eztaox.kernel_stat2

eztaox.kernel_stat2#

Second-Order statistic functions for kernels in kernels.quasisep.

Classes#

gpStat2

Base class for second-order statistics of GP kernels.

Functions#

carma_rms(→ tinygp.helpers.JAXArray)

Return a function that computes CARMA root-mean-squared (RMS).

carma_psd(→ tinygp.helpers.JAXArray)

Return a function that computes CARMA power spectral density (PSD).

carma_acf(→ tinygp.helpers.JAXArray)

Return a function to compute the model autocorrelation function (ACF) of CARMA.

carma_sf(→ tinygp.helpers.JAXArray)

Return a function that computes the CARMA structure function (SF).

Module Contents#

class gpStat2(kernel: collections.abc.Callable)[source]#

Bases: equinox.Module

Base class for second-order statistics of GP kernels.

Parameters:

kernel (Callable) – A kernel function from kernels.quasisep.

kernel_def[source]#

A function to reconstruct kernel objects from its parameters

Type:

Callable

kernel_params[source]#

parameters for kernel function

Type:

JAXArray

acf(ts: tinygp.helpers.JAXArray | numpy.typing.NDArray, params: tinygp.helpers.JAXArray | numpy.typing.NDArray | None = None) → tinygp.helpers.JAXArray[source]#

Compute the autocorrelation function (ACF) for given time lags.

Parameters:

  • ts (JAXArray | NDArray) – Time lags for which to compute the ACF.

  • params (JAXArray | NDArray | None, optional) – Parameters of the GP kernel if different from those used to initialize the object. Defaults to None.

Returns:

The computed ACF values for the given time lags.

Return type:

JAXArray

sf(ts: tinygp.helpers.JAXArray | numpy.typing.NDArray, params: tinygp.helpers.JAXArray | numpy.typing.NDArray | None = None) → tinygp.helpers.JAXArray[source]#

Compute the structure function (SF) for given time lags.

Parameters:

  • ts (JAXArray | NDArray) – Time lags for which to compute the SF.

  • params (JAXArray | NDArray | None, optional) – Parameters of the GP kernel if different from those used to initialize the object. Defaults to None.

Returns:

The computed SF values for the given time lags.

Return type:

JAXArray

psd(fs: tinygp.helpers.JAXArray | numpy.typing.NDArray, params: tinygp.helpers.JAXArray | numpy.typing.NDArray | None = None, df: float | tinygp.helpers.JAXArray | None = 0.01) → tinygp.helpers.JAXArray[source]#

Compute the power spectral density (PSD) for given frequencies.

Parameters:

  • fs (JAXArray | NDArray) – Frequencies for which to compute the PSD.

  • params (JAXArray | NDArray | None, optional) – Parameters of the GP kernel if different from those used to initialize the object. Defaults to None.

  • df (float | JAXArray | None, optional) – Frequency width for create convolved PSDs (not in use). Defaults to 0.01.

Returns:

The computed PSD values for the given frequencies.

Return type:

JAXArray

carma_rms(alpha: tinygp.helpers.JAXArray | numpy.typing.NDArray, beta: tinygp.helpers.JAXArray | numpy.typing.NDArray) → tinygp.helpers.JAXArray[source]#

Return a function that computes CARMA root-mean-squared (RMS).

Parameters:

  • alpha (JAXArray | NDArray) – kernel alpha coefficients.

  • beta (JAXArray | NDArray) – kernel beta coefficients

Returns:

A function that takes in frequencies and returns RMS for the given coefficients.

Return type:

JAXArray

carma_psd(f: tinygp.helpers.JAXArray | numpy.typing.NDArray, arparams: tinygp.helpers.JAXArray | numpy.typing.NDArray, maparams: tinygp.helpers.JAXArray | numpy.typing.NDArray) → tinygp.helpers.JAXArray[source]#

Return a function that computes CARMA power spectral density (PSD).

Parameters:

  • f (JAXArray | NDArray) – frequencies.

  • arparams (JAXArray | NDArray) – AR coefficients.

  • maparams (JAXArray | NDArray) – MA coefficients

Returns:

A function that takes in frequencies and returns PSD at the given frequencies.

Return type:

JAXArray

carma_acf(t: tinygp.helpers.JAXArray | numpy.typing.NDArray, arparams: tinygp.helpers.JAXArray | numpy.typing.NDArray, maparams: tinygp.helpers.JAXArray | numpy.typing.NDArray) → tinygp.helpers.JAXArray[source]#

Return a function to compute the model autocorrelation function (ACF) of CARMA.

Parameters:

  • t (JAXArray | NDArray) – times.

  • arparams (JAXArray | NDArray) – AR coefficients.

  • maparams (JAXArray | NDArray) – MA coefficients.

Returns:

A function that takes in time lags and returns ACF at the given lags.

Return type:

JAXArray

carma_sf(t: tinygp.helpers.JAXArray | numpy.typing.NDArray, arparams: tinygp.helpers.JAXArray | numpy.typing.NDArray, maparams: tinygp.helpers.JAXArray | numpy.typing.NDArray) → tinygp.helpers.JAXArray[source]#

Return a function that computes the CARMA structure function (SF).

Parameters:

  • t (JAXArray | NDArray) – times.

  • arparams (JAXArray | NDArray) – AR coefficients.

  • maparams (JAXArray | NDArray) – MA coefficients.

Returns:

A function that takes in time lags and returns CARMA SF at the given lags.

Return type:

JAXArray