheduling purposes is explained in a comment in sched/sched.h:
/*
* Increase resolution of nice-level calculations for 64-bit architectures.
* The extra resolution improves shares distribution and load balancing of
* low-weight task groups (eg. nice +19 on an autogroup), deeper taskgroup
* hierarchies, especially on larger systems. This is not a user-visible change
* and does not change the user-interface for setting shares/weights.
*
* We increase resolution only if we have enough bits to allow this increased
* resolution (i.e. BITS_PER_LONG > 32). The costs for increasing resolution
* when BITS_PER_LONG <= 32 are pretty high and the returns do not justify the
* increased costs.
*/
As for SRR, mathematically, it computes the rounded result of x / 2y.
To round the result of a division x/q you can calculate x + q/2 floor-divided by q; this is what SRR does by calculating x + 2y-1 floor-divided by 2y.
I am trying to find an algorithm to count from 0 to 2n-1 but their bit pattern reversed. I care about only n LSB of a word. As you may have guessed I failed.
For n=3:
000 -> 0
100 -> 4
010 -> 2
110 -> 6
001 -> 1
101 -> 5
011 -> 3
111 -> 7
You get the idea.
Answers in pseudo-code is great. Code fragments in any language are welcome, answers without bit operations are preferred.
Please don't just post a fragment without even a short explanation or a pointer to a source.
Edit: I forgot to add, I already have a naive implementation which just bit-reverses a count variable. In a sense, this method is not really counting.
This is, I think easiest with bit operations, even though you said this wasn't preferred
Assuming 32 bit ints, here's a nifty chunk of code that can reverse all of the bits without doing it in 32 steps:
unsigned int i;
i = (i & 0x55555555) << 1 | (i & 0xaaaaaaaa) >> 1;
i = (i & 0x33333333) << 2 | (i & 0xcccccccc) >> 2;
i = (i & 0x0f0f0f0f) << 4 | (i & 0xf0f0f0f0) >> 4;
i = (i & 0x00ff00ff) << 8 | (i & 0xff00ff00) >> 8;
i = (i & 0x0000ffff) << 16 | (i & 0xffff0000) >> 16;
i >>= (32 - n);
Essentially this does an interleaved shuffle of all of the bits. Each time around half of the bits in the value are swapped with the other half.
The last line is necessary to realign the bits so that bin "n" is the most significant bit.
Shorter versions of this are possible if "n" is <= 16, or <= 8
At each step, find the leftmost 0 digit of your value. Set it, and clear all digits to the left of it. If you don't find a 0 digit, then you've overflowed: return 0, or stop, or crash, or whatever you want.
This is what happens on a normal binary increment (by which I mean it's the effect, not how it's implemented in hardware), but we're doing it on the left instead of the right.
Whether you do this in bit ops, strings, or whatever, is up to you. If you do it in bitops, then a clz (or call to an equivalent hibit-style function) on ~value might be the most efficient way: __builtin_clz where available. But that's an implementation detail.
This solution was originally in binary and converted to conventional math as the requester specified.
It would make more sense as binary, at least the multiply by 2 and divide by 2 should be << 1 and >> 1 for speed, the additions and subtractions probably don't matter one way or the other.
If you pass in mask instead of nBits, and use bitshifting instead of multiplying or dividing, and change the tail recursion to a loop, this will probably be the most performant solution you'll find since every other call it will be nothing but a single add, it would only be as slow as Alnitak's solution once every 4, maybe even 8 calls.
int incrementBizarre(int initial, int nBits)
// in the 3 bit example, this should create 100
mask=2^(nBits-1)
// This should only return true if the first (least significant) bit is not set
// if initial is 011 and mask is 100
// 3 4, bit is not set
if(initial < mask)
// If it was not, just set it and bail.
return initial+ mask // 011 (3) + 100 (4) = 111 (7)
else
// it was set, are we at the most significant bit yet?
// mask 100 (4) / 2 = 010 (2), 001/2 = 0 indicating overflow
if(mask / 2) > 0
// No, we were't, so unset it (initial-mask) and increment the next bit
return incrementBizarre(initial - mask, mask/2)
else
// Whoops we were at the most significant bit. Error condition
throw new OverflowedMyBitsException()
Wow, that turned out kinda cool. I didn't figure in the recursion until the last second there.
