def test_incomplete_heaps(self):
payload = bytearray(64)
payload[:] = range(64)
packets = [
self.flavour.make_packet([
Item(spead2.HEAP_CNT_ID, 1, True),
Item(spead2.PAYLOAD_OFFSET_ID, 5, True),
Item(spead2.PAYLOAD_LENGTH_ID, 7, True),
Item(spead2.HEAP_LENGTH_ID, 96, True),
Item(0x1600, 12345, True),
Item(0x5000, 0, False, offset=0)], payload[5 : 12]),
self.flavour.make_packet([
Item(spead2.HEAP_CNT_ID, 1, True),
Item(spead2.PAYLOAD_OFFSET_ID, 32, True),
Item(spead2.PAYLOAD_LENGTH_ID, 32, True),
Item(spead2.HEAP_LENGTH_ID, 96, True)], payload[32 : 64])
]
heaps = self.data_to_heaps(b''.join(packets),
contiguous_only=False,
incomplete_keep_payload_ranges=True)
assert_equal(1, len(heaps))
assert_is_instance(heaps[0], recv.IncompleteHeap)
items = heaps[0].get_items()
assert_equal(1, len(items)) # Addressed item must be excluded
assert_equal(0x1600, items[0].id)
assert_equal(96, heaps[0].heap_length)
assert_equal(39, heaps[0].received_length)
assert_equal([(5, 12), (32, 64)], heaps[0].payload_ranges)
def test_slice_types(self):
ac = AlleleCountsArray(allele_counts_data, dtype='u1')
# row slice
s = ac[1:]
assert_is_instance(s, AlleleCountsArray)
# col slice
s = ac[:, 1:]
assert_is_instance(s, np.ndarray)
assert_not_is_instance(s, AlleleCountsArray)
# row index
s = ac[0]
assert_is_instance(s, np.ndarray)
assert_not_is_instance(s, AlleleCountsArray)
# col index
s = ac[:, 0]
assert_is_instance(s, np.ndarray)
assert_not_is_instance(s, AlleleCountsArray)
# item
s = ac[0, 0]
assert_is_instance(s, np.uint8)
assert_not_is_instance(s, AlleleCountsArray)
def test_customer_bank_accounts_list():
fixture = helpers.load_fixture('customer_bank_accounts')['list']
helpers.stub_response(fixture)
response = helpers.client.customer_bank_accounts.list(*fixture['url_params'])
body = fixture['body']['customer_bank_accounts']
assert_is_instance(response, list_response.ListResponse)
assert_is_instance(response.records[0], resources.CustomerBankAccount)
assert_equal(response.before, fixture['body']['meta']['cursors']['before'])
assert_equal(response.after, fixture['body']['meta']['cursors']['after'])
assert_is_none(responses.calls[-1].request.headers.get('Idempotency-Key'))
assert_equal([r.account_holder_name for r in response.records],
[b.get('account_holder_name') for b in body])
assert_equal([r.account_number_ending for r in response.records],
[b.get('account_number_ending') for b in body])
assert_equal([r.bank_name for r in response.records],
[b.get('bank_name') for b in body])
assert_equal([r.country_code for r in response.records],
[b.get('country_code') for b in body])
assert_equal([r.created_at for r in response.records],
[b.get('created_at') for b in body])
assert_equal([r.currency for r in response.records],
[b.get('currency') for b in body])
assert_equal([r.enabled for r in response.records],
[b.get('enabled') for b in body])
assert_equal([r.id for r in response.records],
[b.get('id') for b in body])
assert_equal([r.metadata for r in response.records],
[b.get('metadata') for b in body])
def assert_frame(s):
""" Check that s is a valid frame.
"""
assert_is_instance(s, Frame)
assert s._kb == ec
assert s.test_frame()
def test_slice_types(self):
h = HaplotypeArray(haplotype_data, dtype='i1')
# row slice
s = h[1:]
assert_is_instance(s, HaplotypeArray)
# col slice
s = h[:, 1:]
assert_is_instance(s, HaplotypeArray)
# row index
s = h[0]
assert_is_instance(s, np.ndarray)
assert_not_is_instance(s, HaplotypeArray)
# col index
s = h[:, 0]
assert_is_instance(s, np.ndarray)
assert_not_is_instance(s, HaplotypeArray)
# item
s = h[0, 0]
assert_is_instance(s, np.int8)
assert_not_is_instance(s, HaplotypeArray)
def test_group(module, EXAMPLE):
assert_hasattr(module, 'Group')
assert_is_instance(module.Group, type)
shared = module.Shared.from_dict(EXAMPLE['shared'])
values = EXAMPLE['values']
for value in values:
shared.add_value(value)
group1 = module.Group()
group1.init(shared)
for value in values:
group1.add_value(shared, value)
group2 = module.Group.from_values(shared, values)
assert_close(group1.dump(), group2.dump())
group = module.Group.from_values(shared, values)
dumped = group.dump()
group.init(shared)
group.load(dumped)
assert_close(group.dump(), dumped)
for value in values:
group2.remove_value(shared, value)
assert_not_equal(group1, group2)
group2.merge(shared, group1)
for value in values:
group1.score_value(shared, value)
for _ in xrange(10):
value = group1.sample_value(shared)
group1.score_value(shared, value)
module.sample_group(shared, 10)
group1.score_data(shared)
group2.score_data(shared)
def test_retrun():
p = return_statement()
node, r = p('return 5')
eq_(r, '')
assert_is_instance(node, Return)
eq_(node.result, NumericLiteral('5'))
def test_self_axes(self):
g = ag.PairGrid(self.df)
for ax in g.axes.flat:
nt.assert_is_instance(ax, plt.Axes)
plt.close("all")
def test_value(module, EXAMPLE):
assert_hasattr(module, 'Value')
assert_is_instance(module.Value, type)
values = EXAMPLE['values']
for value in values:
assert_is_instance(value, module.Value)
def test_get_context_data(self):
self.view.draft = self.dr1
res = self.view.get_context_data()
nt.assert_is_instance(res, dict)
nt.assert_in('draft', res)
nt.assert_is_instance(res['draft'], dict)
nt.assert_in('IMMEDIATE', res)
def test_self_axes(self):
g = ag.FacetGrid(self.df, row="a", col="b", hue="c")
for ax in g.axes.flat:
nt.assert_is_instance(ax, plt.Axes)
plt.close("all")
def test_sequence_config():
