TransportMaps.Distributions.Examples.LogGaussianCoxProcess.LogGaussianCoxProcessDistributions
¶
Module Contents¶
Classes¶
Class for densities of the transport map type \(T_\sharp \pi\) |
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Abstract distribution \(\nu_\pi\). |
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Abstract map \(T:\mathbb{R}^{d_x}\rightarrow\mathbb{R}^{d_y}\) |
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Abstract distribution \(\nu_\pi\). |
- class TransportMaps.Distributions.Examples.LogGaussianCoxProcess.LogGaussianCoxProcessDistributions.StationaryKernel[source]¶
Bases:
Kernel
- class TransportMaps.Distributions.Examples.LogGaussianCoxProcess.LogGaussianCoxProcessDistributions.IsotropicStationaryKernel[source]¶
Bases:
StationaryKernel
- class TransportMaps.Distributions.Examples.LogGaussianCoxProcess.LogGaussianCoxProcessDistributions.OrnsteinUhlenbeck(l=1.0)[source]¶
Bases:
IsotropicStationaryKernel
- class TransportMaps.Distributions.Examples.LogGaussianCoxProcess.LogGaussianCoxProcessDistributions.SquaredExponentialKernel(l=1.0)[source]¶
Bases:
IsotropicStationaryKernel
- class TransportMaps.Distributions.Examples.LogGaussianCoxProcess.LogGaussianCoxProcessDistributions.GaussianProcess(pts, kernel, mu=None)[source]¶
Bases:
TransportMaps.Distributions.PushForwardTransportMapDistribution
Class for densities of the transport map type \(T_\sharp \pi\)
- Parameters:
transport_map (Maps.TriangularTransportMap) – transport map \(T\)
base_distribution (Distributions.Distribution) – distribution \(\pi\)
See also
TransportMapDistribution
- class TransportMaps.Distributions.Examples.LogGaussianCoxProcess.LogGaussianCoxProcessDistributions.PoissonPointProcessDistribution(lmb)[source]¶
Bases:
TransportMaps.Distributions.Distribution
Abstract distribution \(\nu_\pi\).
- rvs(n)[source]¶
[Abstract] Generate \(m\) samples from the distribution.
- Parameters:
m (int) – number of samples to generate
- Returns:
- (
ndarray
[\(m,d\)]) – \(m\) \(d\)-dimensional samples
- (
- Raises:
NotImplementedError – the method needs to be defined in the sub-classes
- class TransportMaps.Distributions.Examples.LogGaussianCoxProcess.LogGaussianCoxProcessDistributions.PoissonPointProcessLogLikelihood(obs, dim_in)[source]¶
Bases:
TransportMaps.Maps.Map
Abstract map \(T:\mathbb{R}^{d_x}\rightarrow\mathbb{R}^{d_y}\)
- grad_x(x, *args, **kwargs)[source]¶
[Abstract] Evaluate the gradient \(\nabla_{\bf x}T\) at the points \({\bf x} \in \mathbb{R}^{m \times d_x}\).
- Parameters:
- Returns:
(
ndarray
[\(m,d_y,d_x\)]) – transformed points- Raises:
NotImplementedError – to be implemented in sub-classes
- hess_x(x, *args, **kwargs)[source]¶
[Abstract] Evaluate the Hessian \(\nabla^2_{\bf x}T\) at the points \({\bf x} \in \mathbb{R}^{m \times d_x}\).
- Parameters:
- Returns:
(
ndarray
[\(m,d_y,d_x,d_x\)]) – transformed points- Raises:
NotImplementedError – to be implemented in sub-classes
- class TransportMaps.Distributions.Examples.LogGaussianCoxProcess.LogGaussianCoxProcessDistributions.LogGaussianCoxProcessPosterior(reduced_gp, obs, full_N, full_obs_idxs, full_gp, full_lmb)[source]¶
Bases:
TransportMaps.Distributions.Distribution
Abstract distribution \(\nu_\pi\).
- pdf(x, *args, **kwargs)[source]¶
Evaluate \(\pi({\bf x})\)
- Parameters:
- Returns:
- (
ndarray
[\(m\)]) – values of \(\pi\) at the
x
points.
- (
- Raises:
NotImplementedError – the method calls :fun:`log_pdf`
- log_pdf(x, *args, **kwargs)[source]¶
[Abstract] Evaluate \(\log \pi({\bf x})\)
- Parameters:
- Returns:
- (
ndarray
[\(m\)]) – values of \(\log\pi\) at the
x
points.
- (
- Raises:
NotImplementedError – the method needs to be defined in the sub-classes
- grad_x_log_pdf(x, *args, **kwargs)[source]¶
[Abstract] Evaluate \(\nabla_{\bf x} \log \pi({\bf x})\)
- Parameters:
- Returns:
- (
ndarray
[\(m,d\)]) – values of \(\nabla_x\log\pi\) at the
x
points.
- (
- Raises:
NotImplementedError – the method needs to be defined in the sub-classes
- hess_x_log_pdf(x, *args, **kwargs)[source]¶
[Abstract] Evaluate \(\nabla^2_{\bf x} \log \pi({\bf x})\)
- Parameters:
- Returns:
- (
ndarray
[\(m,d,d\)]) – values of \(\nabla^2_x\log\pi\) at the
x
points.
- (
- Raises:
NotImplementedError – the method needs to be defined in the sub-classes