本来觉得这程序用途较窄没打算单独发贴，test和管理员建议单独发，所以在这里发出来

原贴  http://www.mdbbs.org/thread-4697-1-1.html

用途是把gmx的g_anaeig加-2d参数得到的数据点分布，转化为图中每个位置数据点出现概率，详见原贴和压缩包内的使用说明




例如g_anaeig得到2d.xvg，如图2d.GIF

压缩包里就有2d.xvg，比如放在ddtpd.exe所在目录下，运行后，输入2d.xvg，例如划分为50*50网格，再输入50 [回车] 50 [回车]，就得到了result.txt，在sigmaplot等软件里作图，调整颜色刻度，得到2d.PNG。蓝色越深，对应着2d.xvg图中数据点越密的地方，说明自由能越低，结构越稳定。

做PCA的有福了

WHY? WHY? 每次Sobereva发点儿好东西，我都看不懂

隔行如隔山，你研究的东西我也肯定不熟悉

a question
could convert into 3-D picture?

the three-dimensional fast Fourier transformation is a very efficient,
The procedure used was the following: the simulation box was split into 32×32×32 equivalent cells, and the corresponding matrix was set up, initially containing 32×32×32 zeros.
If an atom in a model fell into such a cell, the corresponding matrix element
was set to unity; in this way, the atomic density has been represented in a
32×32×32 matrix. Then, a three-dimensional fast Fourier transformation
was carried out. This approach also has the advantage that it is consistent with
the periodic boundary conditions used in the molecular-dynamics simulation,
that is, a sharp peak in the transformed Fourier space (if the absolute value
of a matrix element is close to the number of atoms) means a strong periodic
fluctuation in a particular direction with the corresponding wavelength. This
method has been used for all simulations to study in detail the occurrence and
growth of periodicity during the simulations.
NATURE
ARE THEM SIMILAR?

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sigmaplot中也可以用峰的高低代表密度做成三维的图，
如果你是指的数据点是三维的，用g_anaeig加-3d输出的数据也可以用类似方法转化，得到四列数据。但是三维数据点做图很难观察。