sentence1 stringlengths 52 3.87M | sentence2 stringlengths 1 47.2k | label stringclasses 1
value |
|---|---|---|
def name(self):
'''
Returns the name of the current :py:class:`Detrender` subclass.
'''
if self.cadence == 'lc':
return self.__class__.__name__
else:
return '%s.sc' % self.__class__.__name__ | Returns the name of the current :py:class:`Detrender` subclass. | entailment |
def cv_precompute(self, mask, b):
'''
Pre-compute the matrices :py:obj:`A` and :py:obj:`B`
(cross-validation step only)
for chunk :py:obj:`b`.
'''
# Get current chunk and mask outliers
m1 = self.get_masked_chunk(b)
flux = self.fraw[m1]
K = GetCov... | Pre-compute the matrices :py:obj:`A` and :py:obj:`B`
(cross-validation step only)
for chunk :py:obj:`b`. | entailment |
def cv_compute(self, b, A, B, C, mK, f, m1, m2):
'''
Compute the model (cross-validation step only) for chunk :py:obj:`b`.
'''
A = np.sum([l * a for l, a in zip(self.lam[b], A)
if l is not None], axis=0)
B = np.sum([l * b for l, b in zip(self.lam[b], B)
... | Compute the model (cross-validation step only) for chunk :py:obj:`b`. | entailment |
def get_outliers(self):
'''
Performs iterative sigma clipping to get outliers.
'''
log.info("Clipping outliers...")
log.info('Iter %d/%d: %d outliers' %
(0, self.oiter, len(self.outmask)))
def M(x): return np.delete(x, np.concatenate(
[self... | Performs iterative sigma clipping to get outliers. | entailment |
def optimize_lambda(self, validation):
'''
Returns the index of :py:attr:`self.lambda_arr` that minimizes the
validation scatter in the segment with minimum at the lowest value
of :py:obj:`lambda`, with
fractional tolerance :py:attr:`self.leps`.
:param numpy.ndarray vali... | Returns the index of :py:attr:`self.lambda_arr` that minimizes the
validation scatter in the segment with minimum at the lowest value
of :py:obj:`lambda`, with
fractional tolerance :py:attr:`self.leps`.
:param numpy.ndarray validation: The scatter in the validation set \
... | entailment |
def cross_validate(self, ax, info=''):
'''
Cross-validate to find the optimal value of :py:obj:`lambda`.
:param ax: The current :py:obj:`matplotlib.pyplot` axis instance to \
plot the cross-validation results.
:param str info: The label to show in the bottom right-hand co... | Cross-validate to find the optimal value of :py:obj:`lambda`.
:param ax: The current :py:obj:`matplotlib.pyplot` axis instance to \
plot the cross-validation results.
:param str info: The label to show in the bottom right-hand corner \
of the plot. Default `''` | entailment |
def get_ylim(self):
'''
Computes the ideal y-axis limits for the light curve plot. Attempts to
set the limits equal to those of the raw light curve, but if more than
1% of the flux lies either above or below these limits, auto-expands
to include those points. At the end, adds 5% ... | Computes the ideal y-axis limits for the light curve plot. Attempts to
set the limits equal to those of the raw light curve, but if more than
1% of the flux lies either above or below these limits, auto-expands
to include those points. At the end, adds 5% padding to both the
top and the ... | entailment |
def plot_lc(self, ax, info_left='', info_right='', color='b'):
'''
Plots the current light curve. This is called at several stages to
plot the de-trending progress as a function of the different
*PLD* orders.
:param ax: The current :py:obj:`matplotlib.pyplot` axis instance
... | Plots the current light curve. This is called at several stages to
plot the de-trending progress as a function of the different
*PLD* orders.
:param ax: The current :py:obj:`matplotlib.pyplot` axis instance
:param str info_left: Information to display at the left of the \
... | entailment |
def plot_final(self, ax):
'''
Plots the final de-trended light curve.
'''
# Plot the light curve
bnmask = np.array(
list(set(np.concatenate([self.badmask, self.nanmask]))), dtype=int)
def M(x): return np.delete(x, bnmask)
if (self.cadence == 'lc') o... | Plots the final de-trended light curve. | entailment |
def plot_cbv(self, ax, flux, info, show_cbv=False):
'''
Plots the final CBV-corrected light curve.
'''
# Plot the light curve
bnmask = np.array(
list(set(np.concatenate([self.badmask, self.nanmask]))), dtype=int)
def M(x): return np.delete(x, bnmask)
... | Plots the final CBV-corrected light curve. | entailment |
def load_tpf(self):
'''
Loads the target pixel file.
'''
if not self.loaded:
if self._data is not None:
data = self._data
else:
data = self._mission.GetData(
self.ID, season=self.season,
... | Loads the target pixel file. | entailment |
def load_model(self, name=None):
'''
Loads a saved version of the model.
'''
if self.clobber:
return False
if name is None:
name = self.name
file = os.path.join(self.dir, '%s.npz' % name)
if os.path.exists(file):
if not self.... | Loads a saved version of the model. | entailment |
def save_model(self):
'''
Saves all of the de-trending information to disk in an `npz` file
and saves the DVS as a `pdf`.
