| Index Entry | | Section |
|
$ | | |
| ‘$dimetaphi’: | | 2.3.1 Setup a model and compile with cmz |
| ‘$zinit’: | | 2.3.1 Setup a model and compile with cmz |
|
A | | |
| adjoint: | | 4.2.1 Overview of optimisation with Miniker |
| ‘aspha.data’: | | 2.3.3 Running a simulation and using the output |
| ‘aspha.data’, GTLS: | | 4.6.3 Generalized tangent linear system analysis run and output |
| ‘aspha.data’, SVD: | | 4.5.3 Singular Value Decomposition run and output |
|
B | | |
| Borel sweep: | | 4.4 Feedback gain |
| Borel sweep graphics: | | 4.4.2 Borel sweep results |
| Borel sweep results: | | 4.4.2 Borel sweep results |
|
C | | |
| cells: | | Introduction |
| cernlib: | | A.2 Common requisites |
| command law: | | 4.2.2 Control laws |
| compilation: | | 2.3.2 Setup a model and compile with make |
| configuration of source: | | A.4.2 Configuration |
| controlling the run: | | 2.4 Controlling the run |
|
D | | |
| ‘data.data’: | | 3.8.2 Data |
| ‘data.data’: | | 4.3.2.2 Kalman filter results |
| dimetaphi: | | 3.9.1 The explicit size sequence |
| ‘dimetaphi’: | | 3.9.1 The explicit size sequence |
| ‘dimetaphi’, Kalman filter: | | 4.3.1.1 Kalman filter vectors dimensions |
| down node: | | 3.3 Describing 1D gridded model |
| ‘dres.data’: | | 2.3.3 Running a simulation and using the output |
| ‘dres.data’: | | 2.3.3 Running a simulation and using the output |
| ‘dres.data’, GTLS: | | 4.6.3 Generalized tangent linear system analysis run and output |
|
E | | |
| equations, grid: | | Grid node equations |
| error vector dimension: | | 4.3.1.1 Kalman filter vectors dimensions |
|
F | | |
| FDL, GNU Free Documentation License: | | C.1 GNU Free Documentation License |
| feature setting: | | 3.1 Overview of additional features setting |
| Feedback gain: | | 4.4 Feedback gain |
| ffl (linearity test): | | 2.4.1 Executing code at the end of each time step |
| final cost: | | 4.2.1 Overview of optimisation with Miniker |
|
G | | |
| Generalized linear tangent system: | | 4.6 Generalized linear tangent system analysis |
| ‘gradpj.data’: | | 4.2.4 Sensitivity of cost function to parameters |
| graphics: | | 2.3.4 Doing graphics |
| graphics with gnuplot : | | 2.3.4 Doing graphics |
| graphics with PAW : | | 2.3.4 Doing graphics |
| graphics, Borel sweep: | | 4.4.2 Borel sweep results |
| GTLS: | | 4.6 Generalized linear tangent system analysis |
| GTLS output: | | 4.6.3 Generalized tangent linear system analysis run and output |
| GTLS run: | | 4.6.3 Generalized tangent linear system analysis run and output |
|
H | | |
| Heaviside function: | | 3.6 Rule of programming non continuous models |
|
I | | |
| initial variance-covariance on states: | | Initial variance-covariance matrix on the state |
| installation with make: | | A.4.3 Installation with make |
| integrand cost: | | 4.2.1 Overview of optimisation with Miniker |
|
K | | |
| Kalman filter: | | 4.3 Kalman filter |
| Kalman filter output: | | 4.3.2.2 Kalman filter results |
| Kalman filter results: | | 4.3.2.2 Kalman filter results |
|
L | | |
| lapack: | | A.2 Common requisites |
| limiting conditions: | | Limiting conditions |
| linearity test: | | 2.4.1 Executing code at the end of each time step |
| logical flags: | | 3.1 Overview of additional features setting |
| Lyapunov exponents: | | 4.6 Generalized linear tangent system analysis |
|
M | | |
| ‘Makefile.miniker’: | | 5.1 Make variables |
| ‘Makefile.sltc’: | | 4.5.2 Singular Value Decomposition with make |
| ‘Makefile.sltcirc’: | | 4.6.2 Generalized tangent linear system with make |
| ‘mini_ker.cmz’: | | A.3 Miniker with cmz |
| mod : | | 2.3.1 Setup a model and compile with cmz |
| model equations: | | 3.9.2 Entering the model equations, with explicit sizes |
| model size: | | 3.9.1 The explicit size sequence |
| ‘Model.hlp’: | | 2.3.3 Running a simulation and using the output |
| mortran: | | Introduction |
| mortran: | | 2.2.1 All you need to know about mortran and cmz directives |
| mortran , with make: | | A.4.1 Additional requirements for Miniker with make |
|
O | | |
| ‘obs.data’: | | 3.8.1 Observations |
