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pkgw/pwkit | pwkit/environments/casa/tasks.py | importevla | def importevla(asdm, ms):
"""Convert an EVLA low-level SDM dataset to Measurement Set format.
asdm (str)
The path to the input ASDM dataset.
ms (str)
The path to the output MS dataset.
This implementation automatically infers the value of the "tbuff"
parameter.
Example::
fr... | python | def importevla(asdm, ms):
"""Convert an EVLA low-level SDM dataset to Measurement Set format.
asdm (str)
The path to the input ASDM dataset.
ms (str)
The path to the output MS dataset.
This implementation automatically infers the value of the "tbuff"
parameter.
Example::
fr... | [
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pkgw/pwkit | pwkit/environments/casa/tasks.py | listobs | def listobs(vis):
"""Textually describe the contents of a measurement set.
vis (str)
The path to the dataset.
Returns
A generator of lines of human-readable output
Errors can only be detected by looking at the output. Example::
from pwkit.environments.casa import tasks
for li... | python | def listobs(vis):
"""Textually describe the contents of a measurement set.
vis (str)
The path to the dataset.
Returns
A generator of lines of human-readable output
Errors can only be detected by looking at the output. Example::
from pwkit.environments.casa import tasks
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pkgw/pwkit | pwkit/environments/casa/tasks.py | mjd2date | def mjd2date(mjd, precision=3):
"""Convert an MJD to a data string in the format used by CASA.
mjd (numeric)
An MJD value in the UTC timescale.
precision (integer, default 3)
The number of digits of decimal precision in the seconds portion of
the returned string
Returns
A string... | python | def mjd2date(mjd, precision=3):
"""Convert an MJD to a data string in the format used by CASA.
mjd (numeric)
An MJD value in the UTC timescale.
precision (integer, default 3)
The number of digits of decimal precision in the seconds portion of
the returned string
Returns
A string... | [
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pkgw/pwkit | pwkit/environments/casa/tasks.py | plotants | def plotants(vis, figfile):
"""Plot the physical layout of the antennas described in the MS.
vis (str)
Path to the input dataset
figfile (str)
Path to the output image file.
The output image format will be inferred from the extension of *figfile*.
Example::
from pwkit.environmen... | python | def plotants(vis, figfile):
"""Plot the physical layout of the antennas described in the MS.
vis (str)
Path to the input dataset
figfile (str)
Path to the output image file.
The output image format will be inferred from the extension of *figfile*.
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pkgw/pwkit | pwkit/latex.py | latexify | def latexify(obj, **kwargs):
"""Render an object in LaTeX appropriately.
"""
if hasattr(obj, '__pk_latex__'):
return obj.__pk_latex__(**kwargs)
if isinstance(obj, text_type):
from .unicode_to_latex import unicode_to_latex
return unicode_to_latex(obj)
if isinstance(obj, boo... | python | def latexify(obj, **kwargs):
"""Render an object in LaTeX appropriately.
"""
if hasattr(obj, '__pk_latex__'):
return obj.__pk_latex__(**kwargs)
if isinstance(obj, text_type):
from .unicode_to_latex import unicode_to_latex
return unicode_to_latex(obj)
if isinstance(obj, boo... | [
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pkgw/pwkit | pwkit/latex.py | latexify_n2col | def latexify_n2col(x, nplaces=None, **kwargs):
"""Render a number into LaTeX in a 2-column format, where the columns split
immediately to the left of the decimal point. This gives nice alignment of
numbers in a table.
"""
if nplaces is not None:
t = '%.*f' % (nplaces, x)
else:
t... | python | def latexify_n2col(x, nplaces=None, **kwargs):
"""Render a number into LaTeX in a 2-column format, where the columns split
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pkgw/pwkit | pwkit/latex.py | latexify_u3col | def latexify_u3col(obj, **kwargs):
"""Convert an object to special LaTeX for uncertainty tables.
This conversion is meant for uncertain values in a table. The return value
should span three columns. The first column ends just before the decimal
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pkgw/pwkit | pwkit/latex.py | latexify_l3col | def latexify_l3col(obj, **kwargs):
"""Convert an object to special LaTeX for limit tables.
This conversion is meant for limit values in a table. The return value
should span three columns. The first column is the limit indicator: <, >,
~, etc. The second column is the whole part of the value, up until ... | python | def latexify_l3col(obj, **kwargs):
"""Convert an object to special LaTeX for limit tables.
This conversion is meant for limit values in a table. The return value
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pkgw/pwkit | pwkit/tabfile.py | read | def read (path, tabwidth=8, **kwargs):
"""Read a typed tabular text file into a stream of Holders.
Arguments:
path
The path of the file to read.
tabwidth=8
The tab width to assume. Please don't monkey with it.
mode='rt'
The file open mode (passed to io.open()).
noexistok=Fals... | python | def read (path, tabwidth=8, **kwargs):
"""Read a typed tabular text file into a stream of Holders.
Arguments:
path
The path of the file to read.
tabwidth=8
The tab width to assume. Please don't monkey with it.
mode='rt'
The file open mode (passed to io.open()).
noexistok=Fals... | [
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pkgw/pwkit | pwkit/tabfile.py | write | def write (stream, items, fieldnames, tabwidth=8):
"""Write a typed tabular text file to the specified stream.
Arguments:
stream
The destination stream.
items
An iterable of items to write. Two passes have to
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so thi... | python | def write (stream, items, fieldnames, tabwidth=8):
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The destination stream.
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pkgw/pwkit | pwkit/tabfile.py | vizread | def vizread (descpath, descsection, tabpath, tabwidth=8, **kwargs):
"""Read a headerless tabular text file into a stream of Holders.
Arguments:
descpath
The path of the table description ini file.
descsection
The section in the description file to use.
tabpath
The path to the act... | python | def vizread (descpath, descsection, tabpath, tabwidth=8, **kwargs):
"""Read a headerless tabular text file into a stream of Holders.
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descpath
The path of the table description ini file.
descsection
The section in the description file to use.
