I am getting a wrong result for a bigger matrix however for a small matrix like this i am getting results correctly. Can anybody help me what i may be doing wrong
data test1;
input pol $ prod1-prod9;
datalines;
1abc 1 1 0 1 0 0 1 1 0
2abc 0 0 1 1 0 0 1 1 1
3abc 1 1 0 1 0 0 0 0 0
4abc 1 0 1 1 0 0 1 1 0
5abc 0 1 0 1 1 0 0 1 0
6abc 1 1 0 1 0 0 0 0 0
7abc 1 0 1 1 0 0 1 1 0
8abc 0 1 0 1 1 0 0 1 0
9abc 1 1 0 1 0 0 0 0 0
10abc 1 0 1 1 0 0 1 1 0
11abc 0 1 0 1 1 0 0 1 0
12abc 1 1 0 1 0 0 0 0 0
13abc 1 0 1 1 0 0 1 1 0
14abc 0 1 0 1 1 0 0 1 0
15abc 1 1 0 1 0 0 0 0 0
16abc 1 0 1 1 0 0 1 1 0
17abc 0 1 0 1 1 0 0 1 0
;
run;
options mprint mlogic merror symbolgen;
%macro gen_prod_matrix(ilib,ids,olib,oPds) ;
proc sql;
select num_numeric into :prod_size from dictionary.tables where upcase(memname)=upcase(&ids) and upcase(libname)=upcase(&ilib);
SELECT distinct name into :varb_list separated by ' ' FROM dictionary.columns where upcase(memname)=upcase(&ids) AND upcase(libname)=upcase(&ilib) and TYPE='num';
SELECT name into :char_var separated by ' ' FROM dictionary.columns where upcase(memname)=upcase(&ids) AND upcase(libname)=upcase(&ilib) and TYPE='char';
SELECT memname into :ds FROM dictionary.columns where upcase(memname)=upcase(&ids) AND upcase(libname)=upcase(&ilib) and TYPE='num';
SELECT libname into :lib FROM dictionary.columns where upcase(memname)=upcase(&ids) AND upcase(libname)=upcase(&ilib) and TYPE='num';
quit;
%let prod_squ=%eval(&prod_size*&prod_size);
%let diag_siz=%eval(&prod_size+1);
/************************************************/
data step1;
set &lib..&ds;
array prod [&prod_size] &varb_list;
array nmres[&prod_size,&prod_size];
do i=1 to &prod_size;
do j=1 to &prod_size;
val=prod[i]*prod[j];
nmres[i,j]+val;
end;
end;
run;
/*************************************************/
data res1(keep=nmres: key);
set step1 end=last;
key=1;
if last;
run;
/**************************************************/
%macro diag;
%do i=1 %to &prod_squ %by &diag_siz;
nmres&i
%end;
%mend;
%let diag_var=%diag ;
/****************************************************/
data diagonal;
set res1;
keep &diag_var key;
run;
/************************************************/
data step2(keep=dmres: key);
set diagonal;
array diag[&prod_size] nmres:;
array dmres[&prod_size,&prod_size];
do i=1 to &prod_size;
do j=1 to &prod_size;
dmres[i,j]=sqrt(diag[i])*sqrt(diag[j]);
end;
end;
key=1;
run;
/**********************************************************************/
proc sql;
create table dvd_ds as
select * from res1 t1 inner join step2 t2 on t1.key=t2.key;
quit;
/**********************************************************************/
data res3(keep=res:);
set dvd_ds;
array dm[&prod_squ] dmres:;
array nm[&prod_squ] nmres:;
array res[&prod_squ];
do i=1 to &prod_squ;
res[i]=nm[i]/dm[i];
end;
run;
/*******************************************************/
%macro prod;
%do i=1 %to &prod_size;
prod&i
%end;
%mend;
%let prod_var=%prod ;
/****************************************************/
data matrix_op(keep=prod:);
set res3;
array results[&prod_squ] res:;
array products[&prod_size] &prod_var;
arrange=%eval(&prod_size-1);
do i=1 to &prod_squ by &prod_size;
