def test_dist(self):
# dist = self.data.dist_matrix()
# assert isinstance(dist, matplotlib.figure.Figure)
copy_data = self.data.copy()
copy_data.remove_redundant(level='sample', verbose=False, inplace=True)
copy_data.dist_matrix()
copy_data.heatmap(convert_to_log=True,
index='term_name',
columns='sample_id',
figsize=(6, 14),
annotate_sig=True,
linewidths=.01,
cluster_row=True)
plt.close()
dist = self.data.dist_matrix(figsize=(3, 3), level='each')
ok_(isinstance(dist, matplotlib.figure.Figure))
plt.close()
df = load_data(
os.path.join(os.path.dirname(__file__), 'Data',
'example_apoptosis.csv'))
terms = [{'BAX'}, {'PARP4'}]
heatmap_by_terms(df.species, ['1', '2'], terms)
plt.close()
import os
from magine.data.experimental_data import load_data
file_path = os.path.join(os.path.dirname(__file__), 'Data',
'norris_et_al_2017_cisplatin_data.csv.gz')
exp_data = load_data(file_path, low_memory=False)
import os
from magine.data.experimental_data import load_data
# location of data file
file_path = os.path.join(os.path.dirname(__file__), 'Data',
'bendamustine_data.csv.gz')
"""
This loads the ExperimentalData Class instance.
You can load it into any file with the line
'from exp_data import exp_data'
"""
exp_data = load_data(file_path, low_memory=False, index_col=0)
def setUp(self):
self._dir = os.path.join(os.path.dirname(__file__), 'Data')
self.exp_data = load_data(
os.path.join(self._dir, 'example_apoptosis.csv')
)
self.out_dir = tempfile.mkdtemp()
import os
from magine.data.experimental_data import load_data
data_dir = os.path.dirname(__file__)
exp_data = load_data(
os.path.join(os.path.join(data_dir, 'Data'), 'example_apoptosis.csv'))