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pkgw/pwkit | pwkit/lsqmdl.py | _broadcast_shapes | def _broadcast_shapes(s1, s2):
"""Given array shapes `s1` and `s2`, compute the shape of the array that would
result from broadcasting them together."""
n1 = len(s1)
n2 = len(s2)
n = max(n1, n2)
res = [1] * n
for i in range(n):
if i >= n1:
c1 = 1
else:
... | python | def _broadcast_shapes(s1, s2):
"""Given array shapes `s1` and `s2`, compute the shape of the array that would
result from broadcasting them together."""
n1 = len(s1)
n2 = len(s2)
n = max(n1, n2)
res = [1] * n
for i in range(n):
if i >= n1:
c1 = 1
else:
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pkgw/pwkit | pwkit/lsqmdl.py | ModelBase.set_data | def set_data(self, data, invsigma=None):
"""Set the data to be modeled.
Returns *self*.
"""
self.data = np.array(data, dtype=np.float, ndmin=1)
if invsigma is None:
self.invsigma = np.ones(self.data.shape)
else:
i = np.array(invsigma, dtype=np.f... | python | def set_data(self, data, invsigma=None):
"""Set the data to be modeled.
Returns *self*.
"""
self.data = np.array(data, dtype=np.float, ndmin=1)
if invsigma is None:
self.invsigma = np.ones(self.data.shape)
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pkgw/pwkit | pwkit/lsqmdl.py | ModelBase.print_soln | def print_soln(self):
"""Print information about the model solution."""
lmax = reduce(max,(len(x) for x in self.pnames), len('r chi sq'))
if self.puncerts is None:
for pn, val in zip(self.pnames, self.params):
print('%s: %14g' % (pn.rjust(lmax), val))
else:
... | python | def print_soln(self):
"""Print information about the model solution."""
lmax = reduce(max,(len(x) for x in self.pnames), len('r chi sq'))
if self.puncerts is None:
for pn, val in zip(self.pnames, self.params):
print('%s: %14g' % (pn.rjust(lmax), val))
else:
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pkgw/pwkit | pwkit/lsqmdl.py | ModelBase.show_corr | def show_corr(self):
"Show the parameter correlation matrix with `pwkit.ndshow_gtk3`."
from .ndshow_gtk3 import view
d = np.diag(self.covar) ** -0.5
corr = self.covar * d[np.newaxis,:] * d[:,np.newaxis]
view(corr, title='Correlation Matrix') | python | def show_corr(self):
"Show the parameter correlation matrix with `pwkit.ndshow_gtk3`."
from .ndshow_gtk3 import view
d = np.diag(self.covar) ** -0.5
corr = self.covar * d[np.newaxis,:] * d[:,np.newaxis]
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pkgw/pwkit | pwkit/lsqmdl.py | Model.set_func | def set_func(self, func, pnames, args=()):
"""Set the model function to use an efficient but tedious calling convention.
The function should obey the following convention::
def func(param_vec, *args):
modeled_data = { do something using param_vec }
return mo... | python | def set_func(self, func, pnames, args=()):
"""Set the model function to use an efficient but tedious calling convention.
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modeled_data = { do something using param_vec }
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pkgw/pwkit | pwkit/lsqmdl.py | Model.set_simple_func | def set_simple_func(self, func, args=()):
"""Set the model function to use a simple but somewhat inefficient calling
convention.
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def func(param0, param1, ..., paramN, *args):
modeled_data = { do something using the... | python | def set_simple_func(self, func, args=()):
"""Set the model function to use a simple but somewhat inefficient calling
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pkgw/pwkit | pwkit/lsqmdl.py | Model.make_frozen_func | def make_frozen_func(self, params):
"""Returns a model function frozen to the specified parameter values.
Any remaining arguments are left free and must be provided when the
function is called.
For this model, the returned function is the application of
:func:`functools.partial... | python | def make_frozen_func(self, params):
"""Returns a model function frozen to the specified parameter values.
Any remaining arguments are left free and must be provided when the
function is called.
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pkgw/pwkit | pwkit/lsqmdl.py | Model.solve | def solve(self, guess):
"""Solve for the parameters, using an initial guess.
This uses the Levenberg-Marquardt optimizer described in
:mod:`pwkit.lmmin`.
Returns *self*.
"""
guess = np.array(guess, dtype=np.float, ndmin=1)
f = self.func
args = self._arg... | python | def solve(self, guess):
"""Solve for the parameters, using an initial guess.
This uses the Levenberg-Marquardt optimizer described in
:mod:`pwkit.lmmin`.
Returns *self*.
"""
guess = np.array(guess, dtype=np.float, ndmin=1)
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pkgw/pwkit | pwkit/lsqmdl.py | PolynomialModel.as_nonlinear | def as_nonlinear(self, params=None):
"""Return a `Model` equivalent to this object. The nonlinear solver is less
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If the `params` argument is provided, solve() will be called on the
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bibanon/BASC-py4chan | basc_py4chan/thread.py | Thread.files | def files(self):
"""Returns the URLs of all files attached to posts in the thread."""
if self.topic.has_file:
yield self.topic.file.file_url
for reply in self.replies:
if reply.has_file:
yield reply.file.file_url | python | def files(self):
"""Returns the URLs of all files attached to posts in the thread."""
if self.topic.has_file:
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bibanon/BASC-py4chan | basc_py4chan/thread.py | Thread.thumbs | def thumbs(self):
"""Returns the URLs of all thumbnails in the thread."""
if self.topic.has_file:
yield self.topic.file.thumbnail_url
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if reply.has_file:
yield reply.file.thumbnail_url | python | def thumbs(self):
"""Returns the URLs of all thumbnails in the thread."""
if self.topic.has_file:
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bibanon/BASC-py4chan | basc_py4chan/thread.py | Thread.filenames | def filenames(self):
"""Returns the filenames of all files attached to posts in the thread."""
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yield self.topic.file.filename
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yield reply.file.filename | python | def filenames(self):
"""Returns the filenames of all files attached to posts in the thread."""
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bibanon/BASC-py4chan | basc_py4chan/thread.py | Thread.thumbnames | def thumbnames(self):
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bibanon/BASC-py4chan | basc_py4chan/thread.py | Thread.update | def update(self, force=False):
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force (bool): Force a thread update, even if thread has 404'd.
Returns:
int: How many new posts have been fetched.
"""
# The thread has already 404'ed, this function shouldn't... | python | def update(self, force=False):
"""Fetch new posts from the server.
Arguments:
force (bool): Force a thread update, even if thread has 404'd.
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int: How many new posts have been fetched.
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pkgw/pwkit | pwkit/radio_cal_models.py | cas_a | def cas_a (freq_mhz, year):
"""Return the flux of Cas A given a frequency and the year of observation.
Based on the formula given in Baars et al., 1977.
