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CHANGELOG
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2018-08-21 Axel Schnitger <axel.schnitger@aei.mpg.de>
* CHANGELOG, README.md,
function_gfr/batch_processor_partitioned.m: Update documentation.
* commit 072c386874e366e6c23641cc45db2dea75b6f047
2018-08-20 Axel Schnitger <axel.schnitger@aei.mpg.de>
* CHANGELOG: Add CHANGELOG.
* commit 29983b4997d3999bec01f0a8fe56ac37586825e7
2018-08-20 Axel Schnitger <axel.schnitger@aei.mpg.de> 2018-08-20 Axel Schnitger <axel.schnitger@aei.mpg.de>
* README.md, continue_gfr_par_from_iteration.m, get_input_data.sh: * README.md, continue_gfr_par_from_iteration.m, get_input_data.sh:
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README.md
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...@@ -2,7 +2,7 @@ ...@@ -2,7 +2,7 @@
## Overview ## Overview
GRACETOOLS is an archive of MATLAB software that can be used for gravity field GRACETOOLS is a collection of MATLAB scripts that can be used for gravity field
recovery using GRACE type satellite observations. recovery using GRACE type satellite observations.
**Features** **Features**
...@@ -14,48 +14,45 @@ recovery using GRACE type satellite observations. ...@@ -14,48 +14,45 @@ recovery using GRACE type satellite observations.
- This code can be easily modified to run on the user's local parallel - This code can be easily modified to run on the user's local parallel
computations clusters. computations clusters.
## Content **Content**
<!-- vim-markdown-toc GitLab --> <!-- vim-markdown-toc GitLab -->
* [Usage](#usage) * [Usage](#usage)
* [Example dataset](#example-dataset)
* [Linux & Mac](#linux-mac)
* [Manually](#manually)
* [Performance](#performance) * [Performance](#performance)
* [Files](#files) * [Files](#files)
* [Acknowledgments](#acknowledgments)
* [Contributors](#contributors) * [Contributors](#contributors)
<!-- vim-markdown-toc --> <!-- vim-markdown-toc -->
## Usage GRACETOOLS is open source software and licensed under
[GPLv3](https://gitlab.aei.uni-hannover.de/geoq/gracetools/blob/master/LICENSE).
Please reference this article if you use GRACETOOLS:
**Darbeheshti N., Wöske F., Weigelt M., McCullough C., Wu H. (2018) GRACETOOLS - GRACE gravity field recovery tools, Geosciences.**
The main m-files to run are: `gfr_parallel.m` and
`continue_gfr_par_from_iteration.m`.
### Example dataset ## Usage
To be able to run these scripts you need an example data-set. The main m-files to run are:
#### Linux & Mac - `gfr_parallel.m`
- `continue_gfr_par_from_iteration.m`
If you're working with Linux or MacOS simply use the `get_input_data.sh` script You need an example dataset to run these scripts. If you're on Linux or MacOS
to get the dataset: use the `get_input_data.sh` script to get the dataset:
``` ```
$ ./get_input_data.sh $ ./get_input_data.sh
``` ```
#### Manually If you prefer the manual way download the dataset:
Download the following dataset:
- [Download dataset](https://seafile.projekt.uni-hannover.de/f/3ee8fef6c6cb485489b4/?dl=1) - [Download dataset](https://seafile.projekt.uni-hannover.de/f/3ee8fef6c6cb485489b4/?dl=1)
Move the dataset into the `input_data` directory and extract it. Then delete Move the zip file into the `input_data` directory, extract it and delete the
the `input_data.zip` file. In a terminal the commands look like this from the now unnecessary `input_data.zip` file. For completeness here are the terminal
GRACETOOLS main directory: commands:
``` ```
$ mv ~/Downloads/input_data.zip input_data/ $ mv ~/Downloads/input_data.zip input_data/
...@@ -64,14 +61,7 @@ $ unzip input_data.zip ...@@ -64,14 +61,7 @@ $ unzip input_data.zip
$ rm -f input_data.zip $ rm -f input_data.zip
``` ```
Again from the GRACETOOLS main directory you can check the directory structure The directory structure of `input_data/` should look like this:
of the input_data/ directory with the following command:
```
$ tree input_data/
```
The output should look like this:
``` ```
input_data input_data
...@@ -96,55 +86,62 @@ input_data ...@@ -96,55 +86,62 @@ input_data
└── GGM05S.gfc └── GGM05S.gfc
``` ```
## Performance ## Performance
With an older intel i5 (4 cores) a test case with degree and order 10 with 4 With an older Intel i5 (4 cores) a test case with degree and order 10 with 4
days of observation, each iteration takes about 1h 10min. days of observation, each iteration takes about 1h 10min.
