precision

问题 I was playing around with generating Hamming numbers in Haskell, trying to improve on the obvious (pardon the naming of the functions) mergeUniq :: Ord a => [a] -> [a] -> [a] mergeUniq (x:xs) (y:ys) = case x `compare` y of EQ -> x : mergeUniq xs ys LT -> x : mergeUniq xs (y:ys) GT -> y : mergeUniq (x:xs) ys powers :: [Integer] powers = 1 : expand 2 `mergeUniq` expand 3 `mergeUniq` expand 5 where expand factor = (factor *) <$> powers I noticed that I can avoid the (slower) arbitrary precision

问题 I was playing around with generating Hamming numbers in Haskell, trying to improve on the obvious (pardon the naming of the functions) mergeUniq :: Ord a => [a] -> [a] -> [a] mergeUniq (x:xs) (y:ys) = case x `compare` y of EQ -> x : mergeUniq xs ys LT -> x : mergeUniq xs (y:ys) GT -> y : mergeUniq (x:xs) ys powers :: [Integer] powers = 1 : expand 2 `mergeUniq` expand 3 `mergeUniq` expand 5 where expand factor = (factor *) <$> powers I noticed that I can avoid the (slower) arbitrary precision

问题 I have encountered a topic regarding to calculation errors on Accuracy problems . I end up with the following values in one of my queries in PostgreSQL: 1.0752688172043 (when using float) 1.07526881720430110000 (when using numeric) 1) So, for these values I think I should use numeric data type in order to obtain result more accurately. Is that right? 2) What if the following values (assume that the rest digits after the last number is 0). In that case should I still use numeric rather than

问题 Closed . This question needs to be more focused. It is not currently accepting answers. Want to improve this question? Update the question so it focuses on one problem only by editing this post. Closed 2 years ago . How to deal with floating point arithmetic in Rust? For example: fn main() { let vector = vec![1.01_f64, 1.02, 1.03, 1.01, 1.05]; let difference: Vec<f64> = vector.windows(2).map(|slice| slice[0] - slice[1]).collect(); println!("{:?}", difference); } Returns: [-0

问题 I trained a basic FFNN on a example breast cancer dataset. For the results the precision_recall_curve function gives datapoints for 416 different thresholds. My Data contains 569 unique prediction values, as far as I understand the Precision Recall Curve I could apply 568 different threshold values and check the resulting Precision and Recall. But how do I do so? is there a way to set the number of thresholds to test with sklearn ? Or at least an explanation of how sklearn selects those

问题 I often end up in situations where it is necessary to check if the obtained difference is above machine precision. Seems like for this purpose R has a handy variable: .Machine$double.eps . However when I turn to R source code for guidelines about using this value I see multiple different patterns. Examples Here are a few examples from stats library: t.test.R if(stderr < 10 *.Machine$double.eps * abs(mx)) chisq.test.R if(abs(sum(p)-1) > sqrt(.Machine$double.eps)) integrate.R rel.tol < max(50*

问题 I often end up in situations where it is necessary to check if the obtained difference is above machine precision. Seems like for this purpose R has a handy variable: .Machine$double.eps . However when I turn to R source code for guidelines about using this value I see multiple different patterns. Examples Here are a few examples from stats library: t.test.R if(stderr < 10 *.Machine$double.eps * abs(mx)) chisq.test.R if(abs(sum(p)-1) > sqrt(.Machine$double.eps)) integrate.R rel.tol < max(50*

问题 That floating point numbers in PHP are inaccurate is well known (http://php.net/manual/de/language.types.float.php), however I am a bit unsatisfied after the following experiment: var_dump((2.30 * 100)); // float(230) var_dump(round(2.30 * 100)); // float(230) var_dump(ceil(2.30 * 100)); // float(230) var_dump(intval(2.30 * 100)); // int(229) var_dump((int)(2.30 * 100)); // int(229) var_dump(floor(2.30 * 100)); // float(229) The internal representation must be something like 229.999998 . var

问题 I am trying to implement emulated double-precision in GLSL, and I observe a strange behaviour difference leading to subtle floating point errors in GLSL. Consider the following fragment shader, writing to a 4-float texture to print the output. layout (location = 0) out vec4 Output uniform float s; void main() { float a = 0.1f; float b = s; const float split = 8193.0; // = 2^13 + 1 float ca = split * a; float cb = split * b; float v1a = ca - (ca - a); float v1b = cb - (cb - b); Output = vec4(a

问题 I am trying to implement emulated double-precision in GLSL, and I observe a strange behaviour difference leading to subtle floating point errors in GLSL. Consider the following fragment shader, writing to a 4-float texture to print the output. layout (location = 0) out vec4 Output uniform float s; void main() { float a = 0.1f; float b = s; const float split = 8193.0; // = 2^13 + 1 float ca = split * a; float cb = split * b; float v1a = ca - (ca - a); float v1b = cb - (cb - b); Output = vec4(a