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DarkEnergySurvey/ugali | ugali/utils/skymap.py | surveyPixel | def surveyPixel(lon, lat, nside_pix, nside_subpix = None):
"""
Return the set of HEALPix pixels that cover the given coordinates at resolution nside.
Optionally return the set of subpixels within those pixels at resolution nside_subpix
"""
pix = np.unique(ang2pix(nside_pix, lon, lat))
if nside_s... | python | def surveyPixel(lon, lat, nside_pix, nside_subpix = None):
"""
Return the set of HEALPix pixels that cover the given coordinates at resolution nside.
Optionally return the set of subpixels within those pixels at resolution nside_subpix
"""
pix = np.unique(ang2pix(nside_pix, lon, lat))
if nside_s... | [
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DarkEnergySurvey/ugali | ugali/utils/skymap.py | allSkyCoordinates | def allSkyCoordinates(nside):
"""
Generate a set of coordinates at the centers of pixels of resolutions nside across the full sky.
"""
lon,lat = pix2ang(nside, np.arange(0, hp.nside2npix(nside)))
return lon, lat | python | def allSkyCoordinates(nside):
"""
Generate a set of coordinates at the centers of pixels of resolutions nside across the full sky.
"""
lon,lat = pix2ang(nside, np.arange(0, hp.nside2npix(nside)))
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DarkEnergySurvey/ugali | ugali/utils/skymap.py | randomPositionsMask | def randomPositionsMask(mask, nside_pix, n):
"""
Generate n random positions within a HEALPix mask of booleans.
KCB: Likely superceded by the randomPositions function, but more generic.
"""
npix = len(mask)
nside = hp.npix2nside(npix)
# Estimate the number of points that need to be th... | python | def randomPositionsMask(mask, nside_pix, n):
"""
Generate n random positions within a HEALPix mask of booleans.
KCB: Likely superceded by the randomPositions function, but more generic.
"""
npix = len(mask)
nside = hp.npix2nside(npix)
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dwavesystems/dwave_embedding_utilities | dwave_embedding_utilities.py | embed_ising | def embed_ising(source_linear, source_quadratic, embedding, target_adjacency, chain_strength=1.0):
"""Embeds a logical Ising model onto another graph via an embedding.
Args:
source_linear (dict): The linear biases to be embedded. Should be a dict of
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"""Embeds a logical Ising model onto another graph via an embedding.
Args:
source_linear (dict): The linear biases to be embedded. Should be a dict of
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dwavesystems/dwave_embedding_utilities | dwave_embedding_utilities.py | chain_break_frequency | def chain_break_frequency(samples, embedding):
"""Determines the frequency of chain breaks in the given samples.
Args:
samples (iterable): An iterable of samples where each sample
is a dict of the form {v: val, ...} where v is a variable
in the target graph and val is the associ... | python | def chain_break_frequency(samples, embedding):
"""Determines the frequency of chain breaks in the given samples.
Args:
samples (iterable): An iterable of samples where each sample
is a dict of the form {v: val, ...} where v is a variable
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dwavesystems/dwave_embedding_utilities | dwave_embedding_utilities.py | unembed_samples | def unembed_samples(samples, embedding, chain_break_method=None):
"""Return samples over the variables in the source graph.
Args:
samples (iterable): An iterable of samples where each sample
is a dict of the form {v: val, ...} where v is a variable
in the target model and val is... | python | def unembed_samples(samples, embedding, chain_break_method=None):
"""Return samples over the variables in the source graph.
Args:
samples (iterable): An iterable of samples where each sample
is a dict of the form {v: val, ...} where v is a variable
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dwavesystems/dwave_embedding_utilities | dwave_embedding_utilities.py | discard | def discard(sample, embedding):
"""Discards the sample if broken.
Args:
sample (dict): A sample of the form {v: val, ...} where v is
a variable in the target graph and val is the associated value as
determined by a binary quadratic model sampler.
embedding (dict): The ma... | python | def discard(sample, embedding):
"""Discards the sample if broken.
Args:
sample (dict): A sample of the form {v: val, ...} where v is
a variable in the target graph and val is the associated value as
determined by a binary quadratic model sampler.
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dwavesystems/dwave_embedding_utilities | dwave_embedding_utilities.py | majority_vote | def majority_vote(sample, embedding):
"""Determines the sample values by majority vote.
Args:
sample (dict): A sample of the form {v: val, ...} where v is
a variable in the target graph and val is the associated value as
determined by a binary quadratic model sampler.
em... | python | def majority_vote(sample, embedding):
"""Determines the sample values by majority vote.
Args:
sample (dict): A sample of the form {v: val, ...} where v is
a variable in the target graph and val is the associated value as
determined by a binary quadratic model sampler.
