Kang Daniel tops idol ranking chart for a whopping 85 weeks in a row
by olmalKang Daniel ranked 1st on the idol ranking chart for the 85th week in a row.
Kang Daniel topped the 'Idol Chart' with 97,508 votes, making him #1 for the 85th consecutive week. Right behind him at #2 was BTS' Jimin with 64,152 votes, V at 3rd with 46,330 votes, Jungkook at 4th with 19,573 votes, and Jin at 5th with 14,596 votes.
Lai Kuan Lin also made the list at 6th with 10,487 votes, Ha Sung Woon at 7th with 9,928 votes, trot star Song Ga In at 8th with 8,843 votes, AB6IX's Park Woo Jin at 9th with 7,276 votes, and NUEST's Minhyun at 10th with 4,415 votes.
Congratulations to Kang Daniel!


Racoon City PD
Straight from RE2. Uncanny ain't it.  |   Build Credit: Ckwinn
Straight from RE2. Uncanny ain't it.  |   Build Credit: Ckwinn
A more modern take on a pool.  |   Build Credit: Retr0grey
Yes, lighthouses were built too.  |   Build Credit: Korl
You can't have a town without food.   |   Build Credit: thenerdoflight
A more modern take on a pool but at night.  |   Build Credit: Retr0grey
This guy loves quartz.   |   Build Credit: Ckwinn
He really loves quartz.   |   Build Credit: Ckwinn
Seriously, he loves quartz.  |   Build Credit: Ckwinn
Loving quartz at night   |   Build Credit: Ckwinn


Browser Differences
In recent work I've been using Chrome, Firefox and IE8. To be honest with you there doesn't seem to be much difference between their implementations of CSS 2.1. They all have a few quirks here and there, but they basically behave as their meant to.
| Browser | Market Share |
|---|---|
| IE6 | 26% |
| IE7 | 20% |
| IE8 | 19% |
| Firefox | 24% |
| Safari | 4% |
| Chrome | 3% |
| Opera | 2% |
| Other | 2% |
This is good news if you want to develop a website with a CSS based design. However it is still necessary to make your website function with older browsers, in particular the lamentable IE6.
Browser Reset
Lots of the cross browser differences happen because of difference in browsers' default style. What happens is you develop in Firefox, say, and without realising come to rely on some parts of Firefox's default css. When you look in Chrome or IE8 you then see subtle differences in the positioning of the elements. The way to avoid this is to use a browser reset, which sets all the elements to have a common style. A basic reset sets the margin and padding to zero on all elements:
* {
margin:0;
padding:0;
}
More thorough, and better considered resets are Erik Meyer and YUI. You put the reset in before you begin developing, and tweak it for your own needs.
IE8 Compatibility Mode
IE8 has a compatibility mode which renders a web page "like IE7". By default IE8 will render localhost and the internet in IE8 standards mode, but will render the intranet in compatibility mode. To force IE8 into standards mode all the time add the following meta tag to the head section in your document:
<meta http-equiv="X-UA-Compatible" content="IE=EmulateIE8" />
IE6 The Horror
The best resource I found dealing with IE6 is the Ultimate IE6 Cheatsheet. Some good general advice it contains is:
- Develop in standards compliant browsers first. The compliant browsers all render in a fairly similar way, so you start off in a good position. Also you learn how to do CSS properly, before learning hacks.
- Validate your xhtml and css.
- Use jQuery. This irons out many cross browser Javascript incompatibilities.
- Use a correct doctype. This stops IE6 quirks mode, and in particular means the box model will be correct.
- Use a conditional comment to add an IE6 specific "hacks" stylesheet. This concentrates the IE6 weirdness in a single place and stops it polluting the main style. The following code adds Ie6Hacks.css if the browser is less than or equal to IE6. You put it in the head element:
<!--[if lte IE 6]> <link rel="stylesheet" type="text/css" href='Ie6Hacks.css' /> <![endif]-->
It's also helpful to understand exactly what IE6 is meant to be able to do. This document shows the CSS compliance of IE 5,6,7 and 8.
There are 119 documented IE6 bugs. The Ultimate IE6 Cheatsheet covers 25 of the most common, but your quite likely to find more. If something odd is happening, the best advice is to keep googling; it's bound to have been seen and solved already. Some of the IE6 issues we had on our most recent project were:
- IE6 select z-index bug. The bug is "You have a select box on the main page. When you open a pop-up the select box shows through into the pop-up." There is no CSS based fix for this bug. Fortunately we were using jQuery dialogs, which have the bgiframe option to specifically fix this problem. When the dialog opens, bgiframe covers the select boxes with iframes which stops showing through.
- IE6 invisible text next to a floated right element. The bug text to the left of a right floated element turned invisible. The bodge is to a position:relative to the container containing the text.
- Incorrect cursor on hyper-links. For some reason hyper-links in IE6 and IE7 didn't have the pointer cursor (which looks like a hand), but instead had the text cursor. The fix was to reapply the pointer cursor to the a element: a { cursor:pointer; }
- Menu lists stacked vertically instead of horizontally. It's fairly common to use an unordered list to represent menu items for site navigation. Our initial css used float:left on the <ul> and <li> elements to make the list items render horizontally, across the top of the page. This didn't work in IE6, which stubbornly showed a vertical list. The solution was to change the <ul> and <li> elements to display:inline; as described in this Taming Lists article.


Education
- Bachelor's of Arts in International Relations
- University of South Florida - Tampa, FL
- Graduated: Dec. 2011
- Master's of Business Administration
- American Public University - Charles Town, WV
- Still Working
Previous Employment
- Boeing Employer's Credit Union
- Mortgage Sales Assistant
- Navy Federal Credit Union
- Member Service Representative III - MLO
My Top 10 Places I Plan To Visit
Not all those who wander are lost - J.R.R Tolkien
- Iceland
- Singapore
- Amsterdam
- Back to Italy
- Dubai
- Las Vegas
- San Diego
- Hawaii
- Okinawa and Back to Japan
- Philadelphia


HackCville's partners and sponsors:
"HackCville is an incredible institution", a "unicorn", and "like nothing else at any university we work with."
- Brendan Collins, College Recruiter at Google
Here's how your company can connect with our students →


In order to submit your score please visit the Department of Environmental Health webpage and read about the program. Click the button that says "Enroll Now" to submit your score.
This project looks to map the energy efficiency of the commercial buildings in denver that are over 5,000 square feet. If you would like to learn more please check out our about us page.
Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.


load(script, @optional force_compile)
Load the object code file named script.oN
. If it is not found look for the file script.sn
,
compile it to intermediate language and load it into the runtime system.
If force_compile
is true
, the file script.sn
is compiled even if a previous version
of the intermediate file exists.
Return the name of the compiled script file.
// hello.sn
showln("hello, world")
The above script can be compiled into intermediate language representation and loaded into the current program by,
load("hello")


| Network | Mask | NAT IP | Owner | Type | Edit | Delete |
|---|---|---|---|---|---|---|
| {{network.Network}} | {{network.Mask}} | {{network.NATIP}} | {{network.Owner}} | {{network.Type}} |
|
|
| Network | Mask | NAT IP | Owner | Type | Edit | Delete |
|---|---|---|---|---|---|---|
| {{network.Network}} | {{network.Mask}} | {{network.NATIP}} | {{network.Owner}} | {{network.Type}} |
|
|


[1]
the girls on reception were very good as were the young guys in the redwood bar/lounge .
[2]
hotel that is very much to our liking with a lovely reception floor and helpful staff .


To comply with the requirements of the Family Educational Rights and Privacy Act (FERPA). In compliance with FERPA, personally identifiable information obtained by volunteer in performance of MESA events and activities will not be re-disclosed to third parties without written consent of the student’s parent/guardian, and will only be used for the purposes identified in this policy.
MESA is protected service mark that has been registered with the US Patent and Trademark Office and the California Secretary of State by the Regents. Oregon MESA and Portland State University has been granted a non-exclusive, non-assignable, revocable, royalty-free, and non-transferable license of the MESA service mark and program model by The Regents. Use of the MESA service mark is prohibited unless prior written approval granted by the Regents of the University of California.
Oregon MESA will protect the student’s right to their invention and design, and grants sole ownership as the student’s creation and property.
Any user of the MESA Everyday Application agree to the above policies. In addition, the user agrees to treat the system, system owners, other users, and MESA Staff or contractors with respect when using the MESA Everyday Application. The user agrees to abide by, and are subject to any policies set forth by Oregon MESA including but not limited to acceptable use, IP, brand protection, harassment, professional conduct and anti-discrimination policies.


should not touch this:
if below SVG is inlined correctly we can reference its content:
Deep Replace
Inline images
= $foo->bar; ?>


Fatherland is set in an alternative world where Hitler has won the Second World War. It is April 1964 and one week before Hitler's 75th birthday. Xavier March, a detective of the Kriminalpolizei, is called out to investigate the discovery of a dead body in a lake near Berlin's most prestigious suburb. As March discovers the identity of the body, he uncovers signs of a conspiracy that could go to the very top of the German Reich. And, with the Gestapo just one step behind, March, together with an American journalist, is caught up in a race to discover and reveal the truth - a truth that has already killed, a truth that could topple governments, a truth that will change history.
Thick cloud had pressed down on Berlin all night, and now it was lingering into what passed for the morning. On the city's western outskirts, plumes of rain drifted across the surface of Lake Havel, like smoke.


Create an Intuit account
One Account for all of Intuit's products
including Mint. Learn more
By clicking Create Account, you agree to our
Terms of Service and have read and acknowledge
our Privacy Statement
our Privacy Statement
Invisible reCAPTCHA by Google Privacy Policy and Terms of Use.


For example, create a folder called SpryAssets in the root folder of your web site, and move the SpryValidationConfirm.js file to it. The SpryValidationConfirm.js file contains all of the information necessary for making the Confirm widget interactive.

Make sure that the file path to the SpryValidationConfirm.js file is correct. This path varies depending on where you’ve placed the file in your web site.
<link href="SpryAssets/SpryValidationConfirm.css" rel="stylesheet" type="text/css" />
Make sure that the file path to the SpryValidationConfirm.css file is correct. This path varies depending on where you’ve placed the file in your web site.
<input type="password" id="password1" name="password1" />
<input type="password" id="password1" name="password1" /> <input type="password" name="fieldName" value="" />
<input type="password" id="password1" name="password1"/>  <input type="password" name="fieldName" value=""/> >

The first required value in the constructor is the ID of the widget container. The second required value is the ID of the password field that is being confirmed.
Make sure that the ID of the Confirm widget’s container span tag matches the ID parameter you specified in the Spry.Widgets.ValidationConfirm method. Make sure that the JavaScript call comes after the HTML code for the widget.
The complete code looks as follows:
 ...  <link href="includes/SpryValidationConfirm.css" rel="stylesheet" type="text/css" /> ...   ... <input type="password" id="password1" name="password1" />  <input type="password" name="fieldName" value=""/>   ...


