mirror of
https://github.com/astral-sh/ruff.git
synced 2025-08-04 02:38:25 +00:00
[numpy] numpy-legacy-random (#2960)
The new `Generator` in NumPy uses bits provided by [PCG64](https://numpy.org/doc/stable/reference/random/bit_generators/pcg64.html#numpy.random.PCG64) which has better statistical properties than the legacy [MT19937](https://numpy.org/doc/stable/reference/random/bit_generators/mt19937.html#numpy.random.MT19937) used in [RandomState](https://numpy.org/doc/stable/reference/random/legacy.html#numpy.random.RandomState). Global random functions can also be problematic with parallel processing. This rule is probably quite useful for data scientists (perhaps in combination with `nbqa`) References: - [Legacy Random Generation](https://numpy.org/doc/stable/reference/random/legacy.html#legacy) - [Random Sampling](https://numpy.org/doc/stable/reference/random/index.html#random-quick-start) - [Using PyTorch + NumPy? You're making a mistake.](https://tanelp.github.io/posts/a-bug-that-plagues-thousands-of-open-source-ml-projects/)
This commit is contained in:
Simon Brugman
GitHub
parent
e081455b06
commit
34664a0ca0
10 changed files with 757 additions and 0 deletions
|
|
@ -1506,6 +1506,7 @@ For more, see [tryceratops](https://pypi.org/project/tryceratops/1.1.0/) on PyPI
|
|||
| Code | Name | Message | Fix |
|
||||
| ---- | ---- | ------- | --- |
|
||||
| NPY001 | [numpy-deprecated-type-alias](https://beta.ruff.rs/docs/rules/numpy-deprecated-type-alias/) | Type alias `np.{type_name}` is deprecated, replace with builtin type | 🛠 |
|
||||
| NPY002 | [numpy-legacy-random](https://beta.ruff.rs/docs/rules/numpy-legacy-random/) | Replace legacy `np.random.{method_name}` call with `np.random.Generator` | |
|
||||
|
||||
### Ruff-specific rules (RUF)
|
||||
|
||||
|
|
|
|||
62
crates/ruff/resources/test/fixtures/numpy/NPY002.py
vendored
Normal file
62
crates/ruff/resources/test/fixtures/numpy/NPY002.py
vendored
Normal file
|
|
@ -0,0 +1,62 @@
|
|||
# Do this (new version)
|
||||
from numpy.random import default_rng
|
||||
rng = default_rng()
|
||||
vals = rng.standard_normal(10)
|
||||
more_vals = rng.standard_normal(10)
|
||||
numbers = rng.integers(high, size=5)
|
||||
|
||||
# instead of this (legacy version)
|
||||
from numpy import random
|
||||
vals = random.standard_normal(10)
|
||||
more_vals = random.standard_normal(10)
|
||||
numbers = random.integers(high, size=5)
|
||||
|
||||
import numpy
|
||||
numpy.random.seed()
|
||||
numpy.random.get_state()
|
||||
numpy.random.set_state()
|
||||
numpy.random.rand()
|
||||
numpy.random.randn()
|
||||
numpy.random.randint()
|
||||
numpy.random.random_integers()
|
||||
numpy.random.random_sample()
|
||||
numpy.random.choice()
|
||||
numpy.random.bytes()
|
||||
numpy.random.shuffle()
|
||||
numpy.random.permutation()
|
||||
numpy.random.beta()
|
||||
numpy.random.binomial()
|
||||
numpy.random.chisquare()
|
||||
numpy.random.dirichlet()
|
||||
numpy.random.exponential()
|
||||
numpy.random.f()
|
||||
numpy.random.gamma()
|
||||
numpy.random.geometric()
|
||||
numpy.random.get_state()
|
||||
numpy.random.gumbel()
|
||||
numpy.random.hypergeometric()
|
||||
numpy.random.laplace()
|
||||
numpy.random.logistic()
|
||||
numpy.random.lognormal()