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dwavesystems/dwave_embedding_utilities | dwave_embedding_utilities.py | weighted_random | def weighted_random(sample, embedding):
"""Determines the sample values by weighed random choice.
Args:
sample (dict): A sample of the form {v: val, ...} where v is
a variable in the target graph and val is the associated value as
determined by a binary quadratic model sampler.
... | python | def weighted_random(sample, embedding):
"""Determines the sample values by weighed random choice.
Args:
sample (dict): A sample of the form {v: val, ...} where v is
a variable in the target graph and val is the associated value as
determined by a binary quadratic model sampler.
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dwavesystems/dwave_embedding_utilities | dwave_embedding_utilities.py | _all_equal | def _all_equal(iterable):
"""True if all values in `iterable` are equal, else False."""
iterator = iter(iterable)
first = next(iterator)
return all(first == rest for rest in iterator) | python | def _all_equal(iterable):
"""True if all values in `iterable` are equal, else False."""
iterator = iter(iterable)
first = next(iterator)
return all(first == rest for rest in iterator) | [
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dwavesystems/dwave_embedding_utilities | dwave_embedding_utilities.py | _most_common | def _most_common(iterable):
"""Returns the most common element in `iterable`."""
data = Counter(iterable)
return max(data, key=data.__getitem__) | python | def _most_common(iterable):
"""Returns the most common element in `iterable`."""
data = Counter(iterable)
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DarkEnergySurvey/ugali | ugali/analysis/mcmc.py | MCMC.lnlike | def lnlike(self, theta):
""" Logarithm of the likelihood """
params,loglike = self.params,self.loglike
kwargs = dict(list(zip(params,theta)))
try:
lnlike = loglike.value(**kwargs)
except ValueError as AssertionError:
lnlike = -np.inf
return lnlike | python | def lnlike(self, theta):
""" Logarithm of the likelihood """
params,loglike = self.params,self.loglike
kwargs = dict(list(zip(params,theta)))
try:
lnlike = loglike.value(**kwargs)
except ValueError as AssertionError:
lnlike = -np.inf
return lnlike | [
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DarkEnergySurvey/ugali | ugali/analysis/mcmc.py | MCMC.lnprior | def lnprior(self,theta):
""" Logarithm of the prior """
params,priors = self.params,self.priors
kwargs = dict(list(zip(params,theta)))
err = np.seterr(invalid='raise')
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except (Floati... | python | def lnprior(self,theta):
""" Logarithm of the prior """
params,priors = self.params,self.priors
kwargs = dict(list(zip(params,theta)))
err = np.seterr(invalid='raise')
try:
lnprior = np.sum(np.log([priors[k](v) for k,v in list(kwargs.items())]))
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DarkEnergySurvey/ugali | ugali/analysis/mcmc.py | MCMC.lnprob | def lnprob(self,theta):
""" Logarithm of the probability """
global niter
params,priors,loglike = self.params,self.priors,self.loglike
# Avoid extra likelihood calls with bad priors
_lnprior = self.lnprior(theta)
if np.isfinite(_lnprior):
_lnlike = self.lnlike... | python | def lnprob(self,theta):
""" Logarithm of the probability """
global niter
params,priors,loglike = self.params,self.priors,self.loglike
# Avoid extra likelihood calls with bad priors
_lnprior = self.lnprior(theta)
if np.isfinite(_lnprior):
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DarkEnergySurvey/ugali | ugali/analysis/loglike.py | write_membership | def write_membership(filename,config,srcfile,section=None):
"""
Top level interface to write the membership from a config and source model.
"""
source = Source()
source.load(srcfile,section=section)
loglike = createLoglike(config,source)
loglike.write_membership(filename) | python | def write_membership(filename,config,srcfile,section=None):
"""
Top level interface to write the membership from a config and source model.
"""
source = Source()
source.load(srcfile,section=section)
loglike = createLoglike(config,source)
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DarkEnergySurvey/ugali | ugali/analysis/loglike.py | createCatalog | def createCatalog(config,roi=None,lon=None,lat=None):
"""
Create a catalog object
"""
import ugali.observation.catalog
if roi is None: roi = createROI(config,lon,lat)
catalog = ugali.observation.catalog.Catalog(config,roi=roi)
return catalog | python | def createCatalog(config,roi=None,lon=None,lat=None):
"""
Create a catalog object
"""
import ugali.observation.catalog
if roi is None: roi = createROI(config,lon,lat)
catalog = ugali.observation.catalog.Catalog(config,roi=roi)
return catalog | [
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DarkEnergySurvey/ugali | ugali/analysis/loglike.py | simulateCatalog | def simulateCatalog(config,roi=None,lon=None,lat=None):
"""
Simulate a catalog object.
