code string | signature string | docstring string | loss_without_docstring float64 | loss_with_docstring float64 | factor float64 |
|---|---|---|---|---|---|
p = np.power(z, 1. / self.power)
return p | def inverse(self, z) | Inverse of the power transform link function
Parameters
----------
`z` : array-like
Value of the transformed mean parameters at `p`
Returns
-------
`p` : array
Mean parameters
Notes
-----
g^(-1)(z`) = `z`**(1/`power`) | 9.658315 | 6.584755 | 1.466769 |
return self.power * np.power(p, self.power - 1) | def deriv(self, p) | Derivative of the power transform
Parameters
----------
p : array-like
Mean parameters
Returns
--------
g'(p) : array
Derivative of power transform of `p`
Notes
-----
g'(`p`) = `power` * `p`**(`power` - 1) | 6.642684 | 4.747916 | 1.399074 |
return self.power * (self.power - 1) * np.power(p, self.power - 2) | def deriv2(self, p) | Second derivative of the power transform
Parameters
----------
p : array-like
Mean parameters
Returns
--------
g''(p) : array
Second derivative of the power transform of `p`
Notes
-----
g''(`p`) = `power` * (`power` - 1) ... | 4.541001 | 3.011153 | 1.50806 |
return np.power(z, (1 - self.power)/self.power) / self.power | def inverse_deriv(self, z) | Derivative of the inverse of the power transform
Parameters
----------
z : array-like
`z` is usually the linear predictor for a GLM or GEE model.
Returns
-------
g^(-1)'(z) : array
The value of the derivative of the inverse of the power transform... | 7.495506 | 12.126756 | 0.618097 |
p = self._clean(p)
return 1. / self.dbn.pdf(self.dbn.ppf(p)) | def deriv(self, p) | Derivative of CDF link
Parameters
----------
p : array-like
mean parameters
Returns
-------
g'(p) : array
The derivative of CDF transform at `p`
Notes
-----
g'(`p`) = 1./ `dbn`.pdf(`dbn`.ppf(`p`)) | 9.058982 | 3.891714 | 2.327762 |
from statsmodels.tools.numdiff import approx_fprime
p = np.atleast_1d(p)
# Note: special function for norm.ppf does not support complex
return np.diag(approx_fprime(p, self.deriv, centered=True)) | def deriv2(self, p) | Second derivative of the link function g''(p)
implemented through numerical differentiation | 7.519336 | 7.523905 | 0.999393 |
a = np.pi * (p - 0.5)
d2 = 2 * np.pi**2 * np.sin(a) / np.cos(a)**3
return d2 | def deriv2(self, p) | Second derivative of the Cauchy link function.
Parameters
----------
p: array-like
Probabilities
Returns
-------
g''(p) : array
Value of the second derivative of Cauchy link function at `p` | 4.148437 | 5.070708 | 0.818118 |
p = self._clean(p)
return 1. / ((p - 1) * (np.log(1 - p))) | def deriv(self, p) | Derivative of C-Log-Log transform link function
Parameters
----------
p : array-like
Mean parameters
Returns
-------
g'(p) : array
The derivative of the CLogLog transform link function
Notes
-----
g'(p) = - 1 / ((p-1)*log... | 8.379749 | 5.548458 | 1.510284 |
p = self._clean(p)
fl = np.log(1 - p)
d2 = -1 / ((1 - p)**2 * fl)
d2 *= 1 + 1 / fl
return d2 | def deriv2(self, p) | Second derivative of the C-Log-Log ink function
Parameters
----------
p : array-like
Mean parameters
Returns
-------
g''(p) : array
The second derivative of the CLogLog link function | 6.964714 | 8.762305 | 0.794849 |
'''
Second derivative of the negative binomial link function.
Parameters
----------
p : array-like
Mean parameters
Returns
-------
g''(p) : array
The second derivative of the negative binomial transform link
function
... | def deriv2(self,p) | Second derivative of the negative binomial link function.
Parameters
----------
p : array-like
Mean parameters
Returns
-------
g''(p) : array
The second derivative of the negative binomial transform link
function
Notes
... | 5.38317 | 1.625932 | 3.310822 |
'''
Derivative of the inverse of the negative binomial transform
Parameters
-----------
z : array-like
Usually the linear predictor for a GLM or GEE model
Returns
-------
g^(-1)'(z) : array
The value of the derivative of the inver... | def inverse_deriv(self, z) | Derivative of the inverse of the negative binomial transform
Parameters
-----------
z : array-like
Usually the linear predictor for a GLM or GEE model
Returns
-------
g^(-1)'(z) : array
The value of the derivative of the inverse of the negative
... | 8.844493 | 2.214594 | 3.99373 |
try:
return self._databases
except AttributeError:
self._databases = self.einfo().databases
return self._databases | def databases(self) | list of databases available from eutils (per einfo query) | 5.859485 | 3.113484 | 1.88197 |
if db is None:
return EInfoResult(self._qs.einfo()).dblist
return EInfoResult(self._qs.einfo({'db': db, 'version': '2.0'})).dbinfo | def einfo(self, db=None) | query the einfo endpoint
:param db: string (optional)
:rtype: EInfo or EInfoDB object
If db is None, the reply is a list of databases, which is returned
in an EInfo object (which has a databases() method).
