floating-point

问题 My input file has the form: 5.0, 1000.0, 100000000000000.0, 115.2712, 230.538, 345.796, 461.0408, 1.053E-09, 1.839E-09, 1.632E-10, 1.959E-12, 4.109, 3.683, 3.586, 3.650 where every number is essentially in a line. What I want to do is read all the floats, and then append only columns 7 through 10 to an array. Here's what I've written: T=[] with open("test.txt", "r") as file1: for line in file1.readlines(): f_list = [float(i) for i in line.split(",")] T.append(float(f_list[7])) T.append(float

问题 I'm looking to build a browser multiplayer game using rollback netcode that runs a deterministic simulation on the clients. I prototyped the netcode in Flash already before I ran into the floating point roadblock. Basically, from what I understand, integer math in Flash is done by casting int s to Number s, doing the math, then casting back to int . It's faster apparently, but it means that there's no chance of deterministic math across different computer architectures. Before I dump all my

问题 I'm looking to build a browser multiplayer game using rollback netcode that runs a deterministic simulation on the clients. I prototyped the netcode in Flash already before I ran into the floating point roadblock. Basically, from what I understand, integer math in Flash is done by casting int s to Number s, doing the math, then casting back to int . It's faster apparently, but it means that there's no chance of deterministic math across different computer architectures. Before I dump all my

问题 Consider the following function that computes the integral or floating-point modulo depending on the argument type, at compile-time: template<typename T> constexpr T modulo(const T x, const T y) { return (std::is_floating_point<T>::value) ? (x < T() ? T(-1) : T(1))*((x < T() ? -x : x)-static_cast<long long int>((x/y < T() ? -x/y : x/y))*(y < T() ? -y : y)) : (static_cast<typename std::conditional<std::is_floating_point<T>::value, int, T>::type>(x) %static_cast<typename std::conditional<std:

问题 Assume we have a long array of doubles, say, N == 1000000 . array<double, N> arr; There are two naive approaches to compute the average. First double result = 0; for (double x : arr) { result += x; } result /= arr.size(); This may be inaccurate when the sum of values is very big. Floating point numbers lose precision then. Another approach is: double result = 0; for (double x : arr) { result += x / arr.size(); } This may lose precision when the numbers are small. Is there any fail-safe way to

问题 I have a C++ program that takes in values and prints out values like this: getline(in,number); cout << setw(10) << number << endl; I have an equivalent C program that takes in values and prints out like so: fscanf(rhs, "%e", &number); printf("%lf\n", number); But while the C++ program prints out, 0.30951 the C program prints out 0.309510 . More examples: C++: 0.0956439 C: 0.095644 . It seems to print the same results as long as the value is 7 digits long, but if its shorter the 7 digits, it

问题 I have a C++ program that takes in values and prints out values like this: getline(in,number); cout << setw(10) << number << endl; I have an equivalent C program that takes in values and prints out like so: fscanf(rhs, "%e", &number); printf("%lf\n", number); But while the C++ program prints out, 0.30951 the C program prints out 0.309510 . More examples: C++: 0.0956439 C: 0.095644 . It seems to print the same results as long as the value is 7 digits long, but if its shorter the 7 digits, it

问题 Is there any way to get correct rounding with the i387 fsqrt instruction?... ... aside from changing the precision mode in the x87 control word - I know that's possible, but it's not a reasonable solution because it has nasty reentrancy-type issues where the precision mode will be wrong if the sqrt operation is interrupted. The issue I'm dealing with is as follows: the x87 fsqrt opcode performs a correctly-rounded (per IEEE 754) square root operation in the precision of the fpu registers,

问题 Is there any way to get correct rounding with the i387 fsqrt instruction?... ... aside from changing the precision mode in the x87 control word - I know that's possible, but it's not a reasonable solution because it has nasty reentrancy-type issues where the precision mode will be wrong if the sqrt operation is interrupted. The issue I'm dealing with is as follows: the x87 fsqrt opcode performs a correctly-rounded (per IEEE 754) square root operation in the precision of the fpu registers,

问题 I'm currently doing distance calculations between coordinates and have been getting slightly different results depending on the language used. Part of the calculation is taking calculating the cosine of a given radian . I get the following results // cos(0.8941658257446736) // 0.6261694290123146 node // 0.6261694290123146 rust // 0.6261694290123148 go // 0.6261694290123148 python // 0.6261694290123148 swift // 0.6261694290123146 c++ // 0.6261694290123146 java // 0.6261694290123147 c I would