"""
import ugali.simulation.simulator
if roi is None: roi = createROI(config,lon,lat)
sim = ugali.simulation.simulator.Simulator(config,roi)
return sim.catalog() | python | def simulateCatalog(config,roi=None,lon=None,lat=None):
"""
Simulate a catalog object.
"""
import ugali.simulation.simulator
if roi is None: roi = createROI(config,lon,lat)
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DarkEnergySurvey/ugali | ugali/analysis/loglike.py | LogLikelihood.calc_observable_fraction | def calc_observable_fraction(self,distance_modulus):
"""
Calculated observable fraction within each pixel of the target region.
"""
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observable_fraction = self.isochrone.observableFraction(... | python | def calc_observable_fraction(self,distance_modulus):
"""
Calculated observable fraction within each pixel of the target region.
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DarkEnergySurvey/ugali | ugali/analysis/loglike.py | LogLikelihood.calc_signal_spatial | def calc_signal_spatial(self):
"""
Calculate the spatial signal probability for each catalog object.
Parameters:
-----------
None
Returns:
--------
u_spatial : array of spatial probabilities per object
"""
# Calculate the surface intensit... | python | def calc_signal_spatial(self):
"""
Calculate the spatial signal probability for each catalog object.
Parameters:
-----------
None
Returns:
--------
u_spatial : array of spatial probabilities per object
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DarkEnergySurvey/ugali | ugali/analysis/loglike.py | LogLikelihood.fit_richness | def fit_richness(self, atol=1.e-3, maxiter=50):
"""
Maximize the log-likelihood as a function of richness.
ADW 2018-06-04: Does it make sense to set the richness to the mle?
Parameters:
-----------
atol : absolute tolerence for conversion
maxiter : maximum numbe... | python | def fit_richness(self, atol=1.e-3, maxiter=50):
"""
Maximize the log-likelihood as a function of richness.
ADW 2018-06-04: Does it make sense to set the richness to the mle?
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atol : absolute tolerence for conversion
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akx/lepo | lepo/apidef/doc.py | APIDefinition.resolve_reference | def resolve_reference(self, ref):
"""
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:param ref: Reference string (`#/foo/bar`, for instance)
:return: The object, if found
:raises jsonschema.exceptions.RefResolutionError: if there is trouble resolving the referenc... | python | def resolve_reference(self, ref):
"""
Resolve a JSON Pointer object reference to the object itself.
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:return: The object, if found
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akx/lepo | lepo/apidef/doc.py | APIDefinition.get_path | def get_path(self, path):
"""
Construct a Path object from a path string.
The Path string must be declared in the API.
:type path: str
:rtype: lepo.path.Path
"""
mapping = self.get_path_mapping(path)
return self.path_class(api=self, path=path, mapping=ma... | python | def get_path(self, path):
"""
Construct a Path object from a path string.
The Path string must be declared in the API.
:type path: str
:rtype: lepo.path.Path
"""
mapping = self.get_path_mapping(path)
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akx/lepo | lepo/apidef/doc.py | APIDefinition.from_file | def from_file(cls, filename):
"""
Construct an APIDefinition by parsing the given `filename`.
If PyYAML is installed, YAML files are supported.
JSON files are always supported.
:param filename: The filename to read.
:rtype: APIDefinition
"""
with open(fi... | python | def from_file(cls, filename):
"""
Construct an APIDefinition by parsing the given `filename`.
If PyYAML is installed, YAML files are supported.
JSON files are always supported.
:param filename: The filename to read.
:rtype: APIDefinition
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juju/theblues | theblues/utils.py | _server_error_message | def _server_error_message(url, message):
"""Log and return a server error message."""
msg = _error_message.format(url=url, message=message)
log.error(msg)
return msg | python | def _server_error_message(url, message):
"""Log and return a server error message."""
msg = _error_message.format(url=url, message=message)
log.error(msg)
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juju/theblues | theblues/utils.py | make_request | def make_request(
url, method='GET', query=None, body=None, auth=None, timeout=10,
client=None, macaroons=None):
"""Make a request with the provided data.
@param url The url to make the request to.
@param method The HTTP request method (defaulting to "GET").
@param query A dict of the q... | python | def make_request(
url, method='GET', query=None, body=None, auth=None, timeout=10,
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"""Make a request with the provided data.
@param url The url to make the request to.
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juju/theblues | theblues/plans.py | Plans.get_plans | def get_plans(self, reference):
"""Get the plans for a given charm.
@param the Reference to a charm.
@return a tuple of plans or an empty tuple if no plans.
@raise ServerError
"""
response = make_request(
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... | python | def get_plans(self, reference):
"""Get the plans for a given charm.
@param the Reference to a charm.
@return a tuple of plans or an empty tuple if no plans.