|
||||
numpy.random.logseries()
|
||||
numpy.random.multinomial()
|
||||
numpy.random.multivariate_normal()
|
||||
numpy.random.negative_binomial()
|
||||
numpy.random.noncentral_chisquare()
|
||||
numpy.random.noncentral_f()
|
||||
numpy.random.normal()
|
||||
numpy.random.pareto()
|
||||
numpy.random.poisson()
|
||||
numpy.random.power()
|
||||
numpy.random.rayleigh()
|
||||
numpy.random.standard_cauchy()
|
||||
numpy.random.standard_exponential()
|
||||
numpy.random.standard_gamma()
|
||||
numpy.random.standard_normal()
|
||||
numpy.random.standard_t()
|
||||
numpy.random.triangular()
|
||||
numpy.random.uniform()
|
||||
numpy.random.vonmises()
|
||||
numpy.random.wald()
|
||||
numpy.random.weibull()
|
||||
numpy.random.zipf()
|
||||
|
|
@ -2841,6 +2841,11 @@ where
|
|||
flake8_use_pathlib::helpers::replaceable_by_pathlib(self, func);
|
||||
}
|
||||
|
||||
// numpy
|
||||
if self.settings.rules.enabled(&Rule::NumpyLegacyRandom) {
|
||||
numpy::rules::numpy_legacy_random(self, func);
|
||||
}
|
||||
|
||||
// flake8-logging-format
|
||||
if self.settings.rules.enabled(&Rule::LoggingStringFormat)
|
||||
|| self.settings.rules.enabled(&Rule::LoggingPercentFormat)
|
||||
|
|
|
|||
|
|
@ -590,6 +590,7 @@ pub fn code_to_rule(linter: Linter, code: &str) -> Option<Rule> {
|
|||
|
||||
// numpy
|
||||
(Numpy, "001") => Rule::NumpyDeprecatedTypeAlias,
|
||||
(Numpy, "002") => Rule::NumpyLegacyRandom,
|
||||
|
||||
// ruff
|
||||
(Ruff, "001") => Rule::AmbiguousUnicodeCharacterString,
|
||||
|
|
|
|||
|
|
@ -552,6 +552,7 @@ ruff_macros::register_rules!(
|
|||
rules::flake8_self::rules::PrivateMemberAccess,
|
||||
// numpy
|
||||
rules::numpy::rules::NumpyDeprecatedTypeAlias,
|
||||
rules::numpy::rules::NumpyLegacyRandom,
|
||||
// ruff
|
||||
rules::ruff::rules::AmbiguousUnicodeCharacterString,
|
||||
rules::ruff::rules::AmbiguousUnicodeCharacterDocstring,
|
||||
|
|
|
|||
|
|
@ -14,6 +14,7 @@ mod tests {
|
|||
use crate::{assert_yaml_snapshot, settings};
|
||||
|
||||
#[test_case(Rule::NumpyDeprecatedTypeAlias, Path::new("NPY001.py"); "NPY001")]
|
||||
#[test_case(Rule::NumpyLegacyRandom, Path::new("NPY002.py"); "NPY002")]
|
||||
fn rules(rule_code: Rule, path: &Path) -> Result<()> {
|
||||
let snapshot = format!("{}_{}", rule_code.as_ref(), path.to_string_lossy());
|
||||
let diagnostics = test_path(
|
||||
|
|
|
|||
|
|
@ -1,3 +1,5 @@
|
|||
pub use deprecated_type_alias::{deprecated_type_alias, NumpyDeprecatedTypeAlias};
|
||||
pub use numpy_legacy_random::{numpy_legacy_random, NumpyLegacyRandom};
|
||||
|
||||
mod deprecated_type_alias;
|
||||
mod numpy_legacy_random;
|
||||
|
|
|
|||
128
crates/ruff/src/rules/numpy/rules/numpy_legacy_random.rs
Normal file
128
crates/ruff/src/rules/numpy/rules/numpy_legacy_random.rs
Normal file
|
|
@ -0,0 +1,128 @@
|
|||
use ruff_macros::{define_violation, derive_message_formats};
|
||||
use rustpython_parser::ast::Expr;
|
||||
|
||||
use crate::ast::types::Range;
|
||||
use crate::checkers::ast::Checker;
|
||||
use crate::registry::Diagnostic;
|
||||
use crate::violation::Violation;
|
||||
|
||||
define_violation!(
|
||||
/// ## What it does
|
||||
/// Checks for the use of legacy `np.random` function calls.
|
||||
///
|
||||
/// ## Why is this bad?
