Base class containing all the data needed to reconstruct a model. More...

Public Member Functions
FINAL	reconstruction_destruct

PROCEDURE	get_k_use => reconstruction_get_k_use

PROCEDURE	get_exp_dg2 => reconstruction_get_exp_dg2

PROCEDURE	get_exp_g2 => reconstruction_get_exp_g2

PROCEDURE	get_g2 => reconstruction_get_g2

PROCEDURE	get_lastg2 => reconstruction_get_lastg2

PROCEDURE	get_dg2 => reconstruction_get_dg2

PROCEDURE	eval_e => reconstruction_eval_e

PROCEDURE	eval_f => reconstruction_eval_f

PROCEDURE	eval_jacobians => reconstruction_eval_jacobians

PROCEDURE	eval_step => reconstruction_eval_step

PROCEDURE	sl_step => reconstruction_sl_step

PROCEDURE	seg_step => reconstruction_seg_step

PROCEDURE	lm_step => reconstruction_lm_step

PROCEDURE	lm_rootfind => reconstruction_lm_rootfind

PROCEDURE	lm_function => reconstruction_lm_function

PROCEDURE	step => reconstruction_step

PROCEDURE	try_step => reconstruction_try_step

PROCEDURE	eval_sem => reconstruction_eval_sem

PROCEDURE	invert_matrix => reconstruction_invert_matrix

PROCEDURE	write => reconstruction_write

PROCEDURE	write_step1 => reconstruction_write_step1

PROCEDURE	write_step2 => reconstruction_write_step2

GENERIC	write_step => write_step1, write_step2

PROCEDURE	restart => reconstruction_restart

PROCEDURE	sync_state => reconstruction_sync_state

PROCEDURE	sync_svd => reconstruction_sync_svd

PROCEDURE	sync_parent => reconstruction_sync_parent

Public Attributes
integer	step_type = reconstruction_no_step_type
	Type descriptor of the boundry type for the lower(1) and upper(2) ranges. More...

real(rprec)	step_max
	Maximum number of reconstruction steps. More...

logical	use_central = .false.
	Controls if central differencing is used.

integer	current_step = 0
	Counter to track the step number.

integer	last_para_signal = 0
	Index of the last parallelable signal.

real(rprec), dimension(:,:), pointer	e => null()
	Array of all e vectors for each reconstruction step. More...

real(rprec), dimension(:,:), pointer	f => null()
	Array of all f vectors for each reconstruction step. The f vector contains the initial value of the derived parameter.

real(rprec), dimension(:,:), pointer	jacobian => null()
	The normalized jacobian for the current step.

real(rprec), dimension(:,:), pointer	derived_jacobian => null()
	The normalized derived jacobian for the current step.

real(rprec), dimension(:,:), pointer	hessian => null()
	The normalized hessian for the current step.

real(rprec), dimension(:), pointer	gradient => null()
	The normalized gradient for the current step.

real(rprec), dimension(:,:), pointer	delta_a => null()
	The normalized parameter step for each sigular value.

real(rprec), dimension(:), pointer	j_svd_w => null()
	The matrix of singular value decomposition singular values.

real(rprec), dimension(:,:), pointer	j_svd_u => null()
	The U matrix of singular value decomposition.

real(rprec), dimension(:,:), pointer	j_svd_vt => null()
	The tansposed V matrix of singular value decomposition.

real(rprec), dimension(:), pointer	delta_a_len => null()
	The normalized step length for each sigular value.

real(rprec), dimension(:), pointer	svd_w => null()
	The singular values used in inverting parameter covariance matrix.

real(rprec), dimension(:), pointer	exp_g2 => null()
	The expected g^2 for each reconstruction step.

real(rprec), dimension(:), pointer	step_size => null()
	The normalized step size for each reconstruction step.

integer, dimension(:), pointer	num_sv => null()
	The number of sigular values used for each reconstruction step.

real(rprec)	cut_svd
	Cutoff value for relative singular values. More...

real(rprec)	cut_eff
	Cutoff value for expected step efficiency. More...

real(rprec)	cut_marg_eff
	Cutoff value for expected marginal step efficiency. More...

real(rprec)	cut_delta_a
	Cutoff value for expected step size. More...

real(rprec)	cut_dg2
	Cutoff value for expected change in g^2. More...

real(rprec)	cut_inv_svd
	Cutoff value for pseudo inverse singular values. More...

real(rprec), dimension(:,:), pointer	lm_ratio => null()
	Ratio of singular values to the Levenberg-Marquardt lambda.

real(rprec), dimension(:,:), pointer	last_values => null()
	Last signals.