@raise ServerError
"""
response = make_request(
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juju/theblues | theblues/plans.py | Plans.list_wallets | def list_wallets(self):
"""Get the list of wallets.
@return an dict containing a list of wallets, a total, and available
credit.
@raise ServerError
"""
response = make_request(
'{}wallet'.format(self.url),
timeout=self.timeout,
cli... | python | def list_wallets(self):
"""Get the list of wallets.
@return an dict containing a list of wallets, a total, and available
credit.
@raise ServerError
"""
response = make_request(
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timeout=self.timeout,
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juju/theblues | theblues/plans.py | Plans.get_wallet | def get_wallet(self, wallet_name):
"""Get a single wallet.
@param the name of the wallet.
@return the wallet's total.
@raise ServerError
"""
response = make_request(
'{}wallet/{}'.format(self.url, wallet_name),
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cl... | python | def get_wallet(self, wallet_name):
"""Get a single wallet.
@param the name of the wallet.
@return the wallet's total.
@raise ServerError
"""
response = make_request(
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juju/theblues | theblues/plans.py | Plans.update_wallet | def update_wallet(self, wallet_name, limit):
"""Update a wallet with a new limit.
@param the name of the wallet.
@param the new value of the limit.
@return a success string from the plans server.
@raise ServerError via make_request.
"""
request = {
'u... | python | def update_wallet(self, wallet_name, limit):
"""Update a wallet with a new limit.
@param the name of the wallet.
@param the new value of the limit.
@return a success string from the plans server.
@raise ServerError via make_request.
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juju/theblues | theblues/plans.py | Plans.delete_wallet | def delete_wallet(self, wallet_name):
"""Delete a wallet.
@param the name of the wallet.
@return a success string from the plans server.
@raise ServerError via make_request.
"""
return make_request(
'{}wallet/{}'.format(self.url, wallet_name),
met... | python | def delete_wallet(self, wallet_name):
"""Delete a wallet.
@param the name of the wallet.
@return a success string from the plans server.
@raise ServerError via make_request.
"""
return make_request(
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juju/theblues | theblues/plans.py | Plans.create_budget | def create_budget(self, wallet_name, model_uuid, limit):
"""Create a new budget for a model and wallet.
@param the name of the wallet.
@param the model UUID.
@param the new value of the limit.
@return a success string from the plans server.
@raise ServerError via make_re... | python | def create_budget(self, wallet_name, model_uuid, limit):
"""Create a new budget for a model and wallet.
@param the name of the wallet.
@param the model UUID.
@param the new value of the limit.
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juju/theblues | theblues/plans.py | Plans.delete_budget | def delete_budget(self, model_uuid):
"""Delete a budget.
@param the name of the wallet.
@param the model UUID.
@return a success string from the plans server.
@raise ServerError via make_request.
"""
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'{}model/{}/budget'.format(sel... | python | def delete_budget(self, model_uuid):
"""Delete a budget.
@param the name of the wallet.
@param the model UUID.
@return a success string from the plans server.
@raise ServerError via make_request.
"""
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totalgood/pugnlp | src/pugnlp/stats.py | confusion | def confusion(df, labels=['neg', 'pos']):
""" Binary classification confusion """
c = pd.DataFrame(np.zeros((2, 2)), dtype=int)
a, b = df.columns[:2] # labels[df.columns[:2]]
c.columns = sorted(set(df[a]))[:2]
c.columns.name = a
c.index = list(c.columns)
c.index.name = b
c1, c2 = c.colu... | python | def confusion(df, labels=['neg', 'pos']):
""" Binary classification confusion """
c = pd.DataFrame(np.zeros((2, 2)), dtype=int)
a, b = df.columns[:2] # labels[df.columns[:2]]
c.columns = sorted(set(df[a]))[:2]
c.columns.name = a
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totalgood/pugnlp | src/pugnlp/stats.py | thresh_from_spec | def thresh_from_spec(spec, labels, scores, **kwargs):
r"""Find the threshold level that accomplishes the desired specificity"""
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cost_fun.target = spec
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stevearc/dynamo3 | dynamo3/result.py | add_dicts | def add_dicts(d1, d2):
""" Merge two dicts of addable values """
if d1 is None:
return d2
if d2 is None:
return d1
keys = set(d1)
keys.update(set(d2))
ret = {}
for key in keys:
v1 = d1.get(key)
v2 = d2.get(key)
if v1 is None:
ret[key] = v2
... | python | def add_dicts(d1, d2):
""" Merge two dicts of addable values """
if d1 is None:
return d2
if d2 is None:
return d1
keys = set(d1)
keys.update(set(d2))
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stevearc/dynamo3 | dynamo3/result.py | PagedIterator._update_capacity | def _update_capacity(self, data):
""" Update the consumed capacity metrics """
if 'ConsumedCapacity' in data:
# This is all for backwards compatibility
consumed = data['ConsumedCapacity']
if not isinstance(consumed, list):
consumed = [consumed]
... | python | def _update_capacity(self, data):
""" Update the consumed capacity metrics """
if 'ConsumedCapacity' in data:
# This is all for backwards compatibility
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stevearc/dynamo3 | dynamo3/result.py | ResultSet.fetch | def fetch(self):
""" Fetch more results from Dynamo """
self.limit.set_request_args(self.kwargs)
data = self.connection.call(*self.args, **self.kwargs)
self.limit.post_fetch(data)
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... | python | def fetch(self):
""" Fetch more results from Dynamo """
self.limit.set_request_args(self.kwargs)
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self.limit.post_fetch(data)
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stevearc/dynamo3 | dynamo3/result.py | GetResultSet.build_kwargs | def build_kwargs(self):
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stevearc/dynamo3 | dynamo3/result.py | GetResultSet.fetch | def fetch(self):
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stevearc/dynamo3 | dynamo3/result.py | Limit.copy | def copy(self):
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stevearc/dynamo3 | dynamo3/result.py | Limit.set_request_args | def set_request_args(self, args):
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aht/stream.py | example/randwalk.py | returned | def returned(n):
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aht/stream.py | stream.py | seq | def seq(start=0, step=1):
"""An arithmetic sequence generator. Works with any type with + defined.
