Jslet - Master/Detail Dataset Demo
Demonstrate how to configurate master/detail style dataset simply and show how it works.
Setting
append()
Sales Master List
Sales Detail List
Demo Content:
Move cursor in master list, and check detail list.


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{% extends "_base.html" %} {% block content %}
The link below consists of technical instructions for creating capture templates in Emacs' Org-mode.


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Guardiola faces no disciplinary action from FA over comments after Anfield loss
Pep Guardiola will face no disciplinary action from the Football Association for comments made to the referee after his side’s defeat at Liverpool, the PA news agency understands.
Premier League champions Manchester City lost 3-1 at Anfield on Sunday to fall nine points behind leaders Liverpool in the table.
Guardiola was furious after two VAR decisions went against his side and was caught on camera saying “thank you so much” to referee Michael Oliver after the game.
The Spaniard insisted afterwards that he had not been sarcastic when thanking Oliver.
“It was not sarcastic,” Guardiola said. “I say ‘thank you so much’ all the
time. I said the same at Tottenham game at home. All the time I go to referees I say ‘thank you so much’.”
Fabinho’s early goal for Liverpool came moments after Oliver had waved away City’s appeals for a penalty for an alleged handball by home defender Trent Alexander-Arnold.
VAR backed up Oliver’s decision following a referral, while Guardiola was further incensed when another handball incident involving Alexander-Arnold late in the match also went in favour of the home side.
Guardiola refused to be drawn when asked about the controversial refereeing decisions in his post-match press conference.
He said: “You’ll have to ask (referees chief) Mike Riley and the big bosses about that. I’m not here to talk about the decisions over the referees or VAR. Don’t ask me, ask them.”
Liverpool doubled their lead through Mohamed Salah before half-time and Sadio Mane put them 3-0 ahead before Bernardo Silva struck a late consolation for City.


Comments
-
Greg Hurrell
I have a pretty big folder with source files (about 30000 files). There are a lot of subfolders with names I'm not interested in. Is it even possible to search through filenames only?
I gather from this that you mean that if you type "foo", for example, only the filename part of the path would be searched so "a/b/c/foo.txt" would be considered a match but "foo/hello.txt" would not. Is that right?
If that's the case, see ticket #1516. The short version is: Command-T is designed to use a "path-centric" mentality and not a "filename-centric" one. So if you're thinking in terms of filenames only, it's not going to be the right tool for the job. You either need to change your mindset, or change your tool. (And I'd suggest changing your mindset, as thinking in a "filename-centric" way when you're looking for one file among 30,000 is unlikely to be effective.)
You might also want to check out this forum topic, which specifically talks about searching massive hierarchies.
Having said that, you have three options here:
-
Use Vim's
'wildignore'
setting to tell Command-T which subfolders should be ignored. One nice benefit of this is that other file-opening mechanisms in Vim will also ignore the same files (it also means that this really is only for stuff that you never want to open). See the help (:h command-t-wildignore
and also:h 'wildignore'
) for more info. -
If you want to really focus on a specific sub-area of your
project, you can reduce the scope of Command-T's search by
providing it with a specific starting path argument (eg.
:CommandT path/to/some/subdirectory
). - Use a different plug-in which does use a "filename-centric" philosophy — for example, you could use FuzzyFinder in conjunction with a searchstring like "**/foo" — but I would recommend that you try embracing the "path-centric" mindset first as I really do think it's more effective (that's why I wrote Command-T in the first place, after having tried the alternatives and not being satisfied with them).
Actually, I use http://www.wholetomato.com/products/features/fis.asp a lot. It would be nice to get some features in Command-T.
E.g. I miss multiple file opening (when you search for Foo, find files Foo.h and Foo.cpp, and then select and open them simultaneously).
Can you please file separate tickets for each request, so that nothing gets overlooked?
As far as that specific feature you mention, I'm not really sure if it first with the Command-T way. The tool is optimized to help you open that one file which you know you want, but which happens to be buried in a project among a bunch of others, and you want to get to it as fast as possible. There are plug-ins like the excellent a.vim for opening alternate files (eg. opening the header when you're looking at the implementation, and such), and other plug-ins extend that functionality (for a good example, see how rails.vim adds the ability to easily jump between models, views and controllers and such).
In the 30,000 file project you mention, I'll bet that if you type "Foo" you'll get a lot more than just two results returned. How many of them would you want to open? 2? 3? 10? How likely is it that the top 10 results will contain the exact file you want?
I think a better way to operate would be just open the file you want to work on right now, and then open the alternates when you want to edit them (either with a.vim or with Command-T). Note that I am planning on adding buffer navigation to Command-T (ticket #1608) in the future, so this will make jumping between already open files easier.
-
Use Vim's
-
anonymous
OK, I see.
It seems Command-T is just a fast way of navigation through well-know hierarchies. Like a turbo jump to /usr/local/bin by firing ulb. Anyway, you can't do that as you will stuck with / scanning :-)
Sorry, but "path-centric" mindset seems pretty useless to me. Actually, most of files in our project have unique names. And I don't remember those names (tens of thousands). Sure, I don't remember most of folder names (thousands of them). I just remember that we have, say, notification broadcaster, somewhere. So, I just type "broad notif" and got the correct result like: SynchNotificationBroadcastingEngine.h/cpp and similar files. Here it is.
Possible, "path-centric" is good enough for pretty small projects or middle-sized web projects with lots of the similar filenames like index.html :-)
Anyway, thanks a lot for you answer and work. Vim became a lot better with Command-T.
-
Greg Hurrell
Sorry, but "path-centric" mindset seems pretty useless to me. Actually, most of files in our project have unique names. And I don't remember those names (tens of thousands). Sure, I don't remember most of folder names (thousands of them). I just remember that we have, say, notification broadcaster, somewhere. So, I just type "broad notif" and got the correct result like: SynchNotificationBroadcastingEngine.h/cpp and similar files. Here it is.
Well, I think you've got it back to front. It is precisely in your type of project that a path-centric mentality will help you navigate faster than you could with just file names.
As you said, there are fewer folder names than there are file names, so by definition they are "rarer" and therefore more valuable, statistically speaking, as a means of specifying location. Include some letters from your path, and you'll narrow down the list of possible results much faster. Note that you don't have to spell out the entire path; pretty much any characters you supply from the earlier path components will be better than not specifying any at all (ie. just say it is a file inside
spec/controllers/admin/notifications/
, you don't have to spell out "specconadmnot"; including any substring from there will help narrow things down). Also note that some positions in the path are weighted more highly than others (eg. searching for "ab" will rankannotated_bank
more highly thandelegate_subdomain
), so you should try to enter characters which appear after slashes, underscores, hyphens and such.I honestly think that if you actually used the tool the way it is meant to be used that you'd find it to be the best way to get things done.
I do wonder about how your 30,000 file project must be organized, if you have no notion of where files appear in its hierarchy. Don't you have things organized in modules or anything like that?
-
Greg Hurrell
Status changed:
- From: new
- To: closed
-
Greg Hurrell
Closing as a "won't fix" kind of thing.
The ability to open multiple files at once is also kind of handed via the quickfix binding (
<C-q>
).
Add a comment
Comments are now closed for this issue.


For a simple closed curve \(C\) in the \((x,y)-\)plane, show by Green’s theorem that the area enclosed is \(A\,=\,\frac{1}{2}\,\oint_C\,(x dy - y dx)\, .\) (Note, ‘simple’ means that \(C\) does not cross itself, which means that it encloses a well-defined area \(A\).)
Evaluate \(\oint\,{\bf F}\cdot {\bf dx}\,\) around the circle \(x^2\,+\,y^2\,+2x\,=\,0\), where \({\bf F}\,=\,y {\bf e_1}\,-\,x {\bf e_2}\), both directly and by using Green’s theorem in the plane.
Evaluate \(\oint_C\, 2x dy - 3y dx\) around the square with vertices at \((x,y)=(0,2)\), \((2,0)\), \((-2,0)\) and \((0,-2)\).
Let \({\underline{v}}\) be the radial vector field \({\underline{v}}({\underline{x}})={\underline{x}}\) .
Compute \(l_1=\int_{C_1}{\underline{v}}\cdot d{\underline{x}}\) , where \(C_1\) is the straight-line contour from the origin to the point \((2,0,0)\) .