# Test sequence config.
conf = SequenceConfig(sequence_class=Sequence)
conf.sequence_name = 'test'
assert_true(conf.config_ready)
seq = conf.build_sequence()
assert_is_instance(seq, Sequence)
def check_basic_figure_sanity(self, fig, exp_num_subplots, exp_title,
exp_legend_exists, exp_xlabel, exp_ylabel,
exp_zlabel):
# check type
assert_is_instance(fig, mpl.figure.Figure)
# check number of subplots
axes = fig.get_axes()
npt.assert_equal(len(axes), exp_num_subplots)
# check title
ax = axes[0]
npt.assert_equal(ax.get_title(), exp_title)
# shouldn't have tick labels
for tick_label in (ax.get_xticklabels() + ax.get_yticklabels() +
ax.get_zticklabels()):
npt.assert_equal(tick_label.get_text(), '')
# check if legend is present
legend = ax.get_legend()
if exp_legend_exists:
assert_true(legend is not None)
else:
assert_true(legend is None)
# check axis labels
npt.assert_equal(ax.get_xlabel(), exp_xlabel)
npt.assert_equal(ax.get_ylabel(), exp_ylabel)
npt.assert_equal(ax.get_zlabel(), exp_zlabel)
def test_tuple():
tup = (lambda x: x, 1)
bufs = serialize_object(tup)
canned = pickle.loads(bufs[0])
nt.assert_is_instance(canned, tuple)
t2, r = unserialize_object(bufs)
nt.assert_equal(t2[0](t2[1]), tup[0](tup[1]))
def test_list():
lis = [lambda x: x, 1]
bufs = serialize_object(lis)
canned = pickle.loads(bufs[0])
nt.assert_is_instance(canned, list)
l2, r = unserialize_object(bufs)
nt.assert_equal(l2[0](l2[1]), lis[0](lis[1]))
def test_create(self):
"""L5PC: test creation of l5pc template"""
import bluepyopt
l5pc_cell = self.l5pc_template.create()
nt.assert_is_instance(l5pc_cell, bluepyopt.electrical.celltemplate.CellTemplate)
def test_families():
families = table.families()
for name, fdesc in families.iteritems():
assert_is_instance(name, basestring)
assert_is_instance(fdesc, dict)
assert_in('name', fdesc)
assert_in('max_versions', fdesc)
def test_multiple_formulas_value_without_params():
values = send(formula = VALID_FORMULA + '+' + VALID_OTHER_FORMULA)['payload']['values']
for formula_name in (VALID_FORMULA, VALID_OTHER_FORMULA):
assert_in(formula_name, values)
assert_is_instance(values[formula_name], float)
assert_equal(values[formula_name], 0)
def test_csr(self):
pkey = ezbakeca.private_key()
csr = ezbakeca.csr(pkey, CN="Test")
nt.assert_is_instance(csr, crypto.X509Req)
nt.assert_equal(csr.get_subject().CN, "Test")
nt.assert_true(csr.verify(ezbakeca.openssl_key(pkey)))
def test_create_core_default():
"""Test `create_core` with factory defaults."""
with temporary_config_file() as cfgfile:
# std factory params
core = create_core(cfgfile.name)
assert_is_instance(core, Core)
assert_equal(core.auto_enable_auth, True)
def test_get_initial(self):
self.view.user = self.user
self.view.get_initial()
res = self.view.initial
nt.assert_is_instance(res, dict)
nt.assert_equal(res['guid'], self.user._id)
nt.assert_equal(res['emails'], [(r, r) for r in self.user.emails.values_list('address', flat=True)])
def test_default_data_property_ro(self):
assert_is_instance(self.p.data, Maker)
def _set():
self.p.data = None
assert_raises(AttributeError, _set)
def test_mandates_list():
fixture = helpers.load_fixture('mandates')['list']
helpers.stub_response(fixture)
response = helpers.client.mandates.list(*fixture['url_params'])
body = fixture['body']['mandates']
assert_is_instance(response, list_response.ListResponse)
assert_is_instance(response.records[0], resources.Mandate)
assert_equal(response.before, fixture['body']['meta']['cursors']['before'])
assert_equal(response.after, fixture['body']['meta']['cursors']['after'])
assert_equal([r.created_at for r in response.records],
[b.get('created_at') for b in body])
assert_equal([r.id for r in response.records],
[b.get('id') for b in body])
assert_equal([r.metadata for r in response.records],
[b.get('metadata') for b in body])
assert_equal([r.next_possible_charge_date for r in response.records],
[b.get('next_possible_charge_date') for b in body])
assert_equal([r.reference for r in response.records],
[b.get('reference') for b in body])
assert_equal([r.scheme for r in response.records],
[b.get('scheme') for b in body])
assert_equal([r.status for r in response.records],
[b.get('status') for b in body])
def test_resource_definition_via_dict():
"""Test programmatic resource definition (as opposed to reading a config file)."""
