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def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def _deDuplicate(results):
found = dict()
deDuped = list()
for entry in results:
dn = entry.get("dn")
if not dn in found:
found[dn] = 1
deDuped.append(entry)
return deDuped |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def _encrypted_user_photo_key_str(self):
"""
Software Secure needs to have both UserPhoto and PhotoID decrypted in
the same manner. So even though this is going to be the same for every
request, we're also using RSA encryption to encrypt the AES key for
faces.
"""
face_aes_key_str = settings.VERIFY_STUDENT["SOFTWARE_SECURE"]["FACE_IMAGE_AES_KEY"]
face_aes_key = face_aes_key_str.decode("hex")
rsa_key_str = settings.VERIFY_STUDENT["SOFTWARE_SECURE"]["RSA_PUBLIC_KEY"]
rsa_encrypted_face_aes_key = rsa_encrypt(face_aes_key, rsa_key_str)
return rsa_encrypted_face_aes_key.encode("base64") |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def _invert_results(self, candidates):
inverted_candidates = list(self.directory)
for candidate in candidates:
try:
inverted_candidates.remove(candidate)
except ValueError:
pass
return inverted_candidates |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def create_request(self, copy_id_photo_from=None):
"""
Construct the HTTP request to the photo verification service.
Keyword Arguments:
copy_id_photo_from (SoftwareSecurePhotoVerification): If provided, re-send the ID photo
data from this attempt. This is used for reverification, in which new face photos
are sent with previously-submitted ID photos.
Returns:
tuple of (header, body), where both `header` and `body` are dictionaries.
"""
access_key = settings.VERIFY_STUDENT["SOFTWARE_SECURE"]["API_ACCESS_KEY"]
secret_key = settings.VERIFY_STUDENT["SOFTWARE_SECURE"]["API_SECRET_KEY"]
scheme = "https" if settings.HTTPS == "on" else "http"
callback_url = "{}://{}{}".format(
scheme, settings.SITE_NAME, reverse('verify_student_results_callback')
)
# If we're copying the photo ID image from a previous verification attempt,
# then we need to send the old image data with the correct image key.
photo_id_url = (
self.image_url("photo_id")
if copy_id_photo_from is None
else self.image_url("photo_id", override_receipt_id=copy_id_photo_from.receipt_id)
)
photo_id_key = (
self.photo_id_key
if copy_id_photo_from is None else
copy_id_photo_from.photo_id_key
)
body = {
"EdX-ID": str(self.receipt_id),
"ExpectedName": self.name,
"PhotoID": photo_id_url,
"PhotoIDKey": photo_id_key,
"SendResponseTo": callback_url,
"UserPhoto": self.image_url("face"),
"UserPhotoKey": self._encrypted_user_photo_key_str(),
}
headers = {
"Content-Type": "application/json",
"Date": formatdate(timeval=None, localtime=False, usegmt=True)
}
_message, _sig, authorization = generate_signed_message(
"POST", headers, body, access_key, secret_key
)
headers['Authorization'] = authorization
return headers, body |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def _search_not(self, base, search_filter, candidates=None):
# Create empty candidates list as we need to use self.directory for
# each search
candidates = list()
this_filter = list()
index = 0
search_filter.remove("!")
for condition in search_filter:
if not isinstance(condition, list):
this_filter.append(condition)
index +=1
# Remove this_filter items from search_filter list
for condition in this_filter:
search_filter.remove(condition)
try:
search_filter = list(search_filter[0])
for sub_filter in search_filter:
if not isinstance(sub_filter, list):
candidates = self.operation.get(sub_filter)(base,
search_filter,
candidates)
else:
candidates = self.operation.get(sub_filter[0])(base,
sub_filter,
candidates)
except IndexError:
pass
candidates = self._invert_results(candidates)
for item in this_filter:
if ">=" in item:
k, v = item.split(">=")
candidates = Connection._match_less_than(base, k, v,
self.directory)
elif "<=" in item:
k, v = item.split("<=")
candidates = Connection._match_greater_than(base, k, v,
self.directory)
# Emulate AD functionality, same as "="
elif "~=" in item:
k, v = item.split("~=")
candidates = Connection._match_notequal_to(base, k, v,
self.directory)
elif "=" in item:
k, v = item.split("=")
candidates = Connection._match_notequal_to(base, k, v,
self.directory)
return candidates |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def request_message_txt(self):
"""
This is the body of the request we send across. This is never actually
used in the code, but exists for debugging purposes -- you can call
`print attempt.request_message_txt()` on the console and get a readable
rendering of the request that would be sent across, without actually
sending anything.