>>> seq(1, 0.25) >> item[:10]
[1, 1.25, 1.5, 1.75, 2.0, 2.25, 2.5, 2.75, 3.0, 3.25]
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return seq(start, step) | python | def seq(start=0, step=1):
"""An arithmetic sequence generator. Works with any type with + defined.
>>> seq(1, 0.25) >> item[:10]
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DarkEnergySurvey/ugali | ugali/isochrone/model.py | sum_mags | def sum_mags(mags, weights=None):
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mags : array of magnitudes
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"""
Sum an array of magnitudes in flux space.
Parameters:
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mags : array of magnitudes
weights : array of weights for each magnitude (i.e. from a pdf)
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sum_mag : the summed magnitude of all the stars
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DarkEnergySurvey/ugali | ugali/isochrone/model.py | absolute_magnitude | def absolute_magnitude(distance_modulus,g,r,prob=None):
""" Calculate the absolute magnitude from a set of bands """
V = g - 0.487*(g - r) - 0.0249
flux = np.sum(10**(-(V-distance_modulus)/2.5))
Mv = -2.5*np.log10(flux)
return Mv | python | def absolute_magnitude(distance_modulus,g,r,prob=None):
""" Calculate the absolute magnitude from a set of bands """
V = g - 0.487*(g - r) - 0.0249
flux = np.sum(10**(-(V-distance_modulus)/2.5))
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DarkEnergySurvey/ugali | ugali/isochrone/model.py | IsochroneModel.observableFractionCDF | def observableFractionCDF(self, mask, distance_modulus, mass_min=0.1):
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DarkEnergySurvey/ugali | ugali/isochrone/model.py | IsochroneModel.histogram2d | def histogram2d(self,distance_modulus=None,delta_mag=0.03,steps=10000):
"""
Return a 2D histogram the isochrone in mag-mag space.
Parameters:
-----------
distance_modulus : distance modulus to calculate histogram at
delta_mag : magnitude bin size
mass_steps : num... | python | def histogram2d(self,distance_modulus=None,delta_mag=0.03,steps=10000):
"""
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DarkEnergySurvey/ugali | ugali/isochrone/model.py | IsochroneModel.pdf_mmd | def pdf_mmd(self, lon, lat, mag_1, mag_2, distance_modulus, mask, delta_mag=0.03, steps=1000):
"""
Ok, now here comes the beauty of having the signal MMD.
"""
logger.info('Running MMD pdf')
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"""
Ok, now here comes the beauty of having the signal MMD.
"""
logger.info('Running MMD pdf')
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DarkEnergySurvey/ugali | ugali/isochrone/model.py | IsochroneModel.raw_separation | def raw_separation(self,mag_1,mag_2,steps=10000):
"""
Calculate the separation in magnitude-magnitude space between points and isochrone. Uses a dense sampling of the isochrone and calculates the metric distance from any isochrone sample point.
Parameters:
-----------
mag_1 : T... | python | def raw_separation(self,mag_1,mag_2,steps=10000):
"""
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DarkEnergySurvey/ugali | ugali/isochrone/model.py | IsochroneModel.separation | def separation(self, mag_1, mag_2):
"""
Calculate the separation between a specific point and the
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ADW: Could speed this up...