If db is not None, the reply is information about the specified
... | 9.268534 | 5.758118 | 1.609646 |
esr = ESearchResult(self._qs.esearch({'db': db, 'term': term}))
if esr.count > esr.retmax:
logger.warning("NCBI found {esr.count} results, but we truncated the reply at {esr.retmax}"
" results; see https://github.com/biocommons/eutils/issues/124/".format(esr=... | def esearch(self, db, term) | query the esearch endpoint | 7.249032 | 7.576406 | 0.95679 |
db = db.lower()
xml = self._qs.efetch({'db': db, 'id': str(id)})
doc = le.XML(xml)
if db in ['gene']:
return EntrezgeneSet(doc)
if db in ['nuccore', 'nucest', 'protein']:
# TODO: GBSet is misnamed; it should be GBSeq and get the GBSeq XML node as ... | def efetch(self, db, id) | query the efetch endpoint | 6.313598 | 6.182163 | 1.02126 |
if eventObj.type not in (MOUSEMOTION, MOUSEBUTTONUP, MOUSEBUTTONDOWN) or not self._visible:
# The button only cares bout mouse-related events (or no events, if it is invisible)
return []
retVal = []
hasExited = False
if not self.mouseOverButton and sel... | def handleEvent(self, eventObj) | All MOUSEMOTION, MOUSEBUTTONUP, MOUSEBUTTONDOWN event objects
created by Pygame should be passed to this method. handleEvent() will
detect if the event is relevant to this button and change its state.
There are two ways that your code can respond to button-events. One is
to inherit the ... | 2.818779 | 2.534088 | 1.112344 |
if self._visible:
if self.buttonDown:
surfaceObj.blit(self.surfaceDown, self._rect)
elif self.mouseOverButton:
surfaceObj.blit(self.surfaceHighlight, self._rect)
else:
surfaceObj.blit(self.surfaceNormal, self._rect) | def draw(self, surfaceObj) | Blit the current button's appearance to the surface object. | 2.931409 | 2.690086 | 1.089708 |
if self.customSurfaces:
self.surfaceNormal = pygame.transform.smoothscale(self.origSurfaceNormal, self._rect.size)
self.surfaceDown = pygame.transform.smoothscale(self.origSurfaceDown, self._rect.size)
self.surfaceHighlight = pygame.transform.smoothscale(self... | def _update(self) | Redraw the button's Surface object. Call this method when the button has changed appearance. | 1.657754 | 1.573103 | 1.053811 |
if downSurface is None:
downSurface = normalSurface
if highlightSurface is None:
highlightSurface = normalSurface
if type(normalSurface) == str:
self.origSurfaceNormal = pygame.image.load(normalSurface)
if type(downSurface) == str:
... | def setSurfaces(self, normalSurface, downSurface=None, highlightSurface=None) | Switch the button to a custom image type of button (rather than a
text button). You can specify either a pygame.Surface object or a
string of a filename to load for each of the three button appearance
states. | 1.898503 | 1.792674 | 1.059034 |
# TODO: change the links class attribute in the families to hold
# meaningful information instead of a list of links instances such as
# [<statsmodels.family.links.Log object at 0x9a4240c>,
# <statsmodels.family.links.Power object at 0x9a423ec>,
# <statsmodels.family.l... | def _setlink(self, link) | Helper method to set the link for a family.
Raises a ValueError exception if the link is not available. Note that
the error message might not be that informative because it tells you
that the link should be in the base class for the link function.
See glm.GLM for a list of appropriate... | 5.77483 | 5.291931 | 1.091252 |
r
return 1. / (self.link.deriv(mu)**2 * self.variance(mu)) | def weights(self, mu) | r"""
Weights for IRLS steps
Parameters
----------
mu : array-like
The transformed mean response variable in the exponential family
Returns
-------
w : array
The weights for the IRLS steps | 16.942329 | 19.526638 | 0.867652 |
r
loglike = np.sum(freq_weights * (endog * np.log(mu) - mu -
special.gammaln(endog + 1)))
return scale * loglike | def loglike(self, endog, mu, freq_weights=1., scale=1.) | r"""
The log-likelihood function in terms of the fitted mean response.
Parameters
----------
endog : array-like
Endogenous response variable
mu : array-like
Fitted mean response variable
freq_weights : array-like
1d array of frequency ... | 4.760228 | 5.547285 | 0.858119 |
return (endog - mu) / np.sqrt(self.variance(mu)) / scale | def resid_dev(self, endog, mu, scale=1.) | Gaussian deviance residuals
Parameters
-----------
endog : array-like
Endogenous response variable
mu : array-like
Fitted mean response variable
scale : float, optional
An optional argument to divide the residuals by scale. The default
... | 7.153401 | 12.23319 | 0.584754 |
return np.sum((freq_weights * (endog - mu)**2)) / scale | def deviance(self, endog, mu, freq_weights=1., scale=1.) | Gaussian deviance function
Parameters
----------
endog : array-like
Endogenous response variable
mu : array-like
Fitted mean response variable
freq_weights : array-like
1d array of frequency weights. The default is 1.
scale : float, op... | 4.947443 | 8.734039 | 0.566455 |
if isinstance(self.link, L.Power) and self.link.power == 1:
# This is just the loglikelihood for classical OLS
nobs2 = endog.shape[0] / 2.
SSR = np.sum((endog-self.fitted(mu))**2, axis=0)
llf = -np.log(SSR) * nobs2
llf -= (1+np.log(np.pi/nobs2... | def loglike(self, endog, mu, freq_weights=1., scale=1.) | The log-likelihood in terms of the fitted mean response.
