def setup_stack_Example_Data_A(self, name=None, fk=None, xk=None, yk=None, views=None, weights=None):
if name is None:
name = "Example Data (A)"
if fk is None:
fk = ['no_filter']
if xk is None:
xk = self.minimum
if yk is None:
yk = ['@'] + self.minimum
if views is None:
views = ['default']
if not isinstance(weights, list):
weights = [weights]
stack = Stack(name=name)
stack.add_data(
data_key=stack.name,
meta=self.example_data_A_meta,
data=self.example_data_A_data
)
for weight in weights:
stack.add_link(
data_keys=stack.name,
filters=fk,
x=xk,
y=yk,
views=QuantipyViews(views),
weights=weight
)
return stack
def setup_stack_Example_Data_A(self,
fk=None,
xk=None,
yk=None,
views=None,
weights=None):
if fk is None:
fk = 'no_filter'
if xk is None:
xk = self.minimum
if yk is None:
yk = ['@'] + self.minimum
if views is None:
views = ['default', 'cbase', 'counts', 'c%']
if not isinstance(weights, list):
weights = [weights]
self.stack = Stack(name="Example Data (A)")
self.stack.add_data(data_key=self.stack.name,
meta=self.example_data_A_meta,
data=self.example_data_A_data)
for weight in weights:
self.stack.add_link(data_keys=self.stack.name,
filters=fk,
x=xk,
y=yk,
views=QuantipyViews(views),
weights=weight)
def get_stack_Example_Data_A(self, name=None, fk=None, xk=None, yk=None, views=None, weights=None):
if name is None:
name = 'Example Data (A)'
if fk is None:
fk = ['no_filter']
if xk is None:
xk = self.minimum
if yk is None:
yk = ['@'] + self.minimum
if views is None:
views = ['default', 'counts']
if weights is None:
weights = self.weights
stack = Stack(name=name)
stack.add_data(
data_key=stack.name,
meta=self.example_data_A_meta,
data=self.example_data_A_data
)
for weight in weights:
stack.add_link(
data_keys=stack.name,
filters=fk,
x=xk,
y=yk,
views=QuantipyViews(views),
weights=weights
)
return stack
def setUp(self):
self.path = './tests/'
# self.path = ''
self.filepath = '%sengine_B_data.csv' % (self.path)
self.metapath = '%sengine_B_meta.json' % (self.path)
self.stack = Stack("StackName")
self.stack.seperator = ','
self.stack.decoding = "UTF-8"
self.data = pd.DataFrame.from_csv(self.filepath)
self.meta = load_json(self.metapath)
self.stack.add_data(data_key="Jan", meta=self.meta, data=self.data)
# self.x_names=['age', 'cost_breakfast', 'age_group', 'endtime', 'name', 'q4'],
self.x_names = ['age', 'cost_breakfast', 'age_group', 'q4']
# self._types = ['int', 'float', 'single', 'date', 'string', 'delimited set']
self.x_types = ['int', 'float', 'single', 'delimited set']
self.y_names = ['profile_gender']
def get_stack_Example_Data_A(self,
name=None,
fk=None,
xk=None,
yk=None,
views=None,
weights=None):
if name is None:
name = 'Example Data (A)'
if fk is None:
fk = ['no_filter']
if xk is None:
xk = self.minimum
if yk is None:
yk = ['@'] + self.minimum
if views is None:
views = ['default', 'counts']
if weights is None:
weights = self.weights
stack = Stack(name=name)
stack.add_data(data_key=stack.name,
meta=self.example_data_A_meta,
data=self.example_data_A_data)
for weight in weights:
stack.add_link(data_keys=stack.name,
filters=fk,
x=xk,
y=yk,
views=QuantipyViews(views),
weights=weights)
return stack
def setUp(self):
self.path = './tests/'
# self.path = ''
self.filepath = '%sengine_B_data.csv' % (self.path)
self.metapath = '%sengine_B_meta.json' % (self.path)
self.stack = Stack("StackName")
self.stack.seperator = ','
self.stack.decoding = "UTF-8"
self.data = pd.DataFrame.from_csv(self.filepath)
self.meta = load_json(self.metapath)
self.stack.add_data(data_key="Jan", meta=self.meta, data=self.data)
# self.x_names=['age', 'cost_breakfast', 'age_group', 'endtime', 'name', 'q4'],
self.x_names = ['age', 'cost_breakfast', 'age_group', 'q4']
# self._types = ['int', 'float', 'single', 'date', 'string', 'delimited set']
self.x_types = ['int', 'float', 'single', 'delimited set']
self.y_names = ['profile_gender']
class TestChainObject(unittest.TestCase):
def setUp(self):
self.path = './tests/'
self.path_chain = './temp.chain'.format(self.path)
# self.path = ''
project_name = 'Example Data (A)'
# Load Example Data (A) data and meta into self
name_data = '%s.csv' % (project_name)
path_data = '%s%s' % (self.path, name_data)
self.example_data_A_data = pd.DataFrame.from_csv(path_data)
name_meta = '%s.json' % (project_name)
path_meta = '%s%s' % (self.path, name_meta)
self.example_data_A_meta = load_json(path_meta)
# The minimum list of variables required to populate a stack with all single*delimited set variations
self.minimum = ['q2b', 'Wave', 'q2', 'q3', 'q5_1']
self.setup_stack_Example_Data_A()
self.setup_chains_Example_Data_A()
def test_save_chain(self):
self.setup_chains_Example_Data_A()
for chain in self.chains:
# Create a dictionary with the attribute structure of the chain
chain_attributes = chain.__dict__
chain_described = chain.describe()
# Save and then load a copy of the chain
chain.save(path=self.path_chain)
loaded_chain = Chain.load(self.path_chain)
# Ensure that we are not comparing the same variable (in memory)
self.assertNotEqual(id(chain), id(loaded_chain))
# Create a dictionary with the attribute structure of the chain
loaded_chain_attributes = loaded_chain.__dict__
loaded_chain_described = loaded_chain.describe()
# Confirm that the chains contain the same views
sort_order = ['data', 'filter', 'x', 'y', 'view']
actual = chain_described.sort(sort_order).values.tolist()
expected = loaded_chain_described.sort(sort_order).values.tolist()
self.assertSequenceEqual(actual, expected)
# Make sure that this is working by altering the loaded_stack_attributes
# and comparing the result. (It should fail)
# Change a 'value' in the dict
loaded_chain_attributes['name'] = 'SomeOtherName'
with self.assertRaises(AssertionError):
self.assertEqual(chain_attributes, loaded_chain_attributes)
# reset the value
loaded_chain_attributes['name'] = chain_attributes['name']
self.assertEqual(chain_attributes, loaded_chain_attributes)
# Change a 'key' in the dict
del loaded_chain_attributes['name']
loaded_chain_attributes['new_name'] = chain_attributes['name']
with self.assertRaises(AssertionError):
self.assertEqual(chain_attributes, loaded_chain_attributes)
# reset the value
del loaded_chain_attributes['new_name']
loaded_chain_attributes['name'] = chain_attributes['name']
self.assertEqual(chain_attributes, loaded_chain_attributes)
# Remove a key/value pair
del loaded_chain_attributes['name']
with self.assertRaises(AssertionError):
self.assertEqual(chain_attributes, loaded_chain_attributes)
# Cleanup
if os.path.exists('./tests/{0}.chain'.format(chain.name)):
os.remove('./tests/{0}.chain'.format(chain.name))
def test_auto_orientation(self):
fk = 'no_filter'
xk = self.minimum
yk = ['@'] + self.minimum
views = ['cbase', 'counts', 'c%']
# If multiple x and y keys are given without orient_on
# x-orientation chains are assumed.
chain = self.stack.get_chain(name='y',
data_keys=self.stack.name,
filters=fk,
x=xk,
y=yk,
views=views)
self.assertTrue(chain.orientation == 'x')
def test_lazy_name(self):
fk = 'no_filter'
xk = self.minimum
yk = ['@'] + self.minimum
views = ['cbase', 'counts', 'c%']
# get chain but do not name - y orientation
chain_y = self.stack.get_chain(data_keys=self.stack.name,
filters=fk,
x=xk,
y=yk[0],
views=views)
# get chain but do not name - x orientation
chain_x = self.stack.get_chain(data_keys=self.stack.name,
filters=fk,
x=xk[0],
y=yk,
views=views)
# check lazy_name is working as it should be
self.assertEqual(chain_y.name,
'[email protected]_1.cbase.counts.c%')
self.assertEqual(chain_x.name,
'[email protected]_1.cbase.counts.c%')
def test_dervie_attributes(self):
# check chain attributes
self.assertEqual(self.chains[0].name, '@')
self.assertEqual(self.chains[0].orientation, 'y')
self.assertEqual(self.chains[0].source_name, '@')
self.assertEqual(self.chains[0].len_of_axis, 5)
self.assertEqual(self.chains[0].content_of_axis,
['q2b', 'Wave', 'q2', 'q3', 'q5_1'])
self.assertEqual(self.chains[0].views,
['x|f|x:|||cbase', 'x|f|:|||counts', 'x|f|:|y||c%'])
self.assertEqual(self.chains[0].data_key, 'Example Data (A)')
self.assertEqual(self.chains[0].filter, 'no_filter')
self.assertEqual(self.chains[0].source_type, None)
self.assertEqual(self.chains[-1].name, 'q5_1')
self.assertEqual(self.chains[-1].orientation, 'x')
self.assertEqual(self.chains[-1].source_name, 'q5_1')
self.assertEqual(self.chains[-1].len_of_axis, 6)
self.assertEqual(self.chains[-1].content_of_axis,
['@', 'q2b', 'Wave', 'q2', 'q3', 'q5_1'])
self.assertEqual(self.chains[-1].views,
['x|f|x:|||cbase', 'x|f|:|||counts', 'x|f|:|y||c%'])
self.assertEqual(self.chains[-1].data_key, 'Example Data (A)')
self.assertEqual(self.chains[-1].filter, 'no_filter')
self.assertEqual(self.chains[-1].source_type, None)
def test_describe(self):
fk = 'no_filter'
for chain in self.chains:
chain_described = chain.describe()
#test describe() returns a dataframe
self.assertIsInstance(chain_described, pd.DataFrame)
#test descibe() returns the expected dataframe - *no args*
if chain.orientation == 'y':
keys = chain[self.stack.name][fk].keys()
views = chain[self.stack.name][fk][keys[0]][
chain.source_name].keys()
data = [self.stack.name] * (len(keys) * len(views))
filters = [fk] * (len(keys) * len(views))
x = []
for key in keys:
x.extend([key] * len(views))
y = [chain.source_name] * (len(keys) * len(views))
view = [v for v in views] * len(keys)
ones = [1] * (len(keys) * len(views))
df = pd.DataFrame({
'data': data,
'filter': filters,
'x': x,
'y': y,
'view': view,
'#': ones
})
df = df[chain_described.columns.tolist()]
assert_frame_equal(chain_described, df)
elif chain.orientation == 'x':
keys = chain[self.stack.name][fk][chain.source_name].keys()
views = chain[self.stack.name][fk][chain.source_name][
keys[0]].keys()
data = [self.stack.name] * (len(keys) * len(views))
filters = [fk] * (len(keys) * len(views))
y = []
for key in keys:
y.extend([key] * len(views))
x = [chain.source_name] * (len(keys) * len(views))
view = [v for v in views] * len(keys)
ones = [1] * (len(keys) * len(views))
df = pd.DataFrame({
'data': data,
'filter': filters,
'x': x,
'y': y,
'view': view,
'#': ones
})
df = df[chain_described.columns.tolist()]
assert_frame_equal(chain_described, df)
@classmethod
def tearDownClass(self):
self.stack = Stack("StackName")
filepath = './tests/' + self.stack.name + '.stack'
if os.path.exists(filepath):
os.remove(filepath)
def is_empty(self, any_structure):
if any_structure:
#print('Structure is not empty.')
return False
else:
#print('Structure is empty.')
return True
def create_key_stack(self, branch_pos="data"):
""" Creates a dictionary that has the structure of the keys in the Stack
It is used to loop through the stack without affecting it.