'''
# Save the data
log.info("Saving data to '%s.npz'..." % self.name)
d = dict(self.__dict__)
d.pop('_weights', None)
d.pop... | Saves all of the de-trending information to disk in an `npz` file
and saves the DVS as a `pdf`. | entailment |
def exception_handler(self, pdb):
'''
A custom exception handler.
:param pdb: If :py:obj:`True`, enters PDB post-mortem \
mode for debugging.
'''
# Grab the exception
exctype, value, tb = sys.exc_info()
# Log the error and create a .err file
... | A custom exception handler.
:param pdb: If :py:obj:`True`, enters PDB post-mortem \
mode for debugging. | entailment |
def update_gp(self):
'''
Calls :py:func:`gp.GetKernelParams` to optimize the GP and obtain the
covariance matrix for the regression.
'''
self.kernel_params = GetKernelParams(self.time, self.flux,
self.fraw_err,
... | Calls :py:func:`gp.GetKernelParams` to optimize the GP and obtain the
covariance matrix for the regression. | entailment |
def init_kernel(self):
'''
Initializes the covariance matrix with a guess at
the GP kernel parameters.
'''
if self.kernel_params is None:
X = self.apply_mask(self.fpix / self.flux.reshape(-1, 1))
y = self.apply_mask(self.flux) - np.dot(X, np.linalg.solve... | Initializes the covariance matrix with a guess at
the GP kernel parameters. | entailment |
def run(self):
'''
Runs the de-trending step.
'''
try:
# Load raw data
log.info("Loading target data...")
self.load_tpf()
self.mask_planets()
self.plot_aperture([self.dvs.top_right() for i in range(4)])
self.init_... | Runs the de-trending step. | entailment |
def publish(self, **kwargs):
'''
Correct the light curve with the CBVs, generate a
cover page for the DVS figure,
and produce a FITS file for publication.
'''
try:
# HACK: Force these params for publication
self.cbv_win = 999
self.cb... | Correct the light curve with the CBVs, generate a
cover page for the DVS figure,
and produce a FITS file for publication. | entailment |
def setup(self, **kwargs):
'''
This is called during production de-trending, prior to
calling the :py:obj:`Detrender.run()` method.
:param tuple cdpp_range: If :py:obj:`parent_model` is set, \
neighbors are selected only if \
their de-trended CDPPs fall wit... | This is called during production de-trending, prior to
calling the :py:obj:`Detrender.run()` method.
:param tuple cdpp_range: If :py:obj:`parent_model` is set, \
neighbors are selected only if \
their de-trended CDPPs fall within this range. Default `None`
:param t... | entailment |
def setup(self, **kwargs):
'''
This is called during production de-trending, prior to
calling the :py:obj:`Detrender.run()` method.
:param str parent_model: The name of the model to operate on. \
Default `nPLD`
'''
# Load the parent model
self.pa... | This is called during production de-trending, prior to
calling the :py:obj:`Detrender.run()` method.
:param str parent_model: The name of the model to operate on. \
Default `nPLD` | entailment |
def setup(self, **kwargs):
'''
This is called during production de-trending, prior to
calling the :py:obj:`Detrender.run()` method.
:param inter piter: The number of iterations in the minimizer. \
Default 3
:param int pmaxf: The maximum number of function evaluati... | This is called during production de-trending, prior to
calling the :py:obj:`Detrender.run()` method.
:param inter piter: The number of iterations in the minimizer. \
Default 3
:param int pmaxf: The maximum number of function evaluations per \
iteration. Default 300... | entailment |
def run(self):
'''
Runs the de-trending.
'''
try:
# Plot original
self.plot_aperture([self.dvs.top_right() for i in range(4)])
self.plot_lc(self.dvs.left(), info_right='nPLD', color='k')
# Cross-validate
self.cross_validate(... | Runs the de-trending. | entailment |
def cross_validate(self, ax):
'''
Performs the cross-validation step.
'''
# The CDPP to beat
cdpp_opt = self.get_cdpp_arr()
# Loop over all chunks
for b, brkpt in enumerate(self.breakpoints):
log.info("Cross-validating chunk %d/%d..." %
... | Performs the cross-validation step. | entailment |
def validation_scatter(self, log_lam, b, masks, pre_v, gp, flux,
time, med):
'''
Computes the scatter in the validation set.
'''
# Update the lambda matrix
self.lam[b] = 10 ** log_lam
# Validation set scatter
scatter = [None for i in ... | Computes the scatter in the validation set. | entailment |
def populate(datatype='string', size=10, start=None, end=None,
converter=None, choice_from=None, **kwargs):
'''Utility function for populating lists with random data.
Useful for populating database with data for fuzzy testing.
Supported data-types
* *string*
For example::
populat... | Utility function for populating lists with random data.
Useful for populating database with data for fuzzy testing.
Supported data-types
* *string*
For example::
populate('string',100, min_len=3, max_len=10)
create a 100 elements list with random strings
with random length between 3 and... | entailment |
def Search(star, pos_tol=2.5, neg_tol=50., **ps_kwargs):
'''
NOTE: `pos_tol` is the positive (i.e., above the median)
outlier tolerance in standard deviations.
