repo stringlengths 7 55 | path stringlengths 4 127 | func_name stringlengths 1 88 | original_string stringlengths 75 19.8k | language stringclasses 1
value | code stringlengths 75 19.8k | code_tokens list | docstring stringlengths 3 17.3k | docstring_tokens list | sha stringlengths 40 40 | url stringlengths 87 242 | partition stringclasses 1
value |
|---|---|---|---|---|---|---|---|---|---|---|---|
profusion/sgqlc | sgqlc/types/relay.py | connection_args | def connection_args(*lst, **mapping):
'''Returns the default parameters for connection.
Extra parameters may be given as argument, both as iterable,
positional tuples or mapping.
By default, provides:
- ``after: String``
- ``before: String``
- ``first: Int``
- ``last: Int``
''... | python | def connection_args(*lst, **mapping):
'''Returns the default parameters for connection.
Extra parameters may be given as argument, both as iterable,
positional tuples or mapping.
By default, provides:
- ``after: String``
- ``before: String``
- ``first: Int``
- ``last: Int``
''... | [
"def",
"connection_args",
"(",
"*",
"lst",
",",
"**",
"mapping",
")",
":",
"pd",
"=",
"ArgDict",
"(",
"*",
"lst",
",",
"**",
"mapping",
")",
"pd",
".",
"setdefault",
"(",
"'after'",
",",
"String",
")",
"pd",
".",
"setdefault",
"(",
"'before'",
",",
... | Returns the default parameters for connection.
Extra parameters may be given as argument, both as iterable,
positional tuples or mapping.
By default, provides:
- ``after: String``
- ``before: String``
- ``first: Int``
- ``last: Int`` | [
"Returns",
"the",
"default",
"parameters",
"for",
"connection",
"."
] | 684afb059c93f142150043cafac09b7fd52bfa27 | https://github.com/profusion/sgqlc/blob/684afb059c93f142150043cafac09b7fd52bfa27/sgqlc/types/relay.py#L406-L424 | train |
nchopin/particles | book/pmcmc/pmmh_lingauss_varying_scale.py | msjd | def msjd(theta):
"""Mean squared jumping distance.
"""
s = 0.
for p in theta.dtype.names:
s += np.sum(np.diff(theta[p], axis=0) ** 2)
return s | python | def msjd(theta):
"""Mean squared jumping distance.
"""
s = 0.
for p in theta.dtype.names:
s += np.sum(np.diff(theta[p], axis=0) ** 2)
return s | [
"def",
"msjd",
"(",
"theta",
")",
":",
"s",
"=",
"0.",
"for",
"p",
"in",
"theta",
".",
"dtype",
".",
"names",
":",
"s",
"+=",
"np",
".",
"sum",
"(",
"np",
".",
"diff",
"(",
"theta",
"[",
"p",
"]",
",",
"axis",
"=",
"0",
")",
"**",
"2",
")... | Mean squared jumping distance. | [
"Mean",
"squared",
"jumping",
"distance",
"."
] | 3faa97a1073db45c5889eef3e015dd76ef350b52 | https://github.com/nchopin/particles/blob/3faa97a1073db45c5889eef3e015dd76ef350b52/book/pmcmc/pmmh_lingauss_varying_scale.py#L31-L37 | train |
nchopin/particles | particles/smc_samplers.py | StaticModel.loglik | def loglik(self, theta, t=None):
""" log-likelihood at given parameter values.
Parameters
----------
theta: dict-like
theta['par'] is a ndarray containing the N values for parameter par
t: int
time (if set to None, the full log-likelihood is returned)
... | python | def loglik(self, theta, t=None):
""" log-likelihood at given parameter values.
Parameters
----------
theta: dict-like
theta['par'] is a ndarray containing the N values for parameter par
t: int
time (if set to None, the full log-likelihood is returned)
... | [
"def",
"loglik",
"(",
"self",
",",
"theta",
",",
"t",
"=",
"None",
")",
":",
"if",
"t",
"is",
"None",
":",
"t",
"=",
"self",
".",
"T",
"-",
"1",
"l",
"=",
"np",
".",
"zeros",
"(",
"shape",
"=",
"theta",
".",
"shape",
"[",
"0",
"]",
")",
"... | log-likelihood at given parameter values.
Parameters
----------
theta: dict-like
theta['par'] is a ndarray containing the N values for parameter par
t: int
time (if set to None, the full log-likelihood is returned)
Returns
-------
l: fl... | [
"log",
"-",
"likelihood",
"at",
"given",
"parameter",
"values",
"."
] | 3faa97a1073db45c5889eef3e015dd76ef350b52 | https://github.com/nchopin/particles/blob/3faa97a1073db45c5889eef3e015dd76ef350b52/particles/smc_samplers.py#L91-L111 | train |
nchopin/particles | particles/smc_samplers.py | StaticModel.logpost | def logpost(self, theta, t=None):
"""Posterior log-density at given parameter values.
Parameters
----------
theta: dict-like
theta['par'] is a ndarray containing the N values for parameter par
t: int
time (if set to None, the full posterior is returned)... | python | def logpost(self, theta, t=None):
"""Posterior log-density at given parameter values.
Parameters
----------
theta: dict-like
theta['par'] is a ndarray containing the N values for parameter par
t: int
time (if set to None, the full posterior is returned)... | [
"def",
"logpost",
"(",
"self",
",",
"theta",
",",
"t",
"=",
"None",
")",
":",
"return",
"self",
".",
"prior",
".",
"logpdf",
"(",
"theta",
")",
"+",
"self",
".",
"loglik",
"(",
"theta",
",",
"t",
")"
] | Posterior log-density at given parameter values.
Parameters
----------
theta: dict-like
theta['par'] is a ndarray containing the N values for parameter par
t: int
time (if set to None, the full posterior is returned)
Returns
-------
l: ... | [
"Posterior",
"log",
"-",
"density",
"at",
"given",
"parameter",
"values",
"."
] | 3faa97a1073db45c5889eef3e015dd76ef350b52 | https://github.com/nchopin/particles/blob/3faa97a1073db45c5889eef3e015dd76ef350b52/particles/smc_samplers.py#L113-L128 | train |
nchopin/particles | particles/smc_samplers.py | FancyList.copyto | def copyto(self, src, where=None):
"""
Same syntax and functionality as numpy.copyto
"""
for n, _ in enumerate(self.l):
if where[n]:
self.l[n] = src.l[n] | python | def copyto(self, src, where=None):
"""
Same syntax and functionality as numpy.copyto
"""
for n, _ in enumerate(self.l):
if where[n]:
self.l[n] = src.l[n] | [
"def",
"copyto",
"(",
"self",
",",
"src",
",",
"where",
"=",
"None",
")",
":",
"for",
"n",
",",
"_",
"in",
"enumerate",
"(",
"self",
".",
"l",
")",
":",
"if",
"where",
"[",
"n",
"]",
":",
"self",
".",
"l",
"[",
"n",
"]",
"=",
"src",
".",
... | Same syntax and functionality as numpy.copyto | [
"Same",
"syntax",
"and",
"functionality",
"as",
"numpy",
".",
"copyto"
] | 3faa97a1073db45c5889eef3e015dd76ef350b52 | https://github.com/nchopin/particles/blob/3faa97a1073db45c5889eef3e015dd76ef350b52/particles/smc_samplers.py#L178-L185 | train |
nchopin/particles | particles/smc_samplers.py | ThetaParticles.copy | def copy(self):
"""Returns a copy of the object."""
attrs = {k: self.__dict__[k].copy() for k in self.containers}
attrs.update({k: cp.deepcopy(self.__dict__[k]) for k in self.shared})
return self.__class__(**attrs) | python | def copy(self):
"""Returns a copy of the object."""
attrs = {k: self.__dict__[k].copy() for k in self.containers}
attrs.update({k: cp.deepcopy(self.__dict__[k]) for k in self.shared})
return self.__class__(**attrs) | [
"def",
"copy",
"(",
"self",
")",
":",
"attrs",
"=",
"{",
"k",
":",
"self",
".",
"__dict__",
"[",
"k",
"]",
".",
"copy",
"(",
")",
"for",
"k",
"in",
"self",
".",
"containers",
"}",
"attrs",
".",
"update",
"(",
"{",
"k",
":",
"cp",
".",
"deepco... | Returns a copy of the object. | [
"Returns",
"a",
"copy",
"of",
"the",
"object",
"."
] | 3faa97a1073db45c5889eef3e015dd76ef350b52 | https://github.com/nchopin/particles/blob/3faa97a1073db45c5889eef3e015dd76ef350b52/particles/smc_samplers.py#L245-L249 | train |
nchopin/particles | particles/smc_samplers.py | ThetaParticles.copyto | def copyto(self, src, where=None):
"""Emulates function `copyto` in NumPy.
Parameters
----------
where: (N,) bool ndarray
True if particle n in src must be copied.
src: (N,) `ThetaParticles` object
source
for each n such that where[n] is True, cop... | python | def copyto(self, src, where=None):
"""Emulates function `copyto` in NumPy.
Parameters
----------
where: (N,) bool ndarray
True if particle n in src must be copied.
src: (N,) `ThetaParticles` object
source
for each n such that where[n] is True, cop... | [
"def",
"copyto",
"(",
"self",
",",
"src",
",",
"where",
"=",
"None",
")",
":",
"for",
"k",
"in",
"self",
".",
"containers",
":",
"v",
"=",
"self",
".",
"__dict__",
"[",
"k",
"]",
"if",
"isinstance",
"(",
"v",
",",
"np",
".",
"ndarray",
")",
":"... | Emulates function `copyto` in NumPy.
Parameters
----------
where: (N,) bool ndarray
True if particle n in src must be copied.
src: (N,) `ThetaParticles` object
source
for each n such that where[n] is True, copy particle n in src
into self (at locat... | [
"Emulates",
"function",
"copyto",
"in",
"NumPy",
"."
] | 3faa97a1073db45c5889eef3e015dd76ef350b52 | https://github.com/nchopin/particles/blob/3faa97a1073db45c5889eef3e015dd76ef350b52/particles/smc_samplers.py#L251-L270 | train |
nchopin/particles | particles/smc_samplers.py | ThetaParticles.copyto_at | def copyto_at(self, n, src, m):
"""Copy to at a given location.
Parameters
----------
n: int
index where to copy
src: `ThetaParticles` object
source
m: int
index of the element to be copied
Note
----
Basical... | python | def copyto_at(self, n, src, m):
"""Copy to at a given location.
Parameters
----------
n: int
index where to copy
src: `ThetaParticles` object
source
m: int
index of the element to be copied
Note
----
Basical... | [
"def",
"copyto_at",
"(",
"self",
",",
"n",
",",
"src",
",",
"m",
")",
":",
"for",
"k",
"in",
"self",
".",
"containers",
":",
"self",
".",
"__dict__",
"[",
"k",
"]",
"[",
"n",
"]",
"=",
"src",
".",
"__dict__",
"[",
"k",
"]",
"[",
"m",
"]"
] | Copy to at a given location.
Parameters
----------
n: int
index where to copy
src: `ThetaParticles` object
source
m: int
index of the element to be copied
Note
----
Basically, does self[n] <- src[m] | [
"Copy",
"to",
"at",
"a",
"given",
"location",
"."
] | 3faa97a1073db45c5889eef3e015dd76ef350b52 | https://github.com/nchopin/particles/blob/3faa97a1073db45c5889eef3e015dd76ef350b52/particles/smc_samplers.py#L272-L289 | train |
nchopin/particles | particles/smc_samplers.py | MetroParticles.Metropolis | def Metropolis(self, compute_target, mh_options):
"""Performs a certain number of Metropolis steps.
Parameters
----------
compute_target: function
computes the target density for the proposed values
mh_options: dict
+ 'type_prop': {'random_walk', 'inde... | python | def Metropolis(self, compute_target, mh_options):
"""Performs a certain number of Metropolis steps.
Parameters
----------
compute_target: function
computes the target density for the proposed values
mh_options: dict
+ 'type_prop': {'random_walk', 'inde... | [
"def",
"Metropolis",
"(",
"self",
",",
"compute_target",
",",
"mh_options",
")",
":",
"opts",
"=",
"mh_options",
".",
"copy",
"(",
")",
"nsteps",
"=",
"opts",
".",
"pop",
"(",
"'nsteps'",
",",
"0",
")",
"delta_dist",
"=",
"opts",
".",
"pop",
"(",
"'d... | Performs a certain number of Metropolis steps.
Parameters
----------
compute_target: function
computes the target density for the proposed values
mh_options: dict
+ 'type_prop': {'random_walk', 'independent'}
type of proposal: either Gaussian ran... | [
"Performs",
"a",
"certain",
"number",
"of",
"Metropolis",
"steps",
"."
] | 3faa97a1073db45c5889eef3e015dd76ef350b52 | https://github.com/nchopin/particles/blob/3faa97a1073db45c5889eef3e015dd76ef350b52/particles/smc_samplers.py#L375-L418 | train |
nchopin/particles | particles/hmm.py | BaumWelch.backward | def backward(self):
"""Backward recursion.
Upon completion, the following list of length T is available:
* smth: marginal smoothing probabilities
Note
----
Performs the forward step in case it has not been performed before.
"""
if not self.filt:
... | python | def backward(self):
"""Backward recursion.
Upon completion, the following list of length T is available:
* smth: marginal smoothing probabilities
Note
----
Performs the forward step in case it has not been performed before.
"""
if not self.filt:
... | [
"def",
"backward",
"(",
"self",
")",
":",
"if",
"not",
"self",
".",
"filt",
":",
"self",
".",
"forward",
"(",
")",
"self",
".",
"smth",
"=",
"[",
"self",
".",
"filt",
"[",
"-",
"1",
"]",
"]",
"log_trans",
"=",
"np",
".",
"log",
"(",
"self",
"... | Backward recursion.
Upon completion, the following list of length T is available:
* smth: marginal smoothing probabilities
Note
----
Performs the forward step in case it has not been performed before. | [
"Backward",
"recursion",
"."
] | 3faa97a1073db45c5889eef3e015dd76ef350b52 | https://github.com/nchopin/particles/blob/3faa97a1073db45c5889eef3e015dd76ef350b52/particles/hmm.py#L215-L238 | train |
nchopin/particles | particles/kalman.py | predict_step | def predict_step(F, covX, filt):
"""Predictive step of Kalman filter.
Parameters
----------
F: (dx, dx) numpy array
Mean of X_t | X_{t-1} is F * X_{t-1}
covX: (dx, dx) numpy array
covariance of X_t | X_{t-1}
filt: MeanAndCov object
filtering distribution at time t-1
... | python | def predict_step(F, covX, filt):
"""Predictive step of Kalman filter.
Parameters
----------
F: (dx, dx) numpy array
Mean of X_t | X_{t-1} is F * X_{t-1}
covX: (dx, dx) numpy array
covariance of X_t | X_{t-1}
filt: MeanAndCov object
filtering distribution at time t-1
... | [
"def",
"predict_step",
"(",
"F",
",",
"covX",
",",
"filt",
")",
":",
"pred_mean",
"=",
"np",
".",
"matmul",
"(",
"filt",
".",
"mean",
",",
"F",
".",
"T",
")",
"pred_cov",
"=",
"dotdot",
"(",
"F",
",",
"filt",
".",
"cov",
",",
"F",
".",
"T",
"... | Predictive step of Kalman filter.
Parameters
----------
F: (dx, dx) numpy array
Mean of X_t | X_{t-1} is F * X_{t-1}
covX: (dx, dx) numpy array
covariance of X_t | X_{t-1}
filt: MeanAndCov object
filtering distribution at time t-1
Returns
-------
pred: MeanAn... | [
"Predictive",
"step",
"of",
"Kalman",
"filter",
"."
] | 3faa97a1073db45c5889eef3e015dd76ef350b52 | https://github.com/nchopin/particles/blob/3faa97a1073db45c5889eef3e015dd76ef350b52/particles/kalman.py#L163-L187 | train |
nchopin/particles | particles/kalman.py | filter_step | def filter_step(G, covY, pred, yt):
"""Filtering step of Kalman filter.
Parameters
----------
G: (dy, dx) numpy array
mean of Y_t | X_t is G * X_t
covX: (dx, dx) numpy array
covariance of Y_t | X_t
pred: MeanAndCov object
predictive distribution at time t
Returns
... | python | def filter_step(G, covY, pred, yt):
"""Filtering step of Kalman filter.
Parameters
----------
G: (dy, dx) numpy array
mean of Y_t | X_t is G * X_t
covX: (dx, dx) numpy array
covariance of Y_t | X_t
pred: MeanAndCov object
predictive distribution at time t
Returns
... | [
"def",
"filter_step",
"(",
"G",
",",
"covY",
",",
"pred",
",",
"yt",
")",
":",
"data_pred_mean",
"=",
"np",
".",
"matmul",
"(",
"pred",
".",
"mean",
",",
"G",
".",
"T",
")",
"data_pred_cov",
"=",
"dotdot",
"(",
"G",
",",
"pred",
".",
"cov",
",",
... | Filtering step of Kalman filter.
Parameters
----------
G: (dy, dx) numpy array
mean of Y_t | X_t is G * X_t
covX: (dx, dx) numpy array
covariance of Y_t | X_t
pred: MeanAndCov object
predictive distribution at time t
Returns
-------
pred: MeanAndCov object
... | [
"Filtering",
"step",
"of",
"Kalman",
"filter",
"."
] | 3faa97a1073db45c5889eef3e015dd76ef350b52 | https://github.com/nchopin/particles/blob/3faa97a1073db45c5889eef3e015dd76ef350b52/particles/kalman.py#L190-L223 | train |
nchopin/particles | particles/kalman.py | MVLinearGauss.check_shapes | def check_shapes(self):
"""
Check all dimensions are correct.
"""
assert self.covX.shape == (self.dx, self.dx), error_msg
assert self.covY.shape == (self.dy, self.dy), error_msg
assert self.F.shape == (self.dx, self.dx), error_msg
assert self.G.shape == (self.dy, ... | python | def check_shapes(self):
"""
Check all dimensions are correct.
"""
assert self.covX.shape == (self.dx, self.dx), error_msg
assert self.covY.shape == (self.dy, self.dy), error_msg
assert self.F.shape == (self.dx, self.dx), error_msg
assert self.G.shape == (self.dy, ... | [
"def",
"check_shapes",
"(",
"self",
")",
":",
"assert",
"self",
".",
"covX",
".",
"shape",
"==",
"(",
"self",
".",
"dx",
",",
"self",
".",
"dx",
")",
",",
"error_msg",
"assert",
"self",
".",
"covY",
".",
"shape",
"==",
"(",
"self",
".",
"dy",
","... | Check all dimensions are correct. | [
"Check",
"all",
"dimensions",
"are",
"correct",
"."
