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mirror of https://github.com/golang/go synced 2024-11-11 19:21:37 -07:00

math/rand/v2: delete Mitchell/Reeds source

These slowdowns are because we are now using PCG instead of the
Mitchell/Reeds LFSR for the benchmarks. PCG is in fact a bit slower
(but generates statically far better random numbers).

goos: linux
goarch: amd64
pkg: math/rand/v2
cpu: AMD Ryzen 9 7950X 16-Core Processor
                        │ 01ff938549.amd64 │           afa459a2f0.amd64           │
                        │      sec/op      │    sec/op     vs base                │
PCG_DXSM-32                    1.490n ± 0%    1.488n ± 2%        ~ (p=0.408 n=20)
SourceUint64-32                1.352n ± 1%    1.450n ± 3%   +7.21% (p=0.000 n=20)
GlobalInt64-32                 2.083n ± 0%    2.067n ± 2%        ~ (p=0.223 n=20)
GlobalInt64Parallel-32        0.1035n ± 1%   0.1044n ± 2%        ~ (p=0.010 n=20)
GlobalUint64-32                2.038n ± 1%    2.085n ± 0%   +2.28% (p=0.000 n=20)
GlobalUint64Parallel-32       0.1006n ± 1%   0.1008n ± 1%        ~ (p=0.733 n=20)
Int64-32                       1.687n ± 2%    1.779n ± 1%   +5.48% (p=0.000 n=20)
Uint64-32                      1.674n ± 2%    1.854n ± 2%  +10.69% (p=0.000 n=20)
GlobalIntN1000-32              3.135n ± 1%    3.140n ± 3%        ~ (p=0.794 n=20)
IntN1000-32                    2.478n ± 1%    2.496n ± 1%   +0.73% (p=0.006 n=20)
Int64N1000-32                  2.455n ± 1%    2.510n ± 2%   +2.22% (p=0.000 n=20)
Int64N1e8-32                   2.467n ± 2%    2.471n ± 2%        ~ (p=0.050 n=20)
Int64N1e9-32                   2.454n ± 1%    2.488n ± 2%   +1.39% (p=0.000 n=20)
Int64N2e9-32                   2.482n ± 1%    2.478n ± 2%        ~ (p=0.066 n=20)
Int64N1e18-32                  3.349n ± 2%    3.088n ± 1%   -7.81% (p=0.000 n=20)
Int64N2e18-32                  3.537n ± 1%    3.493n ± 1%   -1.24% (p=0.002 n=20)
Int64N4e18-32                  4.917n ± 0%    5.060n ± 2%   +2.91% (p=0.000 n=20)
Int32N1000-32                  2.386n ± 1%    2.620n ± 1%   +9.76% (p=0.000 n=20)
Int32N1e8-32                   2.366n ± 1%    2.652n ± 0%  +12.11% (p=0.000 n=20)
Int32N1e9-32                   2.355n ± 2%    2.644n ± 1%  +12.32% (p=0.000 n=20)
Int32N2e9-32                   2.371n ± 1%    2.619n ± 2%  +10.48% (p=0.000 n=20)
Float32-32                     2.245n ± 2%    2.261n ± 1%        ~ (p=0.625 n=20)
Float64-32                     2.235n ± 1%    2.241n ± 2%        ~ (p=0.393 n=20)
ExpFloat64-32                  3.813n ± 3%    3.716n ± 1%   -2.53% (p=0.000 n=20)
NormFloat64-32                 3.652n ± 2%    3.718n ± 1%   +1.79% (p=0.006 n=20)
Perm3-32                       33.12n ± 3%    34.11n ± 2%        ~ (p=0.021 n=20)
Perm30-32                      205.1n ± 1%    200.6n ± 0%   -2.17% (p=0.000 n=20)
Perm30ViaShuffle-32            110.8n ± 1%    109.7n ± 1%   -0.99% (p=0.002 n=20)
ShuffleOverhead-32             113.0n ± 1%    107.2n ± 1%   -5.09% (p=0.000 n=20)
Concurrent-32                  2.100n ± 0%    2.108n ± 6%        ~ (p=0.103 n=20)

goos: darwin
goarch: arm64
pkg: math/rand/v2
                       │ 01ff938549.arm64 │           afa459a2f0.arm64           │
                       │      sec/op      │    sec/op     vs base                │
PCG_DXSM-8                    2.531n ± 0%    2.531n ± 0%        ~ (p=0.763 n=20)
SourceUint64-8                2.258n ± 1%    2.531n ± 0%  +12.09% (p=0.000 n=20)
GlobalInt64-8                 2.167n ± 0%    2.177n ± 1%        ~ (p=0.213 n=20)
GlobalInt64Parallel-8        0.4310n ± 0%   0.4319n ± 0%        ~ (p=0.027 n=20)
GlobalUint64-8                2.182n ± 1%    2.185n ± 1%        ~ (p=0.683 n=20)
GlobalUint64Parallel-8       0.4297n ± 0%   0.4295n ± 1%        ~ (p=0.941 n=20)
Int64-8                       2.472n ± 1%    4.104n ± 0%  +66.00% (p=0.000 n=20)
Uint64-8                      2.449n ± 1%    4.080n ± 0%  +66.60% (p=0.000 n=20)
GlobalIntN1000-8              2.814n ± 2%    2.814n ± 1%        ~ (p=0.972 n=20)
IntN1000-8                    2.998n ± 2%    4.140n ± 0%  +38.09% (p=0.000 n=20)
Int64N1000-8                  2.949n ± 2%    4.139n ± 0%  +40.35% (p=0.000 n=20)
Int64N1e8-8                   2.953n ± 2%    4.140n ± 0%  +40.22% (p=0.000 n=20)
Int64N1e9-8                   2.950n ± 0%    4.139n ± 0%  +40.32% (p=0.000 n=20)
Int64N2e9-8                   2.946n ± 2%    4.140n ± 0%  +40.53% (p=0.000 n=20)
Int64N1e18-8                  3.779n ± 1%    5.273n ± 0%  +39.52% (p=0.000 n=20)
Int64N2e18-8                  4.370n ± 1%    6.059n ± 0%  +38.65% (p=0.000 n=20)
Int64N4e18-8                  6.544n ± 1%    8.803n ± 0%  +34.52% (p=0.000 n=20)
Int32N1000-8                  2.950n ± 0%    4.131n ± 0%  +40.06% (p=0.000 n=20)
Int32N1e8-8                   2.950n ± 2%    4.131n ± 0%  +40.03% (p=0.000 n=20)
Int32N1e9-8                   2.951n ± 2%    4.131n ± 0%  +39.99% (p=0.000 n=20)
Int32N2e9-8                   2.950n ± 2%    4.131n ± 0%  +40.03% (p=0.000 n=20)
Float32-8                     3.441n ± 0%    4.110n ± 0%  +19.44% (p=0.000 n=20)
Float64-8                     3.442n ± 0%    4.104n ± 0%  +19.24% (p=0.000 n=20)
ExpFloat64-8                  4.481n ± 0%    5.338n ± 0%  +19.11% (p=0.000 n=20)
NormFloat64-8                 4.725n ± 0%    5.731n ± 0%  +21.28% (p=0.000 n=20)
Perm3-8                       26.55n ± 0%    26.62n ± 0%   +0.28% (p=0.000 n=20)
Perm30-8                      181.9n ± 0%    194.6n ± 2%   +6.98% (p=0.000 n=20)
Perm30ViaShuffle-8            142.9n ± 0%    156.4n ± 0%   +9.45% (p=0.000 n=20)
ShuffleOverhead-8             120.8n ± 2%    125.8n ± 0%   +4.10% (p=0.000 n=20)
Concurrent-8                  2.421n ± 6%    2.654n ± 6%   +9.67% (p=0.002 n=20)