Compute \(l_2=\int_{C_2}{\underline{v}}\cdot d{\underline{x}}\) , where \(C_2\) is the semi-circular contour from the origin to the point \((2,0,0)\) defined by \(0\le x\le 2\), \(y=+\sqrt{1-(x{-}1)^2}\) , \(z=0\). [It may help to start by sketching \(C_2\) , and then to parameterize it as \({\underline{x}}(t)= (1-\cos t,\sin t,0)\) with \(0\le t\le\pi\). ]
You should have found that \(l_1=l_2\). Explain this result using Stokes’ theorem.
Integrate \({\rm curl}\,{\bf F}\), where \({\bf F}\,=\, 3y {\bf e_1}- xz {\bf e_2}+ y z^2 {\bf e_3}\), over the portion \(S\) of the surface \(2z\,=\, x^2 + y^2\) below the plane \(z=2\), both directly and by using Stokes’ theorem. Take the area elements of \(S\) to point outwards, so that their \(z\) components are negative.
The paraboloid of equation \(z=x^2+y^2\) intersects the plane \(z=y\) in a curve \(C\). Calculate \(\oint_C\, {\bf v} \cdot {\bf dx}\,\) for \({\bf v}=2z {{\bf e_1}}+x {{\bf e_2}} + y {{\bf e_3}}\) using Stokes’ theorem. Check your answer by evaluating the line integral directly.
For an open surface \(S\) with boundary \(C\), show that \(2\int_S\,{\bf u}\cdot d{\bf A}=\oint_C\, ( {\bf u}\times{\bf x}\,)\cdot d{\bf x}\,\,,\) where \({\bf u}\) is a fixed vector.
Verify Stokes’ theorem for the upper hemispherical surface \(S\): \(z=\sqrt{1-x^2-y^2}\), \(z\ge 0\), with \({\bf F}\) equal to the radial vector field, i.e. \({\bf F}(x,y,z)\,=\,x{\bf e_1}+ y{\bf e_2}+ z{\bf e_3}\).
Let \({\bf F}\,=\, y e^z\, {\bf e_1}+ x e^z\, {\bf e_2}+ xy e^z\, {\bf e_3}\). Show that the integral of \({\bf F}\) around a regular closed curve \(C\) that is the boundary of a surface \(S\) is zero.
By applying Stokes’ theorem to the vector field \({\bf G}=|{\bf x}\,|^2 {\bf a}\) (with \({\bf a}\) a constant vector), or otherwise, show that \(\int_S {\bf x}\,\times d{\bf A}=- \frac{1}{2}\oint_C |{\bf x}\,|^2\, d{\bf x}\,\), where \(S\) is the area bounded by the closed curve \(C\).
Exam question June 2002 (Section B): Evaluate the line integral \(I=\int_C {\bf F}\cdot {d{\bf x}\,}\) where \({\bf F}({ {\bf x}\,})=2y {\bf e_1}+z {\bf e_2}+3y {\bf e_3}\) and the path \(C\) is the intersection of the surface of equation \(x^2+y^2+z^2=4z\) and the surface of equation \(z=x+2\), taken in a clockwise direction to an observer at the origin. A picture of the path is required, as well as full justifications of the theoretical results you might use.
Exam question 2012 (Section B) Q9(a)(ii): Use Stokes’ theorem to calculate the line integral \(\oint_Cydx+zdy+xdz\), where C is the intersection of the surfaces \(x^2 + y^2 + z^2 = a^2\) and \(x + y + z = 0\) and is orientated anticlockwise when viewed from above.
Suggestion: Instead of one of the two standard methods for surface integrals, just use \(d\mathbf{A}=\frac{\underline{\nabla\mkern-2mu}\mkern 3mu f}{|\underline{\nabla\mkern-2mu}\mkern 3mu f|}dA\) and think about how the surfaces intersect.
Consider the vector field \({\bf F}\;=\;y \ {\bf e_1}\,+\, (z-x)\ {\bf e_2}\,+\,(x^3+y) \ {\bf e_3}\). Evaluate \(\int_S\, (\underline{\nabla\mkern-2mu}\mkern 3mu \times{\bf F})\cdot {\bf dA}\,\) explicitly, where
\(S\) is the disk \(x^2 + y^2 \le 4\), \(z=1\),
\(S\) is the surface of a paraboloid \(x^2 + y^2 = 5 - z\) above the plane \(z=1\).
Verify that each of these agrees with Stokes’ theorem by considering the integral of \({\bf F}\) around each bounding contour.
Evaluate the line integral \[\int_{P_1}^{P_2}\; \,yz\,dx +\, xz\,dy+\, (xy + z^2)\,dz\] from \(P_1\) with co-ordinates (1,0,0) to \(P_2\) at (1,0,1) explicitly,
along a straight line in the \(z\)–direction, and
along a helical path parametrised by \({\bf x}\,(t)= {{\bf e_1}}\,\cos t+ {{\bf e_2}}\,\sin t+{{\bf e_3}}\,t/{2\pi}\,,\) where \(t\) varies along the path.
Compare these two results – does this suggest that there might be a general formula for the integral from \(P_1 =(1,0,0)\) to any point \(P\) with coordinates \((x,y,z)\)? Check your answer when \(P = P_2\).
State a necessary and sufficient condition for a vector field \({\bf F}\) to be expressible in the form \({\bf F}\;=\; \underline{\nabla\mkern-2mu}\mkern 3mu \, \phi\) in some simply-connected region. The scalar field \(\phi\) is called a scalar potential, though sometimes the opposite sign is used.
Determine whether the following vector fields are expressible in this form
(i)\(\quad ({\bf a} \cdot { {\bf x}\,}\,) \,{ {\bf x}\,} \,\), (ii)\(\quad ({\bf a} \cdot { {\bf x}\,}\,) \,{\bf a}\,\), (iii)\(\quad ({\bf a} \cdot { {\bf a}}\,) \,{\bf x}\,\,\), (iv)\(\quad {\bf a} \times{ {\bf x}\,}\,\), (v)\(\quad {\bf a} \times\left( {\bf a} \times{ {\bf x}\,}\, \right)\) ,
and find the vector fields, \({\bf F}\), for which the corresponding potentials are
(a)\(\quad {\textstyle\frac{1}{2}}({\bf a} \cdot { {\bf x}\,}\,)^2\,\), (b)\(\quad \frac{1}{2}a^2 |{\bf x}\,|^2 -\frac{1}{2}({\bf a} \cdot { {\bf x}\,}\,)^2\).
Here \({\bf a}\) is a constant non-zero vector, and \(a^2=|{\bf a}|^2\).
Exam question June 2002 (Section B):
State the conditions for the line integral \(\int_c {\bf F} \cdot {d{\bf x}\,}\) from \({ {\bf x}\,}_0\) to \({ {\bf x}\,}_1\) to be independent of the path connecting these two points.
Determine the value of the line integral \(\int_c {\bf F}\cdot {d{\bf x}\,}\) where \[{\bf F}= (e^{-y} - ze^{-x})\,{\bf e_1}+ (e^{-z}- xe^{-y})\,{\bf e_2}+(e^{-x}- ye^{-z})\,{\bf e_3},\] and \(C\) is the path \[x= \frac{1}{\ln 2} \ln (1+p),\quad y={\rm sin} \frac{\pi p}{2},\quad z=\frac{1-e^p}{1-e}\,,\] with the parameter \(p\) in the range \(0 \le p \le 1\), from \((0,0,0)\) to \((1,1,1)\).
If \({\bf F}= x\,{\bf e_1}+ y\,{\bf e_2}\), calculate \(\int_S{\bf F}\cdot {\bf dA}\,\), where \(S\) is the part of the surface \(z= 9 - x^2 - y^2\) that is above the \(x\),\(y\) plane, by applying the divergence theorem to the volume bounded by the surface and the piece it cuts out of the \(x\), \(y\) plane.
Hint: what is \({\bf F}\cdot {\bf dA}\,\) on the \(x\),\(y\) plane?