Parameters:
freq - Observation frequency in MHz.
year - Year of observation. May be floating-point.
Returns: s, flux in Jy.
"""
# T... | python | def cas_a (freq_mhz, year):
"""Return the flux of Cas A given a frequency and the year of observation.
Based on the formula given in Baars et al., 1977.
Parameters:
freq - Observation frequency in MHz.
year - Year of observation. May be floating-point.
Returns: s, flux in Jy.
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pkgw/pwkit | pwkit/radio_cal_models.py | init_cas_a | def init_cas_a (year):
"""Insert an entry for Cas A into the table of models. Need to specify the
year of the observations to account for the time variation of Cas A's
emission.
"""
year = float (year)
models['CasA'] = lambda f: cas_a (f, year) | python | def init_cas_a (year):
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year of the observations to account for the time variation of Cas A's
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"""
year = float (year)
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pkgw/pwkit | pwkit/radio_cal_models.py | add_from_vla_obs | def add_from_vla_obs (src, Lband, Cband):
"""Add an entry into the models table for a source based on L-band and
C-band flux densities.
"""
if src in models:
raise PKError ('already have a model for ' + src)
fL = np.log10 (1425)
fC = np.log10 (4860)
lL = np.log10 (Lband)
lC = ... | python | def add_from_vla_obs (src, Lband, Cband):
"""Add an entry into the models table for a source based on L-band and
C-band flux densities.
"""
if src in models:
raise PKError ('already have a model for ' + src)
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lL = np.log10 (Lband)
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pkgw/pwkit | pwkit/ellipses.py | databiv | def databiv (xy, coordouter=False, **kwargs):
"""Compute the main parameters of a bivariate distribution from data. The
parameters are returned in the same format as used in the rest of this
module.
* xy: a 2D data array of shape (2, nsamp) or (nsamp, 2)
* coordouter: if True, the coordinate axis i... | python | def databiv (xy, coordouter=False, **kwargs):
"""Compute the main parameters of a bivariate distribution from data. The
parameters are returned in the same format as used in the rest of this
module.
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pkgw/pwkit | pwkit/ellipses.py | bivrandom | def bivrandom (x0, y0, sx, sy, cxy, size=None):
"""Compute random values distributed according to the specified bivariate
distribution.
Inputs:
* x0: the center of the x distribution (i.e. its intended mean)
* y0: the center of the y distribution
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"""Compute random values distributed according to the specified bivariate
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* x0: the center of the x distribution (i.e. its intended mean)
* y0: the center of the y distribution
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pkgw/pwkit | pwkit/ellipses.py | bivconvolve | def bivconvolve (sx_a, sy_a, cxy_a, sx_b, sy_b, cxy_b):
"""Given two independent bivariate distributions, compute a bivariate
distribution corresponding to their convolution.
I'm sure this is worked out in a ton of places, but I got the equations
from Pineau+ (2011A&A...527A.126P).
Returns: (sx_c,... | python | def bivconvolve (sx_a, sy_a, cxy_a, sx_b, sy_b, cxy_b):
"""Given two independent bivariate distributions, compute a bivariate
distribution corresponding to their convolution.
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pkgw/pwkit | pwkit/ellipses.py | ellplot | def ellplot (mjr, mnr, pa):
"""Utility for debugging."""
_ellcheck (mjr, mnr, pa)
import omega as om
th = np.linspace (0, 2 * np.pi, 200)
x, y = ellpoint (mjr, mnr, pa, th)
return om.quickXY (x, y, 'mjr=%f mnr=%f pa=%f' %
(mjr, mnr, pa * 180 / np.pi)) | python | def ellplot (mjr, mnr, pa):
"""Utility for debugging."""
_ellcheck (mjr, mnr, pa)
import omega as om
th = np.linspace (0, 2 * np.pi, 200)
x, y = ellpoint (mjr, mnr, pa, th)
return om.quickXY (x, y, 'mjr=%f mnr=%f pa=%f' %
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pkgw/pwkit | pwkit/ellipses.py | abcd2 | def abcd2 (x0, y0, a, b, c, x, y):
"""Given an 2D Gaussian expressed as the ABC polynomial coefficients, compute
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z = exp (-0.5 * d2)
Inputs:
* x0: position of Gaussian center on x axis
* y0: position of Gaussian center on y axis
* a: such that z... | python | def abcd2 (x0, y0, a, b, c, x, y):
"""Given an 2D Gaussian expressed as the ABC polynomial coefficients, compute
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jakevdp/lpproj | lpproj/lpproj.py | eigh_robust | def eigh_robust(a, b=None, eigvals=None, eigvals_only=False,
overwrite_a=False, overwrite_b=False,
turbo=True, check_finite=True):
"""Robustly solve the Hermitian generalized eigenvalue problem
This function robustly solves the Hermetian generalized eigenvalue problem
``A v ... | python | def eigh_robust(a, b=None, eigvals=None, eigvals_only=False,
overwrite_a=False, overwrite_b=False,
turbo=True, check_finite=True):
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jakevdp/lpproj | lpproj/lpproj.py | LocalityPreservingProjection._compute_projection | def _compute_projection(self, X, W):
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W : array_like or sparse matrix, (n_samples, n_samples)
The precomputed adjacency matrix
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"""Compute the LPP projection matrix
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andrenarchy/krypy | krypy/utils.py | find_common_dtype | def find_common_dtype(*args):
'''Returns common dtype of numpy and scipy objects.
Recognizes ndarray, spmatrix and LinearOperator. All other objects are
ignored (most notably None).'''
dtypes = []
for arg in args:
if type(arg) is numpy.ndarray or \
isspmatrix(arg) or \
... | python | def find_common_dtype(*args):
'''Returns common dtype of numpy and scipy objects.
Recognizes ndarray, spmatrix and LinearOperator. All other objects are
ignored (most notably None).'''
dtypes = []
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andrenarchy/krypy | krypy/utils.py | inner | def inner(X, Y, ip_B=None):
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numpy.vdot only works for vectors and numpy.dot does not use the conjugate
transpose.