goos: linux
goarch: 386
pkg: math/rand/v2
cpu: AMD Ryzen 9 7950X 16-Core Processor
                        │ 01ff938549.386 │            afa459a2f0.386             │
                        │     sec/op     │    sec/op     vs base                 │
PCG_DXSM-32                  7.613n ± 1%    7.793n ± 2%    +2.38% (p=0.000 n=20)
SourceUint64-32              2.069n ± 0%    7.680n ± 1%  +271.19% (p=0.000 n=20)
GlobalInt64-32               3.456n ± 1%    3.474n ± 3%         ~ (p=0.654 n=20)
GlobalInt64Parallel-32      0.3252n ± 0%   0.3253n ± 0%         ~ (p=0.952 n=20)
GlobalUint64-32              3.573n ± 1%    3.433n ± 2%    -3.92% (p=0.000 n=20)
GlobalUint64Parallel-32     0.3159n ± 0%   0.3156n ± 0%         ~ (p=0.223 n=20)
Int64-32                     2.562n ± 2%    7.707n ± 1%  +200.74% (p=0.000 n=20)
Uint64-32                    2.592n ± 0%    7.714n ± 1%  +197.65% (p=0.000 n=20)
GlobalIntN1000-32            6.266n ± 2%    6.236n ± 1%         ~ (p=0.039 n=20)
IntN1000-32                  4.724n ± 2%   10.410n ± 1%  +120.39% (p=0.000 n=20)
Int64N1000-32                5.490n ± 2%   10.975n ± 2%   +99.89% (p=0.000 n=20)
Int64N1e8-32                 5.513n ± 2%   10.980n ± 1%   +99.15% (p=0.000 n=20)
Int64N1e9-32                 5.476n ± 1%   10.950n ± 0%   +99.96% (p=0.000 n=20)
Int64N2e9-32                 5.501n ± 2%   11.110n ± 1%  +101.96% (p=0.000 n=20)
Int64N1e18-32                9.043n ± 2%   15.180n ± 2%   +67.86% (p=0.000 n=20)
Int64N2e18-32                9.601n ± 2%   15.610n ± 1%   +62.60% (p=0.000 n=20)
Int64N4e18-32                12.00n ± 1%    19.23n ± 2%   +60.14% (p=0.000 n=20)
Int32N1000-32                4.829n ± 2%   10.345n ± 1%  +114.25% (p=0.000 n=20)
Int32N1e8-32                 4.825n ± 2%   10.330n ± 1%  +114.09% (p=0.000 n=20)
Int32N1e9-32                 4.830n ± 2%   10.350n ± 1%  +114.26% (p=0.000 n=20)
Int32N2e9-32                 4.750n ± 2%   10.345n ± 1%  +117.81% (p=0.000 n=20)
Float32-32                   10.89n ± 4%    13.57n ± 1%   +24.61% (p=0.000 n=20)
Float64-32                   19.60n ± 4%    22.95n ± 4%   +17.12% (p=0.000 n=20)
ExpFloat64-32                12.96n ± 3%    15.23n ± 2%   +17.47% (p=0.000 n=20)
NormFloat64-32               7.516n ± 1%   13.780n ± 1%   +83.34% (p=0.000 n=20)
Perm3-32                     36.78n ± 2%    46.62n ± 2%   +26.72% (p=0.000 n=20)
Perm30-32                    238.9n ± 2%    400.7n ± 1%   +67.73% (p=0.000 n=20)
Perm30ViaShuffle-32          189.7n ± 2%    350.5n ± 1%   +84.79% (p=0.000 n=20)
ShuffleOverhead-32           159.8n ± 1%    326.0n ± 2%  +104.01% (p=0.000 n=20)
Concurrent-32                3.286n ± 1%    3.290n ± 0%         ~ (p=0.743 n=20)

On the other hand, compared to the original "update benchmarks" CL,
the cleanups we've made more than compensate for PCG being a bit
slower than LFSR, at least on 64-bit x86. ARM64 (Apple M1) is a bit
slower: perhaps the 64x64→128 multiply is slower there for some reason.
386 is noticeably slower, but it's also a non-SSA backend.

goos: linux
goarch: amd64
pkg: math/rand/v2
cpu: AMD Ryzen 9 7950X 16-Core Processor
                        │ 220860f76f.amd64 │            afa459a2f0.amd64            │
                        │      sec/op      │    sec/op     vs base                  │
SourceUint64-32                1.555n ± 1%    1.450n ± 3%   -6.78% (p=0.000 n=20)
GlobalInt64-32                 2.071n ± 1%    2.067n ± 2%        ~ (p=0.673 n=20)
GlobalInt63Parallel-32        0.1023n ± 1%
GlobalInt64Parallel-32                       0.1044n ± 2%
GlobalUint64-32                5.193n ± 1%    2.085n ± 0%  -59.86% (p=0.000 n=20)
GlobalUint64Parallel-32       0.2341n ± 0%   0.1008n ± 1%  -56.93% (p=0.000 n=20)
Int64-32                       2.056n ± 2%    1.779n ± 1%  -13.47% (p=0.000 n=20)
Uint64-32                      2.077n ± 2%    1.854n ± 2%  -10.74% (p=0.000 n=20)
GlobalIntN1000-32              4.077n ± 2%    3.140n ± 3%  -22.98% (p=0.000 n=20)
IntN1000-32                    3.476n ± 2%    2.496n ± 1%  -28.19% (p=0.000 n=20)
Int64N1000-32                  3.059n ± 1%    2.510n ± 2%  -17.96% (p=0.000 n=20)
Int64N1e8-32                   2.942n ± 1%    2.471n ± 2%  -15.98% (p=0.000 n=20)
Int64N1e9-32                   2.932n ± 1%    2.488n ± 2%  -15.14% (p=0.000 n=20)
Int64N2e9-32                   2.925n ± 1%    2.478n ± 2%  -15.30% (p=0.000 n=20)
Int64N1e18-32                  3.116n ± 1%    3.088n ± 1%        ~ (p=0.013 n=20)
Int64N2e18-32                  4.067n ± 1%    3.493n ± 1%  -14.11% (p=0.000 n=20)
Int64N4e18-32                  4.054n ± 1%    5.060n ± 2%  +24.80% (p=0.000 n=20)
Int32N1000-32                  2.951n ± 1%    2.620n ± 1%  -11.22% (p=0.000 n=20)
Int32N1e8-32                   3.102n ± 1%    2.652n ± 0%  -14.50% (p=0.000 n=20)
Int32N1e9-32                   3.535n ± 1%    2.644n ± 1%  -25.20% (p=0.000 n=20)
Int32N2e9-32                   3.514n ± 1%    2.619n ± 2%  -25.47% (p=0.000 n=20)
Float32-32                     2.760n ± 1%    2.261n ± 1%  -18.06% (p=0.000 n=20)
Float64-32                     2.284n ± 1%    2.241n ± 2%        ~ (p=0.016 n=20)
ExpFloat64-32                  3.757n ± 1%    3.716n ± 1%        ~ (p=0.034 n=20)
NormFloat64-32                 3.837n ± 1%    3.718n ± 1%   -3.09% (p=0.000 n=20)
Perm3-32                       35.23n ± 2%    34.11n ± 2%   -3.19% (p=0.000 n=20)
Perm30-32                      208.8n ± 1%    200.6n ± 0%   -3.93% (p=0.000 n=20)
Perm30ViaShuffle-32            111.7n ± 1%    109.7n ± 1%   -1.84% (p=0.000 n=20)
ShuffleOverhead-32             101.1n ± 1%    107.2n ± 1%   +6.03% (p=0.000 n=20)
Concurrent-32                  2.108n ± 7%    2.108n ± 6%        ~ (p=0.644 n=20)
PCG_DXSM-32                                   1.488n ± 2%

