* Last update: 18.8.2001
Why does nobody read the readme.txt or this FAQ ?
I really don't know. Most questions I receive via e-mail are
already answered either in the readme or in this FAQ :)
Why is it called "POD-Bot" ?
POD is an abbreviation for "Ping of Death". I called it
that way because it was derived from the "High Ping Bastard Bot"
Botman is doing. And if youlook at the Bots Ping they always have
a Ping of 5 and the very first Generation of Bots did Headshots all the
time, so you know why, huh ?
Who is this Botman Guy everbody seems to mention ?
Botman was the very first who implemented a Method to hook every existing
Halflife MOD DLL. Since you don't usually
have the original Sources of e.a. Counterstrike, DLL Hooking is the only
way to write extensions (Bots) for it. He also was so
kind to put his Sources on his Webpage, so that everybody could see how
it is done and was able to do Bot Programming.
Please visit his Website at: http://www.planethalflife.com/botman/
and also try his HPB-Bot which supports several MODs.
Botman is in no way affiliated with POD-Bot or me so if you have any questions
concerning POD mail me instead of him.
Who is the POD-Bot Team ?
There isn't any Team. I (Count
Floyd) am responsible for all the Bot Coding & Design.
Two friendly people at nuclearbox.com
(Auxois and Smok3)
are doing all the Web Stuff for me there.
Then there are the pages at botepidemic.com
which were done by runab0ut
and hosted by ze0. If you've got
questions or suggestions about the POD Internet pages please mail them instead
of me. Furthermore there are a lot of nice supportive
people like Bluesman (moderator at the forum), TAZ (great
waypointer, good moderator),
Bot_Guy (beta-testing & waypointing), Chris (beta-testing),
Fairus (did invest some time doing a Community Site) and
Kangaroo (always supportive & helpful, 1st person ever who posted
in my forum, will never forget that!) to name just a few.
I know there are a lot more I should mention here, just blame my short-term
memory.
Why did you write this Bot ?
When I started coding, there only was Android Bot by DaTa. I really
liked Android, but at that time you could only play
DE_DUST with it and I got bored with it. Then I found out that it was based
on Botman's Ideas and code and thought I
could do that as well. So instead of waiting for updates, I took my trusty
VC++ and did a Bot on my own.
Besides, I never did a lot of AI programming before nor pathfinding and
we all have to learn the whole life, haven't we ?
Does this Bot support MODs other than CounterStrike ?
No, this Bot was coded especially for CounterStrike. If you want
to play for example TFC with a Bot, you have
to install HPB-Bot by Botman which supports several MODs in one.
I don't plan to extend my Bot to others since I'm
only interested in CS. Maybe I will do modificated Versions of it for other
MODs, but only if I finished all modes for CS
and I find the time and interest to do it.
Why should I use this Bot and not <insert-your-favourite-bot> ?
Well, because at the moment of writing I think this one is the most playable
and human acting Bot for Counterstrike.
Yes, it uses predefined waypoints but show me a Non-Human Opponent in any
newer Game. which doesn't
(Unreal & Quake3 for example also use a mixture of waypoints and terrain
analyzing) If you don't like it, feel free
to try the others. Even if you do, compare it with the others to have your
own judgement.
Will I be able to play CounterStrike on the Internet or on a LAN with
the POD-Bot installed?
YES! You can join a network game over the Internet or on a LAN without having
to uninstall the Bot. You cannot
spawn bots when connected to an Internet server, but you can spawn bots
on a LAN if you are running the server.
If you're hosting a Server you can even spawn Bots in the Internet.
Why do I get "Unknown Command" if I type "addbot"
in the Console ?
You must have overwritten the "liblist.gam" File in the cstrike
Folder. If this happens for example by installing a
Counterstrike Update the liblist.gam will point to the original Counterstrike
DLL and the Bots DLL won't get called.
Search for the Line gamedll "dlls\mp.dll" in liblist.gam
and replace it with gamedll "PODBot\podbot.dll" to
re-install it. Another reason could be that you unzipped the Archive into
the wrong Folder.
NOTE: You have to unzip it into the Halflife Main Folder NOT
the cstrike one !
I downloaded some custom waypoints and POD doesn't seem to find them.
What's wrong ?
You unzipped them into the wrong directory or you're using a wpt file which
is too old for your current POD version.
If you're using POD 1.2 or older the default folder to unpack the
files is the main PODBot Directory.
If you're using V1.4-V1.4x the default folder for wpts is "PODBot/WPTCS10".
Now since POD V2.0 the default waypoint folder is called (Surprise,Surprise!)
"PODBot/WPTDefault".
How do I edit the Config Files you're talking of ?
Just open it with a simple texteditor, for example Windows Notepad will
do.
Is it possible to remove the [POD] and the skill in the botnames ?
Yes, there are 2 different methods to get rid of them. The easiest one is
to edit your podbot.cfg file located in the podbot
folder. Just change the line 'detailnames on' to 'detailnames
off'. The second would be to specify a name when manually
typing addbot.
I can't get the POD-Bot Menu to work, can I bind it to another key
?
I was playing counter-strike, and I hit the minus key several times, shrinking
my screen size. I can't get it bigger
again because the +/= key is bound to the POD-Bot Menu.
Certainly. Take a look into the podbot.cfg and edit the line
'bind "=" "podbotmenu"' to any key you like.
My bots fly and seems to have the legs spread in the air, is it a bug
in POD-Bot ?
LOL! No, it's not. Make sure you always have the latest HL Update
installed.
For example CS 1.0 needs at least the HL Update <IP_ADDRESS> and CS 1.1
won't work properly if you haven't got
the <IP_ADDRESS> Update. If you're sure you've installed the latest patch and
you're still experiencing this
problem, also make sure that you didn't install custom player models.
Why do the Bots get stuck in each other or in the map ?
First and foremost the Bots do navigate the map by the use of waypoints.
These waypoints are somehow like
dropped 'beacons' which help the Bots to orientate themselves. If the waypointer
did a bad job when placing them,
it will result in a crappy movement. So make sure your waypoints files are
new & of good quality to have a good
judgement about the Bots movement. If you're not satisfied with the current
waypoints you can edit them yourself.
Just read the 'waypointshowtodo.html'
in your main podbot folder.
Do Admin Mod and POD-Bot work together ?
Yes. I heard there might be problems with newer versions of Admin-MOD but
I know for sure that running POD with older
versions did work without flaws. If you still can't get it to work please
mail Alfred, the Author of Admin MOD
instead of me.
Can I use different Bots with CounterStrike ?
Not at the same time but you can easily switch between them by changing
the gamedll in 'liblist.gam'. If you don't have a
clue what I'm talking about use a BotLauncher which does it for you e.g.
Multi-Bot Launcher.
When will you be releasing the next version of the POD Bot?
If I believe there are enough Features added, so that a new Release is satisfying
enough
(usually a month or two is enough to add some funky things, but development
cycles are slowing down).
Please don't keep pushing me in e-mails, I will delete them... !
When are you going to provide <insert_your_favorite_feature_here>
into the POD Bot?
I'm adding features to the Bot, which I am most interested in. Over the
time I want to have all Game Goals and
useful stuff implemented. Just be patient and wait for the next release
!
Does POD-Bot run on Linux ?
No, not yet. There needs to be a separate version especially compiled &
modified for the Linux OS for which I sadly
didn't have time to do so yet.
Will there ever be a Linux Version of POD ?
Yes. However since I'm promising this for quite some time now, I won't tell
dates anymore. Just wait and see...
How do I write my own Bot ? What do I need for this ?
First, you need a good understanding of C/C++. It would help a lot if you
did a MOD before or read the Halflife SDK.
A good place to start writing a Halflife Bot is Botmans Webpage (see the
URL in the 2nd Question).
Before you ask: No, there isn't any Webpage or Source I know of, which especially
has Sources on CounterStrike Bots
or how to code one.
UPDATE:
Elite, Coder of the CS Teambot gives away his sources here:
http://www.planethalflife.com/teambot/
CS-Bot & its sources by Eric Bieschke can be found here:
http://gamershomepage.com/csbot/
Would you help me in developing my own Bot ?
It depends. If I see you really know programming by heart, then I will surely
exchange ideas. If you just want to
change minor things in the original HPB Bot, then NO!
Are your Sources available for download ? Will you open your sources
to the public in future times ?
I don't feel like releasing my sources now, because of it's poorly commented,
weak style and I think a lot of people
would only try to rip off parts from it. I will surely release it when I
feel it's in a finished state and I'm not interested in
adding things to it. Until then please be patient and use for example Botman's
templates to do your own Bot.
When will my favourite map be supported ?
I currently only did waypoints for my favourite maps and all of them are
official standard maps. Since V1.1 you're free
to use the built-in waypoint editor to support your favourite maps.
Where can I get this Waypoint Editor to make my own waypoints ? Please
tell me the URL !
You already have it if you installed POD. Type 'waypoint on' to check
it out if you don't believe me ;)
If you're serious about waypointing, then please read 'waypointshowto.html'
What are your favourite CounterStrike Bots besides your own ?
At the time of writing, there are already a few others I like to play with.
I admire "Android" by DaTa for using
wayzones to achieve a great movement. I played a lot of time with NNBot
by Daniel Ditlew which uses Neural
Networks to train the Bots (a thing which I fear I would have never managed
to implement). And finally there is
Realbot by Stefan Hendriks which has a big community since it doesn't
use waypoints of any sort and navigates
from one entity to another. Ah yes, and then there's Rambot by Paulo-La-Fritte
which was released very early
and had some advanced features, but it has been a bit quiet in development
these days. All of these have their own
"look and feel" and make good Bots for playing. Not to mention
SwatBot, BobaBot, Knifebot (I certainly missed some)
there are numerous other CS Bots if you don't like these. If you ask me
again, at the moment I play with NNBot most
of the time and can't wait for a new version of HPB-Bot to be released,
which shocks me with great new
features everytime...
Would you like me to send some suggestions to you ?
Please...no...don't ! I would prefer if you would use the Forum
for that (also for reporting Bugs!) since I get a ton
of e-mails every day and I can't keep up with answering all of them. I visit
the Forum on a regular basis and there might
be some other guys who already posted that suggestion/bug.
Can I help you in some way (betatesting/hosting/gfx) ?
No, thank you. A Bot is best coded by a single person, I'm already hosted
by some friendly people and the best
beta-tester is still me. If you want to help you could review waypoints
for POD or you could do some additional Botchat
Files in your language. There's nothing else I could think of.
Why does your Bot use waypoints ? I want to play some unsupported maps
without doing waypoint files.
I knew you would ask. Simply because I don't believe in a Bot who is doing
great without any kind of navigational help.
Show me only one First Person Shooter where the Computer AI doesn't use
either waypoints, wayzones or pre-defined
areas. I'm pretty sure you won't find any. The reason for this again is
simple. It would just take too much CPU Power to
realtime calculate all Geometry inside a map. Imagine a Bot either shooting
some dozens of TraceLines through the part
of the map he's seeing or sorting all entity coordinates he encounters.
Doesn't matter what he actually does, it's just way
too slow for the current state of CPU technology.
I don't tell this to discourage Bot authors attempting this. Just prove
me wrong and keep trying !
I've downloaded some custom waypoints. Where do I put them ? I always
get a message like 'No Waypoints for this Map' !
If you didn't change the folder for waypoints with the 'wptfolder' command,
the default directory to install waypoints is 'cstrike/podbot/wptdefault'.
I'm unable to do good waypoints for POD. Also I'm unsure about several
explanations in your
waypointshowtodo.html. What can I do ? Should I e-mail you my questions
or should I send you my buggy
waypoint file ?
No ! For heavens sake don't do that ! If you don't know how to waypoint
or have some questions about it, please visit
the waypoint
forum at nuclearbox. There are a lot of experienced people willing to
help you and posting your questions
to the forum might help other newbies, too.
I did Waypoints for a map which isn't officially supported by POD-Bot
yet. May I send it to you to include it
with later versions ?
I don't have an overview of already released waypoint files by other people
than me. Best is to send them to TAZ or
Auxois, who try to collect and maintain all waypoints.
<EMAIL_ADDRESS><EMAIL_ADDRESS>Where can I download additional waypoints for custom maps ?
On the POD Download Page you can download more than 300 additional Waypoint
Files made by other Users
just for you. I don't know the quality of these waypoints though, so please
direct all complains to the original authors.
URL: http://www.nuclearbox.com/podbot/downloads.shtml
Why aren't there any waypoint packs to download ?

