multiplication

Suppose I want a code in PHP that replicates matrix multiplication, where my matrices look like: $matrix_1 = array(array(1,2), array(3,4)) The number of subarrays ( 2 ) is equivalent to the number of columns in the matrix, whereas the number of elements in each subarray ( 2 ) represents the number of rows in the matrix. The code would need to: Account for matrices of different dimensions. Recognise when two matrices cannot be multipled (where the number of columns in matrix A is not the same as the number of rows in matrix B). Possibly account for scalar multiplication, where each element of a

Apologies if this is a simple question. I have two dataframes each with the same columns. I need to multiply each row in the second dataframe by the only row in the first. Eventually there will be more columns of different ages so I do not want to just multiply by a scalar. I have used df.multiply() and continue to get NaN for all values presumably because the two df are not matched in length. Is there a way to multiply each row in one dataframe by a singular row in another? age 51200000.0 70000000.0 SFH 0 0.75 0.25 . age 51200000.0 70000000.0 Lambda 91.0 0.000000e+00 0.000000e+00 94.0 0

I am having a really hard time creating a method to raise a matrix to the power. I tried using this public static int powerMethod(int matrix, int power) { int temp = matrix ; for (int i = power; i == 1; i--) temp = temp * matrix ; return temp ; but the return is WAYYY off. Only the first (1,1) matrix element is on point. I tried using that method in a main like so // Multiplying matrices for (i = 0; i < row; i++) { for (j = 0; j < column; j++) { for (l = 0; l < row; l++) { sum += matrix[i][l] * matrix[l][j] ; } matrix[i][j] = sum ; sum = 0 ; } } // Solving Power of matrix for (i = 0; i < row;

I'm trying to convert whatever numbers the user inputs into 2 decimal places. For instance What is the total cost in cents? 2345 output: 23.45 this is the code i have so far percentage=20 #cannot change numerical value must convert into 0.20 echo -n "What is the total cost? "; read cost_in_cents echo "scale 1; $cost_in_cents" | bc I'm also going to be doing some multiplication with percentage, how can i also convert the percentage into a float (0.20) Perhaps it's nostalgia for reverse polish notation desk calculators, but I'd use dc rather than bc here: dc <<<"2 k $cost_in_cents 100 / p"

If I multiplie two 16-bit numbers, the result will be 32-bit long. But why is this so? What is the clear explanation for this? And for my right understanding: The calculation for this is: n-bit number multiplied with a m-bit number gives a (n+m) bit number? (2 n - 1)*(2 m - 1) = 2 n+m - 2 n - 2 m + 1 -(2 n + 2 m ) is like clearing the bits at index n and m , which does not affect much the result compared to 2 n+m , so you need n+m bits to represent the result. For example 1111 2 *1111 2 = 11100001 2 (15*15 = 225) In general, (b n - 1)*(b m - 1) = b n+m - b n - b m + 1 , so multiply an n-digit

I'm pretty sure I'm being stupid but why isn't this working!? form.find( '.per_time' ).on( 'change', function() { var price = parseInt( form.find( '.section-price' ).attr('data-price'), 10 ) ; var multiplier = parseInt( $( this ).val(), 10 ); var newprice = (price / 7) * multiplier; form.find( '.section-price .price' ).html( newprice ) }) It's this line I'm concerned about: var newprice = (price / 7) * multiplier; The calculation is not dividing by 7, it only calculates price * multiplier ? This code also seems to be dictating what happens but I'm pretty sure it's jsut a shorter version of the

In my code I have this multiplications in a C++ code with all variable types as double[] f1[0] = (f1_rot[0] * xu[0]) + (f1_rot[1] * yu[0]); f1[1] = (f1_rot[0] * xu[1]) + (f1_rot[1] * yu[1]); f1[2] = (f1_rot[0] * xu[2]) + (f1_rot[1] * yu[2]); f2[0] = (f2_rot[0] * xu[0]) + (f2_rot[1] * yu[0]); f2[1] = (f2_rot[0] * xu[1]) + (f2_rot[1] * yu[1]); f2[2] = (f2_rot[0] * xu[2]) + (f2_rot[1] * yu[2]); corresponding to these values Force Rot1 : -5.39155e-07, -3.66312e-07 Force Rot2 : 4.04383e-07, -1.51852e-08 xu: 0.786857, 0.561981, 0.255018 yu: 0.534605, -0.82715, 0.173264 F1: -6.2007e-07, -4.61782e-16,