goos: darwin
goarch: arm64
pkg: math/rand/v2
cpu: Apple M1
                       │ 220860f76f.arm64 │            afa459a2f0.arm64            │
                       │      sec/op      │    sec/op     vs base                  │
SourceUint64-8                2.316n ± 1%    2.531n ± 0%   +9.33% (p=0.000 n=20)
GlobalInt64-8                 2.183n ± 1%    2.177n ± 1%        ~ (p=0.533 n=20)
GlobalInt63Parallel-8        0.4331n ± 0%
GlobalInt64Parallel-8                       0.4319n ± 0%
GlobalUint64-8                4.377n ± 2%    2.185n ± 1%  -50.07% (p=0.000 n=20)
GlobalUint64Parallel-8       0.9237n ± 0%   0.4295n ± 1%  -53.50% (p=0.000 n=20)
Int64-8                       2.538n ± 1%    4.104n ± 0%  +61.68% (p=0.000 n=20)
Uint64-8                      2.604n ± 1%    4.080n ± 0%  +56.68% (p=0.000 n=20)
GlobalIntN1000-8              3.857n ± 2%    2.814n ± 1%  -27.04% (p=0.000 n=20)
IntN1000-8                    3.822n ± 2%    4.140n ± 0%   +8.32% (p=0.000 n=20)
Int64N1000-8                  3.318n ± 0%    4.139n ± 0%  +24.74% (p=0.000 n=20)
Int64N1e8-8                   3.349n ± 1%    4.140n ± 0%  +23.64% (p=0.000 n=20)
Int64N1e9-8                   3.317n ± 2%    4.139n ± 0%  +24.80% (p=0.000 n=20)
Int64N2e9-8                   3.317n ± 2%    4.140n ± 0%  +24.81% (p=0.000 n=20)
Int64N1e18-8                  3.542n ± 1%    5.273n ± 0%  +48.85% (p=0.000 n=20)
Int64N2e18-8                  5.087n ± 0%    6.059n ± 0%  +19.12% (p=0.000 n=20)
Int64N4e18-8                  5.084n ± 0%    8.803n ± 0%  +73.16% (p=0.000 n=20)
Int32N1000-8                  3.208n ± 2%    4.131n ± 0%  +28.79% (p=0.000 n=20)
Int32N1e8-8                   3.610n ± 1%    4.131n ± 0%  +14.43% (p=0.000 n=20)
Int32N1e9-8                   4.235n ± 0%    4.131n ± 0%   -2.44% (p=0.000 n=20)
Int32N2e9-8                   4.229n ± 1%    4.131n ± 0%   -2.33% (p=0.000 n=20)
Float32-8                     3.468n ± 0%    4.110n ± 0%  +18.50% (p=0.000 n=20)
Float64-8                     3.447n ± 0%    4.104n ± 0%  +19.05% (p=0.000 n=20)
ExpFloat64-8                  4.567n ± 0%    5.338n ± 0%  +16.86% (p=0.000 n=20)
NormFloat64-8                 4.821n ± 0%    5.731n ± 0%  +18.89% (p=0.000 n=20)
Perm3-8                       28.89n ± 0%    26.62n ± 0%   -7.84% (p=0.000 n=20)
Perm30-8                      175.7n ± 0%    194.6n ± 2%  +10.76% (p=0.000 n=20)
Perm30ViaShuffle-8            153.5n ± 0%    156.4n ± 0%   +1.86% (p=0.000 n=20)
ShuffleOverhead-8             119.8n ± 1%    125.8n ± 0%   +4.97% (p=0.000 n=20)
Concurrent-8                  2.433n ± 3%    2.654n ± 6%   +9.13% (p=0.001 n=20)
PCG_DXSM-8                                   2.531n ± 0%

goos: linux
goarch: 386
pkg: math/rand/v2
cpu: AMD Ryzen 9 7950X 16-Core Processor
                        │ 220860f76f.386 │             afa459a2f0.386              │
                        │     sec/op     │    sec/op     vs base                   │
SourceUint64-32             2.370n ±  1%    7.680n ± 1%  +224.05% (p=0.000 n=20)
GlobalInt64-32              3.569n ±  1%    3.474n ± 3%    -2.66% (p=0.001 n=20)
GlobalInt63Parallel-32     0.3221n ±  1%
GlobalInt64Parallel-32                     0.3253n ± 0%
GlobalUint64-32             8.797n ± 10%    3.433n ± 2%   -60.98% (p=0.000 n=20)
GlobalUint64Parallel-32    0.6351n ±  0%   0.3156n ± 0%   -50.31% (p=0.000 n=20)
Int64-32                    2.612n ±  2%    7.707n ± 1%  +195.04% (p=0.000 n=20)
Uint64-32                   3.350n ±  1%    7.714n ± 1%  +130.25% (p=0.000 n=20)
GlobalIntN1000-32           5.892n ±  1%    6.236n ± 1%    +5.82% (p=0.000 n=20)
IntN1000-32                 4.546n ±  1%   10.410n ± 1%  +128.97% (p=0.000 n=20)
Int64N1000-32               14.59n ±  1%    10.97n ± 2%   -24.75% (p=0.000 n=20)
Int64N1e8-32                14.76n ±  2%    10.98n ± 1%   -25.58% (p=0.000 n=20)
Int64N1e9-32                16.57n ±  1%    10.95n ± 0%   -33.90% (p=0.000 n=20)
Int64N2e9-32                14.54n ±  1%    11.11n ± 1%   -23.62% (p=0.000 n=20)
Int64N1e18-32               16.14n ±  1%    15.18n ± 2%    -5.95% (p=0.000 n=20)
Int64N2e18-32               18.10n ±  1%    15.61n ± 1%   -13.73% (p=0.000 n=20)
Int64N4e18-32               18.65n ±  1%    19.23n ± 2%    +3.08% (p=0.000 n=20)
Int32N1000-32               3.560n ±  1%   10.345n ± 1%  +190.55% (p=0.000 n=20)
Int32N1e8-32                3.770n ±  2%   10.330n ± 1%  +174.01% (p=0.000 n=20)
Int32N1e9-32                4.098n ±  0%   10.350n ± 1%  +152.53% (p=0.000 n=20)
Int32N2e9-32                4.179n ±  1%   10.345n ± 1%  +147.52% (p=0.000 n=20)
Float32-32                  21.18n ±  4%    13.57n ± 1%   -35.93% (p=0.000 n=20)
Float64-32                  20.60n ±  2%    22.95n ± 4%   +11.41% (p=0.000 n=20)
ExpFloat64-32               13.07n ±  0%    15.23n ± 2%   +16.48% (p=0.000 n=20)
NormFloat64-32              7.738n ±  2%   13.780n ± 1%   +78.08% (p=0.000 n=20)
Perm3-32                    36.73n ±  1%    46.62n ± 2%   +26.91% (p=0.000 n=20)
Perm30-32                   211.9n ±  1%    400.7n ± 1%   +89.05% (p=0.000 n=20)
Perm30ViaShuffle-32         165.2n ±  1%    350.5n ± 1%  +112.20% (p=0.000 n=20)
ShuffleOverhead-32          133.9n ±  1%    326.0n ± 2%  +143.37% (p=0.000 n=20)
Concurrent-32               3.287n ±  2%    3.290n ± 0%         ~ (p=0.365 n=20)
PCG_DXSM-32                                 7.793n ± 2%

For #61716.

Change-Id: I4e9c0525b5f84a2ac46f23da9e365495e2d05777
Reviewed-on: https://go-review.googlesource.com/c/go/+/502506
Reviewed-by: Rob Pike <r@golang.org>
Reviewed-by: Dmitri Shuralyov <dmitshur@google.com>
Auto-Submit: Russ Cox <rsc@golang.org>
LUCI-TryBot-Result: Go LUCI <golang-scoped@luci-project-accounts.iam.gserviceaccount.com>
This commit is contained in:
Russ Cox 2023-06-06 13:50:26 -04:00 committed by Gopher Robot
parent 8631fcbf31
commit 8abde68f19
8 changed files with 334 additions and 690 deletions

View File

@ -10,7 +10,6 @@ pkg math/rand/v2, func IntN(int) int #61716
pkg math/rand/v2, func N[$0 intType]($0) $0 #61716
pkg math/rand/v2, func New(Source) *Rand #61716
pkg math/rand/v2, func NewPCG(uint64, uint64) *PCG #61716
pkg math/rand/v2, func NewSource(int64) Source #61716
pkg math/rand/v2, func NewZipf(*Rand, float64, float64, uint64) *Zipf #61716
pkg math/rand/v2, func NormFloat64() float64 #61716
pkg math/rand/v2, func Perm(int) []int #61716

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@ -26,7 +26,7 @@ func TestAuto(t *testing.T) {
// Strictly speaking, we should look for them in order,
// but this is good enough and not significantly more
// likely to have a false positive.
r := New(NewSource(1))
r := New(NewPCG(1, 0))
found := 0
for i := 0; i < 1000; i++ {
x := r.Int64()