How do I play alone in my team against a team of Bots ?
It's easily done by using the in-build User Menu. Press the key for
displaying the Menu (defaults to the "=" key). Then
select "Fill Server with Bots" and after that choose the
team you want the Bots to be.
I did a translation of the botchat.txt into my own language. Do you
want me to send it to you ?
If it's a 100% translation of the original text, it's not already included,
it's a widely spread language (no local dialects
please!) and you made sure it's working with POD then yes, I'd be glad to
receive it.
Will POD run on a dedicated Server ?
Yes, the most important commands are also supported when starting a dedicated
Server. Most people think that
POD doesn't support it because they didn't get the big difference between
the normal console commands and the
ones for DS. When running a DS you need to have the word "bot"
before the actual command. For example to add a
Bot in non DS Mode you just type "addbot". When running a DS you
need to type "bot addbot". Please take a look into
the readme.html for a summary of all DS commands.

Please be patient ! I really try to answer everyone but I currently have
problems keeping up with all the mails I got.
Also, if you're writing from gmx.net I'm unable to reply, because they seem
to block most mails coming from yahoo.
If one week has passed without any answer then I must have missed your mail
or it just got lost on its way. Also I
usually reply much faster in the forum...
If you have questions not answered in this FAQ you can visit the Forum:
http://www.nuclearbox.com/ubb/cgi-bin/ultimatebb.cgi?ubb=forum&f=15
If you think you can't live without e-mailing me try this one -><EMAIL_ADDRESS>(please don't mail me suggestions or your personal wishlist, use the Forum
instead !
AND DON'T ASK ME FOR RELEASE DATES OF FUTURE VERSIONS, SUCH E-MAILS WILL
BE
DELETED AT ONCE!
There's even a POD-Bot IRC Channel now on irc.gamesnet.net, Port 6667.
Sometimes I can be found chatting in the #podbot channel too.


invitation for #30Days30Sites demo code in github html, scss tourist attraction for #30Days30Sites demo code in github only bootstrap 4 classes


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| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
java.lang.Object rmp.JxtaReliableEvent
Title: Reliable Multicast Pipes
Description:
Container of the JxtaReliableEvent events, generated by the sending - receiving action of the channel
Copyright: Copyright (c) 2005
Company: JXTA ORG
| Field Summary | |
int |
action
It points out whether this event is a Receive [set to RECEIVE ] or a Send [set to SEND ] event. |
java.lang.String |
channelID
It holds the ID of the channel from which the message was received. |
java.lang.String |
Data
The data element of the message that we received , and that generated the event. |
java.lang.String |
McastPath
The path of the multicast tree that is traversed till this hop by the message that we received and then generated the event. |
java.lang.String |
MessageType
It hold the type of the message that we received. |
java.lang.String |
MsgSeqNum
The Sequence Number of the message that we received, as it is numbered by the root-peer of the channel. |
static int |
RECEIVE
one of the values that action can take |
static int |
SEND
one of the values that action can take |
java.lang.String |
sender
It holds the Peer Name of the peer that sent us the message that generated the event. |
java.lang.String |
senderId
It holds the Peer ID of the peer that sent us the message that generated the event. |
| Constructor Summary | |
JxtaReliableEvent()
|
| Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Field Detail |
public static final int SEND
action
can take
public static final int RECEIVE
action
can take
public int action
RECEIVE
] or a Send [set to SEND
] event.
public java.lang.String sender
public java.lang.String senderId
public java.lang.String MessageType
public java.lang.String channelID
public java.lang.String MsgSeqNum
public java.lang.String McastPath
public java.lang.String Data
| Constructor Detail |
public JxtaReliableEvent()
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A community conference for data makers everywhere |
||
|
Featuring stories about data sharing and data analysis from science, journalism, government, and open source. May 2-3 2017, Portland, OR
Building Community
We want to bring together data makers/doers/hackers from backgrounds like science, journalism, open government and the wider software industry to share knowledge and stories.
For those who love data
csv,conf is a non-profit community conference run by some folks who really love data and sharing knowledge. If you are as passionate about data and the application it has to society as us then you should join us in Portland!
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This isn't just a conference about spreadsheets. We are curating content about advancing the art of data collaboration, from putting your data on GitHub to producing meaningful insight by running large scale distributed processing on a cluster. |
| Keynote Speakers | |||
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Mike BostockMike Bostock is the creator of the popular open-source JavaScript library for visualization data, D3.js. Previously he was a graphics editor for The New York Times, where he helped produce a variety of data visualizations (such as Is It Better to Rent or Buy? and 512 Paths to the White House), maps (The Most Detailed Maps You’ll See From the Midterm Elections), and articles (A Game of Shark and Minnow). Prior to The Times, Mike was a visualization scientist for Square and a PhD student in the Stanford Visualization Group. Angela BassaAngela Bassa is the Director of Data Science at iRobot, where she leads the newly-formed team through development of machine learning algorithms, sentiment analysis, and anomaly detection processes. Angela is also a technical advisor for Mirah, a startup focused on making behavioral healthcare more objective and data-driven. Her previous projects earned accolades such as INFORMS’ Edelman award for Achievement in Operations Research and the Management Sciences; and the Massachusetts Innovation & Technology Exchange award for Big Data and Analytics Innovations. She discovered data science while studying math at MIT, only back then it wasn't called that yet. Over the past two decades she has learned to lead data teams in academic, commercial, and industrial applications. Angela also has three patented inventions, as well as 24 patent applications currently pending in the US, the EU, and Australia. Heather JosephHeather Joseph is the Executive Director of SPARC, a global coalition committed to making Open the default for research and education. She has focused SPARC’s efforts on supporting new models for the open sharing of digital articles, data and educational resources. Under her stewardship, SPARC has become widely recognized as the leading international force for effective open access policies and practices. TBA |
| Speakers | |
|---|---|
| Announcing Soon | Our CFP is now closed. We'll let submitters know whether their talk has been accepted by March 15th. We'll announce the line-up shortly afterwards. |
| Date | Location | Link |
|---|---|---|
| 2-3 May 2017 | Portland, Oregon | Earlybird Tickets Now Available! |
| 3-4 May 2016 | Berlin, Germany | See talks |
| 15 July 2014 | Berlin, Germany | See talks |


- validateWithFillDefault() - Method in class io.parallec.core.ParallelTask
-
will do validation.
- validation() - Method in class io.parallec.core.bean.HttpMeta
-
Validation.
- validation() - Method in class io.parallec.core.bean.ping.PingMeta
-
- validation() - Method in class io.parallec.core.bean.ssh.SshMeta
-
Validation.
- validation() - Method in class io.parallec.core.bean.tcp.TcpMeta
-
- validation() - Method in class io.parallec.core.bean.udp.UdpMeta
-
- validation() - Method in class io.parallec.core.ParallelTaskBuilder
-
add some validation to see if this miss anything.
- valueOf(String) - Static method in enum io.parallec.core.actor.message.type.ExecutionManagerMsgType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum io.parallec.core.actor.message.type.OperationWorkerMsgType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum io.parallec.core.actor.message.type.RequestWorkerMsgType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum io.parallec.core.bean.ping.PingMode
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum io.parallec.core.bean.SingleTargetTaskStatus
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum io.parallec.core.bean.ssh.SshLoginType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum io.parallec.core.bean.TaskRunMode
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum io.parallec.core.config.HandlerExecutionLocation
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum io.parallec.core.exception.ExecutionManagerExecutionException.ManagerExceptionType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum io.parallec.core.HostsSourceType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum io.parallec.core.RequestProtocol
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum io.parallec.core.resources.HttpClientType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum io.parallec.core.resources.HttpMethod
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum io.parallec.core.task.ParallelTaskState
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum io.parallec.core.task.RequestReplacementType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum io.parallec.core.task.TaskErrorMeta.TaskErrorType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum io.parallec.core.util.PcErrorMsgUtils.ERROR_TYPE
-
Returns the enum constant of this type with the specified name.
- values() - Static method in enum io.parallec.core.actor.message.type.ExecutionManagerMsgType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum io.parallec.core.actor.message.type.OperationWorkerMsgType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum io.parallec.core.actor.message.type.RequestWorkerMsgType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum io.parallec.core.bean.ping.PingMode
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum io.parallec.core.bean.SingleTargetTaskStatus
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum io.parallec.core.bean.ssh.SshLoginType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum io.parallec.core.bean.TaskRunMode
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum io.parallec.core.config.HandlerExecutionLocation
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum io.parallec.core.exception.ExecutionManagerExecutionException.ManagerExceptionType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum io.parallec.core.HostsSourceType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum io.parallec.core.RequestProtocol
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum io.parallec.core.resources.HttpClientType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum io.parallec.core.resources.HttpMethod
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum io.parallec.core.task.ParallelTaskState
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum io.parallec.core.task.RequestReplacementType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum io.parallec.core.task.TaskErrorMeta.TaskErrorType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum io.parallec.core.util.PcErrorMsgUtils.ERROR_TYPE
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- VAR_NAME_APIVARREPLACE_HTTPHEADER_AUTH_TOKEN - Static variable in class io.parallec.core.util.PcConstants
-
The var name apivarreplace httpheader auth token.
- VarReplacementProvider - Class in io.parallec.core.commander.workflow
-
Deal with WISB Var generator and get values
extending from replacing only WISB based.
- VarReplacementProvider() - Constructor for class io.parallec.core.commander.workflow.VarReplacementProvider
-
Instantiates a new var replacement provider.