"""
headers, body = self.create_request()
header_txt = "\n".join(
u"{}: {}".format(h, v) for h, v in sorted(headers.items())
)
body_txt = json.dumps(body, indent=2, sort_keys=True, ensure_ascii=False).encode('utf-8')
return header_txt + "\n\n" + body_txt |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def _search_and(self, base, search_filter, candidates=None):
# Load the data from the directory, if we aren't passed any
if candidates == [] or candidates is None:
candidates = self.directory
this_filter = list()
index = 0
search_filter.remove("&")
for condition in search_filter:
if not isinstance(condition, list):
this_filter.append(condition)
index +=1
# Remove this_filter items from search_filter list
for condition in this_filter:
search_filter.remove(condition)
try:
search_filter = list(search_filter[0])
for sub_filter in search_filter:
if not isinstance(sub_filter, list):
candidates = self.operation.get(sub_filter)(base,
search_filter,
candidates)
else:
candidates = self.operation.get(sub_filter[0])(base,
sub_filter,
candidates)
except IndexError:
pass
for item in this_filter:
if ">=" in item:
k, v = item.split(">=")
candidates = Connection._match_greater_than_or_equal(base, k, v,
candidates)
elif "<=" in item:
k, v = item.split("<=")
candidates = Connection._match_less_than_or_equal(base, k, v,
candidates)
# Emulate AD functionality, same as "="
elif "~=" in item:
k, v = item.split("~=")
candidates = Connection._match_equal_to(base, k, v,
candidates)
elif "=" in item:
k, v = item.split("=")
candidates = Connection._match_equal_to(base, k, v,
candidates)
return candidates |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def send_request(self, copy_id_photo_from=None):
"""
Assembles a submission to Software Secure and sends it via HTTPS.
Keyword Arguments:
copy_id_photo_from (SoftwareSecurePhotoVerification): If provided, re-send the ID photo
data from this attempt. This is used for reverification, in which new face photos
are sent with previously-submitted ID photos.
Returns:
request.Response
"""
# If AUTOMATIC_VERIFY_STUDENT_IDENTITY_FOR_TESTING is True, we want to
# skip posting anything to Software Secure. We actually don't even
# create the message because that would require encryption and message
# signing that rely on settings.VERIFY_STUDENT values that aren't set
# in dev. So we just pretend like we successfully posted
if settings.FEATURES.get('AUTOMATIC_VERIFY_STUDENT_IDENTITY_FOR_TESTING'):
fake_response = requests.Response()
fake_response.status_code = 200
return fake_response
headers, body = self.create_request(copy_id_photo_from=copy_id_photo_from)
response = requests.post(
settings.VERIFY_STUDENT["SOFTWARE_SECURE"]["API_URL"],
headers=headers,
data=json.dumps(body, indent=2, sort_keys=True, ensure_ascii=False).encode('utf-8'),
verify=False
)
log.info(u"Sent request to Software Secure for receipt ID %s.", self.receipt_id)
if copy_id_photo_from is not None:
log.info(
(
u"Software Secure attempt with receipt ID %s used the same photo ID "
u"data as the receipt with ID %s"
),
self.receipt_id, copy_id_photo_from.receipt_id
)
log.debug("Headers:\n{}\n\n".format(headers))
log.debug("Body:\n{}\n\n".format(body))
log.debug(u"Return code: {}".format(response.status_code))
log.debug(u"Return message:\n\n{}\n\n".format(response.text))
return response |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def _search_or(self, base, search_filter, candidates=None):
# Create empty candidates list as we need to use self.directory for
# each search
candidates = list()
this_filter = list()
index = 0
search_filter.remove("|")
for condition in search_filter:
if not isinstance(condition, list):
this_filter.append(condition)
index +=1
# Remove this_filter items from search_filter list
for condition in this_filter:
search_filter.remove(condition)
try:
search_filter = list(search_filter[0])
for sub_filter in search_filter:
if not isinstance(sub_filter, list):
candidates += self.operation.get(sub_filter)(base,
search_filter,
candidates)
else:
candidates += self.operation.get(sub_filter[0])(base,
sub_filter,
candidates)
except IndexError:
pass
for item in this_filter:
if ">=" in item:
k, v = item.split(">=")
candidates += Connection._match_greater_than_or_equal(base, k, v,
self.directory)
elif "<=" in item:
k, v = item.split("<=")
candidates += Connection._match_less_than_or_equal(base, k, v,
self.directory)
# Emulate AD functionality, same as "="
elif "~=" in item:
k, v = item.split("~=")
candidates += Connection._match_equal_to(base, k, v,
self.directory)
elif "=" in item:
k, v = item.split("=")
candidates += Connection._match_equal_to(base, k, v,
self.directory)
return candidates |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def search(self, search_base=None, search_scope=None,
search_filter=None, attributes=None, paged_size=5,
size_limit=0, paged_cookie=None):
s_filter = list()
candidates = list()
self.response = list()
self.result = dict()
try:
if isinstance(search_filter, bytes):
# We need to convert to unicode otherwise pyparsing will not
# find the u"ö"
search_filter = to_unicode(search_filter)
expr = Connection._parse_filter()
s_filter = expr.parseString(search_filter).asList()[0]
except pyparsing.ParseBaseException as exx:
# Just for debugging purposes
s = "{!s}".format(exx)
for item in s_filter:
if item[0] in self.operation:
candidates = self.operation.get(item[0])(search_base,
s_filter)
self.response = Connection._deDuplicate(candidates)
return True |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def set_deadline(cls, course_key, deadline, is_explicit=False):
"""
Configure the verification deadline for a course.
