Graph plotting in Fortran FTN95

[@Che.Castor]

This is a very useful class. Thank you very much.

[@shivamsinghaswal303]

Wow.. Thanks sir

[@shivakumarnatrajan]

Wow..... Fortran graphics man

[@fethennourskender9159]

thank you for the useful class sir, i have a question
how i do an animation to graph eich set time?
and thank you

[@hectorflorespauner3404]

very nice tutorial, could you please post all the documentation about the winio@ functions and all that stuff so we can customize more the plot, thanks in advance.

[@kspowerconsultinglimited9873]

The documentation can be found online at the following parts of the Silverfrost website:
silverfrost.com/ftn95-help/clearwinp/clearwin.aspx
silverfrost.com/ftn95-help/clearwinp/formats/helpcontents1.aspx
silverfrost.com/ftn95-help/clearwinp/library/helpcontents1.aspx
silverfrost.com/ftn95-help/clearwinp/callback/helpcontents1.aspx

[@FabioLima-pc2dk]

Could you, please, give a link for downloading this demo program? Thank you in advance. Fabio

[@kspowerconsultinglimited9873]

The code is at the end of the video description above.

[@FabioLima-pc2dk]

Ah, ok, I've found it. Thanks again, very useful.

[@FabioLima-pc2dk]

My interest is on a program that plots a given set of (xi,yi) points and the straight-line representing the linear regression (best linear fit). Do you have a such program?

[@kspowerconsultinglimited9873]

@@FabioLima-pc2dk Try the following. No guarantee it's error free!
program linreg_example
implicit none
integer, parameter :: dp = kind (0.1d0)
integer, parameter :: n = 10
real(dp) :: x(n), y(n)
! Define test data - this is a quadratic
x = (/0,1,2,3,4,5,6,7,8,9/)
y = x*x
! Do the analysis and plot the results
call pllinreg (x, y, n)
end program linreg_example
subroutine pllinreg (x, y, n)
use clrwin
implicit none
integer, parameter :: dp = kind (0.1d0)
integer, intent(in) :: n ! No of elements in x and y
real(dp),intent(in) :: x(n) ! X array
real(dp),intent(in) :: y(n) ! Y array
real(dp) m,b,r
real(dp) xlin(2),ylin(2)
integer iw, gx, gy
real(dp) nd, sumx, sumx2, sumxy, sumy, sumy2
! Do linear regression analysis on input data
sumx = sum(x)
sumx2 = sum(x * x)
sumxy = sum(x * y)
sumy = sum(y)
sumy2 = sum(y * y)
nd = dble(n)
m = (nd * sumxy - sumx * sumy) / (nd * sumx2 - sumx*sumx)
b = (sumy * sumx2 - sumx * sumxy) / (nd * sumx2 - sumx*sumx)
r = (sumxy - sumx * sumy / nd) / sqrt((sumx2 - sumx*sumx/nd) * (sumy2 - sumy*sumy/nd))
! Define two points on the linear line
xlin(1) = x(1)
xlin(2) = x(n)
ylin(1) = m*xlin(1) + b
ylin(2) = m*xlin(2) + b
! Plot results
iw = winio@('%mn[Exit]&','exit')
iw = winio@('%fn[Consolas]%ts%bf&',1.5d0)
call winop@('%pl[x_array,independent,n_graphs=2,width=2,smoothing=4,gridlines,frame]')
call winop@('%pl[Title="Linear Regression"]')
call winop@('%pl[link=curves,colour=blue,symbol=1]')
call winop@('%pl[link=lines,colour=grey,symbol=0]')
gx = 500
gy = 500
iw = winio@('%ff%nl%pv%pl&',gx,gy,[n,2],x,y,xlin,ylin)
iw = winio@('%ff%ts&',1.d0)
iw = winio@('%1tl&',30)
iw = winio@('%tc[black]%nl%cn linear slope%ta%`rf&',m)
iw = winio@('%nl%cn y-inercept %ta%`rf&',b)
iw = winio@('%nl%cn correlation coeff. %ta%`rf&',r)
iw = winio@('')
end subroutine pllinreg