The sophisticated tool needed for scientific computing.
Project description
ExPy
The sophisticated tool needed for scientific computing.
- Documentation: https://youseitakei.github.io/expy
- Source code: https://github.com/YouseiTakei/expy
- Contributing: coming soon
- Bug reports: coming soon
- Website: coming soon
It provides:
- useful rendering formula, Formula deformation.
- simply converting Jupyter notebook to PDF based on nbconvert.
To get the latest version :
from https://pypi.python.org/pypl/experiment-python/$ pip install expy-python
To get the latest version do:
$ git clone git://github.com/YouseiTakei/expy.git
$ cd expy
$ python setup.py install
Documentation and usage:
- Everything is at: coming soon
From this directory, start Jupyter notebook and:
>>> from expy import F, x_, y_,
>>> f = F(y_, x_**x_)
>>> f.set(x_, 0)
>>> f.tex()
Convert your Jupyter notebook. start cmd line and:
$ nbc -a -p -t
Usage Example:
Usage | Detail |
---|---|
nbc -h |
check args help |
nbc -i test.ipynb |
convert to pdf |
nbc -a test_dir |
convert all file in your directory |
nbc -r test.pdf |
remove converted pdf file or all files in directory |
nbc -i test.ipynb -o html |
convert to html |
nbc -a test_dir -o html |
convert all files to html |
nbc -r test_dir -o html |
remove all html files in directory |
nbc -i test.ipynb -p result\today\ |
use output path |
nbc -i test.ipynb -t data\article.tplx |
use your template |
Other Usage Hints:
- If you want to change template file, you can edit file in
~/.expy/latex/article.tplx
- If you don't have auth and can't install this, you can use
$pip install expy-python --user
- If you can't convret pd.DataFrame, you should run 'ep.init_ep()'
Call for Contributions:
If you have found ExPy to be useful in your work, research or company, please consider making a donation to the project commensurate with your resources.
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