multiplication

问题 I'm looking for a function or solution to the following: For the chart in SQL Reporting i need to multiply values from a Column A. For summation i would use =SUM(COLUMN_A) for the chart. But what can i use for multiplication - i was not able to find a solution so far? Currently i am calculating the value of the stacked column as following: =ROUND(SUM(Fields!Value_Is.Value)/SUM(Fields!StartValue.Value),3) Instead of SUM i need something to multiply the values. Something like that: =ROUND

问题 How to design an algorithm to simulate multiplication by addition. input two integers. they may be zero, positive or negative.. 回答1: def multiply(a, b): if (a == 1): return b elif (a == 0): return 0 elif (a < 0): return -multiply(-a, b) else: return b + multiply(a - 1, b) 回答2: some pseudocode: function multiply(x, y) if abs(x) = x and abs(y) = y or abs(x) <> x and abs(y) <> y then sign = 'plus' if abs(x) = x and abs(y) <> y or abs(x) <> x and abs(y) = y then sign = 'minus' res = 0 for i = 0

问题 There is already a question for this here: How to repeat a string a variable number of times in C++? However because the question was poorly formulated primarily answers about character multiplication were given. There are two correct, but expensive answers, so I'll be sharpening the requirement here. Perl provides the x operator: http://perldoc.perl.org/perlop.html#Multiplicative-Operators which would let me do this: $foo = "0, " x $bar; I understand that I can do this with the helper

问题 Suppose I have an ndarray, W of shape (m,n,n) and a vector C of dimension (m,n). I need to multiply these two in the following way result = np.empty(m,n) for i in range(m): result[i] = W[i] @ C[i] How do I do this in a vectorized way without loops and all? 回答1: Since, you need to keep the first axis from both W and C aligned, while loosing the last axis from them with the matrix-multiplication, I would suggest using np.einsum for a very efficient approach, like so - np.einsum('ijk,ik->ij',W,C

问题 The following code works fine when reading two .txt files containing two 5X5 array. #include <iostream> #include <string> #include <fstream> #include <sstream> #include <stdio.h> #include <vector> #include <sstream> using namespace std; int main() { string myFile, mysecondFile, mystring; string DIR; string extension; int total = 0; int number_of_lines = 0; string line; extension = ".txt"; DIR = "H:\\Year2\\EE273\\EE273\\Week6\\"; cout << "Enter the name of the file: \t"; cin >> myFile; cout <

问题 multiplication of two numbers x*y ----> x =(x0*10^(n/3)+x1*10^(n/3)+x2) and y=(y0*10^(n/3)+y1*10^(n/3)+y2) It is 9 multiplication of 10^n/3 numbers so 9T(n/3) but it can be reduced to 5 by the following method. x*y= x0*y0+x1*y1+x2*y2+x0*y1+x0*y2+x1*y0+x1*y3+x2*y0+x2*y1 I am able to reduce the multiplication of two numbers to 5T(n/3) by similar trick like Karatsuba's algorithm (x0+x1+x2)(y0+y1+y2)-x0*y0-x1*y1-x2*y2= x0*y1+x0*y2+x1*y0+x1*y3+x2*y0+x2*y1 All and all 5 multiplication of n/3 bits

问题 I'm having issues where my multiplication method is only handling one row, it's currently not advancing to the next row. The add function is working properly, and I'm able to update the current hex number, but for some reason I can only get one line of multiplication to work. Example input: 111# * 333# = 333 123# * 123# = 369 Here is the code in question: LList* Calculator::multiply(LList& left, LList& right) { int product, carry = 0, lval = 0, rval = 0, zeros = 0; bool calculating = true;

问题 I am writing an algorithm to find the inverse of an nxn matrix. Let us take the specific case of a 3x3 matrix. When you invert a matrix by hand, you typically look for rows/columns containing one or more zeros to make the determinant calculation faster as it eliminates terms you need to calculate. Following this logic in C/C++, if you identify a row/column with one or more zeros, you will end up with the following code: float term1 = currentElement * DetOf2x2(...); // ^ // This is equal to 0.

问题 Is there an equivalent of dgemm (from BLAS) for integral types? I only know of dgemm, sgemm for double precision / single precision matrices, but would like to have it for matrices that are of integral type such as int (or short int...). Note: I'm not looking for a solution that involves converting to float/double, and am looking for a fast library implementation. Also, same question for dgemms (using strassen algorithm). 回答1: BLAS algorithms don't natively support integer types. 回答2: You did

问题 If I want to take the product of a list of floating point numbers, what's the worst-case/average-case precision lost by adding their logs and then taking exp of the sum as opposed to just multiplying them. Is there ever a case when this is actually more precise? 回答1: Absent any overflow or underflow shenanigans, if a and b are floating-point numbers, then the product a*b will be computed to within a relative error of 1/2 ulp. A crude bound on the relative error after multiplying a chain of N