NOTE: `neg_tol` is the negative (i.e., below the median)
outlier tolerance in standard deviations.
'''
# Smooth the light curve
... | NOTE: `pos_tol` is the positive (i.e., above the median)
outlier tolerance in standard deviations.
NOTE: `neg_tol` is the negative (i.e., below the median)
outlier tolerance in standard deviations. | entailment |
def iterdirty(self):
'''Ordered iterator over dirty elements.'''
return iter(chain(itervalues(self._new), itervalues(self._modified))) | Ordered iterator over dirty elements. | entailment |
def add(self, instance, modified=True, persistent=None,
force_update=False):
'''Add a new instance to this :class:`SessionModel`.
:param modified: Optional flag indicating if the ``instance`` has been
modified. By default its value is ``True``.
:param force_update: if ``instance`` is pers... | Add a new instance to this :class:`SessionModel`.
:param modified: Optional flag indicating if the ``instance`` has been
modified. By default its value is ``True``.
:param force_update: if ``instance`` is persistent, it forces an update of the
data rather than a full replacement. This is used by the
... | entailment |
def delete(self, instance, session):
'''delete an *instance*'''
if instance._meta.type == 'structure':
return self._delete_structure(instance)
inst = self.pop(instance)
instance = inst if inst is not None else instance
if instance is not None:
state... | delete an *instance* | entailment |
def pop(self, instance):
'''Remove ``instance`` from the :class:`SessionModel`. Instance
could be a :class:`Model` or an id.
:parameter instance: a :class:`Model` or an ``id``.
:rtype: the :class:`Model` removed from session or ``None`` if
it was not in the session.
'''
if isinstance(instan... | Remove ``instance`` from the :class:`SessionModel`. Instance
could be a :class:`Model` or an id.
:parameter instance: a :class:`Model` or an ``id``.
:rtype: the :class:`Model` removed from session or ``None`` if
it was not in the session. | entailment |
def expunge(self, instance):
'''Remove *instance* from the :class:`Session`. Instance could be a
:class:`Model` or an id.
:parameter instance: a :class:`Model` or an *id*
:rtype: the :class:`Model` removed from session or ``None`` if
it was not in the session.
'''
instance = self.pop(instan... | Remove *instance* from the :class:`Session`. Instance could be a
:class:`Model` or an id.
:parameter instance: a :class:`Model` or an *id*
:rtype: the :class:`Model` removed from session or ``None`` if
it was not in the session. | entailment |
def post_commit(self, results):
'''\
Process results after a commit.
:parameter results: iterator over :class:`stdnet.instance_session_result`
items.
:rtype: a two elements tuple containing a list of instances saved and
a list of ids of instances deleted.'''
tpy = self._meta.pk_to_pytho... | \
Process results after a commit.
:parameter results: iterator over :class:`stdnet.instance_session_result`
items.
:rtype: a two elements tuple containing a list of instances saved and
a list of ids of instances deleted. | entailment |
def commit(self, callback=None):
'''Close the transaction and commit session to the backend.'''
if self.executed:
raise InvalidTransaction('Invalid operation. '
'Transaction already executed.')
session = self.session
self.session = N... | Close the transaction and commit session to the backend. | entailment |
def dirty(self):
'''The set of instances in this :class:`Session` which have
been modified.'''
return frozenset(chain(*tuple((sm.dirty for sm
in itervalues(self._models))))) | The set of instances in this :class:`Session` which have
been modified. | entailment |
def begin(self, **options):
'''Begin a new :class:`Transaction`. If this :class:`Session`
is already in a :ref:`transactional state <transactional-state>`,
an error will occur. It returns the :attr:`transaction` attribute.
This method is mostly used within a ``with`` statement block::
with session.... | Begin a new :class:`Transaction`. If this :class:`Session`
is already in a :ref:`transactional state <transactional-state>`,
an error will occur. It returns the :attr:`transaction` attribute.
This method is mostly used within a ``with`` statement block::
with session.begin() as t:
t.add(...)
... | entailment |
def query(self, model, **kwargs):
'''Create a new :class:`Query` for *model*.'''
sm = self.model(model)
query_class = sm.manager.query_class or Query
return query_class(sm._meta, self, **kwargs) | Create a new :class:`Query` for *model*. | entailment |
def update_or_create(self, model, **kwargs):
'''Update or create a new instance of ``model``.
This method can raise an exception if the ``kwargs`` dictionary
contains field data that does not validate.
:param model: a :class:`StdModel`
:param kwargs: dictionary of parame... | Update or create a new instance of ``model``.
This method can raise an exception if the ``kwargs`` dictionary
contains field data that does not validate.
:param model: a :class:`StdModel`
:param kwargs: dictionary of parameters.
:returns: A two elements tuple containing ... | entailment |
def add(self, instance, modified=True, **params):
'''Add an ``instance`` to the session.
If the session is not in a
:ref:`transactional state <transactional-state>`, this operation
commits changes to the back-end server immediately.
:parameter instance: a :class:`Model` ... | Add an ``instance`` to the session.
If the session is not in a
:ref:`transactional state <transactional-state>`, this operation
commits changes to the back-end server immediately.