If `deadline` is `None`, then the course will have no verification
deadline. In this case, users will be able to verify for the course
at any time.
Arguments:
course_key (CourseKey): Identifier for the course.
deadline (datetime or None): The verification deadline.
"""
if deadline is None:
VerificationDeadline.objects.filter(course_key=course_key).delete()
else:
record, created = VerificationDeadline.objects.get_or_create(
course_key=course_key,
defaults={"deadline": deadline, "deadline_is_explicit": is_explicit}
)
if not created:
record.deadline = deadline
record.deadline_is_explicit = is_explicit
record.save() |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def unbind(self):
return True |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def deadlines_for_courses(cls, course_keys):
"""
Retrieve verification deadlines for particular courses.
Arguments:
course_keys (list): List of `CourseKey`s.
Returns:
dict: Map of course keys to datetimes (verification deadlines)
"""
all_deadlines = cache.get(cls.ALL_DEADLINES_CACHE_KEY)
if all_deadlines is None:
all_deadlines = {
deadline.course_key: deadline.deadline
for deadline in VerificationDeadline.objects.all()
}
cache.set(cls.ALL_DEADLINES_CACHE_KEY, all_deadlines)
return {
course_key: all_deadlines[course_key]
for course_key in course_keys
if course_key in all_deadlines
} |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def __init__(self):
self._calls = CallList()
self._server_mock = None
self.directory = []
self.exception = None
self.reset() |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def deadline_for_course(cls, course_key):
"""
Retrieve the verification deadline for a particular course.
Arguments:
course_key (CourseKey): The identifier for the course.
Returns:
datetime or None
"""
try:
deadline = cls.objects.get(course_key=course_key)
return deadline.deadline
except cls.DoesNotExist:
return None |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def reset(self):
self._calls.reset() |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def setLDAPDirectory(self, directory=None):
if directory is None:
self.directory = []
else:
try:
with open(DIRECTORY, 'w+') as f:
f.write(str(directory))
self.directory = directory
except OSError as e:
raise |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def set_exception(self, exc=True):
self.exception = exc |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def _load_data(self, directory):
try:
with open(directory, 'r') as f:
data = f.read()
return literal_eval(data)
except OSError as e:
raise |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def calls(self):
return self._calls |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def __enter__(self):
self.start() |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def __exit__(self, *args):
self.stop()
self.reset() |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def activate(self, func):
evaldict = {'ldap3mock': self, 'func': func}
return get_wrapped(func, _wrapper_template, evaldict) |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def _on_Server(self, host, port, use_ssl, connect_timeout, get_info=None,
tls=None):
# mangle request packet
return "FakeServerObject" |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def _on_Connection(self, server, user, password,
auto_bind=None, client_strategy=None,
authentication=None, check_names=None,
auto_referrals=None, receive_timeout=None):
"""
We need to create a Connection object with
methods:
add()
modify()
search()
unbind()
and object
response
"""
# Raise an exception, if we are told to do so
if self.exception:
raise Exception("LDAP request failed")
# check the password
correct_password = False
# Anonymous bind
# Reload the directory just in case a change has been made to
# user credentials
self.directory = self._load_data(DIRECTORY)
if authentication == ldap3.ANONYMOUS and user == "":
correct_password = True
for entry in self.directory:
if to_unicode(entry.get("dn")) == user:
pw = entry.get("attributes").get("userPassword")
# password can be unicode
if to_bytes(pw) == to_bytes(password):
correct_password = True
elif pw.startswith('{SSHA}'):
correct_password = ldap_salted_sha1.verify(password, pw)
else:
correct_password = False
self.con_obj = Connection(self.directory)
self.con_obj.bound = correct_password
return self.con_obj |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def unbound_on_Server(host, port,
use_ssl,
connect_timeout, *a, **kwargs):
return self._on_Server(host, port,
use_ssl,
connect_timeout, *a, **kwargs) |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def unbound_on_Connection(server, user,
password,
auto_bind,
client_strategy,
authentication,
check_names,
auto_referrals, *a, **kwargs):
return self._on_Connection(server, user,
password,
auto_bind,
client_strategy,
authentication,
check_names,
auto_referrals, *a,
**kwargs) |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def stop(self):
self._patcher.stop()
