mirror of
https://github.com/Ninjdai1/pokeemerald.git
synced 2024-12-27 04:04:17 +01:00
7b306b6147
Converts Tri Attack and Dire Claw to use structured RNG.
113 lines
2.9 KiB
C
113 lines
2.9 KiB
C
#include "global.h"
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#include "test.h"
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#include "random.h"
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TEST("RandomUniform generates lo..hi")
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{
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u32 lo, hi, i;
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PARAMETRIZE { lo = 0; hi = 1; }
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PARAMETRIZE { lo = 0; hi = 2; }
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PARAMETRIZE { lo = 0; hi = 3; }
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PARAMETRIZE { lo = 2; hi = 4; }
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for (i = 0; i < 1024; i++)
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{
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u32 r = RandomUniformDefault(RNG_NONE, lo, hi);
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EXPECT(lo <= r && r <= hi);
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}
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}
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TEST("RandomWeighted generates 0..n-1")
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{
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u32 n, sum, i;
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static const u8 ws[8] = { 1, 1, 1, 1, 1, 1, 1, 1 };
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PARAMETRIZE { n = 1; }
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PARAMETRIZE { n = 2; }
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PARAMETRIZE { n = 3; }
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PARAMETRIZE { n = 4; }
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ASSUME(n <= ARRAY_COUNT(ws));
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for (i = 0, sum = 0; i < n; i++)
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sum += ws[i];
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for (i = 0; i < 1024; i++)
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{
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u32 r = RandomWeightedArrayDefault(RNG_NONE, sum, n, ws);
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EXPECT(0 <= r && r < n);
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}
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}
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TEST("RandomElement generates an element")
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{
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u32 i;
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static const u8 es[4] = { 1, 2, 4, 8 };
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for (i = 0; i < 1024; i++)
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{
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u32 e = *(const u8 *)RandomElementArrayDefault(RNG_NONE, es, sizeof(es[0]), ARRAY_COUNT(es));
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EXPECT(e == 1 || e == 2 || e == 4 || e == 8);
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}
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}
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TEST("RandomUniform generates uniform distribution")
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{
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u32 i, error;
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u16 distribution[4];
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memset(distribution, 0, sizeof(distribution));
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for (i = 0; i < 4096; i++)
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{
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u32 r = RandomUniformDefault(RNG_NONE, 0, ARRAY_COUNT(distribution) - 1);
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EXPECT(0 <= r && r < ARRAY_COUNT(distribution));
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distribution[r]++;
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}
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error = 0;
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for (i = 0; i < ARRAY_COUNT(distribution); i++)
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error += abs(UQ_4_12(0.25) - distribution[i]);
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EXPECT_LT(error, UQ_4_12(0.025));
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}
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TEST("RandomWeighted generates distribution in proportion to the weights")
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{
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u32 i, sum, error;
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static const u8 ws[4] = { 1, 2, 2, 3 };
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u16 distribution[ARRAY_COUNT(ws)];
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for (i = 0, sum = 0; i < ARRAY_COUNT(ws); i++)
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sum += ws[i];
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memset(distribution, 0, sizeof(distribution));
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for (i = 0; i < 4096; i++)
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{
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u32 r = RandomWeightedArrayDefault(RNG_NONE, sum, ARRAY_COUNT(ws), ws);
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EXPECT(0 <= r && r < ARRAY_COUNT(ws));
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distribution[r]++;
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}
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error = 0;
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error += abs(UQ_4_12(0.125) - distribution[0]);
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error += abs(UQ_4_12(0.250) - distribution[1]);
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error += abs(UQ_4_12(0.250) - distribution[2]);
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error += abs(UQ_4_12(0.375) - distribution[3]);
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EXPECT_LT(error, UQ_4_12(0.025));
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}
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TEST("RandomElement generates a uniform distribution")
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{
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u32 i, error;
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static const u8 es[4] = { 1, 2, 4, 8 };
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u16 distribution[9];
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memset(distribution, 0, sizeof(distribution));
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for (i = 0; i < 4096; i++)
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{
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u32 e = *(const u8 *)RandomElementArrayDefault(RNG_NONE, es, sizeof(es[0]), ARRAY_COUNT(es));
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distribution[e]++;
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}
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error = 0;
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for (i = 0; i < ARRAY_COUNT(es); i++)
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error += abs(UQ_4_12(0.25) - distribution[es[i]]);
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EXPECT_LT(error, UQ_4_12(0.025));
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}
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