Evaluate each of the integrals below as either a volume integral or a surface integral, whichever is easier:
\(\int_S {\bf x}\,\cdot{\bf dA}\,\) over the whole surface of a cylinder bounded by \(x^2 + y^2 = R^2\), \(z=0\) and \(z=L\). Note that \({\bf x}\,\) means \(x\,{\bf e_1}+ y\,{\bf e_2}+ z\,{\bf e_3}\).
\(\int_S{\bf F}\cdot{\bf dA}\,\), where \({\bf F}= x \cos^2 y\,{\bf e_1}+xz\,{\bf e_2}+z \sin^2 y\,{\bf e_3}\) , over the surface of a sphere with centre at the origin and radius \(\pi\).
\(\int_V \underline{\nabla\mkern-2mu}\mkern 3mu \cdot {\bf F}\,dV\), where \({\bf F}=\sqrt{x^2{+}y^2} (x\,{\bf e_1}+ y\,{\bf e_2})\), over the three-dimensional volume \(x^2 + y^2 \le R^2\), \(0 \le z \le L\).
Suppose the vector field \({\bf F}\) is everywhere tangent to the closed surface \(S\), which encloses the volume \(V\). Prove that \[\int_V\underline{\nabla\mkern-2mu}\mkern 3mu \cdot {\bf F}\, dV=0\,.\]
Exam question June 2003 (Section A): Evaluate \(\int_S \,{\bf B}({ {\bf x}\,}) \cdot {\bf dA}\,\), where \[{\bf B}({\bf x}\,)=(8x+\alpha \, y-z)\,{\bf e_1}+ (x+2y+\beta\,z)\,{\bf e_2}+(\gamma \,x+y-z)\,{\bf e_3}\] and \(S\) is the surface of the sphere having centre at \((\alpha, \beta, \gamma)\) and radius \(\gamma\), where \(\alpha, \beta \in \mathbb{R}\), and \(\gamma\) is an arbitrary positive real number.
Let \(A\) be the interior of the circle of unit radius centred on the origin. Evaluate \(\iint_A \, \exp(x^2 + y^2)\, dx\, dy\) by making a change of variables to polar co-ordinates.
Let \(A\) be the region \(0 \le y \le x\) and \(0 \le x \le 1\). Evaluate \(\int_A \, ( x + y)\,dx\, dy\) by making the change of variables \(x= u + v\), \(y = u - v\). Check your answer by evaluating the integral directly.
The expressions below are called Green’s first and second identities.
A gas holder has the form of a vertical cylinder of radius \(R\) and height \(H\) with hemispherical top also of radius \(R\). The density, \(\rho\), (i.e. the mass per unit volume) of the gas inside varies with height \(z\) above the base according to the relation \(\rho = C \exp(-z)\), where \(C\) is a constant. Calculate the total mass of gas in the holder, taking care to define any coordinate system used and the range of the corresponding variables.
Use this result to find the integral of the field \[{\bf F}\,=\,B\ z\ e^{-y}\,{\bf e_1}\,+\,
C\ y\ e^{-z}\,{\bf e_2}\] over the curved surface of the gas holder.
Hint: it may help to note first what the integral over the base of the holder is.
Exam question June 2001 (Section B): In electrostatic theory, Gauss’ law states that the flux of an electrostatic (vector) field \({\bf E} ({\bf x}\,)\) over some closed surface \(S\) is equal to the enclosed charge \(q\) divided by a constant \(\epsilon_0\) : \[\int_S {\bf E} ({ {\bf x}\,})\cdot{\bf dA}\,= \frac{q}{\epsilon_0}\,.\] If the electrostatic field is given by \({\bf E}(x,y)=\alpha x {\bf e_1}+ \beta y {\bf e_2}\), use Gauss’ law to find the total charge in the compact region bounded by the surface S consisting of \(S_1\), the curved portion of the half-cylinder \(z=(R^2-y^2)^{1/2}\) of length \(H\); \(S_2\) and \(S_3\) the two semi-circular plane end pieces; and \(S_4\), the rectangular portion of the \((x,y)\)-plane. (In equations, the relevant bounded region may be described by \(z^2+y^2 \le R^2, z \ge 0, -\frac{H}{2} \le x \le \frac{H}{2}\)). Express your result in terms of \(\alpha, \beta, R\) and \(H\).
Exam question June 2002 (Section A): In electrostatic theory, Gauss’ law states that the flux of an electrostatic field \({\bf E} ({ {\bf x}\,})\) over a closed surface \(S\) is given by the ratio of the enclosed charge \(q\) and a constant \(\epsilon_0\). Calculate the electric charge enclosed in the ellipsoid of equation \(x^2+\frac{1}{2}y^2+z^2=1\) in the presence of
an electrostatic field \({\bf E} ({ {\bf x}\,})= y z {\bf e_1}+x z {\bf e_2} +x y {\bf e_3}\) ,
an electrostatic field \({\bf E} ({ {\bf x}\,})=x {\bf e_1}+ y {\bf e_2}+ z {\bf e_3}\) .


83,9% of Children in Bulgaria Aged between 4 the Starting Age of Compulsory Primary Education Were Enrolled in Early Childhood Education
Yesterday was the World Children's Day. To mark the occasion Eurostat published an article about the early childhood education in the European Union (EU).
In 2017, 95.4% of children aged between 4 years old and the starting age of compulsory primary education were enrolled in early childhood education in the EU. This figure has been rising over the last decade and in 2017 it was 4.7 percentage points higher than in 2007.
2016 marked the year in which the target of 95% participation in early childhood education and care, set in the Education and Training 2020 framework for the EU as a whole, was reached.
An analysis by EU Member State for 2017 reveals that at the lower end of the range this ratio was 78.2 % in Slovakia and between 80.0 % and 85.0 % in Greece, Croatia and Bulgaria.
A total of 15 EU Member States reported that they had already achieved the 95 % benchmark in 2017: Italy, Austria, Hungary, Sweden, Latvia, Germany, Malta, Luxembourg, Spain, the Netherlands, Denmark, Belgium, the United Kingdom, France and Ireland (the last three each reporting ratios of 100 %), Eurostat data show.


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security.txt | A proposed standard which allows websites to define security policies A proposed standard which allows websites to define security policies.


# -*- coding: utf-8 -*-
# This code is part of Qiskit.
#
# (C) Copyright IBM 2017, 2019.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any modifications or derivative works of this code must retain this
# copyright notice, and modified files need to carry a notice indicating
# that they have been altered from the originals.
"""Factory and credentials manager for IBM Q Experience."""
import logging
import warnings
from collections import OrderedDict
from qiskit.providers.exceptions import QiskitBackendNotFoundError
from .accountprovider import AccountProvider
from .api_v2.clients import AuthClient, VersionClient
from .credentials import Credentials, discover_credentials
from .credentials.configrc import (read_credentials_from_qiskitrc,
remove_credentials,
store_credentials)
from .credentials.updater import update_credentials
from .exceptions import IBMQAccountError, IBMQApiUrlError, IBMQProviderError
from .ibmqprovider import IBMQProvider
from .utils.deprecation import deprecated, UPDATE_ACCOUNT_TEXT
logger = logging.getLogger(__name__)
QX_AUTH_URL = 'https://auth.quantum-computing.ibm.com/api'
[ドキュメント]class IBMQFactory:
"""Factory and credentials manager for IBM Q Experience."""
def __init__(self):
self._credentials = None
self._providers = OrderedDict()
self._v1_provider = IBMQProvider()
# Account management functions.
[ドキュメント] def enable_account(self, token, url=QX_AUTH_URL, **kwargs):
"""Authenticate against IBM Q Experience for use during this session.
Note: with version 0.3 of this qiskit-ibmq-provider package, use of
the legacy Quantum Experience and Qconsole (also known
as the IBM Q Experience v1) credentials is deprecated. The new
default is to use the IBM Q Experience v2 credentials.
Args:
token (str): IBM Q Experience API token.
url (str): URL for the IBM Q Experience authentication server.
**kwargs (dict): additional settings for the connection:
* proxies (dict): proxy configuration.
* verify (bool): verify the server's TLS certificate.
Returns:
AccountProvider: the provider for the default open access project.
Raises:
IBMQAccountError: if an IBM Q Experience v2 account is already in
use, or if attempting using both IBM Q Experience v1 and v2
accounts.