Check Administration
Sign in with Slack
Sign in with Twitter
Sign in with Facebook
Sign in with e-mail
Email address
Password (minimum 8 characters)
Two-Factor Authentication Token
Sign in »


{% extends "base.html" %} {% block content %}
Please log in using your OpenID. Enter your OpenID url or select one of the providers below.


Gecode::DFS< T > Class Template Reference
[Search engines]
#include <search.hh>
Inherits Gecode::Search::DFS.
Inherited by Gecode::Restart< T >.
Detailed Description
template<class T>
class Gecode::DFS< T >
Depth-first search engine.
This class supports depth-first search for subclasses T of Space.
Definition at line 389 of file search.hh.
Public Member Functions | |
| DFS (T *s, unsigned int c_d=Search::Config::c_d, unsigned int a_d=Search::Config::a_d, Search::Stop *st=NULL) | |
| Initialize search engine. | |
| T * | next (void) |
| Return next solution (NULL, if none exists or search has been stopped). |
Constructor & Destructor Documentation
|
|
Initialize search engine.
|
Member Function Documentation
|
|
Return next solution (NULL, if none exists or search has been stopped).
Reimplemented from Gecode::Search::DFS. Reimplemented in Gecode::Restart< T >. |
The documentation for this class was generated from the following files:
- gecode/search.hh (Revision: 3516)
- gecode/search/dfs.icc (Revision: 3511)


Version 0.01
Quick summary of what the module does.
Perhaps a little code snippet.
use Bubble::Bubble;
my $foo = Bubble::Bubble->new(); ...
A list of functions that can be exported. You can delete this section if you don't export anything, such as for a purely object-oriented module.
Create a new object representing the Bubble::Bubble output. usually called from Bubble::Parse->next
my $bp = Bubble::Bubble->new( -csv_obj => Tie::Handle::CSV line object -seq_obj => Bio::Seq object -csv_headers => array ref of headers in the csv file -seq_headers => array ref of info in the fasta file header );
returns an array ref of the path names in this bubble =cut
sub paths{ my $self = shift; $$self{_paths}; }
get returns attributes for the bubble, from the data portion in the csv or the sequence portion in the fasta file
returns Bio::Seq object of path sequence
Dan MacLean, <maclean.daniel at gmail.com>
Please report any bugs or feature requests to bug-bubble-parse at rt.cpan.org
, or through
the web interface at http://rt.cpan.org/NoAuth/ReportBug.html. I will be notified, and then you'll
automatically be notified of progress on your bug as I make changes.
You can find documentation for this module with the perldoc command.
perldoc Bubble::Parse
You can also look for information at:
Copyright 2013 Dan MacLean.
This program is free software; you can redistribute it and/or modify it under the terms of the the Artistic License (2.0). You may obtain a copy of the full license at:
http://www.perlfoundation.org/artistic_license_2_0
Any use, modification, and distribution of the Standard or Modified Versions is governed by this Artistic License. By using, modifying or distributing the Package, you accept this license. Do not use, modify, or distribute the Package, if you do not accept this license.
If your Modified Version has been derived from a Modified Version made by someone other than you, you are nevertheless required to ensure that your Modified Version complies with the requirements of this license.
This license does not grant you the right to use any trademark, service mark, tradename, or logo of the Copyright Holder.
This license includes the non-exclusive, worldwide, free-of-charge patent license to make, have made, use, offer to sell, sell, import and otherwise transfer the Package with respect to any patent claims licensable by the Copyright Holder that are necessarily infringed by the Package. If you institute patent litigation (including a cross-claim or counterclaim) against any party alleging that the Package constitutes direct or contributory patent infringement, then this Artistic License to you shall terminate on the date that such litigation is filed.
Disclaimer of Warranty: THE PACKAGE IS PROVIDED BY THE COPYRIGHT HOLDER AND CONTRIBUTORS "AS IS' AND WITHOUT ANY EXPRESS OR IMPLIED WARRANTIES.  UNLESS REQUIRED BY LAW, NO COPYRIGHT HOLDER OR CONTRIBUTOR WILL BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES ARISING IN ANY WAY OUT OF THE USE OF THE PACKAGE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.


-- Display all the employees from the employees table
SELECT * FROM employees;
-- Display the column names, datatype and constraints for the employees table
DESCRIBE employees;
-- Display all the employees who are born before 1950-01-01
SELECT * FROM employees WHERE birthdate < "1950-01-01";
-- Display the number of employees who are born before 1960-01-01
SELECT COUNT(employeeid) FROM employees WHERE birthdate < "1960-01-01";
-- Display lastname and firstname of the table employees
SELECT lastname, firstname FROM employees;
-- Display firstname (displayed as nickname) and lastname of the table employees
SELECT firstname AS "nick name",lastname FROM employees;
-- Display the number of employees (displayed as "number of employees") from the table employees
SELECT COUNT(employeeid) AS "number of employees" FROM employees;
-- Display the productname (displayed as product) and the price (displayed as cost) from the table products
SELECT productname as products, price as cost FROM products;
-- Display the productname from the table products and the suppliername from the table suppliers where supplierid is the same in both table
SELECT products.productname, suppliers.suppliername FROM suppliers JOIN products ON suppliers.supplierid=products.supplierid;
-- Create a view named allprice to display productname and price from the table products
CREATE VIEW allprice AS SELECT productname, price FROM products;
-- Display the view allprice
SELECT * FROM allprice;
-- delete the view allquantities
DROP VIEW IF EXISTS allquantities;
-- Create a view named allquantities to display productid and quantity from the table orderdetails
CREATE VIEW allquantities AS SELECT productid, quantity FROM orderdetails;
-- Display the view allquantities
SELECT * FROM allquantities;
-- Display the count, the sum, the maximum, the minimum, the average of price for all the products
SELECT COUNT(price), SUM(price), MAX(price), MIN(price), AVG(price) FROM products;
-- Display the count (displayed as count), the sum (displayed as sum), the maximum (displayed as maximum), the minimum (displayed as minimum), the average (displayed as average) of price for the products where the price is lower than 30
SELECT COUNT(price) as count, SUM(price) as sum, MAX(price) as maximum, MIN(price) as minimum, AVG(price) as average FROM products WHERE price;
-- Goal find statistic of the products that we have sold
-- Display the count (displayed as count), the sum (displayed as sum), the maximum (displayed as maximum), the minimum (displayed as minimum), the average (displayed as average) of price for the products where productid is the same as in orderdetails
SELECT COUNT(price) as count, SUM(price) as sum, MAX(price) as maximum, MIN(price) as minimum, AVG(price) as average FROM products JOIN orderdetails ON products.productid=orderdetails.productid;
-- Create a view name statistic to Display the count (displayed as count), the sum (displayed as sum), the maximum (displayed as maximum), the minimum (displayed as minimum), the average (displayed as average) of price for the products where productid is the same as in orderdetails
CREATE VIEW statistic AS SELECT COUNT(price) as count, SUM(price) as sum, MAX(price) as maximum, MIN(price) as minimum, AVG(price) as average FROM products JOIN orderdetails ON products.productid=orderdetails.productid;
-- Display the view statistic
SELECT * FROM statistic;
-- Display the maximum from the view statistic
SELECT maximum FROM statistic;
-- find total price of each category
-- Display categoryid, sum of the price from the products table group by categoryid
SELECT categoryid, sum(price) FROM products GROUP by categoryid


Hi all,
I set up a basic monitoring system a couple of months back, using a raspberry pi as base station. It was all working fine. The pi came preloaded so I just plugged it in, found the ip address using Fing, and could then set it up using ip address/emoncms. All good.
About a week ago something went wrong and I can nolonger access the pi. I can't even find its IP address using fing. I have tried swapping ethernet cables, ports on my route, but no luck.
There is one IP address on fing which I can't identify, <IP_ADDRESS>, "Cisco", could this be it? I seem to recall the name came out as "pi". When I try to access it (http://<IP_ADDRESS>/emoncms), it doesn't work.
I'm a bit confused now as to the setup for the Pi, as the instruction pages seem to have changed since I set mine up back in Aug/Sept.
Chris
Re: Raspberry Pi - stopped working, can't find IP address
It sounds you have had your SD card fail. This was a common problem when running a full emoncms logging server on the Pi. The SD card gets worn out. This is why we have changed to using the new gateway read-only file system. The change is explained in this post: http://openenergymonitor.blogspot.com/2013/09/raspberrypi-sd-cards-hdd-gateway.html. Another option would be to use a USD external hard drive with the Pi
Re: Raspberry Pi - stopped working, can't find IP address
Hi Glyn,
Thanks for the reply.
Are you saying that the SD card is dead and I need a new one (for either of the two options)?
Chris
Re: Raspberry Pi - stopped working, can't find IP address
Following this, if I understand correctly, for the Rock Solid Gateway approach, the next step is to write the firmware image onto a (possibly new) SD card. I have essentially zero raspberry pi knowledge, but I understand this would have to be done using an SD card reader, then put the card into the pi (i.e., I can't directly write anything to the Pi).
Chris
Re: Raspberry Pi - stopped working, can't find IP address
Hi Chris, yes unfortunately you will need a working SD card regardless of which option you use, as the RaspPi is configured to at least boot from one.
I would remove and test the card, see if it will re-format. If so, great.
If not....... well decide how you want to run your future system, and if it's just going to be to boot your rootfs (ie a USB HDD like mine), you will only need a SD card size of at least 128MB.
If you go for the gateway system - as per Glyn's post above, you will need at least a 4GB SD card.
Paul


František Farka, Ekaterina Komendantskaya,
and Kevin Hammond.
Proof-relevant Horn Clauses for Dependent Type Inference and Term Synthesis
.
To appear in 34nd International Conference on Logic Programming (ICLP 2018),
Oxford, UK, July 14 to July 17, 2018
František Farka, Ekaterina Komendantskaya, Kevin
Hammond.
Coinductive Soundness of Corecursive
Type Class Resolution
.
In Logic-Based Program Synthesis and Transformation - 26th International
Symposium, LOPSTR 2016, Edinburgh,
Scotland, UK, September 6-8, 2016. Revised
Selected Papers
, LNCS volume 10184. Springer 2017.
František Farka, Ekaterina Komendantskaya, Kevin
Hammond and Peng Fu.
Coinductive Soundness of Corecursive
Type Class Resolution
.
In Pre-proceedings of the 26th International Symposium on Logic-Based
Program Synthesis and Transformation (LOPSTR 2016)
2016.
František Farka.
Maintainable type classes for Haskell
.
M.Sc. Thesis. Charles University: Czech
Republic. 2014.