:parameter instance: a :class:`Model` instance. It must be registered
with the :attr:`r... | entailment |
def delete(self, instance_or_query):
'''Delete an ``instance`` or a ``query``.
Adds ``instance_or_query`` to this :class:`Session` list
of data to be deleted. If the session is not in a
:ref:`transactional state <transactional-state>`, this operation
commits changes to the... | Delete an ``instance`` or a ``query``.
Adds ``instance_or_query`` to this :class:`Session` list
of data to be deleted. If the session is not in a
:ref:`transactional state <transactional-state>`, this operation
commits changes to the backend server immediately.
:paramete... | entailment |
def model(self, model, create=True):
'''Returns the :class:`SessionModel` for ``model`` which
can be :class:`Model`, or a :class:`MetaClass`, or an instance
of :class:`Model`.'''
manager = self.manager(model)
sm = self._models.get(manager)
if sm is None and create:
sm ... | Returns the :class:`SessionModel` for ``model`` which
can be :class:`Model`, or a :class:`MetaClass`, or an instance
of :class:`Model`. | entailment |
def expunge(self, instance=None):
'''Remove ``instance`` from this :class:`Session`. If ``instance``
is not given, it removes all instances from this :class:`Session`.'''
if instance is not None:
sm = self._models.get(instance._meta)
if sm:
return sm.expunge... | Remove ``instance`` from this :class:`Session`. If ``instance``
is not given, it removes all instances from this :class:`Session`. | entailment |
def manager(self, model):
'''Retrieve the :class:`Manager` for ``model`` which can be any of the
values valid for the :meth:`model` method.'''
try:
return self.router[model]
except KeyError:
meta = getattr(model, '_meta', model)
if meta.type == 'structu... | Retrieve the :class:`Manager` for ``model`` which can be any of the
values valid for the :meth:`model` method. | entailment |
def new(self, *args, **kwargs):
'''Create a new instance of :attr:`model` and commit it to the backend
server. This a shortcut method for the more verbose::
instance = manager.session().add(MyModel(**kwargs))
'''
return self.session().add(self.model(*args, **kwargs)) | Create a new instance of :attr:`model` and commit it to the backend
server. This a shortcut method for the more verbose::
instance = manager.session().add(MyModel(**kwargs)) | entailment |
def query(self, session=None):
'''Returns a new :class:`Query` for :attr:`Manager.model`.'''
if session is None or session.router is not self.router:
session = self.session()
return session.query(self.model) | Returns a new :class:`Query` for :attr:`Manager.model`. | entailment |
def search(self, text, lookup=None):
'''Returns a new :class:`Query` for :attr:`Manager.model` with
a full text search value.'''
return self.query().search(text, lookup=lookup) | Returns a new :class:`Query` for :attr:`Manager.model` with
a full text search value. | entailment |
def pairs_to_dict(response, encoding):
"Create a dict given a list of key/value pairs"
it = iter(response)
return dict(((k.decode(encoding), v) for k, v in zip(it, it))) | Create a dict given a list of key/value pairs | entailment |
def load_related(self, meta, fname, data, fields, encoding):
'''Parse data for related objects.'''
field = meta.dfields[fname]
if field in meta.multifields:
fmeta = field.structure_class()._meta
if fmeta.name in ('hashtable', 'zset'):
return ((native... | Parse data for related objects. | entailment |
def _execute_query(self):
'''Execute the query without fetching data. Returns the number of
elements in the query.'''
pipe = self.pipe
if not self.card:
if self.meta.ordering:
self.ismember = getattr(self.backend.client, 'zrank')
self.card = get... | Execute the query without fetching data. Returns the number of
elements in the query. | entailment |
def order(self, last):
'''Perform ordering with respect model fields.'''
desc = last.desc
field = last.name
nested = last.nested
nested_args = []
while nested:
meta = nested.model._meta
nested_args.extend((self.backend.basekey(meta), nested... | Perform ordering with respect model fields. | entailment |
def related_lua_args(self):
'''Generator of load_related arguments'''
related = self.queryelem.select_related
if related:
meta = self.meta
for rel in related:
field = meta.dfields[rel]
relmodel = field.relmodel
bk = ... | Generator of load_related arguments | entailment |
def ipop_range(self, start, stop=None, withscores=True, **options):
'''Remove and return a range from the ordered set by rank (index).'''
return self.backend.execute(
self.client.zpopbyrank(self.id, start, stop,
withscores=withscores, **options),
... | Remove and return a range from the ordered set by rank (index). | entailment |
def pop_range(self, start, stop=None, withscores=True, **options):
'''Remove and return a range from the ordered set by score.'''
return self.backend.execute(
self.client.zpopbyscore(self.id, start, stop,
withscores=withscores, **options),
... | Remove and return a range from the ordered set by score. | entailment |
def meta(self, meta):
'''Extract model metadata for lua script stdnet/lib/lua/odm.lua'''
data = meta.as_dict()
data['namespace'] = self.basekey(meta)
return data | Extract model metadata for lua script stdnet/lib/lua/odm.lua | entailment |
def execute_session(self, session_data):
'''Execute a session in redis.'''
pipe = self.client.pipeline()
for sm in session_data: # loop through model sessions
meta = sm.meta
if sm.structures:
self.flush_structure(sm, pipe)
delquery = No... | Execute a session in redis. | entailment |
def flush(self, meta=None):
'''Flush all model keys from the database'''
pattern = self.basekey(meta) if meta else self.namespace
return self.client.delpattern('%s*' % pattern) | Flush all model keys from the database | entailment |
def GetCovariance(kernel, kernel_params, time, errors):
'''
Returns the covariance matrix for a given light curve
segment.