self._patcher2.stop()
self._server_mock = None |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def get_server_mock(self):
return self._server_mock |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def setUp(self):
entry_Li = ComputedEntry("Li", -1.90753119)
with open(os.path.join(PymatgenTest.TEST_FILES_DIR, "LiTiO2_batt.json")) as f:
entries_LTO = json.load(f, cls=MontyDecoder)
self.ie_LTO = InsertionElectrode.from_entries(entries_LTO, entry_Li)
with open(os.path.join(PymatgenTest.TEST_FILES_DIR, "FeF3_batt.json")) as fid:
entries = json.load(fid, cls=MontyDecoder)
self.ce_FF = ConversionElectrode.from_composition_and_entries(Composition("FeF3"), entries) |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def __init__(self):
"""
Every authenticator has to have a name
:param name:
"""
super().__init__() |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def testName(self):
plotter = VoltageProfilePlotter(xaxis="frac_x")
plotter.add_electrode(self.ie_LTO, "LTO insertion")
plotter.add_electrode(self.ce_FF, "FeF3 conversion")
self.assertIsNotNone(plotter.get_plot_data(self.ie_LTO))
self.assertIsNotNone(plotter.get_plot_data(self.ce_FF)) |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def testPlotly(self):
plotter = VoltageProfilePlotter(xaxis="frac_x")
plotter.add_electrode(self.ie_LTO, "LTO insertion")
plotter.add_electrode(self.ce_FF, "FeF3 conversion")
fig = plotter.get_plotly_figure()
self.assertEqual(fig.layout.xaxis.title.text, "Atomic Fraction of Li")
plotter = VoltageProfilePlotter(xaxis="x_form")
plotter.add_electrode(self.ce_FF, "FeF3 conversion")
fig = plotter.get_plotly_figure()
self.assertEqual(fig.layout.xaxis.title.text, "x in Li<sub>x</sub>FeF3")
plotter.add_electrode(self.ie_LTO, "LTO insertion")
fig = plotter.get_plotly_figure()
self.assertEqual(fig.layout.xaxis.title.text, "x Workion Ion per Host F.U.") |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def _no_ssl_required_on_debug(app, **kwargs):
if app.debug or app.testing:
os.environ['AUTHLIB_INSECURE_TRANSPORT'] = '1' |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def __init__(self, head):
self.head = head
self.lsize = 0
while head.next:
head = head.next
self.lsize += 1
self.m1_idx = None
self.m2_idx = None
if self.lsize > self._largesize:
self.m1_idx = self.lsize / 3 # start from 1/3
self.m1 = self._getN(self.m1_idx)
self.m2_idx = self.m1_idx * 2 # start from 2/3
self.m2 = self._getN(self.m2_idx) |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def _getN(self, n):
n -= 1
p = self.head
while n:
p = p.next
n -= 1
return p |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def _get(delta, start):
p = start
while delta:
p = p.next
delta -= 1
return p.val |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def main():
parser = argparse.ArgumentParser()
parser.add_argument("day", help="The day of the results, with format yyyymmdd")
args = parser.parse_args()
install_autopkgtest_results_formatter()
with tempfile.TemporaryDirectory(dir=os.environ.get("HOME")) as temp_dir:
clone_results_repo(temp_dir)
format_results(temp_dir, ACTIVE_DISTROS, args.day)
commit_and_push(temp_dir, args.day) |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def __init__(self, parent, window):
self._parent = parent
self._window = window
self._application = self._parent._application
# create user interface
self._container = gtk.VBox(False, 5)
self._controls = gtk.HBox(False, 5)
separator = gtk.HSeparator()
# pack interface
self._container.pack_end(separator, False, False, 0)
self._container.pack_end(self._controls, False, False, 0) |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def install_autopkgtest_results_formatter():
subprocess.check_call(
["sudo", "snap", "install", "autopkgtest-results-formatter", "--edge"]
) |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def can_handle(self, uri):
"""Returns boolean denoting if specified URI can be handled by this extension"""
return False |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def clone_results_repo(dest_dir):
subprocess.check_call(
["git", "clone", "https://github.com/elopio/autopkgtest-results.git", dest_dir]
) |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def get_container(self):
"""Return container widget"""
return self._container |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def format_results(dest_dir, distros, day):
subprocess.check_call(
[
"/snap/bin/autopkgtest-results-formatter",
"--destination",
dest_dir,
"--distros",
*distros,
"--day",
day,
]
) |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def get_information(self):
"""Returns information about extension"""
icon = None
name = None
return icon, name |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def commit_and_push(repo_dir, day):
subprocess.check_call(
["git", "config", "--global", "user.email", "u1test+m-o@canonical.com"]
)
subprocess.check_call(["git", "config", "--global", "user.name", "snappy-m-o"])