] | 3faa97a1073db45c5889eef3e015dd76ef350b52 | https://github.com/nchopin/particles/blob/3faa97a1073db45c5889eef3e015dd76ef350b52/particles/kalman.py#L326-L335 | train |
nchopin/particles | particles/qmc.py | sobol | def sobol(N, dim, scrambled=1):
""" Sobol sequence.
Parameters
----------
N : int
length of sequence
dim: int
dimension
scrambled: int
which scrambling method to use:
+ 0: no scrambling
+ 1: Owen's scrambling
+ 2: Faure-Tezuka
... | python | def sobol(N, dim, scrambled=1):
""" Sobol sequence.
Parameters
----------
N : int
length of sequence
dim: int
dimension
scrambled: int
which scrambling method to use:
+ 0: no scrambling
+ 1: Owen's scrambling
+ 2: Faure-Tezuka
... | [
"def",
"sobol",
"(",
"N",
",",
"dim",
",",
"scrambled",
"=",
"1",
")",
":",
"while",
"(",
"True",
")",
":",
"seed",
"=",
"np",
".",
"random",
".",
"randint",
"(",
"2",
"**",
"32",
")",
"out",
"=",
"lowdiscrepancy",
".",
"sobol",
"(",
"N",
",",
... | Sobol sequence.
Parameters
----------
N : int
length of sequence
dim: int
dimension
scrambled: int
which scrambling method to use:
+ 0: no scrambling
+ 1: Owen's scrambling
+ 2: Faure-Tezuka
+ 3: Owen + Faure-Tezuka
Ret... | [
"Sobol",
"sequence",
"."
] | 3faa97a1073db45c5889eef3e015dd76ef350b52 | https://github.com/nchopin/particles/blob/3faa97a1073db45c5889eef3e015dd76ef350b52/particles/qmc.py#L29-L64 | train |
nchopin/particles | particles/smoothing.py | smoothing_worker | def smoothing_worker(method=None, N=100, seed=None, fk=None, fk_info=None,
add_func=None, log_gamma=None):
"""Generic worker for off-line smoothing algorithms.
This worker may be used in conjunction with utils.multiplexer in order to
run in parallel (and eventually compare) off-line s... | python | def smoothing_worker(method=None, N=100, seed=None, fk=None, fk_info=None,
add_func=None, log_gamma=None):
"""Generic worker for off-line smoothing algorithms.
This worker may be used in conjunction with utils.multiplexer in order to
run in parallel (and eventually compare) off-line s... | [
"def",
"smoothing_worker",
"(",
"method",
"=",
"None",
",",
"N",
"=",
"100",
",",
"seed",
"=",
"None",
",",
"fk",
"=",
"None",
",",
"fk_info",
"=",
"None",
",",
"add_func",
"=",
"None",
",",
"log_gamma",
"=",
"None",
")",
":",
"T",
"=",
"fk",
"."... | Generic worker for off-line smoothing algorithms.
This worker may be used in conjunction with utils.multiplexer in order to
run in parallel (and eventually compare) off-line smoothing algorithms.
Parameters
----------
method: string
['FFBS_ON', 'FFBS_ON2', 'FFBS_QMC',
'tw... | [
"Generic",
"worker",
"for",
"off",
"-",
"line",
"smoothing",
"algorithms",
"."
] | 3faa97a1073db45c5889eef3e015dd76ef350b52 | https://github.com/nchopin/particles/blob/3faa97a1073db45c5889eef3e015dd76ef350b52/particles/smoothing.py#L367-L444 | train |
nchopin/particles | particles/smoothing.py | ParticleHistory.save | def save(self, X=None, w=None, A=None):
"""Save one "page" of history at a given time.
.. note::
This method is used internally by `SMC` to store the state of the
particle system at each time t. In most cases, users should not
have to call this method directly.
... | python | def save(self, X=None, w=None, A=None):
"""Save one "page" of history at a given time.
.. note::
This method is used internally by `SMC` to store the state of the
particle system at each time t. In most cases, users should not
have to call this method directly.
... | [
"def",
"save",
"(",
"self",
",",
"X",
"=",
"None",
",",
"w",
"=",
"None",
",",
"A",
"=",
"None",
")",
":",
"self",
".",
"X",
".",
"append",
"(",
"X",
")",
"self",
".",
"wgt",
".",
"append",
"(",
"w",
")",
"self",
".",
"A",
".",
"append",
... | Save one "page" of history at a given time.
.. note::
This method is used internally by `SMC` to store the state of the
particle system at each time t. In most cases, users should not
have to call this method directly. | [
"Save",
"one",
"page",
"of",
"history",
"at",
"a",
"given",
"time",
"."
] | 3faa97a1073db45c5889eef3e015dd76ef350b52 | https://github.com/nchopin/particles/blob/3faa97a1073db45c5889eef3e015dd76ef350b52/particles/smoothing.py#L92-L102 | train |
nchopin/particles | particles/smoothing.py | ParticleHistory.extract_one_trajectory | def extract_one_trajectory(self):
"""Extract a single trajectory from the particle history.
The final state is chosen randomly, then the corresponding trajectory
is constructed backwards, until time t=0.
"""
traj = []
for t in reversed(range(self.T)):
if t ... | python | def extract_one_trajectory(self):
"""Extract a single trajectory from the particle history.
The final state is chosen randomly, then the corresponding trajectory
is constructed backwards, until time t=0.
"""
traj = []
for t in reversed(range(self.T)):
if t ... | [
"def",
"extract_one_trajectory",
"(",
"self",
")",
":",
"traj",
"=",
"[",
"]",
"for",
"t",
"in",
"reversed",
"(",
"range",
"(",
"self",
".",
"T",
")",
")",
":",
"if",
"t",
"==",
"self",
".",
"T",
"-",
"1",
":",
"n",
"=",
"rs",
".",
"multinomial... | Extract a single trajectory from the particle history.
The final state is chosen randomly, then the corresponding trajectory
is constructed backwards, until time t=0. | [
"Extract",
"a",
"single",
"trajectory",
"from",
"the",
"particle",
"history",
"."
] | 3faa97a1073db45c5889eef3e015dd76ef350b52 | https://github.com/nchopin/particles/blob/3faa97a1073db45c5889eef3e015dd76ef350b52/particles/smoothing.py#L104-L117 | train |
nchopin/particles | particles/smoothing.py | ParticleHistory.compute_trajectories | def compute_trajectories(self):
"""Compute the N trajectories that constitute the current genealogy.
Compute and add attribute ``B`` to ``self`` where ``B`` is an array
such that ``B[t,n]`` is the index of ancestor at time t of particle X_T^n,
where T is the current length of history.
... | python | def compute_trajectories(self):
"""Compute the N trajectories that constitute the current genealogy.
Compute and add attribute ``B`` to ``self`` where ``B`` is an array
such that ``B[t,n]`` is the index of ancestor at time t of particle X_T^n,
where T is the current length of history.
... | [
"def",
"compute_trajectories",
"(",
"self",
")",
":",
"self",
".",
"B",
"=",
"np",
".",
"empty",
"(",
"(",
"self",
".",
"T",
",",
"self",
".",
"N",
")",
",",
"'int'",
")",
"self",
".",
"B",
"[",
"-",
"1",
",",
":",
"]",
"=",
"self",
".",
"A... | Compute the N trajectories that constitute the current genealogy.
Compute and add attribute ``B`` to ``self`` where ``B`` is an array
such that ``B[t,n]`` is the index of ancestor at time t of particle X_T^n,
where T is the current length of history. | [
"Compute",
"the",
"N",
"trajectories",
"that",
"constitute",
"the",
"current",
"genealogy",
"."
] | 3faa97a1073db45c5889eef3e015dd76ef350b52 | https://github.com/nchopin/particles/blob/3faa97a1073db45c5889eef3e015dd76ef350b52/particles/smoothing.py#L119-L129 | train |
nchopin/particles | particles/smoothing.py | ParticleHistory.twofilter_smoothing | def twofilter_smoothing(self, t, info, phi, loggamma, linear_cost=False,
return_ess=False, modif_forward=None,
modif_info=None):
"""Two-filter smoothing.
Parameters
----------
t: time, in range 0 <= t < T-1
info: SMC object... | python | def twofilter_smoothing(self, t, info, phi, loggamma, linear_cost=False,
return_ess=False, modif_forward=None,
modif_info=None):
"""Two-filter smoothing.
Parameters
----------
t: time, in range 0 <= t < T-1
info: SMC object... | [
"def",
"twofilter_smoothing",
"(",
"self",
",",
"t",
",",
"info",
",",
"phi",
",",
"loggamma",
",",
"linear_cost",
"=",
"False",
",",
"return_ess",
"=",
"False",
",",
"modif_forward",
"=",
"None",
",",
"modif_info",
"=",
"None",
")",
":",
"ti",
"=",
"s... | Two-filter smoothing.
Parameters
----------
t: time, in range 0 <= t < T-1
info: SMC object
the information filter
phi: function
test function, a function of (X_t,X_{t+1})
loggamma: function
a function of (X_{t+1})
linear_cost... | [
"Two",
"-",
"filter",
"smoothing",
"."
] | 3faa97a1073db45c5889eef3e015dd76ef350b52 | https://github.com/nchopin/particles/blob/3faa97a1073db45c5889eef3e015dd76ef350b52/particles/smoothing.py#L286-L317 | train |
nchopin/particles | particles/core.py | multiSMC | def multiSMC(nruns=10, nprocs=0, out_func=None, **args):
"""Run SMC algorithms in parallel, for different combinations of parameters.
`multiSMC` relies on the `multiplexer` utility, and obeys the same logic.
A basic usage is::
results = multiSMC(fk=my_fk_model, N=100, nruns=20, nprocs=0)
T... | python | def multiSMC(nruns=10, nprocs=0, out_func=None, **args):
"""Run SMC algorithms in parallel, for different combinations of parameters.
`multiSMC` relies on the `multiplexer` utility, and obeys the same logic.
A basic usage is::
results = multiSMC(fk=my_fk_model, N=100, nruns=20, nprocs=0)
T... | [
"def",
"multiSMC",
"(",
"nruns",
"=",
"10",
",",
"nprocs",
"=",
"0",
",",
"out_func",
"=",
"None",
",",
"**",
"args",
")",
":",
"def",
"f",
"(",
"**",
"args",
")",
":",
"pf",
"=",
"SMC",
"(",
"**",
"args",
")",
"pf",
".",
"run",
"(",
")",
"... | Run SMC algorithms in parallel, for different combinations of parameters.
`multiSMC` relies on the `multiplexer` utility, and obeys the same logic.
A basic usage is::
results = multiSMC(fk=my_fk_model, N=100, nruns=20, nprocs=0)
This runs the same SMC algorithm 20 times, using all available CP... | [
"Run",
"SMC",
"algorithms",
"in",
"parallel",
"for",
"different",
"combinations",
"of",
"parameters",
"."
] | 3faa97a1073db45c5889eef3e015dd76ef350b52 | https://github.com/nchopin/particles/blob/3faa97a1073db45c5889eef3e015dd76ef350b52/particles/core.py#L438-L512 | train |
nchopin/particles | particles/core.py | SMC.reset_weights | def reset_weights(self):
"""Reset weights after a resampling step.
"""
if self.fk.isAPF:
lw = (rs.log_mean_exp(self.logetat, W=self.W)
- self.logetat[self.A])
self.wgts = rs.Weights(lw=lw)
else:
self.wgts = rs.Weights() | python | def reset_weights(self):
"""Reset weights after a resampling step.
"""
if self.fk.isAPF:
lw = (rs.log_mean_exp(self.logetat, W=self.W)
- self.logetat[self.A])
self.wgts = rs.Weights(lw=lw)
else:
self.wgts = rs.Weights() | [
"def",
"reset_weights",
"(",
"self",
")",
":",
"if",
"self",
".",
"fk",
".",
"isAPF",
":",
"lw",
"=",
"(",
"rs",
".",
"log_mean_exp",
"(",
"self",
".",
"logetat",
",",
"W",
"=",
"self",
".",
"W",
")",
"-",
"self",
".",
"logetat",
"[",
"self",
"... | Reset weights after a resampling step. | [
"Reset",
"weights",
"after",
"a",
"resampling",
"step",
"."
] | 3faa97a1073db45c5889eef3e015dd76ef350b52 | https://github.com/nchopin/particles/blob/3faa97a1073db45c5889eef3e015dd76ef350b52/particles/core.py#L317-L325 | train |
nchopin/particles | particles/resampling.py | log_sum_exp | def log_sum_exp(v):
"""Log of the sum of the exp of the arguments.
Parameters
----------
v: ndarray
Returns
-------
l: float
l = log(sum(exp(v)))
Note
----
use the log_sum_exp trick to avoid overflow: i.e. we remove the max of v
before exponentiating, then we add... | python | def log_sum_exp(v):
"""Log of the sum of the exp of the arguments.
Parameters
----------
v: ndarray
Returns
-------
l: float
l = log(sum(exp(v)))
Note
----
use the log_sum_exp trick to avoid overflow: i.e. we remove the max of v
before exponentiating, then we add... | [
"def",
"log_sum_exp",
"(",
"v",
")",
":",
"m",
"=",
"v",
".",
"max",
"(",
")",
"return",
"m",
"+",
"np",
".",
"log",
"(",
"np",
".",
"sum",
"(",
"np",
".",
"exp",
"(",
"v",
"-",
"m",
")",
")",
")"
] | Log of the sum of the exp of the arguments.
Parameters
----------
v: ndarray
Returns
-------
l: float
l = log(sum(exp(v)))
Note
----
use the log_sum_exp trick to avoid overflow: i.e. we remove the max of v
before exponentiating, then we add it back
See also
... | [
"Log",
"of",
"the",
"sum",
"of",
"the",
"exp",
"of",
"the",
"arguments",
"."
] | 3faa97a1073db45c5889eef3e015dd76ef350b52 | https://github.com/nchopin/particles/blob/3faa97a1073db45c5889eef3e015dd76ef350b52/particles/resampling.py#L233-L256 | train |
nchopin/particles | particles/resampling.py | log_sum_exp_ab | def log_sum_exp_ab(a, b):
"""log_sum_exp for two scalars.
Parameters
----------
a, b: float
Returns
-------
c: float
c = log(e^a + e^b)
"""
if a > b:
return a + np.log(1. + np.exp(b - a))
else:
return b + np.log(1. + np.exp(a - b)) | python | def log_sum_exp_ab(a, b):
"""log_sum_exp for two scalars.
Parameters
----------
a, b: float
Returns
-------
c: float
c = log(e^a + e^b)
"""
if a > b:
return a + np.log(1. + np.exp(b - a))
else:
return b + np.log(1. + np.exp(a - b)) | [
"def",
"log_sum_exp_ab",
"(",
"a",
",",
"b",
")",
":",
"if",
"a",
">",
"b",
":",
"return",
"a",
"+",
"np",
".",
"log",
"(",
"1.",
"+",
"np",
".",
"exp",
"(",
"b",
"-",
"a",
")",
")",
"else",
":",
"return",
"b",
"+",
"np",
".",
"log",
"(",... | log_sum_exp for two scalars.
Parameters
----------
a, b: float
Returns
-------
c: float
c = log(e^a + e^b) | [
"log_sum_exp",
"for",
"two",
"scalars",
"."
] | 3faa97a1073db45c5889eef3e015dd76ef350b52 | https://github.com/nchopin/particles/blob/3faa97a1073db45c5889eef3e015dd76ef350b52/particles/resampling.py#L259-L274 | train |
nchopin/particles | particles/resampling.py | wmean_and_var | def wmean_and_var(W, x):
"""Component-wise weighted mean and variance.
Parameters
----------
W: (N,) ndarray
normalised weights (must be >=0 and sum to one).
x: ndarray (such that shape[0]==N)
data
Returns
-------
dictionary
{'mean':weighted_means, 'var':weig... | python | def wmean_and_var(W, x):
"""Component-wise weighted mean and variance.
Parameters
----------
W: (N,) ndarray
normalised weights (must be >=0 and sum to one).
x: ndarray (such that shape[0]==N)
data
Returns
-------
dictionary
{'mean':weighted_means, 'var':weig... | [
"def",
"wmean_and_var",
"(",
"W",
",",
"x",
")",
":",
"m",
"=",
"np",
".",
"average",
"(",
"x",
",",
"weights",
"=",
"W",
",",
"axis",
"=",
"0",
")",
"m2",
"=",
"np",
".",
"average",
"(",
"x",
"**",
"2",
",",
"weights",
"=",
"W",
",",
"axis... | Component-wise weighted mean and variance.
Parameters
----------
W: (N,) ndarray
normalised weights (must be >=0 and sum to one).
x: ndarray (such that shape[0]==N)
data
Returns
-------
dictionary
{'mean':weighted_means, 'var':weighted_variances} | [
"Component",
"-",
"wise",
"weighted",
"mean",
"and",
"variance",
"."
] | 3faa97a1073db45c5889eef3e015dd76ef350b52 | https://github.com/nchopin/particles/blob/3faa97a1073db45c5889eef3e015dd76ef350b52/particles/resampling.py#L306-L324 | train |
nchopin/particles | particles/resampling.py | wmean_and_var_str_array | def wmean_and_var_str_array(W, x):
"""Weighted mean and variance of each component of a structured array.
Parameters
----------
W: (N,) ndarray
normalised weights (must be >=0 and sum to one).
x: (N,) structured array
data
Returns
-------
dictionary
{'mean':... | python | def wmean_and_var_str_array(W, x):
"""Weighted mean and variance of each component of a structured array.
Parameters
----------
W: (N,) ndarray
normalised weights (must be >=0 and sum to one).
x: (N,) structured array
data
Returns
-------
dictionary
{'mean':... | [
"def",
"wmean_and_var_str_array",
"(",
"W",
",",
"x",
")",
":",
"m",
"=",
"np",
".",
"empty",
"(",
"shape",
"=",
"x",
".",
"shape",
"[",
"1",
":",
"]",
",",
"dtype",
"=",
"x",
".",
"dtype",
")",
"v",
"=",
"np",
".",
"empty_like",
"(",
"m",
")... | Weighted mean and variance of each component of a structured array.
