# TiSKitPy
Routines for time series data processing
Uses the obspy seismological Trace, Stream (data) and Inventory (metadata)
classes, but should work for non-seismology datasets as well
[Documentation](https://tiskitpy.readthedocs.io/en/latest/index.html)
## Classes
- `CleanRotator`: rotate data to minimize noise on vertical channel
- `DataCleaner`: Transfer_Function-based data cleaning
- `Decimator`: Decimate time series and update metadata with the decimator's
response
- `SpectralDensity`: Calculate and manipulate spectral density functions.
- `TimeSpans`: Specify time spans to be removed, kept, zeroed, etc.
- `ResponseFunctions`: Frequency response functions for a given input channel.
## Functions
- `FIR_corr`: transform zero-phase data to minimum phase (only works for
LCHEAPO loggers, need to update to calculate/work for any
zero-phase filter)
- `readMSEED`: read in MSEED data, including if the file is too big (> 2 GB)
for obspy's read() function
- `rptransient`: calculate and remove periodic transient (VERY manual!).
Based on Matlab code by E Wielandt, used in Deen et al., 2017
- `PetersonNoiseModel`: return the Peterson High and Low Noise Models
## Installation
First, install `obspy` using the instructions on their webpage.
Then, in the pip/conda environment that contains obspy...
### From this repository
Clone or download this repository, then from within the main repository directory, run:
`pip install .`
You can also install in editable mode (for developers), with:
`pip install -e .`
### Using `pip`
Type `pip install tiskitpy`
Raw data
{
"_id": null,
"home_page": "https://github.com/WayneCrawford/tiskitpy",
"name": "tiskitpy",
"maintainer": null,
"docs_url": null,
"requires_python": ">=3.8",
"maintainer_email": null,
"keywords": "oceanography, marine, OBS",
"author": "Wayne Crawford",
"author_email": "crawford@ipgp.fr",
"download_url": "https://files.pythonhosted.org/packages/4f/2e/2123a6185385dc0e24e790e55d4c312ce1f60ea1924f19fd9abaa6cde8af/tiskitpy-0.5.tar.gz",
"platform": null,
"description": "# TiSKitPy\n\nRoutines for time series data processing\n\nUses the obspy seismological Trace, Stream (data) and Inventory (metadata)\nclasses, but should work for non-seismology datasets as well\n\n\n[Documentation](https://tiskitpy.readthedocs.io/en/latest/index.html)\n\n\n## Classes\n\n- `CleanRotator`: rotate data to minimize noise on vertical channel\n- `DataCleaner`: Transfer_Function-based data cleaning\n- `Decimator`: Decimate time series and update metadata with the decimator's\n response\n- `SpectralDensity`: Calculate and manipulate spectral density functions.\n- `TimeSpans`: Specify time spans to be removed, kept, zeroed, etc.\n- `ResponseFunctions`: Frequency response functions for a given input channel.\n \n \n## Functions\n\n- `FIR_corr`: transform zero-phase data to minimum phase (only works for\n LCHEAPO loggers, need to update to calculate/work for any\n zero-phase filter)\n- `readMSEED`: read in MSEED data, including if the file is too big (> 2 GB)\n for obspy's read() function\n- `rptransient`: calculate and remove periodic transient (VERY manual!). \n \tBased on Matlab code by E Wielandt, used in Deen et al., 2017\n\n- `PetersonNoiseModel`: return the Peterson High and Low Noise Models\n\n\n## Installation\n\nFirst, install `obspy` using the instructions on their webpage.\nThen, in the pip/conda environment that contains obspy...\n\n### From this repository\n\nClone or download this repository, then from within the main repository directory, run:\n\n`pip install .`\n\nYou can also install in editable mode (for developers), with:\n\n`pip install -e .`\n\n### Using `pip`\n\nType `pip install tiskitpy`\n",
"bugtrack_url": null,
"license": null,
"summary": "TIme Series toolKIT",
"version": "0.5",
"project_urls": {
"Homepage": "https://github.com/WayneCrawford/tiskitpy"
},
"split_keywords": [
"oceanography",
" marine",
" obs"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "1643773fee21f2221146e5f6af491e99a40dd35c69f3ff9c99ee1bd78c9c70a6",
"md5": "d1e669df4b1df97ff397548ceac7dfd0",
"sha256": "5a822a04e7a4d3ad09448908693eb956504c168b0b6e6ad099639bb4e99dab7a"
},
"downloads": -1,
"filename": "tiskitpy-0.5-py3-none-any.whl",
"has_sig": false,
"md5_digest": "d1e669df4b1df97ff397548ceac7dfd0",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.8",
"size": 158076,
"upload_time": "2024-04-18T08:44:01",
"upload_time_iso_8601": "2024-04-18T08:44:01.577611Z",
"url": "https://files.pythonhosted.org/packages/16/43/773fee21f2221146e5f6af491e99a40dd35c69f3ff9c99ee1bd78c9c70a6/tiskitpy-0.5-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "4f2e2123a6185385dc0e24e790e55d4c312ce1f60ea1924f19fd9abaa6cde8af",
"md5": "6d2909f9d9bd2634bb2e308e8d193d96",
"sha256": "a6f9a47266f34b603215a6e9799bcb4cfd1c73c97bb2e799e73d20b217db95f3"
},
"downloads": -1,
"filename": "tiskitpy-0.5.tar.gz",
"has_sig": false,
"md5_digest": "6d2909f9d9bd2634bb2e308e8d193d96",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.8",
"size": 126229,
"upload_time": "2024-04-18T08:44:03",
"upload_time_iso_8601": "2024-04-18T08:44:03.258630Z",
"url": "https://files.pythonhosted.org/packages/4f/2e/2123a6185385dc0e24e790e55d4c312ce1f60ea1924f19fd9abaa6cde8af/tiskitpy-0.5.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-04-18 08:44:03",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "WayneCrawford",
"github_project": "tiskitpy",
"travis_ci": false,
"coveralls": false,
"github_actions": false,
"lcname": "tiskitpy"
}
JSON