subprocess.check_call(["git", "-C", repo_dir, "add", "--all"])
subprocess.check_call(
[
"git",
"-C",
repo_dir,
"commit",
"--message",
"Add the results for {}".format(day),
]
)
subprocess.check_call(
[
"git",
"-C",
repo_dir,
"push",
"https://{GH_TOKEN}@github.com/elopio/autopkgtest-results.git".format(
GH_TOKEN=os.environ.get("GH_TOKEN_PPA_AUTOPKGTEST_RESULTS")
),
]
) |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def unmount(self, uri):
"""Method called by the mount manager for unmounting the selected URI"""
pass |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def focus_object(self):
"""Method called by the mount manager for focusing main object"""
pass |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def __init__(self, gan=None, config=None, trainer=None):
super().__init__(config=config, gan=gan, trainer=trainer)
self.d_grads = None
self.g_grads = None |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def main():
# Contingency Table from Wilks (2011) Table 8.3
table = np.array([[50, 91, 71],
[47, 2364, 170],
[54, 205, 3288]])
mct = MulticlassContingencyTable(table, n_classes=table.shape[0],
class_names=np.arange(table.shape[0]).astype(str))
print(mct.peirce_skill_score())
print(mct.gerrity_score()) |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def gradients(self, d_grads, g_grads):
if self.d_grads is None:
self.d_grads = [torch.zeros_like(_g) for _g in d_grads]
self.g_grads = [torch.zeros_like(_g) for _g in g_grads] |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def __init__(self, table=None, n_classes=2, class_names=("1", "0")):
self.table = table
self.n_classes = n_classes
self.class_names = class_names
if table is None:
self.table = np.zeros((self.n_classes, self.n_classes), dtype=int) |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def __add__(self, other):
assert self.n_classes == other.n_classes, "Number of classes does not match"
return MulticlassContingencyTable(self.table + other.table,
n_classes=self.n_classes,
class_names=self.class_names) |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def peirce_skill_score(self):
"""
Multiclass Peirce Skill Score (also Hanssen and Kuipers score, True Skill Score)
"""
n = float(self.table.sum())
nf = self.table.sum(axis=1)
no = self.table.sum(axis=0)
correct = float(self.table.trace())
return (correct / n - (nf * no).sum() / n ** 2) / (1 - (no * no).sum() / n ** 2) |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def gerrity_score(self):
"""
Gerrity Score, which weights each cell in the contingency table by its observed relative frequency.
:return:
"""
k = self.table.shape[0]
n = float(self.table.sum())
p_o = self.table.sum(axis=0) / n
p_sum = np.cumsum(p_o)[:-1]
a = (1.0 - p_sum) / p_sum
s = np.zeros(self.table.shape, dtype=float)
for (i, j) in np.ndindex(*s.shape):
if i == j:
s[i, j] = 1.0 / (k - 1.0) * (np.sum(1.0 / a[0:j]) + np.sum(a[j:k - 1]))
elif i < j:
s[i, j] = 1.0 / (k - 1.0) * (np.sum(1.0 / a[0:i]) - (j - i) + np.sum(a[j:k - 1]))
else:
s[i, j] = s[j, i]
return np.sum(self.table / float(self.table.sum()) * s) |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def heidke_skill_score(self):
n = float(self.table.sum())
nf = self.table.sum(axis=1)
no = self.table.sum(axis=0)
correct = float(self.table.trace())
return (correct / n - (nf * no).sum() / n ** 2) / (1 - (nf * no).sum() / n ** 2) |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def git_checkout(git_url, git_branch=None, git_tag=None, git_hash=None):
git_dst = tempfile.mkdtemp()
g = GitManager(url=git_url, git_dst=git_dst, git_branch=git_branch, git_tag=git_tag, git_hash=git_hash)
g.run()
shutil.rmtree(git_dst) |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def test_git_tag():
""" Test checkout w/ Tag """
git_checkout(git_url='https://github.com/voltgrid/voltgrid-pie.git', git_branch=None, git_tag='v0.1.0') |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def test_git_branch():
""" Test checkout w/ Branch """
git_checkout(git_url='https://github.com/voltgrid/voltgrid-pie.git', git_branch='master', git_tag=None) |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def test_make_gym_venv_nostack(name, num_envs, state_shape, reward_scale):
seed = 0
frame_op = None
frame_op_len = None
venv = make_gym_venv(name, num_envs, seed, frame_op=frame_op, frame_op_len=frame_op_len, reward_scale=reward_scale)
venv.reset()
for i in range(5):
state, reward, done, info = venv.step([venv.action_space.sample()] * num_envs)
assert isinstance(state, np.ndarray)
assert state.shape == (num_envs,) + state_shape
assert isinstance(reward, np.ndarray)
assert reward.shape == (num_envs,)
assert isinstance(done, np.ndarray)
assert done.shape == (num_envs,)
assert len(info) == num_envs
venv.close() |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def compute_rbf_kernel_matrix(X):
"""Compute the RBF kernel matrix with sigma2 as the median pairwise
distance.