:param X: numpy array with ``shape==(N,m)``
:param Y: numpy array with ``shape==(N,n)``
:param ip_B: (optional) May be one of the foll... | python | def inner(X, Y, ip_B=None):
'''Euclidean and non-Euclidean inner product.
numpy.vdot only works for vectors and numpy.dot does not use the conjugate
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andrenarchy/krypy | krypy/utils.py | norm_squared | def norm_squared(x, Mx=None, inner_product=ip_euclid):
'''Compute the norm^2 w.r.t. to a given scalar product.'''
assert(len(x.shape) == 2)
if Mx is None:
rho = inner_product(x, x)
else:
assert(len(Mx.shape) == 2)
rho = inner_product(x, Mx)
if rho.shape == (1, 1):
if... | python | def norm_squared(x, Mx=None, inner_product=ip_euclid):
'''Compute the norm^2 w.r.t. to a given scalar product.'''
assert(len(x.shape) == 2)
if Mx is None:
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rho = inner_product(x, Mx)
if rho.shape == (1, 1):
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andrenarchy/krypy | krypy/utils.py | get_linearoperator | def get_linearoperator(shape, A, timer=None):
"""Enhances aslinearoperator if A is None."""
ret = None
import scipy.sparse.linalg as scipylinalg
if isinstance(A, LinearOperator):
ret = A
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ret = IdentityLinearOperator(shape)
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"""Enhances aslinearoperator if A is None."""
ret = None
import scipy.sparse.linalg as scipylinalg
if isinstance(A, LinearOperator):
ret = A
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andrenarchy/krypy | krypy/utils.py | orthonormality | def orthonormality(V, ip_B=None):
"""Measure orthonormality of given basis.
:param V: a matrix :math:`V=[v_1,\ldots,v_n]` with ``shape==(N,n)``.
:param ip_B: (optional) the inner product to use, see :py:meth:`inner`.
:return: :math:`\\| I_n - \\langle V,V \\rangle \\|_2`.
"""
return norm(numpy... | python | def orthonormality(V, ip_B=None):
"""Measure orthonormality of given basis.
:param V: a matrix :math:`V=[v_1,\ldots,v_n]` with ``shape==(N,n)``.
:param ip_B: (optional) the inner product to use, see :py:meth:`inner`.
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andrenarchy/krypy | krypy/utils.py | arnoldi_res | def arnoldi_res(A, V, H, ip_B=None):
"""Measure Arnoldi residual.
:param A: a linear operator that can be used with scipy's aslinearoperator
with ``shape==(N,N)``.
:param V: Arnoldi basis matrix with ``shape==(N,n)``.
:param H: Hessenberg matrix: either :math:`\\underline{H}_{n-1}` with
``s... | python | def arnoldi_res(A, V, H, ip_B=None):
"""Measure Arnoldi residual.
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andrenarchy/krypy | krypy/utils.py | qr | def qr(X, ip_B=None, reorthos=1):
"""QR factorization with customizable inner product.
:param X: array with ``shape==(N,k)``
:param ip_B: (optional) inner product, see :py:meth:`inner`.
:param reorthos: (optional) numer of reorthogonalizations. Defaults to
1 (i.e. 2 runs of modified Gram-Schmidt)... | python | def qr(X, ip_B=None, reorthos=1):
"""QR factorization with customizable inner product.
:param X: array with ``shape==(N,k)``
:param ip_B: (optional) inner product, see :py:meth:`inner`.
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andrenarchy/krypy | krypy/utils.py | angles | def angles(F, G, ip_B=None, compute_vectors=False):
"""Principal angles between two subspaces.
This algorithm is based on algorithm 6.2 in `Knyazev, Argentati. Principal
angles between subspaces in an A-based scalar product: algorithms and
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"""Principal angles between two subspaces.
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andrenarchy/krypy | krypy/utils.py | gap | def gap(lamda, sigma, mode='individual'):
"""Compute spectral gap.
Useful for eigenvalue/eigenvector bounds. Computes the gap
:math:`\delta\geq 0` between two sets of real numbers ``lamda`` and
``sigma``. The gap can be computed in several ways and may not exist, see
the ``mode`` parameter.
:p... | python | def gap(lamda, sigma, mode='individual'):
"""Compute spectral gap.
Useful for eigenvalue/eigenvector bounds. Computes the gap
:math:`\delta\geq 0` between two sets of real numbers ``lamda`` and
``sigma``. The gap can be computed in several ways and may not exist, see
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andrenarchy/krypy | krypy/utils.py | bound_perturbed_gmres | def bound_perturbed_gmres(pseudo, p, epsilon, deltas):
'''Compute GMRES perturbation bound based on pseudospectrum
Computes the GMRES bound from [SifEM13]_.
'''
if not numpy.all(numpy.array(deltas) > epsilon):
raise ArgumentError('all deltas have to be greater than epsilon')
bound = []
... | python | def bound_perturbed_gmres(pseudo, p, epsilon, deltas):
'''Compute GMRES perturbation bound based on pseudospectrum
Computes the GMRES bound from [SifEM13]_.
'''
if not numpy.all(numpy.array(deltas) > epsilon):
raise ArgumentError('all deltas have to be greater than epsilon')
bound = []
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andrenarchy/krypy | krypy/utils.py | get_residual_norms | def get_residual_norms(H, self_adjoint=False):
'''Compute relative residual norms from Hessenberg matrix.
It is assumed that the initial guess is chosen as zero.'''
H = H.copy()
n_, n = H.shape
y = numpy.eye(n_, 1, dtype=H.dtype)
resnorms = [1.]
for i in range(n_-1):
G = Givens(H[i:... | python | def get_residual_norms(H, self_adjoint=False):
'''Compute relative residual norms from Hessenberg matrix.
It is assumed that the initial guess is chosen as zero.'''
H = H.copy()
n_, n = H.shape
y = numpy.eye(n_, 1, dtype=H.dtype)
resnorms = [1.]
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andrenarchy/krypy | krypy/utils.py | House.apply | def apply(self, x):
"""Apply Householder transformation to vector x.
Applies the Householder transformation efficiently to the given vector.
"""
# make sure that x is a (N,*) matrix
if len(x.shape) != 2:
raise ArgumentError('x is not a matrix of shape (N,*)')
... | python | def apply(self, x):
"""Apply Householder transformation to vector x.
Applies the Householder transformation efficiently to the given vector.
"""
# make sure that x is a (N,*) matrix
if len(x.shape) != 2:
raise ArgumentError('x is not a matrix of shape (N,*)')
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andrenarchy/krypy | krypy/utils.py | House.matrix | def matrix(self):
"""Build matrix representation of Householder transformation.
Builds the matrix representation
:math:`H = I - \\beta vv^*`.