More examples are in
mop-specs.html
. This file has examples that the test suite framework doesn't currently support, because they run asynchronously or because they write their results to the console. Check the console to see the run results.


| DOSE: |
1200 mg |
oral |
DXM |
(capsule) |
1200 mg of DXM were ingested on an empty stomach in the form of 40 Drixoral gelcaps.
Waiting for the effects to take hold, I worked on some noise compositions with my 4-track recorder. After about 45 minutes, I felt nauseated and as though I had a fever. I no longer had the ability or desire to concentrate on my compositions, so I set the recorder aside and lay back on the bed.
The naseau and feelings of vague but potent physical discomfort increased. I wondered if the dosage would be too much for me to handle. Some ten minutes later, I stumbled drunkenly to the bathroom and vomitted. The discomfort vanished almost immediately; I returned to bed, no longer afraid of being unable to handle the experience.
I do not remember how long it took me to become almost fully dissociated from my body, nor do I remember what happened during the process. Soon, however, I found myself beholding fully three-dimensional crystalline formations, the components of which rotated slowly in synch with one another. Behind the formations there seemed to be a void of infinite space, which flashed strobe-like in brilliant colors.
As the formations rotated, they changed and evolved, always producing beauty and symmetry with mathematical precision, determinacy, and clarity. Only vaguely aware of my body, I felt as though I was soaring through the patterns at unimaginable speeds. Gradually, I moved through the crystalline formations: they seemed to each contain the enormity of the universe itself.
My speed increased, as did the gradual loss of a sense of identity. The patterns gave way to more abstract but no less colorful patterns: wave upon wave of interference patterns, cyclones of flashing colors and spirals that swallowed me. After some time, the boundary between myself and the patterns dissolved almost completely.
Now my being -- which was really a universal 'we' as opposed to an individual identity -- seemed to contract into a single point then explode outward countless times, the infinity of space and time and perception and being contained within each explosion. 'We' were the whole of the multidimensional universe collapsing upon itself and exploding outward over eons of unimaginable time, terrified, relentless, ecstatic. Once in awhile the explosions resulted in vortexes, through which something utterly 'alien' seemed to emerge.
I recall approaching and merging with these 'alien beings' several times, though I do not recall what happened during the merge itself. One such being I recall only in association with a sense of vastness and strange angularity, like a huge mountain tapering to a perfect point.
Sometime later (I do not remember how long), a sense of identity as well as an awareness of my body returned -- at first in brief moments, then for longer episodes. During these moments, I asked 'who am I?' I received a flood of intuitive information, very little of which I was able to comprehend rationally. The gist of the matter, however, was that I was both an individual and the whole of creation; both the creator and the created, and that this is true for all beings.
Remembering that viewing my self and life from my first DXM experience had been one of the most emotionally profound experiences of my life, I attempted to do so again. Now I had a vision of myself as a ribbon or cord wrapped around itself and around other cords. The cords traced the history of my life, and once again I felt an all-encompassing compassion and love for that life, self, and everything within it. Again, I was aware of the possibility of abandoning it and not returning to it, and it struck me as the most precious of all things; I was even more horrified at the thought of leaving it than I had been on the first time.
To see if I could identify the 'cord' of another -- for the universe had become a network of these cords -- I 'called' to my friend Betty. I witnessed her cord and mine separating from a common cord, then rejoining each other in a dance or braiding, yet still retaining their separate identities.
This aspect of the experience was emotionally overwhelming in a way that I really cannot convey; when I chose to end the experience, I did so because I could no longer bear its sheer intensity.
I managed to open my eyes; the sunlight made the room appear maddeningly bright. I could recognize few features: the room was a patchwork collage of textures, shapes, and colors that were sparkling, glittering, and pulsating.
When I closed my eyes, it seemed I still had them open and was looking at the ceiling.
Now what looked as though it were the ceiling gently fell apart into chunks of abstract shapes. The shapes 'morphed' into other ceilings of other rooms similar to my own. Just as each one attained such a level of coherency and clarity that I felt I would be able to stand up and walk around, the room would fall apart then reform into another. One such room attained coherency for longer than the rest; it was dimly lit, as though by candle light, and it seemed to be some sort of basement. There were three others in the room, watching me -- I wondered if I was experiencing some sort of alternate self, who was also experimenting with dissociative states, but in the presence of others. In this room, I was able to sit up for a moment -- how odd it was to sit up and look about me while still feeling the weight of my elbow over my eyes.
Two times, perhaps more, the rooms transformed into seemingly 'alien universes'. Once, I found myself beneath a tree of huge orange flowers. Each blossom had a face; three of them were watching me, remarking without speaking about what a ridiculous sight I was. Another time, I was running through a labyrinth of stones that were somehow plant-like and alive. I understood that I was searching for God within the labyrinth; the labyrinth seemed to reply that God could never be found within it, though the path I took through the labyrinth in my search _was_ God.
I still wondered, nonetheless, whether I could 'call' some representation of Divinity to my presence. The shapes formed an angular and somewhat abstract illustration of a female, crone-like face. The face, like the rooms, cycled relentlessly from one form to another. I tried to speak to the face, but the visions seemed too incoherent to produce a response -- though I got the impression the incoherency itself was an aspect of my own being.
After some time of this, I regained enough awareness of my body to stay in the here-and-now for as long as I chose. I managed to pick up and dial a phone to call my friend Libby to come by or pick me up -- I felt somewhat shellshocked from this experience and no longer wished to be alone.
Shortly after calling Libby, I couldn't remember whether I had actually called her, or, if she had, whether she agreed to pick me up. She arrived about forty minutes later; I staggered down the stairs of my apartment in what seemed like a dream from which I could not awaken.
The next few hours were spent drifting in and out of my body and of the crystalline formations with which the trip had begun. Each time I closed my eyes, I felt as though I shot through space terrifyingly fast. When I was able to speak, I attempted to relate to Libby the nature of my experience. I found it difficult to keep track of what I had just said.
After the DXM had worn off the point that I could move around on my own and interact with others in a somewhat coherent way, I smoked some marijuana. The THC had the effect of ending my grogginess almost immediately. I became extremely hyper -- it was not at all unlike a dissociated version of a cocaine rush. I felt as though the whole world had turned into a video game and I had tremendous fun rushing from room to room as though an animated character in some comptuer-game scenario.
After I'd settled down a bit, I tried again to relate my experiences to Libby. This time, a received a flood of rational knowledge about the nature of the manifestation of duality from unity, the emergence and nature of consciousness and of language. Still simultaneously hyper and detached, I spoke endlessly to Libby about these subjects, as though it was vital that she know them. She was blessedly patient, and, after I had come down more solidly, drove me home.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


--- layout: page ---
Home › Resources › Sermons
{{post.title}}
{{post.date | date: "%-m/%-d/%y"}}
{{post.speaker}}
{{post.verse}}


Congratulations!
You're done!
Just copy & paste the script below into your app!
<script src="https://subdomain.hoodieapp.com/_api/_files/hoodie.js"> </script>
You can manage your app here: (this is for your eyes only)
https://subdomain-74893373298.hoodieapp.com
Instructions per mail?


What a management user is permitted to do is determined by the roles to which the user is assigned. A system of includes and excludes based on the user membership determines to which role a user belongs.
Un utilisateur est associé à un rôle si :
Les exclusions ont priorité sur les inclusions.


My Tasks
| Lead Name | Due Date | Status | Last Modified | Complete | |
|---|---|---|---|---|---|
| Michael | 12/3/2015 | Opportunity |<EMAIL_ADDRESS>| 12/3/2015 | |
| Michael | 12/3/2015 | Opportunity |<EMAIL_ADDRESS>| 12/3/2015 | |
| Michael | 12/3/2015 | Opportunity |<EMAIL_ADDRESS>| 12/3/2015 | |
| Michael | 12/3/2015 | Opportunity |<EMAIL_ADDRESS>| 12/3/2015 |
Comment section here


|
DataStructures
|
Implements a priority queue based on a binary-heap Characteristics: Space Complexity: O(n) Time Complexity: More...
#include <PriorityQueue.h>
Classes | |
| struct | PriorityQueueImpl |
| Internal implementation of the container. More... | |
Public Types | |
| using | value_type = T |
| using | size_type = std::size_t |
| using | difference_type = std::ptrdiff_t |
| using | reference = value_type & |
| using | const_reference = const value_type & |
| using | pointer = value_type * |
| using | const_pointer = const value_type * |
| using | allocator = AllocatorSimple< value_type > |
Public Member Functions | |
| PriorityQueue (void)=default | |
| Default Constructor. More... | |
| PriorityQueue (size_type capacity) | |
| Explicit Constructor. More... | |
| ~PriorityQueue (void) | |
| Destructor. More... | |
| PriorityQueue (const PriorityQueue &other) | |
| Copy Constructor. More... | |
| PriorityQueue & | operator= (const PriorityQueue &other) |
| Copy assignment operator. More... | |
| size_type | height (size_type index) |
| Return the height of the sub-tree. More... | |
| value_type * | top (void) |
| Access the top element O(1) More... | |
| const value_type * | top (void) const |
| Access the top element O(1) More... | |
| constexpr bool | empty () const noexcept |
| Checks if the container is empty. More... | |
| constexpr size_type | size () const noexcept |
| Size of the container. More... | |
| constexpr size_type | capacity () const noexcept |
| Capacity of the container. More... | |
| void | reserve (size_type new_cap) |
| Allocate new storage. More... | |
| void | shrink_to_fit () |
| Shrinks the container to its size. More... | |
| void | clear () noexcept |
| Clears the container of its elements. Does not change reserved memory (capacity). More... | |
| void | push (const value_type &value) |
| Push a new element to the container. More... | |
| void | pop (void) |
| Pops an element from the container. More... | |
| void | print (void) const |
| Logs the container. More... | |
Protected Attributes | |
| PriorityQueueImpl | m_impl |
| Container implementation. More... | |
| allocator | m_allocator |
| Allocator. More... | |
Implements a priority queue based on a binary-heap Characteristics: Space Complexity: O(n) Time Complexity:
| T | the data type of the elements |
| using DS::PriorityQueue< T, isMin >::allocator = AllocatorSimple<value_type> |
| using DS::PriorityQueue< T, isMin >::const_pointer = const value_type* |
| using DS::PriorityQueue< T, isMin >::const_reference = const value_type& |
| using DS::PriorityQueue< T, isMin >::difference_type = std::ptrdiff_t |
| using DS::PriorityQueue< T, isMin >::pointer = value_type * |
| using DS::PriorityQueue< T, isMin >::reference = value_type & |
| using DS::PriorityQueue< T, isMin >::size_type = std::size_t |
| using DS::PriorityQueue< T, isMin >::value_type = T |
|
default |
Default Constructor.
|
explicit |
Explicit Constructor.
| capacity | the initial capacity of the queue |
| DS::PriorityQueue< T, isMin >::~PriorityQueue | ( | void | ) |
Destructor.
| DS::PriorityQueue< T, isMin >::PriorityQueue | ( | const PriorityQueue< T, isMin > & | other | ) |
Copy Constructor.
| other | the container to copy |
|
inlinenoexcept |
Capacity of the container.
|
noexcept |
Clears the container of its elements. Does not change reserved memory (capacity).
|
inlinenoexcept |
Checks if the container is empty.
| PriorityQueue< T, isMin >::size_type DS::PriorityQueue< T, isMin >::height | ( | size_type | index | ) |
Return the height of the sub-tree.
| PriorityQueue< T, isMin > & DS::PriorityQueue< T, isMin >::operator= | ( | const PriorityQueue< T, isMin > & | other | ) |
Copy assignment operator.
| other | the container to copy assign |
| void DS::PriorityQueue< T, isMin >::pop | ( | void | ) |
Pops an element from the container.
| void DS::PriorityQueue< T, isMin >::print | ( | void | ) | const |
Logs the container.
| void DS::PriorityQueue< T, isMin >::push | ( | const value_type & | value | ) |
Push a new element to the container.
| value | the data to insert |
| void DS::PriorityQueue< T, isMin >::reserve | ( | size_type | new_cap | ) |
Allocate new storage.
| new_cap | the size of the new storage |
| void DS::PriorityQueue< T, isMin >::shrink_to_fit | ( | ) |
Shrinks the container to its size.
|
inlinenoexcept |
Size of the container.
|
inline |
Access the top element O(1)
|
inline |
Access the top element O(1)
|
protected |
Allocator.
|
protected |
Container implementation.


