| Name | gravitools JSON |
| Version |
0.2.0
JSON |
| download |
| home_page | None |
| Summary | A collection of tools for gravimeter data analysis |
| upload_time | 2024-12-10 04:04:06 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.8 |
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| keywords |
gravimetry
gravimeter
geodesy
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
A collection of tools to analyze gravimeter data.
This Python package is a collaborative effort by the gravity metrology group at
the [German Federal Agency for Carthography and Geoesy (BKG)][BKG] and the
[hydrology section][Hydrology] at [GFZ German
Research Centre for Geosciences][GFZ].
[BKG]: https://bkg.bund.de
[Hydrology]: https://www.gfz-potsdam.de/sektion/hydrologie
[GFZ]: https://www.gfz-potsdam.de
## Features
* Read and process raw data of the [Exail Absolute Quantum Gravimeter
(AQG)][AQG]
* Apply standardized or customized AQG data processing and outlier detection
* Read and write processed datasets with metadata to .nc-files in
[NETCDF4-format][NETCDF4]
* Handle Earth orientation parameters (EOP) from [iers.org][IERS] for polar
motion correction
* Evaluate tilt calibration measurements
* Visualize data with matplotlib
* CLI for standard processing of AQG raw data to .nc-file
* Dashboard for real-time processing and visualization during measurements (on AQG laptop)
* Dashboard includes a proposed standard template for a measurement protocol
[AQG]: https://www.ixblue.com/quantum-gravimeter
[NETCDF4]: https://www.unidata.ucar.edu/software/netcdf
[IERS]: https://www.iers.org
### Planned
* Handling of [Scintrex CG6][CG6] data and standard analyses
* Generation of PDF-report for tilt calibration analyses
[CG6]: https://scintrexltd.com/product/cg-6-autograv-gravity-meter/
## Dependencies
* Python 3.8 or later
* [allantools](https://github.com/aewallin/allantools) (LGPLv3+ license)
* [fpdf2](https://pypi.org/project/fpdf2/) (LGPLv3)
* [matplotlib](https://matplotlib.org/) (PSF license)
* [netcdf4-python](https://github.com/Unidata/netcdf4-python) (MIT license)
* [numpy](https://numpy.org/) (BSD license)
* [pandas](https://pandas.pydata.org/) (BSD license)
* [pyyaml](https://pyyaml.org/) (MIT license)
* [requests](https://pypi.org/project/requests/) (Apache 2 license)
* [xarray](https://xarray.pydata.org/) (Apache 2 license)
### Optional
#### AQG dashboard
* [PySide6](https://pypi.org/project/PySide6/) (LGPLv3 license)
* [pyqtgraph](https://www.pyqtgraph.org/) (MIT license)
#### Documentation
* [mkdocs](https://pypi.org/project/mkdocs/) (BSD license)
* [mkdocstrings-python](https://pypi.org/project/mkdocstrings-python/) (ISC
license)
* [mkdocs-material](https://pypi.org/project/mkdocs-material/) (MIT license)
* [mkdocs-jupyter](https://pypi.org/project/mkdocs-jupyter/) (Apache 2 license)
#### Unit tests
* [pytest](https://pypi.org/project/pytest/) (MIT license)
* [pytest-cov](https://pypi.org/project/pytest-cov/) (MIT license)
## Installation
For the latest stable release, install from PyPI.org
```console
$ pip install gravitools
```
For the latest (development) version, install from Git repository
```console
$ pip install git+https://gitlab.opencode.de/bkg/gravitools.git
```
For further install instructions please see the respective section in the
documentation.
## Getting started with AQG data processing
Example usage:
```py
from gravitools.aqg import read_aqg_raw_dataset
# Read raw data to an AQGRawData object (which wraps a pandas.DataFrame)
raw = read_aqg_raw_dataset("20240620_163341.zip")
# Apply standard processing
raw.process()
# Finalize processing by converting to an AQGDataset (which wraps an
# xarray.Dataset)
dataset = raw.to_dataset()
# Save processed dataset to file in NETCDF-4 format
dataset.to_nc("20240620_163341.nc")
# Generate and save a measurement report in PDF format
dataset.save_report("report_20240620_163341.pdf")
```
## AQG dashboard
The dashboard has to be run on the AQG laptop in order to profit from its full
functionality. It has the purpose to provide an alternative, customizable way
of viewing and interacting with measurement data, during the process of live
measurements. This is especially helpful for updated, on-the-fly outlier
detection and plots of parameters as time series (e.g. temperatures, tilts).