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| Jeremey White | 03/06/2017 | Bread | 34345 |
| Martin Martinez | 06/15/2021 | Meatballs | 67646 |
| Bethany Tran | 03/21/2021 | Canned Corn | 19854 |
| Stefan Mason | 05/31/2021 | Salad Dressing | 00393 |
Copyright © 2018 Colorlib. All rights reserved. Template by Colorlib.


Class: ActionDispatch::Session::CookieStore
| Inherits: |
AbstractStore
|
| Defined in: |
Overview
This cookie-based session store is the Rails default. It is dramatically faster than the alternatives.
Sessions typically contain at most a user_id and flash message; both fit within the 4K cookie size limit. A CookieOverflow exception is raised if you attempt to store more than 4K of data.
The cookie jar used for storage is automatically configured to be the best possible option given your application's configuration.
If you only have secret_token set, your cookies will be signed, but not
encrypted. This means a user cannot alter their user_id
without knowing your app's secret key, but can easily read their
user_id
. This was the default for Rails 3 apps.
If you have secret_key_base set, your cookies will be encrypted. This goes a step further than signed cookies in that encrypted cookies cannot be altered or read by users. This is the default starting in Rails 4.
If you have both secret_token and secret_key_base set, your cookies will be encrypted, and signed cookies generated by Rails 3 will be transparently read and encrypted to provide a smooth upgrade path.
Configure your session store in config/initializers/session_store.rb:
Rails.application.config.session_store :, key: '_your_app_session'
Configure your secret key in config/secrets.yml:
development:
secret_key_base: 'secret key'
To generate a secret key for an existing application, run `rails secret`.
If you are upgrading an existing Rails 3 app, you should leave your existing secret_token in place and simply add the new secret_key_base. Note that you should wait to set secret_key_base until you have 100% of your userbase on Rails 4 and are reasonably sure you will not need to rollback to Rails 3. This is because cookies signed based on the new secret_key_base in Rails 4 are not backwards compatible with Rails 3. You are free to leave your existing secret_token in place, not set the new secret_key_base, and ignore the deprecation warnings until you are reasonably sure that your upgrade is otherwise complete. Additionally, you should take care to make sure you are not relying on the ability to decode signed cookies generated by your app in external applications or JavaScript before upgrading.
Note that changing the secret key will invalidate all existing sessions!
Because CookieStore extends Rack::Session::Abstract::Persisted
, many of
the options described there can be used to customize the session cookie
that is generated. For example:
Rails.application.config.session_store :, expire_after: 14.days
would set the session cookie to expire automatically 14 days after
creation. Other useful options include :key
,
:secure
and :httponly
.
Class Method Summary collapse
-
.new(app, options = {}) ⇒ CookieStore
constructor
a new instance of CookieStore
Instance Method Summary collapse
- #cookie_jar(request) private
- #delete_session(req, session_id, options)
- #extract_session_id(req) private
- #get_cookie(req) private
- #load_session(req)
- #persistent_session_id!(data, sid = nil) private
- #set_cookie(request, session_id, cookie) private
- #unpacked_cookie_data(req) private
- #write_session(req, sid, session_data, options) private
Methods included from SessionObject
#loaded_session?, #prepare_session
Methods included from StaleSessionCheck
Methods included from Compatibility
#generate_sid, #initialize, #initialize_sid, #make_request
Constructor Details
.new(app, options = {}) ⇒ CookieStore
a new instance of CookieStore
66 67 68
# File 'actionpack/lib/action_dispatch/middleware/session/cookie_store.rb', line 66
def initialize(app, ={}) super(app, .merge!(cookie_only: true)) end
Instance Method Details
#cookie_jar(request) (private)
[ GitHub ]124 125 126
# File 'actionpack/lib/action_dispatch/middleware/session/cookie_store.rb', line 124
def (request) request..signed_or_encrypted end
#delete_session(req, session_id, options)
[ GitHub ]70 71 72 73 74 75
# File 'actionpack/lib/action_dispatch/middleware/session/cookie_store.rb', line 70
def delete_session(req, session_id, ) new_sid = generate_sid unless [:drop] # Reset hash and Assign the new session id req.set_header("action_dispatch.request.unsigned_session_cookie", new_sid ? { "session_id" => new_sid } : {}) new_sid end
#extract_session_id(req) (private)
[ GitHub ]87 88 89 90 91
# File 'actionpack/lib/action_dispatch/middleware/session/cookie_store.rb', line 87
def extract_session_id(req) stale_session_check! do (req)["session_id"] end end
#get_cookie(req) (private)
[ GitHub ]120 121 122
# File 'actionpack/lib/action_dispatch/middleware/session/cookie_store.rb', line 120
def (req) (req)[@key] end
#load_session(req)
[ GitHub ]77 78 79 80 81 82 83
# File 'actionpack/lib/action_dispatch/middleware/session/cookie_store.rb', line 77
def load_session(req) stale_session_check! do data = (req) data = persistent_session_id!(data) [data["session_id"], data] end end
#persistent_session_id!(data, sid = nil) (private)
[ GitHub ]105 106 107 108 109
# File 'actionpack/lib/action_dispatch/middleware/session/cookie_store.rb', line 105
def persistent_session_id!(data, sid=nil) data ||= {} data["session_id"] ||= sid || generate_sid data end
#set_cookie(request, session_id, cookie) (private)
[ GitHub ]116 117 118
# File 'actionpack/lib/action_dispatch/middleware/session/cookie_store.rb', line 116
def (request, session_id, ) (request)[@key] = end
#unpacked_cookie_data(req) (private)
[ GitHub ]93 94 95 96 97 98 99 100 101 102 103
# File 'actionpack/lib/action_dispatch/middleware/session/cookie_store.rb', line 93
def (req) req.fetch_header("action_dispatch.request.unsigned_session_cookie") do |k| v = stale_session_check! do if data = (req) data.stringify_keys! end data || {} end req.set_header k, v end end
#write_session(req, sid, session_data, options) (private)
[ GitHub ]111 112 113 114
# File 'actionpack/lib/action_dispatch/middleware/session/cookie_store.rb', line 111
def write_session(req, sid, session_data, ) session_data["session_id"] = sid session_data end


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Desserts
Follow These Delicious Recipes
Tres Leches CakeOnce you have tried a well prepared Three Milk Cake, you could certanly add this as a part of your life changing experiences. I’m not even exaggerating with this. To say that this spongy cake sogged in the most delicious milk cream is “good” is a major understatement. You can make this cake the day before and decorate with the meringue just before serving. This way the white topping will be flawless. The tres leches are one of those cakes that gets better the day after when the cake has had more time to absorb the milk cream. You can garnish this cake with powder cinnamon. Some people use fresh fruit. If you decided to use fruit, try to place it only when the cake is going to be served. The water of the fruit will melt the meringue. The last thing that you want is stained holes in your meringue with soggy fruit inside. |


Just in Time
JIT TQM: total quality management
TOC: theory of constraints
- Smaller more frequent shipments - toyota production system
- Elimination of waste
- Time is most precious resource
- energy
- supplies
- errors are a waste: design systems that are fail safe
- inventory: reduce inventory to level that is needed
Japanese consider inventory a waste Dr. Ohono
- Stockless production: reduce inventory wherever possible
- Pull production system: pulls in inventory WIP when the worker is ready for new work.
- Push system: go as fast as you can
- Kan ban: Signal from one worker to the next that they are ready for more material
- Reduce batch sizes
- Reduction of all inventory
- Production schedules that level capacity
- Visual control systems
- Direct ties with vendors
- Reduce eliminate setup time
- Focus on continuous improvement
14 Points
America in the Global Market
Demming method of quality - professor TQM
Competitiveness is not what it should be.
We got what we wanted - the reason we are
- The American system of industrial production - Mechanical efficiency
- People not machines
- Production line
- Motion study expert - break big jobs into little jobs.
- Ford >> Bombers
- Every industrial nation was hampered by WWII
- Endure the unendurable - suffer the insufferable
American domestic market used to be the largest market - More educated than rest of world - Managers were more successful - Statistical quality control - Enormous demand - only concern for output no reason to innovate - Never innovated - never developed new solutions
-
The solution to any problem will lead to another problem
- Necessary to continuously improve.
Politics is too concerned with votes and popularity
Protectionism will lead to inflation and recession
Reduce the international trade deficit
The 14 points part 1
Loyd Dawbins
Basic changes
TQM Total quality management We have met the ene - Make change - payoffs will take time 5-10 years long term - Better quality and lower costs - Can only be done by top management - management is super important - Standard of living is improved
- Constancy of purpose: Innovation - look into the future- requires long term vision
- Adopt a new philosophy: quality is made in the board room - specialized knowledge
- Cease dependence on mass inspection: focus on producing quality parts rather than inspecting poorly made products
- Cease doing business on price tag: Make long term relationships with vendors
- Continual improvement of processes: don’t find what’s wrong, fix it
- Training and retraining: management and people/ labor. Everyone is a customer
- Improvement of leadership
The firm of tomorrow will need to create a community for itself
- Staff areas must work together - to drive out fear
- Get rid
-
-
-
-
After WWII made in USA was a big part of success
Jim Sinegal
Costco: founded by Jim Sinegal
- Company that’s on a first name basis
- Working class values for corporate culture
- 4th largest retailer (8 countries)
- Caskets - painting Picasso
- Only sells 4000 items of better quality
- Make it up on volume
- Largest seller of fine wine
- Often managing from the road and will visit up to 12 stores
- Lowest employee turnover with better pay and benefits
- Promote from within
- Doesn’t spend anything on advertising/ or PR
- Pay high wages
- Keep it simple treat your customer like guests