do j=i to i+arrange;
x+1;
products[x]=results[j];
end;
output;
x=0;
end;
run;
/*************************************************************/
data &OLIB..&OPDS;
set matrix_op;
run;
%mend;
/*******************************************************************/
%macro colab_filter(in_A =,in_B=,ou_AB=);
/*determine number of rows and columns in the 2nd matrix*/
%let B_id=%sysfunc(open(&in_B));
%let B_rows=%sysfunc(attrn(&B_id,nobs));
%let B_cols=%sysfunc(attrn(&B_id,nvars));
%let rc=%sysfunc(close(&B_id));
/*transpose the 2nd matrix*/
proc transpose data=&in_B out=t&in_B(drop=_:);run;
/*making Cartesian product of the 1st and transposed 2nd matrices*/
data &ou_AB;
do until(eofA);
set &in_A end=eofA;
do i=1 to n;
set t&in_B nobs=n point=i;
output;
end;
end;
run;
/*multiplication*/
data &ou_AB;
/*new columns for products, equal to number of columns in the 2nd matrix*/
array v[&B_cols];
do j=1 to &B_cols;
v[j]=0;
set &ou_AB;
array col _ALL_;
/*multiply corresponding pairs of columns*/
do i=&B_cols+2 to &B_cols+1+&B_rows;
v[j]+col[i]*col[i+&B_rows];
end;
end;
output;
keep v:;
run;
%mend;
/**********************************/
%gen_prod_matrix('work','test1',work,PROD_MATRIX_test1);
%colab_filter(in_a=test1(DROP=f1:),in_b=PROD_MATRIX_test1,ou_AB=mat_prod_test1);
/**********************************/
If you are talking about Matrix Operator, That is a better question to IML. Post it at IML Forum, and Post some data and the output you want, and the logic behind that operator.
Sorry I dont have proc IML i am using SAS 9.2 and it says
ERROR: Bad product ID for procedure IML.
Thats why rather than posting under IML i posted under base SAS and i wanted it to get done without IML. I am trying proc FCMP to create an user difined function hope this works out
Have you tried the matrix CALL routines available through PROC FCMP?
Otherwise, I think you should clarify what you are trying to achieve and what exactly goes wrong.
For this matrix the results is correctly displayed across all the outputs however if we increase the number of rows to lets say 50000 or so the results are not correct.
I also checked the matrix code and then found out that the matrix multiplication is not getting dynamic
I am attaching the excel file and the logic that i am trying to achieve
Thanks
You can run IML code under University Edition. It is totally free. Can you elaborate How you get Matrix numerator and denominator ?
Numerotor is nothing just the sum of the columns which can be obtained also by proc corr /Cov and creating a daataset for the same
while the dinomintor too is just square root of the combinations of the first matrix
Like Square root for user 1 - it is SQR rooot P1*P1, P1*p2 and so on
IML is the best tool for matrix operation. I really suggest you to use IML code , which is a lot simpler and easier: proc iml; x={ 1 0 1 1, 0 0 1 1, 0 1 0 1, 1 0 1 0, 1 1 0 0 }; n=ncol(x); numerator=j(n,n,.); do i=1 to n; do j=1 to n; numerator[i,j]=sum(x[,i]#x[,j]); end; end; vecdiag=vecdiag(numerator); denominator=j(n,n,.); do i=1 to n; do j=1 to n; denominator[i,j]=sqrt(vecdiag[i]#vecdiag[j]); end; end; divided=numerator/denominator; Multiplicated=xmult(x,divided); print numerator ,denominator,divided,Multiplicated; quit;
