def linear_regression_test():
x = np.linspace(0, 1, 100)
y = 2 * x + 3 + np.random.normal(0, 0.3, len(x))
ax = plot.get_axis(preset='large')
plot.linear_regression(x, y, ax=ax)
ax = plot.get_axis(preset='medium')
plot.linear_regression(x, y, regression=False, ax=ax)
def histogram_test():
iris = sns.load_dataset('iris')
ax = plot.get_axis(preset='wide')
plot.histogram(iris.sepal_length,
bins=22,
xlabel='Sepal Length',
ylabel='Frequency',
ax=ax)
def line_test():
fmri = sns.load_dataset('fmri')
ax = plot.get_axis(preset='wide')
plot.line(
data=fmri,
x='timepoint',
y='signal',
)
def frequency_sort_by_values_test():
data = [np.random.choice(a=range(10)) for _ in range(100)]
ax = plot.get_axis(preset='wide')
plot.frequency(
data=data,
ax=ax,
sort_by_values=True,
)
def umap_test():
iris = sns.load_dataset('iris')
ax = plot.get_axis(preset='wide')
plot.umap(
iris[['sepal_length', 'sepal_width', 'petal_length', 'petal_width']],
ax=ax,
s=5,
labels=iris['species']
)
def dimensionality_reduction_test():
iris = sns.load_dataset('iris')
ax = plot.get_axis(figsize=(8.4 * 3, 8.4))
plot.dimensionality_reduction(
data=iris[['sepal_length', 'sepal_width', 'petal_length', 'petal_width']],
labels=iris.species,
ax=ax,
xticklabels=False,
yticklabels=False,
)
def pca_with_no_xyticklabels_test():
iris = sns.load_dataset('iris')
ax = plot.get_axis(figsize=(8.4, 8.4))
plot.pca(
data=iris[['sepal_length', 'sepal_width', 'petal_length', 'petal_width']],
labels=iris.species,
s=5,
ax=ax,
xticklabels=False,
yticklabels=False,
)
def mutation_signature_test():
data = Counter()
c_contexts = [p + 'C' + n for (p, n) in itertools.product('ACGT', 'ACGT')]
t_contexts = [p + 'T' + n for (p, n) in itertools.product('ACGT', 'ACGT')]
c_alts, t_alts = 'AGT', 'ACG'
for context, alt in itertools.product(c_contexts, c_alts):
data[(context, alt)] = np.random.randint(1, 30)
for context, alt in itertools.product(t_contexts, t_alts):
data[(context, alt)] = np.random.randint(1, 30)
ax = plot.get_axis(figsize=(20.4, 3.4))
plot.mutation_signature(data, ax=ax)
plot.set_suptitle('Mutational signatures.')
def boxplot_test():
iris = sns.load_dataset('iris')
ax = plot.get_axis(preset='wide', transpose=True)
plot.boxplot(data=iris, x='species', y='sepal_length', ax=ax)
def frequency_test():
data = [np.random.choice(a=range(10)) for _ in range(100)]
ax = plot.get_axis(preset='wide')
plot.frequency(data, ax=ax, xlabel='Your numbers', ylabel='Frequency')