:param array_like kernel_params: A list of kernel parameters \
(white noise amplitude, red noise amplitude, and red noise timescale)
:param array_like time: The time ... | Returns the covariance matrix for a given light curve
segment.
:param array_like kernel_params: A list of kernel parameters \
(white noise amplitude, red noise amplitude, and red noise timescale)
:param array_like time: The time array (*N*)
:param array_like errors: The data error array (*N*)... | entailment |
def GetKernelParams(time, flux, errors, kernel='Basic', mask=[],
giter=3, gmaxf=200, guess=None):
'''
Optimizes the GP by training it on the current de-trended light curve.
Returns the white noise amplitude, red noise amplitude,
and red noise timescale.
:param array_like time: T... | Optimizes the GP by training it on the current de-trended light curve.
Returns the white noise amplitude, red noise amplitude,
and red noise timescale.
:param array_like time: The time array
:param array_like flux: The flux array
:param array_like errors: The flux errors array
:param array_like... | entailment |
def NegLnLike(x, time, flux, errors, kernel):
'''
Returns the negative log-likelihood function and its gradient.
'''
gp = GP(kernel, x, white=True)
gp.compute(time, errors)
if OLDGEORGE:
nll = -gp.lnlikelihood(flux)
# NOTE: There was a bug on this next line! Used to be
... | Returns the negative log-likelihood function and its gradient. | entailment |
def missing_intervals(startdate, enddate, start, end,
dateconverter=None,
parseinterval=None,
intervals=None):
'''Given a ``startdate`` and an ``enddate`` dates, evaluate the
date intervals from which data is not available. It return a list of
... | Given a ``startdate`` and an ``enddate`` dates, evaluate the
date intervals from which data is not available. It return a list of
two-dimensional tuples containing start and end date for the interval.
The list could countain 0,1 or 2 tuples. | entailment |
def dategenerator(start, end, step=1, desc=False):
'''Generates dates between *atrt* and *end*.'''
delta = timedelta(abs(step))
end = max(start, end)
if desc:
dt = end
while dt >= start:
yield dt
dt -= delta
else:
dt = start
while dt... | Generates dates between *atrt* and *end*. | entailment |
def InitLog(file_name=None, log_level=logging.DEBUG,
screen_level=logging.CRITICAL, pdb=False):
'''
A little routine to initialize the logging functionality.
:param str file_name: The name of the file to log to. \
Default :py:obj:`None` (set internally by :py:mod:`everest`)
:para... | A little routine to initialize the logging functionality.
:param str file_name: The name of the file to log to. \
Default :py:obj:`None` (set internally by :py:mod:`everest`)
:param int log_level: The file logging level (0-50). Default 10 (debug)
:param int screen_level: The screen logging level... | entailment |
def ExceptionHook(exctype, value, tb):
'''
A custom exception handler that logs errors to file.
'''
for line in traceback.format_exception_only(exctype, value):
log.error(line.replace('\n', ''))
for line in traceback.format_tb(tb):
log.error(line.replace('\n', ''))
sys.__except... | A custom exception handler that logs errors to file. | entailment |
def ExceptionHookPDB(exctype, value, tb):
'''
A custom exception handler, with :py:obj:`pdb` post-mortem for debugging.
'''
for line in traceback.format_exception_only(exctype, value):
log.error(line.replace('\n', ''))
for line in traceback.format_tb(tb):
log.error(line.replace('\n... | A custom exception handler, with :py:obj:`pdb` post-mortem for debugging. | entailment |
def sort_like(l, col1, col2):
'''
Sorts the list :py:obj:`l` by comparing :py:obj:`col2` to :py:obj:`col1`.
Specifically, finds the indices :py:obj:`i` such that ``col2[i] = col1``
and returns ``l[i]``. This is useful when comparing the CDPP values of
catalogs generated by different pipelines. The
... | Sorts the list :py:obj:`l` by comparing :py:obj:`col2` to :py:obj:`col1`.
Specifically, finds the indices :py:obj:`i` such that ``col2[i] = col1``
and returns ``l[i]``. This is useful when comparing the CDPP values of
catalogs generated by different pipelines. The
target IDs are all the same, but won't ... | entailment |
def prange(*x):
'''
Progress bar range with `tqdm`
'''
try:
root = logging.getLogger()
if len(root.handlers):
for h in root.handlers:
if (type(h) is logging.StreamHandler) and \
(h.level != logging.CRITICAL):
from ... | Progress bar range with `tqdm` | entailment |
def front(self, *fields):
'''Return the front pair of the structure'''
ts = self.irange(0, 0, fields=fields)
if ts:
return ts.start(), ts[0] | Return the front pair of the structure | entailment |
def back(self, *fields):
'''Return the back pair of the structure'''
ts = self.irange(-1, -1, fields=fields)
if ts:
return ts.end(), ts[0] | Return the back pair of the structure | entailment |
def parse_backend(backend):
"""Converts the "backend" into the database connection parameters.