Have a go at getting the multiple that doesn't match.
Can you see what fraction is shaded in red?
Can you convert a digital clock into analouge time?


ML-ENSEMBLE
| author: | Sebastian Flennerhag |
|---|---|
| copyright: | 2017-2018 |
| license: | MIT |
Computational graph module for memory-neutral parallel processing of deep general-purpose ensembles.
Implements backend graph managers, base classes for interacting with graph managers, and job managers for preprocessing pipelines and estimators, as well as handles for multiple instances and wrappers for standard parallel job calls.
mlens.parallel¶
Graph Nodes¶
Layer¶
-
class
mlens.parallel.layer.
Layer
(name=None, propagate_features=None, shuffle=False, random_state=None, verbose=False, stack=None, **kwargs)[source]¶ Bases:
mlens.parallel.base.OutputMixin
,mlens.parallel.base.IndexMixin
,mlens.parallel.base.BaseStacker
Layer of preprocessing pipes and estimators.
Layer is an internal class that holds a layer and its associated data including an estimation procedure. It behaves as an estimator from an Scikit-learn API point of view.
Parameters: - propagate_features (list, range, optional) – Features to propagate from the input array to the output array. Carries input features to the output of the layer, useful for propagating original data through several stacked layers. Propagated features are stored in the left-most columns.
- verbose (int or bool (default = False)) –
level of verbosity.
verbose = 0
silent (same asverbose = False
)verbose = 1
messages at start and finish (same asverbose = True
)verbose = 2
messages for preprocessing and estimatorsverbose = 3
messages for completed job
If
verbose >= 10
prints tosys.stderr
, elsesys.stdout
. - shuffle (bool (default = False)) – Whether to shuffle data before fitting layer.
- random_state (obj, int, optional) – Random seed number to use for shuffling inputs
- **kwargs (optional) – optional arguments to
BaseParallel
.
-
data
¶ Cross validated scores
-
indexers
¶ Check indexer
-
learners
¶ Generator for learners in layer
-
raw_data
¶ Cross validated scores
-
set_output_columns
(X, y, job, n_left_concats=0)[source]¶ Compatibility method for setting learner output columns
-
transformers
¶ Generator for learners in layer
Learner¶
-
class
mlens.parallel.learner.
Learner
(estimator, indexer=None, name=None, preprocess=None, attr=None, scorer=None, proba=False, **kwargs)[source]¶ Bases:
mlens.parallel.base.ProbaMixin
,mlens.parallel.learner.BaseNode
Wrapper for base learners.
Parameters: - estimator (obj) – estimator to construct learner from
- preprocess (str, obj) – preprocess transformer. Pass either the string
cache reference or the transformer instance. If the latter,
the
preprocess
will refer to the transformer name. - name (str) – name of learner. If
preprocess
is notNone
, the name will be prepended topreprocess__name
. - attr (str (default='predict')) – predict attribute, typically one of ‘predict’ and ‘predict_proba’
- scorer (func) – function to use for scoring predictions during cross-validated fitting.
- output_columns (dict, optional) – mapping of prediction feature columns from learner to columns in
output array. Normally, this map is
{0: x}
, but if theindexer
creates partitions, each partition needs to be mapped:{0: x, 1: x + 1}
. Note that ifoutput_columns
are not given at initialization, theset_output_columns
method must be called before running estimations. - verbose (bool, int (default = False)) – whether to report completed fits.
- **kwargs (bool (default=True)) – Optional ParallelProcessing arguments. See
BaseParallel
.
-
scorer
¶ Copy of scorer
Transformer¶
-
class
mlens.parallel.learner.
Transformer
(estimator, indexer=None, name=None, **kwargs)[source]¶ Bases:
mlens.parallel.learner.BaseNode
Preprocessing handler.
Wrapper for transformation pipeline.
Parameters: - indexer (obj, None) – indexer to use for generating fits.
Set to
None
to fit only on all data. - estimator (obj) – transformation pipeline to construct learner from
- name (str) – name of learner. If
preprocess
is notNone
, the name will be prepended topreprocess__name
. - output_columns (dict, optional) – If transformer is to be used to output data, need to
set
output_columns
. Normally, this map is{0: x}
, but if theindexer
creates partitions, each partition needs to be mapped:{0: x, 1: x + 1}
. - verbose (bool, int (default = False)) – whether to report completed fits.
- raise_on_exception (bool (default=True)) – whether to warn on non-fatal exceptions or raise an error.
- indexer (obj, None) – indexer to use for generating fits.
Set to
EvalLearner¶
-
class
mlens.parallel.learner.
EvalLearner
(estimator, preprocess, name, attr, scorer, error_score=None, verbose=False, **kwargs)[source]¶ Bases:
mlens.parallel.learner.Learner
EvalLearner is a derived class from Learner used for cross-validated scoring of an estimator.
Parameters: - estimator (obj) – estimator to construct learner from
- preprocess (str) – preprocess cache refernce
- indexer (obj, None) – indexer to use for generating fits.
Set to
None
to fit only on all data. - name (str) – name of learner. If
preprocess
is notNone
, the name will be prepended topreprocess__name
. - attr (str (default='predict')) – predict attribute, typically one of ‘predict’ and ‘predict_proba’
- scorer (func) – function to use for scoring predictions during cross-validated fitting.
- error_score (int, float, None (default = None)) – score to set if cross-validation fails. Set to
None
to raise error. - verbose (bool, int (default = False)) – whether to report completed fits.
- raise_on_exception (bool (default=True)) – whether to warn on non-fatal exceptions or raise an error.
EvalTransformer¶
-
class
mlens.parallel.learner.
EvalTransformer
(estimator, indexer=None, name=None, **kwargs)[source]¶ Bases:
mlens.parallel.learner.Transformer
Evaluator version of the Transformer.
Derived class from Transformer adapted to cross-validated grid-search. See
Transformer
for more details.
BaseNode¶
-
class
mlens.parallel.learner.
BaseNode
(name, estimator, indexer=None, verbose=False, **kwargs)[source]¶ Bases:
mlens.parallel.base.OutputMixin
,mlens.parallel.base.IndexMixin
,mlens.parallel.base.BaseEstimator
Base computational node inherited by job generators.
Common API for job generators. A class that inherits the base need to set a
__subtype__
in the constructor. The sub-type should be the class that runs estimations and must implement a__call__
,fit
,transform
andpredict
method.-
cloned_estimator
¶ Copy of estimator
-
collect
(path=None)[source]¶ Load fitted estimator from cache
Parameters: path (str, list, optional) – path to cache.
-
data
¶ Dictionary with aggregated data from fitting sub-learners.
-
gen_fit
(X, y, P=None)[source]¶ Routine for generating fit jobs conditional on refit
Parameters: - X (array-like of shape [n_samples, n_features]) – input array
- y (array-like of shape [n_samples,]) – targets
- P (array-like of shape [n_samples, n_prediction_features], optional) – output array to populate. Must be writeable. Only pass if predictions are desired.
-
gen_predict
(X, P=None)[source]¶ Generate predicting jobs
Parameters: - X (array-like of shape [n_samples, n_features]) – input array
- y (array-like of shape [n_samples,]) – targets
- P (array-like of shape [n_samples, n_prediction_features], optional) – output array to populate. Must be writeable. Only pass if predictions are desired.
-
gen_transform
(X, P=None)[source]¶ Generate cross-validated predict jobs
Parameters: - X (array-like of shape [n_samples, n_features]) – input array
- y (array-like of shape [n_samples,]) – targets
- P (array-like of shape [n_samples, n_prediction_features], optional) – output array to populate. Must be writeable. Only pass if predictions are desired.
-
learner
¶ Generator for learner fitted on full data
-
raw_data
¶ List of data collected from each sub-learner during fitting.
-
set_indexer
(indexer)[source]¶ Set indexer and auxiliary attributes
Parameters: indexer (obj) – indexer to build instance with.
-
set_output_columns
(X=None, y=None, job=None, n_left_concats=0)[source]¶ Set the output_columns attribute
-
sublearners
¶ Generator for learner fitted on folds
-
times
¶ Fit and predict times for the final learners
-
SubLearner¶
SubTransformer¶
EvalSubTransformer¶
IndexedEstimator¶
Handles¶
Group¶
-
class
mlens.parallel.handles.
Group
(indexer=None, learners=None, transformers=None, name=None, **kwargs)[source]¶ Bases:
mlens.parallel.base.BaseEstimator
A handle for learners and transformers that share a common indexer.
Lightweight class for pairing a set of independent learners with a set of transformers that all share the same cross-validation strategy. A
Group
instance is an acceptable caller toParallelProcessing
.New in version 0.2.0.
Note
All instances will share the same indexer. If instances have a different indexer, that indexer will be replaced.
Parameters: - indexer (inst, optional) – A
index
indexer to build learner and transformers on. If not passed, the first indexer of the learners will be enforced on all instances. - learners (list, inst, optional) –
Learner
instance(s) attached to indexer. Note thatGroup
overrides previousindexer
parameter settings. - transformers (list, inst, optional) –
Transformer
instance(s) attached to indexer. Note thatGroup
overrides previousindexer
parameter settings. - name (str, optional) – name of group
- **kwargs (optional) – Optional keyword arguments to the
BaseParallel
backend.
- indexer (inst, optional) – A
Pipeline¶
-
class
mlens.parallel.handles.
Pipeline
(pipeline, name=None, return_y=False)[source]¶ Bases:
mlens.externals.sklearn.base.BaseEstimator
Transformer pipeline
Pipeline class for wrapping a preprocessing pipeline of transformers.
Parameters: - pipeline (list, instance) –
A
Transformer
instance or a list ofTransformer
instances. Accepted input formats:option_1 = transformer_1 option_2 = [transformer_1, transformer_2] option_3 = [("tr-1", transformer_1), ("tr-2", transformer_2)] option_4 = [transformer_1, ("tr-2", transformer_2)]
- name (str, optional) – name of pipeline.
- return_y (bool, default = False) – If True, both X and y will be returned in a
transform()
call.
-
fit
(X, y=None)[source]¶ Fit pipeline.
Note that the
Pipeline
accepts both X and y arguments, and can return both X and y, depending on the transformers. The pipeline itself does no checks on the input.Parameters: - X (array-like of shape [n_samples, n_features]) – Input data
- y (array-like of shape [n_samples, ]) – Targets
Returns: self – Fitted pipeline
Return type: instance
-
fit_transform
(X, y=None)[source]¶ Fit and transform pipeline.
Note that the
Pipeline
accepts both X and y arguments, and can return both X and y, depending on the transformers. The pipeline itself does no checks on the input.Parameters: - X (array-like of shape [n_samples, n_features]) – Input data
- y (array-like of shape [n_samples, ]) – Targets
Returns: - X_processed (array-like of shape [n_samples, n_preprocessed_features]) – Preprocessed input data