"""
sigma2 = np.median(pairwise_distances(X, metric='euclidean'))**2
K = pairwise_kernels(X, X, metric='rbf', gamma=1.0/sigma2, n_jobs=-1)
return K |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def test_make_gym_concat(name, num_envs, state_shape, reward_scale):
seed = 0
frame_op = 'concat' # used for image, or for concat vector
frame_op_len = 4
venv = make_gym_venv(name, num_envs, seed, frame_op=frame_op, frame_op_len=frame_op_len, reward_scale=reward_scale)
venv.reset()
for i in range(5):
state, reward, done, info = venv.step([venv.action_space.sample()] * num_envs)
assert isinstance(state, np.ndarray)
stack_shape = (num_envs, frame_op_len * state_shape[0],) + state_shape[1:]
assert state.shape == stack_shape
assert isinstance(reward, np.ndarray)
assert reward.shape == (num_envs,)
assert isinstance(done, np.ndarray)
assert done.shape == (num_envs,)
assert len(info) == num_envs
venv.close() |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def balanced_accuracy_scoring(clf, X, y):
"""Scoring function that computes the balanced accuracy to be used
internally in the cross-validation procedure.
"""
y_pred = clf.predict(X)
conf_mat = confusion_matrix(y, y_pred)
bal_acc = 0.
for i in range(len(conf_mat)):
bal_acc += (float(conf_mat[i, i])) / np.sum(conf_mat[i])
bal_acc /= len(conf_mat)
return bal_acc |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def test_make_gym_stack(name, num_envs, state_shape, reward_scale):
seed = 0
frame_op = 'stack' # used for rnn
frame_op_len = 4
venv = make_gym_venv(name, num_envs, seed, frame_op=frame_op, frame_op_len=frame_op_len, reward_scale=reward_scale)
venv.reset()
for i in range(5):
state, reward, done, info = venv.step([venv.action_space.sample()] * num_envs)
assert isinstance(state, np.ndarray)
stack_shape = (num_envs, frame_op_len,) + state_shape
assert state.shape == stack_shape
assert isinstance(reward, np.ndarray)
assert reward.shape == (num_envs,)
assert isinstance(done, np.ndarray)
assert done.shape == (num_envs,)
assert len(info) == num_envs
venv.close() |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def compute_svm_cv(K, y, C=100.0, n_folds=5,
scoring=balanced_accuracy_scoring):
"""Compute cross-validated score of SVM with given precomputed kernel.
"""
cv = StratifiedKFold(y, n_folds=n_folds)
clf = SVC(C=C, kernel='precomputed', class_weight='auto')
scores = cross_val_score(clf, K, y,
scoring=scoring, cv=cv)
return scores.mean() |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def compute_svm_subjects(K, y, n_folds=5):
"""
"""
cv = KFold(len(K)/2, n_folds)
scores = np.zeros(n_folds)
for i, (train, test) in enumerate(cv):
train_ids = np.concatenate((train, len(K)/2+train))
test_ids = np.concatenate((test, len(K)/2+test))
clf = SVC(kernel='precomputed')
clf.fit(K[train_ids, :][:, train_ids], y[train_ids])
scores[i] = clf.score(K[test_ids, :][:, train_ids], y[test_ids])
return scores.mean() |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def permutation_subjects(y):
"""Permute class labels of Contextual Disorder dataset.
"""
y_perm = np.random.randint(0, 2, len(y)/2)
y_perm = np.concatenate((y_perm, np.logical_not(y_perm).astype(int)))
return y_perm |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def permutation_subjects_ktst(y):
"""Permute class labels of Contextual Disorder dataset for KTST.
"""
yp = np.random.randint(0, 2, len(y)/2)
yp = np.concatenate((yp, np.logical_not(yp).astype(int)))
y_perm = np.arange(len(y))
for i in range(len(y)/2):
if yp[i] == 1:
y_perm[i] = len(y)/2+i
y_perm[len(y)/2+i] = i
return y_perm |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def compute_svm_score_nestedCV(K, y, n_folds,
scoring=balanced_accuracy_scoring,
random_state=None,
param_grid=[{'C': np.logspace(-5, 5, 25)}]):
"""Compute cross-validated score of SVM using precomputed kernel.
