option nolet
open #1:screen 0,0.5,0,1
open #2:screen .5,1,.5,1
window #1
! serie :analytical chemistry
! filename :REGRESSIONREALWORLDNEWfinalversion1a.tru
print
print "*********************************************"
print "* regressionline 'version 1.0a' *"
print "* Why use :realworld example *"
print "* (better understanding,relation between ) *"
print "* (weight and length ,to predict ) *"
print "* Labo data: use the below principles *"
print "*********************************************"
print "* [email protected],20/10/2016 *"
print "*********************************************"
print
print "************"
print "* given = *"
print "************"
!**********************************
! info to display data on the graph
!**********************************
dim xp(2),yp(2)
tb_x = 160 ! xmin
te_x = 210 ! xmax
nt_x = 10 ! tick marks x-axis
tb_y = 50 ! ymin
te_y = 100 ! ymax
nt_y = 5 ! tick marks y-axis
!*********************************************************
! info : graph,title,numbering,label axes
!*********************************************************
title$ = "graph 'length versus weight'"
x_txt$ = "length,cm"
y_txt$ = "weight,kg"
txt = 2 ! distance from right part of the window
!read data statement, x data = length, y data = weight
dim xy(2,1)
!read x data
n=10 ! number x data = number y data
mat redim xy(2,n)
! x data
for i=1 to n
read xy(1,i)
next i
! y data
for i=1 to n
read xy(2,i)
next i
print
print " x-data = length 'cm' => "
print
for i=1 to n
print xy(1,i);
next i
print
print
print " y-data = weight 'kg' => "
print
for i=1 to n
print xy(2,i);
next i
print
print
print "*******************************"
print " data range: x,y;tick x,y *"
print "*******************************"
print
print " xmin = ";tb_x
print " xmax = ";te_x
print " number of tick mark,x = ";nt_x
print
print " ymin = ";tb_y
print " ymax = ";te_y
print " number of tick mark,y = ";nt_y
print
print "************"
print "* result = *"
print "************"
print
!sum x,average x,ii=1;sum y,average y,ii=2
call sum_val_average(1,n,xy(,),somvalx,avgx)
call sum_val_average(2,n,xy(,),somvaly,avgy)
print " sum x_values,sum y_values = ";somvalx;",";somvaly
print " mean x_values,mean y_values = ";avgx;",";avgy
print
! sum prod of x_values*y_values
call sum_prod_x_y(n,xy(,),somprodxy)
print " sum(prod(x,y)) = ";somprodxy
! sum prod of x_values*x_values
call sum_prod_x_x(1,n,xy(,),somprodxx)
print " sum(prod(x,x)) = ";somprodxx
! sum prod of y_values*y_values
call sum_prod_x_x(2,n,xy(,),somprodyy)
print " sum(prod(y,y)) = ";somprodyy
! calculation regression line ' y = aa*x+bb'
spxx = somprodxx
spyy = somprodyy
spxy = somprodxy
sx = somvalx
sy = somvaly
call regr_line_aa(n,spxy,spxx,spyy,sx,sy,aa)
call regr_line_bb(n,avgx,avgy,aa,bb)
print
print "******************************"
print " regression line,blue => y = ";aa;" * x(+)";bb
print "******************************"
print
print "********************************************"
print " correlation coef. = spxy/sqr(spxx*spyy) => "
print " -1 = < correlation coef. = < 1 "
print "********************************************"
call correlation_coef(spxy,spxx,spyy,r_cor)
print " correlation coef. = ";r_cor
print
print "********************************************"
print " solve ? What will be weight for person 2 m "
print "********************************************"
person = 200 ! conversion : 2 m = 200 cm
tsolve = aa*person+bb
print " weight for person of 2m = ";tsolve;" kg"
!*******************************************
window #2 ! draw graph right part of screen
!*******************************************
ntx = nt_x ! tick marks x-axis
nty = nt_y ! tick marks y-axis
xp(1)=tb_x ! xmin,cm
xp(2)=te_x ! xmax,cm
yp(1)=tb_y ! ymin,kg
yp(2)=te_y ! ymax,kg
ask pixels px,py
asp_r =1 ! px/py !aspect ratio correction(rectangular window)
set window xp(1)*asp_r,xp(2)*asp_r,yp(1),yp(2)
call draw_axes(xp(1)*asp_r,xp(2)*asp_r,yp(1),yp(2),ntx,nty)
set color "black"
!**********************************************************
call num_txt_axes(title$,x_txt$,y_txt$,xp(),yp(),txt,ntx,nty)
!**********************************************************
