division

So the order of the members returned from the div functions seems to be implementation defined. Is quot the 1 st member or is rem ? Let's say that I'm doing something like this: generate(begin(digits), end(digits), [i = div_t{ quot, 0 }]() mutable { i = div(i.quot, 10); return i.rem; }) Of course the problem here is that I don't know if I initialized i.quot or i.rem in my lambda capture. Is intializing i with div(quot, 1) the only cross platform way to do this? EDIT: I think the VS workaround could look like this: #include <cstdlib> #include <type_traits> template<class T> struct DTMaker {

I noticed that Clang does an interesting division optimization trick for the following snippet int64_t s2(int64_t a, int64_t b) { return a/b; } Below is the assembly output if specifying march as Sandy Bridge or above mov rax, rdi mov rcx, rdi or rcx, rsi shr rcx, 32 je .LBB1_1 cqo idiv rsi ret .LBB1_1: xor edx, edx div esi ret Here are the Godbolt links for the signed version and the unsigned version From what I understand it checks whether the high bits of the two operands are zero, and does a 32-bit division if that's true I checked this table and see that the latencies for 32/64-bit

My question is very simple, suppose that I have an array like array = np.array([1, 2, 3, 4]) and I'd like to get an array like [1, 0.5, 0.3333333, 0.25] However, if you write something like 1/array or np.divide(1.0, array) it won't work. The only way I've found so far is to write something like: print np.divide(np.ones_like(array)*1.0, array) But I'm absolutely certains that there is a better way to do that. Does anyone have any idea? 1 / array makes an integer division and returns array([1, 0, 0, 0]) . 1. / array will cast the array to float and do the trick: >>> array = np.array([1, 2, 3, 4]

I am trying to complete an assignment that requires me to write three functions for binary arithmetic. badd() was provided for me, so I used it to help write the bsub() and bmult() functions. I am having trouble understanding how I should perform the bdiv() function, however. I know I need to iterate through the bits using a right shift and my bsubb() function, but I don't know how to implement it. Below are the functions that I have written so far. Let me know if you notice any mistakes that I made in writing them(meaning bsub() and bmult()). Thanks. /** This function adds the two arguments

Is there any faster method for division of large integers(having 1000 digits or more) other than the school method? Wikipedia lists multiple division algorithms . See Computational complexity of mathematical operations which lists Schoolbook long division as O(n^2) and Newton's method as M(n) where M is the complexity of the multiplication algorithm used, which could be as good as O(n log n 2^( log* n)) asymptotically. Note from the discussion of one of the multiplication algorithms that the best algorithm asymptotically is not necessarily the fastest for "small" inputs: In practice the

What are the similarities and differences between numpy.divide and the Python slash / operator? As far as I can tell they behave the same, both implementing an element-wise division. The Numpy documentation mentions: numpy.divide(x1, x2) ... Equivalent to x1 / x2 in terms of array-broadcasting. ... Implying that np.divide(x1, x2) is not completely equivalent to x1 / x2. I have run the following snippet to compare their speed: import numpy as np import time a = np.random.rand(10000, 10000) b = np.random.rand(10000, 10000) tic = time.time() c = a / b toc = time.time() print("Python divide took:

This question already has an answer here: Why should EDX be 0 before using the DIV instruction? 2 answers In my program, a hex number is divided by ten and the remainder is checked. First division is performed well; however, after the second division, the program goes wrong. I am new to assembly, and I couldn't find where the problem is... Here is the code segment: ORG 1000 MOV AX, 0x04B4 (1204 decimal value ) MOV BX, 0x000A ( 10 decimal value ) MOV CX, 0x0000 DIV BX ( After this part, AX is 120 decimal and DX 4 decimal ) CMP DX, 0x0000 JE eq1 ADD CX, 0x0002 JMP con1 eq1: ADD CX, 0x0001 con1:

( note : not the same as this other question since the OP never explicitly specified rounding towards 0 or -Infinity) JLS 15.17.2 says that integer division rounds towards zero. If I want floor() -like behavior for positive divisors (I don't care about the behavior for negative divisors), what's the simplest way to achieve this that is numerically correct for all inputs? int ifloor(int n, int d) { /* returns q such that n = d*q + r where 0 <= r < d * for all integer n, d where d > 0 * * d = 0 should have the same behavior as `n/d` * * nice-to-have behaviors for d < 0: * option (a). same as

I am currently looking into ways of using the fast single-precision floating-point reciprocal capability of various modern processors to compute a starting approximation for a 64-bit unsigned integer division based on fixed-point Newton-Raphson iterations. It requires computation of 2 64 / divisor, as accurately as possible, where the initial approximation must be smaller than, or equal to, the mathematical result, based on the requirements of the following fixed-point iterations. This means this computation needs to provide an underestimate. I currently have the following code, which works