"""
cv = StratifiedKFold(y, n_folds=n_folds, shuffle=True,
random_state=random_state)
scores = np.zeros(n_folds)
for i, (train, test) in enumerate(cv):
cvclf = SVC(kernel='precomputed')
y_train = y[train]
cvcv = StratifiedKFold(y_train, n_folds=n_folds,
shuffle=True,
random_state=random_state)
clf = GridSearchCV(cvclf, param_grid=param_grid, scoring=scoring,
cv=cvcv, n_jobs=1)
clf.fit(K[train, :][:, train], y_train)
# print clf.best_params_
scores[i] = clf.score(K[test, :][:, train], y[test])
return scores.mean() |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def apply_svm(K, y, n_folds=5, iterations=10000, subjects=False, verbose=True,
random_state=None):
"""
Compute the balanced accuracy, its null distribution and the p-value.
Parameters:
----------
K: array-like
Kernel matrix
y: array_like
class labels
cv: Number of folds in the stratified cross-validation
verbose: bool
Verbosity
Returns:
-------
acc: float
Average balanced accuracy.
acc_null: array
Null distribution of the balanced accuracy.
p_value: float
p-value
"""
# Computing the accuracy
param_grid = [{'C': np.logspace(-5, 5, 20)}]
if subjects:
acc = compute_svm_subjects(K, y, n_folds)
else:
acc = compute_svm_score_nestedCV(K, y, n_folds, param_grid=param_grid,
random_state=random_state)
if verbose:
print("Mean balanced accuracy = %s" % (acc))
print("Computing the null-distribution.")
# Computing the null-distribution
# acc_null = np.zeros(iterations)
# for i in range(iterations):
# if verbose and (i % 1000) == 0:
# print(i),
# stdout.flush()
# y_perm = np.random.permutation(y)
# acc_null[i] = compute_svm_score_nestedCV(K, y_perm, n_folds,
# param_grid=param_grid)
# if verbose:
# print ''
# Computing the null-distribution
if subjects:
yis = [permutation_subjects(y) for i in range(iterations)]
acc_null = Parallel(n_jobs=-1)(delayed(compute_svm_subjects)(K, yis[i], n_folds) for i in range(iterations))
else:
yis = [np.random.permutation(y) for i in range(iterations)]
acc_null = Parallel(n_jobs=-1)(delayed(compute_svm_score_nestedCV)(K, yis[i], n_folds, scoring=balanced_accuracy_scoring, param_grid=param_grid) for i in range(iterations))
# acc_null = Parallel(n_jobs=-1)(delayed(compute_svm_cv)(K, yis[i], C=100., n_folds=n_folds) for i in range(iterations))
p_value = max(1.0 / iterations, (acc_null > acc).sum()
/ float(iterations))
if verbose:
print("p-value ~= %s \t (resolution : %s)" % (p_value, 1.0/iterations))
return acc, acc_null, p_value |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def apply_ktst(K, y, iterations=10000, subjects=False, verbose=True):
"""
Compute MMD^2_u, its null distribution and the p-value of the
kernel two-sample test.
Parameters:
----------
K: array-like
Kernel matrix
y: array_like
class labels
verbose: bool
Verbosity
Returns:
-------
mmd2u: float
MMD^2_u value.
acc_null: array
Null distribution of the MMD^2_u
p_value: float
p-value
"""
assert len(np.unique(y)) == 2, 'KTST only works on binary problems'
# Assuming that the first m rows of the kernel matrix are from one
# class and the other n rows from the second class.
m = len(y[y == 0])
n = len(y[y == 1])
mmd2u = MMD2u(K, m, n)
if verbose:
print("MMD^2_u = %s" % mmd2u)
print("Computing the null distribution.")