! draw graph in the window x-axes ,y-axes(right part)
!**********************************************************
set color "red" ! color of the graph
!*************************************************
! data x,y
!*************************************************
s1=0.4 ! radius
z3$ = "red" ! color 'circle'
asp = px/py ! to draw circle in the graph for data xy
! draw n circles for data xy
for i=1 to n
call smallcir_dr(s1,xy(1,i),xy(2,i),scale,asp,z3$)
flood xy(1,i),xy(2,i) ! fill circle with color 'red'
next i
!*************************************************
! axes ,transformation x=X-avgx,y=Y-avgy
!*************************************************
set color "green"
plot lines :avgx,yp(1);avgx,yp(2)
plot lines :xp(1),avgy;xp(2),avgy
plot text,at avgx,avgy+1:"(mean(x),mean(y))"
!*************************************************
! draw regression line : y = aa*x+bb,2 points
!*************************************************
set color "blue"
! first point xx1,yy1
xx1 = tb_x
yy1 = aa*xx1+bb
! second point xx2,yy2
xx2 = te_x
yy2 = aa*xx2+bb
plot lines :xx1,yy1;xx2,yy2
!*************************************************
! draw : solve example ( person 2m,find weight)
!*************************************************
set color "magenta"
plot lines :person,yp(1);person,tsolve
plot lines :xp(1),tsolve;person,tsolve
cord$ = "(" & str$(person) & "," & str$(tsolve)&")"
plot text,at person,tsolve:cord$
!*************************************************
! data : x,y
!*************************************************
! data statement, x values
data 170,179,185,171,188,175,190,166,186,192
! data statement, y values
data 73,74,81,74,82,70,82,60,90,85
end
!******************************************
! y = aa*x+bb 'regression line
!******************************************
sub regr_line_aa(n,spxy,spxx,spyy,sx,sy,aa)
tel1 = n*spxy-sx*sy
noem1= n*spxx - (sx)^2
aa = tel1/noem1
end sub
sub regr_line_bb(n,avgx,avgy,aa,bb)
bb = avgy - aa*avgx
end sub
!*****************************************
!*****************************************
sub sum_val_average(ii,n,xy(,),somval,avg)
som1 = 0
for i= 1 to n
som1 = som1 + xy(ii,i)
next i
somval=som1
avg = (somval)/n
end sub
sub sum_prod_x_y(n,xy(,),somprodxy)
som2 = 0
for i=1 to n
som2=som2+xy(1,i)*xy(2,i)
next i
somprodxy = som2
end sub
sub sum_prod_x_x(ii,n,xy(,),somprodxx)
som3 = 0
for i=1 to n
som3=som3+xy(ii,i)*xy(ii,i)
next i
somprodxx = som3
end sub
sub correlation_coef(spxy,spxx,spyy,r_cor)
tel2 = spxy
noem2 = sqr(spxx*spyy)
r_cor = tel2/noem2
end sub
sub smallcir_dr(s1,xf,yf,scale,asp,z3$)
set color z3$
for theta=0 to 2*3.14 step 0.0001
plot points:s1*cos(theta)+xf,s1*sin(theta)*asp+yf
next theta
end sub
sub num_txt_axes(title$,x_txt$,y_txt$,xp(),yp(),txt,ntx,nty)
mx = xp(2)-xp(1)
my = yp(2)-yp(1)
plot text,at xp(1)+mx/txt,yp(2)-my/(txt*txt):title$
!*****************************************
!**** range x axis 0 to xmax *******
!*****************************************
for i=2 to ntx
m1 = xp(1)+mx/ntx*(i-1)
plot text,at m1,yp(1):str$(m1)
next i
plot text,at xp(2)-2*txt,yp(1)+txt:x_txt$
!*****************************************
!**** range y axis 0 to ymax ************
!*****************************************
for i=2 to nty
m2 = yp(1)+my/nty*(i-1)
plot text,at xp(1),m2:str$(m2)
next i
plot text,at xp(1)+txt,yp(2)-txt:y_txt$
end sub
SUB draw_axes(xmin,xmax,ymin,ymax,ntx,nty)
! axis :for distribution function
! see extra,website
! distance between tick marks on x-axis
LET dx = (xmax - xmin)/ntx
! distance between tick marks on y-axis
LET dy = (ymax - ymin)/nty
SET WINDOW xmin ,xmax ,ymin ,ymax
LET x0 = max(0,xmin)
LET y0 = max(0,ymin)
IF ymin*ymax < 0 then
LET y0 = 0
ELSE
LET y0 = ymin
END IF
PLOT LINES: xmin,y0;xmax,y0 ! horizontal axis
PLOT LINES: x0,ymin;x0,ymax ! vertical axis
LET tx = 0.1*dy ! size of tick mark
LET ty = 0.1*dx
FOR itick = 0 to ntx
LET x = xmin + itick*dx
PLOT LINES: x,y0 - tx; x,y0 + tx ! draw ticks on x axis
next itick
FOR itick = 0 to nty
LET y = ymin + itick*dy
PLOT LINES: x0 - ty,y; x0 + ty,y ! draw ticks on y axis
NEXT itick
END SUB