More information on this, including all offered options, are addressed in the
documentation.
Install gravitools with the optional dependencies for the dashboard, preferably
in an isolated virtual environment.
```console
$ pip install gravitools[dashboard]
```
Run the dashboard
```console
$ gt-aqg-dash
```
You can now access the dashboard at `http://localhost:8000/`.
## Documentation
The documenation is available at [readthedocs.io][docu_rtd].
[docu_rtd]: https://gravitools.readthedocs.io/en/latest/
To build the documentation, clone the repository and install gravitools with
the necessary dependencies into a virtual environment.
```console
$ git clone https://gitlab.opencode.de/bkg/gravitools.git
$ cd gravitools/
$ python -m venv venv
$ source venv/bin/activate
$ pip install -e .[docs]
```
Build the documentation
```console
$ mkdocs build
```
The documentation can be accessed at `public/index.html`.
## Conventions
### Data
* All corrections are *subtracted* from the measured gravity value.
* Units are assumed as follows (if not provided and parameters are passed only
as numbers). Input data in other units is converted.
- Gravity: nm s^-2^
- Gravity gradient: nm s^-2^ m^-1^
- Heights: m
- Tilt angle: rad
- Polar angles: arcsec
- Coordinates: degree
- Orientation of sensor: degree from North
* Timestamps are always UTC.
### Terminology
Point
: A precisely defined measurement location, usually identified by a point code.
For example, the gravimeter lab at the Geodetic Observatory Wettzell has points
WET_CA, WET_DA, WET_EA, and WET_FA. The vertical gravity gradient is a property
of each point. An Earth tide model can apply to multiple points.
`site_name`
: The AQG control software has an input field for the measurement site name. It
is recored in the metadata (.info file) as `measurement_site_name`. Here, this
parameter name is shortened to `site_name` and its value kept unchanged. Since
this field can contain supplementary metadata, such as sensor orientation, it
is not necessarily identical to the point code. When reading a dataset,
Gravitools attempts to guess the point code and sensor orientation from the
`site_name` by a formatting pattern.
Raw data
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"name": "gravitools",
"maintainer": null,
"docs_url": null,
"requires_python": ">=3.8",
"maintainer_email": null,
"keywords": "gravimetry, gravimeter, geodesy",
"author": null,
"author_email": "Marvin Reich <mreich@gfz-potsdam.de>, Julian Gl\u00e4ssel <julian.glaessel@bkg.bund.de>",
"download_url": "https://files.pythonhosted.org/packages/90/bf/cde6ab14ce8b1593e55fa21674a40fff8293683bdf2810a6db272e30c786/gravitools-0.2.0.tar.gz",
"platform": null,
"description": "\n\nA collection of tools to analyze gravimeter data.\n\nThis Python package is a collaborative effort by the gravity metrology group at\nthe [German Federal Agency for Carthography and Geoesy (BKG)][BKG] and the\n[hydrology section][Hydrology] at [GFZ German\nResearch Centre for Geosciences][GFZ].\n\n[BKG]: https://bkg.bund.de\n[Hydrology]: https://www.gfz-potsdam.de/sektion/hydrologie\n[GFZ]: https://www.gfz-potsdam.de\n\n\n## Features\n\n* Read and process raw data of the [Exail Absolute Quantum Gravimeter\n (AQG)][AQG]\n* Apply standardized or customized AQG data processing and outlier detection\n* Read and write processed datasets with metadata to .nc-files in\n [NETCDF4-format][NETCDF4]\n* Handle Earth orientation parameters (EOP) from [iers.org][IERS] for polar\n motion correction\n* Evaluate tilt calibration measurements\n* Visualize data with matplotlib\n* CLI for standard processing of AQG raw data to .nc-file\n* Dashboard for real-time processing and visualization during measurements (on AQG laptop)\n* Dashboard includes a proposed standard template for a measurement protocol\n\n[AQG]: https://www.ixblue.com/quantum-gravimeter\n[NETCDF4]: https://www.unidata.ucar.edu/software/netcdf\n[IERS]: https://www.iers.org\n\n### Planned\n\n* Handling of [Scintrex CG6][CG6] data and standard analyses\n* Generation of PDF-report for tilt calibration analyses\n\n[CG6]: https://scintrexltd.com/product/cg-6-autograv-gravity-meter/\n\n\n## Dependencies\n\n* Python 3.8 or later\n* [allantools](https://github.com/aewallin/allantools) (LGPLv3+ license)\n* [fpdf2](https://pypi.org/project/fpdf2/) (LGPLv3)\n* [matplotlib](https://matplotlib.org/) (PSF license)\n* [netcdf4-python](https://github.com/Unidata/netcdf4-python) (MIT license)\n* [numpy](https://numpy.org/) (BSD license)\n* [pandas](https://pandas.pydata.org/) (BSD license)\n* [pyyaml](https://pyyaml.org/) (MIT license)\n* [requests](https://pypi.org/project/requests/) (Apache 2 license)\n* [xarray](https://xarray.pydata.org/) (Apache 2 license)\n\n### Optional\n\n#### AQG dashboard\n\n* [PySide6](https://pypi.org/project/PySide6/) (LGPLv3 license)\n* [pyqtgraph](https://www.pyqtgraph.org/) (MIT license)\n\n#### Documentation\n\n* [mkdocs](https://pypi.org/project/mkdocs/) (BSD license)\n* [mkdocstrings-python](https://pypi.org/project/mkdocstrings-python/) (ISC\n license)\n* [mkdocs-material](https://pypi.org/project/mkdocs-material/) (MIT license)\n* [mkdocs-jupyter](https://pypi.org/project/mkdocs-jupyter/) (Apache 2 license)\n\n#### Unit tests\n\n* [pytest](https://pypi.org/project/pytest/) (MIT license)\n* [pytest-cov](https://pypi.org/project/pytest-cov/) (MIT license)\n\n\n## Installation\n\nFor the latest stable release, install from PyPI.org\n\n```console\n $ pip install gravitools\n```\n\nFor the latest (development) version, install from Git repository\n\n```console\n $ pip install git+https://gitlab.opencode.de/bkg/gravitools.git\n```\n\nFor further install instructions please see the respective section in the\ndocumentation.\n\n\n## Getting started with AQG data processing\n\nExample usage:\n\n```py\n from gravitools.aqg import read_aqg_raw_dataset\n\n # Read raw data to an AQGRawData object (which wraps a pandas.DataFrame)\n raw = read_aqg_raw_dataset(\"20240620_163341.zip\")\n\n # Apply standard processing\n raw.process()\n\n # Finalize processing by converting to an AQGDataset (which wraps an\n # xarray.Dataset)\n dataset = raw.to_dataset()\n\n # Save processed dataset to file in NETCDF-4 format\n dataset.to_nc(\"20240620_163341.nc\")\n\n # Generate and save a measurement report in PDF format\n dataset.save_report(\"report_20240620_163341.pdf\")\n```\n\n\n## AQG dashboard\n\nThe dashboard has to be run on the AQG laptop in order to profit from its full\nfunctionality. It has the purpose to provide an alternative, customizable way\nof viewing and interacting with measurement data, during the process of live\nmeasurements. This is especially helpful for updated, on-the-fly outlier\ndetection and plots of parameters as time series (e.g. temperatures, tilts).\nMore information on this, including all offered options, are addressed in the\ndocumentation.\n\nInstall gravitools with the optional dependencies for the dashboard, preferably\nin an isolated virtual environment.\n\n```console\n $ pip install gravitools[dashboard]\n```\n\nRun the dashboard\n\n```console\n $ gt-aqg-dash\n```\n\nYou can now access the dashboard at `http://localhost:8000/`.\n\n\n## Documentation\n\nThe documenation is available at [readthedocs.io][docu_rtd].\n\n[docu_rtd]: https://gravitools.readthedocs.io/en/latest/\n\nTo build the documentation, clone the repository and install gravitools with\nthe necessary dependencies into a virtual environment.\n\n```console\n $ git clone https://gitlab.opencode.de/bkg/gravitools.git\n $ cd gravitools/\n $ python -m venv venv\n $ source venv/bin/activate\n $ pip install -e .[docs]\n```\n\nBuild the documentation\n\n```console\n $ mkdocs build\n```\n\nThe documentation can be accessed at `public/index.html`.