It returns a (scheme, host, params) tuple."""
r = urlparse.urlsplit(backend)
scheme, host = r.scheme, r.netloc
path, query = r.path, r.query
if path and not query:
query, path = path, ''
... | Converts the "backend" into the database connection parameters.
It returns a (scheme, host, params) tuple. | entailment |
def getdb(backend=None, **kwargs):
'''get a :class:`BackendDataServer`.'''
if isinstance(backend, BackendDataServer):
return backend
backend = backend or settings.DEFAULT_BACKEND
if not backend:
return None
scheme, address, params = parse_backend(backend)
params.update(kw... | get a :class:`BackendDataServer`. | entailment |
def basekey(self, meta, *args):
"""Calculate the key to access model data.
:parameter meta: a :class:`stdnet.odm.Metaclass`.
:parameter args: optional list of strings to prepend to the basekey.
:rtype: a native string
"""
key = '%s%s' % (self.namespace, meta.modelkey)
postfix = ':'.join... | Calculate the key to access model data.
:parameter meta: a :class:`stdnet.odm.Metaclass`.
:parameter args: optional list of strings to prepend to the basekey.
:rtype: a native string | entailment |
def make_objects(self, meta, data, related_fields=None):
'''Generator of :class:`stdnet.odm.StdModel` instances with data
from database.
:parameter meta: instance of model :class:`stdnet.odm.Metaclass`.
:parameter data: iterator over instances data.
'''
make_object = meta.make_object
re... | Generator of :class:`stdnet.odm.StdModel` instances with data
from database.
:parameter meta: instance of model :class:`stdnet.odm.Metaclass`.
:parameter data: iterator over instances data. | entailment |
def structure(self, instance, client=None):
'''Create a backend :class:`stdnet.odm.Structure` handler.
:param instance: a :class:`stdnet.odm.Structure`
:param client: Optional client handler.
'''
struct = self.struct_map.get(instance._meta.name)
if struct is None:... | Create a backend :class:`stdnet.odm.Structure` handler.
:param instance: a :class:`stdnet.odm.Structure`
:param client: Optional client handler. | entailment |
def Search(ID, mission='k2'):
"""Why is my target not in the EVEREST database?"""
# Only K2 supported for now
assert mission == 'k2', "Only the K2 mission is supported for now."
print("Searching for target %d..." % ID)
# First check if it is in the database
season = missions.k2.Season(ID)
i... | Why is my target not in the EVEREST database? | entailment |
def DownloadFile(ID, season=None, mission='k2', cadence='lc',
filename=None, clobber=False):
'''
Download a given :py:mod:`everest` file from MAST.
:param str mission: The mission name. Default `k2`
:param str cadence: The light curve cadence. Default `lc`
:param str filename: The ... | Download a given :py:mod:`everest` file from MAST.
:param str mission: The mission name. Default `k2`
:param str cadence: The light curve cadence. Default `lc`
:param str filename: The name of the file to download. Default \
:py:obj:`None`, in which case the default \
FITS file is ret... | entailment |
def DVS(ID, season=None, mission='k2', clobber=False,
cadence='lc', model='nPLD'):
'''
Show the data validation summary (DVS) for a given target.
:param str mission: The mission name. Default `k2`
:param str cadence: The light curve cadence. Default `lc`
:param bool clobber: If :py:obj:`Tru... | Show the data validation summary (DVS) for a given target.
:param str mission: The mission name. Default `k2`
:param str cadence: The light curve cadence. Default `lc`
:param bool clobber: If :py:obj:`True`, download and overwrite \
existing files. Default :py:obj:`False` | entailment |
def compute(self):
'''
Re-compute the :py:mod:`everest` model for the given
value of :py:obj:`lambda`.
For long cadence `k2` light curves, this should take several
seconds. For short cadence `k2` light curves, it may take a
few minutes. Note that this is a simple wrapper ... | Re-compute the :py:mod:`everest` model for the given
value of :py:obj:`lambda`.
For long cadence `k2` light curves, this should take several
seconds. For short cadence `k2` light curves, it may take a
few minutes. Note that this is a simple wrapper around
:py:func:`everest.Baseca... | entailment |
def _get_norm(self):
'''
Computes the PLD flux normalization array.
..note :: `iPLD` model **only**.
'''
log.info('Computing the PLD normalization...')
# Loop over all chunks
mod = [None for b in self.breakpoints]
for b, brkpt in enumerate(self.breakpo... | Computes the PLD flux normalization array.
..note :: `iPLD` model **only**. | entailment |
def load_fits(self):
'''
Load the FITS file from disk and populate the
class instance with its data.
'''
log.info("Loading FITS file for %d." % (self.ID))
with pyfits.open(self.fitsfile) as f:
# Params and long cadence data
self.loaded = True
... | Load the FITS file from disk and populate the
class instance with its data. | entailment |
def plot_aperture(self, show=True):
'''
Plot sample postage stamps for the target with the aperture
outline marked, as well as a high-res target image (if available).