Parameters
----------
W: (N,) ndarray
normalised weights (must be >=0 and sum to one).
x: (N,) structured array
data
Returns
-------
dictionary
{'mean':weighted_means, 'var':weighted_variances} | [
"Weighted",
"mean",
"and",
"variance",
"of",
"each",
"component",
"of",
"a",
"structured",
"array",
"."
] | 3faa97a1073db45c5889eef3e015dd76ef350b52 | https://github.com/nchopin/particles/blob/3faa97a1073db45c5889eef3e015dd76ef350b52/particles/resampling.py#L326-L345 | train |
nchopin/particles | particles/resampling.py | wquantiles | def wquantiles(W, x, alphas=(0.25, 0.50, 0.75)):
"""Quantiles for weighted data.
Parameters
----------
W: (N,) ndarray
normalised weights (weights are >=0 and sum to one)
x: (N,) or (N,d) ndarray
data
alphas: list-like of size k (default: (0.25, 0.50, 0.75))
probabilitie... | python | def wquantiles(W, x, alphas=(0.25, 0.50, 0.75)):
"""Quantiles for weighted data.
Parameters
----------
W: (N,) ndarray
normalised weights (weights are >=0 and sum to one)
x: (N,) or (N,d) ndarray
data
alphas: list-like of size k (default: (0.25, 0.50, 0.75))
probabilitie... | [
"def",
"wquantiles",
"(",
"W",
",",
"x",
",",
"alphas",
"=",
"(",
"0.25",
",",
"0.50",
",",
"0.75",
")",
")",
":",
"if",
"len",
"(",
"x",
".",
"shape",
")",
"==",
"1",
":",
"return",
"_wquantiles",
"(",
"W",
",",
"x",
",",
"alphas",
"=",
"alp... | Quantiles for weighted data.
Parameters
----------
W: (N,) ndarray
normalised weights (weights are >=0 and sum to one)
x: (N,) or (N,d) ndarray
data
alphas: list-like of size k (default: (0.25, 0.50, 0.75))
probabilities (between 0. and 1.)
Returns
-------
a (k... | [
"Quantiles",
"for",
"weighted",
"data",
"."
] | 3faa97a1073db45c5889eef3e015dd76ef350b52 | https://github.com/nchopin/particles/blob/3faa97a1073db45c5889eef3e015dd76ef350b52/particles/resampling.py#L359-L379 | train |
nchopin/particles | particles/resampling.py | wquantiles_str_array | def wquantiles_str_array(W, x, alphas=(0.25, 0.50, 0,75)):
"""quantiles for weighted data stored in a structured array.
Parameters
----------
W: (N,) ndarray
normalised weights (weights are >=0 and sum to one)
x: (N,) structured array
data
alphas: list-like of size k (default: ... | python | def wquantiles_str_array(W, x, alphas=(0.25, 0.50, 0,75)):
"""quantiles for weighted data stored in a structured array.
Parameters
----------
W: (N,) ndarray
normalised weights (weights are >=0 and sum to one)
x: (N,) structured array
data
alphas: list-like of size k (default: ... | [
"def",
"wquantiles_str_array",
"(",
"W",
",",
"x",
",",
"alphas",
"=",
"(",
"0.25",
",",
"0.50",
",",
"0",
",",
"75",
")",
")",
":",
"return",
"{",
"p",
":",
"wquantiles",
"(",
"W",
",",
"x",
"[",
"p",
"]",
",",
"alphas",
")",
"for",
"p",
"in... | quantiles for weighted data stored in a structured array.
Parameters
----------
W: (N,) ndarray
normalised weights (weights are >=0 and sum to one)
x: (N,) structured array
data
alphas: list-like of size k (default: (0.25, 0.50, 0.75))
probabilities (between 0. and 1.)
... | [
"quantiles",
"for",
"weighted",
"data",
"stored",
"in",
"a",
"structured",
"array",
"."
] | 3faa97a1073db45c5889eef3e015dd76ef350b52 | https://github.com/nchopin/particles/blob/3faa97a1073db45c5889eef3e015dd76ef350b52/particles/resampling.py#L381-L399 | train |
nchopin/particles | particles/resampling.py | resampling_scheme | def resampling_scheme(func):
"""Decorator for resampling schemes."""
@functools.wraps(func)
def modif_func(W, M=None):
M = W.shape[0] if M is None else M
return func(W, M)
rs_funcs[func.__name__] = modif_func
modif_func.__doc__ = rs_doc % func.__name__.capitalize()
return modif... | python | def resampling_scheme(func):
"""Decorator for resampling schemes."""
@functools.wraps(func)
def modif_func(W, M=None):
M = W.shape[0] if M is None else M
return func(W, M)
rs_funcs[func.__name__] = modif_func
modif_func.__doc__ = rs_doc % func.__name__.capitalize()
return modif... | [
"def",
"resampling_scheme",
"(",
"func",
")",
":",
"@",
"functools",
".",
"wraps",
"(",
"func",
")",
"def",
"modif_func",
"(",
"W",
",",
"M",
"=",
"None",
")",
":",
"M",
"=",
"W",
".",
"shape",
"[",
"0",
"]",
"if",
"M",
"is",
"None",
"else",
"M... | Decorator for resampling schemes. | [
"Decorator",
"for",
"resampling",
"schemes",
"."
] | 3faa97a1073db45c5889eef3e015dd76ef350b52 | https://github.com/nchopin/particles/blob/3faa97a1073db45c5889eef3e015dd76ef350b52/particles/resampling.py#L423-L433 | train |
nchopin/particles | particles/resampling.py | inverse_cdf | def inverse_cdf(su, W):
"""Inverse CDF algorithm for a finite distribution.
Parameters
----------
su: (M,) ndarray
M sorted uniform variates (i.e. M ordered points in [0,1]).
W: (N,) ndarray
a vector of N normalized weights (>=0 and sum to one)
Re... | python | def inverse_cdf(su, W):
"""Inverse CDF algorithm for a finite distribution.
Parameters
----------
su: (M,) ndarray
M sorted uniform variates (i.e. M ordered points in [0,1]).
W: (N,) ndarray
a vector of N normalized weights (>=0 and sum to one)
Re... | [
"def",
"inverse_cdf",
"(",
"su",
",",
"W",
")",
":",
"j",
"=",
"0",
"s",
"=",
"W",
"[",
"0",
"]",
"M",
"=",
"su",
".",
"shape",
"[",
"0",
"]",
"A",
"=",
"np",
".",
"empty",
"(",
"M",
",",
"'int'",
")",
"for",
"n",
"in",
"range",
"(",
"M... | Inverse CDF algorithm for a finite distribution.
Parameters
----------
su: (M,) ndarray
M sorted uniform variates (i.e. M ordered points in [0,1]).
W: (N,) ndarray
a vector of N normalized weights (>=0 and sum to one)
Returns
-------
... | [
"Inverse",
"CDF",
"algorithm",
"for",
"a",
"finite",
"distribution",
"."
] | 3faa97a1073db45c5889eef3e015dd76ef350b52 | https://github.com/nchopin/particles/blob/3faa97a1073db45c5889eef3e015dd76ef350b52/particles/resampling.py#L443-L467 | train |
nchopin/particles | particles/hilbert.py | hilbert_array | def hilbert_array(xint):
"""Compute Hilbert indices.
Parameters
----------
xint: (N, d) int numpy.ndarray
Returns
-------
h: (N,) int numpy.ndarray
Hilbert indices
"""
N, d = xint.shape
h = np.zeros(N, int64)
for n in range(N):
h[n] = Hilbert_to_int(xint[n... | python | def hilbert_array(xint):
"""Compute Hilbert indices.
Parameters
----------
xint: (N, d) int numpy.ndarray
Returns
-------
h: (N,) int numpy.ndarray
Hilbert indices
"""
N, d = xint.shape
h = np.zeros(N, int64)
for n in range(N):
h[n] = Hilbert_to_int(xint[n... | [
"def",
"hilbert_array",
"(",
"xint",
")",
":",
"N",
",",
"d",
"=",
"xint",
".",
"shape",
"h",
"=",
"np",
".",
"zeros",
"(",
"N",
",",
"int64",
")",
"for",
"n",
"in",
"range",
"(",
"N",
")",
":",
"h",
"[",
"n",
"]",
"=",
"Hilbert_to_int",
"(",... | Compute Hilbert indices.
Parameters
----------
xint: (N, d) int numpy.ndarray
Returns
-------
h: (N,) int numpy.ndarray
Hilbert indices | [
"Compute",
"Hilbert",
"indices",
"."
] | 3faa97a1073db45c5889eef3e015dd76ef350b52 | https://github.com/nchopin/particles/blob/3faa97a1073db45c5889eef3e015dd76ef350b52/particles/hilbert.py#L17-L33 | train |
nchopin/particles | particles/mcmc.py | MCMC.mean_sq_jump_dist | def mean_sq_jump_dist(self, discard_frac=0.1):
"""Mean squared jumping distance estimated from chain.
Parameters
----------
discard_frac: float
fraction of iterations to discard at the beginning (as a burn-in)
Returns
-------
float
"""
... | python | def mean_sq_jump_dist(self, discard_frac=0.1):
"""Mean squared jumping distance estimated from chain.
Parameters
----------
discard_frac: float
fraction of iterations to discard at the beginning (as a burn-in)
Returns
-------
float
"""
... | [
"def",
"mean_sq_jump_dist",
"(",
"self",
",",
"discard_frac",
"=",
"0.1",
")",
":",
"discard",
"=",
"int",
"(",
"self",
".",
"niter",
"*",
"discard_frac",
")",
"return",
"msjd",
"(",
"self",
".",
"chain",
".",
"theta",
"[",
"discard",
":",
"]",
")"
] | Mean squared jumping distance estimated from chain.
Parameters
----------
discard_frac: float
fraction of iterations to discard at the beginning (as a burn-in)
Returns
-------
float | [
"Mean",
"squared",
"jumping",
"distance",
"estimated",
"from",
"chain",
"."
] | 3faa97a1073db45c5889eef3e015dd76ef350b52 | https://github.com/nchopin/particles/blob/3faa97a1073db45c5889eef3e015dd76ef350b52/particles/mcmc.py#L99-L112 | train |
nchopin/particles | particles/mcmc.py | VanishCovTracker.update | def update(self, v):
"""Adds point v"""
self.t += 1
g = self.gamma()
self.mu = (1. - g) * self.mu + g * v
mv = v - self.mu
self.Sigma = ((1. - g) * self.Sigma
+ g * np.dot(mv[:, np.newaxis], mv[np.newaxis, :]))
try:
self.L = chole... | python | def update(self, v):
"""Adds point v"""
self.t += 1
g = self.gamma()
self.mu = (1. - g) * self.mu + g * v
mv = v - self.mu
self.Sigma = ((1. - g) * self.Sigma
+ g * np.dot(mv[:, np.newaxis], mv[np.newaxis, :]))
try:
self.L = chole... | [
"def",
"update",
"(",
"self",
",",
"v",
")",
":",
"self",
".",
"t",
"+=",
"1",
"g",
"=",
"self",
".",
"gamma",
"(",
")",
"self",
".",
"mu",
"=",
"(",
"1.",
"-",
"g",
")",
"*",
"self",
".",
"mu",
"+",
"g",
"*",
"v",
"mv",
"=",
"v",
"-",
... | Adds point v | [
"Adds",
"point",
"v"
] | 3faa97a1073db45c5889eef3e015dd76ef350b52 | https://github.com/nchopin/particles/blob/3faa97a1073db45c5889eef3e015dd76ef350b52/particles/mcmc.py#L161-L172 | train |
nchopin/particles | particles/utils.py | cartesian_lists | def cartesian_lists(d):
"""
turns a dict of lists into a list of dicts that represents
the cartesian product of the initial lists
Example
-------
cartesian_lists({'a':[0, 2], 'b':[3, 4, 5]}
returns
[ {'a':0, 'b':3}, {'a':0, 'b':4}, ... {'a':2, 'b':5} ]
"""
return [{k: v for k, ... | python | def cartesian_lists(d):
"""
turns a dict of lists into a list of dicts that represents
the cartesian product of the initial lists
Example
-------
cartesian_lists({'a':[0, 2], 'b':[3, 4, 5]}
returns
[ {'a':0, 'b':3}, {'a':0, 'b':4}, ... {'a':2, 'b':5} ]
"""
return [{k: v for k, ... | [
"def",
"cartesian_lists",
"(",
"d",
")",
":",
"return",
"[",
"{",
"k",
":",
"v",
"for",
"k",
",",
"v",
"in",
"zip",
"(",
"d",
".",
"keys",
"(",
")",
",",
"args",
")",
"}",
"for",
"args",
"in",
"itertools",
".",
"product",
"(",
"*",
"d",
".",
... | turns a dict of lists into a list of dicts that represents
the cartesian product of the initial lists
Example
-------
cartesian_lists({'a':[0, 2], 'b':[3, 4, 5]}
returns
[ {'a':0, 'b':3}, {'a':0, 'b':4}, ... {'a':2, 'b':5} ] | [
"turns",
"a",
"dict",
"of",
"lists",
"into",
"a",
"list",
"of",
"dicts",
"that",
"represents",
"the",
"cartesian",
"product",
"of",
"the",
"initial",
"lists"
] | 3faa97a1073db45c5889eef3e015dd76ef350b52 | https://github.com/nchopin/particles/blob/3faa97a1073db45c5889eef3e015dd76ef350b52/particles/utils.py#L87-L100 | train |
nchopin/particles | particles/utils.py | cartesian_args | def cartesian_args(args, listargs, dictargs):
""" Compute a list of inputs and outputs for a function
with kw arguments.
args: dict
fixed arguments, e.g. {'x': 3}, then x=3 for all inputs
listargs: dict
arguments specified as a list; then the inputs
should be the Cartesian product... | python | def cartesian_args(args, listargs, dictargs):
""" Compute a list of inputs and outputs for a function
with kw arguments.
args: dict
fixed arguments, e.g. {'x': 3}, then x=3 for all inputs
listargs: dict
arguments specified as a list; then the inputs
should be the Cartesian product... | [
"def",
"cartesian_args",
"(",
"args",
",",
"listargs",
",",
"dictargs",
")",
":",
"ils",
"=",
"{",
"k",
":",
"[",
"v",
",",
"]",
"for",
"k",
",",
"v",
"in",
"args",
".",
"items",
"(",
")",
"}",
"ils",
".",
"update",
"(",
"listargs",
")",
"ils",... | Compute a list of inputs and outputs for a function
with kw arguments.
args: dict
fixed arguments, e.g. {'x': 3}, then x=3 for all inputs
listargs: dict
arguments specified as a list; then the inputs
should be the Cartesian products of these lists
dictargs: dict
same as ab... | [
"Compute",
"a",
"list",
"of",
"inputs",
"and",
"outputs",
"for",
"a",
"function",
"with",
"kw",
"arguments",
"."
] | 3faa97a1073db45c5889eef3e015dd76ef350b52 | https://github.com/nchopin/particles/blob/3faa97a1073db45c5889eef3e015dd76ef350b52/particles/utils.py#L103-L122 | train |
nchopin/particles | particles/utils.py | worker | def worker(qin, qout, f):
"""Worker for muliprocessing.
A worker repeatedly picks a dict of arguments in the queue and computes
f for this set of arguments, until the input queue is empty.
"""
while not qin.empty():
i, args = qin.get()
qout.put((i, f(**args))) | python | def worker(qin, qout, f):
"""Worker for muliprocessing.
A worker repeatedly picks a dict of arguments in the queue and computes
f for this set of arguments, until the input queue is empty.
"""
while not qin.empty():
i, args = qin.get()
qout.put((i, f(**args))) | [
"def",
"worker",
"(",
"qin",
",",
"qout",
",",
"f",
")",
":",
"while",
"not",
"qin",
".",
"empty",
"(",
")",
":",
"i",
",",
"args",
"=",
"qin",
".",
"get",
"(",
")",
"qout",
".",
"put",
"(",
"(",
"i",
",",
"f",
"(",
"**",
"args",
")",
")"... | Worker for muliprocessing.
A worker repeatedly picks a dict of arguments in the queue and computes
f for this set of arguments, until the input queue is empty. | [
"Worker",
"for",
"muliprocessing",
".",
"A",
"worker",
"repeatedly",
"picks",
"a",
"dict",
"of",
"arguments",
"in",
"the",
"queue",
"and",
"computes",
"f",
"for",
"this",
"set",
"of",
"arguments",
"until",
"the",
"input",
"queue",
"is",
"empty",
"."
] | 3faa97a1073db45c5889eef3e015dd76ef350b52 | https://github.com/nchopin/particles/blob/3faa97a1073db45c5889eef3e015dd76ef350b52/particles/utils.py#L133-L141 | train |
nchopin/particles | particles/utils.py | distinct_seeds | def distinct_seeds(k):
""" returns k distinct seeds for random number generation
"""
seeds = []
for _ in range(k):
while True:
s = random.randint(2**32 - 1)
if s not in seeds:
break
seeds.append(s)
return seeds | python | def distinct_seeds(k):
""" returns k distinct seeds for random number generation
"""
seeds = []
for _ in range(k):
while True:
s = random.randint(2**32 - 1)
if s not in seeds:
break
seeds.append(s)
return seeds | [
"def",
"distinct_seeds",
"(",
"k",
")",
":",
"seeds",
"=",
"[",
"]",
"for",
"_",
"in",
"range",
"(",
"k",
")",
":",
"while",
"True",
":",
"s",
"=",
"random",
".",
"randint",
"(",
"2",
"**",
"32",
"-",
"1",
")",
"if",
"s",
"not",
"in",
"seeds"... | returns k distinct seeds for random number generation | [
"returns",
"k",
"distinct",
"seeds",
"for",
"random",
"number",
"generation"
] | 3faa97a1073db45c5889eef3e015dd76ef350b52 | https://github.com/nchopin/particles/blob/3faa97a1073db45c5889eef3e015dd76ef350b52/particles/utils.py#L179-L189 | train |
nchopin/particles | particles/utils.py | multiplexer | def multiplexer(f=None, nruns=1, nprocs=1, seeding=None, **args):
"""Evaluate a function for different parameters, optionally in parallel.
Parameters
----------
f: function
function f to evaluate, must take only kw arguments as inputs
nruns: int
number of evaluations of f for each... | python | def multiplexer(f=None, nruns=1, nprocs=1, seeding=None, **args):
"""Evaluate a function for different parameters, optionally in parallel.
