maths.f File Reference

Data Types
interface	meanvar

Functions/Subroutines
real *8 function	fmax3 (x1, x2, x3)
subroutine	cross (ab, a, b)
subroutine	cross4 (ab, a, b)
subroutine	matrix_old (om, rot)
subroutine	matrix_new (om, rot)
subroutine	matrix (om, rot, old)
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

---

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
	)

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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 meanvar::derivative	(	real ( kind=8 )	input,
		real ( kind=8 )	output,
		real ( kind=8 )	dt,
		real ( kind=8 )	opt_factor
	)

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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
	)

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ggnml4_new()

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

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ggubs()

subroutine ggubs

(

unif

)

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least_square()

subroutine meanvar::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 !!

least_square2()

subroutine meanvar::least_square2	(		n,
			X,
			Y,
			a,
			b,
			d,
			r2
	)

same function, but label array from 1 to N

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matrix()

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

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matrix_new()

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

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matrix_old()

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

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meanvar()

subroutine meanvar	(	real(kind=8)	input,
		real(kind=8)	mean,
		real(kind=8)	var
	)

norm()

subroutine simple_derivative::norm

(

real ( kind = 8 )

wa

)

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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
	)

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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
	)

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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
	)

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simple_derivative()

subroutine derivative::simple_derivative	(	real ( kind=8 )	input,
		real ( kind=8 )	output,
		real ( kind=8 )	dt,
		real ( kind=8 )	opt_factor
	)

kind of derivative, simplified version, gives a smoother approximation

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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
	)

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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
	)