IBMQApiUrlError: if the input token and url are for an IBM Q
Experience v2 account, but the url is not a valid
authentication URL.
"""
# Check if an IBM Q Experience 2 account is already in use.
if self._credentials:
raise IBMQAccountError('An IBM Q Experience v2 account is already '
'enabled.')
# Check the version used by these credentials.
credentials = Credentials(token, url, **kwargs)
version_info = self._check_api_version(credentials)
# For API 1, delegate onto the IBMQProvider.
if not version_info['new_api']:
warnings.warn(
'Using IBM Q Experience v1 credentials is being deprecated. '
'Please use IBM Q Experience v2 credentials instead. '
'You can find the instructions to make the updates here:\n'
'https://github.com/Qiskit/qiskit-ibmq-provider#'
'updating-to-the-new-ibm-q-experience',
DeprecationWarning)
self._v1_provider.enable_account(token, url, **kwargs)
return self._v1_provider
# Prevent using credentials not from the auth server.
if 'api-auth' not in version_info:
raise IBMQApiUrlError(
'The URL specified ({}) is not an IBM Q Experience '
'authentication URL'.format(credentials.url))
# Prevent mixing API 1 and API 2 credentials.
if self._v1_provider.active_accounts():
raise IBMQAccountError('An IBM Q Experience v1 account is '
'already enabled.')
# Initialize the API 2 providers.
self._initialize_providers(credentials)
# Prevent edge case where no hubs are available.
providers = self.providers()
if not providers:
warnings.warn('No Hub/Group/Projects could be found for this '
'account.')
return None
return providers[0]
[ドキュメント] def disable_account(self):
"""Disable the account in the current session.
Raises:
IBMQAccountError: if IBM Q Experience API v1 credentials are found,
or if no account is in use in the session.
"""
if self._v1_provider.active_accounts():
raise IBMQAccountError(
'IBM Q Experience v1 accounts are enabled. Please use '
'IBMQ.disable_accounts() to disable them.')
if not self._credentials:
raise IBMQAccountError('No account is in use for this session.')
self._credentials = None
self._providers = OrderedDict()
[ドキュメント] def load_account(self):
"""Authenticate against IBM Q Experience from stored credentials.
Returns:
AccountProvider: the provider for the default open access project.
Raises:
IBMQAccountError: if an IBM Q Experience v1 account is already in
use, or no IBM Q Experience v2 accounts can be found.
"""
# Prevent mixing API 1 and API 2 credentials.
if self._v1_provider.active_accounts():
raise IBMQAccountError('An IBM Q Experience v1 account is '
'already enabled.')
# Check for valid credentials.
credentials_list = list(discover_credentials().values())
if not credentials_list:
raise IBMQAccountError(
'No IBM Q Experience credentials found on disk.')
if len(credentials_list) > 1:
raise IBMQAccountError('Multiple IBM Q Experience credentials '
'found. ' + UPDATE_ACCOUNT_TEXT)
credentials = credentials_list[0]
# Explicitly check via an API call, to allow environment auth URLs.
# contain API 2 URL (but not auth) slipping through.
version_info = self._check_api_version(credentials)
# For API 1, delegate onto the IBMQProvider.
if not version_info['new_api']:
raise IBMQAccountError('IBM Q Experience v1 credentials found. ' +
UPDATE_ACCOUNT_TEXT)
if 'api-auth' not in version_info:
raise IBMQAccountError('Invalid IBM Q Experience v2 credentials '
'found. ' + UPDATE_ACCOUNT_TEXT)
# Initialize the API 2 providers.
if self._credentials:
# For convention, emit a warning instead of raising.
warnings.warn('Credentials are already in use. The existing '
'account in the session will be replaced.')
self.disable_account()
self._initialize_providers(credentials)
# Prevent edge case where no hubs are available.
providers = self.providers()
if not providers:
warnings.warn('No Hub/Group/Projects could be found for this '
'account.')
return None
return providers[0]
[ドキュメント] @staticmethod
def save_account(token, url=QX_AUTH_URL, overwrite=False, **kwargs):
"""Save the account to disk for future use.
Note: IBM Q Experience v1 credentials are being deprecated. Please
use IBM Q Experience v2 credentials instead.
Args:
token (str): IBM Q Experience API token.
url (str): URL for the IBM Q Experience authentication server.
overwrite (bool): overwrite existing credentials.
**kwargs (dict):
* proxies (dict): Proxy configuration for the API.
* verify (bool): If False, ignores SSL certificates errors
"""
if url != QX_AUTH_URL:
warnings.warn(
'IBM Q Experience v1 credentials are being deprecated. Please '
'use IBM Q Experience v2 credentials instead. '
'You can find the instructions to make the updates here:\n'
'https://github.com/Qiskit/qiskit-ibmq-provider#'
'updating-to-the-new-ibm-q-experience',
DeprecationWarning)
credentials = Credentials(token, url, **kwargs)
store_credentials(credentials, overwrite=overwrite)
[ドキュメント] @staticmethod
def delete_account():
"""Delete the saved account from disk.
Raises:
IBMQAccountError: if no valid IBM Q Experience v2 credentials found.
"""
stored_credentials = read_credentials_from_qiskitrc()
if not stored_credentials:
raise IBMQAccountError('No credentials found.')
if len(stored_credentials) != 1:
raise IBMQAccountError('Multiple credentials found. ' +
UPDATE_ACCOUNT_TEXT)
credentials = list(stored_credentials.values())[0]
if credentials.url != QX_AUTH_URL:
raise IBMQAccountError('IBM Q Experience v1 credentials found. ' +
UPDATE_ACCOUNT_TEXT)
remove_credentials(credentials)
[ドキュメント] @staticmethod
def stored_account():
"""List the account stored on disk.
Returns:
dict: dictionary with information about the account stored on disk.
Raises:
IBMQAccountError: if no valid IBM Q Experience v2 credentials found.
"""
stored_credentials = read_credentials_from_qiskitrc()
if not stored_credentials:
return {}
if (len(stored_credentials) > 1 or
list(stored_credentials.values())[0].url != QX_AUTH_URL):
raise IBMQAccountError('IBM Q Experience v1 credentials found. ' +
UPDATE_ACCOUNT_TEXT)
credentials = list(stored_credentials.values())[0]
return {
'token': credentials.token,
'url': credentials.url
}
[ドキュメント] def active_account(self):
"""List the IBM Q Experience v2 account currently in the session.
Returns:
dict: information about the account currently in the session.
Raises:
IBMQAccountError: if an IBM Q Experience v1 account is already in
use.
"""
if self._v1_provider.active_accounts():
raise IBMQAccountError(
'IBM Q Experience v1 accounts are enabled. Please use '
'IBMQ.active_accounts() to retrieve information about them.')
if not self._credentials:
# Return None instead of raising, for compatibility with the
# previous active_accounts() behavior.
return None
return {
'token': self._credentials.token,
'url': self._credentials.url,
}
[ドキュメント] @staticmethod
def update_account(force=False):
"""Interactive helper from migrating stored credentials to IBM Q Experience v2.
Args:
force (bool): if `True`, disable interactive prompts and perform
the changes.
Returns:
Credentials: if the updating is possible, credentials for the API
version 2; and `None` otherwise.
"""
return update_credentials(force)
# Provider management functions.
[ドキュメント] def providers(self, hub=None, group=None, project=None):
"""Return a list of providers with optional filtering.
Args:
hub (str): name of the hub.
group (str): name of the group.
project (str): name of the project.
Returns:
list[AccountProvider]: list of providers that match the specified
criteria.
"""
filters = []
if hub:
filters.append(lambda hgp: hgp.hub == hub)
if group:
filters.append(lambda hgp: hgp.group == group)
if project:
filters.append(lambda hgp: hgp.project == project)
providers = [provider for key, provider in self._providers.items()
if all(f(key) for f in filters)]
return providers
[ドキュメント] def get_provider(self, hub=None, group=None, project=None):
"""Return a provider for a single hub/group/project combination.
Returns:
AccountProvider: provider that match the specified criteria.
Raises:
IBMQProviderError: if no provider matches the specified criteria,
or more than one provider match the specified criteria.
