maths.f File Reference

Functions/Subroutines
real *8 function	fmax3 (x1, x2, x3)
subroutine	cross (ab, a, b)
subroutine	cross4 (ab, a, b)
subroutine	matrix (om, rot)
subroutine	tr (vo, vn, ex, ey, ez)
subroutine	tr4 (vo, vn, ex, ey, ez)
subroutine	tr_vector (vo, vn, ex, ey, ez, nat)
subroutine	dot (ab, a, b)
subroutine	rotate31 (c, rot, b)
subroutine	rotate3n (c, rot, b, n)
subroutine	rotate33 (c, rot, b)
real(kind=8) function	determinant (mat)
subroutine	ggnml (n, gaus)
subroutine	ggnml4_new (n, gaus)
subroutine	ggubs (unif)
subroutine	meanvar (input, mean, var)
subroutine	least_square (n, X, Y, a, b, d, r2)
	Linear least square. The input data set is X(m), Y(m). The number of data points is n (n must be > 2). The returned parameters are: a,b, coefficients of equation Y = a + b X, and d, standard deviation of fit. original function label array from 0 to n-1 !! More...
subroutine	least_square2 (n, X, Y, a, b, d, r2)
	same function, but label array from 1 to N More...
subroutine	derivative (input, output, dt, opt_factor)
subroutine	simple_derivative (input, output, dt, opt_factor)
	kind of derivative, simplified version, gives a smoother approximation More...
subroutine	norm (wa)

Detailed Description

Version

{version 7.2.3 (2019)}

Copyright (c) 2009, 2010, 2015, 2016, 2019 Heidelberg Institute of Theoretical Studies (HITS, www.h-its.org) Schloss-Wolfsbrunnenweg 35 69118 Heidelberg, Germany

Please send your contact address to get information on updates and new features to "mcmsoft@h-its.org". Questions will be answered as soon as possible.

References: see also http://mcm.h-its.org/sda7/do:c/doc_sda7/references.html:

Brownian dynamics simulation of protein-protein diffusional encounter. (1998) Methods, 14, 329-341.

SDA 7: A modular and parallel implementation of the simulation of diffusional association software. Journal of computational chemistry 36.21 (2015): 1631-1645.

Authors: M.Martinez, N.J.Bruce, J.Romanowska, D.B.Kokh, P.Mereghetti, X. Yu, M. Ozboyaci, M. Reinhardt, P. Friedrich, R.R.Gabdoulline, S.Richter and R.C.Wade

---

group general mathematical functions

Function/Subroutine Documentation

cross()

subroutine cross	(	real ( kind=8 ), dimension ( 3 ), intent(out)	ab,
		real ( kind=8 ), dimension ( 3 ), intent(in)	a,
		real ( kind=8 ), dimension ( 3 ), intent(in)	b
	)

Here is the caller graph for this function:

cross4()

subroutine cross4	(	real ( kind=4 ), dimension ( 3 ), intent(out)	ab,
		real ( kind=4 ), dimension ( 3 ), intent(in)	a,
		real ( kind=4 ), dimension ( 3 ), intent(in)	b
	)

derivative()

subroutine derivative	(	real ( kind=8 ), dimension(:), intent(in)	input,
		real ( kind=8 ), dimension(:), intent(out)	output,
		real ( kind=8 )	dt,
		real ( kind=8 ), optional	opt_factor
	)

Here is the caller graph for this function:

determinant()

real ( kind=8 ) function determinant

(

real ( kind=8 ), dimension(3,3), intent(in)

mat

)

dot()

subroutine dot	(	real(kind=8), intent(out)	ab,
		real(kind=8), dimension(3), intent(in)	a,
		real(kind=8), dimension(3), intent(in)	b
	)

fmax3()

real*8 function fmax3	(		x1,
			x2,
			x3
	)

ggnml()

subroutine ggnml	(		n,
		dimension(3)	gaus
	)

Here is the caller graph for this function:

ggnml4_new()

subroutine ggnml4_new	(	integer	n,
		real ( kind=4 ), dimension ( n )	gaus
	)

Here is the caller graph for this function:

ggubs()

subroutine ggubs

(

unif

)

Here is the caller graph for this function:

least_square()

subroutine least_square	(	integer	n,
		real ( kind=8 ), dimension (n), intent(in)	X,
		real ( kind=8 ), dimension (n), intent(in)	Y,
		real*8	a,
		real*8	b,
		real*8	d,
		real*8	r2
	)

Linear least square.
The input data set is X(m), Y(m).
The number of data points is n (n must be > 2).
The returned parameters are:
a,b, coefficients of equation
Y = a + b X, and d, standard deviation of fit.
original function label array from 0 to n-1 !!