|
||||
/// According to the NumPy documentation's [Legacy Random Generation]:
|
||||
///
|
||||
/// > The `RandomState` provides access to legacy generators... This class
|
||||
/// > should only be used if it is essential to have randoms that are
|
||||
/// > identical to what would have been produced by previous versions of
|
||||
/// > NumPy.
|
||||
///
|
||||
/// The members exposed directly on the `random` module are convenience
|
||||
/// functions that alias to methods on a global singleton `RandomState`
|
||||
/// instance. NumPy recommends using a dedicated `Generator` instance
|
||||
/// rather than the random variate generation methods exposed directly on
|
||||
/// the `random` module, as the new `Generator` is both faster and has
|
||||
/// better statistical properties.
|
||||
///
|
||||
/// See the documentation on [Random Sampling] and [NEP 19] for further
|
||||
/// details.
|
||||
///
|
||||
/// ## Examples
|
||||
/// ```python
|
||||
/// import numpy as np
|
||||
///
|
||||
/// np.random.seed(1337)
|
||||
/// np.random.normal()
|
||||
/// ```
|
||||
///
|
||||
/// Use instead:
|
||||
/// ```python
|
||||
/// rng = np.random.default_rng(1337)
|
||||
/// rng.normal()
|
||||
/// ```
|
||||
///
|
||||
/// [Legacy Random Generation]: https://numpy.org/doc/stable/reference/random/legacy.html#legacy
|
||||
/// [Random Sampling]: https://numpy.org/doc/stable/reference/random/index.html#random-quick-start
|
||||
/// [NEP 19]: https://numpy.org/neps/nep-0019-rng-policy.html
|
||||
pub struct NumpyLegacyRandom {
|
||||
pub method_name: String,
|
||||
}
|
||||
);
|
||||
impl Violation for NumpyLegacyRandom {
|
||||
#[derive_message_formats]
|
||||
fn message(&self) -> String {
|
||||
let NumpyLegacyRandom { method_name } = self;
|
||||
format!("Replace legacy `np.random.{method_name}` call with `np.random.Generator`")
|
||||
}
|
||||
}
|
||||
|
||||
/// NPY002
|
||||
pub fn numpy_legacy_random(checker: &mut Checker, expr: &Expr) {
|
||||
if let Some(method_name) = checker.resolve_call_path(expr).and_then(|call_path| {
|
||||
// seeding state
|
||||
if call_path.as_slice() == ["numpy", "random", "seed"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "get_state"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "set_state"]
|
||||
// simple random data
|
||||
|| call_path.as_slice() == ["numpy", "random", "rand"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "randn"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "randint"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "random_integers"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "random_sample"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "choice"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "bytes"]
|
||||
// permutations
|
||||
|| call_path.as_slice() == ["numpy", "random", "shuffle"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "permutation"]
|
||||
// distributions
|
||||
|| call_path.as_slice() == ["numpy", "random", "beta"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "binomial"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "chisquare"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "dirichlet"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "exponential"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "f"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "gamma"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "geometric"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "get_state"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "gumbel"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "hypergeometric"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "laplace"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "logistic"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "lognormal"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "logseries"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "multinomial"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "multivariate_normal"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "negative_binomial"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "noncentral_chisquare"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "noncentral_f"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "normal"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "pareto"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "poisson"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "power"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "rayleigh"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "standard_cauchy"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "standard_exponential"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "standard_gamma"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "standard_normal"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "standard_t"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "triangular"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "uniform"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "vonmises"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "wald"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "weibull"]