Parameters
----------
f: function
function f to evaluate, must take only kw arguments as inputs
nruns: int
number of evaluations of f for each... | [
"def",
"multiplexer",
"(",
"f",
"=",
"None",
",",
"nruns",
"=",
"1",
",",
"nprocs",
"=",
"1",
",",
"seeding",
"=",
"None",
",",
"**",
"args",
")",
":",
"if",
"not",
"callable",
"(",
"f",
")",
":",
"raise",
"ValueError",
"(",
"'multiplexer: function f... | Evaluate a function for different parameters, optionally in parallel.
Parameters
----------
f: function
function f to evaluate, must take only kw arguments as inputs
nruns: int
number of evaluations of f for each set of arguments
nprocs: int
+ if <=0, set to actual number ... | [
"Evaluate",
"a",
"function",
"for",
"different",
"parameters",
"optionally",
"in",
"parallel",
"."
] | 3faa97a1073db45c5889eef3e015dd76ef350b52 | https://github.com/nchopin/particles/blob/3faa97a1073db45c5889eef3e015dd76ef350b52/particles/utils.py#L192-L240 | train |
nchopin/particles | particles/state_space_models.py | StateSpaceModel.simulate | def simulate(self, T):
"""Simulate state and observation processes.
Parameters
----------
T: int
processes are simulated from time 0 to time T-1
Returns
-------
x, y: lists
lists of length T
"""
x = []
for t in ra... | python | def simulate(self, T):
"""Simulate state and observation processes.
Parameters
----------
T: int
processes are simulated from time 0 to time T-1
Returns
-------
x, y: lists
lists of length T
"""
x = []
for t in ra... | [
"def",
"simulate",
"(",
"self",
",",
"T",
")",
":",
"x",
"=",
"[",
"]",
"for",
"t",
"in",
"range",
"(",
"T",
")",
":",
"law_x",
"=",
"self",
".",
"PX0",
"(",
")",
"if",
"t",
"==",
"0",
"else",
"self",
".",
"PX",
"(",
"t",
",",
"x",
"[",
... | Simulate state and observation processes.
Parameters
----------
T: int
processes are simulated from time 0 to time T-1
Returns
-------
x, y: lists
lists of length T | [
"Simulate",
"state",
"and",
"observation",
"processes",
"."
] | 3faa97a1073db45c5889eef3e015dd76ef350b52 | https://github.com/nchopin/particles/blob/3faa97a1073db45c5889eef3e015dd76ef350b52/particles/state_space_models.py#L280-L298 | train |
nchopin/particles | book/mle/malikpitt_interpolation.py | interpoled_resampling | def interpoled_resampling(W, x):
"""Resampling based on an interpolated CDF, as described in Malik and Pitt.
Parameters
----------
W: (N,) array
weights
x: (N,) array
particles
Returns
-------
xrs: (N,) array
the resampled particles
"""
N = W.shape[... | python | def interpoled_resampling(W, x):
"""Resampling based on an interpolated CDF, as described in Malik and Pitt.
Parameters
----------
W: (N,) array
weights
x: (N,) array
particles
Returns
-------
xrs: (N,) array
the resampled particles
"""
N = W.shape[... | [
"def",
"interpoled_resampling",
"(",
"W",
",",
"x",
")",
":",
"N",
"=",
"W",
".",
"shape",
"[",
"0",
"]",
"idx",
"=",
"np",
".",
"argsort",
"(",
"x",
")",
"xs",
"=",
"x",
"[",
"idx",
"]",
"ws",
"=",
"W",
"[",
"idx",
"]",
"cs",
"=",
"np",
... | Resampling based on an interpolated CDF, as described in Malik and Pitt.
Parameters
----------
W: (N,) array
weights
x: (N,) array
particles
Returns
-------
xrs: (N,) array
the resampled particles | [
"Resampling",
"based",
"on",
"an",
"interpolated",
"CDF",
"as",
"described",
"in",
"Malik",
"and",
"Pitt",
"."
] | 3faa97a1073db45c5889eef3e015dd76ef350b52 | https://github.com/nchopin/particles/blob/3faa97a1073db45c5889eef3e015dd76ef350b52/book/mle/malikpitt_interpolation.py#L26-L59 | train |
Fortran-FOSS-Programmers/ford | ford/sourceform.py | sort_items | def sort_items(self,items,args=False):
"""
Sort the `self`'s contents, as contained in the list `items` as
specified in `self`'s meta-data.
"""
if self.settings['sort'].lower() == 'src': return
def alpha(i):
return i.name
def permission(i):
if args:
if i.intent ==... | python | def sort_items(self,items,args=False):
"""
Sort the `self`'s contents, as contained in the list `items` as
specified in `self`'s meta-data.
"""
if self.settings['sort'].lower() == 'src': return
def alpha(i):
return i.name
def permission(i):
if args:
if i.intent ==... | [
"def",
"sort_items",
"(",
"self",
",",
"items",
",",
"args",
"=",
"False",
")",
":",
"if",
"self",
".",
"settings",
"[",
"'sort'",
"]",
".",
"lower",
"(",
")",
"==",
"'src'",
":",
"return",
"def",
"alpha",
"(",
"i",
")",
":",
"return",
"i",
".",
... | Sort the `self`'s contents, as contained in the list `items` as
specified in `self`'s meta-data. | [
"Sort",
"the",
"self",
"s",
"contents",
"as",
"contained",
"in",
"the",
"list",
"items",
"as",
"specified",
"in",
"self",
"s",
"meta",
"-",
"data",
"."
] | d46a44eae20d99205292c31785f936fbed47070f | https://github.com/Fortran-FOSS-Programmers/ford/blob/d46a44eae20d99205292c31785f936fbed47070f/ford/sourceform.py#L2402-L2451 | train |
Fortran-FOSS-Programmers/ford | ford/sourceform.py | FortranBase.contents_size | def contents_size(self):
'''
Returns the number of different categories to be shown in the
contents side-bar in the HTML documentation.
'''
count = 0
if hasattr(self,'variables'): count += 1
if hasattr(self,'types'): count += 1
if hasattr(self,'modules'): ... | python | def contents_size(self):
'''
Returns the number of different categories to be shown in the
contents side-bar in the HTML documentation.
'''
count = 0
if hasattr(self,'variables'): count += 1
if hasattr(self,'types'): count += 1
if hasattr(self,'modules'): ... | [
"def",
"contents_size",
"(",
"self",
")",
":",
"count",
"=",
"0",
"if",
"hasattr",
"(",
"self",
",",
"'variables'",
")",
":",
"count",
"+=",
"1",
"if",
"hasattr",
"(",
"self",
",",
"'types'",
")",
":",
"count",
"+=",
"1",
"if",
"hasattr",
"(",
"sel... | Returns the number of different categories to be shown in the
contents side-bar in the HTML documentation. | [
"Returns",
"the",
"number",
"of",
"different",
"categories",
"to",
"be",
"shown",
"in",
"the",
"contents",
"side",
"-",
"bar",
"in",
"the",
"HTML",
"documentation",
"."
] | d46a44eae20d99205292c31785f936fbed47070f | https://github.com/Fortran-FOSS-Programmers/ford/blob/d46a44eae20d99205292c31785f936fbed47070f/ford/sourceform.py#L267-L292 | train |
Fortran-FOSS-Programmers/ford | ford/sourceform.py | FortranBase.sort | def sort(self):
'''
Sorts components of the object.
'''
if hasattr(self,'variables'):
sort_items(self,self.variables)
if hasattr(self,'modules'):
sort_items(self,self.modules)
if hasattr(self,'submodules'):
sort_items(self,self.submodul... | python | def sort(self):
'''
Sorts components of the object.
'''
if hasattr(self,'variables'):
sort_items(self,self.variables)
if hasattr(self,'modules'):
sort_items(self,self.modules)
if hasattr(self,'submodules'):
sort_items(self,self.submodul... | [
"def",
"sort",
"(",
"self",
")",
":",
"if",
"hasattr",
"(",
"self",
",",
"'variables'",
")",
":",
"sort_items",
"(",
"self",
",",
"self",
".",
"variables",
")",
"if",
"hasattr",
"(",
"self",
",",
"'modules'",
")",
":",
"sort_items",
"(",
"self",
",",... | Sorts components of the object. | [
"Sorts",
"components",
"of",
"the",
"object",
"."
] | d46a44eae20d99205292c31785f936fbed47070f | https://github.com/Fortran-FOSS-Programmers/ford/blob/d46a44eae20d99205292c31785f936fbed47070f/ford/sourceform.py#L417-L451 | train |
Fortran-FOSS-Programmers/ford | ford/sourceform.py | FortranBase.make_links | def make_links(self, project):
"""
Process intra-site links to documentation of other parts of the program.
"""
self.doc = ford.utils.sub_links(self.doc,project)
if 'summary' in self.meta:
self.meta['summary'] = ford.utils.sub_links(self.meta['summary'],project)
... | python | def make_links(self, project):
"""
Process intra-site links to documentation of other parts of the program.
"""
self.doc = ford.utils.sub_links(self.doc,project)
if 'summary' in self.meta:
self.meta['summary'] = ford.utils.sub_links(self.meta['summary'],project)
... | [
"def",
"make_links",
"(",
"self",
",",
"project",
")",
":",
"self",
".",
"doc",
"=",
"ford",
".",
"utils",
".",
"sub_links",
"(",
"self",
".",
"doc",
",",
"project",
")",
"if",
"'summary'",
"in",
"self",
".",
"meta",
":",
"self",
".",
"meta",
"[",
... | Process intra-site links to documentation of other parts of the program. | [
"Process",
"intra",
"-",
"site",
"links",
"to",
"documentation",
"of",
"other",
"parts",
"of",
"the",
"program",
"."
] | d46a44eae20d99205292c31785f936fbed47070f | https://github.com/Fortran-FOSS-Programmers/ford/blob/d46a44eae20d99205292c31785f936fbed47070f/ford/sourceform.py#L454-L475 | train |
Fortran-FOSS-Programmers/ford | ford/sourceform.py | FortranBase.iterator | def iterator(self, *argv):
""" Iterator returning any list of elements via attribute lookup in `self`
This iterator retains the order of the arguments """
for arg in argv:
if hasattr(self, arg):
for item in getattr(self, arg):
yield item | python | def iterator(self, *argv):
""" Iterator returning any list of elements via attribute lookup in `self`
This iterator retains the order of the arguments """
for arg in argv:
if hasattr(self, arg):
for item in getattr(self, arg):
yield item | [
"def",
"iterator",
"(",
"self",
",",
"*",
"argv",
")",
":",
"for",
"arg",
"in",
"argv",
":",
"if",
"hasattr",
"(",
"self",
",",
"arg",
")",
":",
"for",
"item",
"in",
"getattr",
"(",
"self",
",",
"arg",
")",
":",
"yield",
"item"
] | Iterator returning any list of elements via attribute lookup in `self`
This iterator retains the order of the arguments | [
"Iterator",
"returning",
"any",
"list",
"of",
"elements",
"via",
"attribute",
"lookup",
"in",
"self"
] | d46a44eae20d99205292c31785f936fbed47070f | https://github.com/Fortran-FOSS-Programmers/ford/blob/d46a44eae20d99205292c31785f936fbed47070f/ford/sourceform.py#L486-L493 | train |
Fortran-FOSS-Programmers/ford | ford/sourceform.py | FortranModule.get_used_entities | def get_used_entities(self,use_specs):
"""
Returns the entities which are imported by a use statement. These
are contained in dicts.
"""
if len(use_specs.strip()) == 0:
return (self.pub_procs, self.pub_absints, self.pub_types, self.pub_vars)
only = bool(self.O... | python | def get_used_entities(self,use_specs):
"""
Returns the entities which are imported by a use statement. These
are contained in dicts.
"""
if len(use_specs.strip()) == 0:
return (self.pub_procs, self.pub_absints, self.pub_types, self.pub_vars)
only = bool(self.O... | [
"def",
"get_used_entities",
"(",
"self",
",",
"use_specs",
")",
":",
"if",
"len",
"(",
"use_specs",
".",
"strip",
"(",
")",
")",
"==",
"0",
":",
"return",
"(",
"self",
".",
"pub_procs",
",",
"self",
".",
"pub_absints",
",",
"self",
".",
"pub_types",
... | Returns the entities which are imported by a use statement. These
are contained in dicts. | [
"Returns",
"the",
"entities",
"which",
"are",
"imported",
"by",
"a",
"use",
"statement",
".",
"These",
"are",
"contained",
"in",
"dicts",
"."
] | d46a44eae20d99205292c31785f936fbed47070f | https://github.com/Fortran-FOSS-Programmers/ford/blob/d46a44eae20d99205292c31785f936fbed47070f/ford/sourceform.py#L1138-L1188 | train |
Fortran-FOSS-Programmers/ford | ford/sourceform.py | NameSelector.get_name | def get_name(self,item):
"""
Return the name for this item registered with this NameSelector.
If no name has previously been registered, then generate a new
one.
"""
if not isinstance(item,ford.sourceform.FortranBase):
raise Exception('{} is not of a type deri... | python | def get_name(self,item):
"""
Return the name for this item registered with this NameSelector.
If no name has previously been registered, then generate a new
one.
"""
if not isinstance(item,ford.sourceform.FortranBase):
raise Exception('{} is not of a type deri... | [
"def",
"get_name",
"(",
"self",
",",
"item",
")",
":",
"if",
"not",
"isinstance",
"(",
"item",
",",
"ford",
".",
"sourceform",
".",
"FortranBase",
")",
":",
"raise",
"Exception",
"(",
"'{} is not of a type derived from FortranBase'",
".",
"format",
"(",
"str",... | Return the name for this item registered with this NameSelector.
If no name has previously been registered, then generate a new
one. | [
"Return",
"the",
"name",
"for",
"this",
"item",
"registered",
"with",
"this",
"NameSelector",
".",
"If",
"no",
"name",
"has",
"previously",
"been",
"registered",
"then",
"generate",
"a",
"new",
"one",
"."
] | d46a44eae20d99205292c31785f936fbed47070f | https://github.com/Fortran-FOSS-Programmers/ford/blob/d46a44eae20d99205292c31785f936fbed47070f/ford/sourceform.py#L2466-L2493 | train |
Fortran-FOSS-Programmers/ford | ford/__init__.py | main | def main(proj_data,proj_docs,md):
"""
Main driver of FORD.
"""
if proj_data['relative']: proj_data['project_url'] = '.'
# Parse the files in your project
project = ford.fortran_project.Project(proj_data)
if len(project.files) < 1:
print("Error: No source files with appropriate extens... | python | def main(proj_data,proj_docs,md):
"""
Main driver of FORD.
"""
if proj_data['relative']: proj_data['project_url'] = '.'
# Parse the files in your project
project = ford.fortran_project.Project(proj_data)
if len(project.files) < 1:
print("Error: No source files with appropriate extens... | [
"def",
"main",
"(",
"proj_data",
",",
"proj_docs",
",",
"md",
")",
":",
"if",
"proj_data",
"[",
"'relative'",
"]",
":",
"proj_data",
"[",
"'project_url'",
"]",
"=",
"'.'",
"project",
"=",
"ford",
".",
"fortran_project",
".",
"Project",
"(",
"proj_data",
... | Main driver of FORD. | [
"Main",
"driver",
"of",
"FORD",
"."
] | d46a44eae20d99205292c31785f936fbed47070f | https://github.com/Fortran-FOSS-Programmers/ford/blob/d46a44eae20d99205292c31785f936fbed47070f/ford/__init__.py#L337-L382 | train |
Fortran-FOSS-Programmers/ford | ford/fixed2free2.py | convertToFree | def convertToFree(stream, length_limit=True):
"""Convert stream from fixed source form to free source form."""
linestack = []
for line in stream:
convline = FortranLine(line, length_limit)
if convline.is_regular:
if convline.isContinuation and linestack:
... | python | def convertToFree(stream, length_limit=True):
"""Convert stream from fixed source form to free source form."""
linestack = []
for line in stream:
convline = FortranLine(line, length_limit)
if convline.is_regular:
if convline.isContinuation and linestack:
... | [
"def",
"convertToFree",
"(",
"stream",
",",
"length_limit",
"=",
"True",
")",
":",
"linestack",
"=",
"[",
"]",
"for",
"line",
"in",
"stream",
":",
"convline",
"=",
"FortranLine",
"(",
"line",
",",
"length_limit",
")",
"if",
"convline",
".",
"is_regular",
... | Convert stream from fixed source form to free source form. | [
"Convert",
"stream",
"from",
"fixed",
"source",
"form",
"to",
"free",
"source",
"form",
"."
] | d46a44eae20d99205292c31785f936fbed47070f | https://github.com/Fortran-FOSS-Programmers/ford/blob/d46a44eae20d99205292c31785f936fbed47070f/ford/fixed2free2.py#L110-L127 | train |
Fortran-FOSS-Programmers/ford | ford/fixed2free2.py | FortranLine.continueLine | def continueLine(self):
"""Insert line continuation symbol at end of line."""
if not (self.isLong and self.is_regular):
self.line_conv = self.line_conv.rstrip() + " &\n"
else:
temp = self.line_conv[:72].rstrip() + " &"
self.line_conv = temp.ljust(72) + self.e... | python | def continueLine(self):
"""Insert line continuation symbol at end of line."""
if not (self.isLong and self.is_regular):
self.line_conv = self.line_conv.rstrip() + " &\n"
else:
temp = self.line_conv[:72].rstrip() + " &"
self.line_conv = temp.ljust(72) + self.e... | [
"def",
"continueLine",
"(",
"self",
")",
":",
"if",
"not",
"(",
"self",
".",
"isLong",
"and",
"self",
".",
"is_regular",
")",
":",
"self",
".",
"line_conv",
"=",
"self",
".",
"line_conv",
".",
"rstrip",
"(",
")",
"+",
"\" &\\n\"",
"else",
":",
"temp"... | Insert line continuation symbol at end of line. | [
"Insert",
"line",
"continuation",
"symbol",
"at",
"end",
"of",
"line",
"."
