chainer.distributions.Uniform¶
-
class
chainer.distributions.
Uniform
(**kwargs)[source]¶ Uniform Distribution.
The probability density function of the distribution is expressed as
\[\begin{split}p(x; l, h) = \begin{cases} \frac{1}{h - l} & \text{if }l \leq x \leq h \\ 0 & \text{otherwise} \end{cases}\end{split}\]- Parameters
low (
Variable
or N-dimensional array) – Parameter of distribution representing the lower bound \(l\).high (
Variable
or N-dimensional array) – Parameter of distribution representing the higher bound \(h\).
Methods
-
cdf
(x)[source]¶ Evaluates the cumulative distribution function at the given points.
- Parameters
x (
Variable
or N-dimensional array) – Data points in the domain of the distribution- Returns
Cumulative distribution function value evaluated at x.
- Return type
-
icdf
(x)[source]¶ Evaluates the inverse cumulative distribution function at the given points.
- Parameters
x (
Variable
or N-dimensional array) – Data points in the domain of the distribution- Returns
Inverse cumulative distribution function value evaluated at x.
- Return type
-
log_cdf
(x)[source]¶ Evaluates the log of cumulative distribution function at the given points.
- Parameters
x (
Variable
or N-dimensional array) – Data points in the domain of the distribution- Returns
Logarithm of cumulative distribution function value evaluated at x.
- Return type
-
log_prob
(x)[source]¶ Evaluates the logarithm of probability at the given points.
- Parameters
x (
Variable
or N-dimensional array) – Data points in the domain of the distribution- Returns
Logarithm of probability evaluated at x.
- Return type
-
log_survival_function
(x)[source]¶ Evaluates the logarithm of survival function at the given points.
- Parameters
x (
Variable
or N-dimensional array) – Data points in the domain of the distribution- Returns
Logarithm of survival function value evaluated at x.
- Return type
-
perplexity
(x)[source]¶ Evaluates the perplexity function at the given points.
- Parameters
x (
Variable
or N-dimensional array) – Data points in the domain of the distribution- Returns
Perplexity function value evaluated at x.
- Return type
-
prob
(x)[source]¶ Evaluates probability at the given points.
- Parameters
x (
Variable
or N-dimensional array) – Data points in the domain of the distribution- Returns
Probability evaluated at x.
- Return type
-
sample
(sample_shape=())[source]¶ Samples random points from the distribution.
This function calls sample_n and reshapes a result of sample_n to sample_shape + batch_shape + event_shape. On implementing sampling code in an inherited distribution class, it is not recommended that you override this function. Instead of doing this, it is preferable to override sample_n.
-
sample_n
(n)[source]¶ Samples n random points from the distribution.
This function returns sampled points whose shape is (n,) + batch_shape + event_shape. When implementing sampling code in a subclass, it is recommended that you override this method.
-
survival_function
(x)[source]¶ Evaluates the survival function at the given points.
- Parameters
x (
Variable
or N-dimensional array) – Data points in the domain of the distribution- Returns
Survival function value evaluated at x.
- Return type
-
__eq__
()¶ Return self==value.
-
__ne__
()¶ Return self!=value.
-
__lt__
()¶ Return self<value.
-
__le__
()¶ Return self<=value.
-
__gt__
()¶ Return self>value.
-
__ge__
()¶ Return self>=value.
Attributes
-
batch_shape
¶ Returns the shape of a batch.
- Returns
The shape of a sample that is not identical and independent.
- Return type
-
covariance
¶ Returns the covariance of the distribution.
- Returns
The covariance of the distribution.
- Return type
-
entropy
¶
-
event_shape
¶ Returns the shape of an event.
- Returns
The shape of a sample that is not identical and independent.
- Return type
-
high
¶
-
loc
¶
-
low
¶
-
mean
¶
-
mode
¶ Returns the mode of the distribution.
- Returns
The mode of the distribution.
- Return type
-
params
¶ Returns the parameters of the distribution.
- Returns
The parameters of the distribution.
- Return type
-
scale
¶
-
stddev
¶
-
support
¶ Returns the support of the distribution.
- Returns
String that means support of this distribution.
- Return type
-
variance
¶