"""
key_stack = {}
for data_key in self.stack:
key_stack[data_key] = {}
for the_filter in self.stack[data_key][branch_pos]:
key_stack[data_key][the_filter] = {}
for x in self.stack[data_key][branch_pos][the_filter]:
key_stack[data_key][the_filter][x] = []
for y in self.stack[data_key][branch_pos][the_filter][x]:
link = self.stack[data_key][branch_pos][the_filter][x][
y]
if not isinstance(link, Link):
continue
key_stack[data_key][the_filter][x].append(y)
return key_stack
def setup_stack_Example_Data_A(self,
fk=None,
xk=None,
yk=None,
views=None,
weights=None):
if fk is None:
fk = 'no_filter'
if xk is None:
xk = self.minimum
if yk is None:
yk = ['@'] + self.minimum
if views is None:
views = ['default', 'cbase', 'counts', 'c%']
if not isinstance(weights, list):
weights = [weights]
self.stack = Stack(name="Example Data (A)")
self.stack.add_data(data_key=self.stack.name,
meta=self.example_data_A_meta,
data=self.example_data_A_data)
for weight in weights:
self.stack.add_link(data_keys=self.stack.name,
filters=fk,
x=xk,
y=yk,
views=QuantipyViews(views),
weights=weight)
def setup_chains_Example_Data_A(self,
fk=None,
xk=None,
yk=None,
views=None,
orient_on=None):
if fk is None:
fk = 'no_filter'
if xk is None:
xk = self.minimum
if yk is None:
yk = ['@'] + self.minimum
if views is None:
views = ['x|f|x:|||cbase', 'x|f|:|||counts', 'x|f|:|y||c%']
self.chains = []
for y in yk:
self.chains.append(
self.stack.get_chain(name=y,
data_keys=self.stack.name,
filters='no_filter',
x=xk,
y=y,
views=views))
for x in xk:
self.chains.append(
self.stack.get_chain(name=x,
data_keys=self.stack.name,
filters='no_filter',
x=x,
y=yk,
views=views))
def tearDownClass(self):
self.stack = Stack("StackName")
filepath ='./tests/'+self.stack.name+'.stack'
if os.path.exists(filepath):
os.remove(filepath)
class TestLinkObject(unittest.TestCase):
# stack.add_link(x='q1', y=y, views=mean_views.subset('m1to6'), weights=weight)
def setUp(self):
self.path = './tests/'
# self.path = ''
project_name = 'Example Data (A)'
# Load Example Data (A) data and meta into self
name_data = '%s.csv' % (project_name)
path_data = '%s%s' % (self.path, name_data)
self.example_data_A_data = pd.DataFrame.from_csv(path_data)
name_meta = '%s.json' % (project_name)
path_meta = '%s%s' % (self.path, name_meta)
self.example_data_A_meta = load_json(path_meta)
# The minimum list of variables required to populate a stack with all single*delimited set variations
self.minimum = ['q2b', 'Wave', 'q2', 'q3', 'q5_1']
self.setup_stack_Example_Data_A()
def test_link_is_a_subclassed_dict(self):
dk = self.stack.name
fk = 'no_filter'
xk = self.minimum
yk = ['@'] + self.minimum
for x in xk:
for y in yk:
link = self.stack[dk][fk][x][y]
self.assertIsInstance(link, dict)
self.assertIsInstance(link, Link)
def test_link_behaves_like_a_dict(self):
dk = self.stack.name
fk = 'no_filter'
xk = self.minimum
yk = ['@'] + self.minimum
key = "some_key_name"
value = "some_value"
for x in xk:
for y in yk:
link = self.stack[dk][fk][x][y]
link[key] = value
self.assertIn(
key,
link.keys(),
msg="Link should have key {data_key}, but has {link_keys}".format(
data_key=key,
link_keys=link.keys()
)
)
def test_get_meta(self):
dk = self.stack.name
fk = 'no_filter'
xk = self.minimum
yk = ['@'] + self.minimum
#test returned meta against stack meta
for x in xk:
for y in yk:
link = self.stack[dk][fk][x][y]
self.assertEqual(link.get_meta(), self.stack[dk].meta)
def test_get_data(self):
dk = self.stack.name
fk = 'no_filter'
xk = self.minimum
yk = ['@'] + self.minimum
stack_data = self.stack[dk][fk].data
#test returned data against stack data
for x in xk:
for y in yk:
link_data = self.stack[dk][fk][x][y].get_data()
self.assertTrue(link_data is stack_data)
@classmethod
def tearDownClass(self):
self.stack = Stack("StackName")
filepath ='./tests/'+self.stack.name+'.stack'
if os.path.exists(filepath):
os.remove(filepath)
def is_empty(self, any_structure):
if any_structure:
#print('Structure is not empty.')
return False
else:
#print('Structure is empty.')
return True
def create_key_stack(self, branch_pos="data"):
""" Creates a dictionary that has the structure of the keys in the Stack
It is used to loop through the stack without affecting it.
"""
key_stack = {}
for data_key in self.stack:
key_stack[data_key] = {}
for the_filter in self.stack[data_key][branch_pos]:
key_stack[data_key][the_filter] = {}
for x in self.stack[data_key][branch_pos][the_filter]:
key_stack[data_key][the_filter][x] = []
for y in self.stack[data_key][branch_pos][the_filter][x]:
link = self.stack[data_key][branch_pos][the_filter][x][y]
if not isinstance(link, Link):
continue
key_stack[data_key][the_filter][x].append(y)
return key_stack
def setup_stack_Example_Data_A(self, fk=None, xk=None, yk=None, views=None, weights=None):
if fk is None:
fk = [
'no_filter',
'Wave == 1'
]
if xk is None:
xk = self.minimum
if yk is None:
yk = ['@'] + self.minimum
if views is None:
views = ['default']
if not isinstance(weights, list):
weights = [weights]
self.stack = Stack(name="Example Data (A)")
self.stack.add_data(
data_key=self.stack.name,
meta=self.example_data_A_meta,
data=self.example_data_A_data
)
for weight in weights:
self.stack.add_link(
data_keys=self.stack.name,
filters=fk,
x=xk,
y=yk,
views=QuantipyViews(views),
weights=weight
)
def get_stack(self, meta, data, xks, yks, views, weights):
stack = Stack('test')
stack.add_data('test', data, meta)
stack.add_link(x=xks, y=yks, views=views, weights=weights)
# Add two basic net
net_views = ViewMapper(
template={
'method': QuantipyViews().frequency,
'kwargs': {
'iterators': {
'rel_to': [None, 'y']
}
}
})
net_views.add_method(name='Net 1-3',
kwargs={
'logic': [1, 2, 3],
'axis': 'x',
'text': {
'en-GB': '1-3'
}
})
net_views.add_method(name='Net 4-6',
kwargs={
'logic': [4, 5, 6],
'axis': 'x',
'text': {
'en-GB': '4-6'
}
})
stack.add_link(x=xks, y=yks, views=net_views, weights=weights)
# Add block net
net_views.add_method(name='Block net',
kwargs={
'logic': [{
'bn1': [1, 2]
}, {
'bn2': [2, 3]
}, {
'bn3': [1, 3]
}],
'axis':
'x'
})
stack.add_link(x=xks,
y=yks,
views=net_views.subset(['Block net']),
weights=weights)
# Add NPS
## TO DO
# Add standard deviation
desc_views = ViewMapper(
template={
'method': QuantipyViews().descriptives,
'kwargs': {
'axis': 'x',
'iterators': {
'stats': ['mean', 'median', 'stddev']
}
}
})
desc_views.add_method(name='descriptives')
stack.add_link(x=xks, y=yks, views=desc_views, weights=weights)
# Add tests
test_views = ViewMapper(
template={
'method': QuantipyViews().coltests,
'kwargs': {
'mimic': 'askia',
'iterators': {
'metric': ['props', 'means'],
'level': ['low', 'mid', 'high']
}
}
})
test_views.add_method('askia tests')
stack.add_link(x=xks, y=yks, views=test_views, weights=weights)
return stack
class TestChainObject(unittest.TestCase):
def setUp(self):
self.path = './tests/'
# self.path = ''
project_name = 'Example Data (A)'
# Load Example Data (A) data and meta into self
name_data = '%s.csv' % (project_name)
path_data = '%s%s' % (self.path, name_data)
self.example_data_A_data = pd.DataFrame.from_csv(path_data)
name_meta = '%s.json' % (project_name)
path_meta = '%s%s' % (self.path, name_meta)
self.example_data_A_meta = load_json(path_meta)
# The minimum list of variables required to populate a stack with all single*delimited set variations
self.minimum = ['q2b', 'Wave', 'q2', 'q3', 'q5_1']
self.setup_stack_Example_Data_A()
self.setup_chains_Example_Data_A()
def test_save_chain(self):
self.setup_chains_Example_Data_A()
for chain in self.chains:
chain.save(path=self.path)
loaded_chain = Chain.load('%s%s.chain' % (self.path, chain.name))
# Create a dictionary with the attribute structure of the chain
chain_attributes = test_helper.create_attribute_dict(chain)
# Create a dictionary with the attribute structure of the chain
loaded_chain_attributes = test_helper.create_attribute_dict(loaded_chain)
# Ensure that we are not comparing the same variable (in memory)
self.assertNotEqual(id(chain), id(loaded_chain))
# Make sure that this is working by altering the loaded_stack_attributes
# and comparing the result. (It should fail)
# Change a 'value' in the dict
loaded_chain_attributes['__dict__']['name'] = 'SomeOtherName'
with self.assertRaises(AssertionError):
self.assertEqual(chain_attributes, loaded_chain_attributes)
# reset the value
loaded_chain_attributes['__dict__']['name'] = chain_attributes['__dict__']['name']
self.assertEqual(chain_attributes, loaded_chain_attributes)
# Change a 'key' in the dict
del loaded_chain_attributes['__dict__']['name']
loaded_chain_attributes['__dict__']['new_name'] = chain_attributes['__dict__']['name']
with self.assertRaises(AssertionError):
self.assertEqual(chain_attributes, loaded_chain_attributes)
# reset the value
del loaded_chain_attributes['__dict__']['new_name']
loaded_chain_attributes['__dict__']['name'] = chain_attributes['__dict__']['name']
self.assertEqual(chain_attributes, loaded_chain_attributes)
# Remove a key/value pair
del loaded_chain_attributes['__dict__']['name']
with self.assertRaises(AssertionError):
self.assertEqual(chain_attributes, loaded_chain_attributes)
# Cleanup
if os.path.exists('./tests/{0}.chain'.format(chain.name)):
os.remove('./tests/{0}.chain'.format(chain.name))
def test_validate_x_y_combination(self):
fk = 'no_filter'
xk = self.minimum
yk = ['@'] + self.minimum
views = ['cbase', 'counts', 'c%']
# check the correct error message is returned, irrespective of orientation...
# error #1
expected_message = "If the number of keys for both x and y are greater than 1, whether or not you have specified the x and y values, orient_on must be either 'x' or 'y'."