"""
providers = self.providers(hub, group, project)
if not providers:
raise IBMQProviderError('No provider matching the criteria')
if len(providers) > 1:
raise IBMQProviderError('More than one provider matching the '
'criteria')
return providers[0]
# Private functions.
@staticmethod
def _check_api_version(credentials):
"""Check the version of the API in a set of credentials.
Returns:
dict: dictionary with version information.
"""
version_finder = VersionClient(credentials.base_url,
**credentials.connection_parameters())
return version_finder.version()
def _initialize_providers(self, credentials):
"""Authenticate against IBM Q Experience and populate the providers.
Args:
credentials (Credentials): credentials for IBM Q Experience.
Raises:
IBMQApiUrlError: if the credentials do not belong to a IBM Q
Experience authentication URL.
"""
auth_client = AuthClient(credentials.token,
credentials.base_url)
service_urls = auth_client.current_service_urls()
user_hubs = auth_client.user_hubs()
self._credentials = credentials
for hub_info in user_hubs:
# Build credentials.
provider_credentials = Credentials(
credentials.token,
url=service_urls['http'],
websockets_url=service_urls['ws'],
proxies=credentials.proxies,
verify=credentials.verify,
**hub_info,)
# Build the provider.
try:
provider = AccountProvider(provider_credentials,
auth_client.current_access_token())
self._providers[provider_credentials.unique_id()] = provider
except Exception as ex: # pylint: disable=broad-except
# Catch-all for errors instantiating the provider.
logger.warning('Unable to instantiate provider for %s: %s',
hub_info, ex)
# Deprecated account management functions for backward compatibility.
[ドキュメント] @deprecated
def active_accounts(self):
"""List all IBM Q Experience v1 accounts currently in the session.
Note: this method is being deprecated, and is only available when using
v1 accounts.
Returns:
list[dict]: a list with information about the accounts currently
in the session.
Raises:
IBMQAccountError: if the method is used with an IBM Q Experience
v2 account.
"""
return self._v1_provider.active_accounts()
[ドキュメント] @deprecated
def disable_accounts(self, **kwargs):
"""Disable IBM Q Experience v1 accounts in the current session.
Note: this method is being deprecated, and only available when using
v1 accounts.
The filter kwargs can be `token`, `url`, `hub`, `group`, `project`.
If no filter is passed, all accounts in the current session will be disabled.
Raises:
IBMQAccountError: if the method is used with an IBM Q Experience v2
account, or if no account matched the filter.
"""
self._v1_provider.disable_accounts(**kwargs)
[ドキュメント] @deprecated
def load_accounts(self, **kwargs):
"""Load IBM Q Experience v1 accounts found in the system into current session.
Will also load v2 accounts for backward compatibility, but can lead to
issues if mixing v1 and v2 credentials in other method calls.
Note: this method is being deprecated, and only available when using
v1 accounts.
Automatically load the accounts found in the system. This method
looks for credentials in the following locations, in order, and
returns as soon as credentials are found:
1. in the `Qconfig.py` file in the current working directory.
2. in the environment variables.
3. in the `qiskitrc` configuration file
Raises:
IBMQAccountError: If mixing v1 and v2 account credentials
"""
version_counter = 0
for credentials in discover_credentials().values():
# Explicitly check via an API call, to prevent credentials that
# contain API 2 URL (but not auth) slipping through.
version_info = self._check_api_version(credentials)
version_counter += int(version_info['new_api'])
# Check if mixing v1 and v2 credentials
if version_counter != 0 and version_counter < len(discover_credentials().values()):
raise IBMQAccountError('Can not mix API v1 and v2'
'credentials.')
# If calling using API v2 credentials
if version_counter:
warnings.warn(
'Calling IBMQ.load_accounts() with v2 credentials. '
'This is provided for backwards compatibility '
'and may lead to unexpected behaviour when mixing '
'v1 and v2 account credentials.', DeprecationWarning)
self.load_account()
else:
# Old API v1 call
self._v1_provider.load_accounts(**kwargs)
[ドキュメント] @deprecated
def delete_accounts(self, **kwargs):
"""Delete saved IBM Q Experience v1 accounts from disk, subject to optional filtering.
Note: this method is being deprecated, and only available when using
v1 accounts.
The filter kwargs can be `token`, `url`, `hub`, `group`, `project`.
If no filter is passed, all accounts will be deleted from disk.
Raises:
IBMQAccountError: if the method is used with an IBM Q Experience v2
account, or if no account matched the filter.
"""
self._v1_provider.delete_accounts(**kwargs)
[ドキュメント] @deprecated
def stored_accounts(self):
"""List all IBM Q Experience v1 accounts stored to disk.
Note: this method is being deprecated, and only available when using
v1 accounts.
Returns:
list[dict]: a list with information about the accounts stored
on disk.
Raises:
IBMQAccountError: if the method is used with an IBM Q Experience v2 account.
"""
return self._v1_provider.stored_accounts()
# Deprecated backend-related functionality.
[ドキュメント] def backends(self, name=None, filters=None, **kwargs):
"""Return all backends accessible via IBMQ provider, subject to optional filtering.
Note: this method is being deprecated. Please use an IBM Q Experience v2
account, and::
provider = IBMQ.get_provider(...)
provider.backends()
instead.
Args:
name (str): backend name to filter by
filters (callable): more complex filters, such as lambda functions
e.g. IBMQ.backends(filters=lambda b: b.configuration['n_qubits'] > 5)
kwargs: simple filters specifying a true/false criteria in the
backend configuration or backend status or provider credentials
e.g. IBMQ.backends(n_qubits=5, operational=True, hub='internal')
Returns:
list[IBMQBackend]: list of backends available that match the filter
"""
warnings.warn('IBMQ.backends() is being deprecated. '
'Please use IBMQ.get_provider() to retrieve a provider '
'and AccountProvider.backends() to find its backends.',
DeprecationWarning)
if self._credentials:
hgp_filter = {}
# First filter providers by h/g/p
for key in ['hub', 'group', 'project']:
if key in kwargs:
hgp_filter[key] = kwargs.pop(key)
providers = self.providers(**hgp_filter)
# Aggregate the list of filtered backends.
backends = []
for provider in providers:
backends = backends + provider.backends(
name=name, filters=filters, **kwargs)
return backends
else:
return self._v1_provider.backends(name, filters, **kwargs)
[ドキュメント] def get_backend(self, name=None, **kwargs):
"""Return a single backend matching the specified filtering.
Note: this method is being deprecated. Please use an IBM Q Experience v2
account, and::
provider = IBMQ.get_provider(...)
provider.get_backend('name')
instead.
Args:
name (str): name of the backend.
**kwargs (dict): dict used for filtering.
Returns:
BaseBackend: a backend matching the filtering.
Raises:
QiskitBackendNotFoundError: if no backend could be found or
more than one backend matches the filtering criteria.
"""
warnings.warn('IBMQ.get_backend() is being deprecated. '
'Please use IBMQ.get_provider() to retrieve a provider '
'and AccountProvider.get_backend("name") to retrieve a '
'backend.',
DeprecationWarning)
# Don't issue duplicate warnings
with warnings.catch_warnings():
warnings.filterwarnings('ignore', category=DeprecationWarning)
backends = self.backends(name, **kwargs)
if len(backends) > 1:
raise QiskitBackendNotFoundError('More than one backend matches the criteria')
if not backends:
raise QiskitBackendNotFoundError('No backend matches the criteria')
return backends[0]


Hi! My name is Swarali and I'm from (Incredible!) India - this section is not sponsored by the 'Incredible! India' ad campaign. *Promise* I studied neuroscience at university and researched about autism and motor disorders. I did not achieve anything ground breaking. I did break a few test tubes though! Aside from my studies, I enjoy meditating and meeting new people. Around this time last year, I went for a meditation retreat in India and it was one of the most exciting things I have done in my life! The most exciting would have to be being in the middle of the ocean during a really terrible storm!