cfg = gc3libs.config.Configuration()
# define resource
name = 'test'
cfg.resources[name].update(
name=name,
type='shellcmd',
auth='none',
transport='local',
max_cores_per_job=1,
max_memory_per_core=1*GB,
max_walltime=8*hours,
max_cores=2,
architecture=Run.Arch.X86_64,
)
# make it
resources = cfg.make_resources(ignore_errors=False)
# check result
resource = resources[name]
assert_equal(resource.name, name)
assert_is_instance(resource,
gc3libs.backends.shellcmd.ShellcmdLrms)
assert_is_instance(resource.transport,
gc3libs.backends.transport.LocalTransport)
assert_equal(resource.max_cores_per_job, 1)
assert_equal(resource.max_memory_per_core, 1*GB)
assert_equal(resource.max_walltime, 8*hours)
assert_equal(resource.max_cores, 2)
assert_equal(resource.architecture, Run.Arch.X86_64)
def test_subscriptions_create():
fixture = helpers.load_fixture('subscriptions')['create']
helpers.stub_response(fixture)
response = helpers.client.subscriptions.create(*fixture['url_params'])
body = fixture['body']['subscriptions']
assert_is_instance(response, resources.Subscription)
assert_equal(response.amount, body.get('amount'))
assert_equal(response.count, body.get('count'))
assert_equal(response.created_at, body.get('created_at'))
assert_equal(response.currency, body.get('currency'))
assert_equal(response.day_of_month, body.get('day_of_month'))
assert_equal(response.end_date, body.get('end_date'))
assert_equal(response.id, body.get('id'))
assert_equal(response.interval, body.get('interval'))
assert_equal(response.interval_unit, body.get('interval_unit'))
assert_equal(response.metadata, body.get('metadata'))
assert_equal(response.month, body.get('month'))
assert_equal(response.name, body.get('name'))
assert_equal(response.payment_reference, body.get('payment_reference'))
assert_equal(response.start_date, body.get('start_date'))
assert_equal(response.status, body.get('status'))
assert_equal(response.upcoming_payments, body.get('upcoming_payments'))
assert_equal(response.links.mandate,
body.get('links')['mandate'])
def test_get_item(td, raw):
nt.assert_is_instance(td, JSONMapping)
nt.assert_equal(td['a'], 1)
nt.assert_equal(td['b'], JSONSequence(raw['b']))
nt.assert_equal(td['b'][0], 1)
nt.assert_equal(td['c'], JSONMapping(raw['c']))
nt.assert_equal(td['c']['bb'][-1], 3)
def test_additional_backend():
"""Test instanciating a non-std backend."""
tmpfile = _setup_config_file("""
[resource/test]
type = noop
auth = none
transport = local
max_cores_per_job = 1
max_memory_per_core = 1
max_walltime = 8
max_cores = 2
architecture = x86_64
""")
try:
cfg = gc3libs.config.Configuration(tmpfile)
cfg.TYPE_CONSTRUCTOR_MAP['noop'] = ('gc3libs.backends.noop', 'NoOpLrms')
resources = cfg.make_resources(ignore_errors=False)
# resources are enabled by default
assert 'test' in resources
from gc3libs.backends.noop import NoOpLrms
assert_is_instance(resources['test'], NoOpLrms)
# test types
finally:
# since TYPE_CONSTRUCTOR_MAP is a class-level variable, we
# need to clean up otherwise other tests will see the No-Op
# backend
del cfg.TYPE_CONSTRUCTOR_MAP['noop']
os.remove(tmpfile)
def test_exif_property(self):
assert_is_instance(self.p.exif, exif)
def _set():
self.p.exif = None
assert_raises(AttributeError, _set)
def test_csr_signing(self):
pkey = ca.private_key()
req = ca.csr(pkey, CN="App", O="Ezbake", OU="Ezbake Apps", C="US")
cert = self.get_client(5049).csr(self.get_token(), ca.pem_csr(req))
cert = crypto.load_certificate(crypto.FILETYPE_PEM, cert)
nt.assert_is_instance(cert, crypto.X509)
nt.assert_equal(req.get_subject(), cert.get_subject())
def test_get_class_name(self):
name = Introspection.get_class_name(DummyClass())
assert_is_instance(name, str)
assert_equals(name, 'dummyclass')
name = Introspection.get_class_name(DummyClass)
assert_is_instance(name, str)
assert_equals(name, 'dummyclass')
def test_that_xlsx_is_handled_by_xls_table_set(self):
"""
Should emit a DeprecationWarning.