Parameters
----------
endog : array-like
Endogenous response variable
mu : array-like
Fitted mean response variable
freq_weights : array-like
1d array of frequency weights. The default i... | 5.202494 | 5.179352 | 1.004468 |
r
endog_mu = self._clean(endog/mu)
return 2*np.sum(freq_weights*((endog-mu)/mu-np.log(endog_mu))) | def deviance(self, endog, mu, freq_weights=1., scale=1.) | r"""
Gamma deviance function
Parameters
-----------
endog : array-like
Endogenous response variable
mu : array-like
Fitted mean response variable
freq_weights : array-like
1d array of frequency weights. The default is 1.
scale ... | 8.755331 | 9.060802 | 0.966287 |
r
endog_mu = self._clean(endog / mu)
return np.sign(endog - mu) * np.sqrt(-2 * (-(endog - mu)/mu +
np.log(endog_mu))) | def resid_dev(self, endog, mu, scale=1.) | r"""
Gamma deviance residuals
Parameters
-----------
endog : array-like
Endogenous response variable
mu : array-like
Fitted mean response variable
scale : float, optional
An optional argument to divide the residuals by scale. The defau... | 10.004321 | 10.349361 | 0.966661 |
r
return - 1./scale * np.sum((endog/mu + np.log(mu) + (scale - 1) *
np.log(endog) + np.log(scale) + scale *
special.gammaln(1./scale)) * freq_weights) | def loglike(self, endog, mu, freq_weights=1., scale=1.) | r"""
The log-likelihood function in terms of the fitted mean response.
Parameters
----------
endog : array-like
Endogenous response variable
mu : array-like
Fitted mean response variable
freq_weights : array-like
1d array of frequency ... | 6.594404 | 7.321396 | 0.900703 |
'''
Initialize the response variable.
Parameters
----------
endog : array
Endogenous response variable
Returns
--------
If `endog` is binary, returns `endog`
If `endog` is a 2d array, then the input is assumed to be in the format
... | def initialize(self, endog, freq_weights) | Initialize the response variable.
Parameters
----------
endog : array
Endogenous response variable
Returns
--------
If `endog` is binary, returns `endog`
If `endog` is a 2d array, then the input is assumed to be in the format
(successes, fai... | 5.626321 | 2.70179 | 2.082442 |
r'''
Deviance function for either Bernoulli or Binomial data.
Parameters
----------
endog : array-like
Endogenous response variable (already transformed to a probability
if appropriate).
mu : array
Fitted mean response variable
... | def deviance(self, endog, mu, freq_weights=1, scale=1., axis=None) | r'''
Deviance function for either Bernoulli or Binomial data.
Parameters
----------
endog : array-like
Endogenous response variable (already transformed to a probability
if appropriate).
mu : array
Fitted mean response variable
freq_we... | 3.055517 | 1.85659 | 1.645768 |
r
mu = self.link._clean(mu)
if np.shape(self.n) == () and self.n == 1:
one = np.equal(endog, 1)
return np.sign(endog-mu)*np.sqrt(-2 *
np.log(one * mu + (1 - one) *
(1 - mu)))... | def resid_dev(self, endog, mu, scale=1.) | r"""
Binomial deviance residuals
Parameters
-----------
endog : array-like
Endogenous response variable
mu : array-like
Fitted mean response variable
scale : float, optional
An optional argument to divide the residuals by scale. The de... | 3.842623 | 3.888746 | 0.988139 |
r
if np.shape(self.n) == () and self.n == 1:
return scale * np.sum((endog * np.log(mu/(1 - mu) + 1e-200) +
np.log(1 - mu)) * freq_weights)
else:
y = endog * self.n # convert back to successes
return scale * np.sum((special.... | def loglike(self, endog, mu, freq_weights=1, scale=1.) | r"""
The log-likelihood function in terms of the fitted mean response.
Parameters
----------
endog : array-like
Endogenous response variable
mu : array-like
Fitted mean response variable
freq_weights : array-like
1d array of frequency ... | 3.163597 | 3.35636 | 0.942568 |
'''
The Anscombe residuals
Parameters
----------
endog : array-like
Endogenous response variable
mu : array-like
Fitted mean response variable
Returns
-------
resid_anscombe : array
The Anscombe residuals as de... | def resid_anscombe(self, endog, mu) | The Anscombe residuals
Parameters
----------
endog : array-like
Endogenous response variable
mu : array-like
Fitted mean response variable
Returns
-------
resid_anscombe : array
The Anscombe residuals as defined below.
... | 4.768886 | 1.787251 | 2.66828 |
for entry in self.entries:
if entry.uuid == uuid:
return entry
raise EntryNotFoundError("Entry not found for uuid: %s" % uuid) | def find_by_uuid(self, uuid) | Find an entry by uuid.
:raise: EntryNotFoundError | 3.171579 | 2.819734 | 1.124779 |
for entry in self.entries:
if entry.title == title:
return entry
raise EntryNotFoundError("Entry not found for title: %s" % title) | def find_by_title(self, title) | Find an entry by exact title.
:raise: EntryNotFoundError | 3.123904 | 2.868566 | 1.089012 |
entries = []
# Exact matches trump
for entry in self.entries:
if entry.title == title:
entries.append(entry)
if entries:
return self._filter_entries(entries, ignore_groups)
# Case insensitive matches next.
title_lower = tit... | def fuzzy_search_by_title(self, title, ignore_groups=None) | Find an entry by by fuzzy match.