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mag_1 : The magnitude of the test points in the f... | python | def separation(self, mag_1, mag_2):
"""
Calculate the separation between a specific point and the
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akx/lepo | lepo/router.py | Router.get_handler | def get_handler(self, operation_id):
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consbio/ncdjango | ncdjango/geoprocessing/tasks/raster.py | SingleArrayExpressionBase.get_context | def get_context(self, arr, expr, context):
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Returns a context dictionary for use in evaluating the expression.
:param arr: The input array.
:param expr: The input expression.
:param context: Evaluation context.
"""
expression_names = [x for x in self.get_expr... | python | def get_context(self, arr, expr, context):
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consbio/ncdjango | ncdjango/geoprocessing/tasks/raster.py | MaskByExpression.execute | def execute(self, array_in, expression, **kwargs):
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DarkEnergySurvey/ugali | ugali/utils/plotting.py | histogram | def histogram(title, title_x, title_y,
x, bins_x):
"""
Plot a basic histogram.
"""
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plt.xlabel(title_x)
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plt.title(title) | python | def histogram(title, title_x, title_y,
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"""
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DarkEnergySurvey/ugali | ugali/utils/plotting.py | twoDimensionalHistogram | def twoDimensionalHistogram(title, title_x, title_y,
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DarkEnergySurvey/ugali | ugali/utils/plotting.py | twoDimensionalScatter | def twoDimensionalScatter(title, title_x, title_y,
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Create a two-dimensional scatter plot.
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DarkEnergySurvey/ugali | ugali/utils/plotting.py | drawHealpixMap | def drawHealpixMap(hpxmap, lon, lat, size=1.0, xsize=501, coord='GC', **kwargs):
"""
Draw local projection of healpix map.
"""
ax = plt.gca()
x = np.linspace(-size,size,xsize)
y = np.linspace(-size,size,xsize)
xx, yy = np.meshgrid(x,y)
coord = coord.upper()
if coord == ... | python | def drawHealpixMap(hpxmap, lon, lat, size=1.0, xsize=501, coord='GC', **kwargs):
"""
Draw local projection of healpix map.
"""
ax = plt.gca()
x = np.linspace(-size,size,xsize)
y = np.linspace(-size,size,xsize)
xx, yy = np.meshgrid(x,y)
coord = coord.upper()
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DarkEnergySurvey/ugali | ugali/utils/plotting.py | getDSSImage | def getDSSImage(ra,dec,radius=1.0,xsize=800,**kwargs):
"""
Download Digitized Sky Survey images
https://archive.stsci.edu/cgi-bin/dss_form
https://archive.stsci.edu/cgi-bin/dss_search
Image is in celestial orientation (RA increases to the right)
https://archive.stsci.edu/dss/script_usage.h... | python | def getDSSImage(ra,dec,radius=1.0,xsize=800,**kwargs):
"""
Download Digitized Sky Survey images
https://archive.stsci.edu/cgi-bin/dss_form
https://archive.stsci.edu/cgi-bin/dss_search
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DarkEnergySurvey/ugali | ugali/utils/plotting.py | draw_slices | def draw_slices(hist, func=np.sum, **kwargs):
""" Draw horizontal and vertical slices through histogram """
from mpl_toolkits.axes_grid1 import make_axes_locatable
kwargs.setdefault('ls','-')
ax = plt.gca()
data = hist
# Slices
vslice = func(data,axis=0)
hslice = func(data,axis=1)
... | python | def draw_slices(hist, func=np.sum, **kwargs):
""" Draw horizontal and vertical slices through histogram """
from mpl_toolkits.axes_grid1 import make_axes_locatable
kwargs.setdefault('ls','-')
ax = plt.gca()
data = hist
# Slices
vslice = func(data,axis=0)
hslice = func(data,axis=1)
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DarkEnergySurvey/ugali | ugali/utils/plotting.py | plotSkymapCatalog | def plotSkymapCatalog(lon,lat,**kwargs):
"""
Plot a catalog of coordinates on a full-sky map.
"""
fig = plt.figure()
ax = plt.subplot(111,projection=projection)
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"""
Plot a catalog of coordinates on a full-sky map.
"""
fig = plt.figure()
ax = plt.subplot(111,projection=projection)
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DarkEnergySurvey/ugali | ugali/utils/plotting.py | makePath | def makePath(x_path, y_path, epsilon=1.e-10):
"""
Create closed path.
"""
x_path_closed = np.concatenate([x_path, x_path[::-1]])
y_path_closed = np.concatenate([y_path, epsilon + y_path[::-1]])
path = matplotlib.path.Path(list(zip(x_path_closed, y_path_closed)))
return path | python | def makePath(x_path, y_path, epsilon=1.e-10):
"""
Create closed path.
