Miniker 102 manual

Concepts index

Jump to:	$ A B C D E F G H I K L M O P R S T U V Z

	Index Entry	Section

$
	‘`$dimetaphi`’	Setting up a model with cmz
	‘`$zinit`’	Setting up a model with cmz

A
	adjoint	Overview of optimisation with Miniker
	‘`aspha.data`’	Simulation and output
	‘`aspha.data`’, GTLS	GTLS run and output
	‘`aspha.data`’, SVD	SVD run and output

B
	Borel sweep	Feedback gain
	Borel sweep graphics	Borel sweep results
	Borel sweep results	Borel sweep results

C
	cells	Introduction
	cernlib	Common requisites
	command law	Control laws
	compilation	Setting up a model with make
	configuration of source	Configuration
	controlling the run	Controlling the run

D
	‘`data.data`’	Data
	‘`data.data`’	Kalman filter results
	dimetaphi	Size sequence
	‘`dimetaphi`’	Size sequence
	‘`dimetaphi`’, Kalman filter	Kalman filter vectors dimensions
	down node	1D gridded model
	‘`dres.data`’	Simulation and output
	‘`dres.data`’	Simulation and output
	‘`dres.data`’, GTLS	GTLS run and output

E
	equations, grid	1D gridded model code
	error vector dimension	Kalman filter vectors dimensions

F
	FDL, GNU Free Documentation License	GNU Free Documentation License
	feature setting	Selecting features
	Feedback gain	Feedback gain
	`ffl` (linearity test)	End of time step
	final cost	Overview of optimisation with Miniker

G
	Generalized linear tangent system	Generalized TLS
	‘`gradpj.data`’	Sensitivity of cost function to parameters
	graphics	Graphics
	graphics with `gnuplot`	Graphics
	graphics with `PAW`	Graphics
	graphics, Borel sweep	Borel sweep results
	GTLS	Generalized TLS
	GTLS output	GTLS run and output
	GTLS run	GTLS run and output

H
	Heaviside function	Rule of programming non continuous models

I
	initial variance-covariance on states	Error and observation matrices
	installation with make	Installation with make
	integrand cost	Overview of optimisation with Miniker

K
	Kalman filter	Kalman filter
	Kalman filter output	Kalman filter results
	Kalman filter results	Kalman filter results

L
	lapack	Common requisites
	limiting conditions	1D gridded model code
	linearity test	End of time step
	logical flags	Selecting features
	Lyapunov exponents	Generalized TLS

M
	‘`Makefile.miniker`’	Make variables
	‘`Makefile.sltc`’	SVD with make
	‘`Makefile.sltcirc`’	GTLS with make
	‘`mini_ker.cmz`’	Miniker with cmz
	`mod`	Setting up a model with cmz
	model equations	Model with explicit size
	model size	Size sequence
	‘`Model.hlp`’	Simulation and output
	mortran	Introduction
	mortran	A note about mortran and cmz directives
	`mortran`, with make	Additional requirements

O
	‘`obs.data`’	Observations
	observation function	Observations
	observations	Error and observation matrices
	observations, general	Kalman filter
	optimisation	Overview of optimisation with Miniker
	output file	Simulation and output
	output, GTLS	GTLS run and output
	output, Kalman filter	Kalman filter results
	output, sensitivity	Sensitivities
	output, SVD	SVD run and output

P
	printing	Controlling the printout and data output
	Programming environments	Programming environments
	propagator	Generalized TLS

R
	requirements, with make	Additional requirements
	‘`res.data`’	Simulation and output
	results, Borel sweep	Borel sweep results
	results, Kalman filter	Kalman filter results
	run, GTLS	GTLS run and output
	run, SVD	SVD run and output
	running model	Simulation and output

S
	select flag	Selecting features
	‘`selseq.kumac`’	Selecting features
	‘`selseq.kumac`’	Miniker with cmz
	‘`sens.data`’	Sensitivities
	sensitivities	Sensitivities
	sensitivity, output	Sensitivities
	sequence	Structure of the code
	sequences	A model with Miniker
	‘`sigma.data`’	Sensitivities
	Singular Value Decomposition	Stability of fastest modes
	‘`sltc.exe`’	Stability of fastest modes
	‘`sltc.exe`’	SVD run and output
	‘`sltcirc.exe`’	Generalized TLS
	‘`sltcirc.exe`’	GTLS run and output
	`smod`	SVD with cmz
	`smod`	GTLS with cmz
	starting point	Model equation and parameters
	state matrix	Stability of fastest modes
	SVD	Stability of fastest modes
	SVD output	SVD run and output
	SVD run	SVD run and output

T
	TEF	Introduction
	TEF	A model description
	title file	Model equation and parameters
	‘`title.tex`’	Model equation and parameters
	‘`title.tex`’, GTLS	GTLS run and output
	‘`title.tex`’, SVD	SVD run and output
	‘`tr.data`’	Simulation and output
	transfers	Introduction

U
	up node	1D gridded model
	‘`uxcom.data`’	Control laws
	‘`uycom.data`’	Control laws

V
	variance-covariance error	Error and observation matrices
	variance-covariance matrices	Error and observation matrices
	variance-covariance matrices, general	Kalman filter
	variance-covariance matrix on state	Error and observation matrices

Z
	‘`zcmd_law`’	Control laws
	‘`zcmd_law.inc`’	Control laws
	‘`zinit`’	Model equation and parameters
	zinit, general	Structure of the code
	‘`zinit`’, Kalman filter	Error and observation matrices
	‘`zinit.mti`’	Setting up a model with make
	ZOOM	Introduction
	‘`zsteer`’	End of time step
	‘`zsteer`’, Kalman filter	Feeding the observations
	‘`zsteer.inc`’	End of time step

Jump to:	$ A B C D E F G H I K L M O P R S T U V Z

This document was generated on May 20, 2012 using texi2any.