"""
fh = horror_fobj('simple.xlsx')
assert_is_instance(XLSXTableSet(fh), XLSTableSet)
def test_events_get():
fixture = helpers.load_fixture('events')['get']
helpers.stub_response(fixture)
response = helpers.client.events.get(*fixture['url_params'])
body = fixture['body']['events']
assert_is_instance(response, resources.Event)
assert_is_none(responses.calls[-1].request.headers.get('Idempotency-Key'))
assert_equal(response.action, body.get('action'))
assert_equal(response.created_at, body.get('created_at'))
assert_equal(response.customer_notifications, body.get('customer_notifications'))
assert_equal(response.id, body.get('id'))
assert_equal(response.metadata, body.get('metadata'))
assert_equal(response.resource_type, body.get('resource_type'))
assert_equal(response.details.bank_account_id,
body.get('details')['bank_account_id'])
assert_equal(response.details.cause,
body.get('details')['cause'])
assert_equal(response.details.currency,
body.get('details')['currency'])
assert_equal(response.details.description,
body.get('details')['description'])
assert_equal(response.details.not_retried_reason,
body.get('details')['not_retried_reason'])
assert_equal(response.details.origin,
body.get('details')['origin'])
assert_equal(response.details._property,
body.get('details')['property'])
assert_equal(response.details.reason_code,
body.get('details')['reason_code'])
assert_equal(response.details.scheme,
body.get('details')['scheme'])
assert_equal(response.details.will_attempt_retry,
body.get('details')['will_attempt_retry'])
assert_equal(response.links.creditor,
body.get('links')['creditor'])
assert_equal(response.links.customer,
body.get('links')['customer'])
assert_equal(response.links.customer_bank_account,
body.get('links')['customer_bank_account'])
assert_equal(response.links.instalment_schedule,
body.get('links')['instalment_schedule'])
assert_equal(response.links.mandate,
body.get('links')['mandate'])
assert_equal(response.links.new_customer_bank_account,
body.get('links')['new_customer_bank_account'])
assert_equal(response.links.new_mandate,
body.get('links')['new_mandate'])
assert_equal(response.links.organisation,
body.get('links')['organisation'])
assert_equal(response.links.parent_event,
body.get('links')['parent_event'])
assert_equal(response.links.payer_authorisation,
body.get('links')['payer_authorisation'])
assert_equal(response.links.payment,
body.get('links')['payment'])
assert_equal(response.links.payout,
body.get('links')['payout'])
assert_equal(response.links.previous_customer_bank_account,
body.get('links')['previous_customer_bank_account'])
assert_equal(response.links.refund,
body.get('links')['refund'])
assert_equal(response.links.subscription,
body.get('links')['subscription'])
# ## Part 1: Exploring files and the system
# First, let's start out by listing the contents of the directory `/user/` in HDFS. When you do this, you will pipe the output into a file called temp1.txt so that you may pass the assertion tests below (the easiest way to do this piping is with the `>temp1.txt` statement after your command-line statement).
# In[20]:
get_ipython().system('$HADOOP_PREFIX/bin/hdfs dfs -ls / >temp1.txt')
#get contents and pipe it to temp1
# In[21]:
res1 = get_ipython().getoutput('cat temp1.txt')
assert_is_instance(res1, list)
assert_is_instance(res1[0], str)
assert_is_instance(res1[1], str)
assert_true(res1[1], "Found 1 items")
assert_true(res1[1][:40], "drwxr-xr-x - data_scientist supergroup")
# ## Part 2 Free space:
# Now, let's issue a Hadoop command that allows us to see the free space available to us, making sure to make it human readable. Like before, you will pipe the output into a file called temp2.txt so that you may pass the assertion tests below (this piping can be done by putting `>temp2.txt` after your command-line statement).
# In[22]:
get_ipython().system('$HADOOP_PREFIX/bin/hdfs dfs -df -h >temp2.txt')
#pipe free space info to temp2
def test_Lazy_exteded():
from couchpotato.very.lazy import Lazy
assert_is_instance(Lazy(lambda x: x, (), {}), Lazy)
def test_GitRepo_instance_from_existing(path):
gr = GitRepo(path)
assert_is_instance(gr, GitRepo, "GitRepo was not created.")
assert_true(exists(opj(path, '.git')))
def test_get_object(self):
obj = self.view.get_object()
nt.assert_is_instance(obj, User)
def test_read_simple_xlsx(self):
fh = horror_fobj('simple.xlsx')
table_set = XLSTableSet(fh)
assert_equal(1, len(table_set.tables))
row_set = table_set.tables[0]
first_row = list(row_set.sample)[0]
third_row = list(row_set.sample)[2]
assert_is_instance(first_row[0].value, unicode)
assert_is_instance(first_row[1].value, unicode)
assert_is_instance(first_row[2].value, unicode)
assert_is_instance(third_row[0].value, datetime.datetime)
assert_is_instance(third_row[1].value, float)
assert_is_instance(third_row[2].value, unicode)
assert_equal(first_row[0].value, 'date')
assert_equal(first_row[1].value, 'temperature')
assert_equal(first_row[2].value, 'place')
assert_equal(third_row[0].value, datetime.datetime(2011, 1, 2, 0, 0))
assert_equal(third_row[1].value, -1.0)
assert_equal(third_row[2].value, u'Galway')
for row in list(row_set):
assert 3 == len(row), row
def test_connection():
nt.assert_equal(database.session.dbfile, const.DATABASE)
nt.assert_false(database.session.is_new_db)
nt.assert_is_instance(database.session.connection, sqlite3.Connection)
nt.assert_is_instance(database.session.cursor, sqlite3.Cursor)
def check_children(xblock):
for child in xblock.children:
assert_is_instance(child, UsageKey)
def test_get_templates():
'''Test template getting'''
env = folium.utilities.get_templates()
nt.assert_is_instance(env, jinja2.environment.Environment)
def test_put_chunk_noraise(self):
result = self.store.put_chunk_noraise("x", (1, 2), [])
assert_is_instance(result, BadChunk)
def check_children(payload):
for child in payload['definition']['children']:
assert_is_instance(child, basestring)
def test_get_parser(self):
assert_is_instance(build_utils.get_parser(), argparse.ArgumentParser)
def test_handle_metric_new_metric(self):
res = wsgi.handle_metric_new(req(dict(type="gauge")), "test")
assert_equal(res, "")
metric = metrics.metric("test")
assert_is_instance(metric, metrics.simple_metrics.Gauge)
def test_Entity():
# Test the basics of creating and accessing properties on an entity
for i in range(2):
e = Entity(name='Test object',
description='I hope this works',
annotations=dict(foo=123,
nerds=['chris', 'jen', 'janey'],
annotations='How confusing!'),
properties=dict(
annotations='/repo/v1/entity/syn1234/annotations',
md5='cdef636522577fc8fb2de4d95875b27c',
parentId='syn1234'),
concreteType='org.sagebionetworks.repo.model.Data')
# Should be able to create an Entity from an Entity
if i == 1:
e = Entity.create(e)
assert_equals(e.parentId, 'syn1234')
assert_equals(e['parentId'], 'syn1234')
assert_equals(e.properties['parentId'], 'syn1234')
assert_equals(e.properties.parentId, 'syn1234')
assert_equals(e.foo, 123)
assert_equals(e['foo'], 123)
assert_equals(e.annotations['foo'], 123)
assert_equals(e.annotations.foo, 123)
assert_true(hasattr(e, 'parentId'))
assert_true(hasattr(e, 'foo'))
assert_false(hasattr(e, 'qwerqwer'))
