1 files changed, 116 insertions, 0 deletions
diff --git a/src/pcg.c b/src/pcg.c
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+/*
+ * PCG Random Number Generation for C.
+ *
+ * Copyright 2014 Melissa O'Neill <oneill@pcg-random.org>
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *
+ * For additional information about the PCG random number generation scheme,
+ * including its license and other licensing options, visit
+ *
+ *       http://www.pcg-random.org
+ */
+
+/*
+ * This code is derived from the full C implementation, which is in turn
+ * derived from the canonical C++ PCG implementation. The C++ version
+ * has many additional features and is preferable if you can use C++ in
+ * your project.
+ */
+
+#include "pcg.h"
+
+// state for global RNGs
+
+static pcg32_random_t pcg32_global = PCG32_INITIALIZER;
+
+// pcg32_srandom(initstate, initseq)
+// pcg32_srandom_r(rng, initstate, initseq):
+//     Seed the rng.  Specified in two parts, state initializer and a
+//     sequence selection constant (a.k.a. stream id)
+
+void pcg32_srandom_r(pcg32_random_t* rng, uint64_t initstate, uint64_t initseq)
+{
+    rng->state = 0U;
+    rng->inc = (initseq << 1u) | 1u;
+    pcg32_random_r(rng);
+    rng->state += initstate;
+    pcg32_random_r(rng);
+}
+
+void pcg32_srandom(uint64_t seed, uint64_t seq)
+{
+    pcg32_srandom_r(&pcg32_global, seed, seq);
+}
+
+// pcg32_random()
+// pcg32_random_r(rng)
+//     Generate a uniformly distributed 32-bit random number
+
+uint32_t pcg32_random_r(pcg32_random_t* rng)
+{
+    uint64_t oldstate = rng->state;
+    rng->state = oldstate * 6364136223846793005ULL + rng->inc;
+    uint32_t xorshifted = ((oldstate >> 18u) ^ oldstate) >> 27u;
+    uint32_t rot = oldstate >> 59u;
+    return (xorshifted >> rot) | (xorshifted << ((-rot) & 31));
+}
+
+uint32_t pcg32_random()
+{
+    return pcg32_random_r(&pcg32_global);
+}
+
+
+// pcg32_boundedrand(bound):
+// pcg32_boundedrand_r(rng, bound):
+//     Generate a uniformly distributed number, r, where 0 <= r < bound
+
+uint32_t pcg32_boundedrand_r(pcg32_random_t* rng, uint32_t bound)
+{
+    // To avoid bias, we need to make the range of the RNG a multiple of
+    // bound, which we do by dropping output less than a threshold.
+    // A naive scheme to calculate the threshold would be to do
+    //
+    //     uint32_t threshold = 0x100000000ull % bound;
+    //
+    // but 64-bit div/mod is slower than 32-bit div/mod (especially on
+    // 32-bit platforms).  In essence, we do
+    //
+    //     uint32_t threshold = (0x100000000ull-bound) % bound;
+    //
+    // because this version will calculate the same modulus, but the LHS
+    // value is less than 2^32.
+
+    uint32_t threshold = -bound % bound;
+
+    // Uniformity guarantees that this loop will terminate.  In practice, it
+    // should usually terminate quickly; on average (assuming all bounds are
+    // equally likely), 82.25% of the time, we can expect it to require just
+    // one iteration.  In the worst case, someone passes a bound of 2^31 + 1
+    // (i.e., 2147483649), which invalidates almost 50% of the range.  In
+    // practice, bounds are typically small and only a tiny amount of the range
+    // is eliminated.
+    for (;;) {
+        uint32_t r = pcg32_random_r(rng);
+        if (r >= threshold)
+            return r % bound;
+    }
+}
+
+
+uint32_t pcg32_boundedrand(uint32_t bound)
+{
+    return pcg32_boundedrand_r(&pcg32_global, bound);
+}
+