This will check things such as:
* case insensitive matching
* typo checks
* prefix matches
If the ``ignore_groups`` argument is provided, then any matching
entries in the ``ignore_groups`` list will not be returned. This
... | 2.400787 | 2.589288 | 0.9272 |
configuration = config.Configuration()
pegtree = pegnode.parse(self.filestring)
for section_node in pegtree:
if isinstance(section_node, pegnode.GlobalSection):
configuration.globall = self.build_global(section_node)
elif isinstance(section_node, ... | def build_configuration(self) | Parse the haproxy config file
Raises:
Exception: when there are unsupported section
Returns:
config.Configuration: haproxy config object | 2.336828 | 2.315208 | 1.009338 |
config_block_lines = self.__build_config_block(
global_node.config_block)
return config.Global(config_block=config_block_lines) | def build_global(self, global_node) | parse `global` section, and return the config.Global
Args:
global_node (TreeNode): `global` section treenode
Returns:
config.Global: an object | 5.619693 | 6.289046 | 0.893568 |
node_lists = []
for line_node in config_block_node:
if isinstance(line_node, pegnode.ConfigLine):
node_lists.append(self.__build_config(line_node))
elif isinstance(line_node, pegnode.OptionLine):
node_lists.append(self.__build_option(line... | def __build_config_block(self, config_block_node) | parse `config_block` in each section
Args:
config_block_node (TreeNode): Description
Returns:
[line_node1, line_node2, ...] | 1.940963 | 1.947779 | 0.996501 |
proxy_name = defaults_node.defaults_header.proxy_name.text
config_block_lines = self.__build_config_block(
defaults_node.config_block)
return config.Defaults(
name=proxy_name,
config_block=config_block_lines) | def build_defaults(self, defaults_node) | parse `defaults` sections, and return a config.Defaults
Args:
defaults_node (TreeNode): Description
Returns:
config.Defaults: an object | 5.697782 | 5.470243 | 1.041596 |
proxy_name = userlist_node.userlist_header.proxy_name.text
config_block_lines = self.__build_config_block(
userlist_node.config_block)
return config.Userlist(
name=proxy_name,
config_block=config_block_lines) | def build_userlist(self, userlist_node) | parse `userlist` sections, and return a config.Userlist | 4.858755 | 4.26385 | 1.139523 |
proxy_name = listen_node.listen_header.proxy_name.text
service_address_node = listen_node.listen_header.service_address
# parse the config block
config_block_lines = self.__build_config_block(
listen_node.config_block)
# parse host and port
host, po... | def build_listen(self, listen_node) | parse `listen` sections, and return a config.Listen
Args:
listen_node (TreeNode): Description
Returns:
config.Listen: an object | 3.920623 | 3.78354 | 1.036231 |
proxy_name = frontend_node.frontend_header.proxy_name.text
service_address_node = frontend_node.frontend_header.service_address
# parse the config block
config_block_lines = self.__build_config_block(
frontend_node.config_block)
# parse host and port
... | def build_frontend(self, frontend_node) | parse `frontend` sections, and return a config.Frontend
Args:
frontend_node (TreeNode): Description
Raises:
Exception: Description
Returns:
config.Frontend: an object | 3.975589 | 3.847882 | 1.033189 |
proxy_name = backend_node.backend_header.proxy_name.text
config_block_lines = self.__build_config_block(
backend_node.config_block)
return config.Backend(name=proxy_name, config_block=config_block_lines) | def build_backend(self, backend_node) | parse `backend` sections
Args:
backend_node (TreeNode): Description
Returns:
config.Backend: an object | 5.399443 | 5.315832 | 1.015729 |
try:
return self.template_class(self.engine.from_string(template_code))
except mako_exceptions.SyntaxException as exc:
raise TemplateSyntaxError(exc.args) | def from_string(self, template_code) | Trying to compile and return the compiled template code.
:raises: TemplateSyntaxError if there's a syntax error in
the template.
:param template_code: Textual template source.
:return: Returns a compiled Mako template. | 4.045626 | 4.280306 | 0.945172 |
try:
return self.template_class(self.engine.get_template(template_name))
except mako_exceptions.TemplateLookupException as exc:
raise TemplateDoesNotExist(exc.args)
except mako_exceptions.CompileException as exc:
raise TemplateSyntaxError(exc.args) | def get_template(self, template_name) | Trying to get a compiled template given a template name
:param template_name: The template name.
:raises: - TemplateDoesNotExist if no such template exists.
- TemplateSyntaxError if we couldn't compile the
template using Mako syntax.
:return: Compiled Templa... | 3.110271 | 2.769151 | 1.123186 |
if context is None:
context = {}
context['static'] = static
context['url'] = self.get_reverse_url()
if request is not None:
# As Django doesn't have a global request object,
# it's useful to put it in the context.
context['reques... | def render(self, context=None, request=None) | Render the template with a given context. Here we're adding
some context variables that are required for all templates in
the system like the statix url and the CSRF tokens, etc.
:param context: It must be a dict if provided
:param request: It must be a django.http.HttpRequest if provid... | 4.518238 | 4.558494 | 0.991169 |
if (hasattr(self, 'mle_settings') and
self.mle_settings['optimizer'] in ['l1', 'l1_cvxopt_cp']):
dot_fun = nan_dot
else:
dot_fun = np.dot
if (cov_p is None and self.normalized_cov_params is None and
not hasattr(self, 'cov_params_d... | def cov_params(self, r_matrix=None, column=None, scale=None, cov_p=None,
other=None) | Returns the variance/covariance matrix.
The variance/covariance matrix can be of a linear contrast
of the estimates of params or all params multiplied by scale which
will usually be an estimate of sigma^2. Scale is assumed to be
a scalar.
Parameters
----------
r_... | 2.619558 | 2.59596 | 1.00909 |
bse = self.bse
if self.use_t:
dist = stats.t
df_resid = getattr(self, 'df_resid_inference', self.df_resid)
q = dist.ppf(1 - alpha / 2, df_resid)
else:
dist = stats.norm
q = dist.ppf(1 - alpha / 2)
if cols is None:
... | def conf_int(self, alpha=.05, cols=None, method='default') | Returns the confidence interval of the fitted parameters.
Parameters
----------
alpha : float, optional
The significance level for the confidence interval.
ie., The default `alpha` = .05 returns a 95% confidence
interval.
cols : array-lik... | 2.301911 | 2.359039 | 0.975783 |
seqids = self._xml_root.xpath('GBSeq_other-seqids/GBSeqid/text()')
return {t: l.rstrip('|').split('|')
for t, _, l in [si.partition('|') for si in seqids]} | def other_seqids(self) | returns a dictionary of sequence ids, like {'gi': ['319655736'], 'ref': ['NM_000551.3']} | 10.742264 | 8.746676 | 1.228154 |
def MD5Hash(password):
md5_password = md5.new(password)
password_md5 = md5_password.hexdigest()
return password_md5 | Returns md5 hash of a string.