"""
x_path_closed = np.concatenate([x_path, x_path[::-1]])
y_path_closed = np.concatenate([y_path, epsilon + y_path[::-1]])
path = matplotlib.path.Path(list(zip(x_path_closed, y_path_closed)))
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DarkEnergySurvey/ugali | ugali/utils/plotting.py | BasePlotter.drawMask | def drawMask(self,ax=None, mask=None, mtype='maglim'):
""" Draw the maglim from the mask. """
if not ax: ax = plt.gca()
if mask is None:
mask = ugali.analysis.loglike.createMask(self.config,roi=self.roi)
mask_map = hp.UNSEEN*np.ones(hp.nside2npix(self.nside))
if mtyp... | python | def drawMask(self,ax=None, mask=None, mtype='maglim'):
""" Draw the maglim from the mask. """
if not ax: ax = plt.gca()
if mask is None:
mask = ugali.analysis.loglike.createMask(self.config,roi=self.roi)
mask_map = hp.UNSEEN*np.ones(hp.nside2npix(self.nside))
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warrenspe/hconf | hconf/subparsers/ini.py | INI.parse | def parse(self, configManager, config):
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Parse configuration options out of an .ini configuration file.
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config - The _Config object containing configuration options popul... | python | def parse(self, configManager, config):
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Parse configuration options out of an .ini configuration file.
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"""
Create a chapter
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kallimachos/sphinxmark | sphinxmark/__init__.py | buildcss | def buildcss(app, buildpath, imagefile):
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div = 'body'
repeat = 'repeat-y'
position = 'center'
attachment = 'scroll'
if app.config.sphinxmark_div != 'default':
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"""Create CSS file."""
# set default values
div = 'body'
repeat = 'repeat-y'
position = 'center'
attachment = 'scroll'
if app.config.sphinxmark_div != 'default':
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height = app.config.sphinxmark_text_spacing
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"""Create PNG image from string."""
text = app.config.sphinxmark_text
# draw transparent background
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# append source directory to TEMPLATE_PATH so template is found
srcdir = os.path.abspath(os.path.dirname(__file__))
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kallimachos/sphinxmark | sphinxmark/__init__.py | watermark | def watermark(app, env):
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Configure setup for Sphinx extension.
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DarkEnergySurvey/ugali | ugali/utils/bayesian_efficiency.py | gammalnStirling | def gammalnStirling(z):
"""
Uses Stirling's approximation for the log-gamma function suitable for large arguments.
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return (0.5 * (np.log(2. * np.pi) - np.log(z))) \
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"""
Uses Stirling's approximation for the log-gamma function suitable for large arguments.
"""
return (0.5 * (np.log(2. * np.pi) - np.log(z))) \
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DarkEnergySurvey/ugali | ugali/simulation/simulator.py | satellite | def satellite(isochrone, kernel, stellar_mass, distance_modulus,**kwargs):
"""
Wrapping the isochrone and kernel simulate functions.
"""
mag_1, mag_2 = isochrone.simulate(stellar_mass, distance_modulus)
lon, lat = kernel.simulate(len(mag_1))
return mag_1, mag_2, lon, lat | python | def satellite(isochrone, kernel, stellar_mass, distance_modulus,**kwargs):
"""
Wrapping the isochrone and kernel simulate functions.
"""
mag_1, mag_2 = isochrone.simulate(stellar_mass, distance_modulus)
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DarkEnergySurvey/ugali | ugali/simulation/simulator.py | Generator.detectability | def detectability(self,**kwargs):
"""
An a priori detectability proxy.
"""
distance_modulus = kwargs.get('distance_modulus')
distance = mod2dist(distance_modulus)
stellar_mass = kwargs.get('stellar_mass')
extension = kwargs.get('extension')
# Normalized t... | python | def detectability(self,**kwargs):
"""
An a priori detectability proxy.
"""
distance_modulus = kwargs.get('distance_modulus')
distance = mod2dist(distance_modulus)
stellar_mass = kwargs.get('stellar_mass')
extension = kwargs.get('extension')
# Normalized t... | [
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DarkEnergySurvey/ugali | ugali/simulation/simulator.py | Simulator._create_catalog | def _create_catalog(self,catalog=None):
"""
Bundle it.
"""
if catalog is None:
catalog = ugali.analysis.loglike.createCatalog(self.config,self.roi)
cut = self.mask.restrictCatalogToObservableSpace(catalog)
self.catalog = catalog.applyCut(cut) | python | def _create_catalog(self,catalog=None):
"""
Bundle it.
"""
if catalog is None:
catalog = ugali.analysis.loglike.createCatalog(self.config,self.roi)
cut = self.mask.restrictCatalogToObservableSpace(catalog)
self.catalog = catalog.applyCut(cut) | [
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DarkEnergySurvey/ugali | ugali/simulation/simulator.py | Simulator._setup_subpix | def _setup_subpix(self,nside=2**16):
"""
Subpixels for random position generation.