with self.assertRaises(ValueError) as error_message:
_ = self.stack.get_chain(
name='y',
data_keys=self.stack.name,
filters=fk,
x=xk,
y=yk,
views=views,
post_process=True
)
self.assertEqual(error_message.exception[0], expected_message)
def test_lazy_name(self):
fk = 'no_filter'
xk = self.minimum
yk = ['@'] + self.minimum
views = ['cbase', 'counts', 'c%']
# get chain but do not name - y orientation
chain_y = self.stack.get_chain(
data_keys=self.stack.name,
filters=fk,
x=xk,
y=yk[0],
views=views,
post_process=False
)
# get chain but do not name - x orientation
chain_x = self.stack.get_chain(
data_keys=self.stack.name,
filters=fk,
x=xk[0],
y=yk,
views=views,
post_process=False
)
# check lazy_name is working as it should be
self.assertEqual(chain_y.name, '[email protected]_1.cbase.counts.c%')
self.assertEqual(chain_x.name, '[email protected]_1.cbase.counts.c%')
def test_dervie_attributes(self):
# check chain attributes
self.assertEqual(self.chains[0].name, '@')
self.assertEqual(self.chains[0].orientation, 'y')
self.assertEqual(self.chains[0].source_name, '@')
self.assertEqual(self.chains[0].len_of_axis, 5)
self.assertEqual(self.chains[0].content_of_axis, ['q2b', 'Wave', 'q2', 'q3', 'q5_1'])
self.assertEqual(self.chains[0].views, ['x|frequency|x:y|||cbase', 'x|frequency||||counts', 'x|frequency||y||c%'])
self.assertEqual(self.chains[0].data_key, 'Example Data (A)')
self.assertEqual(self.chains[0].filter, 'no_filter')
self.assertEqual(self.chains[0].source_type, None)
self.assertEqual(self.chains[-1].name, 'q5_1')
self.assertEqual(self.chains[-1].orientation, 'x')
self.assertEqual(self.chains[-1].source_name, 'q5_1')
self.assertEqual(self.chains[-1].len_of_axis, 6)
self.assertEqual(self.chains[-1].content_of_axis, ['@', 'q2b', 'Wave', 'q2', 'q3', 'q5_1'])
self.assertEqual(self.chains[-1].views, ['x|frequency|x:y|||cbase', 'x|frequency||||counts', 'x|frequency||y||c%'])
self.assertEqual(self.chains[-1].data_key, 'Example Data (A)')
self.assertEqual(self.chains[-1].filter, 'no_filter')
self.assertEqual(self.chains[-1].source_type, None)
def test_post_process_shapes(self):
# check chain attributes after post_processing
self.assertEqual(self.chains[0].x_new_order, [[], [], [], [], [], [], [], [], [], [], [], [], [], [], []])
self.assertEqual(self.chains[0].x_hidden_codes, [[], [], [], [], [], [], [], [], [], [], [], [], [], [], []])
self.assertEqual(self.chains[0].y_new_order, None)
self.assertEqual(self.chains[0].y_hidden_codes, None)
self.assertEqual(self.chains[0].props_tests, [])
self.assertEqual(self.chains[0].props_tests_levels, [])
self.assertEqual(self.chains[0].has_props_tests, False)
self.assertEqual(self.chains[0].means_tests, [])
self.assertEqual(self.chains[0].means_tests_levels, [])
self.assertEqual(self.chains[0].has_means_tests, False)
self.assertEqual(self.chains[0].view_sizes, [[(1, 1), (3, 1), (3, 1)], [(1, 1), (5, 1), (5, 1)], [(1, 1), (8, 1), (8, 1)], [(1, 1), (9, 1), (9, 1)], [(1, 1), (7, 1), (7, 1)]])
self.assertEqual(self.chains[0].view_lengths, [[1, 3, 3], [1, 5, 5], [1, 8, 8], [1, 9, 9], [1, 7, 7]])
self.assertEqual(self.chains[0].source_length, 1)
self.assertEqual(self.chains[-1].x_new_order, [[], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], []])
self.assertEqual(self.chains[-1].x_hidden_codes, [[], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], []])
self.assertEqual(self.chains[-1].y_new_order, None)
self.assertEqual(self.chains[-1].y_hidden_codes, None)
self.assertEqual(self.chains[-1].props_tests, [])
self.assertEqual(self.chains[-1].props_tests_levels, [])
self.assertEqual(self.chains[-1].has_props_tests, False)
self.assertEqual(self.chains[-1].means_tests, [])
self.assertEqual(self.chains[-1].means_tests_levels, [])
self.assertEqual(self.chains[-1].has_means_tests, False)
self.assertEqual(self.chains[-1].view_sizes, [[(1, 1), (7, 1), (7, 1)], [(1, 3), (7, 3), (7, 3)], [(1, 5), (7, 5), (7, 5)], [(1, 8), (7, 8), (7, 8)], [(1, 9), (7, 9), (7, 9)], [(1, 7), (7, 7), (7, 7)]])
self.assertEqual(self.chains[-1].view_lengths, [[1, 7, 7], [1, 7, 7], [1, 7, 7], [1, 7, 7], [1, 7, 7], [1, 7, 7]])
self.assertEqual(self.chains[-1].source_length, 9)
def test_describe(self):
fk = 'no_filter'
for chain in self.chains:
chain_described = chain.describe()
#test describe() returns a dataframe
self.assertIsInstance(chain_described, pd.DataFrame)
#test descibe() returns the expected dataframe - *no args*
if chain.orientation == 'y':
keys = chain[self.stack.name][fk].keys()
views = chain[self.stack.name][fk][keys[0]][chain.source_name].keys()
data = [self.stack.name]*(len(keys)*len(views))
filters = [fk]*(len(keys)*len(views))
x = []
for key in keys:
x.extend([key]*len(views))
y = [chain.source_name]*(len(keys)*len(views))
view = [v for v in views]*len(keys)
ones = [1]*(len(keys)*len(views))
df = pd.DataFrame({'data': data,
'filter': filters,
'x': x,
'y': y,
'view': view,
'#': ones})
df = df[chain_described.columns.tolist()]
assert_frame_equal(chain_described, df)
elif chain.orientation == 'x':
keys = chain[self.stack.name][fk][chain.source_name].keys()
views = chain[self.stack.name][fk][chain.source_name][keys[0]].keys()
data = [self.stack.name]*(len(keys)*len(views))
filters = [fk]*(len(keys)*len(views))
y = []
for key in keys:
y.extend([key]*len(views))
x = [chain.source_name]*(len(keys)*len(views))
view = [v for v in views]*len(keys)
ones = [1]*(len(keys)*len(views))
df = pd.DataFrame({'data': data,
'filter': filters,
'x': x,
'y': y,
'view': view,
'#': ones})
df = df[chain_described.columns.tolist()]
assert_frame_equal(chain_described, df)
@classmethod
def tearDownClass(self):
self.stack = Stack("StackName")
filepath ='./tests/'+self.stack.name+'.stack'
if os.path.exists(filepath):
os.remove(filepath)
def is_empty(self, any_structure):
if any_structure:
#print('Structure is not empty.')
return False
else:
#print('Structure is empty.')
return True
def create_key_stack(self, branch_pos="data"):
""" Creates a dictionary that has the structure of the keys in the Stack
It is used to loop through the stack without affecting it.
"""
key_stack = {}
for data_key in self.stack:
key_stack[data_key] = {}
for the_filter in self.stack[data_key][branch_pos]:
key_stack[data_key][the_filter] = {}
for x in self.stack[data_key][branch_pos][the_filter]:
key_stack[data_key][the_filter][x] = []
for y in self.stack[data_key][branch_pos][the_filter][x]:
link = self.stack[data_key][branch_pos][the_filter][x][y]
if not isinstance(link, Link):
continue
key_stack[data_key][the_filter][x].append(y)
return key_stack
def setup_stack_Example_Data_A(self, fk=None, xk=None, yk=None, views=None, weights=None):
if fk is None:
fk = 'no_filter'
if xk is None:
xk = self.minimum
if yk is None:
yk = ['@'] + self.minimum
if views is None:
views = ['default', 'cbase', 'counts', 'c%']
if not isinstance(weights, list):
weights = [weights]
self.stack = Stack(name="Example Data (A)")
self.stack.add_data(
data_key=self.stack.name,
meta=self.example_data_A_meta,
data=self.example_data_A_data
)
for weight in weights:
self.stack.add_link(
data_keys=self.stack.name,
filters=fk,
x=xk,
y=yk,
views=QuantipyViews(views),
weights=weight
)
def setup_chains_Example_Data_A(self, fk=None, xk=None, yk=None, views=None, orient_on=None):
if fk is None:
fk = 'no_filter'
if xk is None:
xk = self.minimum
if yk is None:
yk = ['@'] + self.minimum
if views is None:
views = [
'x|frequency|x:y|||cbase',
'x|frequency||||counts',
'x|frequency||y||c%'
]
self.chains = []
for y in yk:
self.chains.append(
self.stack.get_chain(
name=y,
data_keys=self.stack.name,
filters='no_filter',
x=xk,
y=y,
views=views,
post_process=True
)
)
for x in xk:
self.chains.append(
self.stack.get_chain(
name=x,
data_keys=self.stack.name,
filters='no_filter',
x=x,
y=yk,
views=views,
post_process=True
)
)
class TestChainObject(unittest.TestCase):
def setUp(self):
self.path = './tests/'
# self.path = ''
project_name = 'Example Data (A)'
# Load Example Data (A) data and meta into self
name_data = '%s.csv' % (project_name)
path_data = '%s%s' % (self.path, name_data)
self.example_data_A_data = pd.DataFrame.from_csv(path_data)
name_meta = '%s.json' % (project_name)
path_meta = '%s%s' % (self.path, name_meta)
self.example_data_A_meta = load_json(path_meta)
# The minimum list of variables required to populate a stack with all single*delimited set variations
self.minimum = ['q2b', 'Wave', 'q2', 'q3', 'q5_1']
self.setup_stack_Example_Data_A()
self.setup_chains_Example_Data_A()
def test_save_chain(self):
self.setup_chains_Example_Data_A()
for chain in self.chains:
chain.save(path=self.path)
loaded_chain = Chain.load('%s%s.chain' % (self.path, chain.name))
# Create a dictionary with the attribute structure of the chain
chain_attributes = test_helper.create_attribute_dict(chain)
# Create a dictionary with the attribute structure of the chain
loaded_chain_attributes = test_helper.create_attribute_dict(
loaded_chain)
# Ensure that we are not comparing the same variable (in memory)
self.assertNotEqual(id(chain), id(loaded_chain))
# Make sure that this is working by altering the loaded_stack_attributes
# and comparing the result. (It should fail)
# Change a 'value' in the dict
loaded_chain_attributes['__dict__']['name'] = 'SomeOtherName'
with self.assertRaises(AssertionError):
self.assertEqual(chain_attributes, loaded_chain_attributes)
# reset the value
loaded_chain_attributes['__dict__']['name'] = chain_attributes[
'__dict__']['name']
self.assertEqual(chain_attributes, loaded_chain_attributes)
# Change a 'key' in the dict
del loaded_chain_attributes['__dict__']['name']
loaded_chain_attributes['__dict__']['new_name'] = chain_attributes[
'__dict__']['name']
with self.assertRaises(AssertionError):
self.assertEqual(chain_attributes, loaded_chain_attributes)
# reset the value
del loaded_chain_attributes['__dict__']['new_name']
loaded_chain_attributes['__dict__']['name'] = chain_attributes[
'__dict__']['name']
self.assertEqual(chain_attributes, loaded_chain_attributes)
# Remove a key/value pair
del loaded_chain_attributes['__dict__']['name']
with self.assertRaises(AssertionError):
self.assertEqual(chain_attributes, loaded_chain_attributes)
# Cleanup
if os.path.exists('./tests/{0}.chain'.format(chain.name)):
os.remove('./tests/{0}.chain'.format(chain.name))
def test_validate_x_y_combination(self):
fk = 'no_filter'
xk = self.minimum
yk = ['@'] + self.minimum
views = ['cbase', 'counts', 'c%']