**Use with care!** This routine may be helpful for testing purposes but
should not be used in production codes for high dimensions since... | python | def matrix(self):
"""Build matrix representation of Householder transformation.
Builds the matrix representation
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andrenarchy/krypy | krypy/utils.py | Projection._apply | def _apply(self, a, return_Ya=False):
r'''Single application of the projection.
:param a: array with ``a.shape==(N,m)``.
:param return_inner: (optional) should the inner product
:math:`\langle Y,a\rangle` be returned?
:return:
* :math:`P_{\mathcal{X},\mathcal{Y}^\pe... | python | def _apply(self, a, return_Ya=False):
r'''Single application of the projection.
:param a: array with ``a.shape==(N,m)``.
:param return_inner: (optional) should the inner product
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andrenarchy/krypy | krypy/utils.py | Projection._apply_adj | def _apply_adj(self, a):
# is projection the zero operator?
if self.V.shape[1] == 0:
return numpy.zeros(a.shape)
'''Single application of the adjoint projection.'''
c = inner(self.V, a, ip_B=self.ip_B)
if self.Q is not None and self.R is not None:
c = self... | python | def _apply_adj(self, a):
# is projection the zero operator?
if self.V.shape[1] == 0:
return numpy.zeros(a.shape)
'''Single application of the adjoint projection.'''
c = inner(self.V, a, ip_B=self.ip_B)
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andrenarchy/krypy | krypy/utils.py | Projection.apply | def apply(self, a, return_Ya=False):
r"""Apply the projection to an array.
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``shape==(N,N)``).
See also :py:meth:`_apply`.
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r"""Apply the projection to an array.
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andrenarchy/krypy | krypy/utils.py | Projection.apply_complement | def apply_complement(self, a, return_Ya=False):
"""Apply the complementary projection to an array.
:param z: array with ``shape==(N,m)``.
:return: :math:`P_{\\mathcal{Y}^\\perp,\\mathcal{X}}z =
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"""
# is projection the zer... | python | def apply_complement(self, a, return_Ya=False):
"""Apply the complementary projection to an array.
:param z: array with ``shape==(N,m)``.
:return: :math:`P_{\\mathcal{Y}^\\perp,\\mathcal{X}}z =
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andrenarchy/krypy | krypy/utils.py | Timings.get | def get(self, key):
'''Return timings for `key`. Returns 0 if not present.'''
if key in self and len(self[key]) > 0:
return min(self[key])
else:
return 0 | python | def get(self, key):
'''Return timings for `key`. Returns 0 if not present.'''
if key in self and len(self[key]) > 0:
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andrenarchy/krypy | krypy/utils.py | Timings.get_ops | def get_ops(self, ops):
'''Return timings for dictionary ops holding the operation names as
keys and the number of applications as values.'''
time = 0.
for op, count in ops.items():
time += self.get(op) * count
return time | python | def get_ops(self, ops):
'''Return timings for dictionary ops holding the operation names as
keys and the number of applications as values.'''
time = 0.
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time += self.get(op) * count
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andrenarchy/krypy | krypy/utils.py | Intervals.min_pos | def min_pos(self):
'''Returns minimal positive value or None.'''
if self.__len__() == 0:
return ArgumentError('empty set has no minimum positive value.')
if self.contains(0):
return None
positive = [interval for interval in self.intervals
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'''Returns minimal positive value or None.'''
if self.__len__() == 0:
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if self.contains(0):
return None
positive = [interval for interval in self.intervals
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andrenarchy/krypy | krypy/utils.py | Intervals.max_neg | def max_neg(self):
'''Returns maximum negative value or None.'''
if self.__len__() == 0:
return ArgumentError('empty set has no maximum negative value.')
if self.contains(0):
return None
negative = [interval for interval in self.intervals
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'''Returns maximum negative value or None.'''
if self.__len__() == 0:
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andrenarchy/krypy | krypy/utils.py | Intervals.min_abs | def min_abs(self):
'''Returns minimum absolute value.'''
if self.__len__() == 0:
return ArgumentError('empty set has no minimum absolute value.')
if self.contains(0):
return 0
return numpy.min([numpy.abs(val)
for val in [self.max_neg(), s... | python | def min_abs(self):
'''Returns minimum absolute value.'''
if self.__len__() == 0:
return ArgumentError('empty set has no minimum absolute value.')
if self.contains(0):
return 0
return numpy.min([numpy.abs(val)
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andrenarchy/krypy | krypy/utils.py | Intervals.max_abs | def max_abs(self):
'''Returns maximum absolute value.'''
if self.__len__() == 0:
return ArgumentError('empty set has no maximum absolute value.')
return numpy.max(numpy.abs([self.max(), self.min()])) | python | def max_abs(self):
'''Returns maximum absolute value.'''
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andrenarchy/krypy | krypy/utils.py | BoundMinres.get_step | def get_step(self, tol):
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Useful for computing the extrema of the polynomial over an interval if
the polynomial has real roots. In this case, the maximum is attained
for one of the interval endpoints or a point from the result of this
f... | python | def minmax_candidates(self):
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Useful for computing the extrema of the polynomial over an interval if
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"""
Check for usage errors
"""
try:
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andrenarchy/krypy | krypy/recycling/factories.py | RitzFactory._get_best_subset | def _get_best_subset(self, ritz):
'''Return candidate set with smallest goal functional.'''
# (c,\omega(c)) for all considered subsets c
overall_evaluations = {}
def evaluate(_subset, _evaluations):
try:
_evaluations[_subset] = \
self.sub... | python | def _get_best_subset(self, ritz):
'''Return candidate set with smallest goal functional.'''
# (c,\omega(c)) for all considered subsets c
overall_evaluations = {}
def evaluate(_subset, _evaluations):
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click-contrib/click-default-group | click_default_group.py | DefaultGroup.set_default_command | def set_default_command(self, command):
"""Sets a command function as the default command."""
cmd_name = command.name
self.add_command(command)
self.default_cmd_name = cmd_name | python | def set_default_command(self, command):
"""Sets a command function as the default command."""
cmd_name = command.name
self.add_command(command)
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andrenarchy/krypy | krypy/linsys.py | LinearSystem.get_residual | def get_residual(self, z, compute_norm=False):
r'''Compute residual.
For a given :math:`z\in\mathbb{C}^N`, the residual
.. math::
r = M M_l ( b - A z )
is computed. If ``compute_norm == True``, then also the absolute
residual norm
.. math::
\| M ... | python | def get_residual(self, z, compute_norm=False):
r'''Compute residual.