# Annotations is a bit funny, because there is a property call
# 'annotations', which will be masked by a member of the object
# called 'annotations'. Because annotations are open-ended, we
# might even have an annotations called 'annotations', which gets
# really confusing.
assert_is_instance(e.annotations, collections.Mapping)
assert_is_instance(e['annotations'], collections.Mapping)
assert_equals(e.properties['annotations'],
'/repo/v1/entity/syn1234/annotations')
assert_equals(e.properties.annotations,
'/repo/v1/entity/syn1234/annotations')
assert_equals(e.annotations.annotations, 'How confusing!')
assert_equals(e.annotations['annotations'], 'How confusing!')
assert_equals(e.nerds, ['chris', 'jen', 'janey'])
assert_true(
all([
k in e for k in [
'name', 'description', 'foo', 'nerds', 'annotations',
'md5', 'parentId'
]
]))
# Test modifying properties
e.description = 'Working, so far'
assert_equals(e['description'], 'Working, so far')
e['description'] = 'Wiz-bang flapdoodle'
assert_equals(e.description, 'Wiz-bang flapdoodle')
# Test modifying annotations
e.foo = 999
assert_equals(e.annotations['foo'], 999)
e['foo'] = 12345
assert_equals(e.annotations.foo, 12345)
# Test creating a new annotation
e['bar'] = 888
assert_equals(e.annotations['bar'], 888)
e['bat'] = 7788
assert_equals(e.annotations['bat'], 7788)
# Test replacing annotations object
e.annotations = {
'splat': 'a totally new set of annotations',
'foo': 456
}
assert_equals(e.foo, 456)
assert_equals(e['foo'], 456)
assert_is_instance(e.annotations, collections.Mapping)
assert_is_instance(e['annotations'], collections.Mapping)
assert_equals(e.annotations.foo, 456)
assert_equals(e.properties['annotations'],
'/repo/v1/entity/syn1234/annotations')
assert_equals(e.properties.annotations,
'/repo/v1/entity/syn1234/annotations')
# test unicode properties
e.train = '時刻表には記載されない 月への列車が来ると聞いて'
e.band = "Motörhead"
e.lunch = "すし"
def test_calculate_with_axes():
test_case = {
'output_format':
'variables',
"scenarios": [{
"period": {
"start": 2014,
"unit": "year"
},
"axes": [{
"count": 50,
"max": 100000,
"min": 0,
"name": "salaire_imposable"
}],
"test_case": {
"individus": [
{
"id": "Personne Principale",
"salaire_imposable": 0,
"statut_marital": 2
},
{
"id": "Personne Conjoint",
"salaire_imposable": 2
},
],
"familles": [{
"id":
"Famille 1",
"parents": ["Personne Principale", "Personne Conjoint"],
"enfants": []
}],
"foyers_fiscaux": [{
"id":
"Déclaration d'impôt 1",
"declarants": ["Personne Principale", "Personne Conjoint"],
"personnes_a_charge": []
}],
"menages": [{
"id": "Logement principal 1",
"personne_de_reference": "Personne Principale",
"conjoint": "Personne Conjoint",
"enfants": []
}],
},
}],
'variables': ['impo']
}
req = Request.blank(
'/api/1/calculate',
body=json.dumps(test_case),
headers=(('Content-Type', 'application/json'), ),
method='POST',
)
res = req.get_response(common.app)
assert_equal(res.status_code, 200, res.body)
res_body_json = json.loads(res.body)
impo_values = res_body_json['value'][0]['impo']['2014']
assert_is_instance(impo_values, list)
assert_true(impo_values[-1] < 0)
def test_init(self):
"""Alert Processor - Initialization"""
assert_is_instance(self.processor.config, dict)
def test_is_instance(self):
assert_is_instance(TestToolsBIT.mylist, list)
def test_AnnexRepo_instance_brand_new(path):
ar = AnnexRepo(path)
assert_is_instance(ar, AnnexRepo, "AnnexRepo was not created.")