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@ -46,9 +46,9 @@ func Example() {
// The use of the global functions is the same, without the receiver.
func Example_rand() {
// Create and seed the generator.
// Typically a non-fixed seed should be used, such as time.Now().UnixNano().
// Typically a non-fixed seed should be used, such as Uint64(), Uint64().
// Using a fixed seed will produce the same output on every run.
r := rand.New(rand.NewSource(99))
r := rand.New(rand.NewPCG(1, 2))
// The tabwriter here helps us generate aligned output.
w := tabwriter.NewWriter(os.Stdout, 1, 1, 1, ' ', 0)
@ -83,17 +83,17 @@ func Example_rand() {
// Perm generates a random permutation of the numbers [0, n).
show("Perm", r.Perm(5), r.Perm(5), r.Perm(5))
// Output:
// Float32 0.73793465 0.38461488 0.9940225
// Float64 0.6919607852308565 0.29140004584133117 0.2262092163027547
// ExpFloat64 0.27263589649304043 1.3214739789908194 2.223639057715668
// NormFloat64 -0.09361151905162404 -1.3531915625472757 0.03212053591352371
// Int32 1824388269 1817075958 91420417
// Int64 3546343826724305832 5724354148158589552 5239846799706671610
// Uint32 1380114714 2295813601 961197529
// IntN(10) 8 4 5
// Int32N(10) 1 8 5
// Int64N(10) 4 2 6
// Perm [0 2 4 3 1] [0 4 2 3 1] [2 1 3 0 4]
// Float32 0.95955694 0.8076733 0.8135684
// Float64 0.4297927436037299 0.797802349388613 0.3883664855410056
// ExpFloat64 0.43463410545541104 0.5513632046504593 0.7426404617374481
// NormFloat64 -0.9303318111676635 -0.04750789419852852 0.22248301107582735
// Int32 2020777787 260808523 851126509
// Int64 5231057920893523323 4257872588489500903 158397175702351138
// Uint32 314478343 1418758728 208955345
// IntN(10) 6 2 0
// Int32N(10) 3 7 7
// Int64N(10) 8 9 4
// Perm [0 3 1 4 2] [4 1 2 0 3] [4 3 2 0 1]
}
func ExamplePerm() {

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@ -1,89 +0,0 @@
// Copyright 2009 The Go Authors. All rights reserved.
// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.
//go:build ignore
// This program computes the value of rngCooked in rng.go,
// which is used for seeding all instances of rand.Source.
// a 64bit and a 63bit version of the array is printed to
// the standard output.
package main
import "fmt"
const (
length = 607
tap = 273
mask = (1 << 63) - 1
a = 48271
m = (1 << 31) - 1
q = 44488
r = 3399
)
var (
rngVec [length]int64
rngTap, rngFeed int
)
func seedrand(x int32) int32 {
hi := x / q
lo := x % q
x = a*lo - r*hi
if x < 0 {
x += m
}
return x
}
func srand(seed int32) {
rngTap = 0
rngFeed = length - tap
seed %= m
if seed < 0 {
seed += m
} else if seed == 0 {
seed = 89482311
}
x := seed
for i := -20; i < length; i++ {
x = seedrand(x)
if i >= 0 {
var u int64
u = int64(x) << 20
x = seedrand(x)
u ^= int64(x) << 10
x = seedrand(x)
u ^= int64(x)
rngVec[i] = u
}
}
}
func vrand() int64 {
rngTap--
if rngTap < 0 {
rngTap += length
}
rngFeed--
if rngFeed < 0 {
rngFeed += length
}
x := (rngVec[rngFeed] + rngVec[rngTap])
rngVec[rngFeed] = x
return x
}
func main() {
srand(1)
for i := uint64(0); i < 7.8e12; i++ {
vrand()
}
fmt.Printf("rngVec after 7.8e12 calls to vrand:\n%#v\n", rngVec)
for i := range rngVec {
rngVec[i] &= mask
}
fmt.Printf("lower 63bit of rngVec after 7.8e12 calls to vrand:\n%#v\n", rngVec)
}

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@ -30,20 +30,6 @@ type Source interface {
Uint64() uint64
}
// NewSource returns a new pseudo-random Source seeded with the given value.
// Unlike the default Source used by top-level functions, this source is not
// safe for concurrent use by multiple goroutines.
// The returned Source implements Source64.
func NewSource(seed int64) Source {
return newSource(seed)
}
func newSource(seed int64) *rngSource {
var rng rngSource
rng.Seed(seed)
return &rng
}
// A Rand is a source of random numbers.
type Rand struct {
src Source
@ -273,7 +259,7 @@ func fastrand64() uint64
type fastSource struct{}
func (*fastSource) Int64() int64 {
return int64(fastrand64() & rngMask)
return int64(fastrand64() << 1 >> 1)
}
func (*fastSource) Uint64() uint64 {

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@ -46,7 +46,7 @@ func nearEqual(a, b, closeEnough, maxError float64) bool {
return absDiff/max(math.Abs(a), math.Abs(b)) < maxError
}
var testSeeds = []int64{1, 1754801282, 1698661970, 1550503961}
var testSeeds = []uint64{1, 1754801282, 1698661970, 1550503961}
// checkSimilarDistribution returns success if the mean and stddev of the
// two statsResults are similar.
@ -104,8 +104,8 @@ func checkSampleSliceDistributions(t *testing.T, samples []float64, nslices int,
// Normal distribution tests
//
func generateNormalSamples(nsamples int, mean, stddev float64, seed int64) []float64 {
r := New(NewSource(seed))
func generateNormalSamples(nsamples int, mean, stddev float64, seed uint64) []float64 {
r := New(NewPCG(seed, seed))
samples := make([]float64, nsamples)
for i := range samples {
samples[i] = r.NormFloat64()*stddev + mean
@ -113,7 +113,7 @@ func generateNormalSamples(nsamples int, mean, stddev float64, seed int64) []flo
return samples
}
func testNormalDistribution(t *testing.T, nsamples int, mean, stddev float64, seed int64) {
func testNormalDistribution(t *testing.T, nsamples int, mean, stddev float64, seed uint64) {
//fmt.Printf("testing nsamples=%v mean=%v stddev=%v seed=%v\n", nsamples, mean, stddev, seed);
samples := generateNormalSamples(nsamples, mean, stddev, seed)
@ -161,8 +161,8 @@ func TestNonStandardNormalValues(t *testing.T) {
// Exponential distribution tests
//
func generateExponentialSamples(nsamples int, rate float64, seed int64) []float64 {
r := New(NewSource(seed))
func generateExponentialSamples(nsamples int, rate float64, seed uint64) []float64 {
r := New(NewPCG(seed, seed))
samples := make([]float64, nsamples)
for i := range samples {
samples[i] = r.ExpFloat64() / rate
@ -170,7 +170,7 @@ func generateExponentialSamples(nsamples int, rate float64, seed int64) []float6
return samples
}
func testExponentialDistribution(t *testing.T, nsamples int, rate float64, seed int64) {
func testExponentialDistribution(t *testing.T, nsamples int, rate float64, seed uint64) {
//fmt.Printf("testing nsamples=%v rate=%v seed=%v\n", nsamples, rate, seed);
mean := 1 / rate
@ -398,7 +398,7 @@ func encodePerm(s []int) int {
// TestUniformFactorial tests several ways of generating a uniform value in [0, n!).
func TestUniformFactorial(t *testing.T) {
r := New(NewSource(testSeeds[0]))
r := New(NewPCG(1, 2))
top := 6
if testing.Short() {
top = 3
@ -436,8 +436,8 @@ func TestUniformFactorial(t *testing.T) {
// See https://en.wikipedia.org/wiki/Pearson%27s_chi-squared_test and
// https://www.johndcook.com/Beautiful_Testing_ch10.pdf.
nsamples := 10 * nfact
if nsamples < 500 {
nsamples = 500
if nsamples < 1000 {
nsamples = 1000
}
samples := make([]float64, nsamples)
for i := range samples {
@ -476,11 +476,11 @@ func TestUniformFactorial(t *testing.T) {
var Sink uint64
func testRand() *Rand {
return New(NewSource(1))
return New(NewPCG(1, 2))
}
func BenchmarkSourceUint64(b *testing.B) {
s := NewSource(1)
s := NewPCG(1, 2)
var t uint64
for n := b.N; n > 0; n-- {
t += s.Uint64()