My grandmother, with whom I share my birthday! I lovingly call her Akki. She grew up with 7 siblings in a modest but disciplined household. Because she was born under the British rule in India, she learnt in an English school and can speak the language to this day (she's turning 70 this year!). She studied till 10th grade (a big deal at the time), and because she saw how hard her parents worked for her and her siblings, she always strove to earn money of her own and contribute to her family. First she sewed clothes and sold them for meagre sums of money, then she learnt typewriting and began an illustrious career writing legal documents in the government. Even after she left her job after marriage (as was common in Indian society), she saved diligently to ensure a flow of money when times were tough. Under her motherly shadow, my mother won several awards in drama, dance and even released a music cassette (modern day equivalent would be Youtube Vevo), not to mention top her boards and college degree. She is now studying towars a Master's in Neuropsychology with the hope to develop behavioral therapies for mental health patients at the intersection of music, meditation and counselling. Of course, my mother is also my role model, but she is who she is only because of Akki.
 - Jane Goodall
In case of further questions, you can reach me on:


just got back from the Makers show at great scott. holy smokes.
first off, the great scott is an excellent place. second off, the second opening band Rock n’ Roll Soldiers were pretty damn good.
that said, the night started off with my girlfriend making fun of me because i said hello ( according to her ) like some star-struck groupie to Donny ( Virgo ) Maker and made small talk.
later i got to meet more of the band when i introduced myself and they asked me where a guitar player for the Makers would likely disappear to while in Allston, massachusetts … because he had gone missing and was still a no-show ten minutes before they went on. i wished them the best in finding him ( like a star-struck groupie ) and told them there were a few bars ( where the ‘ladies’ go ) down the road.
a little bit later, he (Jamie the guitarist ) showed up and they went on.
they played like they were in front of a crowd of a hundred and didn’t need any of us, but wanted us. there was about a good twenty of us there…
now that’s rock.
The stage presence Mike Maker has is inexplicable, and seen when they play in the northwest is amazing. when seen over on the other side where they are largely unknown, it is astounding. he commands the stage, letting not even the rats look away.
i hope the rest of the tour goes well, and i hope to see them back here soon.
if you are interested in learning more about the Makers, visit your local library … and for ( in my opinion ) a good introductary album ‘Rock Star God’.
don’t stop there.


The namespace attack discussed in the previous section may be also leveraged to directly interfere with the JavaScript execution environment, without relying on other HTML elements as a proxy. This is because of a little-known link between the markup and the script namespace: In all popular browsers, the identifiers attached to HTML tags are automatically registered in the JavaScript context associated with the page. This registration happens on two levels:
- For any type of a tag, a new node with a name matching the id parameter of the tag is inserted into the default object scope. In other words,
 will create a global variable test (of type HTMLDivElement), pointing to the DOM object associated with the tag.
- In this scenario, the mapping has a lower priority than any built-ins or variables previously created by on-page scripts. The behavior of identically named variables created later on is browser-specific.
- For several special tags, such as , , or <embed>, an entry for both the id and the name is additionally inserted into the document object. For example,  will produce a node named document.test.
- This mapping has a higher priority than built-ins and script-created variables.
An attacker capable of injecting passive markup may leverage this property in a manner illustrated in this code snippet:
 ← Injected markup
...
// Legitimate application code follows
function retrieve_acls() {
...
if (response.access_mode == AM_PUBLIC) ← The subsequent assignment fails in IE
is_public = true;
else
is_public = false;
}
function submit_new_acls() {
...
if (is_public) request.access_mode = AM_PUBLIC; ← Condition always evaluates to true
...
}
The consequences of this namespace pollution are made worse because the DOM objects associated with certain HTML elements have specialized methods for converting them to strings; this enables the attacker to attack not only simple Boolean conditions, but also to spoof numbers and strings:
 ← Injected markup

...
// Legitimate application code follows
function retrieve_data() {
if (window.data_loaded) return; ← Condition met in browsers other than Firefox
...
owner_user = response.owner;
data_loaded = true;
}
function submit_new_acls() {
...
request.can_edit = owner_user + ...; ← The string 'fredmbogo' is inserted
request.can_read = owner_user + ...;
...
}
Several other exploitation venues appear to exist, but will be more closely tied to the design of the targeted application. It is, for example, possible to shadow built-ins such as document.domain, document.cookie, document.location, or document.referrer in order to interfere with certain security decisions; it is also trivial to disrupt the operation of methods such as document.createElement() or document.open(); fabricate the availability of the window.postMessage(...), window.crypto, or other security APIs; and more.


# -*- coding: utf-8 -*-
"""
A Theil-Sen Estimator for Multiple Linear Regression Model
"""
# Author: Florian Wilhelm<EMAIL_ADDRESS>#
# License: BSD 3 clause
from __future__ import division, print_function, absolute_import
import warnings
from itertools import combinations
import numpy as np
from scipy import linalg
from scipy.special import binom
from scipy.linalg.lapack import get_lapack_funcs
from .base import LinearModel
from ..base import RegressorMixin
from ..utils import check_random_state
from ..utils import check_X_y, _get_n_jobs
from ..externals.joblib import Parallel, delayed
from ..externals.six.moves import xrange as range
from ..exceptions import ConvergenceWarning
_EPSILON = np.finfo(np.double).eps
def _modified_weiszfeld_step(X, x_old):
"""Modified Weiszfeld step.
This function defines one iteration step in order to approximate the
spatial median (L1 median). It is a form of an iteratively re-weighted
least squares method.
Parameters
----------
X : array, shape = [n_samples, n_features]
Training vector, where n_samples is the number of samples and
n_features is the number of features.
x_old : array, shape = [n_features]
Current start vector.
Returns
-------
x_new : array, shape = [n_features]
New iteration step.
References
----------
- On Computation of Spatial Median for Robust Data Mining, 2005
T. Kärkkäinen and S. Äyrämö
http://users.jyu.fi/~samiayr/pdf/ayramo_eurogen05.pdf
"""
diff = X - x_old
diff_norm = np.sqrt(np.sum(diff ** 2, axis=1))
mask = diff_norm >= _EPSILON
# x_old equals one of our samples
is_x_old_in_X = int(mask.sum() < X.shape[0])
diff = diff[mask]
diff_norm = diff_norm[mask][:, np.newaxis]
quotient_norm = linalg.norm(np.sum(diff / diff_norm, axis=0))
if quotient_norm > _EPSILON: # to avoid division by zero
new_direction = (np.sum(X[mask, :] / diff_norm, axis=0)
/ np.sum(1 / diff_norm, axis=0))
else:
new_direction = 1.
quotient_norm = 1.
return (max(0., 1. - is_x_old_in_X / quotient_norm) * new_direction
+ min(1., is_x_old_in_X / quotient_norm) * x_old)
def _spatial_median(X, max_iter=300, tol=1.e-3):
"""Spatial median (L1 median).
The spatial median is member of a class of so-called M-estimators which
are defined by an optimization problem. Given a number of p points in an
n-dimensional space, the point x minimizing the sum of all distances to the
p other points is called spatial median.
Parameters
----------
X : array, shape = [n_samples, n_features]
Training vector, where n_samples is the number of samples and
n_features is the number of features.
max_iter : int, optional
Maximum number of iterations. Default is 300.
tol : float, optional
Stop the algorithm if spatial_median has converged. Default is 1.e-3.
Returns
-------
spatial_median : array, shape = [n_features]
Spatial median.
n_iter : int
Number of iterations needed.
References
----------
- On Computation of Spatial Median for Robust Data Mining, 2005
T. Kärkkäinen and S. Äyrämö
http://users.jyu.fi/~samiayr/pdf/ayramo_eurogen05.pdf
"""
if X.shape[1] == 1:
return 1, np.median(X.ravel())
tol **= 2 # We are computing the tol on the squared norm
spatial_median_old = np.mean(X, axis=0)
for n_iter in range(max_iter):
spatial_median = _modified_weiszfeld_step(X, spatial_median_old)
if np.sum((spatial_median_old - spatial_median) ** 2) < tol:
break
else:
spatial_median_old = spatial_median
else:
warnings.warn("Maximum number of iterations {max_iter} reached in "
"spatial median for TheilSen regressor."
"".format(max_iter=max_iter), ConvergenceWarning)
return n_iter, spatial_median
def _breakdown_point(n_samples, n_subsamples):
"""Approximation of the breakdown point.
Parameters
----------
n_samples : int
Number of samples.
n_subsamples : int
Number of subsamples to consider.
Returns
-------
breakdown_point : float
Approximation of breakdown point.
