atomic_distance_density_class2

esta.plot.atomic_distance_density_class2

atom_distance_density

script to calculate the atomic distance density 
for a specific bond of atoms in the POSCAR file

A Gaussian distribution function is used for the delta function:

The probability density for the Gaussian distribution is

p(x) = rac{1}{\sqrt{ 2 \pi \sigma^2 }} e^{ - rac{ (x - \mu)^2 } {2 \sigma^2} },

where \mu is the mean and \sigma the standard deviation. 
The square of the standard deviation, \sigma^2, is called the variance.

The function has its peak at the mean, and its “spread” increases with 
the standard deviation (the function reaches 0.607 times its maximum 
at x + \sigma and x - \sigma [2]). This implies that numpy.random.normal 
is more likely to return samples lying close to the mean, rather than 
those far away.

Parameters/Inputs

x : ?

Returns

`atomic distance density` array  and distance
array are returned.

See Also

--------

add other related things here.

Notes

-----

Examples

--------

dos(array_distribution, sigma)

Now calculation of atomic distance density