Have been there :-) I also travelled trough stackoverflows PiP-suggestions, including your reference and this thread. Unfortunelaty none of the suggestions (at least those I tried) were flawless and sufficient for a real life scenario : like users plotting complex polygon on a google map in freehand, "vicious" right vs left issues, negative numbers and so on.
The PiP-algorithm must work in all cases, even if the polygon consists of hundred thousands of points (like a county-border, nature park and so on) - no matter how "crazy" the polygon is.
So I ended up building a new algoritm, based on some source from an astronomy-app :
//Point class, storage of lat/long-pairs
class Point {
public $lat;
public $long;
function Point($lat, $long) {
$this->lat = $lat;
$this->long = $long;
}
}
//the Point in Polygon function
function pointInPolygon($p, $polygon) {
//if you operates with (hundred)thousands of points
set_time_limit(60);
$c = 0;
$p1 = $polygon[0];
$n = count($polygon);
for ($i=1; $i<=$n; $i++) {
$p2 = $polygon[$i % $n];
if ($p->long > min($p1->long, $p2->long)
&& $p->long <= max($p1->long, $p2->long)
&& $p->lat <= max($p1->lat, $p2->lat)
&& $p1->long != $p2->long) {
$xinters = ($p->long - $p1->long) * ($p2->lat - $p1->lat) / ($p2->long - $p1->long) + $p1->lat;
if ($p1->lat == $p2->lat || $p->lat <= $xinters) {
$c++;
}
}
$p1 = $p2;
}
// if the number of edges we passed through is even, then it's not in the poly.
return $c%2!=0;
}
Illustrative test :
$polygon = array(
new Point(1,1),
new Point(1,4),
new Point(4,4),
new Point(4,1)
);
function test($lat, $long) {
global $polygon;
$ll=$lat.','.$long;
echo (pointInPolygon(new Point($lat,$long), $polygon)) ? $ll .' is inside polygon<br>' : $ll.' is outside<br>';
}
test(2, 2);
test(1, 1);
test(1.5333, 2.3434);
test(400, -100);
test(1.01, 1.01);
Outputs :
2,2 is inside polygon
1,1 is outside
1.5333,2.3434 is inside polygon
400,-100 is outside
1.01,1.01 is inside polygon
It is now more than a year since i switched to the above algorithm on several sites. Unlike the "SO-algorithms" there has not been any complains so far. See it in action here (national mycological database, sorry for the danish). You can plot a polygon, or select a "kommune" (a county) - ultimately compare a polygon with thousands of points to thousands of records).
Update
Note, this algorithm is targeting geodata / lat,lngs which can be very precise (n'th decimal), therefore considering "in polygon" as inside polygon - not on border of polygon. 1,1 is considered outside, since it is on the border. 1.0000000001,1.01 is not.