|
||||
|| call_path.as_slice() == ["numpy", "random", "zipf"]
|
||||
{
|
||||
Some(call_path[2])
|
||||
} else {
|
||||
None
|
||||
}
|
||||
}) {
|
||||
checker.diagnostics.push(Diagnostic::new(
|
||||
NumpyLegacyRandom {
|
||||
method_name: method_name.to_string(),
|
||||
},
|
||||
Range::from_located(expr),
|
||||
));
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,555 @@
|
|||
---
|
||||
source: crates/ruff/src/rules/numpy/mod.rs
|
||||
expression: diagnostics
|
||||
---
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: standard_normal
|
||||
location:
|
||||
row: 10
|
||||
column: 7
|
||||
end_location:
|
||||
row: 10
|
||||
column: 29
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: standard_normal
|
||||
location:
|
||||
row: 11
|
||||
column: 12
|
||||
end_location:
|
||||
row: 11
|
||||
column: 34
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: seed
|
||||
location:
|
||||
row: 15
|
||||
column: 0
|
||||
end_location:
|
||||
row: 15
|
||||
column: 17
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: get_state
|
||||
location:
|
||||
row: 16
|
||||
column: 0
|
||||
end_location:
|
||||
row: 16
|
||||
column: 22
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: set_state
|
||||
location:
|
||||
row: 17
|
||||
column: 0
|
||||
end_location:
|
||||
row: 17
|
||||
column: 22
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: rand
|
||||
location:
|
||||
row: 18
|
||||
column: 0
|
||||
end_location:
|
||||
row: 18
|
||||
column: 17
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: randn
|
||||
location:
|
||||
row: 19
|
||||
column: 0
|
||||
end_location:
|
||||
row: 19
|
||||
column: 18
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: randint
|
||||
location:
|
||||
row: 20
|
||||
column: 0
|
||||
end_location:
|
||||
row: 20
|
||||
column: 20
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: random_integers
|
||||
location:
|
||||
row: 21
|
||||
column: 0
|
||||
end_location:
|
||||
row: 21
|
||||
column: 28
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: random_sample
|
||||
location:
|
||||
row: 22
|
||||
column: 0
|
||||
end_location:
|
||||
row: 22
|
||||
column: 26
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: choice
|
||||
location:
|
||||
row: 23
|
||||
column: 0
|
||||
end_location:
|
||||
row: 23
|
||||
column: 19
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: bytes
|
||||
location:
|
||||
row: 24
|
||||
column: 0
|
||||
end_location:
|
||||
row: 24
|
||||
column: 18
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: shuffle
|
||||
location:
|
||||
row: 25
|
||||
column: 0
|
||||
end_location:
|
||||
row: 25
|
||||
column: 20
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: permutation
|
||||
location:
|
||||
row: 26
|
||||
column: 0
|
||||
end_location:
|
||||
row: 26
|
||||
column: 24
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: beta
|
||||
location:
|
||||
row: 27
|
||||
column: 0
|
||||
end_location:
|
||||
row: 27
|
||||
column: 17
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: binomial
|
||||
location:
|
||||
row: 28
|
||||
column: 0
|
||||
end_location:
|
||||
row: 28
|
||||
column: 21
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: chisquare
|
||||
location:
|
||||
row: 29
|
||||
column: 0
|
||||
end_location:
|
||||
row: 29
|
||||
column: 22
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: dirichlet
|
||||
location:
|
||||
row: 30
|
||||
column: 0
|
||||
end_location:
|
||||
row: 30
|
||||
column: 22
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: exponential
|
||||
location:
|
||||
row: 31
|
||||
column: 0
|
||||
end_location:
|
||||
row: 31
|
||||
column: 24
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: f
|
||||
location:
|
||||
row: 32
|
||||
column: 0
|
||||
end_location:
|
||||
row: 32
|
||||
column: 14
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: gamma
|
||||
location:
|
||||
row: 33
|
||||
column: 0
|
||||
end_location:
|
||||
row: 33
|
||||
column: 18
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: geometric
|
||||
location:
|
||||
row: 34
|
||||
column: 0
|
||||
end_location:
|
||||
row: 34
|
||||
column: 22
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: get_state
|
||||
location:
|
||||
row: 35
|
||||
column: 0
|
||||
end_location:
|
||||
row: 35
|
||||
column: 22
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: gumbel
