拉丁超立方采样(Latin Hypercube Sampling, LHS)是一种统计采样技术,用于生成一组样本点,这些样本点在参数空间中均匀分布,并且满足每个维度只有一个样本点落在该维度的取值范围内。LHS常用于参数优化和模型验证等领域。在Python中,有几种常用的包可以进行拉丁超立方采样,下面介绍两种常用的方法。1. 使用pyDOE2包pyDOE2...
拉丁超立方体抽样Latin hypercube sampling说明[转] LifeBug:03.随机变量和3F(PDF、CDF、PMF)
在这个改写后的代码中,latin_hypercube_sampling函数使用了最大最小思想进行优化的拉丁超立方采样,生成了指定数量和维度的采样点。variable_to_binary_array函数将每个变量转换为指定位数的二进制数组。然后,我们可以使用生成的采样点进行后续操作。
Simple implementation of Latin Hypercube Sampling. numpydesign-of-experimentslatin-hypercube-samplingspace-filling-designs UpdatedApr 18, 2023 Python Spogis/DWSIMChemDesign Sponsor Star6 Code Issues Pull requests Discussions ChemDesign: DWSIM Experiment Toolkit ...
I am attempting to take into account the interaction among 5 different parameters in aLatin hypercube designin Python 3.8. However, I can't understand how, probably also because - not being my field - I never used these methods. I initially posted this on Stack Overflow, but it seems...
mcerp Python Package Code: https://github.com/tisimst/mcerp Documentation: (not online yet, for now, see the doc folder on Github) License: BSD-3-Clause Overview mcerp is a stochastic calculator for Monte Carlo methods that uses latin-hypercube sampling to perform non-order specific error pro...
拉丁超立方采样是一种特殊的采样方法，用于改进蒙特卡洛模拟中的随机抽样。它通过将样本空间分层，然后在每层内随机抽样，最后将样本打乱顺序，得到结果。相比于随机抽样，拉丁超立方采样在复杂分布场景下的效率更高，能够更均匀地覆盖样本空间，尤其是在正态分布等复杂分布的情况下。拉丁超立方采样的主要优点...
(2013). Latin Hypercube Sampling. In: Dubitzky, W., Wolkenhauer, O., Cho, KH., Yokota, H. (eds) Encyclopedia of Systems Biology. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-9863-7_100756 Download citation .RIS .ENW .BIB DOIhttps://doi.org/10.1007/978-1-4419-...
探索未知的科学殿堂，拉丁超立方采样（Latin Hypercube Sampling, LHS）与蒙特卡洛模拟如同夜空中的璀璨星辰，照亮了处理不确定性问题的迷雾。蒙特卡洛，这个名字本身就蕴含着一种随机的魔力，它通过海量的模拟实验，为我们揭示概率世界的奥秘，哪怕是看似简单的抛硬币游戏，也能借此估算出五次投掷中出现一次...
by Latin Hypercube Sampling, the optimal solutions found by IPOPT in each subspace are added to the sampling set. LHS is performed with the pyDOE (v0.3.8) package in python and R(R Core Team, 2016) package ‘lhs’(Carnell, 2016) via Python-R interface ‘RPy2’ (v2.8.5) in python....