assert_true(os.path.exists(os.path.join(path, '.git')))
def test_create_dispatcher(self):
"""Alert Processor - Create Dispatcher - Success"""
dispatcher = self.processor._create_dispatcher(
'aws-s3:unit_test_bucket')
assert_is_instance(dispatcher, OutputDispatcher)
def test_put_chunk_noraise(self):
name = self.array_name('x')
self.store.create_array(name)
result = self.store.put_chunk_noraise(name, (1, 2), [])
assert_is_instance(result, BadChunk)
def check_table(table):
assert_is_instance(table, str)
for member in [COMMAND, DESCRIPTION, TEST_RUN]:
assert_in(member, table)
def test_multi_target_init():
config = Config()
config.update({
"multiprocessing": False,
"blocking": True,
"device": "cpu",
"num_epochs": 1,
"num_inputs": 3,
"num_outputs": {
"t1": 4,
"t2": 5
},
"learning_rate": 1.0,
})
config.network_topology_json = """
{
"fw0": {"class": "hidden", "activation": "identity", "n_out": 3},
"out1": {"class": "softmax", "loss": "ce", "target": "t1", "from": ["fw0"]},
"out2": {"class": "softmax", "loss": "ce", "target": "t2", "from": ["fw0"]}
}
"""
device = Device("cpu", config=config, blocking=True)
assert_true(device.trainnet, "train network initialized")
assert_true(device.testnet, "test network initialized")
param_vars = device.trainnet.get_all_params_vars()
print("params:", param_vars)
assert_equal(len(param_vars), 6, "W, b vars for each out, and fw")
num_params = get_num_params(param_vars)
assert_equal(num_params, (3 * 3 + 3) + (3 * 4 + 4) + (3 * 5 + 5),
"W, b for each out, and fw")
assert_in("fw0", device.testnet.hidden)
assert_in("out1", device.testnet.output)
assert_in("out2", device.testnet.output)
assert_is(device.testnet.j["t1"], device.testnet.output["out1"].index)
assert_true(device.updater)
update_list = device.updater.getUpdateList()
print("update list:")
pprint(update_list)
update_dict = dict(update_list)
assert_equal(len(update_dict), len(update_list),
"all params in update list only once")
assert_in("fw0", device.trainnet.hidden)
assert_equal(len(device.trainnet.hidden), 1)
assert_in("W_in_data_fw0", device.trainnet.hidden["fw0"].params)
assert_in("b_fw0", device.trainnet.hidden["fw0"].params)
assert_equal(len(device.trainnet.hidden["fw0"].params), 2)
assert_in("out1", device.trainnet.output)
assert_equal(len(device.trainnet.output), 2)
assert_in("W_in_fw0_out1", device.trainnet.output["out1"].params)
assert_in("b_out1", device.trainnet.output["out1"].params)
assert_equal(len(device.trainnet.output["out1"].params), 2)
assert_in(device.trainnet.hidden["fw0"].params["W_in_data_fw0"],
update_dict)
assert_in(device.trainnet.hidden["fw0"].params["b_fw0"], update_dict)
assert_in(device.trainnet.output["out1"].params["W_in_fw0_out1"],
update_dict)
assert_in(device.trainnet.output["out1"].params["b_out1"], update_dict)
assert_in(device.trainnet.output["out2"].params["W_in_fw0_out2"],
update_dict)
assert_in(device.trainnet.output["out2"].params["b_out2"], update_dict)
# assert_equal(len(update_dict), 6) # updater adds other stuff...
# Set net params.
net_params = {
"fw0": {
"W_in_data_fw0": numpy.identity(3, dtype="float32"),
"b_fw0": numpy.zeros((3, ), dtype="float32")
},
"out1": {
"W_in_fw0_out1":
numpy.arange(0.0, 1.2, 0.1, dtype="float32").reshape((3, 4)),
"b_out1":
numpy.arange(0.0, 4, dtype="float32")
},
"out2": {
"W_in_fw0_out2":
numpy.arange(0.0, 1.5, 0.1, dtype="float32").reshape((3, 5)),
"b_out2":
numpy.arange(0.0, 5, dtype="float32")
}
}
device.trainnet.set_params_by_dict(net_params)
device.testnet.set_params_by_dict(net_params)
# Show params.
for p in param_vars:
print("init %s:" % p)
pprint(p.get_value())
# Init dataset.
dataset = StaticDataset(data=[{
"data":
numpy.array([[0.1, 0.2, -0.3]], dtype="float32"),
"t1":
numpy.array([2]),
"t2":
numpy.array([4])
}],
output_dim=config.typed_value("num_outputs"))
dataset.init_seq_order()
assert_equal(dataset.is_data_sparse("data"), False)
assert_equal(dataset.is_data_sparse("t1"), True)
assert_equal(dataset.is_data_sparse("t2"), True)
# Copy to device allocation.
success = assign_dev_data_single_seq(device, dataset, 0)
assert_true(success, "failed to allocate & assign data")
# Check allocated data.
assert_equal(device.targets["data"].shape,
(1, 1, 3)) # input shape. (time,batch,dim)
assert_in("t1", device.targets)
assert_in("t2", device.targets)
assert_equal(device.targets["t1"].shape, (1, 1))
assert_equal(device.targets["t2"].shape, (1, 1))
assert_equal(device.output_index["data"].shape, (1, 1))
numpy.testing.assert_equal(device.output_index["data"], numpy.array([[1]]))
assert_equal(device.output_index["t1"].shape, (1, 1))
numpy.testing.assert_equal(device.output_index["t1"], numpy.array([[1]]))
# Forward test.
device.update_data()
device.testnet.costs["out1"].name = "out1_cost" # nice in the func graph
out_i1 = device.testnet.output["out1"].index
out_i1_nonzero = device.testnet.output["out1"].i
nll1, pcx1 = T.nnet.crossentropy_softmax_1hot(
x=device.testnet.output["out1"].y_m[out_i1_nonzero],
y_idx=device.testnet.output["out1"].y_data_flat[out_i1_nonzero])
forward_func = theano.function(
inputs=[device.block_start, device.block_end],
outputs=[
device.testnet.j["t1"], out_i1, out_i1_nonzero[0], nll1, pcx1,
device.testnet.costs["out1"],
device.testnet.output["out1"].p_y_given_x,
device.testnet.costs["out2"],
device.testnet.output["out2"].p_y_given_x
],
givens=device.make_givens(device.testnet),
no_default_updates=True,
on_unused_input='warn',
name="forward")
#print "forward func:"
#theano.printing.debugprint(forward_func)
net_j1, out_i1_val, out_i1_nz_val, nll1_val, pcx1_val, t1_cost, t1_y, t2_cost, t2_y = forward_func(
0, 1)
print("forward results:")
pprint(net_j1)
pprint(out_i1_val)
pprint(out_i1_nz_val)
pprint(nll1_val)
pprint(pcx1_val)
pprint(t1_cost)
pprint(t1_y)
pprint(t2_cost)
pprint(t2_y)
assert_equal(net_j1, numpy.array([[1]]))
assert_equal(out_i1_val, numpy.array([[1]]))
assert_equal(out_i1_nz_val, numpy.array([0]))
assert_almost_equal(nll1_val, numpy.array([t1_cost]))
numpy.testing.assert_almost_equal(t1_y, pcx1_val[None, ...])