- y (array-like of shape [n_samples, ], optional) – Preprocessed targets
-
get_params
(deep=True)[source]¶ Get parameters for this estimator. :param deep: If True, will return the parameters for this estimator and
contained subobjects that are estimators.Returns: params – Parameter names mapped to their values. Return type: mapping of string to any
-
transform
(X, y=None)[source]¶ Transform pipeline.
Note that the
Pipeline
accepts both X and y arguments, and can return both X and y, depending on the transformers. Pipeline itself does not checks the input.Parameters: - X (array-like of shape [n_samples, n_features]) – Input data
- y (array-like of shape [n_samples, ]) – Targets
Returns: - X_processed (array-like of shape [n_samples, n_preprocessed_features]) – Preprocessed input data
- y (array-like of shape [n_samples, ], optional) – Original or preprocessed targets, depending on the transformers.
- pipeline (list, instance) –
make_group¶
-
mlens.parallel.handles.
make_group
(indexer, estimators, preprocessing, learner_kwargs=None, transformer_kwargs=None, name=None)[source]¶ Creating a
Group
from a set learners and transformersUtility function for creating mapping a set of estimators and preprocessing pipelines to a
Group
ofLearner
andTransformer
instances.Parameters: - indexer (instance or None, default = None) – Indexer instance to use. See
index
for details. - estimators (dict of lists or list of estimators.) –
If
preprocessing
isNone
orlist
,estimators
should be alist
. The list can either contain estimator instances, named tuples of estimator instances, or a combination of both.option_1 = [estimator_1, estimator_2] option_2 = [("est-1", estimator_1), ("est-2", estimator_2)] option_3 = [estimator_1, ("est-2", estimator_2)]
If different preprocessing pipelines are desired, a dictionary that maps estimators to preprocessing pipelines must be passed. The names of the estimator dictionary must correspond to the names of the estimator dictionary.
preprocessing_cases = {"case-1": [trans_1, trans_2]. "case-2": [alt_trans_1, alt_trans_2]} estimators = {"case-1": [est_a, est_b]. "case-2": [est_c, est_d]}
The lists for each dictionary entry can be any of
option_1
,option_2
andoption_3
. - preprocessing (dict of lists or list, optional, default = None) –
preprocessing pipelines for given layer. If the same preprocessing applies to all estimators,
preprocessing
should be a list of transformer instances. The list can contain the instances directly, named tuples of transformers, or a combination of both.option_1 = [transformer_1, transformer_2] option_2 = [("trans-1", transformer_1), ("trans-2", transformer_2)] option_3 = [transformer_1, ("trans-2", transformer_2)]
If different preprocessing pipelines are desired, a dictionary that maps preprocessing pipelines must be passed. The names of the preprocessing dictionary must correspond to the names of the estimator dictionary.
preprocessing_cases = {"case-1": [trans_1, trans_2]. "case-2": [alt_trans_1, alt_trans_2]} estimators = {"case-1": [est_a, est_b]. "case-2": [est_c, est_d]}
The lists for each dictionary entry can be any of
option_1
,option_2
andoption_3
. - transformer_kwargs (dict, optional) – Keyword arguments to pass to the
Transformer
instances. - learner_kwargs (dict, optional) – Keyword arguments to pass to the
Learner
instances. - name (str, optional) – Name of group. Should be unique.
- indexer (instance or None, default = None) – Indexer instance to use. See
Wrappers¶
EstimatorMixin¶
-
class
mlens.parallel.wrapper.
EstimatorMixin
[source]¶ Bases:
object
Estimator mixin
Mixin class to build an estimator from a
mlens.parallel
backend class. The backend class should be set as the_backend
attribute of the estimator during afit
call via a_build
method. E.g:Foo(EstimatorMixin, Learner): def __init__(self, ...): self._backend = None def _build(self): self._backend = Learner(...)
It is recommended to combine
EstimatorMixin
with parallel.base.ParamMixin.-
fit
(X, y, proba=False, refit=True)[source]¶ Fit
Fit estimator.
Parameters: - X (array of size [n_samples, n_features]) – input data
- y (array of size [n_features,]) – targets
- proba (bool, optional) – whether to fit for later predict_proba calls. Will register number of classes to expect in later predict and transform calls.
- refit (bool (default = True)) – Whether to refit already fitted sub-learners.
Returns: self – fitted estimator.
Return type: instance
-
fit_transform
(X, y, proba=False, refit=True)[source]¶ Fit
Fit estimator and return cross-validated predictions.
Parameters: - X (array of size [n_samples, n_features]) – input data
- y (array of size [n_features,]) – targets
- proba (bool, optional) – whether to fit for later predict_proba calls. Will register number of classes to expect in later predict and transform calls.
- refit (bool (default = True)) – Whether to refit already fitted sub-learners.
Returns: P – prediction generated by cross-validation.
Return type: array of size [n_samples, n_prediction_features]
-
predict
(X, proba=False)[source]¶ Predict
Predict using full-fold estimator (fitted on all data).
Parameters: - X (array of size [n_samples, n_features]) – input data
- proba (bool, optional) – whether to predict class probabilities
Returns: P – prediction with full-fold estimator.
Return type: array of size [n_samples, n_prediction_features]
-
transform
(X, proba=False)[source]¶ Transform
Use cross-validated estimators to generate predictions.
Parameters: - X (array of size [n_samples, n_features]) – input data
- proba (bool, optional) – whether to predict class probabilities
Returns: P – prediction generated by cross-validation.
Return type: array of size [n_samples, n_prediction_features]
-
run¶
-
mlens.parallel.wrapper.
run
(caller, job, X, y=None, map=True, **kwargs)[source]¶ Utility for running a ParallelProcessing job on a set of callers.
Run is a utility mapping for setting up a ParallelProcessing job and executing across a set of callers. By default run executes:
out = mgr.map(caller, job, X, y, **kwargs)
run()
handles temporary parameter changes, for instance running a learner withproba=True
that hasproba=False
as default. Similarly, instances destined to not produce output can be forced to yield predictions by passingreturn_preds=True
as a keyword argument.Note
To run a learner with a
preprocessing
dependency, the instances need to be wrapped in aGroup
run(Group(learner, transformer), 'predict', X, y)
Parameters: - caller (instance, list) – A runnable instance, or a list of instances.
- job (str) – type of job to run. One of
'fit'
,'transform'
,'predict'
. - X (array-like) – input
- y (array-like, optional) – targets
- map (bool (default=True)) – whether to run a
ParallelProcessing.map()
job. IfFalse
, will instead run aParallelProcessing.stack()
job. - **kwargs (optional) – Keyword arguments.
run()
searches forproba
andreturn_preds
to temporarily update callers to run desired job and return desired output. Otherkwargs
are passed to eithermap
orstack
.
Backend¶
BaseProcessor¶
-
class
mlens.parallel.backend.
BaseProcessor
(backend=None, n_jobs=None, verbose=None)[source]¶ Bases:
object
Parallel processing base class.
Base class for parallel processing engines.
Parameters: -
initialize
(job, X, y, path, warm_start=False, return_preds=False, **kwargs)[source]¶ Initialize processing engine.
Set up the job parameters before an estimation call. Calling
clear()
undoes initialization.Parameters: - job (str) – type of job to complete with each task. One of
'fit'
,'predict'
and'transform'
. - X (array-like of shape [n_samples, n_features]) – Input data
- y (array-like of shape [n_samples,], optional.) – targets. Required for fit, should not be passed to predict or transform jobs.
- path (str or dict, optional) – Custom estimation cache. Pass a string to force use of persistent
cache on disk. Pass a
dict
for in-memory cache (requiresbackend != 'multiprocessing'
. - return_preds (bool or list, optional) – whether to return prediction ouput. If
True
, final prediction is returned. Alternatively, pass a list of task names for which output should be returned. - warm_start (bool, optional) – whether to re-use previous input data initialization. Useful if repeated jobs are made on the same input arrays.
- **kwargs (optional) – optional keyword arguments to pass onto the task’s call method.
Returns: out – An output parameter dictionary to pass to pass to an estimation method. Either
None
(no output), or{'final':True}
for only final prediction, or{'final': False, 'return_names': return_preds}
if a list of task-specific output was passed.Return type: - job (str) – type of job to complete with each task. One of
-
ParallelProcessing¶
-
class
mlens.parallel.backend.
ParallelProcessing
(*args, **kwargs)[source]¶ Bases:
mlens.parallel.backend.BaseProcessor
Parallel processing engine.
Engine for running computational graph.
ParallelProcessing
is a manager for executing a sequence of tasks in a given caller, where each task is run sequentially, but assumed to be parallelized internally. The main responsibility ofParallelProcessing
is to handle memory-mapping, estimation cache updates, input and output array updates and output collection.Parameters: - caller (obj) – the caller of the job. Either a Layer or a meta layer class such as Sequential.
- *args (optional) – Optional arguments to
BaseProcessor
- **kwargs (optional) – Optional keyword arguments to
BaseProcessor
.
-
get_preds
(dtype=None, order='C')[source]¶ Return prediction matrix.
Parameters: - dtype (numpy dtype object, optional) – data type to return
- order (str (default = 'C')) – data order. See
numpy.asarray
for details.
Returns: P – Prediction array
Return type: array-like
-
map
(caller, job, X, y=None, path=None, return_preds=False, wart_start=False, split=False, **kwargs)[source]¶ Parallel task mapping.
Run independent tasks in caller in parallel.
Warning
By default, the :~mlens.parallel.backend.ParallelProcessing.map` runs on a shallow cache, where all tasks share the same cache. As such, the user must ensure that each task has a unique name, or cache retrieval will be corrupted. To commit a seperate sub-cache to each task, set
split=True
.Parameters: - caller (iterable) – Iterable that generates accepted task instances. Caller should be
a child of the
BaseBackend
class, and tasks need to implement an appropriate call method. - job (str) – type of job to complete with each task. One of
'fit'
,'predict'
and'transform'
. - X (array-like of shape [n_samples, n_features]) – Input data
- y (array-like of shape [n_samples,], optional.) – targets. Required for fit, should not be passed to predict or transform jobs.
- path (str or dict, optional) – Custom estimation cache. Pass a string to force use of persistent
cache on disk. Pass a
dict
for in-memory cache (requiresbackend != 'multiprocessing'
. - return_preds (bool or list, optional) – whether to return prediction ouput. If
True
