epsilon

问题 Why doesn't Decimal data type have Epsilon field? From the manual, the range of decimal values is ±1.0 × 10e−28 to ±7.9 × 10e28. The description of Double.Epsilon: Represents the smallest positive Double value greater than zero So it seems, Decimal has such a (non-trivial) value too. But why isn't it easily accessible? I do understand that +1.0 × 10e−28 is exactly the smallest positive Decimal value greater than zero: decimal Decimal_Epsilon = new decimal(1, 0, 0, false, 28); //1e-28m; By the

问题 I wanted to calculate the machine Epsilon, the smallest possible number e that gives 1 + e > 1 using different data types of C++: float , double and long double . Here's my code: #include <cstdio> template<typename T> T machineeps() { T epsilon = 1; T expression; do { epsilon = epsilon / 2; expression = 1 + epsilon; } while(expression > 1); return epsilon; } int main() { auto epsf = machineeps<float>(); auto epsd = machineeps<double>(); auto epsld = machineeps<long double>(); std::printf(

问题 Is there a standard value for (or method for obtaining) epsilon in Python? I need to compare floating point values and want to compare against the smallest possible difference. In C++ there's a function provided numeric_limits::epsilon( ) which gives the epsilon value for any given data type. Is there an equivalent in Python? 回答1: The information is available in sys.float_info, which corresponds to float.h in C99. >>> import sys >>> sys.float_info.epsilon 2.220446049250313e-16 回答2: As strcat

问题 Doing function that takes 2 arrays (column1 and column2) from struct CSV D and plots the graph from it. Idea is to find max, min values of each array, then break range between min−EPSILON and max+EPSILON in to 600 equal regions, where EPSILON = 10^(−6) Problem is that function does not plot the lowest line properly, I think the issue is when comparing the value from array with min-EPSILON , not sure. Please advice. Here's my code. void do_plot(CSV *D, int column1, int column2) { #define Y

问题 Doing function that takes 2 arrays (column1 and column2) from struct CSV D and plots the graph from it. Idea is to find max, min values of each array, then break range between min−EPSILON and max+EPSILON in to 600 equal regions, where EPSILON = 10^(−6) Problem is that function does not plot the lowest line properly, I think the issue is when comparing the value from array with min-EPSILON , not sure. Please advice. Here's my code. void do_plot(CSV *D, int column1, int column2) { #define Y

问题 My team is working with financial software that exposes monetary values as C# floating point doubles. Occasionally, we need to compare these values to see if they equal zero, or fall under a particular limit. When I noticed unexpected behavior in this logic, I quickly learned about the rounding errors inherent in floating point doubles (e.g. 1.1 + 2.2 = 3.3000000000000003). Up until this point, I have primarily used C# decimals to represent monetary values. My team decided to resolve this

问题 When I set epsilon=10e-8 , AdamOptimizer doesn't work. When I set it to 1, it works just fine. 回答1: t <- t + 1 lr_t <- learning_rate * sqrt(1 - beta2^t) / (1 - beta1^t) m_t <- beta1 * m_{t-1} + (1 - beta1) * g v_t <- beta2 * v_{t-1} + (1 - beta2) * g * g where g is gradient variable <- variable - lr_t * m_t / (sqrt(v_t) + epsilon) The epsilon is to avoid divide by zero error in the above equation while updating the variable when the gradient is almost zero. So, ideally epsilon should be a

问题 Is there a "best practice" for less-than-equal comparisons with floating point number after a series of floating-point arithmetic operations? I have the following example in R (although the question applies to any language using floating-point). I have a double x = 1 on which I apply a series of additions and subtractions. In the end x should be exactly one but is not due to floating-point arithmetic (from what I gather). Here is the example: > stop_times <- seq(0.25, 2, by = .25) > expr <-

问题 http://msdn.microsoft.com/en-us/library/system.double.epsilon.aspx If you create a custom algorithm that determines whether two floating-point numbers can be considered equal, you must use a value that is greater than the Epsilon constant to establish the acceptable absolute margin of difference for the two values to be considered equal. (Typically, that margin of difference is many times greater than Epsilon.) So is this not really an epsilon that could be used for comparisons? I don't

问题 After a bit of light reading, this article piqued my interest: I'd have thought that yes, the two statements are equivalent, given MSDN's statement: Represents the smallest positive Double value that is greater than zero. This field is constant. Curious to see what people think. EDIT: Found a computer with VS on and ran this Test. Turns out that yes, as expected, they're equivalent. [Test] public void EpsilonTest() { Compare(0d); Compare(double.Epsilon); Compare(double.Epsilon * 0.5); Compare