| observation function: | | 3.8.1 Observations |
| observations: | | 4.3.1.2 Error and observation matrices |
| observations, general: | | 4.3 Kalman filter |
| optimisation: | | 4.2.1 Overview of optimisation with Miniker |
| output file: | | 2.3.3 Running a simulation and using the output |
| output, GTLS: | | 4.6.3 Generalized tangent linear system analysis run and output |
| output, Kalman filter: | | 4.3.2.2 Kalman filter results |
| output, sensitivity: | | 4.1 Automatic sensitivity computation |
| output, SVD: | | 4.5.3 Singular Value Decomposition run and output |
|
P | | |
| printing: | | 2.4.2 Controlling the printout and data output |
| Programming environments: | | A.1 Programming environments |
| propagator: | | 4.6 Generalized linear tangent system analysis |
|
R | | |
| requirements, with make: | | A.4.1 Additional requirements for Miniker with make |
| ‘res.data’: | | 2.3.3 Running a simulation and using the output |
| results, Borel sweep: | | 4.4.2 Borel sweep results |
| results, Kalman filter: | | 4.3.2.2 Kalman filter results |
| run, GTLS: | | 4.6.3 Generalized tangent linear system analysis run and output |
| run, SVD: | | 4.5.3 Singular Value Decomposition run and output |
| running model: | | 2.3.3 Running a simulation and using the output |
|
S | | |
| select flag: | | 3.1 Overview of additional features setting |
| ‘selseq.kumac’: | | 3.1 Overview of additional features setting |
| ‘selseq.kumac’: | | A.3 Miniker with cmz |
| ‘sens.data’: | | 4.1 Automatic sensitivity computation |
| sensitivities: | | 4.1 Automatic sensitivity computation |
| sensitivity, output: | | 4.1 Automatic sensitivity computation |
| sequence: | | 2.1 General structure of the code |
| sequences: | | 2 Miniker model programming |
| ‘sigma.data’: | | 4.1 Automatic sensitivity computation |
| Singular Value Decomposition: | | 4.5 Stability analysis of fastest modes |
| ‘sltc.exe’: | | 4.5 Stability analysis of fastest modes |
| ‘sltc.exe’: | | 4.5.3 Singular Value Decomposition run and output |
| ‘sltcirc.exe’: | | 4.6 Generalized linear tangent system analysis |
| ‘sltcirc.exe’: | | 4.6.3 Generalized tangent linear system analysis run and output |
| smod : | | 4.5.1 Singular Value Decomposition with cmz |
| smod : | | 4.6.1 Generalized tangent linear system with cmz |
| starting point: | | Starting points |
| state matrix: | | 4.5 Stability analysis of fastest modes |
| SVD: | | 4.5 Stability analysis of fastest modes |
| SVD output: | | 4.5.3 Singular Value Decomposition run and output |
| SVD run: | | 4.5.3 Singular Value Decomposition run and output |
|
T | | |
| TEF: | | Introduction |
| TEF: | | 2.2 Miniker programming illustrated |
| title file: | | title file |
| ‘title.tex’: | | title file |
| ‘title.tex’, GTLS: | | 4.6.3 Generalized tangent linear system analysis run and output |
| ‘title.tex’, SVD: | | 4.5.3 Singular Value Decomposition run and output |
| ‘tr.data’: | | 2.3.3 Running a simulation and using the output |
| transfers: | | Introduction |
|
U | | |
| up node: | | 3.3 Describing 1D gridded model |
| ‘uxcom.data’: | | 4.2.2 Control laws |
| ‘uycom.data’: | | 4.2.2 Control laws |
|
V | | |
| variance-covariance error: | | Error variance-covariance matrices |
| variance-covariance matrices: | | 4.3.1.2 Error and observation matrices |
| variance-covariance matrices, general: | | 4.3 Kalman filter |
| variance-covariance matrix on state: | | Observations and error on state matrix |
|
Z | | |
| ‘zcmd_law’: | | 4.2.2 Control laws |
| ‘zcmd_law.inc’: | | 4.2.2 Control laws |
| ‘zinit’: | | 2.2.2 Entering model equation and parameters |
| zinit, general: | | 2.1 General structure of the code |
| ‘zinit’, Kalman filter: | | 4.3.1.2 Error and observation matrices |
| ‘zinit.mti’: | | 2.3.2 Setup a model and compile with make |
| ZOOM: | | Introduction |
| ‘zsteer’: | | 2.4.1 Executing code at the end of each time step |
| ‘zsteer’, Kalman filter: | | 4.3.2.1 Feeding the observations to the model |
| ‘zsteer.inc’: | | 2.4.1 Executing code at the end of each time step |
|