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@ -33,7 +33,7 @@ func TestRegress(t *testing.T) {
var uint64s = []uint64{1, 10, 32, 1 << 20, 1<<20 + 1, 1000000000, 1 << 30, 1<<31 - 2, 1<<31 - 1, 1000000000000000000, 1 << 60, 1<<63 - 2, 1<<63 - 1, 1<<64 - 2, 1<<64 - 1}
var permSizes = []int{0, 1, 5, 8, 9, 10, 16}
n := reflect.TypeOf(New(NewSource(1))).NumMethod()
n := reflect.TypeOf(New(NewPCG(1, 2))).NumMethod()
p := 0
var buf bytes.Buffer
if *update {
@ -43,7 +43,7 @@ func TestRegress(t *testing.T) {
if *update && i > 0 {
fmt.Fprintf(&buf, "\n")
}
r := New(NewSource(1))
r := New(NewPCG(1, 2))
rv := reflect.ValueOf(r)
m := rv.Type().Method(i)
mv := rv.Method(i)
@ -225,339 +225,339 @@ func replace(t *testing.T, file string, new []byte) {
}
var regressGolden = []any{
float64(0.018945741402288857), // ExpFloat64()
float64(0.13829043737893842), // ExpFloat64()
float64(1.1409883497761604), // ExpFloat64()
float64(1.2449542292186253), // ExpFloat64()
float64(0.4849966704675476), // ExpFloat64()
float64(0.08948056191408837), // ExpFloat64()
float64(0.41380878045769276), // ExpFloat64()
float64(0.31325729628567145), // ExpFloat64()
float64(0.23118058048615886), // ExpFloat64()
float64(0.2090943007446), // ExpFloat64()
float64(2.6861652769471456), // ExpFloat64()
float64(1.3811947596783387), // ExpFloat64()
float64(1.5595976199841015), // ExpFloat64()
float64(2.3469708688771744), // ExpFloat64()
float64(0.5882760784580738), // ExpFloat64()
float64(0.33463787922271115), // ExpFloat64()
float64(0.8799304551478242), // ExpFloat64()
float64(1.616532211418378), // ExpFloat64()
float64(0.09548420514080316), // ExpFloat64()
float64(2.448910012295588), // ExpFloat64()
float64(0.5931317151369719), // ExpFloat64()
float64(0.0680034588807843), // ExpFloat64()
float64(0.036496967459790364), // ExpFloat64()
float64(2.460335459645379), // ExpFloat64()
float64(1.5792300208419903), // ExpFloat64()
float64(0.9149501499404387), // ExpFloat64()
float64(0.43463410545541104), // ExpFloat64()
float64(0.5513632046504593), // ExpFloat64()
float64(0.7426404617374481), // ExpFloat64()
float64(1.2334925132631804), // ExpFloat64()
float64(0.892529142200442), // ExpFloat64()
float64(0.21508763681487764), // ExpFloat64()
float64(1.0208588200798545), // ExpFloat64()
float64(0.7650739736831382), // ExpFloat64()
float64(0.7772788529257701), // ExpFloat64()
float64(1.102732861281323), // ExpFloat64()
float64(0.6982243043885805), // ExpFloat64()
float64(0.4981788638202421), // ExpFloat64()
float64(0.15806532306947937), // ExpFloat64()
float64(0.9419163802459202), // ExpFloat64()
float32(0.39651686), // Float32()
float32(0.38516325), // Float32()
float32(0.06368679), // Float32()
float32(0.027415931), // Float32()
float32(0.3535996), // Float32()
float32(0.9133533), // Float32()
float32(0.40153843), // Float32()
float32(0.034464598), // Float32()
float32(0.4120984), // Float32()
float32(0.51671815), // Float32()
float32(0.9472164), // Float32()
float32(0.14591497), // Float32()
float32(0.42577565), // Float32()
float32(0.7241202), // Float32()
float32(0.7114463), // Float32()
float32(0.01790011), // Float32()
float32(0.22837132), // Float32()
float32(0.5170377), // Float32()
float32(0.9228385), // Float32()
float32(0.9747907), // Float32()
float32(0.95955694), // Float32()
float32(0.8076733), // Float32()
float32(0.8135684), // Float32()
float32(0.92872405), // Float32()
float32(0.97472525), // Float32()
float32(0.5485458), // Float32()
float32(0.97740936), // Float32()
float32(0.042272687), // Float32()
float32(0.99663067), // Float32()
float32(0.035181105), // Float32()
float32(0.45059562), // Float32()
float32(0.86597633), // Float32()
float32(0.8954844), // Float32()
float32(0.090798736), // Float32()
float32(0.46218646), // Float32()
float32(0.5955118), // Float32()
float32(0.08985227), // Float32()
float32(0.19820237), // Float32()
float32(0.7443699), // Float32()
float32(0.56461), // Float32()
float64(0.17213489113047786), // Float64()
float64(0.0813061580926816), // Float64()
float64(0.5094944957341486), // Float64()
float64(0.2193276794677107), // Float64()
float64(0.8287970009760902), // Float64()
float64(0.30682661592006877), // Float64()
float64(0.21230767869565503), // Float64()
float64(0.2757168463782187), // Float64()
float64(0.2967873684321951), // Float64()
float64(0.13374523933395033), // Float64()
float64(0.5777315861149934), // Float64()
float64(0.16732005385910476), // Float64()
float64(0.40620552435192425), // Float64()
float64(0.7929618428784644), // Float64()
float64(0.691570514257735), // Float64()
float64(0.14320118008134408), // Float64()
float64(0.8269708087758376), // Float64()
float64(0.13630191289931604), // Float64()
float64(0.38270814230149663), // Float64()
float64(0.7983258549906352), // Float64()
float64(0.6764556596678251), // Float64()
float64(0.4613862177205994), // Float64()
float64(0.5085473976760264), // Float64()
float64(0.4297927436037299), // Float64()
float64(0.797802349388613), // Float64()
float64(0.3883664855410056), // Float64()
float64(0.8192750264193612), // Float64()
float64(0.3381816951746133), // Float64()
float64(0.9730458047755973), // Float64()
float64(0.281449117585586), // Float64()
float64(0.6047654075331631), // Float64()
float64(0.9278107175107462), // Float64()
float64(0.16387541502137226), // Float64()
float64(0.7263900707339023), // Float64()
float64(0.6974917552729882), // Float64()
float64(0.7640946923790318), // Float64()
float64(0.7188183661358182), // Float64()
float64(0.5856191500346635), // Float64()
float64(0.9549597149363428), // Float64()
float64(0.5168804691962643), // Float64()
int64(5577006791947779410), // Int()
int64(8674665223082153551), // Int()
int64(6129484611666145821), // Int()
int64(4037200794235010051), // Int()
int64(3916589616287113937), // Int()
int64(6334824724549167320), // Int()
int64(605394647632969758), // Int()
int64(1443635317331776148), // Int()
int64(894385949183117216), // Int()
int64(2775422040480279449), // Int()
int64(4751997750760398084), // Int()
int64(7504504064263669287), // Int()
int64(1976235410884491574), // Int()
int64(3510942875414458836), // Int()
int64(2933568871211445515), // Int()
int64(4324745483838182873), // Int()
int64(2610529275472644968), // Int()
int64(2703387474910584091), // Int()
int64(6263450610539110790), // Int()
int64(2015796113853353331), // Int()
int64(4969059760275911952), // Int()
int64(2147869220224756844), // Int()
int64(5246770554000605320), // Int()
int64(5471241176507662746), // Int()
int64(4321634407747778896), // Int()
int64(760102831717374652), // Int()
int64(9221744211007427193), // Int()
int64(8289669384274456462), // Int()
int64(2449715415482412441), // Int()
int64(3389241988064777392), // Int()
int64(2986830195847294191), // Int()
int64(8204908297817606218), // Int()
int64(8134976985547166651), // Int()
int64(2240328155279531677), // Int()
int64(7311121042813227358), // Int()
int64(5231057920893523323), // Int()
int64(4257872588489500903), // Int()
int64(158397175702351138), // Int()
int64(1350674201389090105), // Int()
int64(6093522341581845358), // Int()
int32(649249040), // Int32()
int32(1009863943), // Int32()
int32(1787307747), // Int32()
int32(1543733853), // Int32()
int32(455951040), // Int32()
int32(737470659), // Int32()
int32(1144219036), // Int32()
int32(1241803094), // Int32()
int32(104120228), // Int32()
int32(1396843474), // Int32()
int32(553205347), // Int32()
int32(873639255), // Int32()
int32(1303805905), // Int32()
int32(408727544), // Int32()
int32(1415254188), // Int32()
int32(503466637), // Int32()
int32(1377647429), // Int32()
int32(1388457546), // Int32()
int32(729161618), // Int32()
int32(1308411377), // Int32()
int32(1652216515), // Int32()
int32(1323786710), // Int32()
int32(1684546306), // Int32()
int32(1710678126), // Int32()
int32(503104460), // Int32()
int32(88487615), // Int32()
int32(1073552320), // Int32()
int32(965044529), // Int32()
int32(285184408), // Int32()
int32(394559696), // Int32()
int32(1421454622), // Int32()
int32(955177040), // Int32()
int32(2020777787), // Int32()
int32(260808523), // Int32()
int32(851126509), // Int32()
int32(1682717115), // Int32()
int32(1569423431), // Int32()
int32(1092181682), // Int32()
int32(157239171), // Int32()
