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| 1 | +Random Number Generation |
| 2 | +======================== |
| 3 | + |
| 4 | +DPPY does not provides a random number generation algorithm that can be executed |
| 5 | +on the GPU. |
| 6 | + |
| 7 | +DPPY provides access to NumPy random algorithms that can be executed on the GPU |
| 8 | +via integration with `dpNP Random`_. |
| 9 | + |
| 10 | +.. _`dpNP Random`: https://intelpython.github.io/dpnp/reference/comparison.html#random-sampling |
| 11 | + |
| 12 | + |
| 13 | +DPPY supported functions |
| 14 | +------------------------ |
| 15 | + |
| 16 | +Simple random |
| 17 | +````````````` |
| 18 | + |
| 19 | +- `random <https://numpy.org/doc/1.16/reference/generated/numpy.random.random.html#numpy.random.random>`_ |
| 20 | +- `sample <https://numpy.org/doc/1.16/reference/generated/numpy.random.sample.html#numpy.random.sample>`_ |
| 21 | +- `ranf <https://numpy.org/doc/1.16/reference/generated/numpy.random.ranf.html#numpy.random.ranf>`_ |
| 22 | +- `random_sample <https://numpy.org/doc/1.16/reference/generated/numpy.random.random_sample.html#numpy.random.random_sample>`_ |
| 23 | +- `rand <https://numpy.org/doc/1.16/reference/generated/numpy.random.rand.html#numpy.random.rand>`_ |
| 24 | +- `randint <https://numpy.org/doc/1.16/reference/generated/numpy.random.randint.html#numpy.random.randint>`_ |
| 25 | +- `random_integers <https://numpy.org/doc/1.16/reference/generated/numpy.random.random_integers.html#numpy.random.random_integers>`_ |
| 26 | + |
| 27 | +Distribution |
| 28 | +```````````` |
| 29 | + |
| 30 | +- `beta <https://numpy.org/doc/1.16/reference/generated/numpy.random.beta.html#numpy.random.beta>`_ |
| 31 | +- `binomial <https://numpy.org/doc/1.16/reference/generated/numpy.random.binomial.html#numpy.random.binomial>`_ |
| 32 | +- `chisquare <https://numpy.org/doc/1.16/reference/generated/numpy.random.chisquare.html#numpy.random.chisquare>`_ |
| 33 | +- `exponential <https://numpy.org/doc/1.16/reference/generated/numpy.random.exponential.html#numpy.random.exponential>`_ |
| 34 | +- `gamma <https://numpy.org/doc/1.16/reference/generated/numpy.random.gamma.html#numpy.random.gamma>`_ |
| 35 | +- `geometric <https://numpy.org/doc/1.16/reference/generated/numpy.random.geometric.html#numpy.random.geometric>`_ |
| 36 | +- `gumbel <https://numpy.org/doc/1.16/reference/generated/numpy.random.gumbel.html#numpy.random.gumbel>`_ |
| 37 | +- `hypergeometric <https://numpy.org/doc/1.16/reference/generated/numpy.random.hypergeometric.html#numpy.random.hypergeometric>`_ |
| 38 | +- `laplace <https://numpy.org/doc/1.16/reference/generated/numpy.random.laplace.html#numpy.random.laplace>`_ |
| 39 | +- `lognormal <https://numpy.org/doc/1.16/reference/generated/numpy.random.lognormal.html#numpy.random.lognormal>`_ |
| 40 | +- `multinomial <https://numpy.org/doc/1.16/reference/generated/numpy.random.multinomial.html#numpy.random.multinomial>`_ |
| 41 | +- `multivariate_normal <https://numpy.org/doc/1.16/reference/generated/numpy.random.multivariate_normal.html#numpy.random.multivariate_normal>`_ |
| 42 | +- `negative_binomial <https://numpy.org/doc/1.16/reference/generated/numpy.random.negative_binomial.html#numpy.random.negative_binomial>`_ |
| 43 | +- `normal <https://numpy.org/doc/1.16/reference/generated/numpy.random.normal.html#numpy.random.normal>`_ |
| 44 | +- `poisson <https://numpy.org/doc/1.16/reference/generated/numpy.random.poisson.html#numpy.random.poisson>`_ |
| 45 | +- `rayleigh <https://numpy.org/doc/1.16/reference/generated/numpy.random.rayleigh.html#numpy.random.rayleigh>`_ |
| 46 | +- `standard_cauchy <https://numpy.org/doc/1.16/reference/generated/numpy.random.standard_cauchy.html#numpy.random.standard_cauchy>`_ |
| 47 | +- `standard_exponential <https://numpy.org/doc/1.16/reference/generated/numpy.random.standard_exponential.html#numpy.random.standard_exponential>`_ |
| 48 | +- `standard_gamma <https://numpy.org/doc/1.16/reference/generated/numpy.random.standard_gamma.html#numpy.random.standard_gamma>`_ |
| 49 | +- `standard_normal <https://numpy.org/doc/1.16/reference/generated/numpy.random.standard_normal.html#numpy.random.standard_normal>`_ |
| 50 | +- `uniform <https://numpy.org/doc/1.16/reference/generated/numpy.random.uniform.html#numpy.random.uniform>`_ |
| 51 | +- `weibull <https://numpy.org/doc/1.16/reference/generated/numpy.random.weibull.html#numpy.random.weibull>`_ |
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