Metadata-Version: 2.1
Name: penguins
Version: 0.4.0
Summary: Penguins: an Easy, NPE-free Gateway to Unpacking and Illustrating NMR Spectra
Home-page: https://github.com/yongrenjie/penguins
Author: Jonathan Yong
Author-email: yongrenjie@gmail.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE.txt

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## Penguins: an Easy, NPE-free Gateway to Unpacking and Illustrating NMR Spectra

```
pip install penguins
```

`penguins` is a Python 3 package intended mainly for generating publication-quality plots of NMR spectra in a programmatic, reproducible fashion.

Documentation can be found at https://yongrenjie.github.io/penguins.
Everything is documented in one form or another, although I'm still working on tutorial-type pages which are easier to read than the docstrings.

Note that `penguins` is still in development, so the interface should not be assumed to be (too) stable. For now, I am working directly on the master branch, and rebasing/force pushing may occur without warning.

---------

As an example of the output, here's Figure 2 from [*Angew. Chem. Int. Ed.* **2017**, *56* (39), 11779–11783](https://doi.org/10.1002/anie.201705506):

<div align="center"><img src="https://raw.githubusercontent.com/yongrenjie/penguins/master/docs/images/angew_example.png" height="500"></div>

And here's a similar plot that can be done in under 20 lines of PEP8-compliant code using penguins (it's the same compound, but not the same data):

<div align="center"><img src="https://raw.githubusercontent.com/yongrenjie/penguins/master/docs/images/readme_example.png" height="550"></div>

```python
import penguins as pg
hmqc, hsqc, cosy, noesy = (pg.read("penguins-testdata", expno)
                           for expno in range(22001, 22005))

fig, axs = pg.subplots2d(2, 2)
hmqc.stage(axs[0, 0], levels=7e3, f1_bounds="110..130", f2_bounds="7..9.5")
hsqc.stage(axs[0, 1], levels=4e4, f1_bounds="12..65", f2_bounds="0.5..5")
cosy.stage(axs[1, 0], levels=8e5)
noesy.stage(axs[1, 1], levels=1e5)

titles = [r"$^{15}$N HMQC", r"$^{13}$C HSQC", "COSY", "NOESY"]
for ax, title in zip(axs.flat, titles):
    pg.mkplot(ax, title=title)
    pg.ymove(ax, pos="topright")

pg.label_axes(axs, fstr="({})", fontweight="semibold", fontsize=12)
pg.cleanup_axes()
pg.show()
```

----------

(The 'NPE' in the name stands for the "billion-dollar mistake", i.e. the `NullPointerException` familiar to TopSpin users.)


