def plot_distribution(n_clicks, files_content, nodes_content):
"""Plots the distribution"""
if files_content is not None and nodes_content is not None:
filestring = stringify_contents(files_content)
nodestring = stringify_contents(nodes_content)
print(nodestring)
distribution = Distribution.from_strings(nodestring, filestring)
fig = distribution.get_plotly(output_file=False)
component = dcc.Graph(id="distribution_chart", figure=fig)
return component
def test_parsing(self):
"""Test parsing functionality"""
nodetext = 'node_1 10\nnode_2 100'
parsed = parse_string(nodetext)
self.assertEqual(parsed[0], ('node_1', 10))
self.assertEqual(parsed[1], ('node_2', 100))
longtext = generate_text(100, 'nodes', upper=100, lower=10)
parsed = parse_string(longtext)
nnames, sizes = list(zip(*parsed))
sizes = np.array(sizes)
# Check text generator
self.assertTrue((sizes >= 10).all())
self.assertTrue((sizes <= 100).all())
self.assertTrue(all([name.startswith('nodes') for name in nnames]))
# Check invocation from strings
dist = Distribution.from_strings(longtext, longtext)
with tempfile.ScratchDir('.'):
with open('files.txt', 'w') as f:
f.write(longtext)
with open('nodes.txt', 'w') as f:
f.write(longtext)
dist = Distribution.from_filenames('nodes.txt', 'files.txt')
def test_large(self):
"""Test some big cases to get an idea of scaling"""
bigfiles = generate_text(1000000, 'files', upper=100)
bignodes = generate_text(1000, 'nodes')
# Takes around 1 min now
dist = Distribution.from_strings(bignodes, bigfiles)