, final prediction is returned. Alternatively, pass a list of task names for which output should be returned. - warm_start (bool, optional) – whether to re-use previous input data initialization. Useful if repeated jobs are made on the same input arrays.
- split (bool, default = False) – whether to commit a separate sub-cache to each task.
- **kwargs (optional) – optional keyword arguments to pass onto each task.
Returns: out – Prediction array(s).
Return type: array-like, list, optional
- caller (iterable) – Iterable that generates accepted task instances. Caller should be
a child of the
-
process
(caller, out, **kwargs)[source]¶ Process job.
Main method for processing a caller. Requires the instance to be setup by a prior call to
initialize()
.Parameters: - caller (iterable) – Iterable that generates accepted task instances. Caller should be
a child of the
BaseBackend
class, and tasks need to implement an appropriate call method. - out (dict) – A dictionary with output parameters. Pass an empty dict for no
output. See
initialize()
for more details.
Returns: out – Prediction array(s).
Return type: array-like, list, optional
- caller (iterable) – Iterable that generates accepted task instances. Caller should be
a child of the
-
stack
(caller, job, X, y=None, path=None, return_preds=False, warm_start=False, split=True, **kwargs)[source]¶ Stacked parallel task mapping.
Run stacked tasks in caller in parallel.
This method runs a stack of tasks as a stack, where the output of each task is the input to the next.
Warning
By default, the
stack()
method runs on a deep cache, where each tasks has a separate cache. As such, the user must ensure that tasks don’t depend on data cached by previous tasks. To run all tasks in a single sub-cache, setsplit=False
.Parameters: - caller (iterable) – Iterable that generates accepted task instances. Caller should be
a child of the
BaseBackend
class, and tasks need to implement an appropriate call method. - job (str) – type of job to complete with each task. One of
'fit'
,'predict'
and'transform'
. - X (array-like of shape [n_samples, n_features]) – Input data
- y (array-like of shape [n_samples,], optional.) – targets. Required for fit, should not be passed to predict or transform jobs.
- path (str or dict, optional) – Custom estimation cache. Pass a string to force use of persistent
cache on disk. Pass a
dict
for in-memory cache (requiresbackend != 'multiprocessing'
. - return_preds (bool or list, optional) – whether to return prediction output. If
True
, final prediction is returned. Alternatively, pass a list of task names for which output should be returned. - warm_start (bool, optional) – whether to re-use previous input data initialization. Useful if repeated jobs are made on the same input arrays.
- split (bool, default = True) – whether to commit a separate sub-cache to each task.
- **kwargs (optional) – optional keyword arguments to pass onto each task.
Returns: out – Prediction array(s).
Return type: array-like, list, optional
- caller (iterable) – Iterable that generates accepted task instances. Caller should be
a child of the
ParallelEvaluation¶
-
class
mlens.parallel.backend.
ParallelEvaluation
(*args, **kwargs)[source]¶ Bases:
mlens.parallel.backend.BaseProcessor
Parallel cross-validation engine.
Minimal parallel processing engine. Similar to
ParallelProcessing
, but offers less features, only fits the callers indexer, and excepts no task output.-
process
(caller, case, X, y, path=None, **kwargs)[source]¶ Process caller.
Parameters: - caller (iterable) – Iterable for evaluation job.s Expected caller is a
Evaluator
instance. - case (str) – evaluation case to run on the evaluator. One of
'preprocess'
and'evaluate'
. - X (array-like of shape [n_samples, n_features]) – Input data
- y (array-like of shape [n_samples,], optional.) – targets. Required for fit, should not be passed to predict or transform jobs.
- path (str or dict, optional) – Custom estimation cache. Pass a string to force use of persistent
cache on disk. Pass a
dict
for in-memory cache (requiresbackend != 'multiprocessing'
.
- caller (iterable) – Iterable for evaluation job.s Expected caller is a
-
Job¶
-
class
mlens.parallel.backend.
Job
(job, stack, split, dir=None, tmp=None, predict_in=None, targets=None, predict_out=None)[source]¶ Bases:
object
Container class for holding and managing job data.
Job
is intended as a on-the-fly job handler that keeps track of input data, predictions, and manages estimation caches.Changed in version 0.2.0.
See also
Parameters: - job (str) – Type of job to run. One of
'fit'
,'transform'
,'predict'
. - stack (bool) – Whether to stack outputs when calls to
update()
are made. This will make thepredict_out
array becomepredict_in
. - split (bool) – Whether to create a new sub-cache when the
args
property is called. - dir (str, dict, optional) – estimation cache. Pass dictionary for use with multiprocessing or a string pointing to the disk directory to create the cache in
- tmp (obj, optional) – a Tempfile object for temporary directories
- targets (array-like of shape [n_in_samples,], optional) – input targets
- predict_in (array-like of shape [n_in_samples, n_in_features], optional) – input data
- predict_out (array_like of shape [n_out_samples, n_out_features], optional) – prediction output array
-
args
(**kwargs)[source]¶ Produce args dict
New in version 0.2.0.
Returns the arguments dictionary passed to a task of a parallel processing manager. Output dictionary has the following form:
out = {'auxiliary': {'X': self.predict_in, 'P': self.predict_out}, 'main': {'X': self.predict_in, 'P': self.predict_out}, 'dir': self.subdir(), 'job': self.job }
Parameters: **kwargs (optional) – Optional keyword arguments to pass to the task. Returns: args – Arguments dictionary Return type: dict
-
rebase
()[source]¶ Rebase output labels to input indexing.
Some indexers that only generate predictions for subsets of the training data require the targets to be rebased. Since indexers operate in a strictly sequential manner, rebase simply drop the first
n
observations in the target vector until number of observations remaining coincide.See also
BlendIndex
-
shuffle
(random_state)[source]¶ Shuffle inputs.
Permutes the indexing of
predict_in
andy
arrays.Parameters: random_state (int, obj) – Random seed number or generator to use.
-
subdir
()[source]¶ Return a cache subdirectory
If
split
is en force, a new sub-cache will be created in the main cache. Otherwise the same sub-cache as used in previous call will be returned.New in version 0.2.0.
Returns: cache – Either a string pointing to a cache persisted to disk, or an in-memory cache in the form of a list. Return type: str, list
- job (str) – Type of job to run. One of
Base classes¶
Schedulers for global setups:
| Order | Setup types | Function calls |
|---|---|---|
|
Independent of other features | IndexMixin._setup_0_index |
|
Reserved for aggregating classes | BaseStacker._setup_1_global |
|
Setups Dependents on 0 | ProbaMixin.__setup_2_multiplier |
|
Setups Dependents on 0, 2 | OutputMixin.__setup_3__output_columns |
Note that base classes and setup schedulers are experimental and may change without a deprecation cycle.
BaseBackend¶
-
class
mlens.parallel.base.
BaseBackend
(backend=None, n_jobs=-1, dtype=None, raise_on_exception=True)[source]¶ Bases:
object
Base class for parallel backend
Implements default backend settings.
-
__init__
(backend=None, n_jobs=-1, dtype=None, raise_on_exception=True)[source]¶ Initialize self. See help(type(self)) for accurate signature.
-
__weakref__
¶ list of weak references to the object (if defined)
-
BaseParallel¶
-
class
mlens.parallel.base.
BaseParallel
(name, *args, **kwargs)[source]¶ Bases:
mlens.parallel.base.BaseBackend
Base class for parallel objects
Parameters: - name (str) – name of instance. Should be unique.
- backend (str or object (default = 'threading')) – backend infrastructure to use during call to
mlens.externals.joblib.Parallel
. See Joblib for further documentation. To set global backend, seeset_backend()
. - raise_on_exception (bool (default = True)) – whether to issue warnings on soft exceptions or raise error.
Examples include lack of layers, bad inputs, and failed fit of an
estimator in a layer. If set to
False
, warnings are issued instead but estimation continues unless exception is fatal. Note that this can result in unexpected behavior unless the exception is anticipated. - verbose (int or bool (default = False)) – level of verbosity.
- n_jobs (int (default = -1)) – Degree of concurrency in estimation. Set to -1 to maximize, 1 runs on a single process (or thread).
- dtype (obj (default = np.float32)) – data type to use, must be compatible with a numpy array dtype.
BaseEstimator¶
-
class
mlens.parallel.base.
BaseEstimator
(*args, **kwargs)[source]¶ Bases:
mlens.parallel.base.ParamMixin
,mlens.externals.sklearn.base.BaseEstimator
,mlens.parallel.base.BaseParallel
Base Parallel Estimator class
Modified Scikit-learn class to handle backend params that we want to protect from changes.
-
__fitted__
¶ Fit status
-
BaseStacker¶
-
class
mlens.parallel.base.
BaseStacker
(stack=None, verbose=False, *args, **kwargs)[source]¶ Bases:
mlens.parallel.base.BaseEstimator
Base class for instanes that stack job estimators
-
__fitted__
¶ Fitted status
-
__init__
(stack=None, verbose=False, *args, **kwargs)[source]¶ Initialize self. See help(type(self)) for accurate signature.
-
__stack__
¶ Check stack
-
get_params
(deep=True)[source]¶ Get parameters for this estimator.
Parameters: deep (boolean, optional) – whether to return nested parameters.
-
verbose
¶ Verbosity
-
Mixins¶
ParamMixin¶
-
class
mlens.parallel.base.
ParamMixin
[source]¶ Bases:
mlens.externals.sklearn.base.BaseEstimator
,object
Parameter Mixin
Mixin for protecting static parameters from changes after fitting.
Note
To use this mixin the instance inheriting it must set
__static__=list()
and_static_fit_params_=dict()
in__init__
.
IndexMixin¶
-
class
mlens.parallel.base.
IndexMixin
[source]¶ Bases:
object
Indexer mixin
Mixin for handling indexers.
Note
- To use this mixin the instance inheriting it must set the
indexer
orindexers
attribute in__init__
(not both).
-
__indexer__
¶ Flag for existence of indexer
-
__weakref__
¶ list of weak references to the object (if defined)
OutputMixin¶
-
class
mlens.parallel.base.
OutputMixin
[source]¶ Bases:
mlens.parallel.base.IndexMixin
Output Mixin
Mixin class for interfacing with ParallelProcessing when outputs are desired.
Note
To use this mixin the instance inheriting it must set the
feature_span
attribute and__no_output__
flag in__init__
.
ProbaMixin¶
-
class
mlens.parallel.base.
ProbaMixin
[source]¶ Bases:
object
“Probability Mixin
Mixin for probability features on objects interfacing with
ParallelProcessing
Note
To use this mixin the instance inheriting it must set the
proba
and the_classes(=None)``attribute in ``__init__
.-
__weakref__
¶ list of weak references to the object (if defined)
-
classes_
¶ Prediction classes during proba
-