:param bool show: Show the plot or return the `(fig, ax)` instance? \
Default :py:obj:`True`
'''... | Plot sample postage stamps for the target with the aperture
outline marked, as well as a high-res target image (if available).
:param bool show: Show the plot or return the `(fig, ax)` instance? \
Default :py:obj:`True` | entailment |
def plot(self, show=True, plot_raw=True, plot_gp=True,
plot_bad=True, plot_out=True, plot_cbv=True,
simple=False):
'''
Plots the final de-trended light curve.
:param bool show: Show the plot or return the `(fig, ax)` instance? \
Default :py:obj:`True`
... | Plots the final de-trended light curve.
:param bool show: Show the plot or return the `(fig, ax)` instance? \
Default :py:obj:`True`
:param bool plot_raw: Show the raw light curve? Default :py:obj:`True`
:param bool plot_gp: Show the GP model prediction? \
Default ... | entailment |
def dvs(self):
'''
Shows the data validation summary (DVS) for the target.
'''
DVS(self.ID, season=self.season, mission=self.mission,
model=self.model_name, clobber=self.clobber) | Shows the data validation summary (DVS) for the target. | entailment |
def plot_pipeline(self, pipeline, *args, **kwargs):
'''
Plots the light curve for the target de-trended with a given pipeline.
:param str pipeline: The name of the pipeline (lowercase). Options \
are 'everest2', 'everest1', and other mission-specific \
pipelines. F... | Plots the light curve for the target de-trended with a given pipeline.
:param str pipeline: The name of the pipeline (lowercase). Options \
are 'everest2', 'everest1', and other mission-specific \
pipelines. For `K2`, the available pipelines are 'k2sff' \
and 'k2sc'... | entailment |
def get_pipeline(self, *args, **kwargs):
'''
Returns the `time` and `flux` arrays for the target obtained by a given
pipeline.
Options :py:obj:`args` and :py:obj:`kwargs` are passed directly to
the :py:func:`pipelines.get` function of the mission.
'''
return ge... | Returns the `time` and `flux` arrays for the target obtained by a given
pipeline.
Options :py:obj:`args` and :py:obj:`kwargs` are passed directly to
the :py:func:`pipelines.get` function of the mission. | entailment |
def mask_planet(self, t0, period, dur=0.2):
'''
Mask all of the transits/eclipses of a given planet/EB. After calling
this method, you must re-compute the model by calling
:py:meth:`compute` in order for the mask to take effect.
:param float t0: The time of first transit (same u... | Mask all of the transits/eclipses of a given planet/EB. After calling
this method, you must re-compute the model by calling
:py:meth:`compute` in order for the mask to take effect.
:param float t0: The time of first transit (same units as light curve)
:param float period: The period of ... | entailment |
def _plot_weights(self, show=True):
'''
.. warning:: Untested!
'''
# Set up the axes
fig = pl.figure(figsize=(12, 12))
fig.subplots_adjust(top=0.95, bottom=0.025, left=0.1, right=0.92)
fig.canvas.set_window_title(
'%s %d' % (self._mission.IDSTRING, s... | .. warning:: Untested! | entailment |
def _save_npz(self):
'''
Saves all of the de-trending information to disk in an `npz` file
'''
# Save the data
d = dict(self.__dict__)
d.pop('_weights', None)
d.pop('_A', None)
d.pop('_B', None)
d.pop('_f', None)
d.pop('_mK', None)
... | Saves all of the de-trending information to disk in an `npz` file | entailment |
def optimize(self, piter=3, pmaxf=300, ppert=0.1):
'''
Runs :py:obj:`pPLD` on the target in an attempt to further optimize the
values of the PLD priors. See :py:class:`everest.detrender.pPLD`.
'''
self._save_npz()
optimized = pPLD(self.ID, piter=piter, pmaxf=pmaxf,
... | Runs :py:obj:`pPLD` on the target in an attempt to further optimize the
values of the PLD priors. See :py:class:`everest.detrender.pPLD`. | entailment |
def plot_folded(self, t0, period, dur=0.2):
'''
Plot the light curve folded on a given `period` and centered at `t0`.
When plotting folded transits, please mask them using
:py:meth:`mask_planet` and re-compute the model using
:py:meth:`compute`.
:param float t0: The time... | Plot the light curve folded on a given `period` and centered at `t0`.
When plotting folded transits, please mask them using
:py:meth:`mask_planet` and re-compute the model using
:py:meth:`compute`.
:param float t0: The time at which to center the plot \
(same units as lig... | entailment |
def plot_transit_model(self, show=True, fold=None, ax=None):
'''
Plot the light curve de-trended with a join instrumental + transit
model with the best fit transit model overlaid. The transit model
should be specified using the :py:obj:`transit_model` attribute
and should be an i... | Plot the light curve de-trended with a join instrumental + transit
model with the best fit transit model overlaid. The transit model
should be specified using the :py:obj:`transit_model` attribute
and should be an instance or list of instances of
:py:class:`everest.transit.TransitModel`.... | entailment |
def Interpolate(time, mask, y):
'''
Masks certain elements in the array `y` and linearly
interpolates over them, returning an array `y'` of the
same length.
