natural-logarithm

How to apply a natural logarithm to a matrix and obtain zero for when the matrix entry is zero

由 走远了吗. 提交于 2021-02-11 12:47:24
问题 In Python I have a Matrix with some zero values, how can I apply a natural logarithm and obtain zero for when the matrix entry is zero? I am using numpy.log(matrix) to apply the natural logarithm function, but I am getting nan when the matrix entry is equal to zero, and I would like it to be zero instead 回答1: You can do something like this: arr = numpy.nan_to_num(numpy.log(matrix)) The behavior of nan_to_num replaces all the NaNs by zeroes. You can find more information here: https://docs

R: Exponent returning infinity

由 只谈情不闲聊 提交于 2020-08-12 01:29:28
问题 I need to remove logarithms of my data and thus am taking e to the power of the values which are logarithmed. My issue is that when I have e to the power of more than 709 R returns the value of infinity. How can I surpass this? e^710 [1] Inf Thanks :) 回答1: If you really want to work with numbers that big you can use a Rmpfr package. library('Rmpfr') x <- mpfr(710, precBits = 106) exp(x) 1 'mpfr' number of precision 106 bits [1] 2.233994766161711031253644458116e308 来源： https://stackoverflow

Logarithm with SSE, or switch to FPU?

由 ∥☆過路亽．° 提交于 2019-12-30 08:23:21
问题 I'm doing some statistics calculations. I need them to be fast, so I rewrote most of it to use SSE. I'm pretty much new to it, so I was wondering what the right approach here is: To my knowledge, there is no log2 or ln function in SSE, at least not up to 4.1, which is the latest version supported by the hardware I use. Is it better to: extract 4 floats, and do FPU calculations on them to determine enthropy - I won't need to load any of those values back into SSE registers, just sum them up to

How to calculate log(sum of terms) from its component log-terms

由 萝らか妹 提交于 2019-12-23 15:14:12
问题 (1) The simple version of the problem: How to calculate log(P1+P2+...+Pn), given log(P1), log(P2), ..., log(Pn), without taking the exp of any terms to get the original Pi. I don't want to get the original Pi because they are super small and may cause numeric computer underflow. (2) The long version of the problem: I am using Bayes' Theorem to calculate a conditional probability P(Y|E). P(Y|E) = P(E|Y)*P(Y) / P(E) I have a thousand probabilities multiplying together. P(E|Y) = P(E1|Y) * P(E2|Y

How do you do natural logs (e.g. “ln()”) with numpy in Python?

由 霸气de小男生 提交于 2019-12-09 04:27:44
问题 Using numpy, how can I do the following: ln(x) Is it equivalent to: np.log(x) I apologise for such a seemingly trivial question, but my understanding of the difference between log and ln is that ln is logspace e? 回答1: np.log is ln , whereas np.log10 is your standard base 10 log. Relevant documentation: http://docs.scipy.org/doc/numpy/reference/generated/numpy.log.html http://docs.scipy.org/doc/numpy/reference/generated/numpy.log10.html 回答2: Correct, np.log(x) is the Natural Log (base e log)

Logarithm computing without math.h

由 那年仲夏 提交于 2019-12-07 09:07:32
问题 I'm trying to compute ln(x) by Taylor series. Here is my code: #define N 10 float ln(float x){ int i; float result; float xt; float xtpow; int sign; if(x > 0 && x <= 1){ xt = x - 1.0; sign = -1; xtpow = 1.0; result = 0; for(i = 1 ; i < N + 1; i++ ); { // Problem here printf("%d\n", i); sign = sign * (-1); xtpow *= xt; result += xtpow * sign / i; } }else if(x >= 1) { return -1 * ln(1.0 / x); } return result; } The problem is with my series cycle(see above). It seems like after 1 cycle variable

ln (Natural Log) in Python

由 本小妞迷上赌 提交于 2019-12-07 06:33:45
问题 In this assignment I have completed all the problems except this one. I have to create a python script to solve an equation (screenshot). Unfortunately, in my research all over the internet I cannot figure out how in the world to either convert ln to log or anything usable, or anything. The code I have written so far is below. I will also post the answer that our teacher says we should get. import math p = 100 r = 0.06 / 12 FV = 4000 n = str(ln * ((1 + (FV * r) / p) / (ln * (1 + r)))) print (

Logarithm computing without math.h

由 做~自己de王妃 提交于 2019-12-05 11:50:07
I'm trying to compute ln(x) by Taylor series. Here is my code: #define N 10 float ln(float x){ int i; float result; float xt; float xtpow; int sign; if(x > 0 && x <= 1){ xt = x - 1.0; sign = -1; xtpow = 1.0; result = 0; for(i = 1 ; i < N + 1; i++ ); { // Problem here printf("%d\n", i); sign = sign * (-1); xtpow *= xt; result += xtpow * sign / i; } }else if(x >= 1) { return -1 * ln(1.0 / x); } return result; } The problem is with my series cycle(see above). It seems like after 1 cycle variable i becomes equal N + 1 , and nothing going on after it. Have you any ideas why it is so? It seems like

How do you do natural logs (e.g. “ln()”) with numpy in Python?

由 一个人想着一个人 提交于 2019-12-03 01:58:47
Using numpy, how can I do the following: ln(x) Is it equivalent to: np.log(x) I apologise for such a seemingly trivial question, but my understanding of the difference between log and ln is that ln is logspace e? JoshAdel np.log is ln , whereas np.log10 is your standard base 10 log. Relevant documentation: http://docs.scipy.org/doc/numpy/reference/generated/numpy.log.html http://docs.scipy.org/doc/numpy/reference/generated/numpy.log10.html Correct, np.log(x) is the Natural Log (base e log) of x . For other bases, remember this law of logs: log-b(x) = log-k(x) / log-k(b) where log-b is the log

Does scipy logsumexp() deal with the underflow challenge?

由 倾然丶 夕夏残阳落幕 提交于 2019-12-01 18:29:06
问题 Does the scipy's logsumexp() implementation include the hack that prevents underflow by subtracting the maximum found value in the array from each element? The one explained here below, where m = maxval : 回答1: You can inspect the source code defining logsumexp here. (Note that there is a link to the source on the doc page). You'll see: a_max = a.max(axis=0) ... out = log(sum(exp(a - a_max), axis=0)) So yes, scipy's logsumexp is subtracting the maximum from each element. 来源： https:/
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