assert_almost_equal(t1_cost, 1.440189698561195, places=6)
assert_almost_equal(t2_cost, 0.45191439593759336, places=6)
numpy.testing.assert_almost_equal(
t1_y,
numpy.array([[[0.0320586, 0.08714432, 0.23688282, 0.64391426]]]),
decimal=6)
numpy.testing.assert_almost_equal(t2_y,
numpy.array([[[
0.01165623, 0.03168492, 0.08612854,
0.23412166, 0.63640865
]]]),
decimal=6)
# One train step.
device.set_learning_rate(config.typed_value("learning_rate"))
device.run("train")
output_list, outputs_format = device.result()
assert_is_instance(output_list, list)
assert_true(outputs_format, "for train, we should always get the format")
outputs = Device.make_result_dict(output_list, outputs_format)
pprint(outputs)
assert_in("cost:out1", outputs)
assert_greater(outputs["cost:out1"], 0)
assert_almost_equal(outputs["cost:out1"], t1_cost)
# Get net params.
params = device.get_net_train_params(device.trainnet)
references_params = {
"W_in_data_fw0":
numpy.array([[1.00055406e+00, 5.54056978e-04, 5.54056978e-04],
[1.10811396e-03, 1.00110811e+00, 1.10811396e-03],
[-1.66217093e-03, -1.66217093e-03, 9.98337829e-01]]),
"b_fw0":
numpy.array([0.00554057, 0.00554057, 0.00554057]),
"W_in_fw0_out1":
numpy.array([[-0.00320586, 0.09128557, 0.27631172, 0.23560857],
[0.39358828, 0.48257114, 0.75262344, 0.57121715],
[0.80961758, 0.9261433, 0.77106485, 1.29317428]]),
"b_out1":
numpy.array([-0.0320586, 0.91285568, 2.76311718, 2.35608574]),
"W_in_fw0_out2":
numpy.array([[
-1.16562310e-03, 9.68315079e-02, 1.91387146e-01, 2.76587834e-01,
4.36359135e-01
],
[
4.97668754e-01, 5.93663016e-01, 6.82774291e-01,
7.53175669e-01, 9.72718271e-01
],
[
1.00349687e+00, 1.10950548e+00, 1.22583856e+00,
1.37023650e+00, 1.29092259e+00
]]),
"b_out2":
numpy.array(
[-0.01165623, 0.96831508, 1.91387146, 2.76587834, 4.36359135])
}
assert_equal(len(param_vars), len(params))
for p, v in zip(param_vars, params):
print("%s:" % p)
pprint(v)
assert_true(p.name)
numpy.testing.assert_almost_equal(references_params[p.name],
v,
decimal=6)
def test_exception(sefl):
e = InventoryException("test")
print(e)
assert_is_instance(e, InventoryException)
def test_combi_auto_enc():
config = Config()
config.update({
"multiprocessing": False,
"blocking": True,
"device": "cpu",
"num_epochs": 1,
"num_inputs": 3,
"num_outputs": {
"classes": 2
},
"learning_rate": 1.0,
"network": {
"output": {
"class": "softmax",
"loss": "ce",
"target": "classes"
},
"auto-enc": {
"class": "softmax",
"loss": "sse",
"dtype": "float32",
"target": "data"
}
}
})
device = Device("cpu", config=config, blocking=True)
# Set net params.
def get_net_params(with_auto_enc=True):
d = {
"output": {
"W_in_data_output":
numpy.arange(0.1, 0.7, 0.1, dtype="float32").reshape((3, 2)),
"b_output":
numpy.arange(0.0, 2, dtype="float32")
}
}
if with_auto_enc:
d["auto-enc"] = {
"W_in_data_auto-enc":
numpy.arange(0.1, 1.0, 0.1, dtype="float32").reshape((3, 3)),
"b_auto-enc":
numpy.arange(0.0, 3, dtype="float32")
}
return d
device.trainnet.set_params_by_dict(get_net_params())
device.testnet.set_params_by_dict(get_net_params())
# Show params.
for p in device.trainnet.get_all_params_vars():
print("init %s:" % p)
pprint(p.get_value())
# Init dataset.
dataset = StaticDataset(data=[{
"data":
numpy.array([[0.1, 0.2, -0.3]], dtype="float32"),
"classes":
numpy.array([1]),
}],
output_dim=config.typed_value("num_outputs"))
dataset.init_seq_order()
# Copy to device allocation.
success = assign_dev_data_single_seq(device, dataset, 0)
assert_true(success, "failed to allocate & assign data")
# One train step.
device.set_learning_rate(config.typed_value("learning_rate"))
device.run("train")
output_list, outputs_format = device.result()
assert_is_instance(output_list, list)
assert_true(outputs_format, "for train, we should always get the format")
outputs = Device.make_result_dict(output_list, outputs_format)
pprint(outputs)
assert_in("cost:output", outputs)
assert_in("cost:auto-enc", outputs)
expected_cost_output = 0.3132616877555847
assert_almost_equal(outputs["cost:output"], expected_cost_output, places=6)
exact_cost_output = outputs["cost:output"]
assert_almost_equal(outputs["cost:auto-enc"], 1.7544001340866089, places=6)