int32(709379364), // Int32()
int32(0), // Int32N(1)
int32(4), // Int32N(10)
int32(29), // Int32N(32)
int32(883715), // Int32N(1048576)
int32(222632), // Int32N(1048577)
int32(343411536), // Int32N(1000000000)
int32(957743134), // Int32N(1073741824)
int32(1241803092), // Int32N(2147483646)
int32(104120228), // Int32N(2147483647)
int32(0), // Int32N(1)
int32(2), // Int32N(10)
int32(7), // Int32N(32)
int32(96566), // Int32N(1048576)
int32(199574), // Int32N(1048577)
int32(659029087), // Int32N(1000000000)
int32(606492121), // Int32N(1073741824)
int32(1377647428), // Int32N(2147483646)
int32(1388457546), // Int32N(2147483647)
int32(0), // Int32N(1)
int32(6), // Int32N(10)
int32(8), // Int32N(32)
int32(704922), // Int32N(1048576)
int32(245656), // Int32N(1048577)
int32(41205257), // Int32N(1000000000)
int32(43831929), // Int32N(1073741824)
int32(965044528), // Int32N(2147483646)
int32(285184408), // Int32N(2147483647)
int32(0), // Int32N(1)
int32(6), // Int32N(10)
int32(10), // Int32N(32)
int32(283579), // Int32N(1048576)
int32(127348), // Int32N(1048577)
int32(396336665), // Int32N(1000000000)
int32(911873403), // Int32N(1073741824)
int32(1569423430), // Int32N(2147483646)
int32(1092181681), // Int32N(2147483647)
int32(0), // Int32N(1)
int32(3), // Int32N(10)
int64(5577006791947779410), // Int64()
int64(8674665223082153551), // Int64()
int64(6129484611666145821), // Int64()
int64(4037200794235010051), // Int64()
int64(3916589616287113937), // Int64()
int64(6334824724549167320), // Int64()
int64(605394647632969758), // Int64()
int64(1443635317331776148), // Int64()
int64(894385949183117216), // Int64()
int64(2775422040480279449), // Int64()
int64(4751997750760398084), // Int64()
int64(7504504064263669287), // Int64()
int64(1976235410884491574), // Int64()
int64(3510942875414458836), // Int64()
int64(2933568871211445515), // Int64()
int64(4324745483838182873), // Int64()
int64(2610529275472644968), // Int64()
int64(2703387474910584091), // Int64()
int64(6263450610539110790), // Int64()
int64(2015796113853353331), // Int64()
int64(4969059760275911952), // Int64()
int64(2147869220224756844), // Int64()
int64(5246770554000605320), // Int64()
int64(5471241176507662746), // Int64()
int64(4321634407747778896), // Int64()
int64(760102831717374652), // Int64()
int64(9221744211007427193), // Int64()
int64(8289669384274456462), // Int64()
int64(2449715415482412441), // Int64()
int64(3389241988064777392), // Int64()
int64(2986830195847294191), // Int64()
int64(8204908297817606218), // Int64()
int64(8134976985547166651), // Int64()
int64(2240328155279531677), // Int64()
int64(7311121042813227358), // Int64()
int64(5231057920893523323), // Int64()
int64(4257872588489500903), // Int64()
int64(158397175702351138), // Int64()
int64(1350674201389090105), // Int64()
int64(6093522341581845358), // Int64()
int64(0), // Int64N(1)
int64(4), // Int64N(10)
int64(29), // Int64N(32)
int64(883715), // Int64N(1048576)
int64(222632), // Int64N(1048577)
int64(343411536), // Int64N(1000000000)
int64(957743134), // Int64N(1073741824)
int64(1241803092), // Int64N(2147483646)
int64(104120228), // Int64N(2147483647)
int64(650455930292643530), // Int64N(1000000000000000000)
int64(140311732333010180), // Int64N(1152921504606846976)
int64(3752252032131834642), // Int64N(9223372036854775806)
int64(5599803723869633690), // Int64N(9223372036854775807)
int64(0), // Int64N(1)
int64(6), // Int64N(10)
int64(25), // Int64N(32)
int64(920424), // Int64N(1048576)
int64(677958), // Int64N(1048577)
int64(339542337), // Int64N(1000000000)
int64(701992307), // Int64N(1073741824)
int64(8), // Int64N(32)
int64(704922), // Int64N(1048576)
int64(245656), // Int64N(1048577)
int64(41205257), // Int64N(1000000000)
int64(43831929), // Int64N(1073741824)
int64(965044528), // Int64N(2147483646)
int64(285184408), // Int64N(2147483647)
int64(183731176326946086), // Int64N(1000000000000000000)
int64(680987186633600239), // Int64N(1152921504606846976)
int64(4102454148908803108), // Int64N(9223372036854775806)
int64(8679174511200971228), // Int64N(9223372036854775807)
int64(0), // Int64N(1)
int64(3), // Int64N(10)
int64(27), // Int64N(32)
int64(665831), // Int64N(1048576)
int64(533292), // Int64N(1048577)
int64(73220195), // Int64N(1000000000)
int64(686060398), // Int64N(1073741824)
int64(0), // IntN(1)
int64(4), // IntN(10)
int64(29), // IntN(32)
int64(883715), // IntN(1048576)
int64(222632), // IntN(1048577)
int64(343411536), // IntN(1000000000)
int64(957743134), // IntN(1073741824)
int64(1241803092), // IntN(2147483646)
int64(104120228), // IntN(2147483647)
int64(650455930292643530), // IntN(1000000000000000000)
int64(140311732333010180), // IntN(1152921504606846976)
int64(3752252032131834642), // IntN(9223372036854775806)
int64(5599803723869633690), // IntN(9223372036854775807)
int64(0), // IntN(1)
int64(6), // IntN(10)
int64(25), // IntN(32)
int64(920424), // IntN(1048576)
int64(677958), // IntN(1048577)
int64(339542337), // IntN(1000000000)
int64(701992307), // IntN(1073741824)
int64(8), // IntN(32)
int64(704922), // IntN(1048576)
int64(245656), // IntN(1048577)
int64(41205257), // IntN(1000000000)
int64(43831929), // IntN(1073741824)
int64(965044528), // IntN(2147483646)
int64(285184408), // IntN(2147483647)
int64(183731176326946086), // IntN(1000000000000000000)
int64(680987186633600239), // IntN(1152921504606846976)
int64(4102454148908803108), // IntN(9223372036854775806)
int64(8679174511200971228), // IntN(9223372036854775807)
int64(0), // IntN(1)
int64(3), // IntN(10)
int64(27), // IntN(32)
int64(665831), // IntN(1048576)
int64(533292), // IntN(1048577)
int64(73220195), // IntN(1000000000)
int64(686060398), // IntN(1073741824)
float64(0.06909351197715208), // NormFloat64()
float64(0.5938704963270934), // NormFloat64()
float64(1.306028863617345), // NormFloat64()
float64(1.4117443127537266), // NormFloat64()
float64(0.15696085092285333), // NormFloat64()
float64(1.360954184661658), // NormFloat64()
float64(0.34312984093649135), // NormFloat64()
float64(0.7340067314938814), // NormFloat64()
float64(0.22135434353553696), // NormFloat64()
float64(-0.15741313389982836), // NormFloat64()
float64(-1.080896970111088), // NormFloat64()
float64(-0.6107370548788273), // NormFloat64()
float64(-2.3550050260853643), // NormFloat64()
float64(1.8363976597396832), // NormFloat64()
float64(-0.7167650947520989), // NormFloat64()
float64(0.6860847654927735), // NormFloat64()
float64(0.3403802538398155), // NormFloat64()
float64(-1.3884780626234523), // NormFloat64()
float64(0.14097321427512907), // NormFloat64()
float64(-1.032800550788109), // NormFloat64()
float64(0.37944549835531083), // NormFloat64()
float64(0.07473804659119399), // NormFloat64()
float64(0.20006841200604142), // NormFloat64()
float64(-1.1253144115495104), // NormFloat64()
float64(-0.4005883316435388), // NormFloat64()
float64(-3.0853771402394736), // NormFloat64()
float64(1.932330243076978), // NormFloat64()
float64(1.726131393719264), // NormFloat64()
float64(-0.11707238034168332), // NormFloat64()
float64(-0.9303318111676635), // NormFloat64()
float64(-0.04750789419852852), // NormFloat64()
float64(0.22248301107582735), // NormFloat64()
float64(-1.83630520614272), // NormFloat64()
float64(0.7259521217919809), // NormFloat64()
float64(0.8806882871913041), // NormFloat64()
float64(-1.5022903484270484), // NormFloat64()
float64(0.5972577266810571), // NormFloat64()
float64(1.5631937339973658), // NormFloat64()
float64(-0.3841235370075905), // NormFloat64()
float64(-0.2967295854430667), // NormFloat64()
[]int{}, // Perm(0)
[]int{0}, // Perm(1)
[]int{0, 4, 2, 3, 1}, // Perm(5)
[]int{4, 5, 7, 0, 6, 3, 2, 1}, // Perm(8)
[]int{2, 5, 4, 0, 7, 8, 1, 6, 3}, // Perm(9)
[]int{9, 8, 7, 1, 3, 2, 5, 4, 0, 6}, // Perm(10)
[]int{1, 5, 8, 11, 14, 2, 7, 10, 15, 9, 13, 6, 0, 3, 12, 4}, // Perm(16)
[]int{1, 4, 2, 0, 3}, // Perm(5)
[]int{4, 3, 6, 1, 5, 2, 7, 0}, // Perm(8)
[]int{6, 5, 1, 8, 7, 2, 0, 3, 4}, // Perm(9)
[]int{9, 4, 2, 5, 6, 8, 1, 7, 0, 3}, // Perm(10)
[]int{5, 9, 3, 1, 4, 2, 10, 7, 15, 11, 0, 14, 13, 8, 6, 12}, // Perm(16)
[]int{}, // Perm(0)
[]int{0}, // Perm(1)
[]int{4, 1, 2, 0, 3}, // Perm(5)
[]int{7, 0, 3, 5, 4, 1, 2, 6}, // Perm(8)
[]int{6, 7, 1, 2, 0, 5, 8, 3, 4}, // Perm(9)
[]int{7, 2, 8, 6, 1, 5, 9, 0, 3, 4}, // Perm(10)