Here is the call graph for this function:

least_square2()

subroutine least_square2	(	integer, intent(in)	n,
		real ( kind=8 ), dimension (n), intent(in)	X,
		real ( kind=8 ), dimension (n), intent(in)	Y,
		real ( kind=8 ), intent(out)	a,
		real ( kind=8 ), intent(out)	b,
		real ( kind=8 ), intent(out)	d,
		real ( kind=8 ), intent(out)	r2
	)

same function, but label array from 1 to N

Here is the call graph for this function:

Here is the caller graph for this function:

matrix()

subroutine matrix	(	real ( kind=8 ), dimension ( 3 ), intent(in)	om,
		real ( kind=8 ), dimension ( 3,3 ), intent(out)	rot
	)

Here is the caller graph for this function:

meanvar()

subroutine meanvar	(	real(kind=8), dimension(:), intent(in)	input,
		real(kind=8), intent(out)	mean,
		real(kind=8), intent(out)	var
	)

Here is the caller graph for this function:

norm()

subroutine norm

(

real ( kind = 8 ), dimension ( 3 )

wa

)

Here is the caller graph for this function:

rotate31()

subroutine rotate31	(	real (kind=8 ), dimension(3), intent(out)	c,
		real( kind=8 ), dimension(3,3), intent(in)	rot,
		real (kind=8 ), dimension(3), intent(in)	b
	)

Here is the caller graph for this function:

rotate33()

subroutine rotate33	(	real (kind=8 ), dimension(3,3), intent(out)	c,
		real( kind=8 ), dimension(3,3), intent(in)	rot,
		real (kind=8 ), dimension(3,3), intent(in)	b
	)

Here is the call graph for this function:

Here is the caller graph for this function:

rotate3n()

subroutine rotate3n	(	real (kind=8 ), dimension(3,n), intent(out)	c,
		real( kind=8 ), dimension(3,3), intent(in)	rot,
		real (kind=8 ), dimension(3,n), intent(in)	b,
		integer	n
	)

Here is the call graph for this function:

simple_derivative()

subroutine simple_derivative	(	real ( kind=8 ), dimension(:), intent(in)	input,
		real ( kind=8 ), dimension(:), intent(out)	output,
		real ( kind=8 )	dt,
		real ( kind=8 ), optional	opt_factor
	)

kind of derivative, simplified version, gives a smoother approximation

Here is the caller graph for this function:

tr()

subroutine tr	(	real( kind=8 ), dimension( 3 ), intent(in)	vo,
		real ( kind=8 ), dimension ( 3 ), intent(out)	vn,
		real( kind=8 ), dimension( 3 ), intent(in)	ex,
		real( kind=8 ), dimension( 3 ), intent(in)	ey,
		real( kind=8 ), dimension( 3 ), intent(in)	ez
	)

Here is the caller graph for this function:

tr4()

subroutine tr4	(	real ( kind = 4 ), dimension ( 3 )	vo,
		real ( kind = 4 ), dimension ( 3 )	vn,
		real ( kind = 8 ), dimension ( 3 )	ex,
		real ( kind = 8 ), dimension ( 3 )	ey,
		real ( kind = 8 ), dimension ( 3 )	ez
	)

tr_vector()

subroutine tr_vector	(	real ( kind = 8 ), dimension ( 3,nat ), intent(in)	vo,
		real ( kind = 8 ), dimension ( 3,nat ), intent(out)	vn,
		real ( kind = 8 ), dimension ( 3 ), intent(in)	ex,
		real ( kind = 8 ), dimension ( 3 ), intent(in)	ey,
		real ( kind = 8 ), dimension ( 3 ), intent(in)	ez,
		integer, intent(in)	nat
	)