Fortran中随机数据最大值一半的全宽
我有一组高斯随机生成的数据。我获取这些数据的方式并不重要，但它是通过一个带有扩散的粒子代码实现的 我知道python中有一些函数可以做到这一点，但是我不能在每个时间步都将这些数据写入一个文件中，然后进行分析，因为我需要它来进行诊断。因此我需要在代码中计算它 我的代码是用Fortran 95编写的 我需要找到半个最大宽度的数据示例如下（完整数据如下所示） 然而，正如你所看到的，它有点吵 我手工计算出这个长度是Fortran中随机数据最大值一半的全宽,fortran,gfortran,Fortran,Gfortran,我有一组高斯随机生成的数据。我获取这些数据的方式并不重要，但它是通过一个带有扩散的粒子代码实现的 我知道python中有一些函数可以做到这一点，但是我不能在每个时间步都将这些数据写入一个文件中，然后进行分析，因为我需要它来进行诊断。因此我需要在代码中计算它 我的代码是用Fortran 95编写的 我需要找到半个最大宽度的数据示例如下（完整数据如下所示） 然而，正如你所看到的，它有点吵 我手工计算出这个长度是0.00235（因为这是我知道的起始数据，所以这个长度是0.00235482045030
0.002350.00235482045030949533.6编辑：我忘了提到我已经做了西格玛槽的计算：
Sigma = Sum( (x - Av(x))**2 )/N
1.89624932667106 0
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假设为高斯分布，您可以使用平均值和标准偏差计算 示例实现
program main
implicit none
integer :: n
real :: mu, sigma, FWHM
real, allocatable :: x(:)
! read data from file. here we just set some values as an easy example
x = [-2, 0, 5, -10, 3]
! estimator for mean value
n = size(x)
mu = sum(x) / n
! estimator for standard deviation (biased estimator -> divide by (n-1) )
sigma = sqrt(sum((x-mu)**2)/(n-1))
! full-width half maximum is simple scaling of standard deviation
! for Gaussian distribution
FWHM = 2*sqrt(2*log(2.0)) * sigma
end program
假设为高斯分布，您可以使用平均值和标准偏差计算 示例实现
program main
implicit none
integer :: n
real :: mu, sigma, FWHM
real, allocatable :: x(:)
! read data from file. here we just set some values as an easy example
x = [-2, 0, 5, -10, 3]
! estimator for mean value
n = size(x)
mu = sum(x) / n
! estimator for standard deviation (biased estimator -> divide by (n-1) )
sigma = sqrt(sum((x-mu)**2)/(n-1))
! full-width half maximum is simple scaling of standard deviation
! for Gaussian distribution
FWHM = 2*sqrt(2*log(2.0)) * sigma
end program
这回答了你的问题吗？看起来很有希望。我完全忘记了使用插值，也许它会起作用，我会试试。@Gundro插值对嘈杂的数据不好，你需要曲线拟合，就像上一个答案一样。你所说的“它适用于后面的时间步，但不适用于开头”是什么意思？您的系统是否显示瞬态行为，或者您的意思是，对于少量样本大小，错误太大？这是否回答了您的问题？看起来很有希望。我完全忘记了使用插值，也许它会起作用，我会试试。@Gundro插值对嘈杂的数据不好，你需要曲线拟合，就像上一个答案一样。你所说的“它适用于后面的时间步，但不适用于开头”是什么意思？您的系统是否显示瞬态行为，或者您的意思是，对于少量样本大小，误差太大？在Wikipedia中，离散点计算的标准偏差中，它们除以
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