def test_ordered_list_unique(self):
"""
Verify only unique items are there and the order is kept
"""
orig = [1, 5, unittest, 1, 3, 'a', 7, 7, None, 0, unittest]
self.assertEqual(data_structures.ordered_list_unique(orig),
[1, 5, unittest, 3, 'a', 7, None, 0])
def test_ordered_list_unique(self):
"""
Verify only unique items are there and the order is kept
"""
orig = [1, 5, unittest, 1, 3, 'a', 7, 7, None, 0, unittest]
self.assertEqual(data_structures.ordered_list_unique(orig),
[1, 5, unittest, 3, 'a', 7, None, 0])
def get_submodules(module_name):
"""
Get all submodules of the module.
:param module_name: Name of module to search for
:type module_name: str
:return: List of the submodules
:rtype: builtin.list
"""
module_info = loaded_module_info(module_name)
module_list = []
try:
submodules = module_info["submodules"]
except KeyError:
LOG.info("Module %s is not loaded", module_name)
else:
module_list = submodules
for module in submodules:
module_list += get_submodules(module)
return data_structures.ordered_list_unique(module_list)
def process_results(self, results, label=None):
"""
Process a list of IOzone results according to label.
:label: IOzone column label that we'll use to filter and compute
geometric mean results, in practical term either 'file_size'
or 'record_size'.
:result: A list of n x m columns with original iozone results.
:return: A list of n-? x (m-1) columns with geometric averages for
values of each label (ex, average for all file_sizes).
"""
performance = []
if label is not None:
index = _LABELS.index(label)
sizes = data_structures.ordered_list_unique(
[line[index] for line in results])
for size in sizes:
r_results = [line for line in results if line[index] == size]
performance.append(self.average_performance(r_results, size))
else:
performance.append(self.average_performance(results))
return performance