## Files ## Files
| m-file | Description | - `batch_processor_partitioned.m` - batch processing algorithm for GRACE
| :------------------------------ | :-------------------------------------------------------------------------------------------------------------------- | range-rate observations
| `batch_processor_partitioned.m` | batch processing algorithm for GRACE range-rate observations. | - `cs2sc.m`- converts the square containing spherical harmonics coefficients
| `cs2sc.m` | converts the square containing spherical harmonics coefficients storage format into a rectangular format. | storage format into a rectangular format
| `cs2vec` | rearranges a field of spherical harmonic coefficients in cs-or sc-format to a vector shape. | - `cs2vec`- rearranges a field of spherical harmonic coefficients in cs-or
| `deriv.m` | calculates equation of motion and all partials. | sc-format to a vector shape
| `dv_geoidn.m` | reads an Earth's gravity field model and plots the degree variances. | - `deriv.m`- calculates equation of motion and all partials
| `dv_geoidn_no_plot` | reads an Earth's gravity field model and gives the degree variances without plotting. | - `dv_geoidn.m`- reads an Earth's gravity field model and plots the degree
| `grtenpshs.m` | calculates the gradient and the tensor of the gravity field. | variances
| `hmat.m` | makes the Hi_tilda matrix. | - `dv_geoidn_no_plot`- reads an Earth's gravity field model and gives the
| `importGravityField.m` | import numeric data from a text file as a matrix. | degree variances without plotting
| `initplm.m` | initialzes a plm calculation. | - `grtenpshs.m`- calculates the gradient and the tensor of the gravity field
| `inter_sat_dist.m` | calculates range and range rate from position and velocity. | - `hmat.m`- makes the Hi_tilda matrix
| `llpartialgradV.m` | determines the partial derivative of the gradient of the gravity field w.r.t. the coefficients. | - `importGravityField.m`- import numeric data from a text file as a matrix
| `multmatvek.m` | mulitplicates a matrix and a vector. | - `initplm.m`- initializes a plm calculation
| `odeint.m` | integrates one step with step size dt from t0 and initial values y0. | - `inter_sat_dist.m`- calculates range and range rate from position and
| `odeint_abm.m` | integrates one step with step size h from t0 and initial values y0. | velocity
| `odeint_dp8.m` | integrates one step with step size h from t0 and initial values y0 with Runge-Kutta (RK) integrator. | - `llpartialgradV.m`- determines the partial derivative of the gradient of the
| `odeint_dp8_abm_init.m` | integrates one step with step size h from t0 and initial values y0 with Runge-Kutta (RK) integrator. | gravity field w.r.t. the coefficients
| `odeint_rk4.m` | integrates one step with step size h from t0 and initial values y0 with simple 4th order Runge-Kutta (RK) integrator. | - `multmatvek.m`- mulitplicates a matrix and a vector
| `odeint_rk4_abm_init.m` | integrates one step with step size h from t0 and initial values y0 with simple 4th order Runge-Kutta (RK) integrator. | - `odeint.m`- integrates one step with step size dt from t0 and initial values
| `plm.m` | fully normalized associated Legendre functions for a selected order M. | y0
| `plmsp.m` | fully normalized associated Legendre functions for all degree and order but in a single points. | - `odeint_abm.m`- integrates one step with step size h from t0 and initial
| `readACC.m` | Read GRACE ACC1B data | values y0
| `readGFC.m` | Read gfc files | - `odeint_dp8.m`- integrates one step with step size h from t0 and initial
| `readGNV.m` | Read GRACE GNV1B data | values y0 with Runge-Kutta (RK) integrator