I don't know what you are talking about. If you want read data from table as your sample data. You can do this. But that lead to ERROR information due to P6 value are all zero , and make Matrix Product meaning nothing. data test1; input pol $ prod1-prod9; datalines; 1abc 1 1 0 1 0 0 1 1 0 2abc 0 0 1 1 0 0 1 1 1 3abc 1 1 0 1 0 0 0 0 0 4abc 1 0 1 1 0 0 1 1 0 5abc 0 1 0 1 1 0 0 1 0 6abc 1 1 0 1 0 0 0 0 0 7abc 1 0 1 1 0 0 1 1 0 8abc 0 1 0 1 1 0 0 1 0 9abc 1 1 0 1 0 0 0 0 0 10abc 1 0 1 1 0 0 1 1 0 11abc 0 1 0 1 1 0 0 1 0 12abc 1 1 0 1 0 0 0 0 0 13abc 1 0 1 1 0 0 1 1 0 14abc 0 1 0 1 1 0 0 1 0 15abc 1 1 0 1 0 0 0 0 0 16abc 1 0 1 1 0 0 1 1 0 17abc 0 1 0 1 1 0 0 1 0 ; run; proc iml; use test1; read all var _num_ into x; close; n=ncol(x); numerator=j(n,n,.); do i=1 to n; do j=1 to n; numerator[i,j]=sum(x[,i]#x[,j]); end; end; vecdiag=vecdiag(numerator); denominator=j(n,n,.); do i=1 to n; do j=1 to n; denominator[i,j]=sqrt(vecdiag[i]#vecdiag[j]); end; end; divided=numerator/denominator; Multiplicated=xmult(x,divided); print numerator ,denominator,divided,Multiplicated; quit; OUTPUT: numerator 11 6 5 11 0 0 6 6 0 6 11 0 11 5 0 1 6 0 5 0 6 6 0 0 6 6 1 11 11 6 17 5 0 7 12 1 0 5 0 5 5 0 0 5 0 0 0 0 0 0 0 0 0 0 6 1 6 7 0 0 7 7 1 6 6 6 12 5 0 7 12 1 0 0 1 1 0 0 1 1 1 denominator 11 11 8.1240384 13.674794 7.4161985 0 8.7749644 11.489125 3.3166248 11 11 8.1240384 13.674794 7.4161985 0 8.7749644 11.489125 3.3166248 8.1240384 8.1240384 6 10.099505 5.4772256 0 6.4807407 8.4852814 2.4494897 13.674794 13.674794 10.099505 17 9.2195445 0 10.908712 14.282857 4.1231056 7.4161985 7.4161985 5.4772256 9.2195445 5 0 5.9160798 7.7459667 2.236068 0 0 0 0 0 0 0 0 0 8.7749644 8.7749644 6.4807407 10.908712 5.9160798 0 7 9.1651514 2.6457513 11.489125 11.489125 8.4852814 14.282857 7.7459667 0 9.1651514 12 3.4641016 3.3166248 3.3166248 2.4494897 4.1231056 2.236068 0 2.6457513 3.4641016 1 divided 1 0.5454545 0.6154575 0.8043997 0 . 0.6837635 0.522233 0 0.5454545 1 0 0.8043997 0.6741999 . 0.1139606 0.522233 0 0.6154575 0 1 0.5940885 0 . 0.9258201 0.7071068 0.4082483 0.8043997 0.8043997 0.5940885 1 0.5423261 . 0.6416889 0.8401681 0.2425356 0 0.6741999 0 0.5423261 1 . 0 0.6454972 0 . . . . . . . . . 0.6837635 0.1139606 0.9258201 0.6416889 0 . 1 0.7637626 0.3779645 0.522233 0.522233 0.7071068 0.8401681 0.6454972 . 0.7637626 1 0.2886751 0 0 0.4082483 0.2425356 0 . 0.3779645 0.2886751 1 You notice that P6 are all missing, thus lead to Matrix 'divided' has missing value and can't perform matrix product.
I am NOT going to do it by data step. That is a very nasty work. Maybe that is loss of precision problem. When you have some very very small value ,that would generate some error value. Example : a = 1e13; b = 1e13; c = 100 * a; a = a+1; x = c || a || b || c; y = c || a || (-b) || (-c); z = xmult(x,y`); / * correct answer * / print z [format=16.0]; wrong = x * y`; / * loss of precision * / print wrong [format=16.0]; Figure 24.433 Extended-Precision Multiplication z 20000000000001 wrong 0
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