shamo.core.distributions.uniform.DistUniform¶

class shamo.core.distributions.uniform.DistUniform(lower, upper)[source]¶

Bases: shamo.core.distributions.abc.DistABC

A uniform distribution.

Parameters

lowerfloat: The lower bound of the distribution.
upperfloat: The upper bound of the distribution.

Methods

`clear`
`copy`
`fromkeys`	Create a new dictionary with keys from iterable and values set to value.
`get`	Return the value for key if key is in the dictionary, else default.
`items`
`keys`
`load`	Load a distribution from its dict representation.
`pop`	If key is not found, d is returned if given, otherwise KeyError is raised
`popitem`	Remove and return a (key, value) pair as a 2-tuple.
`setdefault`	Insert key with a value of default if key is not in the dictionary.
`update`	If E is present and has a .keys() method, then does: for k in E: D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k]
`values`

Attributes

`TYPE_CONSTANT`
`TYPE_NORMAL`
`TYPE_TRUNC_NORMAL`
`TYPE_UNIFORM`
`dist`	Return the actual distribution.
`dist_type`	Return the type of the distribution.
`expect`	Return the expected value of the distribution.
`lower`	Return the lower bound of the distribution.
`salib_bounds`	Return the bounds of the distribution in SALib.
`salib_name`	Return the name of the distribution in SALib.
`uniform_dist`	Return a uniform distribution used for sampling.
`upper`	Return the upper bound of the distribution.

clear() → None. Remove all items from D.¶

copy() → a shallow copy of D¶

property dist¶

Return the actual distribution.

Returns

chaospy.Uniform: The actual distribution.

property dist_type¶

Return the type of the distribution.

Returns

str: The type of the distribution.

property expect¶

Return the expected value of the distribution.

Returns

float: The expected value of the distribution.

fromkeys(iterable, value=None, /)¶: Create a new dictionary with keys from iterable and values set to value.

get(key, default=None, /)¶: Return the value for key if key is in the dictionary, else default.

items() → a set-like object providing a view on D’s items¶

keys() → a set-like object providing a view on D’s keys¶

static load(dist_type, **kwargs)¶

Load a distribution from its dict representation.

Returns

DistABC: The loaded distribution.

property lower¶

Return the lower bound of the distribution.

Returns

float: The lower bound of the distribution.

pop(k[, d]) → v, remove specified key and return the corresponding value.¶: If key is not found, d is returned if given, otherwise KeyError is raised

popitem(/)¶

Remove and return a (key, value) pair as a 2-tuple.

Pairs are returned in LIFO (last-in, first-out) order. Raises KeyError if the dict is empty.

property salib_bounds¶

Return the bounds of the distribution in SALib.

Returns

list [float]: The bounds of the distribution in SALib.

property salib_name¶

Return the name of the distribution in SALib.

Returns

str: The name of the distribution in SALib.

setdefault(key, default=None, /)¶

Insert key with a value of default if key is not in the dictionary.

Return the value for key if key is in the dictionary, else default.

property uniform_dist¶

Return a uniform distribution used for sampling.

Returns

chaospy.Uniform: The uniform distribution.

update([E, ]**F) → None. Update D from dict/iterable E and F.¶: If E is present and has a .keys() method, then does: for k in E: D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k]

property upper¶

Return the upper bound of the distribution.

Returns

float: The upper bound of the distribution.

values() → an object providing a view on D’s values¶