# check the correct error message is returned, irrespective of orientation...
# error #1
expected_message = "If the number of keys for both x and y are greater than 1, whether or not you have specified the x and y values, orient_on must be either 'x' or 'y'."
with self.assertRaises(ValueError) as error_message:
_ = self.stack.get_chain(name='y',
data_keys=self.stack.name,
filters=fk,
x=xk,
y=yk,
views=views,
post_process=True)
self.assertEqual(error_message.exception[0], expected_message)
def test_lazy_name(self):
fk = 'no_filter'
xk = self.minimum
yk = ['@'] + self.minimum
views = ['cbase', 'counts', 'c%']
# get chain but do not name - y orientation
chain_y = self.stack.get_chain(data_keys=self.stack.name,
filters=fk,
x=xk,
y=yk[0],
views=views,
post_process=False)
# get chain but do not name - x orientation
chain_x = self.stack.get_chain(data_keys=self.stack.name,
filters=fk,
x=xk[0],
y=yk,
views=views,
post_process=False)
# check lazy_name is working as it should be
self.assertEqual(chain_y.name,
'[email protected]_1.cbase.counts.c%')
self.assertEqual(chain_x.name,
'[email protected]_1.cbase.counts.c%')
def test_dervie_attributes(self):
# check chain attributes
self.assertEqual(self.chains[0].name, '@')
self.assertEqual(self.chains[0].orientation, 'y')
self.assertEqual(self.chains[0].source_name, '@')
self.assertEqual(self.chains[0].len_of_axis, 5)
self.assertEqual(self.chains[0].content_of_axis,
['q2b', 'Wave', 'q2', 'q3', 'q5_1'])
self.assertEqual(self.chains[0].views, [
'x|frequency|x:y|||cbase', 'x|frequency||||counts',
'x|frequency||y||c%'
])
self.assertEqual(self.chains[0].data_key, 'Example Data (A)')
self.assertEqual(self.chains[0].filter, 'no_filter')
self.assertEqual(self.chains[0].source_type, None)
self.assertEqual(self.chains[-1].name, 'q5_1')
self.assertEqual(self.chains[-1].orientation, 'x')
self.assertEqual(self.chains[-1].source_name, 'q5_1')
self.assertEqual(self.chains[-1].len_of_axis, 6)
self.assertEqual(self.chains[-1].content_of_axis,
['@', 'q2b', 'Wave', 'q2', 'q3', 'q5_1'])
self.assertEqual(self.chains[-1].views, [
'x|frequency|x:y|||cbase', 'x|frequency||||counts',
'x|frequency||y||c%'
])
self.assertEqual(self.chains[-1].data_key, 'Example Data (A)')
self.assertEqual(self.chains[-1].filter, 'no_filter')
self.assertEqual(self.chains[-1].source_type, None)
def test_post_process_shapes(self):
# check chain attributes after post_processing
self.assertEqual(
self.chains[0].x_new_order,
[[], [], [], [], [], [], [], [], [], [], [], [], [], [], []])
self.assertEqual(
self.chains[0].x_hidden_codes,
[[], [], [], [], [], [], [], [], [], [], [], [], [], [], []])
self.assertEqual(self.chains[0].y_new_order, None)
self.assertEqual(self.chains[0].y_hidden_codes, None)
self.assertEqual(self.chains[0].props_tests, [])
self.assertEqual(self.chains[0].props_tests_levels, [])
self.assertEqual(self.chains[0].has_props_tests, False)
self.assertEqual(self.chains[0].means_tests, [])
self.assertEqual(self.chains[0].means_tests_levels, [])
self.assertEqual(self.chains[0].has_means_tests, False)
self.assertEqual(
self.chains[0].view_sizes,
[[(1, 1), (3, 1),
(3, 1)], [(1, 1), (5, 1),
(5, 1)], [(1, 1), (8, 1),
(8, 1)], [(1, 1), (9, 1),
(9, 1)], [(1, 1), (7, 1), (7, 1)]])
self.assertEqual(
self.chains[0].view_lengths,
[[1, 3, 3], [1, 5, 5], [1, 8, 8], [1, 9, 9], [1, 7, 7]])
self.assertEqual(self.chains[0].source_length, 1)
self.assertEqual(self.chains[-1].x_new_order,
[[], [], [], [], [], [], [], [], [], [], [], [], [],
[], [], [], [], []])
self.assertEqual(self.chains[-1].x_hidden_codes,
[[], [], [], [], [], [], [], [], [], [], [], [], [],
[], [], [], [], []])
self.assertEqual(self.chains[-1].y_new_order, None)
self.assertEqual(self.chains[-1].y_hidden_codes, None)
self.assertEqual(self.chains[-1].props_tests, [])
self.assertEqual(self.chains[-1].props_tests_levels, [])
self.assertEqual(self.chains[-1].has_props_tests, False)
self.assertEqual(self.chains[-1].means_tests, [])
self.assertEqual(self.chains[-1].means_tests_levels, [])
self.assertEqual(self.chains[-1].has_means_tests, False)
self.assertEqual(self.chains[-1].view_sizes,
[[(1, 1), (7, 1), (7, 1)], [(1, 3), (7, 3), (7, 3)],
[(1, 5), (7, 5),
(7, 5)], [(1, 8), (7, 8),
(7, 8)], [(1, 9), (7, 9),
(7, 9)], [(1, 7), (7, 7),
(7, 7)]])
self.assertEqual(
self.chains[-1].view_lengths,
[[1, 7, 7], [1, 7, 7], [1, 7, 7], [1, 7, 7], [1, 7, 7], [1, 7, 7]])
self.assertEqual(self.chains[-1].source_length, 9)
def test_describe(self):
fk = 'no_filter'
for chain in self.chains:
chain_described = chain.describe()
#test describe() returns a dataframe
self.assertIsInstance(chain_described, pd.DataFrame)
#test descibe() returns the expected dataframe - *no args*
if chain.orientation == 'y':
keys = chain[self.stack.name][fk].keys()
views = chain[self.stack.name][fk][keys[0]][
chain.source_name].keys()
data = [self.stack.name] * (len(keys) * len(views))
filters = [fk] * (len(keys) * len(views))
x = []
for key in keys:
x.extend([key] * len(views))
y = [chain.source_name] * (len(keys) * len(views))
view = [v for v in views] * len(keys)
ones = [1] * (len(keys) * len(views))
df = pd.DataFrame({
'data': data,
'filter': filters,
'x': x,
'y': y,
'view': view,
'#': ones
})
df = df[chain_described.columns.tolist()]
assert_frame_equal(chain_described, df)
elif chain.orientation == 'x':
keys = chain[self.stack.name][fk][chain.source_name].keys()
views = chain[self.stack.name][fk][chain.source_name][
keys[0]].keys()
data = [self.stack.name] * (len(keys) * len(views))
filters = [fk] * (len(keys) * len(views))
y = []
for key in keys:
y.extend([key] * len(views))
x = [chain.source_name] * (len(keys) * len(views))
view = [v for v in views] * len(keys)
ones = [1] * (len(keys) * len(views))
df = pd.DataFrame({
'data': data,
'filter': filters,
'x': x,
'y': y,
'view': view,
'#': ones
})
df = df[chain_described.columns.tolist()]
assert_frame_equal(chain_described, df)
@classmethod
def tearDownClass(self):
self.stack = Stack("StackName")
filepath = './tests/' + self.stack.name + '.stack'
if os.path.exists(filepath):
os.remove(filepath)
def is_empty(self, any_structure):
if any_structure:
#print('Structure is not empty.')
return False
else:
#print('Structure is empty.')
return True
def create_key_stack(self, branch_pos="data"):
""" Creates a dictionary that has the structure of the keys in the Stack
It is used to loop through the stack without affecting it.