It feels wrong--like there are some operations that should not work, but they do because of the nature of what you are doing (like it feels like you should get into trouble when you are operating on a bit and some bits to the left are non-zero, but it turns out you can't ever be operating on a bit unless all the bits to the left are zero--which is a very strange condition, but true.
Example of flow to get from 110 to 001 (backwards 3 to backwards 4):
mask 100 (4), initial 110 (6); initial < mask=false; initial-mask = 010 (2), now try on the next bit
mask 010 (2), initial 010 (2); initial < mask=false; initial-mask = 000 (0), now inc the next bit
mask 001 (1), initial 000 (0); initial < mask=true; initial + mask = 001--correct answer
Here's a solution from my answer to a different question that computes the next bit-reversed index without looping. It relies heavily on bit operations, though.
The key idea is that incrementing a number simply flips a sequence of least-significant bits, for example from nnnn0111 to nnnn1000. So in order to compute the next bit-reversed index, you have to flip a sequence of most-significant bits. If your target platform has a CTZ ("count trailing zeros") instruction, this can be done efficiently.
Example in C using GCC's __builtin_ctz:
void iter_reversed(unsigned bits) {
unsigned n = 1 << bits;
for (unsigned i = 0, j = 0; i < n; i++) {
printf("%x\n", j);
// Compute a mask of LSBs.
unsigned mask = i ^ (i + 1);
// Length of the mask.
unsigned len = __builtin_ctz(~mask);
// Align the mask to MSB of n.
mask <<= bits - len;
// XOR with mask.
j ^= mask;
}
}
Without a CTZ instruction, you can also use integer division:
void iter_reversed(unsigned bits) {
unsigned n = 1 << bits;
for (unsigned i = 0, j = 0; i < n; i++) {
printf("%x\n", j);
// Find least significant zero bit.
unsigned bit = ~i & (i + 1);
// Using division to bit-reverse a single bit.
unsigned rev = (n / 2) / bit;
// XOR with mask.
j ^= (n - 1) & ~(rev - 1);
}
}
void reverse(int nMaxVal, int nBits)
{
int thisVal, bit, out;
// Calculate for each value from 0 to nMaxVal.
for (thisVal=0; thisVal<=nMaxVal; ++thisVal)
{
out = 0;
// Shift each bit from thisVal into out, in reverse order.
for (bit=0; bit<nBits; ++bit)
out = (out<<1) + ((thisVal>>bit) & 1)
}
printf("%d -> %d\n", thisVal, out);
}
Maybe increment from 0 to N (the "usual" way") and do ReverseBitOrder() for each iteration. You can find several implementations here (I like the LUT one the best).
Should be really quick.
Here's an answer in Perl. You don't say what comes after the all ones pattern, so I just return zero. I took out the bitwise operations so that it should be easy to translate into another language.
sub reverse_increment {
my($n, $bits) = #_;
my $carry = 2**$bits;
while($carry > 1) {
$carry /= 2;
if($carry > $n) {
return $carry + $n;
} else {
$n -= $carry;
}
}
return 0;
}
Here's a solution which doesn't actually try to do any addition, but exploits the on/off pattern of the seqence (most sig bit alternates every time, next most sig bit alternates every other time, etc), adjust n as desired:
#define FLIP(x, i) do { (x) ^= (1 << (i)); } while(0)
int main() {
int n = 3;
int max = (1 << n);
int x = 0;
for(int i = 1; i <= max; ++i) {
std::cout << x << std::endl;
/* if n == 3, this next part is functionally equivalent to this:
*
* if((i % 1) == 0) FLIP(x, n - 1);
* if((i % 2) == 0) FLIP(x, n - 2);
* if((i % 4) == 0) FLIP(x, n - 3);
*/
for(int j = 0; j < n; ++j) {
if((i % (1 << j)) == 0) FLIP(x, n - (j + 1));
}
}
}
How about adding 1 to the most significant bit, then carrying to the next (less significant) bit, if necessary. You could speed this up by operating on bytes:
Precompute a lookup table for counting in bit-reverse from 0 to 256 (00000000 -> 10000000, 10000000 -> 01000000, ..., 11111111 -> 00000000).