:param array_like time: The time array
:param array_like mask: The indices to be interpolated over
:param array_like y: The dependent ... | Masks certain elements in the array `y` and linearly
interpolates over them, returning an array `y'` of the
same length.
:param array_like time: The time array
:param array_like mask: The indices to be interpolated over
:param array_like y: The dependent array | entailment |
def Chunks(l, n, all=False):
'''
Returns a generator of consecutive `n`-sized chunks of list `l`.
If `all` is `True`, returns **all** `n`-sized chunks in `l`
by iterating over the starting point.
'''
if all:
jarr = range(0, n - 1)
else:
jarr = [0]
for j in jarr:
... | Returns a generator of consecutive `n`-sized chunks of list `l`.
If `all` is `True`, returns **all** `n`-sized chunks in `l`
by iterating over the starting point. | entailment |
def Smooth(x, window_len=100, window='hanning'):
'''
Smooth data by convolving on a given timescale.
:param ndarray x: The data array
:param int window_len: The size of the smoothing window. Default `100`
:param str window: The window type. Default `hanning`
'''
if window_len == 0:
... | Smooth data by convolving on a given timescale.
:param ndarray x: The data array
:param int window_len: The size of the smoothing window. Default `100`
:param str window: The window type. Default `hanning` | entailment |
def Scatter(y, win=13, remove_outliers=False):
'''
Return the scatter in ppm based on the median running standard deviation
for a window size of :py:obj:`win` = 13 cadences (for K2, this
is ~6.5 hours, as in VJ14).
:param ndarray y: The array whose CDPP is to be computed
:param int win: The win... | Return the scatter in ppm based on the median running standard deviation
for a window size of :py:obj:`win` = 13 cadences (for K2, this
is ~6.5 hours, as in VJ14).
:param ndarray y: The array whose CDPP is to be computed
:param int win: The window size in cadences. Default `13`
:param bool remove_o... | entailment |
def SavGol(y, win=49):
'''
Subtracts a second order Savitsky-Golay filter with window size `win`
and returns the result. This acts as a high pass filter.
'''
if len(y) >= win:
return y - savgol_filter(y, win, 2) + np.nanmedian(y)
else:
return y | Subtracts a second order Savitsky-Golay filter with window size `win`
and returns the result. This acts as a high pass filter. | entailment |
def NumRegressors(npix, pld_order, cross_terms=True):
'''
Return the number of regressors for `npix` pixels
and PLD order `pld_order`.
:param bool cross_terms: Include pixel cross-terms? Default :py:obj:`True`
'''
res = 0
for k in range(1, pld_order + 1):
if cross_terms:
... | Return the number of regressors for `npix` pixels
and PLD order `pld_order`.
:param bool cross_terms: Include pixel cross-terms? Default :py:obj:`True` | entailment |
def Downbin(x, newsize, axis=0, operation='mean'):
'''
Downbins an array to a smaller size.
:param array_like x: The array to down-bin
:param int newsize: The new size of the axis along which to down-bin
:param int axis: The axis to operate on. Default 0
:param str operation: The operation to p... | Downbins an array to a smaller size.
:param array_like x: The array to down-bin
:param int newsize: The new size of the axis along which to down-bin
:param int axis: The axis to operate on. Default 0
:param str operation: The operation to perform when down-binning. \
Default `mean` | entailment |
def register_with_model(self, name, model):
'''Called during the creation of a the :class:`StdModel`
class when :class:`Metaclass` is initialised. It fills
:attr:`Field.name` and :attr:`Field.model`. This is an internal
function users should never call.'''
if self.name:
raise FieldError('Fie... | Called during the creation of a the :class:`StdModel`
class when :class:`Metaclass` is initialised. It fills
:attr:`Field.name` and :attr:`Field.model`. This is an internal
function users should never call. | entailment |
def add_to_fields(self):
'''Add this :class:`Field` to the fields of :attr:`model`.'''
meta = self.model._meta
meta.scalarfields.append(self)
if self.index:
meta.indices.append(self) | Add this :class:`Field` to the fields of :attr:`model`. | entailment |
def get_lookup(self, remaining, errorClass=ValueError):
'''called by the :class:`Query` method when it needs to build
lookup on fields with additional nested fields. This is the case of
:class:`ForeignKey` and :class:`JSONField`.
:param remaining: the :ref:`double underscored` fields if this :class:`Field`
:pa... | called by the :class:`Query` method when it needs to build
lookup on fields with additional nested fields. This is the case of
:class:`ForeignKey` and :class:`JSONField`.
:param remaining: the :ref:`double underscored` fields if this :class:`Field`
:param errorClass: Optional exception class to use if the *remaining* ... | entailment |
def get_value(self, instance, *bits):
'''Retrieve the value :class:`Field` from a :class:`StdModel`
``instance``.
:param instance: The :class:`StdModel` ``instance`` invoking this function.
:param bits: Additional information for nested fields which derives from
the :ref:`double underscore <tutorial-unders... | Retrieve the value :class:`Field` from a :class:`StdModel`
``instance``.
:param instance: The :class:`StdModel` ``instance`` invoking this function.
:param bits: Additional information for nested fields which derives from
the :ref:`double underscore <tutorial-underscore>` notation.
:return: the value of this :clas... | entailment |
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