| `readKBR.m` | Read GRACE KBR1B data | - `odeint_dp8_abm_init.m`- integrates one step with step size h from t0 and
| `readSCA.m` | Read GRACE SCA1B data | initial values y0 with Runge-Kutta (RK) integrator
| `Ri2e.m` | returns the rotation matrix from an inertial frame to an Earth-fixed coordinate system. | - `odeint_rk4.m`- integrates one step with step size h from t0 and initial
| `Ri2e_dot.m` | returns the derivative of the rotation matrix from inertial frame to an Earth-fixed Earth-centered coordinate system. | values y0 with simple 4th order Runge-Kutta (RK) integrator
| `save_vars2continue_itr.m` | save all important variables of a gravity estimation. | - `odeint_rk4_abm_init.m`- integrates one step with step size h from t0 and
| `vec2cs.m` | rearranges a vector shaped set of spherical harmonic coefficients into cs-format. | initial values y0 with simple 4th order Runge-Kutta (RK) integrator
- `plm.m`- fully normalized associated Legendre functions for a selected order
## Acknowledgments M
- `plmsp.m`- fully normalized associated Legendre functions for all degree and
- GRACETOOLS is open source software (LICENSE GPLv3). order but in a single points
- Please reference this article if you use GRACETOOLS: - `readACC.m`- Read GRACE ACC1B
- `readGFC.m`- Read GFC file
``` - `readGNV.m`- Read GRACE GNV1B
Darbeheshti N., Wöske F., Weigelt M., Mccullough C., Wu H. (2018) GRACETOOLS - GRACE gravity field recovery tools, Geosciences. - `readKBR.m`- Read GRACE KBR1B
``` - `readSCA.m`- Read GRACE SCA1B
- `Ri2e.m`- returns the rotation matrix from an inertial frame to an
Earth-fixed coordinate system
- `Ri2e_dot.m`- returns the derivative of the rotation matrix from inertial
frame to an Earth-fixed Earth-centered coordinate system
- `save_vars2continue_itr.m`- save all important variables of a gravity
estimation
- `vec2cs.m`- rearranges a vector shaped set of spherical harmonic coefficients
into cs-format
## Contributors ## Contributors
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function_gfr/batch_processor_partitioned.m
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function batch_processor_partitioned(Mday,FolderName,lmaxcs,mKBR,field,data_plm,GM,ae,lmaxf,state,timeKBR,observation,x0x) function batch_processor_partitioned(Mday,FolderName,lmaxcs,mKBR,field,data_plm,GM,ae,lmaxf,state,timeKBR,observation,x0x)
% Batch processing algorithm for GRACE range-rate observations. % BATCH_PROCESSOR_PARTITIONED provides a batch processing algorithm for GRACE
% separation between local and global parameters, which are estimated for % range-rate observations.
%
% Separation between local and global parameters, which are estimated for
% different arcs. E.g. Initial states daily and spherical harmonics % different arcs. E.g. Initial states daily and spherical harmonics
% coefficients for the whole time. Using Partitioned Normal Equations % coefficients for the whole time. Using Partitioned Normal Equations based on:
% based on:
% - Gunter's MSc(2000)thesis, page 27 % - Gunter's MSc(2000)thesis, page 27
% - Statistical Orbit Determination (Tapley et al., 2004), page 196-197 % - Statistical Orbit Determination (Tapley et al., 2004), page 196-197
% %
...@@ -23,7 +24,7 @@ function batch_processor_partitioned(Mday,FolderName,lmaxcs,mKBR,field,data_plm, ...@@ -23,7 +24,7 @@ function batch_processor_partitioned(Mday,FolderName,lmaxcs,mKBR,field,data_plm,
% x0x = state deviation [12x1] % x0x = state deviation [12x1]
% %
% Output: function has no output, output is saved in file for easy % Output: function has no output, output is saved in file for easy
% paralleization % parallelization
% %
% Example: see gfr_parallel.m % Example: see gfr_parallel.m
% %
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