] | d46a44eae20d99205292c31785f936fbed47070f | https://github.com/Fortran-FOSS-Programmers/ford/blob/d46a44eae20d99205292c31785f936fbed47070f/ford/fixed2free2.py#L52-L59 | train |
Fortran-FOSS-Programmers/ford | ford/fortran_project.py | id_mods | def id_mods(obj,modlist,intrinsic_mods={},submodlist=[]):
"""
Match USE statements up with the right modules
"""
for i in range(len(obj.uses)):
for candidate in modlist:
if obj.uses[i][0].lower() == candidate.name.lower():
obj.uses[i] = [candidate, obj.uses[i][1]]
... | python | def id_mods(obj,modlist,intrinsic_mods={},submodlist=[]):
"""
Match USE statements up with the right modules
"""
for i in range(len(obj.uses)):
for candidate in modlist:
if obj.uses[i][0].lower() == candidate.name.lower():
obj.uses[i] = [candidate, obj.uses[i][1]]
... | [
"def",
"id_mods",
"(",
"obj",
",",
"modlist",
",",
"intrinsic_mods",
"=",
"{",
"}",
",",
"submodlist",
"=",
"[",
"]",
")",
":",
"for",
"i",
"in",
"range",
"(",
"len",
"(",
"obj",
".",
"uses",
")",
")",
":",
"for",
"candidate",
"in",
"modlist",
":... | Match USE statements up with the right modules | [
"Match",
"USE",
"statements",
"up",
"with",
"the",
"right",
"modules"
] | d46a44eae20d99205292c31785f936fbed47070f | https://github.com/Fortran-FOSS-Programmers/ford/blob/d46a44eae20d99205292c31785f936fbed47070f/ford/fortran_project.py#L338-L366 | train |
Fortran-FOSS-Programmers/ford | ford/fortran_project.py | Project.allfiles | def allfiles(self):
""" Instead of duplicating files, it is much more efficient to create the itterator on the fly """
for f in self.files:
yield f
for f in self.extra_files:
yield f | python | def allfiles(self):
""" Instead of duplicating files, it is much more efficient to create the itterator on the fly """
for f in self.files:
yield f
for f in self.extra_files:
yield f | [
"def",
"allfiles",
"(",
"self",
")",
":",
"for",
"f",
"in",
"self",
".",
"files",
":",
"yield",
"f",
"for",
"f",
"in",
"self",
".",
"extra_files",
":",
"yield",
"f"
] | Instead of duplicating files, it is much more efficient to create the itterator on the fly | [
"Instead",
"of",
"duplicating",
"files",
"it",
"is",
"much",
"more",
"efficient",
"to",
"create",
"the",
"itterator",
"on",
"the",
"fly"
] | d46a44eae20d99205292c31785f936fbed47070f | https://github.com/Fortran-FOSS-Programmers/ford/blob/d46a44eae20d99205292c31785f936fbed47070f/ford/fortran_project.py#L124-L129 | train |
Fortran-FOSS-Programmers/ford | ford/fortran_project.py | Project.make_links | def make_links(self,base_url='..'):
"""
Substitute intrasite links to documentation for other parts of
the program.
"""
ford.sourceform.set_base_url(base_url)
for src in self.allfiles:
src.make_links(self) | python | def make_links(self,base_url='..'):
"""
Substitute intrasite links to documentation for other parts of
the program.
"""
ford.sourceform.set_base_url(base_url)
for src in self.allfiles:
src.make_links(self) | [
"def",
"make_links",
"(",
"self",
",",
"base_url",
"=",
"'..'",
")",
":",
"ford",
".",
"sourceform",
".",
"set_base_url",
"(",
"base_url",
")",
"for",
"src",
"in",
"self",
".",
"allfiles",
":",
"src",
".",
"make_links",
"(",
"self",
")"
] | Substitute intrasite links to documentation for other parts of
the program. | [
"Substitute",
"intrasite",
"links",
"to",
"documentation",
"for",
"other",
"parts",
"of",
"the",
"program",
"."
] | d46a44eae20d99205292c31785f936fbed47070f | https://github.com/Fortran-FOSS-Programmers/ford/blob/d46a44eae20d99205292c31785f936fbed47070f/ford/fortran_project.py#L305-L312 | train |
Fortran-FOSS-Programmers/ford | ford/utils.py | sub_notes | def sub_notes(docs):
"""
Substitutes the special controls for notes, warnings, todos, and bugs with
the corresponding div.
"""
def substitute(match):
ret = "</p><div class=\"alert alert-{}\" role=\"alert\"><h4>{}</h4>" \
"<p>{}</p></div>".format(NOTE_TYPE[match.group(1).lower()... | python | def sub_notes(docs):
"""
Substitutes the special controls for notes, warnings, todos, and bugs with
the corresponding div.
"""
def substitute(match):
ret = "</p><div class=\"alert alert-{}\" role=\"alert\"><h4>{}</h4>" \
"<p>{}</p></div>".format(NOTE_TYPE[match.group(1).lower()... | [
"def",
"sub_notes",
"(",
"docs",
")",
":",
"def",
"substitute",
"(",
"match",
")",
":",
"ret",
"=",
"\"</p><div class=\\\"alert alert-{}\\\" role=\\\"alert\\\"><h4>{}</h4>\"",
"\"<p>{}</p></div>\"",
".",
"format",
"(",
"NOTE_TYPE",
"[",
"match",
".",
"group",
"(",
"... | Substitutes the special controls for notes, warnings, todos, and bugs with
the corresponding div. | [
"Substitutes",
"the",
"special",
"controls",
"for",
"notes",
"warnings",
"todos",
"and",
"bugs",
"with",
"the",
"corresponding",
"div",
"."
] | d46a44eae20d99205292c31785f936fbed47070f | https://github.com/Fortran-FOSS-Programmers/ford/blob/d46a44eae20d99205292c31785f936fbed47070f/ford/utils.py#L42-L55 | train |
Fortran-FOSS-Programmers/ford | ford/utils.py | paren_split | def paren_split(sep,string):
"""
Splits the string into pieces divided by sep, when sep is outside of parentheses.
"""
if len(sep) != 1: raise Exception("Separation string must be one character long")
retlist = []
level = 0
blevel = 0
left = 0
for i in range(len(string)):
if ... | python | def paren_split(sep,string):
"""
Splits the string into pieces divided by sep, when sep is outside of parentheses.
"""
if len(sep) != 1: raise Exception("Separation string must be one character long")
retlist = []
level = 0
blevel = 0
left = 0
for i in range(len(string)):
if ... | [
"def",
"paren_split",
"(",
"sep",
",",
"string",
")",
":",
"if",
"len",
"(",
"sep",
")",
"!=",
"1",
":",
"raise",
"Exception",
"(",
"\"Separation string must be one character long\"",
")",
"retlist",
"=",
"[",
"]",
"level",
"=",
"0",
"blevel",
"=",
"0",
... | Splits the string into pieces divided by sep, when sep is outside of parentheses. | [
"Splits",
"the",
"string",
"into",
"pieces",
"divided",
"by",
"sep",
"when",
"sep",
"is",
"outside",
"of",
"parentheses",
"."
] | d46a44eae20d99205292c31785f936fbed47070f | https://github.com/Fortran-FOSS-Programmers/ford/blob/d46a44eae20d99205292c31785f936fbed47070f/ford/utils.py#L88-L106 | train |
Fortran-FOSS-Programmers/ford | ford/utils.py | quote_split | def quote_split(sep,string):
"""
Splits the strings into pieces divided by sep, when sep in not inside quotes.
"""
if len(sep) != 1: raise Exception("Separation string must be one character long")
retlist = []
squote = False
dquote = False
left = 0
i = 0
while i < len(string):
... | python | def quote_split(sep,string):
"""
Splits the strings into pieces divided by sep, when sep in not inside quotes.
"""
if len(sep) != 1: raise Exception("Separation string must be one character long")
retlist = []
squote = False
dquote = False
left = 0
i = 0
while i < len(string):
... | [
"def",
"quote_split",
"(",
"sep",
",",
"string",
")",
":",
"if",
"len",
"(",
"sep",
")",
"!=",
"1",
":",
"raise",
"Exception",
"(",
"\"Separation string must be one character long\"",
")",
"retlist",
"=",
"[",
"]",
"squote",
"=",
"False",
"dquote",
"=",
"F... | Splits the strings into pieces divided by sep, when sep in not inside quotes. | [
"Splits",
"the",
"strings",
"into",
"pieces",
"divided",
"by",
"sep",
"when",
"sep",
"in",
"not",
"inside",
"quotes",
"."
] | d46a44eae20d99205292c31785f936fbed47070f | https://github.com/Fortran-FOSS-Programmers/ford/blob/d46a44eae20d99205292c31785f936fbed47070f/ford/utils.py#L110-L140 | train |
Fortran-FOSS-Programmers/ford | ford/utils.py | split_path | def split_path(path):
'''
Splits the argument into its constituent directories and returns them as
a list.
'''
def recurse_path(path,retlist):
if len(retlist) > 100:
fullpath = os.path.join(*([ path, ] + retlist))
print("Directory '{}' contains too many levels".format... | python | def split_path(path):
'''
Splits the argument into its constituent directories and returns them as
a list.
'''
def recurse_path(path,retlist):
if len(retlist) > 100:
fullpath = os.path.join(*([ path, ] + retlist))
print("Directory '{}' contains too many levels".format... | [
"def",
"split_path",
"(",
"path",
")",
":",
"def",
"recurse_path",
"(",
"path",
",",
"retlist",
")",
":",
"if",
"len",
"(",
"retlist",
")",
">",
"100",
":",
"fullpath",
"=",
"os",
".",
"path",
".",
"join",
"(",
"*",
"(",
"[",
"path",
",",
"]",
... | Splits the argument into its constituent directories and returns them as
a list. | [
"Splits",
"the",
"argument",
"into",
"its",
"constituent",
"directories",
"and",
"returns",
"them",
"as",
"a",
"list",
"."
] | d46a44eae20d99205292c31785f936fbed47070f | https://github.com/Fortran-FOSS-Programmers/ford/blob/d46a44eae20d99205292c31785f936fbed47070f/ford/utils.py#L143-L167 | train |
Fortran-FOSS-Programmers/ford | ford/utils.py | sub_macros | def sub_macros(string,base_url):
'''
Replaces macros in documentation with their appropriate values. These macros
are used for things like providing URLs.
'''
macros = { '|url|': base_url,
'|media|': os.path.join(base_url,'media'),
'|page|': os.path.join(base_url,'page'... | python | def sub_macros(string,base_url):
'''
Replaces macros in documentation with their appropriate values. These macros
are used for things like providing URLs.
'''
macros = { '|url|': base_url,
'|media|': os.path.join(base_url,'media'),
'|page|': os.path.join(base_url,'page'... | [
"def",
"sub_macros",
"(",
"string",
",",
"base_url",
")",
":",
"macros",
"=",
"{",
"'|url|'",
":",
"base_url",
",",
"'|media|'",
":",
"os",
".",
"path",
".",
"join",
"(",
"base_url",
",",
"'media'",
")",
",",
"'|page|'",
":",
"os",
".",
"path",
".",
... | Replaces macros in documentation with their appropriate values. These macros
are used for things like providing URLs. | [
"Replaces",
"macros",
"in",
"documentation",
"with",
"their",
"appropriate",
"values",
".",
"These",
"macros",
"are",
"used",
"for",
"things",
"like",
"providing",
"URLs",
"."
] | d46a44eae20d99205292c31785f936fbed47070f | https://github.com/Fortran-FOSS-Programmers/ford/blob/d46a44eae20d99205292c31785f936fbed47070f/ford/utils.py#L279-L290 | train |
Fortran-FOSS-Programmers/ford | ford/output.py | copytree | def copytree(src, dst):
"""Replaces shutil.copytree to avoid problems on certain file systems.
shutil.copytree() and shutil.copystat() invoke os.setxattr(), which seems
to fail when called for directories on at least one NFS file system.
The current routine is a simple replacement, which should be good... | python | def copytree(src, dst):
"""Replaces shutil.copytree to avoid problems on certain file systems.
shutil.copytree() and shutil.copystat() invoke os.setxattr(), which seems
to fail when called for directories on at least one NFS file system.
The current routine is a simple replacement, which should be good... | [
"def",
"copytree",
"(",
"src",
",",
"dst",
")",
":",
"def",
"touch",
"(",
"path",
")",
":",
"now",
"=",
"time",
".",
"time",
"(",
")",
"try",
":",
"os",
".",
"utime",
"(",
"path",
",",
"(",
"now",
",",
"now",
")",
")",
"except",
"os",
".",
... | Replaces shutil.copytree to avoid problems on certain file systems.
shutil.copytree() and shutil.copystat() invoke os.setxattr(), which seems
to fail when called for directories on at least one NFS file system.
The current routine is a simple replacement, which should be good enough for
Ford. | [
"Replaces",
"shutil",
".",
"copytree",
"to",
"avoid",
"problems",
"on",
"certain",
"file",
"systems",
"."
] | d46a44eae20d99205292c31785f936fbed47070f | https://github.com/Fortran-FOSS-Programmers/ford/blob/d46a44eae20d99205292c31785f936fbed47070f/ford/output.py#L520-L551 | train |
gem/oq-engine | openquake/calculators/export/hazard.py | export_hmaps_csv | def export_hmaps_csv(key, dest, sitemesh, array, comment):
"""
Export the hazard maps of the given realization into CSV.
:param key: output_type and export_type
:param dest: name of the exported file
:param sitemesh: site collection
:param array: a composite array of dtype hmap_dt
:param co... | python | def export_hmaps_csv(key, dest, sitemesh, array, comment):
"""
Export the hazard maps of the given realization into CSV.
:param key: output_type and export_type
:param dest: name of the exported file
:param sitemesh: site collection
:param array: a composite array of dtype hmap_dt
:param co... | [
"def",
"export_hmaps_csv",
"(",
"key",
",",
"dest",
",",
"sitemesh",
",",
"array",
",",
"comment",
")",
":",
"curves",
"=",
"util",
".",
"compose_arrays",
"(",
"sitemesh",
",",
"array",
")",
"writers",
".",
"write_csv",
"(",
"dest",
",",
"curves",
",",
... | Export the hazard maps of the given realization into CSV.
:param key: output_type and export_type
:param dest: name of the exported file
:param sitemesh: site collection
:param array: a composite array of dtype hmap_dt
:param comment: comment to use as header of the exported CSV file | [
"Export",
"the",
"hazard",
"maps",
"of",
"the",
"given",
"realization",
"into",
"CSV",
"."
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/calculators/export/hazard.py#L223-L235 | train |
gem/oq-engine | openquake/calculators/export/hazard.py | export_hcurves_by_imt_csv | def export_hcurves_by_imt_csv(
key, kind, rlzs_assoc, fname, sitecol, array, oq, checksum):
"""
Export the curves of the given realization into CSV.
:param key: output_type and export_type
:param kind: a string with the kind of output (realization or statistics)
:param rlzs_assoc: a :class:... | python | def export_hcurves_by_imt_csv(
key, kind, rlzs_assoc, fname, sitecol, array, oq, checksum):
"""
Export the curves of the given realization into CSV.
:param key: output_type and export_type
:param kind: a string with the kind of output (realization or statistics)
:param rlzs_assoc: a :class:... | [
"def",
"export_hcurves_by_imt_csv",
"(",
"key",
",",
"kind",
",",
"rlzs_assoc",
",",
"fname",
",",
"sitecol",
",",
"array",
",",
"oq",
",",
"checksum",
")",
":",
"nsites",
"=",
"len",
"(",
"sitecol",
")",
"fnames",
"=",
"[",
"]",
"for",
"imt",
",",
"... | Export the curves of the given realization into CSV.
:param key: output_type and export_type
:param kind: a string with the kind of output (realization or statistics)
:param rlzs_assoc: a :class:`openquake.commonlib.source.RlzsAssoc` instance
:param fname: name of the exported file
:param sitecol: ... | [
"Export",
"the",
"curves",
"of",
"the",
"given",
"realization",
"into",
"CSV",
"."
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/calculators/export/hazard.py#L248-L277 | train |
gem/oq-engine | openquake/calculators/export/hazard.py | export_hcurves_csv | def export_hcurves_csv(ekey, dstore):
"""
Exports the hazard curves into several .csv files
:param ekey: export key, i.e. a pair (datastore key, fmt)
:param dstore: datastore object
"""
oq = dstore['oqparam']
info = get_info(dstore)
rlzs_assoc = dstore['csm_info'].get_rlzs_assoc()
R... | python | def export_hcurves_csv(ekey, dstore):
"""
Exports the hazard curves into several .csv files
:param ekey: export key, i.e. a pair (datastore key, fmt)
:param dstore: datastore object
"""
oq = dstore['oqparam']
info = get_info(dstore)
rlzs_assoc = dstore['csm_info'].get_rlzs_assoc()
R... | [
"def",
"export_hcurves_csv",
"(",
"ekey",
",",
"dstore",
")",
":",
"oq",
"=",
"dstore",
"[",
"'oqparam'",
"]",
"info",
"=",
"get_info",
"(",
"dstore",
")",
"rlzs_assoc",
"=",
"dstore",
"[",
"'csm_info'",
"]",
".",
"get_rlzs_assoc",
"(",
")",
"R",
"=",
... | Exports the hazard curves into several .csv files
:param ekey: export key, i.e. a pair (datastore key, fmt)
:param dstore: datastore object | [
"Exports",
"the",
"hazard",
"curves",
"into",
"several",
".",
"csv",
"files"
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/calculators/export/hazard.py#L333-L373 | train |
gem/oq-engine | openquake/calculators/export/hazard.py | save_disagg_to_csv | def save_disagg_to_csv(metadata, matrices):
"""
Save disaggregation matrices to multiple .csv files.
"""
skip_keys = ('Mag', 'Dist', 'Lon', 'Lat', 'Eps', 'TRT')
base_header = ','.join(
'%s=%s' % (key, value) for key, value in metadata.items()
if value is not None and key not in skip_... | python | def save_disagg_to_csv(metadata, matrices):
"""
Save disaggregation matrices to multiple .csv files.
"""
skip_keys = ('Mag', 'Dist', 'Lon', 'Lat', 'Eps', 'TRT')
base_header = ','.join(
'%s=%s' % (key, value) for key, value in metadata.items()
if value is not None and key not in skip_... | [
"def",
"save_disagg_to_csv",
"(",
"metadata",
",",
"matrices",
")",
":",
"skip_keys",
"=",
"(",
"'Mag'",
",",
"'Dist'",
",",
"'Lon'",
",",
"'Lat'",
",",
"'Eps'",
",",
"'TRT'",
")",
"base_header",
"=",
"','",
".",
"join",
"(",
"'%s=%s'",
"%",
"(",
"key"... | Save disaggregation matrices to multiple .csv files. | [
"Save",
"disaggregation",
"matrices",
"to",
"multiple",
".",
"csv",
"files",
"."
