multiplication

Simimilar problem to Math.Atan2 or class instance problem in C# and add two double given wrong result It is something that simple lines: public static String DegreeToRadianStr(Double degree) { Double piBy180 = (Math.PI / 180); Double Val = (piBy180 * degree); // Here it is giving wrong value } piBy180 * degree = -3.1415926535897931 but Val = -3.1415927410125732 alt text http://www.imagechicken.com/uploads/1262936639009840000.jpg I really have no clue what to do .. Please ask some questions regarding this, so that I can point out where it is going wrong. It is amazing that piBy180 is keeping

I am currently trying to multiply two floats, one that comes from a float vector (address stored in ebx) and against the value I stored in ecx. I have confirmed that the input values are correct, however, if I multiply 32 and 1, for example, the value in EAX changes to 00000000 and the one in EDX to 105F0000. From my understanding of MUL, this happens because it is storing the high order bits of the result in EDX and the low order ones in EDX. Question is, how do I move the result into an output variable (returnValue) ? Here is the code snippet in question: AddColumnsIteration: cmp esi, 4 //

I'm trying to multiply a column by a float. I have the code for it here: if str(cMachineName)==str("K42"): df_temp.loc[:, "P"] *= float((105.0* 59.0*math.pi*0.95/1000)/3540) But it gives me this error: TypeError: can't multiply sequence by non-int of type 'float'. How do I solve it? I think problem is some non numeric values like 45 as string: Solution is converting to float , int by astype : df_temp = pd.DataFrame({'P':[1,2.5,'45']}) print (df_temp['P'].dtype) object df_temp["P"] = df_temp["P"].astype(float) df_temp["P"] *= float((105.0* 59.0*math.pi*0.95/1000)/3540) print (df_temp) P 0 0

Possible Duplicate: How to round a number to n decimal places in Java When multiplying two numbers in java happens this: double a = 9.495 * 100; Expected result: a = 949.5; But the obtained result is: a = 949.4999999999999 When I try to round number 9.495 in two decimal places the result is 9.49 instead of 9.50 Any ideas how to solve this problem? If you want accurate floating point computations, do not use the float or double types, but rather make use of the BigDecimal class. You cannot. Floating point and double precision numbers in a computer cannot represent all possible values. This is a

Is it possible to calculate result of multiplication without using instructions MUL, IMUL, SHL, SHR, LOOP, JMP in x86 assembly language? The following code will multiply the contents of the registers ecx and edx and store the result in register eax . The content of the registers ebx and edx is destroyed: mov ebx, 1 mov eax, 0 repeat: test ecx, ebx jz dontadd add eax, edx dontadd: add edx, edx add ebx, ebx jnz repeat without ... LOOP If "LOOP" does not only cover the "LOOP" instruction but any conditional jump instructions: Doing a multiplication without conditional jump instructions is a bit

I have two numpy arrays: A 1D array called t of shape (70L,) with element called let s say ti A 3D array called I with shape (70L, 1024L, 1024L), with each elements called Ii. Ii are thus of dimension (1024L, 1024L) I would like to make a product of the two array along the first dimension, i.e.: tI = t1*I1,t2*I2,...,tN*IN such as to obtain again a new array of dimension (70L, 1024L, 1024L) and then take the sum along the first dimension in order to obtain an array of dimension (1024L, 1024L): tsum = t1*I1 + t2*I2 + ... +tN*IN For the moment I am satisfied with doing the following: tI = np

I'm using the dataset BreastCancer in the mlbench package, and I am trying to do the following matrix multiplication as a part of logistic regression. I got the features in the first 10 columns, and create a vector of parameters called theta: X <- BreastCancer[, 1:10] theta <- data.frame(rep(1, 10)) Then I did the following matrix multiplication: constant <- as.matrix(X) %*% as.vector(theta[, 1]) However, I got the following error: Error in as.matrix(X) %*% as.vector(theta[, 1]) : requires numeric/complex matrix/vector arguments Do I need to cast the matrix to double using as.numeric(X) first?