daynebatten

/* Run the optimization */

proc optmodel;
	set patterns = 1..&num_patterns;
	set cuts = 1..&num_cuts;

	number choices {patterns, cuts};
	number prices {patterns};
	number targets {cuts};

daynebatten

data testset;
	input @1 level @3 county $3. @7 degree $3. @11 num 3. @15 salary 5.;

datalines;
3 WAY B   100 30000
3 WAY M   25  50000
3 WAY P   1   70000
3 FAR B   200 30000
3 FAR M   50  50000
3 FAR P   2   70000

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/* "Primary" suppression - hide all values equal to 1 */

data testset;
	set testset;

	if num = 1 then num = .;
run;

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/* Code below here should be run repeatedly until the data no longer changes... */

/* Suppress across the county dimension */

/* Put the data in order of degrees, and ascending number of citizens (missing sorts low in SAS) */

proc sort data = testset;
	by level degree num;
run;

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/* Hide salaries if number is hidden... */

data testset;
	set testset;

	if num = . then salary = .;
run;

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/* target_data is the data set you want to suppress
	target_var is the variable you want to suppress
	dimensions is a pipe-separated list of dimensions to suppress
	cutoff is the highest value you want to suppress */

%macro suppress(target_data, target_var, dimensions, cutoff);
	/* Count the number of dimensions we're working with */

	%let num_dims = %eval(%sysfunc(count(&dimensions, |)) + 1);

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data names_raw;
	infile "C:\Users\dbatten\Desktop\Name Data.csv" dlm = ',' dsd truncover lrecl = 1000;
	
	input first_name :$50. last_name :$50. race :$3. number :5.;
run;

proc means noprint data = names_raw;
	class first_name last_name race;
	var number;

daynebatten

data testset;
	input @1 county $3. @5 degree $3. @9 num 3. @13 salary 5.;
 
datalines;
WAY B   100 30000
WAY M   25  50000
WAY P   1   70000
FAR B   200 30000
FAR M   50  50000
FAR P   2   70000

daynebatten

/*	We need constraints for every combination of dimensions you can build by leaving out one dimension at a time.
	This is pretty simple in a 2-dimensional dataset. */

proc sql;
	create table
		levels

	/* Constraints across the degree dimension */

	as select distinct

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/* Merge our raw data with our constraint categories to determine which constraints apply to which data points */

proc sql;
	create table
		joined
	as select
		t.*,
		con,
		case when
			(t.county = l.county and l.degree = 'dummy' and t.degree ~= 'ALL')