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My personal python utility library.

Project description

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

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)

mutation_signature

dohlee.plot.boxplot

ax = plot.get_axis(preset='wide', transpose=True)
plot.boxplot(data=iris, x='species', y='sepal_length', ax=ax)

dohlee.plot.histogram

ax = plot.get_axis(preset='wide')
plot.histogram(iris.sepal_length, bins=22, xlabel='Sepal Length', ylabel='Frequency', ax=ax)

dohlee.plot.frequency

ax = plot.get_axis(preset='wide')
plot.frequency(data, ax=ax, xlabel='Your numbers', ylabel='Frequency')

dohlee.plot.tsne

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

# 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

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.
nosetests --exe --with-coverage --cover-package=dohlee

OR

tox -e py35,py36
  • When sufficient progress have been made, test if the package can be published.
tox
  • If all tests are passed, distribute the package via PyPI.
python setup.py sdist
twine upload dist/dohlee-x.x.x.tar.gz

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