| Acey Ducey |
aceyducey.bas |
Play acey-ducey with the computer |
| Amazing |
amazing.bas |
Computer constructs a maze |
| Animal |
animal.bas |
Computer guesses animals and learns new ones from you |
| Awari |
awari.bas |
Ancient game of rotating beans in pits |
| Bagels |
bagels.bas |
Guess a mystery 3-digit number by logic |
| Banner |
banner.bas |
Prints any message on a large banner |
| Basketball |
basketball.bas |
Basketball game |
| Batnum |
batnum.bas |
Match wits in a battle of numbers vs. the computer |
| Battle |
battle.bas |
Decode a matrix to locate enemy battleship |
| Blackjack |
blackjack.bas |
Blackjack (very comprehensive), Las Vegas rules |
| Bombardment |
bombardment.bas |
Destroy the computer's platoons with missles before it finds yours |
| Bombs Away |
bombsaway.bas |
Fly World War II bombing missions |
| Bounce |
bounce.bas |
Plot a bouncing ball |
| Bowling |
bowling.bas |
Bowling at the neighborhood lanes |
| Boxing |
boxing.bas |
3-round Olympic boxing match |
| Bug |
bug.bas |
Roll dice vs. the computer to draw a bug |
| Bullfight |
bullfight.bas |
You're the matador in a championship bullfight |
| Bullseye |
bullseye.bas |
Throw darts |
| Bunny |
bunny.bas |
Computer drawing of the Playboy bunny |
| Buzzword |
buzzword.bas |
Compose your speeches with the latest buzzwords |
| Calendar |
calendar.bas |
Calendar for any year |
| Change |
change.bas |
Computer imitates a cashier |
| Checkers |
checkers.bas |
Game of checkers |
| Chemist |
chemist.bas |
Dilute kryptocyanic acid to make it harmless |
| Chief |
chief.bas |
Silly arithmetic drill |
| Chomp |
chomp.bas |
Eat a cookie avoiding the poison piece (2 or more players) |
| Civil War |
civilwar.bas |
Fight the Civil War |
| Combat |
combat.bas |
Fight a small-scale war with the computer |
| Craps |
craps.bas |
Play craps (dice), Las Vegas style |
| Cube |
cube.bas |
Negotiate a 3-D cube avoiding hidden landmines |
| Depth Charge |
depthcharge.bas |
Launch depth charges to destroy a submarine |
| Diamond |
diamond.bas |
Prints 1-page diamond patterns |
| Dice |
dice.bas |
Summarizes dice rolls |
| Digits |
digits.bas |
Computer tries to guess digits you select at random |
| Even Wins |
evenwins.bas |
Take objects from a pile—try to end with an even number |
| Game of Even Wins |
gameofevenwins.bas |
Same as Even Wins—computer improves its play |
| Flip Flop |
flipflop.bas |
Solitaire logic game—change a row of Xs to Os |
| Ftball |
ftball.bas |
American football—you vs. the computer |
| Football |
football.bas |
American football for two players |
| Fur Trader |
furtrader.bas |
Trade furs with the white man |
| Golf |
golf.bas |
Golf game—choose your clubs and swing |
| Gomoko |
gomoko.bas |
Ancient board game of logic and strategy |
| Guess |
guess.bas |
Guess a mystery number—computer gives you clues |
| Gunner |
gunner.bas |
Fire a cannon at a stationary target |
| Hammurabi |
hammurabi.bas |
Govern the ancient city-state of Sumeria |
| Hangman |
hangman.bas |
Hangman word guessing game |
| Hello |
hello.bas |
Computer becomes your friendly psychiatrist |
| Hexapawn |
hexapawn.bas |
Hexapawn game |
| Hi-Lo |
hi-lo.bas |
Try to hit the mystery jackpot |
| High I-Q |
highiq.bas |
Try to remove all the pegs from a board |
| Hockey |
hockey.bas |
Ice hockey, two players |
| Horserace |
horserace.bas |
Off-track betting on a horse race |
| Hurkle |
hurkle.bas |
Find the Hurkle hiding on a 10x10 grid |
| Kinema |
kinema.bas |
Drill in simple kinematics |
| King |
king.bas |
Govern a modern island kingdom wisely |
| Letter |
letter.bas |
Guess a mystery letter—computer gives you clues |
| Life |
life.bas |
John Conway's Game of Life |
| Life For Two |
lifefortwo.bas |
Competitive game of Life (two or more players) |
| Literature Quiz |
litquiz.bas |
Children's literature quiz |
| Love |
love.bas |
Robert Indiana's artwork, your message |
| Lunar |
lunar.bas |
Land an Apollo capsule on the moon |
| LEM |
lem.bas |
Very comprehensive lunar landing |
| Rocket |
rocket.bas |
Lunar landing from 500 feet (with plot) |
| Master Mind |
mastermind.bas |
Guess the colors of pegs—then the computer guesses yours |
| Math Dice |
mathdice.bas |
Children's arithmetic drill using pictures of dice |
| Mugwump |
mugwump.bas |
Locate 4 mugwumps hiding on a 10x10 grid |
| Name |
name.bas |
An ice-breaker with the computer |
| Nicomachus |
nicomachus.bas |
Computer guesses number you think of |
| Nim |
nim.bas |
Chinese game of Nim |
| Number |
number.bas |
Silly number matching game |
| One Check |
onecheck.bas |
Challenging game to remove checkers from a board |
| Orbit |
orbit.bas |
Destroy an orbiting germ-laden enemy spaceship |
| Pizza |
pizza.bas |
Deliver pizzas successfully |
| Poetry |
poetry.bas |
Computer composes random poetry |
| Poker |
poker.bas |
Poker game |
| Queen |
queen.bas |
Move a single chess queen vs. the computer |
| Reverse |
reverse.bas |
Order a series of numbers by reversing |
| Rock, Scissors, Paper |
rockscissors.bas |
Game of rock, scissors, paper |
| Roulette |
roulette.bas |
European roulette table |
| Russian Roulette |
russianroulette.bas |
Russian roulette |
| Salvo |
salvo.bas |
Destroy an enemy fleet of ships |
| Sine Wave |
sinewave.bas |
Draw a sine wave on screen |
| Slalom |
slalom.bas |
Simulates a slalom run |
| Slots |
slots.bas |
Slot machine (one-armed bandit) |
| Splat |
splat.bas |
Open a parachute at the last possible moment |
| Stars |
stars.bas |
Guess a mystery number—stars give you clues |
| Stock Market |
stockmarket.bas |
Stock market simulation |
| Super Star Trek |
superstartrek.bas |
Comprehensive game of Star Trek |
| Super Star Trek: Instructions |
superstartrekins.bas |
Instructions for Super Star Trek |
| Synonym |
synonym.bas |
Word synonym drill |
| Target |
target.bas |
Destroy a target in 3-D space—very tricky |
| 3-D Plot |
3dplot.bas |
Plot families of curves—looks 3-dimensional |
| 3-D Tic-Tac-Toe |
qubit.bas |
Game of tic-tac-toe in a 4x4x4 cube |
| Tic-Tac-Toe 1 |
tictactoe1.bas |
Simple version |
| Tic-Tac-Toe 2 |
tictactoe2.bas |
This version prints out the board |
| Tower |
tower.bas |
Towers of Hanoi puzzle |
| Train |
train.bas |
Time-speed-distance quiz |
| Trap |
trap.bas |
Trap a mystery number—computer gives you clues |
| 23 Matches |
23matches.bas |
Game of 23 matches—try not to take the last one |
| War |
war.bas |
Card game of war |
| Weekday |
weekday.bas |
Facts about your birthday |
| Word |
word.bas |
Word guessing game |


17 Nov 2018
In some prior work, my colleagues and I have found that active control—being able to dictate the content or pacing of information—leads to enhanced episodic memory for materials experienced during study. Let’s say that I’m your instructor and I have a set of definitions on flashcards that I want you to learn. If I give you (the student) more control over the selection and pacing of flashcards, it’s likely that you’ll have better memory later on compared to conditions where you don’t have control.
But as an instructor, I don’t just want my students to memorize a set of independent definitions. I also want them to integrate those concepts together to form some coherent knowledge about the domain. For example, I don’t just want my research methods students to be able to define different types of validity; I also want them to be able to relate them to each other and the broader goals of experimental methods. In contrast to the first goal of forming memories of independent sets of items, it is less clear to what extent having control over learning leads to enhanced integration of study experiences into conceptual knowledge.
The project described in this poster aims to understand the effects of active control on relational knowledge formation. It uses a common relational reasoning task (transitive inference) to disentangle enhancements to memory for individual items from enhanced integrative encoding. The results so far suggest that having control over the selection of items leads to improved integrative encoding over a passive condition lacking such control. Critically, however, the benefit of active control only appears among people with higher working memory capacity. This provides another piece of evidence that the benefits of “active learning” may not be so universal, but instead depend on students having the cognitive resources to maintain and integrate disparate study experiences.
Click on the image below to get the PDF of the poster:
15 Nov 2016
Imagine that you’re on Amazon trying to decide which of two products to purchase. One way to learn about the options before you buy is to look at reviews from other people who have bought the same items. Each review gives you a glimpse into the relative value of each option, and you can explore each item (i.e., keep on reading reviews) for as long as you like until you feel ready to hit the buy button.
So, how many reviews do you decide to read for each product? How does the variability in the ratings affect how long you explore—for example, is there a difference between seeing a string of solid 4-star reviews as opposed to a mixture of 5-star and 3-star reviews? How does your exploration change when searching for a relatively mundane product like a power adapter as opposed to a major purchase like a computer?
At Psychonomics this week I’m presenting some new results from a project where we try to understand how people adapt their exploration in response to these kinds of environmental factors, including the variability in the outcomes they experience and the rewards that are at stake. The experiment described in the poster below was designed to test the predictions of a sequential sampling model that accounts for this adaptive exploration and its effects on how people make choices. Sequential sampling models are widely used to model the relationship between choices and response times in a number of decision making tasks, and our results suggest that similar mechanisms can account for the way that people sample experiences from the environment prior to making a choice.
Click on the image below to get the PDF of the poster:
16 Aug 2016
At CogSci this year I presented some new work on hypothesis generation and its role in self-directed learning (specifically, the learning of categorical rules). This project explores the idea that hypothesis generation is a bottleneck in active learning, as is suggested by a lot of work in classic cognitive tasks as well as studies from educational psychology. The results give an example of how biases in the hypothesis generation process can have a big impact on whether people can efficiently learn different kinds of rules.
For more on this project, see the paper in the proceedings and the poster below (PDF).
13 Jul 2016
I have a new paper out in Mind, Brain, and Education, coauthored with Azzu Ruggeri, Todd Gureckis, and Fei Xu. In the paper we argue that one reason active learning improves outcomes relative to passive conditions (like lectures) is that exercising control leads to enhanced memory (in particular, episodic memory for the events experienced during learning).
In many lab-based tasks, having control over learning (e.g., controlling the selection or pacing of new information) often leads to better memory compared to yoked conditions in which such control is absent but the same information is experienced. By surveying a range of research that has employed this kind of active/yoked design in different domains, we outline how improved memory can arise from a number of different mechanisms depending on the kind of control afforded to the active learner. Thinking about real-world learning activities in terms of this basic dimension of control (which is just one part of what people typically think of as “active learning”) may help us understand when and why active learning tends to produce better outcomes than traditional instruction.
A couple of things struck me while researching the paper:
-
Some form of episodic memory is important to many theories of conceptual learning or semantic memory – but episodic memory is not really a focus in educational research. Perhaps unsurprisingly, educational psychologists seem to be primarily interested in measures of conceptual learning: does the student remember the definition of a term, or how to solve a certain kind of physics problem? As far as I can tell there isn’t much work examining memory for the details of the learning experience (e.g., the activities completed, example problems that were encountered, conversations during class, etc.) and how it relates to other performance measures.
-
There’s a similar gap in lab-based research related to inquiry-based learning (including work on category and causal learning which usually shows an advantage for active control over yoked observation). This work has largely focused on the value of the information that active learners select (e.g., do they ask questions that are useful? Can they come up with experiments that lead to unconfounded evidence?). But it seems likely that the same set of memory-based mechanisms could play a role, particularly in real-world inquiry learning settings that involve richer materials and forms of interaction than the typical lab-based experiment.
Writing the paper helped me pinpoint some of these big open questions about how memory and control interact during learning. Of course, despite our best efforts it’s inevitable that we missed some existing work that would be useful. If you know of something relevant or have any other comments about the paper, let me know!
04 Jul 2016
Next month I’ll be participating in a full-day workshop at CogSci,
entitled “Active learning: Cognitive development, education, and
computational models.”
The workshop will feature lots of terrific researchers from the CogSci community
who have been thinking about active learning from many angles.
Come by if you are in Philly on Wednesday!