Module rules3
Contrast set learning
Usage:
Rules3 v3.0 : Contrast set learning (c) 2021 Tim Menzies<EMAIL_ADDRESS>unlicense.org The difference between things (in the same domain) is often shorter to describe than the things themselves. USAGE: ./rules.lua [OPTIONS] OPTIONS: -h print help -data FILE read data from FILE +verbose enable verbose mode
Info:
- Copyright: 2021
- License: unlicense.org
- Author: Tim Menzies
Table functions
Useful utilities for opening foobar format files.
- Tab.pump (o)
- Convert a table to key, val pairs, then print it.
- Tab.dump (o)
- Convert a table to key, val pairs.
- Tab.inc (d, k, n)
-
Add
n
(defaults to 1) tod[k]
(self-initializing if needed). - Tab.subsets (s)
-
Return all subsets of table
s
(including empty table)
File functions
Useful utilities for opening foobar format files.
Object functions
Useful utilities for opening foobar format files.
System functions
Useful utilities for opening foobar format files.
Class Num
Num functions.
Useful utilities for opening foobar format files.
Eg functions
Useful utilities for opening foobar format files.


Indicates which button was pressed on the mouse or pointer device to trigger the event.
Indicates which buttons are pressed on the mouse or pointer device when the event is triggered.
This point stores the global coords of where the touch/mouse event happened
The height of the pointer's contact along the y-axis, measured in CSS pixels. radiusY of TouchEvents will be represented by this value.
Unique identifier for this interaction
Indicates whether or not the pointer device that created the event is the primary pointer.
When passed to an event handler, this will be the original DOM Event that was captured
The unique identifier of the pointer. It will be the same as identifier
.
The type of pointer that triggered the event.
Pressure applied by the pointing device during the event. A Touch's force property will be represented by this value.
From TouchEvents (not PointerEvents triggered by touches), the rotationAngle of the Touch.
Barrel pressure on a stylus pointer.
The target Sprite that was interacted with
The angle, in degrees, between the pointer device and the screen.
The angle, in degrees, between the pointer device and the screen.
Twist of a stylus pointer.
The width of the pointer's contact along the x-axis, measured in CSS pixels. radiusX of TouchEvents will be represented by this value.
Copies properties from normalized event data.
The normalized event data
This will return the local coordinates of the specified displayObject for this InteractionData
The DisplayObject that you would like the local coords off
A point containing the coordinates of the InteractionData position relative to the DisplayObject
Resets the data for pooling.
Generated using TypeDoc
Holds all information related to an Interaction event
PIXI.interaction


Position 19° 58'42"S, 158° 08'52"W.
Yachts can clear at Atiu (Avamutu), but must pay for transporting the Customs officer by air or sea.
See Cook Islands Formalities for complete clearance information.
There is no harbour, so one has to anchor off the reef.


{% extends "appfd/base.html" %} {% load staticfiles %} {% block content %}
Welcome to First Draft, a website that automatically creates the first drafts of maps for you. You give it information and it returns a map of that information.


The Specialization relationship indicates that an object is a specialisation of another object.
The Specialization relationship can relate any instance of a concept with another instance of the same concept.
Specialization is always possible between two instances of the same concept.
Other.
A "Take out travel insurance" and a "Take out luggage insurance" process are a specialization of a more generic "Take out insurance" process.


gridfile.buildSources
Build dataSources for gridfile operations
Syntax
Description
Builds the dataSource objects for the specified sources. If a data source fails to build, or does not match the values recorded in the gridfile, exits immediately and reports the failed data source as well as the cause of the failure.
Specify whether the method should stop immediately when a data source fails. Default is true. If false, the method will continue through the full set of data sources, reporting all failed data sources and the causes of their failures.
Builds data sources using the values recorded in the gridfile, but with custom filepaths.
Input Arguments
s
vector, linear indices [nSources]
The indices of the data sources in the gridfile for which to build dataSource objects.
fatal
scalar logical
Set to true (default) if the method should exit immediately when a data source fails. Set to false to continue and attempt to build all sources
filepaths
string vector [nSources]
The absolute filepaths to use when building the dataSources
Output Arguments
dataSources
cell vector [nSources] {scalar dataSource object | []} | []
dataSource objects for the specified sources. If fatal is true, and a dataSource fails, dataSources is an empty array. If not fatal, the elements for failed sources are empty arrays.
failed
false | scalar integer | logical vector [nSources]
Indicates whether any data sources failed. If fatal, failed is false or the index of the failed source. If not fatal, failed is a logical vector with one element per data source. If not fatal and there are no requested data sources, then failed will be false.
causes
[] | scalar MException | cell vector [nSources] {scalar MException}
If fatal and all sources succeeded, returns an empty array. If fatal and failed, a scalar MException. If not fatal, has one element per source. Elements of failed sources hold the MException reporting the cause of the failure. Elements of successful sources are empty arrays.


The $location service parses the URL in the browser address bar (based on the window.location) and makes the URL available to your application. Changes to the URL in the address bar are reflected into $location service and changes to $location are reflected into the browser address bar.
The $location service:
For more information see Developer Guide: Angular Services: Using $location
This method is getter only.
Return full url representation with all segments encoded according to rules specified in RFC 3986.
This method is getter / setter.
Return hash fragment when called without any parameter.
Change hash fragment when called with parameter and return $location
.
hash(optional) – {string=} –
New hash fragment
This method is getter only.
Return host of current url.
This method is getter / setter.
Return path of current url when called without any parameter.
Change path when called with parameter and return $location
.
Note: Path should always begin with forward slash (/), this method will add the forward slash if it is missing.
path(optional) – {string=} –
New path
This method is getter only.
Return port of current url.
This method is getter only.
Return protocol of current url.
If called, all changes to $location during current $digest
will be replacing current history
record, instead of adding new one.
This method is getter / setter.
Return search part (as object) of current url when called without any parameter.
Change search part when called with parameter and return $location
.
search(optional) – {string|object<string,string>=} –
New search params - string or hash object
paramValue(optional) – {string=} –
If search
is a string, then paramValue
will override only a
single search parameter. If the value is null
, the parameter will be deleted.
This method is getter / setter.
Return url (e.g. /path?a=b#hash
) when called without any parameter.
Change path, search and hash, when called with parameter and return $location
.
url(optional) – {string=} –
New url without base prefix (e.g. /path?a=b#hash
)


{% extends "layout.html" %} {% block page_title %} What’s your business structure? - Business matching - Anti-money laundering registration - GOV.UK {% endblock %} {% block content %} {% include "includes/phase_banner_research.html" %} What’s your business structure? This section is Business matching What’s your business structure? Limited company Sole proprietor Partnership Limited partnership or limited liability partnership Unincorporated association or trust Save and continue {% endblock %}
This section is Business matching


Everyone should be jealous of this website, because it is amazing.
It was hand-crafted as part of a small batch by HTML artisans tucked in southeast Portland, Oregon.
All of the artisans had moustaches, so you know they’re super, super serious about quality.


|
Apache Mesos
|
#include <network.hpp>
Public Member Functions | |
| ZooKeeperNetwork (const std::string &servers, const Duration &timeout, const std::string &znode, const Option< zookeeper::Authentication > &auth, const std::set< process::UPID > &base=std::set< process::UPID >()) | |
| Public Member Functions inherited from Network | |
| Network () | |
| Network (const std::set< process::UPID > &pids) | |
| virtual | ~Network () |
| void | add (const process::UPID &pid) |
| void | remove (const process::UPID &pid) |
| void | set (const std::set< process::UPID > &pids) |
| process::Future< size_t > | watch (size_t size, WatchMode mode=NOT_EQUAL_TO) const |
| template<typename Req , typename Res > | |
| process::Future< std::set < process::Future< Res > > > | broadcast (const Protocol< Req, Res > &protocol, const Req &req, const std::set< process::UPID > &filter=std::set< process::UPID >()) const |
| template<typename M > | |
| process::Future< Nothing > | broadcast (const M &m, const std::set< process::UPID > &filter=std::set< process::UPID >()) const |
Additional Inherited Members | |
| Public Types inherited from Network | |
| enum | WatchMode { EQUAL_TO, NOT_EQUAL_TO, LESS_THAN, LESS_THAN_OR_EQUAL_TO, GREATER_THAN, GREATER_THAN_OR_EQUAL_TO } |
|
inline |


Susan Granger's review of "TWO CAN PLAY THAT GAME" (Screen Gems)
Since the success of "Waiting to Exhale," there have been several romantic comedies about African-American professionals. This female revenge fantasy, Vivica A. Fox plays Shante Smith, a stunning ad exec who seems to have reached the pinnacle of success: a mansion, a sporty car and an idyllic relationship with a hunky, hot-shot lawyer, Morris Chestnut. She's at a point in her life when she dispenses advice to her grateful girl-friends (Mo'Nique, Wendy Racquel Robinson, Tamala Jones). "When your man messes up, no matter how small it is," she smugly decrees, "yuh gots to punish him." So when she catches her hot man dancing at a bar with a smart and sexy rival, Gabrielle Union, she devises her own version of "The Rules," a 10-day "tough love" emotionally punishing plan to get him back. Unfortunately, writer/director Mark Brown ("How To Be a Player") breaks the cardinal rule of romantic comedy: you have to like the protagonist - and shrill, self-congratulatory Shante Smith is a smirking, superficial, spiteful shrew who doesn't realize that rational rules cannot always be applied to love. Having her talk directly into the camera gets stale very quickly and the "Day One," "Day Two" title-card device underscores the tedium. Comic Anthony Anderson scores as Chestnut's boisterous best-friend, and singer Bobby Brown does a cameo as a scuzzy mechanic who's given a smooth makeover by Ms. Robinson. But the out-takes over the closing credits contain more humor than the film itself. On the Granger Movie Gauge of 1 to 10, "Two Can Play That Game" is smarmy if slick 4, filled with misogynistic attitude and blatant product placements (Coca-Cola, Miller Genuine Draft) but little else. In this R-rated (for explicit sexual language), pseudo-hip battle of the sexes, the audience loses.
========== X-RAMR-ID: 29465 X-Language: en X-RT-ReviewID: 249902 X-RT-TitleID: 1109701 X-RT-SourceID: 742 X-RT-AuthorID: 1274 X-RT-RatingText: 4/10
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