\n\n\n## Conventions\n\n### Data\n\n* All corrections are *subtracted* from the measured gravity value.\n* Units are assumed as follows (if not provided and parameters are passed only\n as numbers). Input data in other units is converted.\n - Gravity: nm s^-2^\n - Gravity gradient: nm s^-2^ m^-1^\n - Heights: m\n - Tilt angle: rad\n - Polar angles: arcsec\n - Coordinates: degree\n - Orientation of sensor: degree from North\n* Timestamps are always UTC.\n\n### Terminology\n\nPoint\n: A precisely defined measurement location, usually identified by a point code.\nFor example, the gravimeter lab at the Geodetic Observatory Wettzell has points\nWET_CA, WET_DA, WET_EA, and WET_FA. The vertical gravity gradient is a property\nof each point. An Earth tide model can apply to multiple points.\n\n`site_name`\n: The AQG control software has an input field for the measurement site name. It\nis recored in the metadata (.info file) as `measurement_site_name`. Here, this\nparameter name is shortened to `site_name` and its value kept unchanged. Since\nthis field can contain supplementary metadata, such as sensor orientation, it\nis not necessarily identical to the point code. When reading a dataset,\nGravitools attempts to guess the point code and sensor orientation from the\n`site_name` by a formatting pattern.\n",
"bugtrack_url": null,
"license": "EUROPEAN UNION PUBLIC LICENCE v. 1.2 EUPL \u00a9 the European Union 2007, 2016 This European Union Public Licence (the \u2018EUPL\u2019) applies to the Work (as defined below) which is provided under the terms of this Licence. Any use of the Work, other than as authorised under this Licence is prohibited (to the extent such use is covered by a right of the copyright holder of the Work). The Work is provided under the terms of this Licence when the Licensor (as defined below) has placed the following notice immediately following the copyright notice for the Work: Licensed under the EUPL or has expressed by any other means his willingness to license under the EUPL. 1. Definitions In this Licence, the following terms have the following meaning: - \u2018The Licence\u2019: this Licence. - \u2018The Original Work\u2019: the work or software distributed or communicated by the Licensor under this Licence, available as Source Code and also as Executable Code as the case may be. - \u2018Derivative Works\u2019: the works or software that could be created by the Licensee, based upon the Original Work or modifications thereof. This Licence does not define the extent of modification or dependence on the Original Work required in order to classify a work as a Derivative Work; this extent is determined by copyright law applicable in the country mentioned in Article 15. - \u2018The Work\u2019: the Original Work or its Derivative Works. - \u2018The Source Code\u2019: the human-readable form of the Work which is the most convenient for people to study and modify. - \u2018The Executable Code\u2019: any code which has generally been compiled and which is meant to be interpreted by a computer as a program. - \u2018The Licensor\u2019: the natural or legal person that distributes or communicates the Work under the Licence. - \u2018Contributor(s)\u2019: any natural or legal person who modifies the Work under the Licence, or otherwise contributes to the creation of a Derivative Work. - \u2018The Licensee\u2019 or \u2018You\u2019: any natural or legal person who makes any usage of the Work under the terms of the Licence. - \u2018Distribution\u2019 or \u2018Communication\u2019: any act of selling, giving, lending, renting, distributing, communicating, transmitting, or otherwise making available, online or offline, copies of the Work or providing access to its essential functionalities at the disposal of any other natural or legal person. 2. 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