Thalaivi First Look Poster: Kangana Ranaut In And As Former Tamil Nadu CM Jayalalithaa
by Digital DeskBollywood News
Bollywood star Kangana Ranaut is all set to portray former Tamil Nadu chief minister, J Jayalalithaa, in a biopic. Rangoli released the first look poster.
Written By Digital Desk | Mumbai | Updated On: November 23, 2019 15:16 IST
Bollywood star Kangana Ranaut is all set to portray former Tamil Nadu chief minister, J Jayalalithaa, in a biopic. The first look of Kangana as the political stalwart will leave you shocked. Take a look.
Kangana Ranaut's sister Rangoli shares 'mood' after Maharashtra's political developments
The actor-turned-politician, who passed away on December 5, 2016 due to cardiac arrest, is fondly referred to as 'Puratchi Thalaivi', which means 'revolutionary leader'.
Titled "Thalaivi" in Tamil and "Jaya" in Hindi, the biographical drama will be directed by Vijay, one of the top filmmakers from South who has helmed movies like "Madrasapattinam" and "Deiva Thirumagal". "Jayalalithaa ji is one of the biggest female success stories of this century. She was a superstar and went on to become an iconic politician,it's a great concept for mainstream film. I am honoured to be a part of this mega project," Kangana said in a statement.
Amitabh Bachchan crowns Kangana Ranaut as 'Number 1 actress', Rangoli replies
Vijay said he is aware of the responsibility of making this film and the team will deal it with utmost care and honesty. "Jayalalithaa madam was one of the most prominent leaders of our country.  I am proud and happy with our association with Kangana Ranaut ji to portray the dynamic role of our very dynamic leader," he said.
Kangana Ranaut commences shooting for Jayalalithaa biopic Thalaivi
The film will be written by K V Vijayendra Prasad, who has also penned "Baahubali" and "Manikarnika", and will be produced by Vishnu Vardhan Induri and Shaailesh R Singh under the banners of Vibri & Karma Media and Entertainment.
Kangana Ranaut and Rangoli Chandel celebrate brother's engagement
Get the latest entertainment news from India & around the world. Now follow your favourite television celebs and telly updates. Republic World is your one-stop destination for trending Bollywood news. Tune in today to stay updated with all the latest news and headlines from the world of entertainment.


Accordion inside Tabcontrol
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{% extends 'includes/layout.html' %}
{% block content %}
{% include 'includes/personal.html' %}
{% include 'includes/skills.html' %}
{% include 'includes/other-skills.html' %}
{% include 'includes/projects.html' %}
{% include 'includes/work.html' %}
{% endblock %}


OHA board names Hussey permanent chief executive officer | Honolulu Star-Advertiser
Office of Hawaiian Affairs interim chief executive officer Sylvia Hussey today was named the agency’s next permanent CEO in a unanimous vote of the board of trustees.
Hussey, OHA’s former chief operating officer, will get a five-year contract worth $170,000 a year, starting Dec. 1.
Hussey, an educator with a doctor’s degree in education, became interim CEO July 1 following the expiration of the contract of her predecessor, Kamanaʻopono Crabbe.
The board previously hired a professional consultant to help search for a new executive, but Hussey’s time as interim CEO was exceptional, prompting the unanimous action, OHA Chairperson Colette Machado said in an interview.
“Each trustee feels confident that they will be treated with the same kind of aloha that she can treat me as the chair and some of the leadership, and that’s important when you want to build unity,” Machado said.
Hussey was hired as chief operating officer in November 2018 after more than 30 years in education administration, policy development, finance, operations and information technology. She previously served as executive director of the Native Hawaiian Education Council and before that as vice president of administration with Kamehameha Schools.


linefinder.analyze_data.worldline_set module¶
Tools for loading in multiple worldline data sets, for comparison
@author: Zach Hafen @contact<EMAIL_ADDRESS>@status: Development
-
class
linefinder.analyze_data.worldline_set.
WorldlineSet
(defaults, variations)[source]¶ Bases:
verdict.Dict
Container for multiple Worldlines classes. The nice thing about this class is you can use it like a Worldlines class, with the output being a dictionary of the different sets instead.
-
apply
(fn, *args, **kwargs)¶ Apply some function to each item in the smart dictionary, and return the results as a Dict.
-
array
()¶ Returns a np.ndarray of values with unique order (sorted keys )
-
call_custom_kwargs
(kwargs, default_kwargs={}, verbose=False)¶ Perform call, but using custom keyword arguments per dictionary tag.
Parameters: Returns: Dictionary of results.
Return type: results (dict)
-
call_iteratively
(args_list)¶
-
depth
(level=1)¶ Depth of the Dict.
Parameters: level (int) – A level of N means this Dict is contained in N-1 other Dict.
-
classmethod
from_class_and_args
(contained_cls, args, default_args={})¶ Alternate constructor. Creates a Dict of contained_cls objects, with arguments passed to it from the dictionary created by defaults and variations.
Parameters: - contained_cls (type of object/constructor) – What class should the smart dict consist of?
- args (dict/other) – Arguments that should be passed to contained_cls. If not a dict, assumed to be the first and only argument for the constructor.
- default_args – Default arguments to fill in args
Returns: The constructed instance.
Return type: Dict
-
classmethod
from_hdf5
(filepath, load_attributes=True, unpack=False)¶ Load a HDF5 file as a verdict Dict.
Parameters: - filepath (str) – Location to load the hdf5 file from.
- load_attributes (boolean) – If True, load attributes stored in the hdf5 file’s .attrs keys and return as a separate dictionary.
- unpack (boolean) – If True and the inner-most groups are combined into a condensed DataFrame/array-like format, unpack them into a traditional structure.
-
classmethod
from_tag_expansion
(defaults, tag_expansion)[source]¶ Create a worldline set using a bash-style expansion for the variations.
Parameters: Returns: worldline_set (WorldlineSet instance)
-
get
(k[, d]) → D[k] if k in D, else d. d defaults to None.¶
-
inner_item
(item)¶ When Dict is a dictionary of dicts themselves, this can be used to get an item from those dictionaries.
-
inner_keys
()¶
-
items
() → a set-like object providing a view on D's items¶
-
keymax
()¶
-
keymin
()¶
-
keys
() → a set-like object providing a view on D's keys¶
-
keys_array
()¶ Returns a np.ndarray of keys with unique order (sorted keys )
-
log10
()¶ Wrapper for np.log10
-
median
()¶
-
nanmedian
()¶
-
nanpercentile
(q)¶
-
percentile
(q)¶
-
plot_classification_bar_same_axis
(kwargs=<object object>, ind=0, width=0.5, data_order=<object object>, legend_args=<object object>, y_label='Classification Fraction', out_dir=None, save_file='bar_map.pdf', **default_kwargs)[source]¶
-
remove_empty_items
()¶ Look for empty items and delete them.
-
split_by_dict
(d, return_list=False)¶ Break the smart dictionary into smaller smart dictionaries according to their label provided by a dictionary
Parameters:
-
split_by_key_slice
(sl, str_to_match=None)¶ Break the smart dictionary into smaller smart dictionaries according to a subset of the key.
Parameters:
-
store_quantity
(output_filepath, quantity_method='get_categories_selected_quantity_fraction', variations=None, verbose=True, *args, **kwargs)[source]¶ Iterate over each Worldlines class in the set, obtaining a specified quantity and then saving that to an .hdf5 file. Note that verdict.Dict’s to_hdf5 method is simpler and more functional for many cases.
Parameters: - output_filepath (str) – Full path to store the output at.
- quantity_method (str) – What method to use for getting the quantity out.
- variations (dict) – If provided, we get different quantities from each Worldlines instance by passing different args to quantity_method according to variations. kwargs is taken as the default arguments when none are specified.
- **kwargs (*args,) –
Arguments to be passed to quantity_method.
-
store_redshift_dependent_quantity
(output_filepath, max_snum, choose_snum_by='pulling_from_ids', *args, **kwargs)[source]¶ Store a redshift dependent quantity. In particular, this method assumes that the differences between the Worldlines is a redshift difference, and that the label for each Worldlines class contains the relevant snapshot number. It then parses the label for that snapshot number, and passes it to store_dependent_quantity as a key.
Parameters: - output_filepath (str) – Where to save the output data.
- max_snum (int) – Maximum snapshot number the snapshots can go to. Used for parsing the label as well as specifying the ind.
- choose_snum_by (str) – How to to vary the snapshot used when the arguments are passed to the Worldlines.
- **kwargs (*args,) –
Arguments passed to self.store_dependent_quantity()
-
sum_contents
()¶ Get the sum of all the contents inside the Dict.
-
to_df
()¶ Join the innermost Dict classes into a pandas DataFrame, where the keys in the innermost dictionaries are the index and the keys for the innermost dictionaries are the column headers.
-
to_hdf5
(filepath, attributes=None, overwrite_existing_file=True, condensed=False)¶ Save the contents as a HDF5 file.
Parameters: - filepath (str) – Location to save the hdf5 file at.
- attributes (dict) – Dictionary of attributes to store as attributes for the HDF5 file.
- overwrite_existing_file (boolean) – If True and a file already exists at filepath, delete it prior to saving.
- condensed (boolean) – If True, combine the innermost dictionaries into a condensed DataFrame/array-like format.
-
transpose
()¶
-
values
() → an object providing a view on D's values¶
-