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/calculators/export/hazard.py#L743-L776 | train |
gem/oq-engine | openquake/hazardlib/gsim/bradley_2013b.py | Bradley2013bChchCBD._interp_function | def _interp_function(self, y_ip1, y_i, t_ip1, t_i, imt_per):
"""
Generic interpolation function used in equation 19 of 2013 report.
"""
return y_i + (y_ip1 - y_i) / (t_ip1 - t_i) * (imt_per - t_i) | python | def _interp_function(self, y_ip1, y_i, t_ip1, t_i, imt_per):
"""
Generic interpolation function used in equation 19 of 2013 report.
"""
return y_i + (y_ip1 - y_i) / (t_ip1 - t_i) * (imt_per - t_i) | [
"def",
"_interp_function",
"(",
"self",
",",
"y_ip1",
",",
"y_i",
",",
"t_ip1",
",",
"t_i",
",",
"imt_per",
")",
":",
"return",
"y_i",
"+",
"(",
"y_ip1",
"-",
"y_i",
")",
"/",
"(",
"t_ip1",
"-",
"t_i",
")",
"*",
"(",
"imt_per",
"-",
"t_i",
")"
] | Generic interpolation function used in equation 19 of 2013 report. | [
"Generic",
"interpolation",
"function",
"used",
"in",
"equation",
"19",
"of",
"2013",
"report",
"."
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/hazardlib/gsim/bradley_2013b.py#L154-L158 | train |
gem/oq-engine | openquake/hazardlib/gsim/bradley_2013b.py | Bradley2013bChchCBD._get_SRF_tau | def _get_SRF_tau(self, imt_per):
"""
Table 6 and equation 19 of 2013 report.
"""
if imt_per < 1:
srf = 0.87
elif 1 <= imt_per < 5:
srf = self._interp_function(0.58, 0.87, 5, 1, imt_per)
elif 5 <= imt_per <= 10:
srf = 0.58
else:
... | python | def _get_SRF_tau(self, imt_per):
"""
Table 6 and equation 19 of 2013 report.
"""
if imt_per < 1:
srf = 0.87
elif 1 <= imt_per < 5:
srf = self._interp_function(0.58, 0.87, 5, 1, imt_per)
elif 5 <= imt_per <= 10:
srf = 0.58
else:
... | [
"def",
"_get_SRF_tau",
"(",
"self",
",",
"imt_per",
")",
":",
"if",
"imt_per",
"<",
"1",
":",
"srf",
"=",
"0.87",
"elif",
"1",
"<=",
"imt_per",
"<",
"5",
":",
"srf",
"=",
"self",
".",
"_interp_function",
"(",
"0.58",
",",
"0.87",
",",
"5",
",",
"... | Table 6 and equation 19 of 2013 report. | [
"Table",
"6",
"and",
"equation",
"19",
"of",
"2013",
"report",
"."
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/hazardlib/gsim/bradley_2013b.py#L160-L173 | train |
gem/oq-engine | openquake/hazardlib/gsim/bradley_2013b.py | Bradley2013bChchCBD._get_SRF_phi | def _get_SRF_phi(self, imt_per):
"""
Table 7 and equation 19 of 2013 report. NB change in notation,
2013 report calls this term 'sigma' but it is referred to here
as phi.
"""
if imt_per < 0.6:
srf = 0.8
elif 0.6 <= imt_per < 1:
srf = self._... | python | def _get_SRF_phi(self, imt_per):
"""
Table 7 and equation 19 of 2013 report. NB change in notation,
2013 report calls this term 'sigma' but it is referred to here
as phi.
"""
if imt_per < 0.6:
srf = 0.8
elif 0.6 <= imt_per < 1:
srf = self._... | [
"def",
"_get_SRF_phi",
"(",
"self",
",",
"imt_per",
")",
":",
"if",
"imt_per",
"<",
"0.6",
":",
"srf",
"=",
"0.8",
"elif",
"0.6",
"<=",
"imt_per",
"<",
"1",
":",
"srf",
"=",
"self",
".",
"_interp_function",
"(",
"0.7",
",",
"0.8",
",",
"1",
",",
... | Table 7 and equation 19 of 2013 report. NB change in notation,
2013 report calls this term 'sigma' but it is referred to here
as phi. | [
"Table",
"7",
"and",
"equation",
"19",
"of",
"2013",
"report",
".",
"NB",
"change",
"in",
"notation",
"2013",
"report",
"calls",
"this",
"term",
"sigma",
"but",
"it",
"is",
"referred",
"to",
"here",
"as",
"phi",
"."
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/hazardlib/gsim/bradley_2013b.py#L175-L190 | train |
gem/oq-engine | openquake/hazardlib/gsim/bradley_2013b.py | Bradley2013bChchCBD._get_SRF_sigma | def _get_SRF_sigma(self, imt_per):
"""
Table 8 and equation 19 of 2013 report. NB change in notation,
2013 report calls this term 'sigma_t' but it is referred to
here as sigma. Note that Table 8 is identical to Table 7 in
the 2013 report.
"""
if imt_per < 0.6:
... | python | def _get_SRF_sigma(self, imt_per):
"""
Table 8 and equation 19 of 2013 report. NB change in notation,
2013 report calls this term 'sigma_t' but it is referred to
here as sigma. Note that Table 8 is identical to Table 7 in
the 2013 report.
"""
if imt_per < 0.6:
... | [
"def",
"_get_SRF_sigma",
"(",
"self",
",",
"imt_per",
")",
":",
"if",
"imt_per",
"<",
"0.6",
":",
"srf",
"=",
"0.8",
"elif",
"0.6",
"<=",
"imt_per",
"<",
"1",
":",
"srf",
"=",
"self",
".",
"_interp_function",
"(",
"0.7",
",",
"0.8",
",",
"1",
",",
... | Table 8 and equation 19 of 2013 report. NB change in notation,
2013 report calls this term 'sigma_t' but it is referred to
here as sigma. Note that Table 8 is identical to Table 7 in
the 2013 report. | [
"Table",
"8",
"and",
"equation",
"19",
"of",
"2013",
"report",
".",
"NB",
"change",
"in",
"notation",
"2013",
"report",
"calls",
"this",
"term",
"sigma_t",
"but",
"it",
"is",
"referred",
"to",
"here",
"as",
"sigma",
".",
"Note",
"that",
"Table",
"8",
"... | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/hazardlib/gsim/bradley_2013b.py#L192-L208 | train |
gem/oq-engine | openquake/hazardlib/gsim/bradley_2013b.py | Bradley2013bChchCBD._get_dL2L | def _get_dL2L(self, imt_per):
"""
Table 3 and equation 19 of 2013 report.
"""
if imt_per < 0.18:
dL2L = -0.06
elif 0.18 <= imt_per < 0.35:
dL2L = self._interp_function(0.12, -0.06, 0.35, 0.18, imt_per)
elif 0.35 <= imt_per <= 10:
dL2L =... | python | def _get_dL2L(self, imt_per):
"""
Table 3 and equation 19 of 2013 report.
"""
if imt_per < 0.18:
dL2L = -0.06
elif 0.18 <= imt_per < 0.35:
dL2L = self._interp_function(0.12, -0.06, 0.35, 0.18, imt_per)
elif 0.35 <= imt_per <= 10:
dL2L =... | [
"def",
"_get_dL2L",
"(",
"self",
",",
"imt_per",
")",
":",
"if",
"imt_per",
"<",
"0.18",
":",
"dL2L",
"=",
"-",
"0.06",
"elif",
"0.18",
"<=",
"imt_per",
"<",
"0.35",
":",
"dL2L",
"=",
"self",
".",
"_interp_function",
"(",
"0.12",
",",
"-",
"0.06",
... | Table 3 and equation 19 of 2013 report. | [
"Table",
"3",
"and",
"equation",
"19",
"of",
"2013",
"report",
"."
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/hazardlib/gsim/bradley_2013b.py#L210-L223 | train |
gem/oq-engine | openquake/hazardlib/gsim/bradley_2013b.py | Bradley2013bChchCBD._get_dS2S | def _get_dS2S(self, imt_per):
"""
Table 4 of 2013 report
"""
if imt_per == 0:
dS2S = 0.05
elif 0 < imt_per < 0.15:
dS2S = self._interp_function(-0.15, 0.05, 0.15, 0, imt_per)
elif 0.15 <= imt_per < 0.45:
dS2S = self._interp_function(0.4... | python | def _get_dS2S(self, imt_per):
"""
Table 4 of 2013 report
"""
if imt_per == 0:
dS2S = 0.05
elif 0 < imt_per < 0.15:
dS2S = self._interp_function(-0.15, 0.05, 0.15, 0, imt_per)
elif 0.15 <= imt_per < 0.45:
dS2S = self._interp_function(0.4... | [
"def",
"_get_dS2S",
"(",
"self",
",",
"imt_per",
")",
":",
"if",
"imt_per",
"==",
"0",
":",
"dS2S",
"=",
"0.05",
"elif",
"0",
"<",
"imt_per",
"<",
"0.15",
":",
"dS2S",
"=",
"self",
".",
"_interp_function",
"(",
"-",
"0.15",
",",
"0.05",
",",
"0.15"... | Table 4 of 2013 report | [
"Table",
"4",
"of",
"2013",
"report"
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/hazardlib/gsim/bradley_2013b.py#L225-L244 | train |
gem/oq-engine | openquake/hazardlib/calc/filters.py | context | def context(src):
"""
Used to add the source_id to the error message. To be used as
with context(src):
operation_with(src)
Typically the operation is filtering a source, that can fail for
tricky geometries.
"""
try:
yield
except Exception:
etype, err, tb = sys.e... | python | def context(src):
"""
Used to add the source_id to the error message. To be used as
with context(src):
operation_with(src)
Typically the operation is filtering a source, that can fail for
tricky geometries.
"""
try:
yield
except Exception:
etype, err, tb = sys.e... | [
"def",
"context",
"(",
"src",
")",
":",
"try",
":",
"yield",
"except",
"Exception",
":",
"etype",
",",
"err",
",",
"tb",
"=",
"sys",
".",
"exc_info",
"(",
")",
"msg",
"=",
"'An error occurred with source id=%s. Error: %s'",
"msg",
"%=",
"(",
"src",
".",
... | Used to add the source_id to the error message. To be used as
with context(src):
operation_with(src)
Typically the operation is filtering a source, that can fail for
tricky geometries. | [
"Used",
"to",
"add",
"the",
"source_id",
"to",
"the",
"error",
"message",
".",
"To",
"be",
"used",
"as"
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/hazardlib/calc/filters.py#L39-L55 | train |
gem/oq-engine | openquake/hazardlib/calc/filters.py | IntegrationDistance.get_bounding_box | def get_bounding_box(self, lon, lat, trt=None, mag=None):
"""
Build a bounding box around the given lon, lat by computing the
maximum_distance at the given tectonic region type and magnitude.
:param lon: longitude
:param lat: latitude
:param trt: tectonic region type, po... | python | def get_bounding_box(self, lon, lat, trt=None, mag=None):
"""
Build a bounding box around the given lon, lat by computing the
maximum_distance at the given tectonic region type and magnitude.
:param lon: longitude
:param lat: latitude
:param trt: tectonic region type, po... | [
"def",
"get_bounding_box",
"(",
"self",
",",
"lon",
",",
"lat",
",",
"trt",
"=",
"None",
",",
"mag",
"=",
"None",
")",
":",
"if",
"trt",
"is",
"None",
":",
"maxdist",
"=",
"max",
"(",
"self",
"(",
"trt",
",",
"mag",
")",
"for",
"trt",
"in",
"se... | Build a bounding box around the given lon, lat by computing the
maximum_distance at the given tectonic region type and magnitude.
:param lon: longitude
:param lat: latitude
:param trt: tectonic region type, possibly None
:param mag: magnitude, possibly None
:returns: min... | [
"Build",
"a",
"bounding",
"box",
"around",
"the",
"given",
"lon",
"lat",
"by",
"computing",
"the",
"maximum_distance",
"at",
"the",
"given",
"tectonic",
"region",
"type",
"and",
"magnitude",
"."
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/hazardlib/calc/filters.py#L138-L155 | train |
gem/oq-engine | openquake/hazardlib/calc/filters.py | IntegrationDistance.get_affected_box | def get_affected_box(self, src):
"""
Get the enlarged bounding box of a source.
:param src: a source object
:returns: a bounding box (min_lon, min_lat, max_lon, max_lat)
"""
mag = src.get_min_max_mag()[1]
maxdist = self(src.tectonic_region_type, mag)
bbox... | python | def get_affected_box(self, src):
"""
Get the enlarged bounding box of a source.
:param src: a source object
:returns: a bounding box (min_lon, min_lat, max_lon, max_lat)
"""
mag = src.get_min_max_mag()[1]
maxdist = self(src.tectonic_region_type, mag)
bbox... | [
"def",
"get_affected_box",
"(",
"self",
",",
"src",
")",
":",
"mag",
"=",
"src",
".",
"get_min_max_mag",
"(",
")",
"[",
"1",
"]",
"maxdist",
"=",
"self",
"(",
"src",
".",
"tectonic_region_type",
",",
"mag",
")",
"bbox",
"=",
"get_bounding_box",
"(",
"s... | Get the enlarged bounding box of a source.
:param src: a source object
:returns: a bounding box (min_lon, min_lat, max_lon, max_lat) | [
"Get",
"the",
"enlarged",
"bounding",
"box",
"of",
"a",
"source",
"."
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/hazardlib/calc/filters.py#L157-L167 | train |
gem/oq-engine | openquake/hazardlib/calc/filters.py | SourceFilter.sitecol | def sitecol(self):
"""
Read the site collection from .filename and cache it
"""
if 'sitecol' in vars(self):
return self.__dict__['sitecol']
if self.filename is None or not os.path.exists(self.filename):
# case of nofilter/None sitecol
return
... | python | def sitecol(self):
"""
Read the site collection from .filename and cache it
"""
if 'sitecol' in vars(self):
return self.__dict__['sitecol']
if self.filename is None or not os.path.exists(self.filename):
# case of nofilter/None sitecol
return
... | [
"def",
"sitecol",
"(",
"self",
")",
":",
"if",
"'sitecol'",
"in",
"vars",
"(",
"self",
")",
":",
"return",
"self",
".",
"__dict__",
"[",
"'sitecol'",
"]",
"if",
"self",
".",
"filename",
"is",
"None",
"or",
"not",
"os",
".",
"path",
".",
"exists",
"... | Read the site collection from .filename and cache it | [
"Read",
"the",
"site",
"collection",
"from",
".",
"filename",
"and",
"cache",
"it"
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/hazardlib/calc/filters.py#L276-L287 | train |
gem/oq-engine | openquake/hazardlib/geo/surface/simple_fault.py | SimpleFaultSurface.hypocentre_patch_index | def hypocentre_patch_index(cls, hypocentre, rupture_top_edge,
upper_seismogenic_depth,
lower_seismogenic_depth, dip):
"""
This methods finds the index of the fault patch including
the hypocentre.
:param hypocentre:
... | python | def hypocentre_patch_index(cls, hypocentre, rupture_top_edge,
upper_seismogenic_depth,
lower_seismogenic_depth, dip):
"""
This methods finds the index of the fault patch including
the hypocentre.
:param hypocentre:
... | [
"def",
"hypocentre_patch_index",
"(",
"cls",
",",
"hypocentre",
",",
"rupture_top_edge",
",",
"upper_seismogenic_depth",
",",
"lower_seismogenic_depth",
",",
"dip",
")",
":",
"totaln_patch",
"=",
"len",
"(",
"rupture_top_edge",
")",
"indexlist",
"=",
"[",
"]",
"di... | This methods finds the index of the fault patch including
the hypocentre.
:param hypocentre:
:class:`~openquake.hazardlib.geo.point.Point` object
representing the location of hypocentre.
:param rupture_top_edge:
A instances of :class:`openquake.hazardlib.geo.... | [
"This",
"methods",
"finds",
"the",
"index",
"of",
"the",
"fault",
"patch",
"including",
"the",
"hypocentre",
"."
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/hazardlib/geo/surface/simple_fault.py#L256-L298 | train |
gem/oq-engine | openquake/hazardlib/geo/surface/simple_fault.py | SimpleFaultSurface.get_surface_vertexes | def get_surface_vertexes(cls, fault_trace,
upper_seismogenic_depth,
lower_seismogenic_depth, dip):
"""
Get surface main vertexes.
Parameters are the same as for :meth:`from_fault_data`, excluding
mesh spacing.
:returns:
... | python | def get_surface_vertexes(cls, fault_trace,
upper_seismogenic_depth,
lower_seismogenic_depth, dip):
"""
Get surface main vertexes.
Parameters are the same as for :meth:`from_fault_data`, excluding
mesh spacing.
:returns:
... | [
"def",
"get_surface_vertexes",
"(",
"cls",
",",
"fault_trace",
",",
"upper_seismogenic_depth",
",",
"lower_seismogenic_depth",
",",
"dip",
")",
":",
"dip_tan",
"=",
"math",
".",
"tan",
"(",
"math",
".",
"radians",
"(",
"dip",
")",
")",
"hdist_top",
"=",
"upp... | Get surface main vertexes.
Parameters are the same as for :meth:`from_fault_data`, excluding
mesh spacing.
:returns:
Instance of :class:`~openquake.hazardlib.geo.polygon.Polygon`
describing the surface projection of the simple fault with
specified parameters... | [
"Get",
"surface",
"main",
"vertexes",
"."
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/hazardlib/geo/surface/simple_fault.py#L301-L336 | train |
gem/oq-engine | openquake/hazardlib/geo/surface/simple_fault.py | SimpleFaultSurface.surface_projection_from_fault_data | def surface_projection_from_fault_data(cls, fault_trace,
upper_seismogenic_depth,
lower_seismogenic_depth, dip):
"""
Get a surface projection of the simple fault surface.
Parameters are the same as for :meth:`... | python | def surface_projection_from_fault_data(cls, fault_trace,
upper_seismogenic_depth,
lower_seismogenic_depth, dip):
"""
Get a surface projection of the simple fault surface.
Parameters are the same as for :meth:`... | [
"def",
"surface_projection_from_fault_data",
"(",
"cls",
",",
"fault_trace",
",",
"upper_seismogenic_depth",
",",
"lower_seismogenic_depth",
",",
"dip",
")",
":",
"lons",
",",
"lats",
"=",
"cls",
".",
"get_surface_vertexes",
"(",
"fault_trace",
",",
"upper_seismogenic... | Get a surface projection of the simple fault surface.
