more random functions #4145
more random functions #4145
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python/hail/expr/functions.py
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| Parameters | ||
| ---------- | ||
| a : float or :class:`.Expression` of type :py:data:`.tfloat64` |
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you can simplify this here and elsewhere:
float or :class`Float64Expression`
python/hail/expr/functions.py
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| max=nullable(expr_float64), | ||
| seed=nullable(int)) | ||
| def rand_beta(a, b, min=None, max=None, seed=None) -> Float64Expression: | ||
| """Returns a random floating-point number drawn from a beta distribution |
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I'd shorten to "Returns a random draw from a beta distribution." and link beta distribution to: https://en.wikipedia.org/wiki/Beta_distribution
python/hail/expr/functions.py
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| ---------- | ||
| a : float or :class:`.Expression` of type :py:data:`.tfloat64` | ||
| b : float or :class:`.Expression` of type :py:data:`.tfloat64` | ||
| min : float or :class:`.Expression` of type :py:data:`.tfloat64` |
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convention is:
float or :class`Float64Expression`, optional
python/hail/expr/functions.py
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| (Optional) Left boundary of truncated beta distribution. | ||
| max : float or :class:`.Expression` of type :py:data:`.tfloat64` | ||
| (Optional) Right boundary of truncated beta distribution. | ||
| seed : :obj:`int` or `None` |
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:obj:`int`, optional
make this change below too (and check that all these random functions are consistently documented)
python/hail/expr/functions.py
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| max : float or :class:`.Expression` of type :py:data:`.tfloat64` | ||
| (Optional) Right boundary of truncated beta distribution. | ||
| seed : :obj:`int` or `None` | ||
| If not `None`, function will be seeded with provided seed. |
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Just put "Random seed".
python/hail/methods/statgen.py
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| @@ -2207,6 +2204,7 @@ def balding_nichols_model(n_populations, n_samples, n_variants, n_partitions=Non | |||
| mixture) | |||
| return MatrixTable(jmt) | |||
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| def rgamma(a: Double, scale: Double): Double = Gamma.random(a, scale, random) | ||
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| def rdraw(a: Array[Double]): Int = { |
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| def rdraw(a: Array[Double]): Int = { | ||
| val sum = a.sum | ||
| val probs = Array.tabulate(a.length)(i => a(i) / sum) |
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no need for rescaling. Just set draw = random.nextDouble() * sum
python/hail/expr/functions.py
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| Warning | ||
| ------- | ||
| This function may be slow over very large arrays. |
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This function may be slow when the number of categories is large.
| Examples | ||
| -------- | ||
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| >>> hl.rand_dirichlet([1, 1, 1]).value |
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what behavior do you get if a value is negative?
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>>> hl.rand_dirichlet([-1, -1, 1]).value
[nan, nan, nan]
python/hail/expr/functions.py
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| """ | ||
| return _seeded_func("rand_norm", tfloat64, seed, mean, sd) | ||
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| @typecheck(lamb=expr_float64, seed=nullable(int)) | ||
| def rand_pois(lamb, seed=None) -> Float64Expression: | ||
| """Samples from a Poisson distribution with rate parameter `lamb` (RNG). | ||
| """Samples from a Poisson distribution with rate parameter `lamb`. |
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please change parameter name to lambda and link to https://en.wikipedia.org/wiki/Poisson_distribution
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lambda is a reserved word in python, unfortunately
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oh right, that's why we used lamb. ok
python/hail/expr/functions.py
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| """Returns a random index from an array of unnormalized probabilities. | ||
| def rand_cat(prob, seed=None) -> Int32Expression: | ||
| """Samples from a `categorical distribution | ||
| <https://en.wikipedia.org/wiki/Categorical_distribution>`__ |
python/hail/expr/functions.py
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| def rand_beta(a, b, lower=None, upper=None, seed=None) -> Float64Expression: | ||
| """Samples from a `beta distribution | ||
| <https://en.wikipedia.org/wiki/Beta_distribution>`__ with parameters `a` | ||
| (alpha) and `b` (beta). |
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don't forget to make a discuss post on the breaking change on the parameter names (lower/upper) |
(mostly the ones that balding nichols uses.)