"""
return 1 - (0.5 ** (1 / n_subsamples) * (n_samples - n_subsamples + 1) +
n_subsamples - 1) / n_samples
def _lstsq(X, y, indices, fit_intercept):
"""Least Squares Estimator for TheilSenRegressor class.
This function calculates the least squares method on a subset of rows of X
and y defined by the indices array. Optionally, an intercept column is
added if intercept is set to true.
Parameters
----------
X : array, shape = [n_samples, n_features]
Design matrix, where n_samples is the number of samples and
n_features is the number of features.
y : array, shape = [n_samples]
Target vector, where n_samples is the number of samples.
indices : array, shape = [n_subpopulation, n_subsamples]
Indices of all subsamples with respect to the chosen subpopulation.
fit_intercept : bool
Fit intercept or not.
Returns
-------
weights : array, shape = [n_subpopulation, n_features + intercept]
Solution matrix of n_subpopulation solved least square problems.
"""
fit_intercept = int(fit_intercept)
n_features = X.shape[1] + fit_intercept
n_subsamples = indices.shape[1]
weights = np.empty((indices.shape[0], n_features))
X_subpopulation = np.ones((n_subsamples, n_features))
# gelss need to pad y_subpopulation to be of the max dim of X_subpopulation
y_subpopulation = np.zeros((max(n_subsamples, n_features)))
lstsq, = get_lapack_funcs(('gelss',), (X_subpopulation, y_subpopulation))
for index, subset in enumerate(indices):
X_subpopulation[:, fit_intercept:] = X[subset, :]
y_subpopulation[:n_subsamples] = y[subset]
weights[index] = lstsq(X_subpopulation,
y_subpopulation)[1][:n_features]
return weights
class TheilSenRegressor(LinearModel, RegressorMixin):
"""Theil-Sen Estimator: robust multivariate regression model.
The algorithm calculates least square solutions on subsets with size
n_subsamples of the samples in X. Any value of n_subsamples between the
number of features and samples leads to an estimator with a compromise
between robustness and efficiency. Since the number of least square
solutions is "n_samples choose n_subsamples", it can be extremely large
and can therefore be limited with max_subpopulation. If this limit is
reached, the subsets are chosen randomly. In a final step, the spatial
median (or L1 median) is calculated of all least square solutions.
Read more in the :ref:`User Guide <theil_sen_regression>`.
Parameters
----------
fit_intercept : boolean, optional, default True
Whether to calculate the intercept for this model. If set
to false, no intercept will be used in calculations.
copy_X : boolean, optional, default True
If True, X will be copied; else, it may be overwritten.
max_subpopulation : int, optional, default 1e4
Instead of computing with a set of cardinality 'n choose k', where n is
the number of samples and k is the number of subsamples (at least
number of features), consider only a stochastic subpopulation of a
given maximal size if 'n choose k' is larger than max_subpopulation.
For other than small problem sizes this parameter will determine
memory usage and runtime if n_subsamples is not changed.
n_subsamples : int, optional, default None
Number of samples to calculate the parameters. This is at least the
number of features (plus 1 if fit_intercept=True) and the number of
samples as a maximum. A lower number leads to a higher breakdown
point and a low efficiency while a high number leads to a low
breakdown point and a high efficiency. If None, take the
minimum number of subsamples leading to maximal robustness.
If n_subsamples is set to n_samples, Theil-Sen is identical to least
squares.
max_iter : int, optional, default 300
Maximum number of iterations for the calculation of spatial median.
tol : float, optional, default 1.e-3
Tolerance when calculating spatial median.
random_state : int, RandomState instance or None, optional, default None
A random number generator instance to define the state of the random
permutations generator. If int, random_state is the seed used by the
random number generator; If RandomState instance, random_state is the
random number generator; If None, the random number generator is the
RandomState instance used by `np.random`.
n_jobs : integer, optional, default 1
Number of CPUs to use during the cross validation. If ``-1``, use
all the CPUs.
verbose : boolean, optional, default False
Verbose mode when fitting the model.
Attributes
----------
coef_ : array, shape = (n_features)
Coefficients of the regression model (median of distribution).
intercept_ : float
Estimated intercept of regression model.
breakdown_ : float
Approximated breakdown point.
n_iter_ : int
Number of iterations needed for the spatial median.
n_subpopulation_ : int
Number of combinations taken into account from 'n choose k', where n is
the number of samples and k is the number of subsamples.
References
----------
- Theil-Sen Estimators in a Multiple Linear Regression Model, 2009
Xin Dang, Hanxiang Peng, Xueqin Wang and Heping Zhang
http://home.olemiss.edu/~xdang/papers/MTSE.pdf
"""
def __init__(self, fit_intercept=True, copy_X=True,
max_subpopulation=1e4, n_subsamples=None, max_iter=300,
tol=1.e-3, random_state=None, n_jobs=1, verbose=False):
self.fit_intercept = fit_intercept
self.copy_X = copy_X
self.max_subpopulation = int(max_subpopulation)
self.n_subsamples = n_subsamples
self.max_iter = max_iter
self.tol = tol
self.random_state = random_state
self.n_jobs = n_jobs
self.verbose = verbose
def _check_subparams(self, n_samples, n_features):
n_subsamples = self.n_subsamples
if self.fit_intercept:
n_dim = n_features + 1
else:
n_dim = n_features
if n_subsamples is not None:
if n_subsamples > n_samples:
raise ValueError("Invalid parameter since n_subsamples > "
"n_samples ({0} > {1}).".format(n_subsamples,
n_samples))
if n_samples >= n_features:
if n_dim > n_subsamples:
plus_1 = "+1" if self.fit_intercept else ""
raise ValueError("Invalid parameter since n_features{0} "
"> n_subsamples ({1} > {2})."
"".format(plus_1, n_dim, n_samples))
else: # if n_samples < n_features
if n_subsamples != n_samples:
raise ValueError("Invalid parameter since n_subsamples != "
"n_samples ({0} != {1}) while n_samples "
"< n_features.".format(n_subsamples,
n_samples))
else:
n_subsamples = min(n_dim, n_samples)
if self.max_subpopulation <= 0:
raise ValueError("Subpopulation must be strictly positive "
"({0} <= 0).".format(self.max_subpopulation))
all_combinations = max(1, np.rint(binom(n_samples, n_subsamples)))
n_subpopulation = int(min(self.max_subpopulation, all_combinations))
return n_subsamples, n_subpopulation
[docs] def fit(self, X, y):
"""Fit linear model.
Parameters
----------
X : numpy array of shape [n_samples, n_features]
Training data
y : numpy array of shape [n_samples]
Target values
Returns
-------
self : returns an instance of self.
"""
random_state = check_random_state(self.random_state)
X, y = check_X_y(X, y, y_numeric=True)
n_samples, n_features = X.shape
n_subsamples, self.n_subpopulation_ = self._check_subparams(n_samples,
n_features)
self.breakdown_ = _breakdown_point(n_samples, n_subsamples)
if self.verbose:
print("Breakdown point: {0}".format(self.breakdown_))
print("Number of samples: {0}".format(n_samples))
tol_outliers = int(self.breakdown_ * n_samples)
print("Tolerable outliers: {0}".format(tol_outliers))
print("Number of subpopulations: {0}".format(
self.n_subpopulation_))
# Determine indices of subpopulation
if np.rint(binom(n_samples, n_subsamples)) <= self.max_subpopulation:
indices = list(combinations(range(n_samples), n_subsamples))
else:
indices = [random_state.choice(n_samples, size=n_subsamples,
replace=False)
for _ in range(self.n_subpopulation_)]
n_jobs = _get_n_jobs(self.n_jobs)
index_list = np.array_split(indices, n_jobs)
weights = Parallel(n_jobs=n_jobs,
verbose=self.verbose)(
delayed(_lstsq)(X, y, index_list[job], self.fit_intercept)
for job in range(n_jobs))
weights = np.vstack(weights)
self.n_iter_, coefs = _spatial_median(weights,
max_iter=self.max_iter,
tol=self.tol)
if self.fit_intercept:
self.intercept_ = coefs[0]
self.coef_ = coefs[1:]
else:
self.intercept_ = 0.
