| Name | reddutils JSON |
| Version |
1.0.7
JSON |
| download |
| home_page | |
| Summary | Small package for personal use |
| upload_time | 2023-08-09 19:35:25 |
| maintainer | |
| docs_url | None |
| author | ReddTea |
| requires_python | >=3.6 |
| license | |
| keywords |
|
| VCS |
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| bugtrack_url |
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| requirements |
No requirements were recorded.
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| Travis-CI |
No Travis.
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# Reddutils
This is ReddTea's small package compiling useful self-made functions for an astrophysical context.
# Overview
Reddutils contains many functions and classes for personal use.
Some of them may be of use for the community.
# Dependencies
This code makes use of:
- Numpy
- pandas
- Scipy
- PyAstronomy (http://www.hs.uni-hamburg.de/DE/Ins/Per/Czesla/PyA/PyA/index.html)
- tqdm (https://pypi.python.org/pypi/tqdm)
- tabulate
- matplotlib.pyplot
- ipywidgets
- IPython.display
Most of them come with conda, if some are missing they can be easily installed with pip.
# Installation
In the console type in your work folder
```sh
pip install reddutils
```
# Usage
## Correlator
For a pandas dataframe or three-column table:
```sh
from reddutils import correlator as rc
import pandas as pd
df = pd.read_csv('data.csv')
cor = rc.correlator()
cor.display(df)
```
## Exodus
Use for visualising the NASA Exoplanet Archive:
```sh
from reddutils import exodus
#exopop = exodus.Exoplanet_Archive()
exopop = exodus.Exoplanet_Archive('NasaExoplanetArchive')
#exopop = exodus.Exoplanet_Archive('ExoplanetEU2')
#exopop = exodus.Exoplanet_Archive('ExoplanetsOrg')
exopop.display()
```
Try out the histogram mode:
```sh
exopop.display_hist()
```
## Fourier Transform Visualiser
For visualising fourier transforms and the nyquist limit.
```sh
from reddutils import fourier
fou = fourier.fourier()
fou.display()
```
## Periodogram
For a pandas dataframe:
```sh
from reddutils import periodogram as rp
import pandas as pd
df = pd.read_csv('data.csv')
per = rp.LSP()
per.display(df)
```
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"description": "# Reddutils\n\nThis is ReddTea's small package compiling useful self-made functions for an astrophysical context.\n\n# Overview\nReddutils contains many functions and classes for personal use.\nSome of them may be of use for the community.\n\n# Dependencies\n\nThis code makes use of:\n - Numpy\n - pandas\n - Scipy\n - PyAstronomy (http://www.hs.uni-hamburg.de/DE/Ins/Per/Czesla/PyA/PyA/index.html)\n - tqdm (https://pypi.python.org/pypi/tqdm)\n - tabulate\n - matplotlib.pyplot\n - ipywidgets\n - IPython.display\n \nMost of them come with conda, if some are missing they can be easily installed with pip.\n\n# Installation\n\nIn the console type in your work folder\n```sh\npip install reddutils\n```\n\n# Usage\n\n## Correlator\nFor a pandas dataframe or three-column table:\n```sh\nfrom reddutils import correlator as rc\nimport pandas as pd\n\ndf = pd.read_csv('data.csv')\n\ncor = rc.correlator()\ncor.display(df)\n```\n\n\n\n## Exodus\nUse for visualising the NASA Exoplanet Archive:\n\n```sh\nfrom reddutils import exodus\n\n#exopop = exodus.Exoplanet_Archive()\nexopop = exodus.Exoplanet_Archive('NasaExoplanetArchive')\n#exopop = exodus.Exoplanet_Archive('ExoplanetEU2')\n#exopop = exodus.Exoplanet_Archive('ExoplanetsOrg')\n\nexopop.display()\n```\n\n\nTry out the histogram mode:\n\n```sh\nexopop.display_hist()\n```\n\n## Fourier Transform Visualiser\nFor visualising fourier transforms and the nyquist limit.\n\n```sh\nfrom reddutils import fourier\n\nfou = fourier.fourier()\nfou.display()\n```\n\n\n\n## Periodogram\nFor a pandas dataframe:\n```sh\nfrom reddutils import periodogram as rp\nimport pandas as pd\n\ndf = pd.read_csv('data.csv')\n\nper = rp.LSP()\nper.display(df)\n```\n\n\n\n",
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