The Monacan Indian Nation is an indigenous group from the greater Piedmont and Blue Ridge, with some of their earliest settlements dating to 1000 A.D. Their history is marked by resilience and their tie to this place. Today, the Monacans need help saving the remains of their historic capitol, Rassawek, located at the confluence of the Rivanna and James Rivers, from development.
For a millennium, the Monacan Nation honored their ancestors with burial mounds, an ancient practice associated with the most politically and economically powerful tribes in North America. The mounds grew over generations: remains were buried once, but then ceremonially reburied as part of a layered, earthen structure. Some of these burials are more than eight feet tall, around forty feet in diameter, and are home to over a thousand individuals’ remains, representing centuries of ancestral history.
The mounds could have only been built through sustained ritual over hundreds of years, showing that the Monacans were a settled, agricultural society—not solely hunter-gatherers, they gardened and relied on the forests for sustenance. In this matrilineal society, mothers and aunts passed down their family identities, which endured for generations. The mounds serve as a monument to a lineage and a connection to place. The thirteen known mounds represent thousands of years of history and habitation. Even after the practice ended, continued visitations to the mounds into at least the eighteenth century, and the mounds’ impressive stature today, link present generations to the past. The burial sites are physical testimonies to a lived connection to the Appalachian Mountains older than any other.
Between A.D. 1000 and 1700, Monacans resided in oval-shaped pole and thatch houses, typically between 130 and 285 square feet in size. These were permanent structures, but the Monacans also established smaller “hunting towns” with temporary buildings.
Monacans established their towns along rivers, home to between a few dozen and over a hundred individuals. Their capital city of Rassawek sat at the confluence of the Rivanna and James Rivers. By 1600, about 15,000 Monacans lived in towns that fanned out north and west from the capitol.
 Women farmed crops, primarily pumpkins, squash, corn, beans, gourds, and sunflowers. Trade with Spanish and English settlers introduced non-indigenous fleshy fruits, possibly persimmons and grapes, to Monacans’ diets. In hunting for venison, farming, and building towns, everyday life was sustained by the region’s resources.
From the early 1600s, the Monacan Indians purposefully relocated away from European colonization. In 1608, Virginia colonist John Smith penned in his journal about his experience traversing up the James River eager to “finish the discovery” when he crossed into Monacan territories. After an altercation between the colonists and the Monacans, John Smith captured an injured Monacan man, Amoroleck, and questioned him to procure information on tribal relations and local resources. John Smith tells of Amoroleck’s response.
“They heard we were a people who came from under the world, to take their world from them.”
- Amoroleck
As Amoroleck described, the English soon came for the Monacans’ territories. John Smith first drew the Monacan territory in 1624, which he depicts with five major settlements on his map. On the 1624 map pictured here, Smith marked the Monacans territory along with five surrounding Monacan towns including the Monahassanugh, Rassawek, Mowhemencho, Monassukapanough, and Massinacack.
In 1680, the Monacans signed the Treaty of Middle Plantation, which made the Monacans and other groups tributaries to the English. In exchange, the English agreed to stay three miles from Indian settlements. Virginians failed to uphold this promise, while the Monacan tribe pays tribute to the Virginia governor up to the present day. A chief named Shurenough signed the Treaty of Middle Plantation in 1680 as the “King of Manakins,” with his “mark” pictured here.
Through trade, the Monacans thrived and contributed to the survival of other Native people. The interior of Virginia held many prestige minerals that were used in trade, all situated within Monacan territory.
The Monacans traded important goods such as soapstone, copper, and mica, linking the peoples of the Piedmont and the Coastal Plain of Virginia. Competition for status was determined by access to nonlocal prestige goods, to which the Monacans had bountiful access.
Varying in shape, color, and size, copper was one of the most valuable trade items for the Monacans. The metal had a number of uses ranging from decorative purposes, jewelry, and tools needed for everyday life. Its versatility made it valuable. A majority of the copper found in this area was traded and transported from the Great Lakes. This illustrates the reach and distance that the Moncans had in trading with other tribes and the creation of many social networks. These materials were fundamental to their relationship with neighboring tribes such as the Powhatans and to establishing a stable economy.
Monacan trading towns, centers for exchange between colonists and Native peoples, were generally situated on interior trading paths within Roanoke and Shenandoah River Valleys. English trading posts and forts developed along the fall line in Virginia’s interior, impacting the economic and political landscape for Monacans. These trading posts and forts would build upon existing trade routes that indigenous peoples used for centuries, connecting people through trade. Fort Henry, which was established on Appomattox River south of the James, was especially important in the creation of a booming economy and social network for the indigenous people to the west. The development and expansion of trading towns around 1650 aided the exchange of hides and metal goods.
During English colonization, the Monacans moved away from plantations, with some joining allied tribes in the Virginia Piedmont. At the turn of the seventeenth century, Virginia lawmakers imposed harsh regulations to control their growing enslaved labor force by punishing interracial sex and marriage, and increasing punishment for resistance on the part of enslaved Africans and Indians. By 1723, most free Indians could not vote, own firearms, testify as a witness in a trial, or serve in the militia. While Native people saw themselves as members of distinct nations, Virginia law classified them all as “Indian” and identified them with mixed-race and African-American Virginians as people without rights.
By 1830 with the Indian Removal Act, United States policy focused on displacement of Native Americans from historical and ancestral lands. In efforts to acculturate Native populations, the United States government established reservations and appropriated Native land, and churches established missionary schools for Native children.
After the Civil War, the state of Virginia did not recognize “Indian” as an identity. As Reconstruction and Jim Crow began in Virginia, Monacans began to face racial discrimination from both white and African American citizens. In the nineteenth and early twentieth centuries, many Monacans left ancestral lands they had known for generations. Some settled in cities like Baltimore and Johnson City, while a considerable number remained in the Blue Ridge Mountains. Some Monacans remained and settled in Amherst County, on historical lands, where they now worked and lived.
It is in this area that the Bear Mountain Mission School opened. From 1898 through 1964, the Bear Mountain Indian Mission School was a central cultural point for the Monacan Indian Nation, serving not only as an educational resource prior to integration, but also as a community focus and historical marker through the process of state and federal recognition.
After centuries of overt racism and systemic attempts to erase their identity, the Monacan people persevered as a tribe. For several decades the tribe has worked closely with a handful of committed scientists and academics to reconstruct the traditions and lifeways of their ancestors. Members of the Monacan Indian Nation continue to research their pre-colonial history and teach the public about their under-recognized culture.
The Monacan Indian Nation holds an annual Powwow, a representation of the transformation and merging of pre-colonial tradition with contemporary practices. The yearly gathering both raises money for Monacan student scholarships and educates the public through direct Monacan representation.
After an eighteen-year battle, the Monacan Indian Nation finally gained federal recognition on January 30, 2018. While federal acknowledgment does not entitle Monacan people to direct financial benefits, the tribe’s 2000 members can now apply for educational scholarships, housing opportunities, medical assistance and tribal grants. Federal recognition also provides the Monacan tribe with a stronger voice in protecting their ancestral lands, as in their struggle to save Rassawek, the Monacan capitol documented by John Smith. This sacred place is under threat by the James River Water Authority, which applied to build a water pump station in the center of Rassawek.
For generations, Rassawek defined life in the region. Preservation will save this important historical site, the capitol of a nation, for future generations. Because Monacans lived for some time after the nearby mounds were built, there are certain to be human burials at the site. The Monacan tribal leaders have already once felt the pain of repatriation and reburial of their ancestors’ remains. Moving the station to another location will respect a millennium of Monacan life and influence, and allow Rassawek's remains to rest in peace. The Save Rassawek campaign is happening now, and you can help.

We can touch the windowsill,
where October air gathers
as hours slip past in thin robes,
the forest a concert of voices.
The last crickets let go of their songs.
The land speaks, its language arising
from its own geography—
the mountains’ hulked shapes
are blue whales, remembering
when they were undersea ridges,
and rivers are serpentine strands
hammered from silver, and dark trees
talk to the wind—weaving mortal lives,
drumbeats, pillars of smoke,
voices wavering into updraft,
the storyteller shifting the present.
This exhibit was made possible by students in the Virginia Tech ASPECT Spring 2020 graduate course, the Politics of Memory, who researched the long history of the Monacan Indian Nation. Thank you to everyone who helped make this exhibit possible.
For more information about this exhibit and exhibits in the University Libraries contact Scott Fralin, safralin@vt.edu.


{% extends "instructions/home.html" %} {% block header %} {% with headerMessage='Gene Concept Marking Rules' %} {% include "includes/header.html" %} {% endwith %} {% endblock %} {% block breadcrumb %}
Mark every instance of a Gene or Gene Product (like proteins or MicroRNAs)
--This includes Gene or Gene Product names and symbols
Eg- Caveolin1 gene or CAV1 protein
Use the minimum span needed to encompass multiple terms of a Gene or Gene Product.
Eg- Cluster of Differentiation IV gene or CD4 protein , NOT just Cluster or Differentiation IV
Mark each instance of a Gene or Gene Product separately or in a separate span (if an instance has multiple words
Eg- RasGAP (GTPase activating protein of Ras) prevented indirect activation of PDGFRβ
Mark each instance of an abbreviation of a Gene or Gene Product
Eg- AKT levels may affect PIM1 expression in
Don't highlight generic terms like 'gene' or 'protein' unless they are part of a gene or protein name
Eg- Heat shock protein 90 is correct, but NOT CAV1 protein
If you suspect an unfamiliar term of being a gene/gene product name or symbol but are unsure, check here: genenames.org or ncbi.nlm.nih.gov/gene/ or visit our new Wikia forum for help


The IFRC’s Middle East and North Africa regional office works in support of 17 National Red Cross and Red Crescent Societies in the region. Through its country cluster support teams and country offices, it provides coordination, financial and technical support for disaster operations and longer term development programmes throughout the region. Amid political turmoil that has been ravaging several countries in MENA in recent years, National Red Cross and Red Crescent Societies have focused much of their efforts of providing relief and support to communities affected by conflicts. They have also made significant investment in strengthening the expertise of their volunteer teams to respond to a variety of crises. This form of development is an ongoing process.
Data Source: The INFORM Risk Index
| Crisis Name | Start Date | End Date | Targeted | Budget | Funding | Coverage | Appeal Code |
| Crisis Name | Start Date | End Date | Targeted | Budget | Appeal Code |