Parameters are the same as for :meth:`from_fault_data`, excluding
mesh spacing.
:returns:
Instance of :class:`~openquake.hazardlib.geo.polygon.Polygon`
describing the surface projection of the simple fault with
... | [
"Get",
"a",
"surface",
"projection",
"of",
"the",
"simple",
"fault",
"surface",
"."
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/hazardlib/geo/surface/simple_fault.py#L339-L356 | train |
gem/oq-engine | openquake/hazardlib/gsim/zhao_2006.py | ZhaoEtAl2006Asc._compute_distance_term | def _compute_distance_term(self, C, mag, rrup):
"""
Compute second and third terms in equation 1, p. 901.
"""
term1 = C['b'] * rrup
term2 = - np.log(rrup + C['c'] * np.exp(C['d'] * mag))
return term1 + term2 | python | def _compute_distance_term(self, C, mag, rrup):
"""
Compute second and third terms in equation 1, p. 901.
"""
term1 = C['b'] * rrup
term2 = - np.log(rrup + C['c'] * np.exp(C['d'] * mag))
return term1 + term2 | [
"def",
"_compute_distance_term",
"(",
"self",
",",
"C",
",",
"mag",
",",
"rrup",
")",
":",
"term1",
"=",
"C",
"[",
"'b'",
"]",
"*",
"rrup",
"term2",
"=",
"-",
"np",
".",
"log",
"(",
"rrup",
"+",
"C",
"[",
"'c'",
"]",
"*",
"np",
".",
"exp",
"(... | Compute second and third terms in equation 1, p. 901. | [
"Compute",
"second",
"and",
"third",
"terms",
"in",
"equation",
"1",
"p",
".",
"901",
"."
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/hazardlib/gsim/zhao_2006.py#L133-L140 | train |
gem/oq-engine | openquake/hazardlib/gsim/zhao_2006.py | ZhaoEtAl2006Asc._compute_focal_depth_term | def _compute_focal_depth_term(self, C, hypo_depth):
"""
Compute fourth term in equation 1, p. 901.
"""
# p. 901. "(i.e, depth is capped at 125 km)".
focal_depth = hypo_depth
if focal_depth > 125.0:
focal_depth = 125.0
# p. 902. "We used the value of 1... | python | def _compute_focal_depth_term(self, C, hypo_depth):
"""
Compute fourth term in equation 1, p. 901.
"""
# p. 901. "(i.e, depth is capped at 125 km)".
focal_depth = hypo_depth
if focal_depth > 125.0:
focal_depth = 125.0
# p. 902. "We used the value of 1... | [
"def",
"_compute_focal_depth_term",
"(",
"self",
",",
"C",
",",
"hypo_depth",
")",
":",
"focal_depth",
"=",
"hypo_depth",
"if",
"focal_depth",
">",
"125.0",
":",
"focal_depth",
"=",
"125.0",
"hc",
"=",
"15.0",
"return",
"float",
"(",
"focal_depth",
">=",
"hc... | Compute fourth term in equation 1, p. 901. | [
"Compute",
"fourth",
"term",
"in",
"equation",
"1",
"p",
".",
"901",
"."
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/hazardlib/gsim/zhao_2006.py#L142-L157 | train |
gem/oq-engine | openquake/hazardlib/gsim/zhao_2006.py | ZhaoEtAl2006Asc._compute_site_class_term | def _compute_site_class_term(self, C, vs30):
"""
Compute nine-th term in equation 1, p. 901.
"""
# map vs30 value to site class, see table 2, p. 901.
site_term = np.zeros(len(vs30))
# hard rock
site_term[vs30 > 1100.0] = C['CH']
# rock
site_term[... | python | def _compute_site_class_term(self, C, vs30):
"""
Compute nine-th term in equation 1, p. 901.
"""
# map vs30 value to site class, see table 2, p. 901.
site_term = np.zeros(len(vs30))
# hard rock
site_term[vs30 > 1100.0] = C['CH']
# rock
site_term[... | [
"def",
"_compute_site_class_term",
"(",
"self",
",",
"C",
",",
"vs30",
")",
":",
"site_term",
"=",
"np",
".",
"zeros",
"(",
"len",
"(",
"vs30",
")",
")",
"site_term",
"[",
"vs30",
">",
"1100.0",
"]",
"=",
"C",
"[",
"'CH'",
"]",
"site_term",
"[",
"(... | Compute nine-th term in equation 1, p. 901. | [
"Compute",
"nine",
"-",
"th",
"term",
"in",
"equation",
"1",
"p",
".",
"901",
"."
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/hazardlib/gsim/zhao_2006.py#L168-L190 | train |
gem/oq-engine | openquake/hazardlib/gsim/zhao_2006.py | ZhaoEtAl2006Asc._compute_magnitude_squared_term | def _compute_magnitude_squared_term(self, P, M, Q, W, mag):
"""
Compute magnitude squared term, equation 5, p. 909.
"""
return P * (mag - M) + Q * (mag - M) ** 2 + W | python | def _compute_magnitude_squared_term(self, P, M, Q, W, mag):
"""
Compute magnitude squared term, equation 5, p. 909.
"""
return P * (mag - M) + Q * (mag - M) ** 2 + W | [
"def",
"_compute_magnitude_squared_term",
"(",
"self",
",",
"P",
",",
"M",
",",
"Q",
",",
"W",
",",
"mag",
")",
":",
"return",
"P",
"*",
"(",
"mag",
"-",
"M",
")",
"+",
"Q",
"*",
"(",
"mag",
"-",
"M",
")",
"**",
"2",
"+",
"W"
] | Compute magnitude squared term, equation 5, p. 909. | [
"Compute",
"magnitude",
"squared",
"term",
"equation",
"5",
"p",
".",
"909",
"."
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/hazardlib/gsim/zhao_2006.py#L192-L196 | train |
gem/oq-engine | openquake/hazardlib/gsim/zhao_2006.py | ZhaoEtAl2006SSlab._compute_slab_correction_term | def _compute_slab_correction_term(self, C, rrup):
"""
Compute path modification term for slab events, that is
the 8-th term in equation 1, p. 901.
"""
slab_term = C['SSL'] * np.log(rrup)
return slab_term | python | def _compute_slab_correction_term(self, C, rrup):
"""
Compute path modification term for slab events, that is
the 8-th term in equation 1, p. 901.
"""
slab_term = C['SSL'] * np.log(rrup)
return slab_term | [
"def",
"_compute_slab_correction_term",
"(",
"self",
",",
"C",
",",
"rrup",
")",
":",
"slab_term",
"=",
"C",
"[",
"'SSL'",
"]",
"*",
"np",
".",
"log",
"(",
"rrup",
")",
"return",
"slab_term"
] | Compute path modification term for slab events, that is
the 8-th term in equation 1, p. 901. | [
"Compute",
"path",
"modification",
"term",
"for",
"slab",
"events",
"that",
"is",
"the",
"8",
"-",
"th",
"term",
"in",
"equation",
"1",
"p",
".",
"901",
"."
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/hazardlib/gsim/zhao_2006.py#L369-L376 | train |
gem/oq-engine | openquake/hazardlib/gsim/zhao_2006.py | ZhaoEtAl2006AscSGS.get_mean_and_stddevs | def get_mean_and_stddevs(self, sites, rup, dists, imt, stddev_types):
"""
Using a minimum distance of 5km for the calculation.
"""
dists_mod = copy.deepcopy(dists)
dists_mod.rrup[dists.rrup <= 5.] = 5.
return super().get_mean_and_stddevs(
sites, rup, dists_m... | python | def get_mean_and_stddevs(self, sites, rup, dists, imt, stddev_types):
"""
Using a minimum distance of 5km for the calculation.
"""
dists_mod = copy.deepcopy(dists)
dists_mod.rrup[dists.rrup <= 5.] = 5.
return super().get_mean_and_stddevs(
sites, rup, dists_m... | [
"def",
"get_mean_and_stddevs",
"(",
"self",
",",
"sites",
",",
"rup",
",",
"dists",
",",
"imt",
",",
"stddev_types",
")",
":",
"dists_mod",
"=",
"copy",
".",
"deepcopy",
"(",
"dists",
")",
"dists_mod",
".",
"rrup",
"[",
"dists",
".",
"rrup",
"<=",
"5."... | Using a minimum distance of 5km for the calculation. | [
"Using",
"a",
"minimum",
"distance",
"of",
"5km",
"for",
"the",
"calculation",
"."
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/hazardlib/gsim/zhao_2006.py#L654-L663 | train |
gem/oq-engine | openquake/engine/utils/__init__.py | confirm | def confirm(prompt):
"""
Ask for confirmation, given a ``prompt`` and return a boolean value.
"""
while True:
try:
answer = input(prompt)
except KeyboardInterrupt:
# the user presses ctrl+c, just say 'no'
return False
answer = answer.strip().lo... | python | def confirm(prompt):
"""
Ask for confirmation, given a ``prompt`` and return a boolean value.
"""
while True:
try:
answer = input(prompt)
except KeyboardInterrupt:
# the user presses ctrl+c, just say 'no'
return False
answer = answer.strip().lo... | [
"def",
"confirm",
"(",
"prompt",
")",
":",
"while",
"True",
":",
"try",
":",
"answer",
"=",
"input",
"(",
"prompt",
")",
"except",
"KeyboardInterrupt",
":",
"return",
"False",
"answer",
"=",
"answer",
".",
"strip",
"(",
")",
".",
"lower",
"(",
")",
"... | Ask for confirmation, given a ``prompt`` and return a boolean value. | [
"Ask",
"for",
"confirmation",
"given",
"a",
"prompt",
"and",
"return",
"a",
"boolean",
"value",
"."
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/engine/utils/__init__.py#L20-L34 | train |
gem/oq-engine | openquake/risklib/asset.py | Exposure._csv_header | def _csv_header(self):
"""
Extract the expected CSV header from the exposure metadata
"""
fields = ['id', 'number', 'taxonomy', 'lon', 'lat']
for name in self.cost_types['name']:
fields.append(name)
if 'per_area' in self.cost_types['type']:
fields.... | python | def _csv_header(self):
"""
Extract the expected CSV header from the exposure metadata
"""
fields = ['id', 'number', 'taxonomy', 'lon', 'lat']
for name in self.cost_types['name']:
fields.append(name)
if 'per_area' in self.cost_types['type']:
fields.... | [
"def",
"_csv_header",
"(",
"self",
")",
":",
"fields",
"=",
"[",
"'id'",
",",
"'number'",
",",
"'taxonomy'",
",",
"'lon'",
",",
"'lat'",
"]",
"for",
"name",
"in",
"self",
".",
"cost_types",
"[",
"'name'",
"]",
":",
"fields",
".",
"append",
"(",
"name... | Extract the expected CSV header from the exposure metadata | [
"Extract",
"the",
"expected",
"CSV",
"header",
"from",
"the",
"exposure",
"metadata"
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/risklib/asset.py#L885-L897 | train |
gem/oq-engine | openquake/risklib/riskmodels.py | build_vf_node | def build_vf_node(vf):
"""
Convert a VulnerabilityFunction object into a Node suitable
for XML conversion.
"""
nodes = [Node('imls', {'imt': vf.imt}, vf.imls),
Node('meanLRs', {}, vf.mean_loss_ratios),
Node('covLRs', {}, vf.covs)]
return Node(
'vulnerabilityFunc... | python | def build_vf_node(vf):
"""
Convert a VulnerabilityFunction object into a Node suitable
for XML conversion.
"""
nodes = [Node('imls', {'imt': vf.imt}, vf.imls),
Node('meanLRs', {}, vf.mean_loss_ratios),
Node('covLRs', {}, vf.covs)]
return Node(
'vulnerabilityFunc... | [
"def",
"build_vf_node",
"(",
"vf",
")",
":",
"nodes",
"=",
"[",
"Node",
"(",
"'imls'",
",",
"{",
"'imt'",
":",
"vf",
".",
"imt",
"}",
",",
"vf",
".",
"imls",
")",
",",
"Node",
"(",
"'meanLRs'",
",",
"{",
"}",
",",
"vf",
".",
"mean_loss_ratios",
... | Convert a VulnerabilityFunction object into a Node suitable
for XML conversion. | [
"Convert",
"a",
"VulnerabilityFunction",
"object",
"into",
"a",
"Node",
"suitable",
"for",
"XML",
"conversion",
"."
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/risklib/riskmodels.py#L69-L79 | train |
gem/oq-engine | openquake/risklib/riskmodels.py | get_riskmodel | def get_riskmodel(taxonomy, oqparam, **extra):
"""
Return an instance of the correct riskmodel class, depending on the
attribute `calculation_mode` of the object `oqparam`.
:param taxonomy:
a taxonomy string
:param oqparam:
an object containing the parameters needed by the riskmodel... | python | def get_riskmodel(taxonomy, oqparam, **extra):
"""
Return an instance of the correct riskmodel class, depending on the
attribute `calculation_mode` of the object `oqparam`.
:param taxonomy:
a taxonomy string
:param oqparam:
an object containing the parameters needed by the riskmodel... | [
"def",
"get_riskmodel",
"(",
"taxonomy",
",",
"oqparam",
",",
"**",
"extra",
")",
":",
"riskmodel_class",
"=",
"registry",
"[",
"oqparam",
".",
"calculation_mode",
"]",
"argnames",
"=",
"inspect",
".",
"getfullargspec",
"(",
"riskmodel_class",
".",
"__init__",
... | Return an instance of the correct riskmodel class, depending on the
attribute `calculation_mode` of the object `oqparam`.
:param taxonomy:
a taxonomy string
:param oqparam:
an object containing the parameters needed by the riskmodel class
:param extra:
extra parameters to pass t... | [
"Return",
"an",
"instance",
"of",
"the",
"correct",
"riskmodel",
"class",
"depending",
"on",
"the",
"attribute",
"calculation_mode",
"of",
"the",
"object",
"oqparam",
"."
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/risklib/riskmodels.py#L548-L580 | train |
gem/oq-engine | openquake/hmtk/plotting/beachball.py | Beachball | def Beachball(fm, linewidth=2, facecolor='b', bgcolor='w', edgecolor='k',
alpha=1.0, xy=(0, 0), width=200, size=100, nofill=False,
zorder=100, outfile=None, format=None, fig=None):
"""
Draws a beach ball diagram of an earthquake focal mechanism.
S1, D1, and R1, the strike, dip a... | python | def Beachball(fm, linewidth=2, facecolor='b', bgcolor='w', edgecolor='k',
alpha=1.0, xy=(0, 0), width=200, size=100, nofill=False,
zorder=100, outfile=None, format=None, fig=None):
"""
Draws a beach ball diagram of an earthquake focal mechanism.
S1, D1, and R1, the strike, dip a... | [
"def",
"Beachball",
"(",
"fm",
",",
"linewidth",
"=",
"2",
",",
"facecolor",
"=",
"'b'",
",",
"bgcolor",
"=",
"'w'",
",",
"edgecolor",
"=",
"'k'",
",",
"alpha",
"=",
"1.0",
",",
"xy",
"=",
"(",
"0",
",",
"0",
")",
",",
"width",
"=",
"200",
",",... | Draws a beach ball diagram of an earthquake focal mechanism.
S1, D1, and R1, the strike, dip and rake of one of the focal planes, can
be vectors of multiple focal mechanisms.
:param fm: Focal mechanism that is either number of mechanisms (NM) by 3
(strike, dip, and rake) or NM x 6 (M11, M22, M33, ... | [
"Draws",
"a",
"beach",
"ball",
"diagram",
"of",
"an",
"earthquake",
"focal",
"mechanism",
"."
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/hmtk/plotting/beachball.py#L147-L230 | train |
gem/oq-engine | openquake/hmtk/plotting/beachball.py | StrikeDip | def StrikeDip(n, e, u):
"""
Finds strike and dip of plane given normal vector having components n, e,
and u.
Adapted from MATLAB script
`bb.m <http://www.ceri.memphis.edu/people/olboyd/Software/Software.html>`_
written by Andy Michael and Oliver Boyd.
"""
r2d = 180 / np.pi
if u < 0:... | python | def StrikeDip(n, e, u):
"""
Finds strike and dip of plane given normal vector having components n, e,
and u.
Adapted from MATLAB script
`bb.m <http://www.ceri.memphis.edu/people/olboyd/Software/Software.html>`_
written by Andy Michael and Oliver Boyd.
"""
r2d = 180 / np.pi
if u < 0:... | [
"def",
"StrikeDip",
"(",
"n",
",",
"e",
",",
"u",
")",
":",
"r2d",
"=",
"180",
"/",
"np",
".",
"pi",
"if",
"u",
"<",
"0",
":",
"n",
"=",
"-",
"n",
"e",
"=",
"-",
"e",
"u",
"=",
"-",
"u",
"strike",
"=",
"np",
".",
"arctan2",
"(",
"e",
... | Finds strike and dip of plane given normal vector having components n, e,
and u.
Adapted from MATLAB script
`bb.m <http://www.ceri.memphis.edu/people/olboyd/Software/Software.html>`_
written by Andy Michael and Oliver Boyd. | [
"Finds",
"strike",
"and",
"dip",
"of",
"plane",
"given",
"normal",
"vector",
"having",
"components",
"n",
"e",
"and",
"u",
"."
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/hmtk/plotting/beachball.py#L669-L692 | train |
gem/oq-engine | openquake/hmtk/plotting/beachball.py | AuxPlane | def AuxPlane(s1, d1, r1):
"""
Get Strike and dip of second plane.
Adapted from MATLAB script
`bb.m <http://www.ceri.memphis.edu/people/olboyd/Software/Software.html>`_
written by Andy Michael and Oliver Boyd.
"""
r2d = 180 / np.pi
z = (s1 + 90) / r2d
z2 = d1 / r2d
z3 = r1 / r2d... | python | def AuxPlane(s1, d1, r1):
"""
Get Strike and dip of second plane.
Adapted from MATLAB script
`bb.m <http://www.ceri.memphis.edu/people/olboyd/Software/Software.html>`_
written by Andy Michael and Oliver Boyd.
"""
r2d = 180 / np.pi
z = (s1 + 90) / r2d
z2 = d1 / r2d
z3 = r1 / r2d... | [
"def",
"AuxPlane",
"(",
"s1",
",",
"d1",
",",
"r1",
")",
":",
"r2d",
"=",
"180",
"/",
"np",
".",
"pi",
"z",
"=",
"(",
"s1",
"+",
"90",
")",
"/",
"r2d",
"z2",
"=",
"d1",
"/",
"r2d",
"z3",
"=",
"r1",
"/",
"r2d",
"sl1",
"=",
"-",
"np",
"."... | Get Strike and dip of second plane.