@param password (string) - String to be hashed.
@return (string) - Md5 hash of password. | null | null | null | |
def setVerbosity(self, verbose):
if not (verbose == True or verbose == False):
return False
else:
self.__verbose__ = verbose
return True | Set verbosity of the SenseApi object.
@param verbose (boolean) - True of False
@return (boolean) - Boolean indicating whether setVerbosity succeeded | null | null | null | |
def setServer(self, server):
if server == 'live':
self.__server__ = server
self.__server_url__ = 'api.sense-os.nl'
self.setUseHTTPS()
return True
elif server == 'dev':
self.__server__ = server
self.__server_url__ =... | Set server to interact with.
@param server (string) - 'live' for live server, 'dev' for test server, 'rc' for release candidate
@return (boolean) - Boolean indicating whether setServer succeeded | null | null | null | |
def getAllSensors(self):
j = 0
sensors = []
parameters = {'page':0, 'per_page':1000, 'owned':1}
while True:
parameters['page'] = j
if self.SensorsGet(parameters):
s = json.loads(self.getResponse())['sensors']
senso... | Retrieve all the user's own sensors by iterating over the SensorsGet function
@return (list) - Array of sensors | null | null | null | |
def findSensor(self, sensors, sensor_name, device_type = None):
if device_type == None:
for sensor in sensors:
if sensor['name'] == sensor_name:
return sensor['id']
else:
for sensor in sensors:
if sensor['name... | Find a sensor in the provided list of sensors
@param sensors (list) - List of sensors to search in
@param sensor_name (string) - Name of sensor to find
@param device_type (string) - Device type of sensor to find, can be None
@return (string... | null | null | null | |
def AuthenticateSessionId(self, username, password):
self.__setAuthenticationMethod__('authenticating_session_id')
parameters = {'username':username, 'password':password}
if self.__SenseApiCall__("/login.json", "POST", parameters = parameters):
try:
... | Authenticate using a username and password.
The SenseApi object will store the obtained session_id internally until a call to LogoutSessionId is performed.
@param username (string) - CommonSense username
@param password (string) - MD5Hash of CommonSense password
... | null | null | null | |
def LogoutSessionId(self):
if self.__SenseApiCall__('/logout.json', 'POST'):
self.__setAuthenticationMethod__('not_authenticated')
return True
else:
self.__error__ = "api call unsuccessful"
return False | Logout the current session_id from CommonSense
@return (bool) - Boolean indicating whether LogoutSessionId was successful | null | null | null | |
def AuthenticateOauth (self, oauth_token_key, oauth_token_secret, oauth_consumer_key, oauth_consumer_secret):
self.__oauth_consumer__ = oauth.OAuthConsumer(str(oauth_consumer_key), str(oauth_consumer_secret))
self.__oauth_token__ = oauth.OAuthToken(str(oauth_token_key), str(oauth_token_secre... | Authenticate using Oauth
@param oauth_token_key (string) - A valid oauth token key obtained from CommonSense
@param oauth_token_secret (string) - A valid oauth token secret obtained from CommonSense
@param oauth_consumer_key (string) - A valid oauth consumer key obta... | null | null | null | |
def OauthGetAccessToken(self):
self.__setAuthenticationMethod__('authenticating_oauth')
# obtain access token
oauth_request = oauth.OAuthRequest.from_consumer_and_token(self.__oauth_consumer__, \
token = self.... | Use token_verifier to obtain an access token for the user. If this function returns True, the clients __oauth_token__ member
contains the access token.
@return (boolean) - Boolean indicating whether OauthGetRequestToken was successful | null | null | null | |
def OauthAuthorizeApplication(self, oauth_duration = 'hour'):
if self.__session_id__ == '':
self.__error__ = "not logged in"
return False
# automatically get authorization for the application
parameters = {'oauth_token':self.__oauth_token__.key, 'tok_expir':s... | Authorize an application using oauth. If this function returns True, the obtained oauth token can be retrieved using getResponse and will be in url-parameters format.
TODO: allow the option to ask the user himself for permission, instead of doing this automatically. Especially important for web application... | null | null | null | |
def SensorsGet(self, parameters = None, sensor_id = -1):
url = ''
if parameters is None and sensor_id <> -1:
url = '/sensors/{0}.json'.format(sensor_id)
else:
url = '/sensors.json'
if self.__SenseApiCall__(url, 'GET', parameters = parameters):
... | Retrieve sensors from CommonSense, according to parameters, or by sensor id.
If successful, result can be obtained by a call to getResponse(), and should be a json string.
@param parameters (dictionary) (optional) - Dictionary containing the parameters for the api-call.
... | null | null | null | |
def SensorsDelete(self, sensor_id):
if self.__SenseApiCall__('/sensors/{0}.json'.format(sensor_id), 'DELETE'):
return True
else:
self.__error__ = "api call unsuccessful"
return False | Delete a sensor from CommonSense.
@param sensor_id (int) - Sensor id of sensor to delete from CommonSense.
@return (bool) - Boolean indicating whether SensorsDelete was successful. | null | null | null | |
def SensorsPost(self, parameters):
if self.__SenseApiCall__('/sensors.json', 'POST', parameters = parameters):
return True
else:
self.__error__ = "api call unsuccessful"
return False | Create a sensor in CommonSense.
If SensorsPost is successful, the sensor details, including its sensor_id, can be obtained by a call to getResponse(), and should be a json string.
@param parameters (dictonary) - Dictionary containing the details of the sensor to be created.
... | null | null | null | |
def SensorsMetatagsGet(self, parameters, namespace = None):
ns = "default" if namespace is None else namespace
parameters['namespace'] = ns
if self.__SenseApiCall__('/sensors/metatags.json', 'GET', parameters = parameters):
return True
else:
self._... | Retrieve sensors with their metatags.
