[](https://www.python.org/)
[](https://circleci.com/gh/insarlab/PySolid)
[](https://anaconda.org/conda-forge/pysolid)
[](https://github.com/insarlab/PySolid/releases)
[](https://github.com/insarlab/PySolid/blob/main/LICENSE)
[](https://doi.org/10.1109/TGRS.2022.3168509)
## PySolid
The Python based solid Earth tides (PySolid) is a thin Python wrapper of the [`solid.for`](http://geodesyworld.github.io/SOFTS/solid.htm) program (by Dennis Milbert based on [_dehanttideinelMJD.f_](https://iers-conventions.obspm.fr/content/chapter7/software/dehanttideinel/) from V. Dehant, S. Mathews, J. Gipson and C. Bruyninx) to calculate [solid Earth tides](https://en.wikipedia.org/wiki/Earth_tide) in east, north and up directions (section 7.1.1 in the [2010 IERS Conventions](https://www.iers.org/IERS/EN/Publications/TechnicalNotes/tn36.html)). Solid Earth tides introduce large offsets in SAR observations and long spatial wavelength ramps in InSAR observations, as shown in the Sentinel-1 data with regular acquisitions and large swaths ([Yunjun et al., 2022](https://doi.org/10.1109/TGRS.2022.3168509)).
This is research code provided to you "as is" with NO WARRANTIES OF CORRECTNESS. Use at your own risk.
### 1. Install
PySolid is available on the [conda-forge](https://anaconda.org/conda-forge/pysolid) channel and the main archive of the [Debian](https://tracker.debian.org/pkg/pysolid) GNU/Linux OS. The released version can be install via `conda` as:
```shell
# run "conda update pysolid" to update the installed version
conda install -c conda-forge pysolid
```
or via `apt` (or other package managers) for [Debian-derivative OS](https://wiki.debian.org/Derivatives/Census) users, including [Ubuntu](https://ubuntu.com), as:
```shell
apt install python3-pysolid
```
<details>
<p><summary>Or build from source:</summary></p>
PySolid relies on a few Python modules as described in [requirements.txt](./requirements.txt) and [NumPy's f2py](https://numpy.org/doc/stable/f2py/) to build the Fortran source code. You could use `conda` to install all the dependencies, including the Fortran compiler, or use your own installed Fortran compiler and `pip` to install the rest.
##### a. Download source code
```bash
# run "cd PySolid; git pull" to update to the latest development version
git clone https://github.com/insarlab/PySolid.git
```
##### b. Install dependencies
```bash
# option 1: use conda to install dependencies into an existing, activated environment
conda install -c conda-forge fortran-compiler --file PySolid/requirements.txt --file PySolid/tests/requirements.txt
# option 2: use conda to install dependencies into a new environment, e.g. named "pysolid"
conda create --name pysolid fortran-compiler --file PySolid/requirements.txt --file PySolid/tests/requirements.txt
conda activate pysolid
# option 3: have a Fortran compiler already installed and use pip to install the rest dependencies
python -m pip install -r PySolid/requirements.txt -r PySolid/tests/requirements.txt
```
##### c. Install PySolid
```bash
# option 1: use pip to install pysolid into the current environment
python -m pip install PySolid
# option 2: use pip to install pysolid in develop mode (editable) into the current environment
# setting an environmental variable as below is required for editable installs via pyproject.toml
export SETUPTOOLS_ENABLE_FEATURES="legacy-editable"
python -m pip install -e PySolid
# option 3: manually compile the Fortran code and setup environment variable
cd PySolid/src/pysolid
f2py -c -m solid solid.for
export PYTHONPATH=${PYTHONPATH}:~/tools/PySolid
```
##### d. Test the installation
To test the installation, run the following:
```bash
python -c "import pysolid; print(pysolid.__version__)"
python PySolid/tests/grid.py
python PySolid/tests/point.py
```
</details>
### 2. Usage
PySolid could compute solid Earth tides in two modes: **point** and **grid**. Both modes produce displacement in east, north and up directions.