Adapted from MATLAB script
`bb.m <http://www.ceri.memphis.edu/people/olboyd/Software/Software.html>`_
written by Andy Michael and Oliver Boyd. | [
"Get",
"Strike",
"and",
"dip",
"of",
"second",
"plane",
"."
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/hmtk/plotting/beachball.py#L695-L729 | train |
gem/oq-engine | openquake/hmtk/plotting/beachball.py | MT2Plane | def MT2Plane(mt):
"""
Calculates a nodal plane of a given moment tensor.
:param mt: :class:`~MomentTensor`
:return: :class:`~NodalPlane`
Adapted from MATLAB script
`bb.m <http://www.ceri.memphis.edu/people/olboyd/Software/Software.html>`_
written by Andy Michael and Oliver Boyd.
"""
... | python | def MT2Plane(mt):
"""
Calculates a nodal plane of a given moment tensor.
:param mt: :class:`~MomentTensor`
:return: :class:`~NodalPlane`
Adapted from MATLAB script
`bb.m <http://www.ceri.memphis.edu/people/olboyd/Software/Software.html>`_
written by Andy Michael and Oliver Boyd.
"""
... | [
"def",
"MT2Plane",
"(",
"mt",
")",
":",
"(",
"d",
",",
"v",
")",
"=",
"np",
".",
"linalg",
".",
"eig",
"(",
"mt",
".",
"mt",
")",
"D",
"=",
"np",
".",
"array",
"(",
"[",
"d",
"[",
"1",
"]",
",",
"d",
"[",
"0",
"]",
",",
"d",
"[",
"2",... | Calculates a nodal plane of a given moment tensor.
:param mt: :class:`~MomentTensor`
:return: :class:`~NodalPlane`
Adapted from MATLAB script
`bb.m <http://www.ceri.memphis.edu/people/olboyd/Software/Software.html>`_
written by Andy Michael and Oliver Boyd. | [
"Calculates",
"a",
"nodal",
"plane",
"of",
"a",
"given",
"moment",
"tensor",
"."
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/hmtk/plotting/beachball.py#L732-L766 | train |
gem/oq-engine | openquake/hmtk/plotting/beachball.py | TDL | def TDL(AN, BN):
"""
Helper function for MT2Plane.
Adapted from MATLAB script
`bb.m <http://www.ceri.memphis.edu/people/olboyd/Software/Software.html>`_
written by Andy Michael and Oliver Boyd.
"""
XN = AN[0]
YN = AN[1]
ZN = AN[2]
XE = BN[0]
YE = BN[1]
ZE = BN[2]
AAA... | python | def TDL(AN, BN):
"""
Helper function for MT2Plane.
Adapted from MATLAB script
`bb.m <http://www.ceri.memphis.edu/people/olboyd/Software/Software.html>`_
written by Andy Michael and Oliver Boyd.
"""
XN = AN[0]
YN = AN[1]
ZN = AN[2]
XE = BN[0]
YE = BN[1]
ZE = BN[2]
AAA... | [
"def",
"TDL",
"(",
"AN",
",",
"BN",
")",
":",
"XN",
"=",
"AN",
"[",
"0",
"]",
"YN",
"=",
"AN",
"[",
"1",
"]",
"ZN",
"=",
"AN",
"[",
"2",
"]",
"XE",
"=",
"BN",
"[",
"0",
"]",
"YE",
"=",
"BN",
"[",
"1",
"]",
"ZE",
"=",
"BN",
"[",
"2",... | Helper function for MT2Plane.
Adapted from MATLAB script
`bb.m <http://www.ceri.memphis.edu/people/olboyd/Software/Software.html>`_
written by Andy Michael and Oliver Boyd. | [
"Helper",
"function",
"for",
"MT2Plane",
"."
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/hmtk/plotting/beachball.py#L769-L849 | train |
gem/oq-engine | openquake/hmtk/plotting/beachball.py | MT2Axes | def MT2Axes(mt):
"""
Calculates the principal axes of a given moment tensor.
:param mt: :class:`~MomentTensor`
:return: tuple of :class:`~PrincipalAxis` T, N and P
Adapted from ps_tensor / utilmeca.c /
`Generic Mapping Tools (GMT) <http://gmt.soest.hawaii.edu>`_.
"""
(D, V) = np.linalg... | python | def MT2Axes(mt):
"""
Calculates the principal axes of a given moment tensor.
:param mt: :class:`~MomentTensor`
:return: tuple of :class:`~PrincipalAxis` T, N and P
Adapted from ps_tensor / utilmeca.c /
`Generic Mapping Tools (GMT) <http://gmt.soest.hawaii.edu>`_.
"""
(D, V) = np.linalg... | [
"def",
"MT2Axes",
"(",
"mt",
")",
":",
"(",
"D",
",",
"V",
")",
"=",
"np",
".",
"linalg",
".",
"eigh",
"(",
"mt",
".",
"mt",
")",
"pl",
"=",
"np",
".",
"arcsin",
"(",
"-",
"V",
"[",
"0",
"]",
")",
"az",
"=",
"np",
".",
"arctan2",
"(",
"... | Calculates the principal axes of a given moment tensor.
:param mt: :class:`~MomentTensor`
:return: tuple of :class:`~PrincipalAxis` T, N and P
Adapted from ps_tensor / utilmeca.c /
`Generic Mapping Tools (GMT) <http://gmt.soest.hawaii.edu>`_. | [
"Calculates",
"the",
"principal",
"axes",
"of",
"a",
"given",
"moment",
"tensor",
"."
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/hmtk/plotting/beachball.py#L852-L879 | train |
gem/oq-engine | openquake/hmtk/strain/strain_utils.py | tapered_gutenberg_richter_cdf | def tapered_gutenberg_richter_cdf(moment, moment_threshold, beta,
corner_moment):
'''
Tapered Gutenberg Richter Cumulative Density Function
:param float or numpy.ndarray moment:
Moment for calculation of rate
:param float or numpy.ndarray moment_threshold:
... | python | def tapered_gutenberg_richter_cdf(moment, moment_threshold, beta,
corner_moment):
'''
Tapered Gutenberg Richter Cumulative Density Function
:param float or numpy.ndarray moment:
Moment for calculation of rate
:param float or numpy.ndarray moment_threshold:
... | [
"def",
"tapered_gutenberg_richter_cdf",
"(",
"moment",
",",
"moment_threshold",
",",
"beta",
",",
"corner_moment",
")",
":",
"cdf",
"=",
"np",
".",
"exp",
"(",
"(",
"moment_threshold",
"-",
"moment",
")",
"/",
"corner_moment",
")",
"return",
"(",
"(",
"momen... | Tapered Gutenberg Richter Cumulative Density Function
:param float or numpy.ndarray moment:
Moment for calculation of rate
:param float or numpy.ndarray moment_threshold:
Threshold Moment of the distribution (moment rate essentially!)
:param float beta:
Beta value (b * ln(10.)) of... | [
"Tapered",
"Gutenberg",
"Richter",
"Cumulative",
"Density",
"Function"
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/hmtk/strain/strain_utils.py#L111-L134 | train |
gem/oq-engine | openquake/hmtk/strain/strain_utils.py | tapered_gutenberg_richter_pdf | def tapered_gutenberg_richter_pdf(moment, moment_threshold, beta,
corner_moment):
'''
Tapered Gutenberg-Richter Probability Density Function
:param float or numpy.ndarray moment:
Moment for calculation of rate
:param float or numpy.ndarray moment_threshold:
... | python | def tapered_gutenberg_richter_pdf(moment, moment_threshold, beta,
corner_moment):
'''
Tapered Gutenberg-Richter Probability Density Function
:param float or numpy.ndarray moment:
Moment for calculation of rate
:param float or numpy.ndarray moment_threshold:
... | [
"def",
"tapered_gutenberg_richter_pdf",
"(",
"moment",
",",
"moment_threshold",
",",
"beta",
",",
"corner_moment",
")",
":",
"return",
"(",
"(",
"beta",
"/",
"moment",
"+",
"1.",
"/",
"corner_moment",
")",
"*",
"tapered_gutenberg_richter_cdf",
"(",
"moment",
","... | Tapered Gutenberg-Richter Probability Density Function
:param float or numpy.ndarray moment:
Moment for calculation of rate
:param float or numpy.ndarray moment_threshold:
Threshold Moment of the distribution (moment rate essentially!)
:param float beta:
Beta value (b * ln(10.)) o... | [
"Tapered",
"Gutenberg",
"-",
"Richter",
"Probability",
"Density",
"Function"
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/hmtk/strain/strain_utils.py#L137-L159 | train |
gem/oq-engine | openquake/engine/export/core.py | makedirs | def makedirs(path):
"""
Make all of the directories in the ``path`` using `os.makedirs`.
"""
if os.path.exists(path):
if not os.path.isdir(path):
# If it's not a directory, we can't do anything.
# This is a problem
raise RuntimeError('%s already exists and is ... | python | def makedirs(path):
"""
Make all of the directories in the ``path`` using `os.makedirs`.
"""
if os.path.exists(path):
if not os.path.isdir(path):
# If it's not a directory, we can't do anything.
# This is a problem
raise RuntimeError('%s already exists and is ... | [
"def",
"makedirs",
"(",
"path",
")",
":",
"if",
"os",
".",
"path",
".",
"exists",
"(",
"path",
")",
":",
"if",
"not",
"os",
".",
"path",
".",
"isdir",
"(",
"path",
")",
":",
"raise",
"RuntimeError",
"(",
"'%s already exists and is not a directory.'",
"%"... | Make all of the directories in the ``path`` using `os.makedirs`. | [
"Make",
"all",
"of",
"the",
"directories",
"in",
"the",
"path",
"using",
"os",
".",
"makedirs",
"."
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/engine/export/core.py#L80-L91 | train |
gem/oq-engine | openquake/hmtk/seismicity/max_magnitude/base.py | _get_observed_mmax | def _get_observed_mmax(catalogue, config):
'''Check see if observed mmax values are input, if not then take
from the catalogue'''
if config['input_mmax']:
obsmax = config['input_mmax']
if config['input_mmax_uncertainty']:
return config['input_mmax'], config['input_mmax_uncertaint... | python | def _get_observed_mmax(catalogue, config):
'''Check see if observed mmax values are input, if not then take
from the catalogue'''
if config['input_mmax']:
obsmax = config['input_mmax']
if config['input_mmax_uncertainty']:
return config['input_mmax'], config['input_mmax_uncertaint... | [
"def",
"_get_observed_mmax",
"(",
"catalogue",
",",
"config",
")",
":",
"if",
"config",
"[",
"'input_mmax'",
"]",
":",
"obsmax",
"=",
"config",
"[",
"'input_mmax'",
"]",
"if",
"config",
"[",
"'input_mmax_uncertainty'",
"]",
":",
"return",
"config",
"[",
"'in... | Check see if observed mmax values are input, if not then take
from the catalogue | [
"Check",
"see",
"if",
"observed",
"mmax",
"values",
"are",
"input",
"if",
"not",
"then",
"take",
"from",
"the",
"catalogue"
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/hmtk/seismicity/max_magnitude/base.py#L57-L83 | train |
gem/oq-engine | openquake/hmtk/seismicity/max_magnitude/base.py | _get_magnitude_vector_properties | def _get_magnitude_vector_properties(catalogue, config):
'''If an input minimum magnitude is given then consider catalogue
only above the minimum magnitude - returns corresponding properties'''
mmin = config.get('input_mmin', np.min(catalogue['magnitude']))
neq = np.float(np.sum(catalogue['magnitude'] ... | python | def _get_magnitude_vector_properties(catalogue, config):
'''If an input minimum magnitude is given then consider catalogue
only above the minimum magnitude - returns corresponding properties'''
mmin = config.get('input_mmin', np.min(catalogue['magnitude']))
neq = np.float(np.sum(catalogue['magnitude'] ... | [
"def",
"_get_magnitude_vector_properties",
"(",
"catalogue",
",",
"config",
")",
":",
"mmin",
"=",
"config",
".",
"get",
"(",
"'input_mmin'",
",",
"np",
".",
"min",
"(",
"catalogue",
"[",
"'magnitude'",
"]",
")",
")",
"neq",
"=",
"np",
".",
"float",
"(",... | If an input minimum magnitude is given then consider catalogue
only above the minimum magnitude - returns corresponding properties | [
"If",
"an",
"input",
"minimum",
"magnitude",
"is",
"given",
"then",
"consider",
"catalogue",
"only",
"above",
"the",
"minimum",
"magnitude",
"-",
"returns",
"corresponding",
"properties"
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/hmtk/seismicity/max_magnitude/base.py#L104-L110 | train |
gem/oq-engine | openquake/hazardlib/geo/surface/complex_fault.py | ComplexFaultSurface.get_dip | def get_dip(self):
"""
Return the fault dip as the average dip over the mesh.
The average dip is defined as the weighted mean inclination
of all the mesh cells. See
:meth:`openquake.hazardlib.geo.mesh.RectangularMesh.get_mean_inclination_and_azimuth`
:returns:
... | python | def get_dip(self):
"""
Return the fault dip as the average dip over the mesh.
The average dip is defined as the weighted mean inclination
of all the mesh cells. See
:meth:`openquake.hazardlib.geo.mesh.RectangularMesh.get_mean_inclination_and_azimuth`
:returns:
... | [
"def",
"get_dip",
"(",
"self",
")",
":",
"if",
"self",
".",
"dip",
"is",
"None",
":",
"mesh",
"=",
"self",
".",
"mesh",
"self",
".",
"dip",
",",
"self",
".",
"strike",
"=",
"mesh",
".",
"get_mean_inclination_and_azimuth",
"(",
")",
"return",
"self",
... | Return the fault dip as the average dip over the mesh.
The average dip is defined as the weighted mean inclination
of all the mesh cells. See
:meth:`openquake.hazardlib.geo.mesh.RectangularMesh.get_mean_inclination_and_azimuth`
:returns:
The average dip, in decimal degrees. | [
"Return",
"the",
"fault",
"dip",
"as",
"the",
"average",
"dip",
"over",
"the",
"mesh",
"."
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/hazardlib/geo/surface/complex_fault.py#L96-L111 | train |
gem/oq-engine | openquake/hazardlib/geo/surface/complex_fault.py | ComplexFaultSurface.check_surface_validity | def check_surface_validity(cls, edges):
"""
Check validity of the surface.
Project edge points to vertical plane anchored to surface upper left
edge and with strike equal to top edge strike. Check that resulting
polygon is valid.
This method doesn't have to be called by... | python | def check_surface_validity(cls, edges):
"""
Check validity of the surface.
Project edge points to vertical plane anchored to surface upper left
edge and with strike equal to top edge strike. Check that resulting
polygon is valid.
This method doesn't have to be called by... | [
"def",
"check_surface_validity",
"(",
"cls",
",",
"edges",
")",
":",
"full_boundary",
"=",
"[",
"]",
"left_boundary",
"=",
"[",
"]",
"right_boundary",
"=",
"[",
"]",
"for",
"i",
"in",
"range",
"(",
"1",
",",
"len",
"(",
"edges",
")",
"-",
"1",
")",
... | Check validity of the surface.
Project edge points to vertical plane anchored to surface upper left
edge and with strike equal to top edge strike. Check that resulting
polygon is valid.
This method doesn't have to be called by hands before creating the
surface object, because i... | [
"Check",
"validity",
"of",
"the",
"surface",
"."
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/hazardlib/geo/surface/complex_fault.py#L182-L230 | train |
gem/oq-engine | openquake/hazardlib/geo/surface/complex_fault.py | ComplexFaultSurface.surface_projection_from_fault_data | def surface_projection_from_fault_data(cls, edges):
"""
Get a surface projection of the complex fault surface.
:param edges:
A list of horizontal edges of the surface as instances
of :class:`openquake.hazardlib.geo.line.Line`.
:returns:
Instance of :c... | python | def surface_projection_from_fault_data(cls, edges):
"""
Get a surface projection of the complex fault surface.
:param edges:
A list of horizontal edges of the surface as instances
of :class:`openquake.hazardlib.geo.line.Line`.
:returns:
Instance of :c... | [
"def",
"surface_projection_from_fault_data",
"(",
"cls",
",",
"edges",
")",
":",
"lons",
"=",
"[",
"]",
"lats",
"=",
"[",
"]",
"for",
"edge",
"in",
"edges",
":",
"for",
"point",
"in",
"edge",
":",
"lons",
".",
"append",
"(",
"point",
".",
"longitude",
... | Get a surface projection of the complex fault surface.
:param edges:
A list of horizontal edges of the surface as instances
of :class:`openquake.hazardlib.geo.line.Line`.
:returns:
Instance of :class:`~openquake.hazardlib.geo.polygon.Polygon`
describing t... | [
"Get",
"a",
"surface",
"projection",
"of",
"the",
"complex",
"fault",
"surface",
"."
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/hazardlib/geo/surface/complex_fault.py#L302-L323 | train |
gem/oq-engine | openquake/calculators/base.py | check_time_event | def check_time_event(oqparam, occupancy_periods):
"""
Check the `time_event` parameter in the datastore, by comparing
with the periods found in the exposure.
"""
time_event = oqparam.time_event
if time_event and time_event not in occupancy_periods:
raise ValueError(
'time_eve... | python | def check_time_event(oqparam, occupancy_periods):
"""
Check the `time_event` parameter in the datastore, by comparing
with the periods found in the exposure.
"""
time_event = oqparam.time_event
if time_event and time_event not in occupancy_periods:
raise ValueError(
'time_eve... | [
"def",
"check_time_event",
"(",
"oqparam",
",",
"occupancy_periods",
")",
":",
"time_event",
"=",
"oqparam",
".",
"time_event",
"if",
"time_event",
"and",
"time_event",
"not",
"in",
"occupancy_periods",
":",
"raise",
"ValueError",
"(",
"'time_event is %s in %s, but th... | Check the `time_event` parameter in the datastore, by comparing
with the periods found in the exposure. | [
"Check",
"the",
"time_event",
"parameter",
"in",
"the",
"datastore",
"by",
"comparing",
"with",
"the",
"periods",
"found",
"in",
"the",
"exposure",
"."
] | 8294553a0b8aba33fd96437a35065d03547d0040 | https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/calculators/base.py#L321-L331 | train |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.