@param namespace (string) - Namespace for which to retrieve the metatags.
@param parameters (dictionary - Dictionary containing further parameters.
@return (bool) - Boolean indicating whether SensorsMetatagsget was ... | null | null | null | |
def GroupSensorsMetatagsGet(self, group_id, parameters, namespace = None):
ns = "default" if namespace is None else namespace
parameters['namespace'] = ns
if self.__SenseApiCall__('/groups/{0}/sensors/metatags.json'.format(group_id), 'GET', parameters = parameters):
ret... | Retrieve sensors in a group with their metatags.
@param group_id (int) - Group id for which to retrieve metatags.
@param namespace (string) - Namespace for which to retrieve the metatags.
@param parameters (dictionary) - Dictionary containing further parameters.
... | null | null | null | |
def SensorMetatagsGet(self, sensor_id, namespace = None):
ns = "default" if namespace is None else namespace
if self.__SenseApiCall__('/sensors/{0}/metatags.json'.format(sensor_id), 'GET', parameters = {'namespace': ns}):
return True
else:
self.__error__ = ... | Retrieve the metatags of a sensor.
@param sensor_id (int) - Id of the sensor to retrieve metatags from
@param namespace (stirng) - Namespace for which to retrieve metatags.
@return (bool) - Boolean indicating whether SensorMetatagsGet was successful | null | null | null | |
def SensorMetatagsPost(self, sensor_id, metatags, namespace = None):
ns = "default" if namespace is None else namespace
if self.__SenseApiCall__("/sensors/{0}/metatags.json?namespace={1}".format(sensor_id, ns), "POST", parameters = metatags):
return True
else:
... | Attach metatags to a sensor for a specific namespace
@param sensor_id (int) - Id of the sensor to attach metatags to
@param namespace (string) - Namespace for which to attach metatags
@param metatags (dictionary) - Metatags to attach to the sensor
... | null | null | null | |
def GroupSensorsFind(self, group_id, parameters, filters, namespace = None):
ns = "default" if namespace is None else namespace
parameters['namespace'] = ns
if self.__SenseApiCall__("/groups/{0}/sensors/find.json?{1}".format(group_id, urllib.urlencode(parameters, True)), "POST", par... | Find sensors in a group based on a number of filters on metatags
@param group_id (int) - Id of the group in which to find sensors
@param namespace (string) - Namespace to use in filtering on metatags
@param parameters (dictionary) - Dictionary containing additional p... | null | null | null | |
def MetatagDistinctValuesGet(self, metatag_name, namespace = None):
ns = "default" if namespace is None else namespace
if self.__SenseApiCall__("/metatag_name/{0}/distinct_values.json", "GET", parameters = {'namespace': ns}):
return True
else:
self.__error_... | Find the distinct value of a metatag name in a certain namespace
@param metatag_name (string) - Name of the metatag for which to find the distinct values
@param namespace (stirng) - Namespace in which to find the distinct values
@return (bool) - Boolean... | null | null | null | |
def SensorsDataGet(self, sensorIds, parameters):
if parameters is None:
parameters = {}
parameters["sensor_id[]"] = sensorIds
if self.__SenseApiCall__('/sensors/data.json', 'GET', parameters = parameters):
return True
else:
sel... | Retrieve sensor data for the specified sensors from CommonSense.
If SensorsDataGet is successful, the result can be obtained by a call to getResponse(), and should be a json string.
@param sensorIds (list) a list of sensor ids to retrieve the data for
@param parameters (dictiona... | null | null | null | |
def SensorDataDelete(self, sensor_id, data_id):
if self.__SenseApiCall__('/sensors/{0}/data/{1}.json'.format(sensor_id, data_id), 'DELETE'):
return True
else:
self.__error_ = "api call unsuccessful"
return False | Delete a sensor datum from a specific sensor in CommonSense.
@param sensor_id (int) - Sensor id of the sensor to delete data from
@param data_id (int) - Id of the data point to delete
@return (bool) - Boolean indicating whether SensorDataDelete was succ... | null | null | null | |
def SensorsDataPost(self, parameters):
if self.__SenseApiCall__('/sensors/data.json', 'POST', parameters = parameters):
return True
else:
self.__error__ = "api call unsuccessful"
return False | Post sensor data to multiple sensors in CommonSense simultaneously.
@param parameters (dictionary) - Data to post to the sensors.
@note - http://www.sense-os.nl/59?nodeId=59&selectedId=11887
@return (bool) - Boolean indicating whether Se... | null | null | null | |
def ServicesGet (self, sensor_id):
if self.__SenseApiCall__('/sensors/{0}/services.json'.format(sensor_id), 'GET'):
return True
else:
self.__error__ = "api call unsuccessful"
return False | Retrieve services connected to a sensor in CommonSense.
If ServicesGet is successful, the result can be obtained by a call to getResponse() and should be a json string.
@sensor_id (int) - Sensor id of sensor to retrieve services from.
@return (bool) - B... | null | null | null | |
def ServicesPost (self, sensor_id, parameters):
if self.__SenseApiCall__('/sensors/{0}/services.json'.format(sensor_id), 'POST', parameters = parameters):
return True
else:
self.__error__ = "api call unsuccessful"
return False | Create a new service in CommonSense, attached to a specific sensor.
If ServicesPost was successful, the service details, including its service_id, can be obtained from getResponse(), and should be a json string.
@param sensor_id (int) - The sensor id of the sensor to connect the... | null | null | null | |
def ServicesDelete (self, sensor_id, service_id):
if self.__SenseApiCall__('/sensors/{0}/services/{1}.json'.format(sensor_id, service_id), 'DELETE'):
return True
else:
self.__error__ = "api call unsuccessful"
return False | Delete a service from CommonSense.
@param sensor_id (int) - Sensor id of the sensor the service is connected to.