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module Interpreter:sig
..end
The Interpreter.
The Interpreter is the core componet of the Primus Machine. It provides lots of observations, giving other components an ability to track every event that happens during the program evaluation. The components can affect the results of evaluation in a limited way, by affecting the state of the components that are used by the Interpreter, name the Environemnt and the Memory.
Note: we the observation (x,y,z)
notation in the
documentation to denote an observation of a value represented
with the (x,y,z)
tuple, that in fact corresponds to
observation >>> fun (x,y,z)
-> ...
val pc_change : Std.addr Std.Primus.observation
pc_change x
happens every time a code at address x
is executed.
val loading : Std.Primus.value Std.Primus.observation
loading x
happens before a value from the address x
is loaded
by the interpreter from the memory.
val loaded : (Std.Primus.value * Std.Primus.value)
Std.Primus.observation
loaded (addr,value)
happens after the value
is loaded
from the address addr
.
val storing : Std.Primus.value Std.Primus.observation
storing x
happens before a value is stored at address x
val stored : (Std.Primus.value * Std.Primus.value)
Std.Primus.observation
stored (addr,value)
happens after the value
is stored at
the address addr
val reading : Std.var Std.Primus.observation
reading x
happens before the variable x
is read from the
environment.
val read : (Std.var * Std.Primus.value) Std.Primus.observation
read (var,x)
happens after a variable var
is evaluated
to the value x
val writing : Std.var Std.Primus.observation
writing v
happens before a value is written to the variable v
val written : (Std.var * Std.Primus.value) Std.Primus.observation
written (v,x)
happens after x
is assinged to v
val jumping : (Std.Primus.value * Std.Primus.value)
Std.Primus.observation
jumping (cond,dest)
happens just before a jump to dest
is taken under the specified condition cond
.
Note: cond
is always true
val eval_cond : Std.Primus.value Std.Primus.observation
eval_cond v
occurs every time the cond
part of a jump is
evaluated.
val undefined : Std.Primus.value Std.Primus.observation
undefined x
happens when a computation produces an
undefined value x
.
val const : Std.Primus.value Std.Primus.observation
const x
happens when a constant x
is created
val binop : ((Std.binop * Std.Primus.value * Std.Primus.value) *
Std.Primus.value)
Std.Primus.observation
binop ((op,x,y),r)
happens after the binary operation op
is applied to values x
and y
and evaluates to r
val unop : ((Std.unop * Std.Primus.value) * Std.Primus.value)
Std.Primus.observation
unop ((op,x),r)
happens after the unary operation op
is
applied to x
and results r
val cast : ((Std.cast * int * Std.Primus.value) *
Std.Primus.value)
Std.Primus.observation
cast ((t,x),r)
happens after x
is casted to r
using
the casting type t
val extract : ((int * int * Std.Primus.value) * Std.Primus.value)
Std.Primus.observation
extract ((hi,lo,x),r)
happens after r
is extracted from x
val concat : ((Std.Primus.value * Std.Primus.value) *
Std.Primus.value)
Std.Primus.observation
extract ((x,y),z)
happens after x
is concatenated with y
and produces z
as a result.
val ite : ((Std.Primus.value * Std.Primus.value *
Std.Primus.value) *
Std.Primus.value)
Std.Primus.observation
ite ((cond, yes, no), res)
happens after the ite expression
that corresponds to ite(cond
, yes
, no
) is evaluated
to res
.
val enter_term : Std.tid Std.Primus.observation
an identifier of a term that will be executed next.
val leave_term : Std.tid Std.Primus.observation
an identifier of a term that just finished the execution.
val enter_pos : Std.Primus.pos Std.Primus.observation
new program locatio entered
val leave_pos : Std.Primus.pos Std.Primus.observation
a program location left
val enter_sub : Std.sub Std.term Std.Primus.observation
a subroutine entered
val enter_arg : Std.arg Std.term Std.Primus.observation
a subroutine argument is entered
val enter_blk : Std.blk Std.term Std.Primus.observation
a basic block is entered
val enter_phi : Std.phi Std.term Std.Primus.observation
a phi-node is entered
val enter_def : Std.def Std.term Std.Primus.observation
a definition is entered
val enter_jmp : Std.jmp Std.term Std.Primus.observation
a jump term is entered
val leave_sub : Std.sub Std.term Std.Primus.observation
a subroutine was left
val leave_arg : Std.arg Std.term Std.Primus.observation
a subroutine argument was left
val leave_blk : Std.blk Std.term Std.Primus.observation
a basic block was left
val leave_phi : Std.phi Std.term Std.Primus.observation
a phi-node was left
val leave_def : Std.def Std.term Std.Primus.observation
a definition was left
val leave_jmp : Std.jmp Std.term Std.Primus.observation
a jump term was left
val enter_exp : Std.exp Std.Primus.observation
an expression was entered
val leave_exp : Std.exp Std.Primus.observation
an expression was left
val halting : unit Std.Primus.observation
occurs on halt
operation
val interrupt : int Std.Primus.observation
interrupt n
occurs on the machine interrupt n
(aka CPU
exception)
val division_by_zero : unit Std.Primus.observation
division_by_zero
occurs just before the division by zero trap
is signaled.
See the binop
operation and division_by_zero_handler
for more
information.
val pagefault : Std.addr Std.Primus.observation
pagefault x
occurs just before the pagefault trap is signaled.
See load
and store
operations, and pagefault_handler
for
more information.
val segfault : Std.addr Std.Primus.observation
segfault x
occurs when an invalid memory operation is performed
on the address x
. See the load
and store
operations for more.
type
Std.Primus.exn +=
| |
Halt |
is raised when a computation is halted
type
Std.Primus.exn +=
| |
Division_by_zero |
is raised by a machine that attempts to divide by zero
type
Std.Primus.exn +=
| |
Segmentation_fault of |
is raised when a memory operation has failed.
val pagefault_handler : string
pagefault_hanlder
is a trap handler that is invoked when the Pagefault
exception is raised by the machine memory component. If the handler is
provided via the Linker, then it is invoked, otherwise a segmentation
fault is raised. If the hanlder returns normally then the faulty operation is
repeated.
Note, page faults are usually handled together with the pagefault
observation.
val division_by_zero_handler : string
division_by_zero_hanlder
is a trap handler for
the Division_by_zero exception. If it is linked into the machine,
then it will be invoked when the division by zero trap is signaled.
If it returns normally, then the result of the faulty operation is
undefined.
module Make(
Machine
:
Std.Primus.Machine.S
)
:sig
..end
Make(Machine) makes an interpreter that computes in the
given Machine
.


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The National Pension System (NPS) is a voluntary defined contribution pension system in India. National Pension System, like PPF and EPF is an EEE (Exempt-Exempt-Exempt) instrument in India where the entire corpus escapes tax at maturity and entire pension withdrawal amount is tax-free.NPS started with the decision of the Government of India to stop defined benefit pensions for all its employees who joined after 1 April 2004. While the scheme was initially designed for government employees only, it was opened up for all citizens of India between the age of 18 and 65 in 2009, for OCI card holders and PIO's in October 2019