"""
key_stack = {}
for data_key in self.stack:
key_stack[data_key] = {}
for the_filter in self.stack[data_key][branch_pos]:
key_stack[data_key][the_filter] = {}
for x in self.stack[data_key][branch_pos][the_filter]:
key_stack[data_key][the_filter][x] = []
for y in self.stack[data_key][branch_pos][the_filter][x]:
link = self.stack[data_key][branch_pos][the_filter][x][
y]
if not isinstance(link, Link):
continue
key_stack[data_key][the_filter][x].append(y)
return key_stack
def setup_stack_Example_Data_A(self,
fk=None,
xk=None,
yk=None,
views=None,
weights=None):
if fk is None:
fk = 'no_filter'
if xk is None:
xk = self.minimum
if yk is None:
yk = ['@'] + self.minimum
if views is None:
views = ['default', 'cbase', 'counts', 'c%']
if not isinstance(weights, list):
weights = [weights]
self.stack = Stack(name="Example Data (A)")
self.stack.add_data(data_key=self.stack.name,
meta=self.example_data_A_meta,
data=self.example_data_A_data)
for weight in weights:
self.stack.add_link(data_keys=self.stack.name,
filters=fk,
x=xk,
y=yk,
views=QuantipyViews(views),
weights=weight)
def setup_chains_Example_Data_A(self,
fk=None,
xk=None,
yk=None,
views=None,
orient_on=None):
if fk is None:
fk = 'no_filter'
if xk is None:
xk = self.minimum
if yk is None:
yk = ['@'] + self.minimum
if views is None:
views = [
'x|frequency|x:y|||cbase', 'x|frequency||||counts',
'x|frequency||y||c%'
]
self.chains = []
for y in yk:
self.chains.append(
self.stack.get_chain(name=y,
data_keys=self.stack.name,
filters='no_filter',
x=xk,
y=y,
views=views,
post_process=True))
for x in xk:
self.chains.append(
self.stack.get_chain(name=x,
data_keys=self.stack.name,
filters='no_filter',
x=x,
y=yk,
views=views,
post_process=True))
def test_iterations_object(self):
# Set up path to example files
path_tests = self.path
project_name = 'Example Data (A)'
# Load Example Data (A) data and meta
name_data = '%s.csv' % (project_name)
path_data = '%s%s' % (path_tests, name_data)
example_data_A_data = pd.DataFrame.from_csv(path_data)
name_meta = '%s.json' % (project_name)
path_meta = '%s%s' % (path_tests, name_meta)
example_data_A_meta = load_json(path_meta)
# Variables by type for Example Data A
eda_int = ['record_number', 'unique_id', 'age', 'birth_day', 'birth_month']
eda_float = ['weight', 'weight_a', 'weight_b']
eda_single = ['gender', 'locality', 'ethnicity', 'religion', 'q1']
eda_delimited_set = ['q2', 'q3', 'q8', 'q9']
eda_string = ['q8a', 'q9a']
eda_date = ['start_time', 'end_time']
eda_time = ['duration']
eda_array = ['q5', 'q6', 'q7']
eda_minimum = ['q2b', 'Wave', 'q2', 'q3', 'q5_1']
# Create basic stack
stack = Stack(name=project_name)
stack.add_data(project_name, example_data_A_data, example_data_A_meta)
stack.add_link(
data_keys=project_name,
filters=['no_filter'],
x=eda_minimum,
y=['@'],
views=QuantipyViews(['default', 'cbase', 'counts', 'c%']),
weights=[None, 'weight_a', 'weight_b']
)
# Get list of views created
views_present = stack.describe(index=['view'])
# Test that weighted an unweighted versions of all basic views
# were created
self.assertIn('x|default|x:y|||default', views_present)
self.assertIn('x|default|x:y||weight_a|default', views_present)
self.assertIn('x|default|x:y||weight_b|default', views_present)
self.assertIn('x|frequency|x:y|||cbase', views_present)
self.assertIn('x|frequency|x:y||weight_a|cbase', views_present)
self.assertIn('x|frequency|x:y||weight_b|cbase', views_present)
self.assertIn('x|frequency||y||c%', views_present)
self.assertIn('x|frequency||y|weight_a|c%', views_present)
self.assertIn('x|frequency||y|weight_b|c%', views_present)
self.assertIn('x|frequency||||counts', views_present)
self.assertIn('x|frequency|||weight_a|counts', views_present)
self.assertIn('x|frequency|||weight_b|counts', views_present)
# Create a ViewMapper using the iterator object in a template
xnets = ViewMapper(
template={
'method': QuantipyViews().frequency,
'kwargs': {
'axis': 'x',
'groups': ['Nets'],
'iterators': {
'rel_to': [None, 'y'],
'weights': [None, 'weight_a']
}
}
})
# Add a method to the xnets ViewMapper, then use it to generate additional
# views which include N/c% and unweighted/weighted
xnets.add_method(name='ever', kwargs={'text': 'Ever', 'logic': [1, 2]})
stack.add_link(x='q2b', y=['@'], views=xnets.subset(['ever']))
# Get list of views created
views_present = stack.describe(index=['view'])
# Test that the expected views were all created
self.assertIn('x|frequency|x[(1,2)]:y|||ever', views_present)
self.assertIn('x|frequency|x[(1,2)]:y|y||ever', views_present)
self.assertIn('x|frequency|x[(1,2)]:y||weight_a|ever', views_present)
self.assertIn('x|frequency|x[(1,2)]:y|y|weight_a|ever', views_present)
# Add another method to the xnets ViewMapper, but then override the weights
# in the iterator object using the stack.add_link(weights) parameter
stack.add_link(x='q2b', y=['@'], views=xnets.subset(['ever']), weights='weight_b')
# Get list of views created
views_present = stack.describe(index=['view'])
# Test that the expected views were all created
self.assertIn('x|frequency|x[(1,2)]:y||weight_b|ever', views_present)
self.assertIn('x|frequency|x[(1,2)]:y|y|weight_b|ever', views_present)
# Add two methods and apply them at the same time, make sure all expected iterations
# of both were created
xnets.add_method(name='ever (multi test)', kwargs={'text': 'Ever', 'logic': [1, 2]})
xnets.add_method(name='never (multi test)', kwargs={'text': 'Never', 'logic': [2, 3]})
stack.add_link(x='q2b', y=['@'], views=xnets.subset(['ever (multi test)', 'never (multi test)']))
# Get list of views created
views_present = stack.describe(index=['view'])
# Test that the expected views were all created
self.assertIn('x|frequency|x[(1,2)]:y|||ever (multi test)', views_present)
self.assertIn('x|frequency|x[(1,2)]:y|y||ever (multi test)', views_present)
self.assertIn('x|frequency|x[(1,2)]:y||weight_a|ever (multi test)', views_present)
self.assertIn('x|frequency|x[(1,2)]:y|y|weight_a|ever (multi test)', views_present)
self.assertIn('x|frequency|x[(2,3)]:y|||never (multi test)', views_present)
self.assertIn('x|frequency|x[(2,3)]:y|y||never (multi test)', views_present)
self.assertIn('x|frequency|x[(2,3)]:y||weight_a|never (multi test)', views_present)
self.assertIn('x|frequency|x[(2,3)]:y|y|weight_a|never (multi test)', views_present)
# Add two methods and apply them at the same time, make sure all expected iterations
# of both were created, in this case that the weights arg for stack.add_link() overrides
# what the iterator object is asking for
xnets.add_method(name='ever (weights test)', kwargs={'text': 'Ever', 'logic': [1, 2]})
xnets.add_method(name='never (weights test)', kwargs={'text': 'Never', 'logic': [2, 3]})
stack.add_link(
x='q2b', y=['@'],
views=xnets.subset(['ever (weights test)', 'never (weights test)']),
weights=['weight_b']
)
# Get list of views created
views_present = stack.describe(index=['view'])
# Test that the expected views were all created
self.assertNotIn('x|frequency|x[(1,2)]:y|||ever (weights test)', views_present)
self.assertNotIn('x|frequency|x[(1,2)]:y|y||ever (weights test)', views_present)
self.assertIn('x|frequency|x[(1,2)]:y||weight_b|ever (weights test)', views_present)
self.assertIn('x|frequency|x[(1,2)]:y|y|weight_b|ever (weights test)', views_present)
self.assertNotIn('x|frequency|x[(2,3)]:y|||never (weights test)', views_present)
self.assertNotIn('x|frequency|x[(2,3)]:y|y||never (weights test)', views_present)
self.assertIn('x|frequency|x[(2,3)]:y||weight_b|never (weights test)', views_present)
self.assertIn('x|frequency|x[(2,3)]:y|y|weight_b|never (weights test)', views_present)
class TestViewObject(unittest.TestCase):
def setUp(self):
self.path = './tests/'
# self.path = ''
self.filepath = '%sengine_B_data.csv' % (self.path)
self.metapath = '%sengine_B_meta.json' % (self.path)
self.stack = Stack("StackName")
self.stack.seperator = ','
self.stack.decoding = "UTF-8"
self.data = pd.DataFrame.from_csv(self.filepath)
self.meta = load_json(self.metapath)
self.stack.add_data(data_key="Jan", meta=self.meta, data=self.data)
# self.x_names=['age', 'cost_breakfast', 'age_group', 'endtime', 'name', 'q4'],
self.x_names = ['age', 'cost_breakfast', 'age_group', 'q4']
# self._types = ['int', 'float', 'single', 'date', 'string', 'delimited set']
self.x_types = ['int', 'float', 'single', 'delimited set']
self.y_names = ['profile_gender']
def test_add_method(self):
views = ViewMapper()
#At first there should not be method 'plus' in views
self.assertRaises(KeyError, lambda: views['plus'])
self.assertNotIn('plus', views.keys())
#Plus method added:
views.add_method('plus', lambda x: 2)
#Checked for the existance of the plus method
self.assertIsNotNone(views['plus']['method'])
self.assertIsNotNone(views['plus']['kwargs'])
self.assertIn('plus', views.keys())
#Check to see wether a method is overridden properly
views.add_method('plus', 'me')
#The method should have changed from lambda x:2 to me
self.assertEqual(views['plus']['method'], 'me')
# Check to see wether a method is overridden properly
views.add_method('minus', 'x', {'key': 'value'})
self.assertEqual(views['minus']['method'], 'x')