@param service_id (int) - Sensor id of the service to delete.
@return (bool) - Boolean indicating whether ServicesDelete was successful. | null | null | null | |
def ServicesSetMetod (self, sensor_id, service_id, method, parameters):
if self.__SenseApiCall__('/sensors/{0}/services/{1}/{2}.json'.format(sensor_id, service_id, method), 'POST', parameters = parameters):
return True
else:
self.__error__ = "api call unsuccessful"
... | Set expression for the math service.
@param sensor_id (int) - Sensor id of the sensor the service is connected to.
@param service_id (int) - Service id of the service for which to set the expression.
@param method (string) - The set method name.
@param p... | null | null | null | |
def ServicesGetMetod (self, sensor_id, service_id, method):
if self.__SenseApiCall__('/sensors/{0}/services/{1}/{2}.json'.format(sensor_id, service_id, method), 'GET'):
return True
else:
self.__error__ = "api call unsuccessful"
return False | Set expression for the math service.
@param sensor_id (int) - Sensor id of the sensor the service is connected to.
@param service_id (int) - Service id of the service for which to set the expression.
@param method (string) - The get method name.
... | null | null | null | |
def ServicesSetUseDataTimestamp(self, sensor_id, service_id, parameters):
if self.__SenseApiCall__('/sensors/{0}/services/{1}/SetUseDataTimestamp.json'.format(sensor_id, service_id), 'POST', parameters = parameters):
return True
else:
self.__error__ = "api call unsu... | Indicate whether a math service should use the original timestamps of the incoming data, or let CommonSense timestamp the aggregated data.
@param sensors_id (int) - Sensor id of the sensor the service is connected to.
@param service_id (int) - Service id of the service for which ... | null | null | null | |
def CreateUser (self, parameters):
print "Creating user"
print parameters
if self.__SenseApiCall__('/users.json', 'POST', parameters = parameters):
return True
else:
self.__error__ = "api call unsuccessful"
return False | Create a user
This method creates a user and returns the user object and session
@param parameters (dictionary) - Parameters according to which to create the user. | null | null | null | |
def UsersUpdate (self, user_id, parameters):
if self.__SenseApiCall__('/users/{0}.json'.format(user_id), 'PUT', parameters):
return True
else:
self.__error__ = "api call unsuccessful"
return False | Update the current user.
@param user_id (int) - id of the user to be updated
@param parameters (dictionary) - user object to update the user with
@return (bool) - Boolean indicating whether UserUpdate was successful. | null | null | null | |
def UsersChangePassword (self, current_password, new_password):
if self.__SenseApiCall__('/change_password', "POST", {"current_password":current_password, "new_password":new_password}):
return True
else:
self.__error__ = "api call unsuccessful"
return F... | Change the password for the current user
@param current_password (string) - md5 hash of the current password of the user
@param new_password (string) - md5 hash of the new password of the user (make sure to doublecheck!)
@return (bool) - Boolean indicat... | null | null | null | |
def UsersDelete (self, user_id):
if self.__SenseApiCall__('/users/{user_id}.json'.format(user_id = user_id), 'DELETE'):
return True
else:
self.__error__ = "api call unsuccessful"
return False | Delete user.
@return (bool) - Boolean indicating whether UsersDelete was successful. | null | null | null | |
def EventsNotificationsGet(self, event_notification_id = -1):
if event_notification_id == -1:
url = '/events/notifications.json'
else:
url = '/events/notifications/{0}.json'.format(event_notification_id)
if self.__SenseApiCall__(url, 'GET'):
... | Retrieve either all notifications or the notifications attached to a specific event.
If successful, result can be obtained by a call to getResponse(), and should be a json string.
@param event_notification_id (int) (optional) - Id of the event-notification to retrieve details fro... | null | null | null | |
def EventsNotificationsDelete(self, event_notification_id):
if self.__SenseApiCall__('/events/notifications/{0}.json'.format(event_notification_id), 'DELETE'):
return True
else:
self.__error__ = "api call unsuccessful"
return False | Delete an event-notification from CommonSense.
@param event_notification_id (int) - Id of the event-notification to delete.
@return (bool) - Boolean indicating whether EventsNotificationsDelete was successful. | null | null | null | |
def EventsNotificationsPost(self, parameters):
if self.__SenseApiCall__('/events/notifications.json', 'POST', parameters = parameters):
return True
else:
self.__error__ = "api call unsuccessful"
return False | Create an event-notification in CommonSense.
If EvensNotificationsPost was successful the result, including the event_notification_id can be obtained from getResponse(), and should be a json string.
@param parameters (dictionary) - Parameters according to which to create the even... | null | null | null | |
def TriggersGet(self, trigger_id = -1):
if trigger_id == -1:
url = '/triggers.json'
else:
url = '/triggers/{0}.json'.format(trigger_id)
if self.__SenseApiCall__(url, 'GET'):
return True
else:
self.__error__ = "api call uns... | Retrieve either all triggers or the details of a specific trigger.
If successful, result can be obtained by a call to getResponse(), and should be a json string.
@param trigger_id (int) (optional) - Trigger id of the trigger to retrieve details from.
@param (bool) ... | null | null | null | |
def TriggersDelete(self, trigger_id):
if self.__SenseApiCall__('/triggers/{0}'.format(trigger_id), 'DELETE'):
return True
else:
self.__error__ = "api call unsuccessful"
return False | Delete a trigger from CommonSense.
@param trigger_id (int) - Trigger id of the trigger to delete.
@return (bool) - Boolean indicating whether TriggersDelete was successful. | null | null | null | |
def TriggersPost(self, parameters):
if self.__SenseApiCall__('/triggers.json', 'POST', parameters = parameters):
return True
else:
self.__error__ = "api call unsuccessful"
return False | Create a trigger on CommonSense.