self.coef_ = coefs
return self


hunch_net hunch_net-2005 hunch_net-2005-11 knowledge-graph by maker-knowledge-mining
Source: html
Introduction: Itâ€™s conference season, and smell of budding papers is in the air. IJCAI 2005 , January 21 COLT 2005 , February 2 KDD 2005 , February 18 ICML 2005 , March 8 UAI 2005 , March 16 AAAI 2005 , March 18
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same-blog 1 0.99999994 11 hunch net-2005-02-02-Paper Deadlines
Introduction: Itâ€™s conference season, and smell of budding papers is in the air. IJCAI 2005 , January 21 COLT 2005 , February 2 KDD 2005 , February 18 ICML 2005 , March 8 UAI 2005 , March 16 AAAI 2005 , March 18
2 0.36708033 387 hunch net-2010-01-19-Deadline Season, 2010
Introduction: Many conference deadlines are coming soon. Deadline Double Blind / Author Feedback Time/Place ICML January 18((workshops) / February 1 (Papers) / February 13 (Tutorials) Y/Y Haifa, Israel, June 21-25 KDD February 1(Workshops) / February 2&5 (Papers) / February 26 (Tutorials & Panels)) / April 17 (Demos) N/S Washington DC, July 25-28 COLT January 18 (Workshops) / February 19 (Papers) N/S Haifa, Israel, June 25-29 UAI March 11 (Papers) N?/Y Catalina Island, California, July 8-11 ICML continues to experiment with the reviewing process, although perhaps less so than last year. The S “sort-of” for COLT is because author feedback occurs only after decisions are made. KDD is notable for being the most comprehensive in terms of {Tutorials, Workshops, Challenges, Panels, Papers (two tracks), Demos}. The S for KDD is because there is sometimes author feedback at the decision of the SPC. The (past) January 18 de
3 0.34763205 145 hunch net-2005-12-29-Deadline Season
Introduction: Many different paper deadlines are coming up soon so I made a little reference table. Out of curiosity, I also computed the interval between submission deadline and conference. Conference Location Date Deadline interval COLT Pittsburgh June 22-25 January 21 152 ICML Pittsburgh June 26-28 January 30/February 6 140 UAI MIT July 13-16 March 9/March 16 119 AAAI Boston July 16-20 February 16/21 145 KDD Philadelphia August 23-26 March 3/March 10 166 It looks like the northeastern US is the big winner as far as location this year.
4 0.34658018 226 hunch net-2007-01-04-2007 Summer Machine Learning Conferences
Introduction: It’s conference season once again. Conference Due? When? Where? double blind? author feedback? Workshops? AAAI February 1/6 (and 27) July 22-26 Vancouver, British Columbia Yes Yes Done UAI February 28/March 2 July 19-22 Vancouver, British Columbia No No No COLT January 16 June 13-15 San Diego, California (with FCRC ) No No No ICML February 7/9 June 20-24 Corvallis, Oregon Yes Yes February 16 KDD February 23/28 August 12-15 San Jose, California Yes No? February 28 The geowinner this year is the west coast of North America. Last year ‘s geowinner was the Northeastern US, and the year before it was mostly Europe. It’s notable how tightly the conferences cluster, even when they don’t colocate.
5 0.31798142 422 hunch net-2011-01-16-2011 Summer Conference Deadline Season
Introduction: Machine learning always welcomes the new year with paper deadlines for summer conferences. This year, we have: Conference Paper Deadline When/Where Double blind? Author Feedback? Notes ICML February 1 June 28-July 2, Bellevue, Washington, USA Y Y Weak colocation with ACL COLT February 11 July 9-July 11, Budapest, Hungary N N colocated with FOCM KDD February 11/18 August 21-24, San Diego, California, USA N N UAI March 18 July 14-17, Barcelona, Spain Y N The larger conferences are on the west coast in the United States, while the smaller ones are in Europe.
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20 0.09732499 453 hunch net-2012-01-28-Why COLT?
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same-blog 1 0.98721755 11 hunch net-2005-02-02-Paper Deadlines
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2 0.80579066 226 hunch net-2007-01-04-2007 Summer Machine Learning Conferences
Introduction: It’s conference season once again. Conference Due? When? Where? double blind? author feedback? Workshops? AAAI February 1/6 (and 27) July 22-26 Vancouver, British Columbia Yes Yes Done UAI February 28/March 2 July 19-22 Vancouver, British Columbia No No No COLT January 16 June 13-15 San Diego, California (with FCRC ) No No No ICML February 7/9 June 20-24 Corvallis, Oregon Yes Yes February 16 KDD February 23/28 August 12-15 San Jose, California Yes No? February 28 The geowinner this year is the west coast of North America. Last year ‘s geowinner was the Northeastern US, and the year before it was mostly Europe. It’s notable how tightly the conferences cluster, even when they don’t colocate.
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4 0.78041649 422 hunch net-2011-01-16-2011 Summer Conference Deadline Season
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Introduction: After a major financial crisis , there is much discussion about how finance has become a casino gambling with other’s money, keeping the winnings, and walking away when the money is lost. When thinking about financial reform, all the many losers in the above scenario are apt to take the view that this activity should be completely, or nearly completely curtailed. But, a more thoughtful view is that sometimes there is a real sense in which there are right and wrong decisions, and we as a society would really prefer that the people most likely to make right decisions are making them. A crucial question then is: “What is the difference between gambling and rewarding good prediction?” We discussed this before the financial crisis . The cheat-sheet sketch is that the online learning against an adversary problem, algorithm, and theorems, provide a good mathematical model for thinking about this question. What I would like to do here is map this onto various types of financial t
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Introduction: The essential problem here is the large gap between experimental observation and theoretical understanding. Method K-fold cross validation is a commonly used technique which takes a set of m examples and partitions them into K sets (“folds”) of size m/K . For each fold, a classifier is trained on the other folds and then test on the fold. Problem Assume only independent samples. Derive a classifier from the K classifiers with a small bound on the true error rate. Past Work (I’ll add more as I remember/learn.) Devroye , Rogers, and Wagner analyzed cross validation and found algorithm specific bounds. Not all of this is online, but here is one paper . Michael Kearns and Dana Ron analyzed cross validation and found that under additional stability assumptions the bound for the classifier which learns on all the data is not much worse than for a test set of size m/K . Avrim Blum, Adam Kalai , and myself analyzed cross validation and found tha
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Introduction: Hal , Daniel , and I have been working on the algorithm Searn for structured prediction. This was just conditionally accepted and then rejected from ICML, and we were quite surprised. By any reasonable criteria, it seems this is an interesting algorithm. Prediction Performance: Searn performed better than any other algorithm on all the problems we tested against using the same feature set. This is true even using the numbers reported by authors in their papers. Theoretical underpinning. Searn is a reduction which comes with a reduction guarantee: the good performance on a base classifiers implies good performance for the overall system. No other theorem of this type has been made for other structured prediction algorithms, as far as we know. Speed. Searn has no problem handling much larger datasets than other algorithms we tested against. Simplicity. Given code for a binary classifier and a problem-specific search algorithm, only a few tens of lines are necessary to
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Narcotics case: Rana Sanaullah's judicial remand extended till Nov 16
by https://www.facebook.com/dunyanewsLAHORE (Dunya News) – An Anti-Narcotics Court has on Saturday extended Pakistan Muslim League-Nawaz (PML-N) Punjab President Rana Sanaullah’s judicial remand till November 16.
Duty judge Khalid Bashir conducted the hearing. Call Data Record (CDR) of the investigation officer was submitted in the court. Rana Sanaullah’s counsels also requested the court take action over their client’s plea to hand over the seized car.
The PML-N leader’s wife talked to media inside the court premises and reiterated support for Jamiat Ulema-e-Islam-Fazal (JUI-F) Chief Fazal-ur- Rehman’s Azadi March while terming Imran Khan as selected prime minister.
Earlier, the Anti-Narcotics Force (ANF) had challenged trial court’s decision of not hearing heroin smuggling case against Rana Sanaullah on daily basis in the Lahore High Court (LHC).
The petition was filed by the ANF legal director maintaining that a drug trafficking case was lodged against the PML-N leader on July 1 and the challan was timely submitted.
The ANF took the stance that the trial court, contrary to facts, rejected the plea seeking hearing on daily basis. The ANF requested the Lahore High Court to nullify the trial court’s decision and allow conducting hearing on daily basis.