def test__custom_methods(self):
views = ViewMapper()
views.add_method('minus_x', 'x', {'key': 'value'})
views.add_method('minus_y', 'y')
views.add_method('minus_z', 'z')
for view in ['minus_x', 'minus_y', 'minus_z']:
self.assertIn(view, views._custom_methods())
for view in ['X', 'Y', 'Z']:
self.assertNotIn(view, views._custom_methods())
def test__get_method_types(self):
#not checked - time & string - need to implemented
#examples: time - "endtime"
# string - "name"
views = QuantipyViews(['default'])
self.stack.add_link(data_keys="Jan",
x=self.x_names,
y=self.y_names,
views=views)
for x_type, x_name in zip(self.x_types, self.x_names):
link = self.stack['Jan']['no_filter'][x_name]['profile_gender']
self.assertEqual(x_type, views._get_method_types(link)[0])
def test__apply_to(self):
#not checked - time & string - need to implemented
#examples: time - "endtime"
# string - "name"
views = QuantipyViews(['cbase', 'counts', 'mean'])
# This matches the view method names to their resulting view key
# based on the new view notation
notation = {
'default': 'x|default|x:y|||default',
'cbase': 'x|frequency|x:y|||cbase',
'counts': 'x|frequency||||counts',
'mean': 'x|mean|x:y|||mean'
}
x_names = ['profile_gender', 'age_group', 'q4']
y_names = x_names
self.stack.add_link(data_keys="Jan",
x=x_names,
y=y_names)
for a_x in self.stack['Jan']['no_filter'].keys():
for a_y in self.stack['Jan']['no_filter'][a_x].keys():
link = self.stack['Jan']['no_filter'][a_x][a_y]
if not link.y == "@":
views._apply_to(link)
for view in views.keys():
for a_x in self.stack['Jan']['no_filter'].keys():
for a_y in self.stack['Jan']['no_filter'][a_x].keys():
if views[view]['method'] == 'descriptives':
if a_x == 'q4':
self.assertNotIn(notation[view], self.stack['Jan']['no_filter'][a_x][a_y].keys())
else:
self.assertIn(notation[view], self.stack['Jan']['no_filter'][a_x][a_y].keys())
else:
self.assertIn(notation[view], self.stack['Jan']['no_filter'][a_x][a_y].keys())
def test_get_view_iterations(self):
views = QuantipyViews(['default'])
iterators = {'A': [1, 2], 'B': [3, 4, 5], 'C': [6, 7, 8, 9]}
iterations = views.__get_view_iterations__(iterators)
# Test that iterations has the anticipated number of items
# It should be the multiplication of the len of all of
# iterators lists, in this case 2x3x4=24
self.assertEqual(len(iterations), 24)
self.assertEqual(iterations[0], {'A': 1, 'B': 3, 'C': 6})
self.assertEqual(iterations[1], {'A': 1, 'B': 4, 'C': 6})
self.assertEqual(iterations[2], {'A': 1, 'B': 5, 'C': 6})
self.assertEqual(iterations[3], {'A': 1, 'B': 3, 'C': 7})
self.assertEqual(iterations[4], {'A': 1, 'B': 4, 'C': 7})
self.assertEqual(iterations[5], {'A': 1, 'B': 5, 'C': 7})
self.assertEqual(iterations[6], {'A': 1, 'B': 3, 'C': 8})
self.assertEqual(iterations[7], {'A': 1, 'B': 4, 'C': 8})
self.assertEqual(iterations[8], {'A': 1, 'B': 5, 'C': 8})
self.assertEqual(iterations[9], {'A': 1, 'B': 3, 'C': 9})
self.assertEqual(iterations[10], {'A': 1, 'B': 4, 'C': 9})
self.assertEqual(iterations[11], {'A': 1, 'B': 5, 'C': 9})
self.assertEqual(iterations[12], {'A': 2, 'B': 3, 'C': 6})
self.assertEqual(iterations[13], {'A': 2, 'B': 4, 'C': 6})
self.assertEqual(iterations[14], {'A': 2, 'B': 5, 'C': 6})
self.assertEqual(iterations[15], {'A': 2, 'B': 3, 'C': 7})
self.assertEqual(iterations[16], {'A': 2, 'B': 4, 'C': 7})
self.assertEqual(iterations[17], {'A': 2, 'B': 5, 'C': 7})
self.assertEqual(iterations[18], {'A': 2, 'B': 3, 'C': 8})
self.assertEqual(iterations[19], {'A': 2, 'B': 4, 'C': 8})
self.assertEqual(iterations[20], {'A': 2, 'B': 5, 'C': 8})
self.assertEqual(iterations[21], {'A': 2, 'B': 3, 'C': 9})
self.assertEqual(iterations[22], {'A': 2, 'B': 4, 'C': 9})
self.assertEqual(iterations[23], {'A': 2, 'B': 5, 'C': 9})
def test_iterations_object(self):
# Set up path to example files
path_tests = self.path
project_name = 'Example Data (A)'
# Load Example Data (A) data and meta
name_data = '%s.csv' % (project_name)
path_data = '%s%s' % (path_tests, name_data)
example_data_A_data = pd.DataFrame.from_csv(path_data)
name_meta = '%s.json' % (project_name)
path_meta = '%s%s' % (path_tests, name_meta)
example_data_A_meta = load_json(path_meta)
# Variables by type for Example Data A
eda_int = ['record_number', 'unique_id', 'age', 'birth_day', 'birth_month']
eda_float = ['weight', 'weight_a', 'weight_b']
eda_single = ['gender', 'locality', 'ethnicity', 'religion', 'q1']
eda_delimited_set = ['q2', 'q3', 'q8', 'q9']
eda_string = ['q8a', 'q9a']
eda_date = ['start_time', 'end_time']
eda_time = ['duration']
eda_array = ['q5', 'q6', 'q7']
eda_minimum = ['q2b', 'Wave', 'q2', 'q3', 'q5_1']
# Create basic stack
stack = Stack(name=project_name)
stack.add_data(project_name, example_data_A_data, example_data_A_meta)
stack.add_link(
data_keys=project_name,
filters=['no_filter'],
x=eda_minimum,
y=['@'],
views=QuantipyViews(['default', 'cbase', 'counts', 'c%']),
weights=[None, 'weight_a', 'weight_b']
)
# Get list of views created
views_present = stack.describe(index=['view'])
# Test that weighted an unweighted versions of all basic views
# were created
self.assertIn('x|default|x:y|||default', views_present)
self.assertIn('x|default|x:y||weight_a|default', views_present)
self.assertIn('x|default|x:y||weight_b|default', views_present)
self.assertIn('x|frequency|x:y|||cbase', views_present)
self.assertIn('x|frequency|x:y||weight_a|cbase', views_present)
self.assertIn('x|frequency|x:y||weight_b|cbase', views_present)
self.assertIn('x|frequency||y||c%', views_present)
self.assertIn('x|frequency||y|weight_a|c%', views_present)
self.assertIn('x|frequency||y|weight_b|c%', views_present)
self.assertIn('x|frequency||||counts', views_present)
self.assertIn('x|frequency|||weight_a|counts', views_present)
self.assertIn('x|frequency|||weight_b|counts', views_present)
# Create a ViewMapper using the iterator object in a template
xnets = ViewMapper(
template={
'method': QuantipyViews().frequency,
'kwargs': {
'axis': 'x',
'groups': ['Nets'],
'iterators': {
'rel_to': [None, 'y'],
'weights': [None, 'weight_a']
}
}
})
# Add a method to the xnets ViewMapper, then use it to generate additional
# views which include N/c% and unweighted/weighted
xnets.add_method(name='ever', kwargs={'text': 'Ever', 'logic': [1, 2]})
stack.add_link(x='q2b', y=['@'], views=xnets.subset(['ever']))
# Get list of views created
views_present = stack.describe(index=['view'])
# Test that the expected views were all created
self.assertIn('x|frequency|x[(1,2)]:y|||ever', views_present)
self.assertIn('x|frequency|x[(1,2)]:y|y||ever', views_present)
self.assertIn('x|frequency|x[(1,2)]:y||weight_a|ever', views_present)
self.assertIn('x|frequency|x[(1,2)]:y|y|weight_a|ever', views_present)
# Add another method to the xnets ViewMapper, but then override the weights
# in the iterator object using the stack.add_link(weights) parameter
stack.add_link(x='q2b', y=['@'], views=xnets.subset(['ever']), weights='weight_b')
# Get list of views created
views_present = stack.describe(index=['view'])
# Test that the expected views were all created
self.assertIn('x|frequency|x[(1,2)]:y||weight_b|ever', views_present)
self.assertIn('x|frequency|x[(1,2)]:y|y|weight_b|ever', views_present)
# Add two methods and apply them at the same time, make sure all expected iterations
# of both were created
xnets.add_method(name='ever (multi test)', kwargs={'text': 'Ever', 'logic': [1, 2]})
xnets.add_method(name='never (multi test)', kwargs={'text': 'Never', 'logic': [2, 3]})
stack.add_link(x='q2b', y=['@'], views=xnets.subset(['ever (multi test)', 'never (multi test)']))
# Get list of views created
views_present = stack.describe(index=['view'])
# Test that the expected views were all created
self.assertIn('x|frequency|x[(1,2)]:y|||ever (multi test)', views_present)
self.assertIn('x|frequency|x[(1,2)]:y|y||ever (multi test)', views_present)
self.assertIn('x|frequency|x[(1,2)]:y||weight_a|ever (multi test)', views_present)
self.assertIn('x|frequency|x[(1,2)]:y|y|weight_a|ever (multi test)', views_present)
self.assertIn('x|frequency|x[(2,3)]:y|||never (multi test)', views_present)
self.assertIn('x|frequency|x[(2,3)]:y|y||never (multi test)', views_present)
self.assertIn('x|frequency|x[(2,3)]:y||weight_a|never (multi test)', views_present)
self.assertIn('x|frequency|x[(2,3)]:y|y|weight_a|never (multi test)', views_present)
# Add two methods and apply them at the same time, make sure all expected iterations
# of both were created, in this case that the weights arg for stack.add_link() overrides
# what the iterator object is asking for
xnets.add_method(name='ever (weights test)', kwargs={'text': 'Ever', 'logic': [1, 2]})
xnets.add_method(name='never (weights test)', kwargs={'text': 'Never', 'logic': [2, 3]})
stack.add_link(
x='q2b', y=['@'],
views=xnets.subset(['ever (weights test)', 'never (weights test)']),
weights=['weight_b']
)
# Get list of views created
views_present = stack.describe(index=['view'])
# Test that the expected views were all created
self.assertNotIn('x|frequency|x[(1,2)]:y|||ever (weights test)', views_present)