"""
# Only setup once...
if hasattr(self,'subpix'): return
# Simulate over full ROI
self.roi_radius = self.config['coords']['roi_radius']
# Setup background spatial stuff... | python | def _setup_subpix(self,nside=2**16):
"""
Subpixels for random position generation.
"""
# Only setup once...
if hasattr(self,'subpix'): return
# Simulate over full ROI
self.roi_radius = self.config['coords']['roi_radius']
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DarkEnergySurvey/ugali | ugali/simulation/simulator.py | Simulator._setup_cmd | def _setup_cmd(self,mode='cloud-in-cells'):
"""
The purpose here is to create a more finely binned
background CMD to sample from.
"""
# Only setup once...
if hasattr(self,'bkg_lambda'): return
logger.info("Setup color...")
# In the limit theta->0: 2*pi*(1... | python | def _setup_cmd(self,mode='cloud-in-cells'):
"""
The purpose here is to create a more finely binned
background CMD to sample from.
"""
# Only setup once...
if hasattr(self,'bkg_lambda'): return
logger.info("Setup color...")
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DarkEnergySurvey/ugali | ugali/simulation/simulator.py | Simulator.toy_background | def toy_background(self,mc_source_id=2,seed=None):
"""
Quick uniform background generation.
"""
logger.info("Running toy background simulation...")
size = 20000
nstar = np.random.poisson(size)
#np.random.seed(0)
logger.info("Simulating %i background stars... | python | def toy_background(self,mc_source_id=2,seed=None):
"""
Quick uniform background generation.
"""
logger.info("Running toy background simulation...")
size = 20000
nstar = np.random.poisson(size)
#np.random.seed(0)
logger.info("Simulating %i background stars... | [
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DarkEnergySurvey/ugali | ugali/simulation/simulator.py | Simulator.satellite | def satellite(self,stellar_mass,distance_modulus,mc_source_id=1,seed=None,**kwargs):
"""
Create a simulated satellite. Returns a catalog object.
"""
if seed is not None: np.random.seed(seed)
isochrone = kwargs.pop('isochrone',self.isochrone)
kernel = kwargs.pop('kerne... | python | def satellite(self,stellar_mass,distance_modulus,mc_source_id=1,seed=None,**kwargs):
"""
Create a simulated satellite. Returns a catalog object.
"""
if seed is not None: np.random.seed(seed)
isochrone = kwargs.pop('isochrone',self.isochrone)
kernel = kwargs.pop('kerne... | [
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DarkEnergySurvey/ugali | ugali/simulation/simulator.py | Simulator.makeHDU | def makeHDU(self, mag_1, mag_err_1, mag_2, mag_err_2, lon, lat, mc_source_id):
"""
Create a catalog fits file object based on input data.
ADW: This should be combined with the write_membership
function of loglike.
"""
if self.config['catalog']['coordsys'].lower() == 'cel... | python | def makeHDU(self, mag_1, mag_err_1, mag_2, mag_err_2, lon, lat, mc_source_id):
"""
Create a catalog fits file object based on input data.
ADW: This should be combined with the write_membership
function of loglike.
"""
if self.config['catalog']['coordsys'].lower() == 'cel... | [
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totalgood/pugnlp | src/pugnlp/util.py | inverted_dict | def inverted_dict(d):
"""Return a dict with swapped keys and values
>>> inverted_dict({0: ('a', 'b'), 1: 'cd'}) == {'cd': 1, ('a', 'b'): 0}
True
"""
return dict((force_hashable(v), k) for (k, v) in viewitems(dict(d))) | python | def inverted_dict(d):
"""Return a dict with swapped keys and values
>>> inverted_dict({0: ('a', 'b'), 1: 'cd'}) == {'cd': 1, ('a', 'b'): 0}
True
"""
return dict((force_hashable(v), k) for (k, v) in viewitems(dict(d))) | [
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totalgood/pugnlp | src/pugnlp/util.py | inverted_dict_of_lists | def inverted_dict_of_lists(d):
"""Return a dict where the keys are all the values listed in the values of the original dict
>>> inverted_dict_of_lists({0: ['a', 'b'], 1: 'cd'}) == {'a': 0, 'b': 0, 'cd': 1}
True
"""
new_dict = {}
for (old_key, old_value_list) in viewitems(dict(d)):
for n... | python | def inverted_dict_of_lists(d):
"""Return a dict where the keys are all the values listed in the values of the original dict
>>> inverted_dict_of_lists({0: ['a', 'b'], 1: 'cd'}) == {'a': 0, 'b': 0, 'cd': 1}
True
"""
new_dict = {}
for (old_key, old_value_list) in viewitems(dict(d)):
for n... | [
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