[]int{11, 0, 5, 1, 12, 4, 13, 9, 7, 2, 15, 10, 8, 14, 6, 3}, // Perm(16)
[]int{4, 2, 1, 3, 0}, // Perm(5)
[]int{0, 2, 3, 1, 5, 4, 6, 7}, // Perm(8)
[]int{2, 0, 8, 3, 4, 7, 6, 5, 1}, // Perm(9)
[]int{0, 6, 5, 3, 8, 4, 1, 2, 9, 7}, // Perm(10)
[]int{9, 14, 4, 11, 13, 8, 0, 6, 2, 12, 3, 7, 1, 10, 5, 15}, // Perm(16)
[]int{}, // Perm(0)
[]int{0}, // Perm(1)
[]int{2, 4, 0, 3, 1}, // Perm(5)
[]int{4, 2, 5, 0, 6, 3, 1, 7}, // Perm(8)
[]int{3, 2, 8, 6, 5, 7, 1, 4, 0}, // Perm(9)
[]int{2, 0, 7, 5, 6, 1, 8, 3, 4, 9}, // Perm(10)
[]int{3, 2, 1, 0, 7, 5, 4, 6}, // Perm(8)
[]int{1, 3, 4, 5, 0, 2, 7, 8, 6}, // Perm(9)
[]int{1, 8, 4, 7, 2, 6, 5, 9, 0, 3}, // Perm(10)
uint32(1298498081), // Uint32()
uint32(2019727887), // Uint32()
uint32(3574615495), // Uint32()
uint32(3087467707), // Uint32()
uint32(911902081), // Uint32()
uint32(1474941318), // Uint32()
uint32(2288438073), // Uint32()
uint32(2483606188), // Uint32()
uint32(208240456), // Uint32()
uint32(2793686948), // Uint32()
uint32(1106410694), // Uint32()
uint32(1747278511), // Uint32()
uint32(2607611810), // Uint32()
uint32(817455089), // Uint32()
uint32(2830508376), // Uint32()
uint32(1006933274), // Uint32()
uint32(2755294859), // Uint32()
uint32(2776915093), // Uint32()
uint32(1458323237), // Uint32()
uint32(2616822754), // Uint32()
uint32(3304433030), // Uint32()
uint32(2647573421), // Uint32()
uint32(3369092613), // Uint32()
uint32(3421356252), // Uint32()
uint32(1006208920), // Uint32()
uint32(176975231), // Uint32()
uint32(2147104640), // Uint32()
uint32(1930089058), // Uint32()
uint32(570368816), // Uint32()
uint32(789119393), // Uint32()
uint32(2842909244), // Uint32()
uint32(1910354080), // Uint32()
uint32(4041555575), // Uint32()
uint32(521617046), // Uint32()
uint32(1702253018), // Uint32()
uint32(3365434230), // Uint32()
uint32(3138846863), // Uint32()
uint32(2184363364), // Uint32()
uint32(314478343), // Uint32()
uint32(1418758728), // Uint32()
uint32(0), // Uint32N(1)
uint32(4), // Uint32N(10)
uint32(29), // Uint32N(32)
uint32(883715), // Uint32N(1048576)
uint32(222632), // Uint32N(1048577)
uint32(343411536), // Uint32N(1000000000)
uint32(957743134), // Uint32N(1073741824)
uint32(1241803092), // Uint32N(2147483646)
uint32(104120228), // Uint32N(2147483647)
uint32(2793686946), // Uint32N(4294967294)
uint32(1106410694), // Uint32N(4294967295)
uint32(0), // Uint32N(1)
uint32(6), // Uint32N(10)
uint32(20), // Uint32N(32)
uint32(240907), // Uint32N(1048576)
uint32(245833), // Uint32N(1048577)
uint32(641517075), // Uint32N(1000000000)
uint32(340335899), // Uint32N(1073741824)
uint32(729161617), // Uint32N(2147483646)
uint32(1308411376), // Uint32N(2147483647)
uint32(8), // Uint32N(32)
uint32(704922), // Uint32N(1048576)
uint32(245656), // Uint32N(1048577)
uint32(41205257), // Uint32N(1000000000)
uint32(43831929), // Uint32N(1073741824)
uint32(965044528), // Uint32N(2147483646)
uint32(285184408), // Uint32N(2147483647)
uint32(789119393), // Uint32N(4294967294)
uint32(2842909244), // Uint32N(4294967295)
uint32(0), // Uint32N(1)
uint32(9), // Uint32N(10)
uint32(29), // Uint32N(32)
uint32(266590), // Uint32N(1048576)
uint32(821640), // Uint32N(1048577)
uint32(730819735), // Uint32N(1000000000)
uint32(522841378), // Uint32N(1073741824)
uint32(157239171), // Uint32N(2147483646)
uint32(709379364), // Uint32N(2147483647)
uint64(5577006791947779410), // Uint64()
uint64(8674665223082153551), // Uint64()
uint64(15352856648520921629), // Uint64()
uint64(13260572831089785859), // Uint64()
uint64(3916589616287113937), // Uint64()
uint64(6334824724549167320), // Uint64()
uint64(9828766684487745566), // Uint64()
uint64(10667007354186551956), // Uint64()
uint64(894385949183117216), // Uint64()
uint64(11998794077335055257), // Uint64()
uint64(4751997750760398084), // Uint64()
uint64(7504504064263669287), // Uint64()
uint64(11199607447739267382), // Uint64()
uint64(3510942875414458836), // Uint64()
uint64(12156940908066221323), // Uint64()
uint64(4324745483838182873), // Uint64()
uint64(11833901312327420776), // Uint64()
uint64(11926759511765359899), // Uint64()
uint64(6263450610539110790), // Uint64()
uint64(11239168150708129139), // Uint64()
uint64(14192431797130687760), // Uint64()
uint64(11371241257079532652), // Uint64()
uint64(14470142590855381128), // Uint64()
uint64(14694613213362438554), // Uint64()
uint64(4321634407747778896), // Uint64()
uint64(760102831717374652), // Uint64()
uint64(9221744211007427193), // Uint64()
uint64(8289669384274456462), // Uint64()
uint64(2449715415482412441), // Uint64()
uint64(3389241988064777392), // Uint64()
uint64(12210202232702069999), // Uint64()
uint64(8204908297817606218), // Uint64()
uint64(17358349022401942459), // Uint64()
uint64(2240328155279531677), // Uint64()
uint64(7311121042813227358), // Uint64()
uint64(14454429957748299131), // Uint64()
uint64(13481244625344276711), // Uint64()
uint64(9381769212557126946), // Uint64()
uint64(1350674201389090105), // Uint64()
uint64(6093522341581845358), // Uint64()
uint64(0), // Uint64N(1)
uint64(4), // Uint64N(10)
uint64(29), // Uint64N(32)
uint64(883715), // Uint64N(1048576)
uint64(222632), // Uint64N(1048577)
uint64(343411536), // Uint64N(1000000000)
uint64(957743134), // Uint64N(1073741824)
uint64(1241803092), // Uint64N(2147483646)
uint64(104120228), // Uint64N(2147483647)
uint64(650455930292643530), // Uint64N(1000000000000000000)
uint64(140311732333010180), // Uint64N(1152921504606846976)
uint64(3752252032131834642), // Uint64N(9223372036854775806)
uint64(5599803723869633690), // Uint64N(9223372036854775807)
uint64(3510942875414458835), // Uint64N(18446744073709551614)
uint64(12156940908066221322), // Uint64N(18446744073709551615)
uint64(0), // Uint64N(1)
uint64(6), // Uint64N(10)
uint64(27), // Uint64N(32)
uint64(205190), // Uint64N(1048576)
uint64(638873), // Uint64N(1048577)
uint64(0), // Uint64N(1)
uint64(6), // Uint64N(10)
uint64(8), // Uint64N(32)
uint64(704922), // Uint64N(1048576)
uint64(245656), // Uint64N(1048577)
uint64(41205257), // Uint64N(1000000000)
uint64(43831929), // Uint64N(1073741824)
uint64(965044528), // Uint64N(2147483646)
uint64(285184408), // Uint64N(2147483647)
uint64(183731176326946086), // Uint64N(1000000000000000000)
uint64(680987186633600239), // Uint64N(1152921504606846976)
uint64(4102454148908803108), // Uint64N(9223372036854775806)
uint64(8679174511200971228), // Uint64N(9223372036854775807)
uint64(2240328155279531676), // Uint64N(18446744073709551614)
uint64(7311121042813227357), // Uint64N(18446744073709551615)
uint64(0), // Uint64N(1)
uint64(7), // Uint64N(10)
uint64(2), // Uint64N(32)
uint64(312633), // Uint64N(1048576)
uint64(346376), // Uint64N(1048577)
uint64(0), // UintN(1)
uint64(4), // UintN(10)
uint64(29), // UintN(32)
uint64(883715), // UintN(1048576)
uint64(222632), // UintN(1048577)
uint64(343411536), // UintN(1000000000)
uint64(957743134), // UintN(1073741824)
uint64(1241803092), // UintN(2147483646)
uint64(104120228), // UintN(2147483647)
uint64(650455930292643530), // UintN(1000000000000000000)
uint64(140311732333010180), // UintN(1152921504606846976)
uint64(3752252032131834642), // UintN(9223372036854775806)
uint64(5599803723869633690), // UintN(9223372036854775807)
uint64(3510942875414458835), // UintN(18446744073709551614)
uint64(12156940908066221322), // UintN(18446744073709551615)
uint64(0), // UintN(1)
uint64(6), // UintN(10)
uint64(27), // UintN(32)
uint64(205190), // UintN(1048576)
uint64(638873), // UintN(1048577)
uint64(0), // UintN(1)
uint64(6), // UintN(10)
uint64(8), // UintN(32)
uint64(704922), // UintN(1048576)
uint64(245656), // UintN(1048577)
uint64(41205257), // UintN(1000000000)
uint64(43831929), // UintN(1073741824)
uint64(965044528), // UintN(2147483646)
uint64(285184408), // UintN(2147483647)
uint64(183731176326946086), // UintN(1000000000000000000)
uint64(680987186633600239), // UintN(1152921504606846976)
uint64(4102454148908803108), // UintN(9223372036854775806)
uint64(8679174511200971228), // UintN(9223372036854775807)
uint64(2240328155279531676), // UintN(18446744073709551614)
uint64(7311121042813227357), // UintN(18446744073709551615)
uint64(0), // UintN(1)
uint64(7), // UintN(10)
uint64(2), // UintN(32)
uint64(312633), // UintN(1048576)
uint64(346376), // UintN(1048577)
}