if subjects:
perms = [permutation_subjects_ktst(y) for i in range(iterations)]
mmd2u_null = compute_null_distribution_given_permutations(K, m, n,
perms,
iterations)
else:
mmd2u_null = compute_null_distribution(K, m, n, iterations,
verbose=verbose)
p_value = max(1.0/iterations, (mmd2u_null > mmd2u).sum()
/ float(iterations))
if verbose:
print("p-value ~= %s \t (resolution : %s)" % (p_value, 1.0/iterations))
return mmd2u, mmd2u_null, p_value |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def test_login(self, mock_login_with_token, mock_input, mock_open_url):
quilt3.login()
url = quilt3.session.get_registry_url()
mock_open_url.assert_called_with(f'{url}/login')
mock_login_with_token.assert_called_with('123456') |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def decode(value):
if isinstance(value, bytes):
value = value.decode(errors="surrogateescape")
for char in ("\\", "\n", "\t"):
value = value.replace(
char.encode(encoding="unicode-escape").decode(), char
)
return value |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def test_login_with_token(self, mock_save_credentials, mock_save_auth):
url = quilt3.session.get_registry_url()
mock_auth = dict(
refresh_token='refresh-token',
access_token='access-token',
expires_at=123456789
)
self.requests_mock.add(
responses.POST,
f'{url}/api/token',
json=mock_auth,
status=200
)
self.requests_mock.add(
responses.GET,
f'{url}/api/auth/get_credentials',
json=dict(
AccessKeyId='access-key',
SecretAccessKey='secret-key',
SessionToken='session-token',
Expiration="2019-05-28T23:58:07+00:00"
),
status=200
)
quilt3.session.login_with_token('123456')
mock_save_auth.assert_called_with({url: mock_auth})
mock_save_credentials.assert_called_with(dict(
access_key='access-key',
secret_key='secret-key',
token='session-token',
expiry_time="2019-05-28T23:58:07+00:00"
)) |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def encode(value):
if isinstance(value, bytes):
value = value.decode(errors="surrogateescape")
for char in ("\\", "\n", "\t"):
value = value.replace(
char, char.encode(encoding="unicode-escape").decode()
)
return value |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def format_date(date):
return date.replace(tzinfo=datetime.timezone.utc, microsecond=0).isoformat() |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def deserialize(self, value):
"""Cast raw string to appropriate type."""
return decode(value) |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def serialize(self, value, display=False):
"""Convert value back to string for saving."""
if value is None:
return ""
return str(value) |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def deserialize(self, value):
return DeprecatedValue() |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def serialize(self, value, display=False):
return DeprecatedValue() |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def __init__(self, optional=False, choices=None):
self._required = not optional
self._choices = choices |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def deserialize(self, value):
value = decode(value).strip()
validators.validate_required(value, self._required)
if not value:
return None
validators.validate_choice(value, self._choices)
return value |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def serialize(self, value, display=False):
if value is None:
return ""
return encode(value) |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def __init__(self, optional=False, choices=None):
self._required = not optional
self._choices = None # Choices doesn't make sense for secrets |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def serialize(self, value, display=False):
if value is not None and display:
return "********"
return super().serialize(value, display) |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def __init__(
self, minimum=None, maximum=None, choices=None, optional=False
):
self._required = not optional
self._minimum = minimum
self._maximum = maximum
self._choices = choices |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def deserialize(self, value):
value = decode(value)
validators.validate_required(value, self._required)
if not value:
return None
value = int(value)
validators.validate_choice(value, self._choices)
validators.validate_minimum(value, self._minimum)
validators.validate_maximum(value, self._maximum)
return value |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def __init__(self, optional=False):
self._required = not optional |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def deserialize(self, value):
value = decode(value)
validators.validate_required(value, self._required)
if not value:
return None
if value.lower() in self.true_values:
return True
elif value.lower() in self.false_values:
return False
raise ValueError(f"invalid value for boolean: {value!r}") |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def serialize(self, value, display=False):
if value is True:
return "true"
elif value in (False, None):
return "false"
else:
raise ValueError(f"{value!r} is not a boolean") |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def deserialize(self, value):
value = decode(value)
if "\n" in value:
values = re.split(r"\s*\n\s*", value)
else:
values = re.split(r"\s*,\s*", value)
values = tuple(v.strip() for v in values if v.strip())
validators.validate_required(values, self._required)
return tuple(values) |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def serialize(self, value, display=False):
if not value:
return ""
return "\n " + "\n ".join(encode(v) for v in value if v) |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def deserialize(self, value):
value = decode(value)
validators.validate_choice(value.lower(), log.COLORS)
return value.lower() |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def serialize(self, value, display=False):
if value.lower() in log.COLORS:
return encode(value.lower())
return "" |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def deserialize(self, value):
value = decode(value)
validators.validate_choice(value.lower(), self.levels.keys())
return self.levels.get(value.lower()) |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def serialize(self, value, display=False):
lookup = {v: k for k, v in self.levels.items()}
if value in lookup:
return encode(lookup[value])
return "" |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def deserialize(self, value, display=False):
value = decode(value).strip()
validators.validate_required(value, self._required)
if not value:
return None
socket_path = path.get_unix_socket_path(value)
if socket_path is not None:
path_str = Path(not self._required).deserialize(socket_path)
return f"unix:{path_str}"
try:
socket.getaddrinfo(value, None)
except OSError:
raise ValueError("must be a resolveable hostname or valid IP")
return value |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def __init__(self, choices=None, optional=False):
super().__init__(
minimum=0, maximum=2 ** 16 - 1, choices=choices, optional=optional
) |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def __new__(cls, original, expanded):
return super().__new__(cls, expanded) |
def dist(a, b):
return sum((i-j)**2 for i, j in zip(a, b)) | def __init__(self, original, expanded):
self.original = original |
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