For a given :math:`z\in\mathbb{C}^N`, the residual
.. math::
r = M M_l ( b - A z )
is computed. If ``compute_norm == True``, then also the absolute
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andrenarchy/krypy | krypy/linsys.py | LinearSystem.get_ip_Minv_B | def get_ip_Minv_B(self):
'''Returns the inner product that is implicitly used with the positive
definite preconditioner ``M``.'''
if not isinstance(self.M, utils.IdentityLinearOperator):
if isinstance(self.Minv, utils.IdentityLinearOperator):
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'''Returns the inner product that is implicitly used with the positive
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andrenarchy/krypy | krypy/linsys.py | _KrylovSolver._get_xk | def _get_xk(self, yk):
'''Compute approximate solution from initial guess and approximate
solution of the preconditioned linear system.'''
if yk is not None:
return self.x0 + self.linear_system.Mr * yk
return self.x0 | python | def _get_xk(self, yk):
'''Compute approximate solution from initial guess and approximate
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return self.x0 + self.linear_system.Mr * yk
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andrenarchy/krypy | krypy/linsys.py | _KrylovSolver._finalize_iteration | def _finalize_iteration(self, yk, resnorm):
'''Compute solution, error norm and residual norm if required.
:return: the residual norm or ``None``.
'''
self.xk = None
# compute error norm if asked for
if self.linear_system.exact_solution is not None:
self.xk =... | python | def _finalize_iteration(self, yk, resnorm):
'''Compute solution, error norm and residual norm if required.
:return: the residual norm or ``None``.
'''
self.xk = None
# compute error norm if asked for
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andrenarchy/krypy | krypy/linsys.py | Gmres.operations | def operations(nsteps):
'''Returns the number of operations needed for nsteps of GMRES'''
return {'A': 1 + nsteps,
'M': 2 + nsteps,
'Ml': 2 + nsteps,
'Mr': 1 + nsteps,
'ip_B': 2 + nsteps + nsteps*(nsteps+1)/2,
'axpy': 4 + 2*... | python | def operations(nsteps):
'''Returns the number of operations needed for nsteps of GMRES'''
return {'A': 1 + nsteps,
'M': 2 + nsteps,
'Ml': 2 + nsteps,
'Mr': 1 + nsteps,
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andrenarchy/krypy | krypy/recycling/linsys.py | _RecyclingSolver.solve | def solve(self, linear_system,
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vector_factory=None,
*args, **kwargs):
'''Solve the given linear system with recycling.
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getdnsapi/getdns-python-bindings | examples/checkdanecert.py | compute_hash | def compute_hash(func, string):
"""compute hash of string using given hash function"""
h = func()
h.update(string)
return h.hexdigest() | python | def compute_hash(func, string):
"""compute hash of string using given hash function"""
h = func()
h.update(string)
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reincubate/deviceidentifier-py | deviceidentifier/util/local.py | get_local_serial | def get_local_serial():
''' Retrieves the serial number from the executing host.
For example, 'C02NT43PFY14'
'''
return [x for x in [subprocess.Popen("system_profiler SPHardwareDataType |grep -v tray |awk '/Serial/ {print $4}'", shell=True, stdout=subprocess.PIPE).communicate()[0].strip()] if x] | python | def get_local_serial():
''' Retrieves the serial number from the executing host.
For example, 'C02NT43PFY14'
'''
return [x for x in [subprocess.Popen("system_profiler SPHardwareDataType |grep -v tray |awk '/Serial/ {print $4}'", shell=True, stdout=subprocess.PIPE).communicate()[0].strip()] if x] | [
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andrenarchy/krypy | krypy/recycling/evaluators.py | RitzApriori._estimate_eval_intervals | def _estimate_eval_intervals(ritz, indices, indices_remaining,
eps_min=0,
eps_max=0,
eps_res=None):
'''Estimate evals based on eval inclusion theorem + heuristic.
:returns: Intervals object with inclusion... | python | def _estimate_eval_intervals(ritz, indices, indices_remaining,
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andrenarchy/krypy | krypy/deflation.py | ObliqueProjection.correct | def correct(self, z):
'''Correct the given approximate solution ``z`` with respect to the
linear system ``linear_system`` and the deflation space defined by
``U``.'''
c = self.linear_system.Ml*(
self.linear_system.b - self.linear_system.A*z)
c = utils.inner(self.W, c,... | python | def correct(self, z):
'''Correct the given approximate solution ``z`` with respect to the
linear system ``linear_system`` and the deflation space defined by
``U``.'''
c = self.linear_system.Ml*(
self.linear_system.b - self.linear_system.A*z)
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andrenarchy/krypy | krypy/deflation.py | _DeflationMixin._apply_projection | def _apply_projection(self, Av):
'''Apply the projection and store inner product.
:param v: the vector resulting from an application of :math:`M_lAM_r`
to the current Arnoldi vector. (CG needs special treatment, here).
'''
PAv, UAv = self.projection.apply_complement(Av, return... | python | def _apply_projection(self, Av):
'''Apply the projection and store inner product.
:param v: the vector resulting from an application of :math:`M_lAM_r`
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andrenarchy/krypy | krypy/deflation.py | _DeflationMixin._get_initial_residual | def _get_initial_residual(self, x0):
'''Return the projected initial residual.
Returns :math:`MPM_l(b-Ax_0)`.
'''
if x0 is None:
Mlr = self.linear_system.Mlb
else:
r = self.linear_system.b - self.linear_system.A*x0
Mlr = self.linear_system.Ml*... | python | def _get_initial_residual(self, x0):
'''Return the projected initial residual.
Returns :math:`MPM_l(b-Ax_0)`.
'''
if x0 is None:
Mlr = self.linear_system.Mlb
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r = self.linear_system.b - self.linear_system.A*x0
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andrenarchy/krypy | krypy/deflation.py | _DeflationMixin.estimate_time | def estimate_time(self, nsteps, ndefl, deflweight=1.0):
'''Estimate time needed to run nsteps iterations with deflation
Uses timings from :py:attr:`linear_system` if it is an instance of
:py:class:`~krypy.linsys.TimedLinearSystem`. Otherwise, an
:py:class:`~krypy.utils.OtherError`
... | python | def estimate_time(self, nsteps, ndefl, deflweight=1.0):
'''Estimate time needed to run nsteps iterations with deflation
Uses timings from :py:attr:`linear_system` if it is an instance of
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andrenarchy/krypy | krypy/deflation.py | Ritz.get_vectors | def get_vectors(self, indices=None):
'''Compute Ritz vectors.'''