If TriggersPost was successful the result, including the trigger_id, can be obtained from getResponse().
@param parameters (dictionary) - Parameters of the trigger to create.
@note
@return (... | null | null | null | |
def SensorsTriggersGet(self, sensor_id, trigger_id = -1):
if trigger_id == -1:
url = '/sensors/{0}/triggers.json'.format(sensor_id)
else:
url = '/sensors/{0}/triggers/{1}.json'.format(sensor_id, trigger_id)
if self.__SenseApiCall__(url, 'GET'):
... | Obtain either all triggers connected to a sensor, or the details of a specific trigger connected to a sensor.
If successful, result can be obtained from getResponse(), and should be a json string.
@param sensor_id (int) - Sensor id of the sensor to retrieve triggers from.
... | null | null | null | |
def SensorsTriggersNotificationsGet(self, sensor_id, trigger_id):
if self.__SenseApiCall__('/sensors/{0}/triggers/{1}/notifications.json'.format(sensor_id, trigger_id), 'GET'):
return True
else:
self.__error__ = "api call unsuccessful"
return False | Obtain all notifications connected to a sensor-trigger combination.
If successful, the result can be obtained from getResponse(), and should be a json string.
@param sensor_id (int) - Sensor id if the sensor-trigger combination.
@param trigger_id (int) - Trigger id o... | null | null | null | |
def SensorsTriggersNotificationsDelete(self, sensor_id, trigger_id, notification_id):
if self.__SenseApiCall__('/sensors/{0}/triggers/{1}/notifications/{2}.json'.format(sensor_id, trigger_id, notification_id), 'DELETE'):
return True
else:
self.__error__ = "api call ... | Disconnect a notification from a sensor-trigger combination.
@param sensor_id (int) - Sensor id if the sensor-trigger combination.
@param trigger_id (int) - Trigger id of the sensor-trigger combination.
@param notification_id (int) - Notification id of the notificati... | null | null | null | |
def SensorsTriggersNotificationsPost(self, sensor_id, trigger_id, parameters):
if self.__SenseApiCall__('/sensors/{0}/triggers/{1}/notifications.json'.format(sensor_id, trigger_id), 'POST', parameters = parameters):
return True
else:
self.__error__ = "api call unsuc... | Connect a notification to a sensor-trigger combination.
@param sensor_id (int) - Sensor id if the sensor-trigger combination.
@param trigger_id (int) - Trigger id of the sensor-trigger combination.
@param parameters (dictionary) - Dictionary containing the notificati... | null | null | null | |
def NotificationsGet(self, notification_id = -1):
if notification_id == -1:
url = '/notifications.json'
else:
url = '/notifications/{0}.json'.format(notification_id)
if self.__SenseApiCall__(url, 'GET'):
return True
else:
... | Obtain either all notifications from CommonSense, or the details of a specific notification.
If successful, the result can be obtained from getResponse(), and should be a json string.
@param notification_id (int) (optional) - Notification id of the notification to obtain details ... | null | null | null | |
def NotificationsDelete(self, notification_id):
if self.__SenseApiCall__('/notifications/{0}.json'.format(notification_id), 'DELETE'):
return True
else:
self.__error__ = "api call unsuccessful"
return False | Delete a notification from CommonSense.
@param notification_id (int) - Notification id of the notification to delete.
@return (bool) - Boolean indicating whether NotificationsDelete was successful. | null | null | null | |
def NotificationsPost(self, parameters):
if self.__SenseApiCall__('/notifications.json', 'POST', parameters = parameters):
return True
else:
self.__error__ = "api call unsuccessful"
return False | Create a notification on CommonSense.
If successful the result, including the notification_id, can be obtained from getResponse(), and should be a json string.
@param parameters (dictionary) - Dictionary containing the notification to create.
@note -
... | null | null | null | |
def DeviceGet(self, device_id):
if self.__SenseApiCall__('/devices/{0}'.format(device_id), 'GET'):
return True
else:
self.__error__ = "api call unsuccessful"
return False | Obtain details of a single device
@param device_id (int) - Device for which to obtain details | null | null | null | |
def DeviceSensorsGet(self, device_id, parameters):
if self.__SenseApiCall__('/devices/{0}/sensors.json'.format(device_id), 'GET', parameters = parameters):
return True
else:
self.__error__ = "api call unsuccessful"
return False | Obtain a list of all sensors attached to a device.
@param device_id (int) - Device for which to retrieve sensors
@param parameters (dict) - Search parameters
@return (bool) - Boolean indicating whether DeviceSensorsGet was succesful. | null | null | null | |
def GroupsGet(self, parameters = None, group_id = -1):
if parameters is None and group_id == -1:
self.__error__ = "no arguments"
return False
url = ''
if group_id is -1:
url = '/groups.json'
else:
url = '/groups/{0}.json... | Retrieve groups from CommonSense, according to parameters, or by group id.
If successful, result can be obtained by a call to getResponse(), and should be a json string.
@param parameters (dictionary) (optional) - Dictionary containing the parameters for the api-call.
... | null | null | null | |
def GroupsDelete(self, group_id):
if self.__SenseApiCall__('/groups/{0}.json'.format(group_id), 'DELETE'):
return True
else:
self.__error__ = "api call unsuccessful"
return False | Delete a group from CommonSense.
@param group_id (int) - group id of group to delete from CommonSense.
@return (bool) - Boolean indicating whether GroupsDelete was successful. | null | null | null | |
def GroupsPost(self, parameters):
if self.__SenseApiCall__('/groups.json', 'POST', parameters = parameters):
return True
else:
self.__error__ = "api call unsuccessful"
return False | Create a group in CommonSense.
If GroupsPost is successful, the group details, including its group_id, can be obtained by a call to getResponse(), and should be a json string.
@param parameters (dictonary) - Dictionary containing the details of the group to be created.
... | null | null | null |
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