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|
JavaTM 2 Platform Standard Ed. 5.0 |
|||||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
java.lang.Object java.awt.image.ColorConvertOp
public class ColorConvertOp
This class performs a pixel-by-pixel color conversion of the data in the source image. The resulting color values are scaled to the precision of the destination image. Color conversion can be specified via an array of ColorSpace objects or an array of ICC_Profile objects.
If the source is a BufferedImage with premultiplied alpha, the color components are divided by the alpha component before color conversion. If the destination is a BufferedImage with premultiplied alpha, the color components are multiplied by the alpha component after conversion. Rasters are treated as having no alpha channel, i.e. all bands are color bands.
If a RenderingHints object is specified in the constructor, the color rendering hint and the dithering hint may be used to control color conversion.
Note that Source and Destination may be the same object.
RenderingHints.KEY_COLOR_RENDERING
,
RenderingHints.KEY_DITHERING
| Constructor Summary | |
|---|---|
ColorConvertOp(ColorSpace srcCspace,
ColorSpace dstCspace,
RenderingHints hints)
Constructs a new ColorConvertOp from two ColorSpace objects. |
|
ColorConvertOp(ColorSpace cspace,
RenderingHints hints)
Constructs a new ColorConvertOp from a ColorSpace object. |
|
ColorConvertOp(ICC_Profile[] profiles,
RenderingHints hints)
Constructs a new ColorConvertOp from an array of ICC_Profiles. |
|
ColorConvertOp(RenderingHints hints)
Constructs a new ColorConvertOp which will convert from a source color space to a destination color space. |
| Method Summary | |
|---|---|
BufferedImage |
createCompatibleDestImage(BufferedImage src,
ColorModel destCM)
Creates a zeroed destination image with the correct size and number of bands, given this source. |
WritableRaster |
createCompatibleDestRaster(Raster src)
Creates a zeroed destination Raster with the correct size and number of bands, given this source. |
BufferedImage |
filter(BufferedImage src,
BufferedImage dest)
ColorConverts the source BufferedImage. |
WritableRaster |
filter(Raster src,
WritableRaster dest)
ColorConverts the image data in the source Raster. |
Rectangle2D |
getBounds2D(BufferedImage src)
Returns the bounding box of the destination, given this source. |
Rectangle2D |
getBounds2D(Raster src)
Returns the bounding box of the destination, given this source. |
ICC_Profile[] |
getICC_Profiles()
Returns the array of ICC_Profiles used to construct this ColorConvertOp. |
Point2D |
getPoint2D(Point2D srcPt,
Point2D dstPt)
Returns the location of the destination point given a point in the source. |
RenderingHints |
getRenderingHints()
Returns the rendering hints used by this op. |
| Methods inherited from class java.lang.Object |
|---|
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Constructor Detail |
|---|
public ColorConvertOp(RenderingHints hints)
hints
- the RenderingHints
object used to control
the color conversion, or null
public ColorConvertOp(ColorSpace cspace, RenderingHints hints)
filter
method is invoked with a destination argument of null.
In that case, the ColorSpace defines the destination color space
for the destination created by the filter method. Otherwise, the
ColorSpace defines an intermediate space to which the source is
converted before being converted to the destination space.
cspace
- defines the destination ColorSpace
or an
intermediate ColorSpace
hints
- the RenderingHints
object used to control
the color conversion, or null
NullPointerException
- if cspace is nullpublic ColorConvertOp(ColorSpace srcCspace, ColorSpace dstCspace, RenderingHints hints)
srcCspace
- the source ColorSpace
dstCspace
- the destination ColorSpace
hints
- the RenderingHints
object used to control
the color conversion, or null
NullPointerException
- if either srcCspace or dstCspace is nullpublic ColorConvertOp(ICC_Profile[] profiles, RenderingHints hints)
For BufferedImages, if the ColorSpace of the source BufferedImage does not match the requirements of the first profile in the array, the first conversion is to an appropriate ColorSpace. If the requirements of the last profile in the array are not met by the ColorSpace of the destination BufferedImage, the last conversion is to the destination's ColorSpace.
For Rasters, the number of bands in the source Raster must match the requirements of the first profile in the array, and the number of bands in the destination Raster must match the requirements of the last profile in the array. The array must have at least two elements or calling the filter method for Rasters will throw an IllegalArgumentException.
profiles
- the array of ICC_Profile
objectshints
- the RenderingHints
object used to control
the color conversion, or null
IllegalArgumentException
- when the profile sequence does not
specify a well-defined color conversion
NullPointerException
- if profiles is null| Method Detail |
|---|
public final ICC_Profile[] getICC_Profiles()
ICC_Profile
objects of this
ColorConvertOp
, or null
if this
ColorConvertOp
was not constructed with an
array of ICC_Profile
objects.public final BufferedImage filter(BufferedImage src, BufferedImage dest)
filter
in interface BufferedImageOp
src
- the source BufferedImage
to be converteddest
- the destination BufferedImage
,
or null
dest
color converted from src
or a new, converted BufferedImage
if dest
is null
IllegalArgumentException
- if dest is null and this op was
constructed using the constructor which takes only a
RenderingHints argument, since the operation is ill defined.public final WritableRaster filter(Raster src, WritableRaster dest)
filter
in interface RasterOp
src
- the source Raster
to be converteddest
- the destination WritableRaster
,
or null
dest
color converted from src
or a new, converted WritableRaster
if dest
is null
IllegalArgumentException
- if the number of source or
destination bands is incorrect, the source or destination
color spaces are undefined, or this op was constructed
with one of the constructors that applies only to
operations on BufferedImages.public final Rectangle2D getBounds2D(BufferedImage src)
getBounds2D
in interface BufferedImageOp
src
- the source BufferedImage
Rectangle2D
that is the bounding box
of the destination, given the specified src
public final Rectangle2D getBounds2D(Raster src)
getBounds2D
in interface RasterOp
src
- the source Raster
Rectangle2D
that is the bounding box
of the destination, given the specified src
public BufferedImage createCompatibleDestImage(BufferedImage src, ColorModel destCM)
createCompatibleDestImage
in interface BufferedImageOp
src
- Source image for the filter operation.destCM
- ColorModel of the destination. If null, an
appropriate ColorModel will be used.
BufferedImage
with the correct size and
number of bands from the specified src
.
IllegalArgumentException
- if destCM
is
null
and this ColorConvertOp
was
created without any ICC_Profile
or
ColorSpace
defined for the destinationpublic WritableRaster createCompatibleDestRaster(Raster src)
createCompatibleDestRaster
in interface RasterOp
src
- the specified Raster
WritableRaster
with the correct size and number
of bands from the specified src
IllegalArgumentException
- if this ColorConvertOp
was created without sufficient information to define the
dst
and src
color spacespublic final Point2D getPoint2D(Point2D srcPt, Point2D dstPt)
dstPt
is non-null,
it will be used to hold the return value. Note that
for this class, the destination point will be the same
as the source point.
getPoint2D
in interface BufferedImageOp
getPoint2D
in interface RasterOp
srcPt
- the specified source Point2D
dstPt
- the destination Point2D
dstPt
after setting its location to be
the same as srcPt
public final RenderingHints getRenderingHints()
getRenderingHints
in interface BufferedImageOp
getRenderingHints
in interface RasterOp
RenderingHints
object of this
ColorConvertOp
|
JavaTM 2 Platform Standard Ed. 5.0 |
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| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
Copyright © 2004, 2010 Oracle and/or its affiliates. All rights reserved. Use is subject to license terms. Also see the documentation redistribution policy.