|
||||
location:
|
||||
row: 36
|
||||
column: 0
|
||||
end_location:
|
||||
row: 36
|
||||
column: 19
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: hypergeometric
|
||||
location:
|
||||
row: 37
|
||||
column: 0
|
||||
end_location:
|
||||
row: 37
|
||||
column: 27
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: laplace
|
||||
location:
|
||||
row: 38
|
||||
column: 0
|
||||
end_location:
|
||||
row: 38
|
||||
column: 20
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: logistic
|
||||
location:
|
||||
row: 39
|
||||
column: 0
|
||||
end_location:
|
||||
row: 39
|
||||
column: 21
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: lognormal
|
||||
location:
|
||||
row: 40
|
||||
column: 0
|
||||
end_location:
|
||||
row: 40
|
||||
column: 22
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: logseries
|
||||
location:
|
||||
row: 41
|
||||
column: 0
|
||||
end_location:
|
||||
row: 41
|
||||
column: 22
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: multinomial
|
||||
location:
|
||||
row: 42
|
||||
column: 0
|
||||
end_location:
|
||||
row: 42
|
||||
column: 24
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: multivariate_normal
|
||||
location:
|
||||
row: 43
|
||||
column: 0
|
||||
end_location:
|
||||
row: 43
|
||||
column: 32
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: negative_binomial
|
||||
location:
|
||||
row: 44
|
||||
column: 0
|
||||
end_location:
|
||||
row: 44
|
||||
column: 30
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: noncentral_chisquare
|
||||
location:
|
||||
row: 45
|
||||
column: 0
|
||||
end_location:
|
||||
row: 45
|
||||
column: 33
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: noncentral_f
|
||||
location:
|
||||
row: 46
|
||||
column: 0
|
||||
end_location:
|
||||
row: 46
|
||||
column: 25
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: normal
|
||||
location:
|
||||
row: 47
|
||||
column: 0
|
||||
end_location:
|
||||
row: 47
|
||||
column: 19
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: pareto
|
||||
location:
|
||||
row: 48
|
||||
column: 0
|
||||
end_location:
|
||||
row: 48
|
||||
column: 19
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: poisson
|
||||
location:
|
||||
row: 49
|
||||
column: 0
|
||||
end_location:
|
||||
row: 49
|
||||
column: 20
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: power
|
||||
location:
|
||||
row: 50
|
||||
column: 0
|
||||
end_location:
|
||||
row: 50
|
||||
column: 18
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: rayleigh
|
||||
location:
|
||||
row: 51
|
||||
column: 0
|
||||
end_location:
|
||||
row: 51
|
||||
column: 21
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: standard_cauchy
|
||||
location:
|
||||
row: 52
|
||||
column: 0
|
||||
end_location:
|
||||
row: 52
|
||||
column: 28
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: standard_exponential
|
||||
location:
|
||||
row: 53
|
||||
column: 0
|
||||
end_location:
|
||||
row: 53
|
||||
column: 33
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: standard_gamma
|
||||
location:
|
||||
row: 54
|
||||
column: 0
|
||||
end_location:
|
||||
row: 54
|
||||
column: 27
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: standard_normal
|
||||
location:
|
||||
row: 55
|
||||
column: 0
|
||||
end_location:
|
||||
row: 55
|
||||
column: 28
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: standard_t
|
||||
location:
|
||||
row: 56
|
||||
column: 0
|
||||
end_location:
|
||||
row: 56
|
||||
column: 23
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: triangular
|
||||
location:
|
||||
row: 57
|
||||
column: 0
|
||||
end_location:
|
||||
row: 57
|
||||
column: 23
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: uniform
|
||||
location:
|
||||
row: 58
|
||||
column: 0
|
||||
end_location:
|
||||
row: 58
|
||||
column: 20
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: vonmises
|
||||
location:
|
||||
row: 59
|
||||
column: 0
|
||||
end_location:
|
||||
row: 59
|
||||
column: 21
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: wald
|
||||
location:
|
||||
row: 60
|
||||
column: 0
|
||||
end_location:
|
||||
row: 60
|
||||
column: 17
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: weibull
|
||||
location:
|
||||
row: 61
|
||||
column: 0
|
||||
end_location:
|
||||
row: 61
|
||||
column: 20
|
||||
fix: ~
|
||||
parent: ~
|
||||
- kind:
|
||||
NumpyLegacyRandom:
|
||||
method_name: zipf
|
||||
location:
|
||||
row: 62
|
||||
column: 0
|
||||
end_location:
|
||||
row: 62
|
||||
column: 17
|
||||
fix: ~
|
||||
parent: ~
|
||||
|
||||
|
|
@ -1673,6 +1673,7 @@
|
|||
"NPY0",
|
||||
"NPY00",
|
||||
"NPY001",
|
||||
"NPY002",
|
||||
"PD",
|
||||
"PD0",
|
||||
"PD00",
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue