Use approxEqual for doubles in some examples.

Replaced a few instances of doubles being compared with == in std.algorithm's examples.  They are now compared with approxEqual.  This should encourage better practices, since floating point numbers can experience rounding errors that would make direct equality checks fail in situations where they are expected to work.

std/algorithm.d

@@ -649,11 +649,11 @@ assert(r == 107);
 // Mixing convertible types is fair game, too
 double[] c = [ 2.5, 3.0 ];
 auto r1 = reduce!("a + b")(chain(a, b, c));
-assert(r1 == 112.5);
+assert(approxEqual(r1, 112.5));
 
 // To minimize nesting of parentheses, Uniform Function Call Syntax can be used
 auto r2 = chain(a, b, c).reduce!("a + b");
-assert(r2 == 112.5);
+assert(approxEqual(r2, 112.5));
 ----
 
 $(DDOC_SECTION_H Multiple functions:) Sometimes it is very useful to
@@ -669,14 +669,14 @@ Example:
 double[] a = [ 3.0, 4, 7, 11, 3, 2, 5 ];
 // Compute minimum and maximum in one pass
 auto r = reduce!(min, max)(a);
-// The type of r is Tuple!(double, double)
-assert(r[0] == 2);  // minimum
-assert(r[1] == 11); // maximum
+// The type of r is Tuple!(int, int)
+assert(approxEqual(r[0], 2));  // minimum
+assert(approxEqual(r[1], 11)); // maximum
 
 // Compute sum and sum of squares in one pass
 r = reduce!("a + b", "a + b * b")(tuple(0.0, 0.0), a);
-assert(r[0] == 35);  // sum
-assert(r[1] == 233); // sum of squares
+assert(approxEqual(r[0], 35));  // sum
+assert(approxEqual(r[1], 233)); // sum of squares
 // Compute average and standard deviation from the above
 auto avg = r[0] / a.length;
 auto stdev = sqrt(r[1] / a.length - avg * avg);
@@ -1285,7 +1285,7 @@ assert(equal(r, [ 3, 400, 100, 102 ]));
 // Mixing convertible types is fair game, too
 double[] c = [ 2.5, 3.0 ];
 auto r1 = chain(c, a, b).filter!(a => cast(int) a != a);
-assert(equal(r1, [ 2.5 ]));
+assert(approxEqual(r1, [ 2.5 ]));
 ----
  */
 template filter(alias pred) if (is(typeof(unaryFun!pred)))