H_ = self._deflated_solver.H
(n_, n) = H_.shape
coeffs = self.coeffs if indices is None else self.coeffs[:, indices]
return numpy.c_[self._deflated_solver.V[:, :n],
self._deflated_solver.proj... | python | def get_vectors(self, indices=None):
'''Compute Ritz vectors.'''
H_ = self._deflated_solver.H
(n_, n) = H_.shape
coeffs = self.coeffs if indices is None else self.coeffs[:, indices]
return numpy.c_[self._deflated_solver.V[:, :n],
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andrenarchy/krypy | krypy/deflation.py | Ritz.get_explicit_residual | def get_explicit_residual(self, indices=None):
'''Explicitly computes the Ritz residual.'''
ritz_vecs = self.get_vectors(indices)
return self._deflated_solver.linear_system.MlAMr * ritz_vecs \
- ritz_vecs * self.values | python | def get_explicit_residual(self, indices=None):
'''Explicitly computes the Ritz residual.'''
ritz_vecs = self.get_vectors(indices)
return self._deflated_solver.linear_system.MlAMr * ritz_vecs \
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andrenarchy/krypy | krypy/deflation.py | Ritz.get_explicit_resnorms | def get_explicit_resnorms(self, indices=None):
'''Explicitly computes the Ritz residual norms.'''
res = self.get_explicit_residual(indices)
# apply preconditioner
linear_system = self._deflated_solver.linear_system
Mres = linear_system.M * res
# compute norms
re... | python | def get_explicit_resnorms(self, indices=None):
'''Explicitly computes the Ritz residual norms.'''
res = self.get_explicit_residual(indices)
# apply preconditioner
linear_system = self._deflated_solver.linear_system
Mres = linear_system.M * res
# compute norms
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wrobstory/bearcart | bearcart/bearcart.py | Chart.transform_data | def transform_data(self, data):
'''Transform Pandas Timeseries into JSON format
Parameters
----------
data: DataFrame or Series
Pandas DataFrame or Series must have datetime index
Returns
-------
JSON to object.json_data
Example
----... | python | def transform_data(self, data):
'''Transform Pandas Timeseries into JSON format
Parameters
----------
data: DataFrame or Series
Pandas DataFrame or Series must have datetime index
Returns
-------
JSON to object.json_data
Example
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wrobstory/bearcart | bearcart/bearcart.py | Chart._build_graph | def _build_graph(self):
'''Build Rickshaw graph syntax with all data'''
# Set palette colors if necessary
if not self.colors:
self.palette = self.env.get_template('palette.js')
self.template_vars.update({'palette': self.palette.render()})
self.colors = {x['na... | python | def _build_graph(self):
'''Build Rickshaw graph syntax with all data'''
# Set palette colors if necessary
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self.palette = self.env.get_template('palette.js')
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wrobstory/bearcart | bearcart/bearcart.py | Chart.create_chart | def create_chart(self, html_path='index.html', data_path='data.json',
js_path='rickshaw.min.js', css_path='rickshaw.min.css',
html_prefix=''):
'''Save bearcart output to HTML and JSON.
Parameters
----------
html_path: string, default 'index.html... | python | def create_chart(self, html_path='index.html', data_path='data.json',
js_path='rickshaw.min.js', css_path='rickshaw.min.css',
html_prefix=''):
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raymontag/kppy | kppy/groups.py | v1Group.set_expire | def set_expire(self, y = 2999, mon = 12, d = 28, h = 23, min_ = 59,
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s = 59):
"""This method is used to change the expire date of a group
- y is the year between 1 and 9999 inclusive
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raymontag/kppy | kppy/groups.py | v1Group.create_entry | def create_entry(self, title='', image=1, url='', username='', password='',
comment='', y=2999, mon=12, d=28, h=23, min_=59, s=59):
"""This method creates an entry in this group.
Compare to StdEntry for information about the arguments.
One of the following arguments is ne... | python | def create_entry(self, title='', image=1, url='', username='', password='',
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raymontag/kppy | kppy/entries.py | v1Entry.set_title | def set_title(self, title = None):
"""This method is used to change an entry title.
A new title string is needed.
"""
if title is None or type(title) is not str:
raise KPError("Need a new title.")
else:
self.title = title
self.last_mod = dat... | python | def set_title(self, title = None):
"""This method is used to change an entry title.
A new title string is needed.
"""
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raymontag/kppy | kppy/entries.py | v1Entry.set_image | def set_image(self, image = None):
"""This method is used to set the image number.
image must be an unsigned int.
"""
if image is None or type(image) is not int:
raise KPError("Need a new image number")
else:
self.image = image
self.... | python | def set_image(self, image = None):
"""This method is used to set the image number.
image must be an unsigned int.
"""
if image is None or type(image) is not int:
raise KPError("Need a new image number")
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self.image = image
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raymontag/kppy | kppy/entries.py | v1Entry.set_url | def set_url(self, url = None):
"""This method is used to set the url.
url must be a string.
"""
if url is None or type(url) is not str:
raise KPError("Need a new image number")
else:
self.url = url
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"""This method is used to set the url.
url must be a string.
"""
if url is None or type(url) is not str:
raise KPError("Need a new image number")
else:
self.url = url
self.last_mod = datetime.no... | [
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raymontag/kppy | kppy/entries.py | v1Entry.set_username | def set_username(self, username = None):
"""This method is used to set the username.
username must be a string.
"""
if username is None or type(username) is not str:
raise KPError("Need a new image number")
else:
self.username = username
... | python | def set_username(self, username = None):
"""This method is used to set the username.
username must be a string.
"""
if username is None or type(username) is not str:
raise KPError("Need a new image number")
else:
self.username = username
... | [
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raymontag/kppy | kppy/entries.py | v1Entry.set_password | def set_password(self, password = None):
"""This method is used to set the password.
password must be a string.
"""
if password is None or type(password) is not str:
raise KPError("Need a new image number")
else:
self.password = password
... | python | def set_password(self, password = None):
"""This method is used to set the password.
password must be a string.
"""
if password is None or type(password) is not str:
raise KPError("Need a new image number")
else:
self.password = password
... | [
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raymontag/kppy | kppy/entries.py | v1Entry.set_comment | def set_comment(self, comment = None):
"""This method is used to the the comment.
comment must be a string.