| info-namespace |
nyu |
| namespace-title |
Identifiers for New York University Digital Objects |
| registration-date |
|
| namespace-authority |
| organisation-name |
New York University |
| organisation-address |
70 Washington Square South, New York, NY 10012 |
| organisation-uri |
http://www.nyu.edu |
| contact-person |
Rasan Rasch |
| contact-email |
<EMAIL_ADDRESS>|
| contact-tel |
|
| contact-uri |
http://dlib.nyu.edu |
|
| identifier-syntax |
| description |
An 'info' URI with namespace 'nyu' takes the form:
info:nyu/<nyu-info-subspace>/<subspace-specific-string>
nyu-info-subspace
nyu-info-subspace = ALPHA *( ALPHA / DIGIT )
i.e. alphanumeric with leading alphabetic character.
Values of nyu-info-subspace are assigned by NYU Libraries.
subspace-specific-string
subspace-specific-string =
subspace-specific-component *("/" subspace-specific-component)
subspace-specific-component
subspace-specific-component = pchar *(pchar)
pchar (etc.)
pchar is as defined in RFC 3986, that is:
pchar = unreserved / pct-encoded / sub-delims / ":" / "@"
unreserved = ALPHA / DIGIT / "-" / "." / "_" / "~"
pct-encoded = "%" HEXDIG HEXDIG
sub-delims = "!" / "$" / "&" / "'" / "(" / ")" / "*" / "+" / "," / ";" / "="
ALPHA, DIGIT, AND HEXDIG are as defined in RFC 2234:
upper or lower case alphabetic (A-Z / a-z), decimal digit (0-9),
and hexadecimal digit (DIGIT / "A" / "B" / "C" / "D" / "E" /
"F") respectively.
Percent Encoded Characters
No characters in general need to be percent encoded.
Acknowledgements:
the text and form of this registration was based on Ray Denenberg's info:lc registration.
Additional information on the info:nyu namespace can be found here: |
| uri |
http://hdl.handle.net/2333.1/v9s4mww5 |
|
| identifier-normalization |
|
| identifier-examples |
| identifier-example |
| native |
|
| info-uri |
info:nyu/dl/v1.0/files/xpnvx139 |
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info:nyu/dl/v1.0/aips/mw6m90b/versions/1 |
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info:nyu/dl/v1.0/sips/sxksn1k/state
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info:nyu/dl/v1.0/files/xpnvx139/fixity
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info:nyu/dl/v1.0/agents/software/droid/versions/4.0.0
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| namespace-information |
| description |
Identifiers in the info:nyu namespace will be used to identify information assets in New York University systems. Identifiers will vary by nyu-info-subspace. |
| uri |
http://hdl.handle.net/2333.1/v9s4mww5 |
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"""
Sintef
======
Evaluate initial bubble and droplet sizes from the SINTEF model
This module applies the modified Weber number model of SINTEF with corrections
for the presence of oil and gas together to estimate the volume mean diameters
of oil and gas at the end of the break-up region.
Notes
-----
The empirical coefficients A and B were obtained from Tower Basin experiments
of oil into water with and without dispersant. These experiments had small
exit diameters (generally 1.5 mm or less) and large relative momentum length
scales l_M/D >> 1. The corrections for the presence of gas in oil (both a
void fraction corrections and buoyancy correction) are theoretical, and any
affect these corrections may have on the parameters A and B has not yet been
studied in detail.
References
----------
Brandvik, P.J., Johansen, O., Farooq, U., Angell, G., and Leirvik, F. (2012),
"Sub-surface oil releases--Experimental study of droplet distributions and
different dispersant injection techniques. A scaled experimental approach
using the SINTEF Tower Basin." Draft report, prepared by SINTEF Materials
and Chemistry, Aug. 2012.
Johansen, O., Brandvik, P.J. and Farooq, U. (2012), "Droplet breakup in subsea
oil releases--Part 2: Prediction of droplet size distributions with and
without injection of chemical dispersants." Marine Pollution Bulletin.
"""
# S. Socolofsky, September 2013, Texas A&M University<EMAIL_ADDRESS>import numpy as np
from copy import copy
from scipy.optimize import fsolve
[docs]def modified_We_model(D, rho_gas, m_gas, mu_gas, sigma_gas, rho_oil, m_oil,
mu_oil, sigma_oil, rho):
"""
Compute the initial oil droplet and gas bubble sizes from the SINTEF model
Apply the SINTEF modified Weber number model to estimate the initial
oil and gas particle sizes. This function calculates the adjusted exit
velocity based on a void fraction and buoyancy adjustment per the method
suggested by SINTEF.
Parameters
----------
D : float
Diameter of the release point (m)
rho_gas : float
In-situ density of the gas (kg/m^3)
m_gas : ndarray
Array of mass fluxes for each component of the gas object (kg/s)
mu_gas : float
Dynamic viscosity of gas (Pa s)
sigma_gas : float
Interfacial tension between gas and seawater (N/m)
rho_oil : float
In-situ density of the oil
m_oil : ndarray
Array of mass fluxes for each component of the oil object (kg/s)
mu_oil : float
Dynamic viscosity of oil (Pa s)
sigma_oil : float
Interfacial tension between oil and seawater (N/m)
rho : float
Density of the continuous phase fluid (kg/m^3)
Returns
-------
A tuple containing:
de_gas : float
The volume mean diameter of the gas bubbles (m)
de_oil : float
The volume mean diameter of the oil droplets (m)
"""
# Make sure the masses are in arrays
if not isinstance(m_gas, np.ndarray):
if not isinstance(m_gas, list):
m_gas = np.array([m_gas])
else:
m_gas = np.array(m_gas)
if not isinstance(m_oil, np.ndarray):
if not isinstance(m_oil, list):
m_oil = np.array([m_oil])
else:
m_oil = np.array(m_oil)
# Get the volume flow rates of gas and oil
if np.sum(m_gas) >0.:
Q_gas = np.sum(m_gas) / rho_gas
else:
Q_gas = 0.
if np.sum(m_oil) >0.:
Q_oil = np.sum(m_oil) / rho_oil
else:
Q_oil = 0.
# Get the void-fraction adjusted velocity Un
if Q_oil == 0.:
# This is gas only
n = 1.0
Un = 4. * Q_gas / (np.pi * D**2)
else:
# This is either oil only or oil and gas
n = Q_gas / (Q_gas + Q_oil)
Un = 4. * Q_oil / (np.pi * D**2) / (1. - n)**(1./2.)
# Get the densimetric Froude number
Fr = Un / (9.81 * (rho - rho_oil * (1. - n) - rho_gas * n) / \
rho * D)**(1./2.)
# Compute the final characteristic velocity to use in the model
Uc = Un * (1. + 1./Fr)
# Compute the gas volume mean droplet size
if Q_gas > 0.:
de_gas = de_50(Uc, D, rho_gas, mu_gas, sigma_gas, rho)
else:
de_gas = None
# Compute the oil volume mean droplet size
if Q_oil > 0.:
de_oil = de_50(Uc, D, rho_oil, mu_oil, sigma_oil, rho)
else:
de_oil = None
# Return the bubble and droplet sizes
return (de_gas, de_oil)
# Provide tool to estimate the maximum stable particle size
[docs]def de_max(sigma, rho_p, rho):
"""
Calculate the maximum stable particle size
Predicts the maximum stable particle size per Clift et al. (1978) via
the equation:
d_max = 4. * np.sqrt(sigma / (g (rho - rho_p)))
Parameters
----------
sigma : float
Interfacial tension between the phase undergoing breakup and the
ambient receiving continuous phase (N/m)
rho_p : float
Density of the phase undergoing breakup (kg/m^3)
rho : float
Density of the ambient receiving continuous phase (kg/m^3)
Returns
-------
d_max : float
Maximum stable particle size (m)
"""
return 4. * np.sqrt(sigma / (9.81 * (rho - rho_p)))
[docs]def de_50(U, D, rho_p, mu_p, sigma, rho):
"""
Predict the volume mean diameter from a modified Weber number model
Calculates the SINTEF modified Weber number model for the volume mean
diameter of a blowout release.
Parameters
----------
U : float
Effective exit velocity after void fraction and buoyancy correction
of the phase undergoing breakup (m/s)
D : float
Diameter of the discharge (m)
rho_p : float
Density of the phase undergoing breakup (kg/m^3)
mu_p : float
Dynamic viscosity of the phase undergoing breakup (Pa s)
sigma : float
Interfacial tension between the phase undergoing breakup and the
ambient receiving continuous phase (N/m)
Returns
-------
de_50 : float
The volume mean diameter of the phase undergoing breakup
Notes
-----
This function first checks the We number. If the We is less than the
critical value of 350 required for atomization, then the fluid particle
diameter is estimated as 1.2 D. Otherwise, the SINTEF modified We number
model is used. In both cases, the resulting particle diameter is compared
to the maximum stable particle size per Clif et al. (1978) of
d_max = 4 (sigma/ (g (rho - rho_p)))^(1/2).
The function returns the lesser of the estimated particle size or the
maximum stable particle size.
"""
# Compute the non-dimensional constants
We = rho_p * U**2 * D / sigma
Vi = mu_p * U / sigma
if We > 350.:
# Atomization...use the SINTEF model.
# A = 24.8
# B = 0.08
A = 15.
B = 0.8
# Solve for the volume mean diameter from the implicit equation
def residual(dp):
"""
Compute the residual of the SINTEF modified Weber number model
Evaluate the residual of the non-dimensional diameter dp = de_50 / D
for the SINTEF droplet break-up model.
Input variables are:
We, Vi, A, B = constant and inherited from above
dp = Non-dimensional diameter de_50 / D (--)
"""
# Compute the non-dimensional diameter and return the residual
return dp - A * (We / (1. + B * Vi * dp**(1./3.)))**(-3./5.)
# Find the gas and liquid fraction for the mixture
dp = fsolve(residual, 5.)[0]
de = dp * D
else:
# Sinuous wave breakup...use the pipe diameter
de = 1.2 * D
# Require the diameter to be less than the maximum stable size
dmax = de_max(sigma, rho_p, rho)
if de > dmax:
de = dmax
# Return the result
return de
[docs]def rosin_rammler(nbins, d50, md_total, sigma, rho_p, rho):
"""
Return the volume size distribution from the Rosin Rammler distribution
Returns the fluid particle diameters in the selected number of bins on
a volume basis from the Rosin Rammler distribution with parameters
k = -ln(0.5) and alpha = 1.8.
Parameters
----------
nbins : int
Desired number of size bins in the particle volume size distribution
d50 : float
Volume mean particle diameter (m)
md_total : float
Total particle mass flux (kg/s)
sigma : float
Interfacial tension between the phase undergoing breakup and the
ambient receiving continuous phase (N/m)
rho_p : float
Density of the phase undergoing breakup (kg/m^3)
rho : float
Density of the ambient receiving continuous phase (kg/m^3)
Returns
-------
de : ndarray
Array of particle sizes at the center of each bin in the distribution
(m)
md : ndarray
Total mass flux of particles corresponding to each bin (kg/s)
Notes
-----
This method computes the un-truncated volume size distribution from the
Rosin-Rammler distribution and then enforces that all particle sizes
be less than the maximum stable size by moving mass in larger sizes to
the maximum stable size bin.
References
----------
Johansen, Brandvik, and Farooq (2013), "Droplet breakup in subsea oil
releases - Part 2: Predictions of droplet size distributions with and
without injection of chemical dispersants." Marine Pollution Bulletin,
73: 327-335. doi:10.1016/j.marpolbul.2013.04.012.
"""
# Compute the maximum stable particle diameter
dmax = de_max(sigma, rho_p, rho)
# Define the parameters of the distribution
k = -np.log(0.5)
alpha = 1.8
# Get the de/d50 ratio for the edges of each bin in the distribution
# using a log-spacing
bin_edges = np.logspace(-1, 1, nbins + 1)
# Find the logarithmic average location of the center of each bin
bin_centers = np.zeros(len(bin_edges) - 1)
for i in range(len(bin_centers)):
bin_centers[i] = np.exp(np.log(bin_edges[i]) +
(np.log(bin_edges[i+1]) - np.log(bin_edges[i])) / 2.)
# Get the cumulative volume fraction within each bin
Vn = 1. - np.exp(-k * bin_edges**alpha)
# Get the actual volume fraction within each bin
V_frac = np.zeros(len(bin_centers))
for i in range(len(bin_edges) - 1):
V_frac[i] = Vn[i+1] - Vn[i]
V_frac += (1.0 - np.sum(V_frac)) / nbins
# Compute the actual diameters of each particle
de = d50 * bin_centers
# Compute the mass fraction for each diameter
md = V_frac * md_total
# Truncate the distribution at the maximum stable droplet size
imax = -1
for i in range(len(de)):
if de[i] > dmax:
if imax < 0:
imax = i
de[i] = dmax
else:
md[imax] += md[i]
md[i] = 0.
# Return the particle size distribution
return (de, md)


Priestess Glyvka:
Ah, so you have brought me twenty bundles of swamp moss. As soon as these are prepared, Jonas will be able to use them in his salad.
But it would be a much better dish if you could get twenty bundles of brown moss ... How about if you try a little harder to find the brown moss?
Say you will try to find brown moss
Ask Priestess Glyvka to prepare the moss that was brought


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ordered(list, *names, reverse=False)
Creates a sorted copy of a list of objects (similar to Python's built-in sorted
function). Lists of dictionaries or objects can be sorted based on a common key or attribute if any name
strings are provided. If more than one name is present, they will be used (in order) as primary, secondary, tertiary, etc. sorting criteria.
Lists are returned in ascending order unless the reverse
parameter is True
.
a sorted copy of the original sequence
students = [{"name":"Alice", "grade":95}, {"name":"Bob", "grade":60}, {"name":"Carol", "grade":88}, {"name":"Eve", "grade":95} ] for s in ordered(students, 'grade', 'name'): print(s['grade'], s['name']) >>> 60 Bob >>> 88 Carol >>> 95 Alice >>> 95 Eve


String s3 = "All good things must come to an end";
String letter2 = "e";
s3.indexOf(letter2)
What is returned by this method call?
String s4 = "I'll make him an offer he can't refuse.";
String s3 = "To be or not to be, that is the question.";
s3.charAt(s4.substring(5).substring(17).length())
What is returned by this method call?
String s3 = "I'm Sorry Dave. I'm afraid I can't do that.";
s3.charAt(s3.indexOf("o") + 5);
What is returned by this method call?
String s4 = "i am Roger the Shrubber";
String s3 = "I'll make him an offer he can't refuse.";
String letter2 = "a";
s4.charAt(s3.indexOf(letter2))


sometimes i wonder how dev bloggers have it in them to maintain posting on their website. does it have to do with their time management? to be honest, i don't know. whatever it is they possess that allows them to stay consistent and helpful, i know i don't have.
#oil-language
Oil Language —
A legacy-free dialect of shell with:
var
keywordecho $myfunc(x, y)
push
and repr
For a taste of the syntax, see The Simplest Explanation of Oil.
It shares the same runtime as OSH, so it's a smooth upgrade from both bash and OSH. Compatibility is selectively broken with Oil Options.
i want to atleast try to keep a blog, whether it isn't as consistent as the ones i read, hopefully it helps someone out there reading it. i dont expect many people to read my blog, but i'll welcome anyone who cares enough to pay attention.
although blogging isn't really my thing (yet), i do read some people's and i often take interest in whatever they end up writing about, tech related or not.
recently, i've really enjoyed watching luke smith's channel on youtube in my free time. he does a really good job at getting to the point and giving meaning to the content he puts out. his humor is sardonic and his subscribers love how little he seems to care about his channel, while still having strong opinions about the state of tech.