View File

@ -1,252 +0,0 @@
// Copyright 2009 The Go Authors. All rights reserved.
// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.
package rand
/*
* Uniform distribution
*
* algorithm by
* DP Mitchell and JA Reeds
*/
const (
rngLen = 607
rngTap = 273
rngMax = 1 << 63
rngMask = rngMax - 1
int32max = (1 << 31) - 1
)
var (
// rngCooked used for seeding. See gen_cooked.go for details.
rngCooked [rngLen]int64 = [...]int64{
-4181792142133755926, -4576982950128230565, 1395769623340756751, 5333664234075297259,
-6347679516498800754, 9033628115061424579, 7143218595135194537, 4812947590706362721,
7937252194349799378, 5307299880338848416, 8209348851763925077, -7107630437535961764,
4593015457530856296, 8140875735541888011, -5903942795589686782, -603556388664454774,
-7496297993371156308, 113108499721038619, 4569519971459345583, -4160538177779461077,
-6835753265595711384, -6507240692498089696, 6559392774825876886, 7650093201692370310,
7684323884043752161, -8965504200858744418, -2629915517445760644, 271327514973697897,
-6433985589514657524, 1065192797246149621, 3344507881999356393, -4763574095074709175,
7465081662728599889, 1014950805555097187, -4773931307508785033, -5742262670416273165,
2418672789110888383, 5796562887576294778, 4484266064449540171, 3738982361971787048,
-4699774852342421385, 10530508058128498, -589538253572429690, -6598062107225984180,
8660405965245884302, 10162832508971942, -2682657355892958417, 7031802312784620857,
6240911277345944669, 831864355460801054, -1218937899312622917, 2116287251661052151,
2202309800992166967, 9161020366945053561, 4069299552407763864, 4936383537992622449,
457351505131524928, -8881176990926596454, -6375600354038175299, -7155351920868399290,
4368649989588021065, 887231587095185257, -3659780529968199312, -2407146836602825512,
5616972787034086048, -751562733459939242, 1686575021641186857, -5177887698780513806,
-4979215821652996885, -1375154703071198421, 5632136521049761902, -8390088894796940536,
-193645528485698615, -5979788902190688516, -4907000935050298721, -285522056888777828,
-2776431630044341707, 1679342092332374735, 6050638460742422078, -2229851317345194226,
-1582494184340482199, 5881353426285907985, 812786550756860885, 4541845584483343330,
-6497901820577766722, 4980675660146853729, -4012602956251539747, -329088717864244987,
-2896929232104691526, 1495812843684243920, -2153620458055647789, 7370257291860230865,
-2466442761497833547, 4706794511633873654, -1398851569026877145, 8549875090542453214,
-9189721207376179652, -7894453601103453165, 7297902601803624459, 1011190183918857495,
-6985347000036920864, 5147159997473910359, -8326859945294252826, 2659470849286379941,
6097729358393448602, -7491646050550022124, -5117116194870963097, -896216826133240300,
-745860416168701406, 5803876044675762232, -787954255994554146, -3234519180203704564,
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}
)
type rngSource struct {
tap int // index into vec
feed int // index into vec
vec [rngLen]int64 // current feedback register
}
// seed rng x[n+1] = 48271 * x[n] mod (2**31 - 1)
func seedrand(x int32) int32 {
const (
A = 48271
Q = 44488
R = 3399
)
hi := x / Q
lo := x % Q
x = A*lo - R*hi
if x < 0 {
x += int32max
}
return x
}
// Seed uses the provided seed value to initialize the generator to a deterministic state.
func (rng *rngSource) Seed(seed int64) {
rng.tap = 0
rng.feed = rngLen - rngTap
seed = seed % int32max
if seed < 0 {
seed += int32max
}
if seed == 0 {
seed = 89482311
}
x := int32(seed)
for i := -20; i < rngLen; i++ {
x = seedrand(x)
if i >= 0 {
var u int64
u = int64(x) << 40
x = seedrand(x)
u ^= int64(x) << 20
x = seedrand(x)
u ^= int64(x)
u ^= rngCooked[i]
rng.vec[i] = u
}
}
}
// Int64 returns a non-negative pseudo-random 63-bit integer as an int64.
func (rng *rngSource) Int64() int64 {
return int64(rng.Uint64() & rngMask)
}
// Uint64 returns a non-negative pseudo-random 64-bit integer as a uint64.
func (rng *rngSource) Uint64() uint64 {
rng.tap--
if rng.tap < 0 {
rng.tap += rngLen
}
rng.feed--
if rng.feed < 0 {
rng.feed += rngLen
}
x := rng.vec[rng.feed] + rng.vec[rng.tap]
rng.vec[rng.feed] = x
return uint64(x)
}