# Now, drop the auto-enc from the network, and redo the same thing.
del config.typed_value("network")["auto-enc"]
device = Device("cpu", config=config, blocking=True)
device.trainnet.set_params_by_dict(get_net_params(with_auto_enc=False))
device.testnet.set_params_by_dict(get_net_params(with_auto_enc=False))
for p in device.trainnet.get_all_params_vars():
print("second run, init %s:" % p)
pprint(p.get_value())
dataset.init_seq_order() # reset. probably not needed
success = assign_dev_data_single_seq(device, dataset, 0)
assert_true(success, "failed to allocate & assign data")
device.set_learning_rate(config.typed_value("learning_rate"))
device.run("train")
output_list, outputs_format = device.result()
assert_is_instance(output_list, list)
assert_true(outputs_format, "for train, we should always get the format")
outputs = Device.make_result_dict(output_list, outputs_format)
pprint(outputs)
assert_in("cost:output", outputs)
assert_not_in("cost:auto-enc", outputs)
assert_almost_equal(outputs["cost:output"], expected_cost_output, places=6)
assert_equal(outputs["cost:output"], exact_cost_output)
def test_create_dispatcher():
"""StreamAlertOutput - Create Dispatcher"""
dispatcher = StreamAlertOutput.create_dispatcher('aws-s3', REGION,
FUNCTION_NAME, CONFIG)
assert_is_instance(dispatcher, S3Output)
def test_get_frame(self):
ret_1, ret_2 = self.videoThread.get_frame()
assert_false(ret_1)
assert_is_instance(ret_2, np.ndarray)
def test_combi_auto_enc_longer():
config = Config()
config.update({
"multiprocessing": False,
"blocking": True,
"device": "cpu",
"num_epochs": 1,
"num_inputs": 3,
"num_outputs": {
"classes": 2
},
"learning_rate": 1.0,
"adadelta": True,
"network": {
"output": {
"class": "softmax",
"loss": "ce",
"target": "classes"
},
"auto-enc": {
"class": "softmax",
"loss": "sse",
"dtype": "float32",
"target": "data"
}
}
})
device = Device("cpu", config=config, blocking=True)
# Set net params.
def get_net_params(with_auto_enc=True):
d = {
"output": {
"W_in_data_output":
numpy.arange(0.1, 0.7, 0.1, dtype="float32").reshape((3, 2)),
"b_output":
numpy.arange(0.0, 2, dtype="float32")
}
}
if with_auto_enc:
d["auto-enc"] = {
"W_in_data_auto-enc":
numpy.arange(0.1, 1.0, 0.1, dtype="float32").reshape((3, 3)),
"b_auto-enc":
numpy.arange(0.0, 3, dtype="float32")
}
return d
device.trainnet.set_params_by_dict(get_net_params())
device.testnet.set_params_by_dict(get_net_params())
# Show params.
for p in device.trainnet.get_all_params_vars():
print("init %s:" % p)
pprint(p.get_value())
# Init dataset.
dataset = DummyDataset(input_dim=config.typed_value("num_inputs"),
output_dim=config.typed_value("num_outputs"),
num_seqs=10)
dataset.init_seq_order()
cost_output_sum = 0.0
for seq_idx in range(dataset.num_seqs):
# Copy to device allocation.
success = assign_dev_data_single_seq(device, dataset, seq_idx)
assert_true(success, "failed to allocate & assign data")
# One train step.
device.set_learning_rate(config.typed_value("learning_rate"))
device.run("train")
output_list, outputs_format = device.result()
assert_is_instance(output_list, list)
assert_true(outputs_format,
"for train, we should always get the format")
outputs = Device.make_result_dict(output_list, outputs_format)
print(("seq %i" % seq_idx))
pprint(outputs)
assert_in("cost:output", outputs)
assert_in("cost:auto-enc", outputs)
cost_output_sum += outputs["cost:output"]
# Now, drop the auto-enc from the network, and redo the same thing.
del config.typed_value("network")["auto-enc"]
device = Device("cpu", config=config, blocking=True)
device.trainnet.set_params_by_dict(get_net_params(with_auto_enc=False))
device.testnet.set_params_by_dict(get_net_params(with_auto_enc=False))
for p in device.trainnet.get_all_params_vars():
print("second run, init %s:" % p)
pprint(p.get_value())
dataset.init_seq_order() # reset
cost2_output_sum = 0.0
for seq_idx in range(dataset.num_seqs):
# Copy to device allocation.
success = assign_dev_data_single_seq(device, dataset, seq_idx)
assert_true(success, "failed to allocate & assign data")
# One train step.
device.set_learning_rate(config.typed_value("learning_rate"))
device.run("train")
output_list, outputs_format = device.result()
assert_is_instance(output_list, list)
assert_true(outputs_format,
"for train, we should always get the format")
outputs = Device.make_result_dict(output_list, outputs_format)
print(("seq %i" % seq_idx))
pprint(outputs)
assert_in("cost:output", outputs)
assert_not_in("cost:auto-enc", outputs)
cost2_output_sum += outputs["cost:output"]
assert_equal(cost_output_sum, cost2_output_sum)
assert_almost_equal(cost_output_sum, 16.028842568397522, places=6)
def test_get_event_camera_chosen(self):
assert_is_instance(self.videoThread.get_event_camera_chosen(),
threading._Event)
def test_get_number_of_cameras(self):
assert_is_instance(self.videoThread.get_number_of_cameras(), int)
