ptypy.engines.ML.BaseModel#

class ptypy.engines.ML.BaseModel(MLengine)#

Bases: object

Base class for log-likelihood models.

__init__(MLengine)#: Core functions for ML computation using a Gaussian model.

Methods

`__init__`(MLengine)	Core functions for ML computation using a Gaussian model.
`new_grad`()	Compute a new gradient direction according to the noise model.
`poly_line_all_coeffs`(ob_h, pr_h)	Compute all the coefficients of the polynomial for line minimization in direction h
`poly_line_coeffs`(ob_h, pr_h)	Compute the coefficients of the polynomial for line minimization in direction h
`prepare`()

new_grad()#

Compute a new gradient direction according to the noise model.

Note: The negative log-likelihood and local errors should also be computed here.

poly_line_all_coeffs(ob_h, pr_h)#: Compute all the coefficients of the polynomial for line minimization in direction h

poly_line_coeffs(ob_h, pr_h)#: Compute the coefficients of the polynomial for line minimization in direction h