+ **Point mode:** compute 1D tides time-series at a specific point for a given time period
+ **Grid mode:** compute 2D tides grid at a specific time for a given spatial grid
#### 2.1 Point Mode [[notebook](./docs/plot_point_SET.ipynb)]
```python
import datetime as dt
import pysolid
# prepare inputs
lat, lon = 34.0, -118.0 # point of interest in degree, Los Angles, CA
step_sec = 60 * 5 # sample spacing in time domain in seconds
dt0 = dt.datetime(2020, 1, 1, 4, 0, 0) # start date and time
dt1 = dt.datetime(2021, 1, 1, 2, 0, 0) # end date and time
# compute SET via pysolid
dt_out, tide_e, tide_n, tide_u = pysolid.calc_solid_earth_tides_point(
lat, lon, dt0, dt1,
step_sec=step_sec,
display=False,
verbose=False,
)
# plot the power spectral density of SET up component
pysolid.plot_power_spectral_density4tides(tide_u, sample_spacing=step_sec)
```
<p align="left">
<img width="600" src="./docs/images/set_point_ts.png">
<img width="600" src="./docs/images/set_point_psd.png">
</p>
#### 2.2 Grid Mode [[notebook](./docs/plot_grid_SET.ipynb)]
```python
import datetime as dt
import numpy as np
import pysolid
# prepare inputs
dt_obj = dt.datetime(2020, 12, 25, 14, 7, 44)
meta = {
'LENGTH' : 500, # number of rows
'WIDTH' : 450, # number of columns
'X_FIRST': -126, # min longitude in degree (upper left corner of the upper left pixel)
'Y_FIRST': 43, # max laitude in degree (upper left corner of the upper left pixel)
'X_STEP' : 0.000925926 * 30, # output resolution in degree
'Y_STEP' : -0.000925926 * 30, # output resolution in degree
}
# compute SET via pysolid
tide_e, tide_n, tide_u = pysolid.calc_solid_earth_tides_grid(
dt_obj, meta,
display=False,
verbose=True,
)
# project SET from ENU to satellite line-of-sight (LOS) direction with positive for motion towards the satellite
# inc_angle : incidence angle of the LOS vector (from ground to radar platform) measured from vertical.
# az_angle : azimuth angle of the LOS vector (from ground to radar platform) measured from the north, with anti-clockwirse as positive.
inc_angle = np.deg2rad(34) # radian, typical value for Sentinel-1
az_angle = np.deg2rad(-102) # radian, typical value for Sentinel-1 descending track
tide_los = ( tide_e * np.sin(inc_angle) * np.sin(az_angle) * -1
+ tide_n * np.sin(inc_angle) * np.cos(az_angle)
+ tide_u * np.cos(inc_angle))
```
<p align="left">
<img width="800" src="./docs/images/set_grid.png">
</p>
### 3. Citing this work
+ Yunjun, Z., Fattahi, H., Pi, X., Rosen, P., Simons, M., Agram, P., & Aoki, Y. (2022). Range Geolocation Accuracy of C-/L-band SAR and its Implications for Operational Stack Coregistration. _IEEE Trans. Geosci. Remote Sens., 60_, 5227219. [ [doi](https://doi.org/10.1109/TGRS.2022.3168509) \| [arxiv](https://doi.org/10.31223/X5F641) \| [data](https://doi.org/10.5281/zenodo.6360749) \| [notebook](https://github.com/yunjunz/2022-Geolocation) ]
+ Milbert, D. (2018), "solid: Solid Earth Tide", [Online]. Available: http://geodesyworld.github.io/SOFTS/solid.htm. Accessd on: 2020-09-06.