"""
if comment is None or type(comment) is not str:
raise KPError("Need a new image number")
else:
self.comment = comment
sel... | python | def set_comment(self, comment = None):
"""This method is used to the the comment.
comment must be a string.
"""
if comment is None or type(comment) is not str:
raise KPError("Need a new image number")
else:
self.comment = comment
sel... | [
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raymontag/kppy | kppy/database.py | KPDBv1.read_buf | def read_buf(self):
"""Read database file"""
with open(self.filepath, 'rb') as handler:
try:
buf = handler.read()
# There should be a header at least
if len(buf) < 124:
raise KPError('Unexpected file size. ... | python | def read_buf(self):
"""Read database file"""
with open(self.filepath, 'rb') as handler:
try:
buf = handler.read()
# There should be a header at least
if len(buf) < 124:
raise KPError('Unexpected file size. ... | [
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raymontag/kppy | kppy/database.py | KPDBv1.close | def close(self):
"""This method closes the database correctly."""
if self.filepath is not None:
if path.isfile(self.filepath+'.lock'):
remove(self.filepath+'.lock')
self.filepath = None
self.read_only = False
self.lock()
... | python | def close(self):
"""This method closes the database correctly."""
if self.filepath is not None:
if path.isfile(self.filepath+'.lock'):
remove(self.filepath+'.lock')
self.filepath = None
self.read_only = False
self.lock()
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raymontag/kppy | kppy/database.py | KPDBv1.lock | def lock(self):
"""This method locks the database."""
self.password = None
self.keyfile = None
self.groups[:] = []
self.entries[:] = []
self._group_order[:] = []
self._entry_order[:] = []
self.root_group = v1Group()
self._num_groups = 1
... | python | def lock(self):
"""This method locks the database."""
self.password = None
self.keyfile = None
self.groups[:] = []
self.entries[:] = []
self._group_order[:] = []
self._entry_order[:] = []
self.root_group = v1Group()
self._num_groups = 1
... | [
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raymontag/kppy | kppy/database.py | KPDBv1.unlock | def unlock(self, password = None, keyfile = None, buf = None):
"""Unlock the database.
masterkey is needed.
"""
if ((password is None or password == "") and (keyfile is None or
keyfile == "")):
raise KPError("A password/keyfile is needed")
elif... | python | def unlock(self, password = None, keyfile = None, buf = None):
"""Unlock the database.
masterkey is needed.
"""
if ((password is None or password == "") and (keyfile is None or
keyfile == "")):
raise KPError("A password/keyfile is needed")
elif... | [
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raymontag/kppy | kppy/database.py | KPDBv1.remove_group | def remove_group(self, group = None):
"""This method removes a group.
The group needed to remove the group.
group must be a v1Group.
"""
if group is None:
raise KPError("Need group to remove a group")
elif type(group) is not v1Group:
ra... | python | def remove_group(self, group = None):
"""This method removes a group.
The group needed to remove the group.
group must be a v1Group.
"""
if group is None:
raise KPError("Need group to remove a group")
elif type(group) is not v1Group:
ra... | [
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] | a43f1fff7d49da1da4b3d8628a1b3ebbaf47f43a | https://github.com/raymontag/kppy/blob/a43f1fff7d49da1da4b3d8628a1b3ebbaf47f43a/kppy/database.py#L547-L579 | train | 62,494 |
raymontag/kppy | kppy/database.py | KPDBv1.move_group | def move_group(self, group = None, parent = None):
"""Append group to a new parent.
group and parent must be v1Group-instances.
"""
if group is None or type(group) is not v1Group:
raise KPError("A valid group must be given.")
elif parent is not None and type(parent... | python | def move_group(self, group = None, parent = None):
"""Append group to a new parent.
group and parent must be v1Group-instances.
"""
if group is None or type(group) is not v1Group:
raise KPError("A valid group must be given.")
elif parent is not None and type(parent... | [
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raymontag/kppy | kppy/database.py | KPDBv1.move_group_in_parent | def move_group_in_parent(self, group = None, index = None):
"""Move group to another position in group's parent.
index must be a valid index of group.parent.groups
"""
if group is None or index is None:
raise KPError("group and index must be set")
e... | python | def move_group_in_parent(self, group = None, index = None):
"""Move group to another position in group's parent.
index must be a valid index of group.parent.groups
"""
if group is None or index is None:
raise KPError("group and index must be set")
e... | [
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raymontag/kppy | kppy/database.py | KPDBv1._move_group_helper | def _move_group_helper(self, group):
"""A helper to move the chidren of a group."""
for i in group.children:
self.groups.remove(i)
i.level = group.level + 1
self.groups.insert(self.groups.index(group) + 1, i)
if i.children:
self._move_grou... | python | def _move_group_helper(self, group):
"""A helper to move the chidren of a group."""
for i in group.children:
self.groups.remove(i)
i.level = group.level + 1
self.groups.insert(self.groups.index(group) + 1, i)
if i.children:
self._move_grou... | [
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raymontag/kppy | kppy/database.py | KPDBv1.create_entry | def create_entry(self, group = None, title = "", image = 1, url = "",
username = "", password = "", comment = "",
y = 2999, mon = 12, d = 28, h = 23, min_ = 59,
s = 59):
"""This method creates a new entry.
The group which should hol... | python | def create_entry(self, group = None, title = "", image = 1, url = "",
username = "", password = "", comment = "",
y = 2999, mon = 12, d = 28, h = 23, min_ = 59,
s = 59):
"""This method creates a new entry.
The group which should hol... | [
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The group which should hold the entry is needed.
image must be an unsigned int >0, group a v1Group.
It is possible to give an expire date in the following way:
- y is the year between 1 and 9999 inclusive
- mon is the mo... | [
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raymontag/kppy | kppy/database.py | KPDBv1.remove_entry | def remove_entry(self, entry = None):
"""This method can remove entries.
The v1Entry-object entry is needed.
"""
if entry is None or type(entry) is not v1Entry:
raise KPError("Need an entry.")
elif entry in self.entries:
entry.gr... | python | def remove_entry(self, entry = None):
"""This method can remove entries.
The v1Entry-object entry is needed.
"""
if entry is None or type(entry) is not v1Entry:
raise KPError("Need an entry.")
elif entry in self.entries:
entry.gr... | [
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