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https://github.com/dohlee/python-dohlee
:package: My personal python utility library.
https://github.com/dohlee/python-dohlee
bioinformatics bioinformatics-analysis mutational-signatures personal-utility python3 visualization
Last synced: about 1 month ago
JSON representation
:package: My personal python utility library.
- Host: GitHub
- URL: https://github.com/dohlee/python-dohlee
- Owner: dohlee
- License: mit
- Created: 2018-04-22T04:47:11.000Z (over 6 years ago)
- Default Branch: develop
- Last Pushed: 2019-11-25T07:21:44.000Z (about 5 years ago)
- Last Synced: 2024-08-10T09:13:26.480Z (4 months ago)
- Topics: bioinformatics, bioinformatics-analysis, mutational-signatures, personal-utility, python3, visualization
- Language: Python
- Homepage: https://python-dohlee.rtfd.io
- Size: 2.37 MB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.rst
- Contributing: CONTRIBUTING.rst
- License: LICENSE
Awesome Lists containing this project
README
python-dohlee
My personal python library.
Installation
```
pip install dohlee
```
Examples
### dohlee.plot
Plotting library. Provides simple ways to produce publication-ready plots.
***dohlee.plot.mutation_signature***
```python
import dohlee.plot as plot; plot.set_style() # Sets plot styles.
ax = plot.get_axis(figsize=(20.4, 3.4))
plot.mutation_signature(data, ax=ax)
```
***dohlee.plot.boxplot***
```python
ax = plot.get_axis(preset='wide', transpose=True)
plot.boxplot(data=iris, x='species', y='sepal_length', ax=ax)
```
***dohlee.plot.histogram***
```python
ax = plot.get_axis(preset='wide')
plot.histogram(iris.sepal_length, bins=22, xlabel='Sepal Length', ylabel='Frequency', ax=ax)
```
***dohlee.plot.frequency***
```python
ax = plot.get_axis(preset='wide')
plot.frequency(data, ax=ax, xlabel='Your numbers', ylabel='Frequency')
```
***dohlee.plot.tsne***
```python
ax = plot.get_axis(preset='wide')
plot.tsne(
iris[['sepal_length', 'sepal_width', 'petal_length', 'petal_width']],
ax=ax,
s=5,
labels=iris['species']
)
```
***dohlee.plot.stacked_bar_chart***
```python
# Generate sample data.
n_samples = 100
sample_dict = {'Sample': ['S%d' % i for i in range(1, n_samples + 1)]}
value_dict = {c: np.random.randint(0, 100, size=n_samples) for c in ['Missense', 'Nonsense', 'Silent']}
test_data = pd.DataFrame({**sample_dict, **value_dict})
# Plot stacked bar chart.
plot.stacked_bar_chart(
data=test_data,
x='Sample',
y=['Missense', 'Nonsense', 'Silent'],
ax=plot.get_axis(figsize=(14.4, 3.4)),
xticklabels=False,
sort=True,
ylabel='Number of mutations',
xlabel='Sample',
legend_size='xx-large')
```
***dohlee.plot.linear_regression***
```python
ax = plot.get_axis(preset='wide')
x = np.linspace(0, 1, 100)
y = 2 * x + 3 + np.random.normal(0, 0.3, len(x))
plot.linear_regression(x, y, ax=ax)
```
Development
Since this package is updated as needed when I'm doing my research, the development process fits well with TDD cycle.
- When you feel a need to write frequently-used research workflow as a function, write rough tests so that you can be sure that the function you've implemented just meets your need. Write the name of test function as verbose as possible!
- Run test with following commands. By default, nosetests ignores runnable files while finding test scripts. *--exe* option revokes it.
```shell
nosetests --exe --with-coverage --cover-package=dohlee
```
OR
```shell
tox -e py35,py36
```
- When sufficient progress have been made, test if the package can be published.
```shell
tox
```
- If all tests are passed, distribute the package via PyPI.
```shell
python setup.py sdist
twine upload dist/dohlee-x.x.x.tar.gz
```