I need the zipdecode program to include Alaska & Hawaai as well.
please help me to make necessary changes.

Currently it is work fine without Alaska & Hawaaai, i tried to make x,y coordinates regenerated by remove filteration on AK,HI state abbrevations in  the code below:

// Indices for each of the columns
int ZIP_CODE = 0;
int LATITUDE = 1;
int LONGITUDE = 2;
int ZIP_CLASS = 3;
int PONAME = 4;
int STATE_FIPS = 5;
int COUNTY = 6;


void setup( ) {
// Load the state FIPS codes into a table.
Hashtable fipsTable = new Hashtable( );
String[] fipsLines = loadStrings("fips.tsv");
for (int i = 0; i < fipsLines.length; i++) {
// Split each line on the tab characters.
String[] pieces = split(fipsLines[i], TAB);
// The FIPS code is in column 1,
// and the state abbreviation in column 2
// (keep in mind that columns are numbered from zero).
fipsTable.put(pieces[1], pieces[2]);
}
String[] lines = loadStrings("zipnov99.csv");

// Set the minimum and maximum values arbitrarily large.
float minX = 1;
float maxX = -1;
float minY = 1;
float maxY = -1;
// Set up an array for the cleaned data.
String[] cleaned = new String[lines.length];
// Number of cleaned entries found
int placeCount = 0;
// Start at row 1, because the first row is the column titles.
for (int row = 1; row < lines.length; row++) {
// Split the row into pieces on each comma.
String[] data = split(lines[row], ',');
scrubQuotes(data);
// Remove extra whitespace on either side of each column.
data = trim(data);
String stateAbbrev = (String) fipsTable.get(data[STATE_FIPS]);
// If the abbreviation was not found, skip this line,
// because that means it's an outlying territory.
if (stateAbbrev == null) continue;
// For now, also skip Alaska and Hawaii.

//*** if not need alaska & hawaai, uncomment to proceed! ***
//if (stateAbbrev.equals("AK") || stateAbbrev.equals("HI")) continue;

// Attempt to fix the capitalization of the city/town name.
String placeName = fixCapitals(data[PONAME]) + ", " + stateAbbrev;
float lat = float(data[LATITUDE]);
float lon = float(data[LONGITUDE]);

// Albers equal-area conic projection.
// USGS uses standard parallels at 45.5˚N and 29.5˚N
// with a central meridian value of 96˚W.
// Latitude value is phi, longitude is lambda.
float phi0 = 0;
float lambda0 = radians(-96);
float phi1 = radians(30f);
float phi2 = radians(45.5f);
float phi = radians(lat);
float lambda = radians(lon);
float n = 0.5f * (sin(phi1) + sin(phi2));
float theta = n * (lambda - lambda0); //radians(lon - lambda0);
float c = sq(cos(phi1)) + 2*n*sin(phi1);
float rho = sqrt(c - 2*n*sin(phi)) / n;
float rho0 = sqrt(c - 2*n*sin(phi0)) / n;
float x = rho * sin(theta);
float y = rho0 - rho*cos(theta);

if (x > maxX) maxX = x;
if (x < minX) minX = x;
if (y > maxY) maxY = y;
if (y < minY) minY = y;
// Add a cleaned version of the line, separated by tabs, to the list.
cleaned[placeCount++] = data[ZIP_CODE] + " " + x + " "+ y + " "+ placeName;
}
// Write to a file called "zips.tsv" in the sketch folder.
PrintWriter tsv = createWriter("zips.tsv");
// Use the first line to specify the number of data points in the file,
// along with the minimum and maximum latitude and longitude coordinates.
// Use a # to mark the line as different from the other data.
tsv.println("# " + placeCount +
"," + minX + "," + maxX + "," + minY + "," + maxY);
// Write each line of the cleaned data.
for (int i = 0; i < placeCount; i++) {
tsv.println(cleaned[i]);
}
// Flush and close the file buffer.
tsv.flush( );
tsv.close( );
// Finished; quit the program.
println("Finished.");
exit( );
}


// Parse quotes from CSV or TSV data. Quotes around a column are common,
// and actual double quotes (") are specified by two double quotes ("").
void scrubQuotes(String[] array) {
  for (int i = 0; i < array.length; i++) {
    if (array[i].length(  ) > 2) {
      // Remove quotes at start and end, if present.
      if (array[i].startsWith("\"") && array[i].endsWith("\"")) {
        array[i] = array[i].substring(1, array[i].length(  ) - 1);
      }
    }
    // Make double quotes into single quotes.
    array[i] = array[i].replaceAll("\"\"", "\"");
  }
}


// Capitalize the first letter of each word in a string.
String fixCapitals(String title) {
char[] text = title.toCharArray( );
// If set to true, the next letter will be capitalized.
boolean capitalizeNext = true;

for (int i = 0; i < text.length; i++) {
if (Character.isSpace(text[i])) {
capitalizeNext = true;
} else if (capitalizeNext) {
text[i] = Character.toUpperCase(text[i]);
capitalizeNext = false;
} else {
text[i] = Character.toLowerCase(text[i]);
}
}
return new String(text);
}

I need to know how exactly map() function works!
If anyone can explain what are the formulas inside this map() function including the role of each of four parameters used to parse data in to the function.

please help me, i'm creating a project using javascripting & html and need help to understand the formulas.

I have read the ben-fry's book visualizing data and had the maximum taste out of it, i was read this book in two days with the curiosity took me into do this project.

Tks for Benjamin Fry here i am on the business ;-)