distribution module¶
Computation of tolerance intervals from a data-fitted probability distribution.
Classes:
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Computation of tolerance intervals from a data-fitted probability distribution. |
A factory of |
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An enumeration. |
- class gemseo.uncertainty.statistics.tolerance_interval.distribution.ToleranceInterval(size)[source]¶
Bases:
object
Computation of tolerance intervals from a data-fitted probability distribution.
A
ToleranceInterval
(TI) is initialized from the number of samples used to estimate the parameters of the probability distribution and from the estimations of these parameters.A
ToleranceInterval
can be evaluated from:a coverage defining the minimum percentage of belonging to the TI, e.g. 0.90,
a level of confidence in [0,1], e.g. 0.95,
a type of interval, either ‘lower’ for lower-sided TI, ‘upper’ for upper-sided TI or ‘both for both-sided TI.
Note
Lower-sided tolerance intervals are used to analyse the strength of materials. They are also known as basis tolerance limits. In particular, the B-value is the lower bound of the lower-sided tolerance interval with 90%-coverage and 95%-confidence while the A-value is the lower bound of the lower-sided tolerance interval with 95%-coverage and 95%-confidence.
Initialize self. See help(type(self)) for accurate signature.
- Parameters
size (int) – The number of samples.
- Return type
None
Methods:
compute
(coverage[, confidence, side])Compute a tolerance interval.
- compute(coverage, confidence=0.95, side=ToleranceIntervalSide.BOTH)[source]¶
Compute a tolerance interval.
- Parameters
coverage (float) – A minimum percentage of belonging to the TI.
confidence (float) –
A level of confidence in [0,1].
By default it is set to 0.95.
side (gemseo.uncertainty.statistics.tolerance_interval.distribution.ToleranceIntervalSide) –
The type of the tolerance interval characterized by its sides of interest, either a lower-sided tolerance interval \([a, +\infty[\), an upper-sided tolerance interval \(]-\infty, b]\), or a two-sided tolerance interval \([c, d]\).
By default it is set to BOTH.
- Returns
The tolerance bounds.
- Return type
Tuple[numpy.ndarray, numpy.ndarray]
- class gemseo.uncertainty.statistics.tolerance_interval.distribution.ToleranceIntervalFactory[source]¶
Bases:
object
A factory of
ToleranceInterval
.Methods:
create
(class_name, size, *args)Return an instance of
ToleranceInterval
.get_class
(name)Return a class from its name.
- Return type
None
- create(class_name, size, *args)[source]¶
Return an instance of
ToleranceInterval
.- Parameters
size (int) – The number of samples used to estimate the parameters of the probability distribution.
*args (float) – The arguments of the probability distribution.
class_name (str) –
- Returns
The instance of the class.
- Raises
TypeError – If the class cannot be instantiated.
- Return type
gemseo.uncertainty.statistics.tolerance_interval.distribution.ToleranceInterval