self.assertNotIn('x|frequency|x[(1,2)]:y|y||ever (weights test)', views_present)
self.assertIn('x|frequency|x[(1,2)]:y||weight_b|ever (weights test)', views_present)
self.assertIn('x|frequency|x[(1,2)]:y|y|weight_b|ever (weights test)', views_present)
self.assertNotIn('x|frequency|x[(2,3)]:y|||never (weights test)', views_present)
self.assertNotIn('x|frequency|x[(2,3)]:y|y||never (weights test)', views_present)
self.assertIn('x|frequency|x[(2,3)]:y||weight_b|never (weights test)', views_present)
self.assertIn('x|frequency|x[(2,3)]:y|y|weight_b|never (weights test)', views_present)
def test_iterations_object(self):
# Set up path to example files
path_tests = self.path
project_name = 'Example Data (A)'
# Load Example Data (A) data and meta
name_data = '%s.csv' % (project_name)
path_data = '%s%s' % (path_tests, name_data)
example_data_A_data = pd.DataFrame.from_csv(path_data)
name_meta = '%s.json' % (project_name)
path_meta = '%s%s' % (path_tests, name_meta)
example_data_A_meta = load_json(path_meta)
# Variables by type for Example Data A
eda_int = [
'record_number', 'unique_id', 'age', 'birth_day', 'birth_month'
]
eda_float = ['weight', 'weight_a', 'weight_b']
eda_single = ['gender', 'locality', 'ethnicity', 'religion', 'q1']
eda_delimited_set = ['q2', 'q3', 'q8', 'q9']
eda_string = ['q8a', 'q9a']
eda_date = ['start_time', 'end_time']
eda_time = ['duration']
eda_array = ['q5', 'q6', 'q7']
eda_minimum = ['q2b', 'Wave', 'q2', 'q3', 'q5_1']
# Create basic stack
stack = Stack(name=project_name)
stack.add_data(project_name, example_data_A_data, example_data_A_meta)
stack.add_link(data_keys=project_name,
filters=['no_filter'],
x=eda_minimum,
y=['@'],
views=QuantipyViews(
['default', 'cbase', 'counts', 'c%']),
weights=[None, 'weight_a', 'weight_b'])
# Get list of views created
views_present = stack.describe(index=['view'])
# Test that weighted an unweighted versions of all basic views
# were created
self.assertIn('x|default|x:y|||default', views_present)
self.assertIn('x|default|x:y||weight_a|default', views_present)
self.assertIn('x|default|x:y||weight_b|default', views_present)
self.assertIn('x|frequency|x:y|||cbase', views_present)
self.assertIn('x|frequency|x:y||weight_a|cbase', views_present)
self.assertIn('x|frequency|x:y||weight_b|cbase', views_present)
self.assertIn('x|frequency||y||c%', views_present)
self.assertIn('x|frequency||y|weight_a|c%', views_present)
self.assertIn('x|frequency||y|weight_b|c%', views_present)
self.assertIn('x|frequency||||counts', views_present)
self.assertIn('x|frequency|||weight_a|counts', views_present)
self.assertIn('x|frequency|||weight_b|counts', views_present)
# Create a ViewMapper using the iterator object in a template
xnets = ViewMapper(
template={
'method': QuantipyViews().frequency,
'kwargs': {
'axis': 'x',
'groups': ['Nets'],
'iterators': {
'rel_to': [None, 'y'],
'weights': [None, 'weight_a']
}
}
})
# Add a method to the xnets ViewMapper, then use it to generate additional
# views which include N/c% and unweighted/weighted
xnets.add_method(name='ever', kwargs={'text': 'Ever', 'logic': [1, 2]})
stack.add_link(x='q2b', y=['@'], views=xnets.subset(['ever']))
# Get list of views created
views_present = stack.describe(index=['view'])
# Test that the expected views were all created
self.assertIn('x|frequency|x[(1,2)]:y|||ever', views_present)
self.assertIn('x|frequency|x[(1,2)]:y|y||ever', views_present)
self.assertIn('x|frequency|x[(1,2)]:y||weight_a|ever', views_present)
self.assertIn('x|frequency|x[(1,2)]:y|y|weight_a|ever', views_present)
# Add another method to the xnets ViewMapper, but then override the weights
# in the iterator object using the stack.add_link(weights) parameter
stack.add_link(x='q2b',
y=['@'],
views=xnets.subset(['ever']),
weights='weight_b')
# Get list of views created
views_present = stack.describe(index=['view'])
# Test that the expected views were all created
self.assertIn('x|frequency|x[(1,2)]:y||weight_b|ever', views_present)
self.assertIn('x|frequency|x[(1,2)]:y|y|weight_b|ever', views_present)
# Add two methods and apply them at the same time, make sure all expected iterations
# of both were created
xnets.add_method(name='ever (multi test)',
kwargs={
'text': 'Ever',
'logic': [1, 2]
})
xnets.add_method(name='never (multi test)',
kwargs={
'text': 'Never',
'logic': [2, 3]
})
stack.add_link(x='q2b',
y=['@'],
views=xnets.subset(
['ever (multi test)', 'never (multi test)']))
# Get list of views created
views_present = stack.describe(index=['view'])
# Test that the expected views were all created
self.assertIn('x|frequency|x[(1,2)]:y|||ever (multi test)',
views_present)
self.assertIn('x|frequency|x[(1,2)]:y|y||ever (multi test)',
views_present)
self.assertIn('x|frequency|x[(1,2)]:y||weight_a|ever (multi test)',
views_present)
self.assertIn('x|frequency|x[(1,2)]:y|y|weight_a|ever (multi test)',
views_present)
self.assertIn('x|frequency|x[(2,3)]:y|||never (multi test)',
views_present)
self.assertIn('x|frequency|x[(2,3)]:y|y||never (multi test)',
views_present)
self.assertIn('x|frequency|x[(2,3)]:y||weight_a|never (multi test)',
views_present)
self.assertIn('x|frequency|x[(2,3)]:y|y|weight_a|never (multi test)',
views_present)
# Add two methods and apply them at the same time, make sure all expected iterations
# of both were created, in this case that the weights arg for stack.add_link() overrides
# what the iterator object is asking for
xnets.add_method(name='ever (weights test)',
kwargs={
'text': 'Ever',
'logic': [1, 2]
})
xnets.add_method(name='never (weights test)',
kwargs={
'text': 'Never',
'logic': [2, 3]
})
stack.add_link(x='q2b',
y=['@'],
views=xnets.subset(
['ever (weights test)', 'never (weights test)']),
weights=['weight_b'])
# Get list of views created
views_present = stack.describe(index=['view'])
# Test that the expected views were all created
self.assertNotIn('x|frequency|x[(1,2)]:y|||ever (weights test)',
views_present)
self.assertNotIn('x|frequency|x[(1,2)]:y|y||ever (weights test)',
views_present)
self.assertIn('x|frequency|x[(1,2)]:y||weight_b|ever (weights test)',
views_present)
self.assertIn('x|frequency|x[(1,2)]:y|y|weight_b|ever (weights test)',
views_present)
self.assertNotIn('x|frequency|x[(2,3)]:y|||never (weights test)',
views_present)
self.assertNotIn('x|frequency|x[(2,3)]:y|y||never (weights test)',
views_present)
self.assertIn('x|frequency|x[(2,3)]:y||weight_b|never (weights test)',
views_present)
self.assertIn('x|frequency|x[(2,3)]:y|y|weight_b|never (weights test)',
views_present)
def tearDownClass(self):
self.stack = Stack("StackName")
filepath = './tests/' + self.stack.name + '.stack'
if os.path.exists(filepath):
os.remove(filepath)
class TestLinkObject(unittest.TestCase):
# stack.add_link(x='q1', y=y, views=mean_views.subset('m1to6'), weights=weight)
def setUp(self):
self.path = './tests/'
# self.path = ''
project_name = 'Example Data (A)'
# Load Example Data (A) data and meta into self
name_data = '%s.csv' % (project_name)
path_data = '%s%s' % (self.path, name_data)
self.example_data_A_data = pd.read_csv(path_data)
self.example_data_A_data = dataframe_fix_string_types(
self.example_data_A_data)
name_meta = '%s.json' % (project_name)
path_meta = '%s%s' % (self.path, name_meta)
self.example_data_A_meta = load_json(path_meta)
# The minimum list of variables required to populate a stack with all single*delimited set variations
self.minimum = ['q2b', 'Wave', 'q2', 'q3', 'q5_1']
self.setup_stack_Example_Data_A()
def test_link_is_a_subclassed_dict(self):
dk = self.stack.name
fk = 'no_filter'
xk = self.minimum
yk = ['@'] + self.minimum
for x in xk:
for y in yk:
link = self.stack[dk][fk][x][y]
self.assertIsInstance(link, dict)
self.assertIsInstance(link, Link)
def test_link_behaves_like_a_dict(self):
dk = self.stack.name
fk = 'no_filter'
xk = self.minimum
yk = ['@'] + self.minimum
key = "some_key_name"
value = "some_value"
for x in xk:
for y in yk:
link = self.stack[dk][fk][x][y]
link[key] = value
self.assertIn(
key,
link.keys(),
msg="Link should have key {data_key}, but has {link_keys}".
format(data_key=key, link_keys=link.keys()))
def test_get_meta(self):
dk = self.stack.name
fk = 'no_filter'
xk = self.minimum
yk = ['@'] + self.minimum
#test returned meta against stack meta
for x in xk:
for y in yk:
link = self.stack[dk][fk][x][y]
self.assertEqual(link.get_meta(), self.stack[dk].meta)
def test_get_data(self):
dk = self.stack.name
fk = 'no_filter'
xk = self.minimum
yk = ['@'] + self.minimum
stack_data = self.stack[dk][fk].data
#test returned data against stack data
for x in xk:
for y in yk:
link_data = self.stack[dk][fk][x][y].get_data()
self.assertTrue(link_data is stack_data)
@classmethod
def tearDownClass(self):
self.stack = Stack("StackName")
filepath = './tests/' + self.stack.name + '.stack'
if os.path.exists(filepath):
os.remove(filepath)
def is_empty(self, any_structure):
if any_structure:
#print('Structure is not empty.')
return False
else:
#print('Structure is empty.')
return True
def create_key_stack(self, branch_pos="data"):
""" Creates a dictionary that has the structure of the keys in the Stack
It is used to loop through the stack without affecting it.
