LostTech.TensorFlow : API Documentation

Type Cauchy

Namespace tensorflow.contrib.distributions

Parent Distribution

Interfaces ICauchy

The Cauchy distribution with location `loc` and scale `scale`.

#### Mathematical details

The probability density function (pdf) is,

```none pdf(x; loc, scale) = 1 / (pi scale (1 + z**2)) z = (x - loc) / scale ``` where `loc` is the location, and `scale` is the scale.

The Cauchy distribution is a member of the [location-scale family]( https://en.wikipedia.org/wiki/Location-scale_family), i.e. `Y ~ Cauchy(loc, scale)` is equivalent to,

```none X ~ Cauchy(loc=0, scale=1) Y = loc + scale * X ```

#### Examples

Examples of initialization of one or a batch of distributions.
Show Example
import tensorflow_probability as tfp
            tfd = tfp.distributions 

# Define a single scalar Cauchy distribution. dist = tfd.Cauchy(loc=0., scale=3.)

# Evaluate the cdf at 1, returning a scalar. dist.cdf(1.)

# Define a batch of two scalar valued Cauchy distributions. dist = tfd.Cauchy(loc=[1, 2.], scale=[11, 22.])

# Evaluate the pdf of the first distribution on 0, and the second on 1.5, # returning a length two tensor. dist.prob([0, 1.5])

# Get 3 samples, returning a 3 x 2 tensor. dist.sample([3])

# Arguments are broadcast when possible. # Define a batch of two scalar valued Cauchy distributions. # Both have median 1, but different scales. dist = tfd.Cauchy(loc=1., scale=[11, 22.])

# Evaluate the pdf of both distributions on the same point, 3.0, # returning a length 2 tensor. dist.prob(3.)

Properties

Public properties

object allow_nan_stats get;

object allow_nan_stats_dyn get;

TensorShape batch_shape get;

object batch_shape_dyn get;

object dtype get;

object dtype_dyn get;

TensorShape event_shape get;

object event_shape_dyn get;

object loc get;

Distribution parameter for the mean.

object loc_dyn get;

Distribution parameter for the mean.

string name get;

object name_dyn get;

IDictionary<object, object> parameters get;

object parameters_dyn get;

object PythonObject get;

object reparameterization_type get;

object reparameterization_type_dyn get;

object scale get;

Distribution parameter for standard deviation.

object scale_dyn get;

Distribution parameter for standard deviation.

object validate_args get;

object validate_args_dyn get;