Raw data
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"keywords": "solid Eartth tides,deformation,geodesy,geophysics",
"author": "Zhang Yunjun, Dennis Milbert",
"author_email": "yunjunz@outlook.com",
"download_url": "https://files.pythonhosted.org/packages/3f/f5/e582719eaa586303caf0ffc6357576a996cb64465cd222a60a42b541c3d2/pysolid-0.3.2.tar.gz",
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"description": "[](https://www.python.org/)\n[](https://circleci.com/gh/insarlab/PySolid)\n[](https://anaconda.org/conda-forge/pysolid)\n[](https://github.com/insarlab/PySolid/releases)\n[](https://github.com/insarlab/PySolid/blob/main/LICENSE)\n[](https://doi.org/10.1109/TGRS.2022.3168509)\n\n## PySolid\n\nThe Python based solid Earth tides (PySolid) is a thin Python wrapper of the [`solid.for`](http://geodesyworld.github.io/SOFTS/solid.htm) program (by Dennis Milbert based on [_dehanttideinelMJD.f_](https://iers-conventions.obspm.fr/content/chapter7/software/dehanttideinel/) from V. Dehant, S. Mathews, J. Gipson and C. Bruyninx) to calculate [solid Earth tides](https://en.wikipedia.org/wiki/Earth_tide) in east, north and up directions (section 7.1.1 in the [2010 IERS Conventions](https://www.iers.org/IERS/EN/Publications/TechnicalNotes/tn36.html)). Solid Earth tides introduce large offsets in SAR observations and long spatial wavelength ramps in InSAR observations, as shown in the Sentinel-1 data with regular acquisitions and large swaths ([Yunjun et al., 2022](https://doi.org/10.1109/TGRS.2022.3168509)).\n\nThis is research code provided to you \"as is\" with NO WARRANTIES OF CORRECTNESS. Use at your own risk.\n\n### 1. Install\n\nPySolid is available on the [conda-forge](https://anaconda.org/conda-forge/pysolid) channel and the main archive of the [Debian](https://tracker.debian.org/pkg/pysolid) GNU/Linux OS. The released version can be install via `conda` as:\n\n```shell\n# run \"conda update pysolid\" to update the installed version\nconda install -c conda-forge pysolid\n```\n\nor via `apt` (or other package managers) for [Debian-derivative OS](https://wiki.debian.org/Derivatives/Census) users, including [Ubuntu](https://ubuntu.com), as:\n\n```shell\napt install python3-pysolid\n```\n\n<details>\n<p><summary>Or build from source:</summary></p>\n\nPySolid relies on a few Python modules as described in [requirements.txt](./requirements.txt) and [NumPy's f2py](https://numpy.org/doc/stable/f2py/) to build the Fortran source code. You could use `conda` to install all the dependencies, including the Fortran compiler, or use your own installed Fortran compiler and `pip` to install the rest.\n\n##### a. Download source code\n\n```bash\n# run \"cd PySolid; git pull\" to update to the latest development version\ngit clone https://github.com/insarlab/PySolid.git\n```\n\n##### b. Install dependencies\n\n```bash\n# option 1: use conda to install dependencies into an existing, activated environment\nconda install -c conda-forge fortran-compiler --file PySolid/requirements.txt --file PySolid/tests/requirements.txt\n\n# option 2: use conda to install dependencies into a new environment, e.g. named \"pysolid\"\nconda create --name pysolid fortran-compiler --file PySolid/requirements.txt --file PySolid/tests/requirements.txt\nconda activate pysolid\n\n# option 3: have a Fortran compiler already installed and use pip to install the rest dependencies\npython -m pip install -r PySolid/requirements.txt -r PySolid/tests/requirements.txt\n```\n\n##### c. Install PySolid\n\n```bash\n# option 1: use pip to install pysolid into the current environment\npython -m pip install PySolid\n\n# option 2: use pip to install pysolid in develop mode (editable) into the current environment\n# setting an environmental variable as below is required for editable installs via pyproject.toml\nexport SETUPTOOLS_ENABLE_FEATURES=\"legacy-editable\"\npython -m pip install -e PySolid\n\n# option 3: manually compile the Fortran code and setup environment variable\ncd PySolid/src/pysolid\nf2py -c -m solid solid.for\nexport PYTHONPATH=${PYTHONPATH}:~/tools/PySolid\n```\n\n##### d. Test the installation\n\nTo test the installation, run the following:\n\n```bash\npython -c \"import pysolid; print(pysolid.