Set all bytes in your multi-byte number to zero.
Increment the most significant byte using the lookup table. If the byte is 0, increment the next byte using the lookup table. If the byte is 0, increment the next byte...
Go to step 3.
With n as your power of 2 and x the variable you want to step:
(defun inv-step (x n) ; the following is a function declaration
"returns a bit-inverse step of x, bounded by 2^n" ; documentation
(do ((i (expt 2 (- n 1)) ; loop, init of i
(/ i 2)) ; stepping of i
(s x)) ; init of s as x
((not (integerp i)) ; breaking condition
s) ; returned value if all bits are 1 (is 0 then)
(if (< s i) ; the loop's body: if s < i
(return-from inv-step (+ s i)) ; -> add i to s and return the result
(decf s i)))) ; else: reduce s by i
I commented it thoroughly as you may not be familiar with this syntax.
edit: here is the tail recursive version. It seems to be a little faster, provided that you have a compiler with tail call optimization.
(defun inv-step (x n)
(let ((i (expt 2 (- n 1))))
(cond ((= n 1)
(if (zerop x) 1 0)) ; this is really (logxor x 1)
((< x i)
(+ x i))
(t
(inv-step (- x i) (- n 1))))))
When you reverse 0 to 2^n-1 but their bit pattern reversed, you pretty much cover the entire 0-2^n-1 sequence
Sum = 2^n * (2^n+1)/2
O(1) operation. No need to do bit reversals
Edit: Of course original poster's question was about to do increment by (reversed) one, which makes things more simple than adding two random values. So nwellnhof's answer contains the algorithm already.
Summing two bit-reversal values
Here is one solution in php:
function RevSum ($a,$b) {
// loop until our adder, $b, is zero
while ($b) {
// get carry (aka overflow) bit for every bit-location by AND-operation
// 0 + 0 --> 00 no overflow, carry is "0"
// 0 + 1 --> 01 no overflow, carry is "0"
// 1 + 0 --> 01 no overflow, carry is "0"
// 1 + 1 --> 10 overflow! carry is "1"
$c = $a & $b;
// do 1-bit addition for every bit location at once by XOR-operation
// 0 + 0 --> 00 result = 0
// 0 + 1 --> 01 result = 1
// 1 + 0 --> 01 result = 1
// 1 + 1 --> 10 result = 0 (ignored that "1", already taken care above)
$a ^= $b;
// now: shift carry bits to the next bit-locations to be added to $a in
// next iteration.
// PHP_INT_MAX here is used to ensure that the most-significant bit of the
// $b will be cleared after shifting. see link in the side note below.
$b = ($c >> 1) & PHP_INT_MAX;
}
return $a;
}
Side note: See this question about shifting negative values.
And as for test; start from zero and increment value by 8-bit reversed one (10000000):
$value = 0;
$add = 0x80; // 10000000 <-- "one" as bit reversed
for ($count = 20; $count--;) { // loop 20 times
printf("%08b\n", $value); // show value as 8-bit binary
$value = RevSum($value, $add); // do addition
}
... will output:
00000000
10000000
01000000
11000000
00100000
10100000
01100000
11100000
00010000
10010000
01010000
11010000
00110000
10110000
01110000
11110000
00001000
10001000
01001000
11001000
Let assume number 1110101 and our task is to find next one.
1) Find zero on highest position and mark position as index.
11101010 (4th position, so index = 4)
2) Set to zero all bits on position higher than index.
00001010
3) Change founded zero from step 1) to '1'
00011010
That's it. This is by far the fastest algorithm since most of cpu's has instructions to achieve this very efficiently. Here is a C++ implementation which increment 64bit number in reversed patern.
#include <intrin.h>
unsigned __int64 reversed_increment(unsigned __int64 number)
{
unsigned long index, result;
_BitScanReverse64(&index, ~number); // returns index of the highest '1' on bit-reverse number (trick to find the highest '0')
result = _bzhi_u64(number, index); // set to '0' all bits at number higher than index position
result |= (unsigned __int64) 1 << index; // changes to '1' bit on index position
return result;
}
Its not hit your requirements to have "no bits" operations, however i fear there is now way how to achieve something similar without them.