"""
key_stack = {}
for data_key in self.stack:
key_stack[data_key] = {}
for the_filter in self.stack[data_key][branch_pos]:
key_stack[data_key][the_filter] = {}
for x in self.stack[data_key][branch_pos][the_filter]:
key_stack[data_key][the_filter][x] = []
for y in self.stack[data_key][branch_pos][the_filter][x]:
link = self.stack[data_key][branch_pos][the_filter][x][
y]
if not isinstance(link, Link):
continue
key_stack[data_key][the_filter][x].append(y)
return key_stack
def setup_stack_Example_Data_A(self,
fk=None,
xk=None,
yk=None,
views=None,
weights=None):
if fk is None:
fk = ['no_filter', 'Wave == 1']
if xk is None:
xk = self.minimum
if yk is None:
yk = ['@'] + self.minimum
if views is None:
views = ['default']
if not isinstance(weights, list):
weights = [weights]
self.stack = Stack(name="Example Data (A)")
self.stack.add_data(data_key=self.stack.name,
meta=self.example_data_A_meta,
data=self.example_data_A_data)
for weight in weights:
self.stack.add_link(data_keys=self.stack.name,
filters=fk,
x=xk,
y=yk,
views=QuantipyViews(views),
weights=weight)
class TestViewObject(unittest.TestCase):
def setUp(self):
self.path = './tests/'
# self.path = ''
self.filepath = '%sengine_B_data.csv' % (self.path)
self.metapath = '%sengine_B_meta.json' % (self.path)
self.stack = Stack("StackName")
self.stack.seperator = ','
self.stack.decoding = "UTF-8"
self.data = pd.DataFrame.from_csv(self.filepath)
self.meta = load_json(self.metapath)
self.stack.add_data(data_key="Jan", meta=self.meta, data=self.data)
# self.x_names=['age', 'cost_breakfast', 'age_group', 'endtime', 'name', 'q4'],
self.x_names = ['age', 'cost_breakfast', 'age_group', 'q4']
# self._types = ['int', 'float', 'single', 'date', 'string', 'delimited set']
self.x_types = ['int', 'float', 'single', 'delimited set']
self.y_names = ['profile_gender']
def test_add_method(self):
views = ViewMapper()
#At first there should not be method 'plus' in views
self.assertRaises(KeyError, lambda: views['plus'])
self.assertNotIn('plus', views.keys())
#Plus method added:
views.add_method('plus', lambda x: 2)
#Checked for the existance of the plus method
self.assertIsNotNone(views['plus']['method'])
self.assertIsNotNone(views['plus']['kwargs'])
self.assertIn('plus', views.keys())
#Check to see wether a method is overridden properly
views.add_method('plus', 'me')
#The method should have changed from lambda x:2 to me
self.assertEqual(views['plus']['method'], 'me')
# Check to see wether a method is overridden properly
views.add_method('minus', 'x', {'key': 'value'})
self.assertEqual(views['minus']['method'], 'x')
def test__custom_methods(self):
views = ViewMapper()
views.add_method('minus_x', 'x', {'key': 'value'})
views.add_method('minus_y', 'y')
views.add_method('minus_z', 'z')
for view in ['minus_x', 'minus_y', 'minus_z']:
self.assertIn(view, views._custom_methods())
for view in ['X', 'Y', 'Z']:
self.assertNotIn(view, views._custom_methods())
def test__get_method_types(self):
#not checked - time & string - need to implemented
#examples: time - "endtime"
# string - "name"
views = QuantipyViews(['default'])
self.stack.add_link(data_keys="Jan",
x=self.x_names,
y=self.y_names,
views=views)
for x_type, x_name in zip(self.x_types, self.x_names):
link = self.stack['Jan']['no_filter'][x_name]['profile_gender']
self.assertEqual(x_type, views._get_method_types(link)[0])
def test__apply_to(self):
#not checked - time & string - need to implemented
#examples: time - "endtime"
# string - "name"
views = QuantipyViews(['cbase', 'counts', 'mean'])
# This matches the view method names to their resulting view key
# based on the new view notation
notation = {
'default': 'x|default|x:y|||default',
'cbase': 'x|frequency|x:y|||cbase',
'counts': 'x|frequency||||counts',
'mean': 'x|mean|x:y|||mean'
}
x_names = ['profile_gender', 'age_group', 'q4']
y_names = x_names
self.stack.add_link(data_keys="Jan", x=x_names, y=y_names)
for a_x in self.stack['Jan']['no_filter'].keys():
for a_y in self.stack['Jan']['no_filter'][a_x].keys():
link = self.stack['Jan']['no_filter'][a_x][a_y]
if not link.y == "@":
views._apply_to(link)
for view in views.keys():
for a_x in self.stack['Jan']['no_filter'].keys():
for a_y in self.stack['Jan']['no_filter'][a_x].keys():
if views[view]['method'] == 'descriptives':
if a_x == 'q4':
self.assertNotIn(
notation[view], self.stack['Jan']['no_filter']
[a_x][a_y].keys())
else:
self.assertIn(
notation[view], self.stack['Jan']['no_filter']
[a_x][a_y].keys())
else:
self.assertIn(
notation[view],
self.stack['Jan']['no_filter'][a_x][a_y].keys())
def test_get_view_iterations(self):
views = QuantipyViews(['default'])
iterators = {'A': [1, 2], 'B': [3, 4, 5], 'C': [6, 7, 8, 9]}
iterations = views.__get_view_iterations__(iterators)
# Test that iterations has the anticipated number of items
# It should be the multiplication of the len of all of
# iterators lists, in this case 2x3x4=24
self.assertEqual(len(iterations), 24)
self.assertEqual(iterations[0], {'A': 1, 'B': 3, 'C': 6})
self.assertEqual(iterations[1], {'A': 1, 'B': 4, 'C': 6})
self.assertEqual(iterations[2], {'A': 1, 'B': 5, 'C': 6})
self.assertEqual(iterations[3], {'A': 1, 'B': 3, 'C': 7})
self.assertEqual(iterations[4], {'A': 1, 'B': 4, 'C': 7})
self.assertEqual(iterations[5], {'A': 1, 'B': 5, 'C': 7})
self.assertEqual(iterations[6], {'A': 1, 'B': 3, 'C': 8})
self.assertEqual(iterations[7], {'A': 1, 'B': 4, 'C': 8})
self.assertEqual(iterations[8], {'A': 1, 'B': 5, 'C': 8})
self.assertEqual(iterations[9], {'A': 1, 'B': 3, 'C': 9})
self.assertEqual(iterations[10], {'A': 1, 'B': 4, 'C': 9})
self.assertEqual(iterations[11], {'A': 1, 'B': 5, 'C': 9})
self.assertEqual(iterations[12], {'A': 2, 'B': 3, 'C': 6})
self.assertEqual(iterations[13], {'A': 2, 'B': 4, 'C': 6})
self.assertEqual(iterations[14], {'A': 2, 'B': 5, 'C': 6})
self.assertEqual(iterations[15], {'A': 2, 'B': 3, 'C': 7})
self.assertEqual(iterations[16], {'A': 2, 'B': 4, 'C': 7})
self.assertEqual(iterations[17], {'A': 2, 'B': 5, 'C': 7})
self.assertEqual(iterations[18], {'A': 2, 'B': 3, 'C': 8})
self.assertEqual(iterations[19], {'A': 2, 'B': 4, 'C': 8})
self.assertEqual(iterations[20], {'A': 2, 'B': 5, 'C': 8})
self.assertEqual(iterations[21], {'A': 2, 'B': 3, 'C': 9})
self.assertEqual(iterations[22], {'A': 2, 'B': 4, 'C': 9})
self.assertEqual(iterations[23], {'A': 2, 'B': 5, 'C': 9})
def test_iterations_object(self):
# Set up path to example files
path_tests = self.path
project_name = 'Example Data (A)'
# Load Example Data (A) data and meta
name_data = '%s.csv' % (project_name)
path_data = '%s%s' % (path_tests, name_data)
example_data_A_data = pd.DataFrame.from_csv(path_data)
name_meta = '%s.json' % (project_name)
path_meta = '%s%s' % (path_tests, name_meta)
example_data_A_meta = load_json(path_meta)
# Variables by type for Example Data A
eda_int = [
'record_number', 'unique_id', 'age', 'birth_day', 'birth_month'
]
eda_float = ['weight', 'weight_a', 'weight_b']
eda_single = ['gender', 'locality', 'ethnicity', 'religion', 'q1']
eda_delimited_set = ['q2', 'q3', 'q8', 'q9']
eda_string = ['q8a', 'q9a']
eda_date = ['start_time', 'end_time']
eda_time = ['duration']
eda_array = ['q5', 'q6', 'q7']
eda_minimum = ['q2b', 'Wave', 'q2', 'q3', 'q5_1']
# Create basic stack
stack = Stack(name=project_name)
stack.add_data(project_name, example_data_A_data, example_data_A_meta)
stack.add_link(data_keys=project_name,
filters=['no_filter'],
x=eda_minimum,
y=['@'],
views=QuantipyViews(
['default', 'cbase', 'counts', 'c%']),
weights=[None, 'weight_a', 'weight_b'])
# Get list of views created
views_present = stack.describe(index=['view'])
# Test that weighted an unweighted versions of all basic views
# were created
self.assertIn('x|default|x:y|||default', views_present)
self.assertIn('x|default|x:y||weight_a|default', views_present)
self.assertIn('x|default|x:y||weight_b|default', views_present)
self.assertIn('x|frequency|x:y|||cbase', views_present)
self.assertIn('x|frequency|x:y||weight_a|cbase', views_present)
self.assertIn('x|frequency|x:y||weight_b|cbase', views_present)
self.assertIn('x|frequency||y||c%', views_present)
self.assertIn('x|frequency||y|weight_a|c%', views_present)
self.assertIn('x|frequency||y|weight_b|c%', views_present)
self.assertIn('x|frequency||||counts', views_present)
self.assertIn('x|frequency|||weight_a|counts', views_present)
self.assertIn('x|frequency|||weight_b|counts', views_present)
# Create a ViewMapper using the iterator object in a template
xnets = ViewMapper(
template={
'method': QuantipyViews().frequency,
'kwargs': {
'axis': 'x',
'groups': ['Nets'],
'iterators': {
'rel_to': [None, 'y'],
'weights': [None, 'weight_a']
}
}
})
# Add a method to the xnets ViewMapper, then use it to generate additional
# views which include N/c% and unweighted/weighted
xnets.add_method(name='ever', kwargs={'text': 'Ever', 'logic': [1, 2]})
stack.add_link(x='q2b', y=['@'], views=xnets.subset(['ever']))
# Get list of views created
views_present = stack.describe(index=['view'])
# Test that the expected views were all created
self.assertIn('x|frequency|x[(1,2)]:y|||ever', views_present)
self.assertIn('x|frequency|x[(1,2)]:y|y||ever', views_present)
self.assertIn('x|frequency|x[(1,2)]:y||weight_a|ever', views_present)
self.assertIn('x|frequency|x[(1,2)]:y|y|weight_a|ever', views_present)
# Add another method to the xnets ViewMapper, but then override the weights
# in the iterator object using the stack.add_link(weights) parameter
stack.add_link(x='q2b',
y=['@'],
views=xnets.subset(['ever']),
weights='weight_b')
# Get list of views created
views_present = stack.describe(index=['view'])
# Test that the expected views were all created
self.assertIn('x|frequency|x[(1,2)]:y||weight_b|ever', views_present)
self.assertIn('x|frequency|x[(1,2)]:y|y|weight_b|ever', views_present)
# Add two methods and apply them at the same time, make sure all expected iterations
# of both were created
xnets.add_method(name='ever (multi test)',
kwargs={
'text': 'Ever',
'logic': [1, 2]
})
xnets.add_method(name='never (multi test)',
kwargs={
'text': 'Never',
'logic': [2, 3]
})
stack.add_link(x='q2b',
y=['@'],
views=xnets.subset(
['ever (multi test)', 'never (multi test)']))
# Get list of views created
views_present = stack.describe(index=['view'])
# Test that the expected views were all created
self.assertIn('x|frequency|x[(1,2)]:y|||ever (multi test)',
views_present)
self.assertIn('x|frequency|x[(1,2)]:y|y||ever (multi test)',
views_present)
self.assertIn('x|frequency|x[(1,2)]:y||weight_a|ever (multi test)',
views_present)
self.assertIn('x|frequency|x[(1,2)]:y|y|weight_a|ever (multi test)',
views_present)
self.assertIn('x|frequency|x[(2,3)]:y|||never (multi test)',
views_present)
self.assertIn('x|frequency|x[(2,3)]:y|y||never (multi test)',
views_present)
self.assertIn('x|frequency|x[(2,3)]:y||weight_a|never (multi test)',
views_present)
self.assertIn('x|frequency|x[(2,3)]:y|y|weight_a|never (multi test)',
views_present)
# Add two methods and apply them at the same time, make sure all expected iterations
# of both were created, in this case that the weights arg for stack.add_link() overrides
# what the iterator object is asking for
xnets.add_method(name='ever (weights test)',
kwargs={
'text': 'Ever',
'logic': [1, 2]
})
xnets.add_method(name='never (weights test)',
kwargs={
'text': 'Never',
'logic': [2, 3]
})
stack.add_link(x='q2b',
y=['@'],
views=xnets.subset(
['ever (weights test)', 'never (weights test)']),
weights=['weight_b'])
# Get list of views created
views_present = stack.describe(index=['view'])
# Test that the expected views were all created
self.assertNotIn('x|frequency|x[(1,2)]:y|||ever (weights test)',
views_present)
self.assertNotIn('x|frequency|x[(1,2)]:y|y||ever (weights test)',
views_present)
self.assertIn('x|frequency|x[(1,2)]:y||weight_b|ever (weights test)',
views_present)
self.assertIn('x|frequency|x[(1,2)]:y|y|weight_b|ever (weights test)',
views_present)
self.assertNotIn('x|frequency|x[(2,3)]:y|||never (weights test)',
views_present)
self.assertNotIn('x|frequency|x[(2,3)]:y|y||never (weights test)',
views_present)
self.assertIn('x|frequency|x[(2,3)]:y||weight_b|never (weights test)',
views_present)
self.assertIn('x|frequency|x[(2,3)]:y|y|weight_b|never (weights test)',
views_present)