__version__)\"\npython PySolid/tests/grid.py\npython PySolid/tests/point.py\n```\n</details>\n\n### 2. Usage\n\nPySolid could compute solid Earth tides in two modes: **point** and **grid**. Both modes produce displacement in east, north and up directions.\n\n+ **Point mode:** compute 1D tides time-series at a specific point for a given time period\n+ **Grid mode:** compute 2D tides grid at a specific time for a given spatial grid\n\n#### 2.1 Point Mode [[notebook](./docs/plot_point_SET.ipynb)]\n\n```python\nimport datetime as dt\nimport pysolid\n\n# prepare inputs\nlat, lon = 34.0, -118.0 # point of interest in degree, Los Angles, CA\nstep_sec = 60 * 5 # sample spacing in time domain in seconds\ndt0 = dt.datetime(2020, 1, 1, 4, 0, 0) # start date and time\ndt1 = dt.datetime(2021, 1, 1, 2, 0, 0) # end date and time\n\n# compute SET via pysolid\ndt_out, tide_e, tide_n, tide_u = pysolid.calc_solid_earth_tides_point(\n lat, lon, dt0, dt1,\n step_sec=step_sec,\n display=False,\n verbose=False,\n)\n\n# plot the power spectral density of SET up component\npysolid.plot_power_spectral_density4tides(tide_u, sample_spacing=step_sec)\n```\n\n<p align=\"left\">\n <img width=\"600\" src=\"./docs/images/set_point_ts.png\">\n <img width=\"600\" src=\"./docs/images/set_point_psd.png\">\n</p>\n\n#### 2.2 Grid Mode [[notebook](./docs/plot_grid_SET.ipynb)]\n\n```python\nimport datetime as dt\nimport numpy as np\nimport pysolid\n\n# prepare inputs\ndt_obj = dt.datetime(2020, 12, 25, 14, 7, 44)\nmeta = {\n 'LENGTH' : 500, # number of rows\n 'WIDTH' : 450, # number of columns\n 'X_FIRST': -126, # min longitude in degree (upper left corner of the upper left pixel)\n 'Y_FIRST': 43, # max laitude in degree (upper left corner of the upper left pixel)\n 'X_STEP' : 0.000925926 * 30, # output resolution in degree\n 'Y_STEP' : -0.000925926 * 30, # output resolution in degree\n}\n\n# compute SET via pysolid\ntide_e, tide_n, tide_u = pysolid.calc_solid_earth_tides_grid(\n dt_obj, meta,\n display=False,\n verbose=True,\n)\n\n# project SET from ENU to satellite line-of-sight (LOS) direction with positive for motion towards the satellite\n# inc_angle : incidence angle of the LOS vector (from ground to radar platform) measured from vertical.\n# az_angle : azimuth angle of the LOS vector (from ground to radar platform) measured from the north, with anti-clockwirse as positive.\ninc_angle = np.deg2rad(34) # radian, typical value for Sentinel-1\naz_angle = np.deg2rad(-102) # radian, typical value for Sentinel-1 descending track\ntide_los = ( tide_e * np.sin(inc_angle) * np.sin(az_angle) * -1\n + tide_n * np.sin(inc_angle) * np.cos(az_angle)\n + tide_u * np.cos(inc_angle))\n```\n\n<p align=\"left\">\n <img width=\"800\" src=\"./docs/images/set_grid.png\">\n</p>\n\n### 3. Citing this work\n\n+ Yunjun, Z., Fattahi, H., Pi, X., Rosen, P., Simons, M., Agram, P., & Aoki, Y. (2022). Range Geolocation Accuracy of C-/L-band SAR and its Implications for Operational Stack Coregistration. _IEEE Trans. Geosci. Remote Sens., 60_, 5227219. [ [doi](https://doi.org/10.1109/TGRS.2022.3168509) \\| [arxiv](https://doi.org/10.31223/X5F641) \\| [data](https://doi.org/10.5281/zenodo.6360749) \\| [notebook](https://github.com/yunjunz/2022-Geolocation) ]\n+ Milbert, D. (2018), \"solid: Solid Earth Tide\", [Online]. Available: http://geodesyworld.github.io/SOFTS/solid.htm. Accessd on: 2020-09-06.\n\n\n",
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