All form controls accept a data-mini="true" attribute that renders a smaller version of the enhanced element. In the case of grouped buttons, the data-mini="true" attribute can be added to the containing controlgroup.
data-mini="true"


Organization administrators can use their registered credentials and add individual users onto Sunbird. To add users on Sunbird, the administrator must upload required details of the users.
| Step | Screen |
|---|---|
| 1. You are logged in 2. You are currently on Profile page. You want to upload users 3. You have clicked on Upload Users Note: Ensure that the administrator of your organization has assigned user roles on the portal. For details on how to assign user roles, refer Assigning User Roles |
1.The Upload Users page is displayed
2.Enter Provider details. Channel ID of the organization administrator must be entered here
3.Enter External ID. Unique ID of the user that has to be uploaded must be entered here OR
4.Enter OrgID. Unique ID of the admin organization must be entered here
- For example, in the case of a state, state repository is the system administrator repository and the ID given to each school, or education body in the state is the External ID. <br /> OR
- Enter OrgID. Unique ID of the administration organization that is generated on Sunbird. This ID is generated when the organization is successfully uploaded on Sunbird.
5.Download the csv file for reference
6.You can add or upload details of up to 1000 users at a time in one csv file
7.You can upload users of only a single organization in one csv file
8.Descriptions and valid values for each columns are as listed below:
| S No | Column Name | Description | Valid Value | Field Type | |
|---|---|---|---|---|---|
| 1 | firstName | User’s first name | Alphabetic Value | Mandatory | |
| 2 | lastName | User’s last name | Alphabetic Value | Optional | |
| 3 | phone | User’s phone number | Ten digit mobile number | Optional | |
| 4 | User’s verified email ID | Alphanumeric, standard email ID format Note: You can provide (i) only the phone number, (ii) only email or (iii) both email and phone number |
Mandatory | ||
| 5 | userName | Unique name assigned to the user by the organization | Alphanumeric | Mandatory | |
| 6 | password | Unique/common password given by the organization | Alphanumeric | Mandatory | |
| 7 | provider | Channel ID shared with the system administrator | Alphanumeric Note: Enter values in the provider column and the phoneVerified column or keep both columns blank |
Conditional | |
| 8 | phoneVerified | Whether user’s phone number is verified | TRUE, if phone number is provided Note: Enter values in the provider column and the phoneVerified column or keep both columns blank |
Conditional | |
| 9 | emailVerified | Whether user’s email ID is verified | TRUE, if email ID is provided | Optional | |
| 10 | roles | User’s role | Select one or more of the following roles: CONTENT_CREATOR CONTENT_REVIEWER FLAG_REVIEWER COURSE_MENTOR BOOK_CREATOR BOOK_REVIEWER ORG_ADMIN TEACHER_BADGE_ISSUER BADGE_ISSUER ANNOUNCEMENT_SENDER PUBLIC |
Optional | |
| 11 | position | User’s designation in the organization | Alphanumeric | Optional | |
| 12 | grade | Classes taught by the user | Select one or more of the following grades: Class 1, Class 2, Class 3, Class 4, Class 5, Class 6, Class 7, Class 8, Class 9, Class 10, Kindergarten, Other |
Optional | |
| 13 | location | User’s geographical location | Alphanumeric | Optional | |
| 14 | DOB | User’s date of birth | DD-MM-YYYY | Optional | |
| 15 | gender | User’s gender | Male, Female, Transgender | Optional | |
| 16 | language | User’s language preferences | Select one or more of the following grades: English, Gujarati, Hindi, Kannada, Marathi, Punjabi, Tamil, Telugu | Optional | |
| 17 | profileSummary | User’s professional profile summary, skills, certifications | Alphanumeric | Optional | |
| 18 | subject | Subjects taught by the user | Select one or more of the following grades: Assamese, Bengali, English, Hindi, Kannada, Malayalam, Oriya, Punjabi, Tamil, Telugu, Urdu, Biology, Chemistry, Physics, Mathematics, Environmental Studies, Geography, History, Political Science, Economics, Sanskrit, Gujarati, Marathi, Nepali | Optional | |
| 19 | externalId | User’s identity in an external system **Note **:Enter values in the externalid column and the externalIdType & externalIdprovider column or keep all three columns blank |
Alphanumeric | Optional | |
| 20 | externalIds | An array of externalId represented as JSON string | Enter details within curly brackets in double quotes. Separate each detail with a comma, and, detail name and corresponding value with a colon (:). For example; [{“id”:”someId”,”idType”:”someIdType”,”provider”:”someProvider”,”operation”:”ADD,EDIT,REMOVE”}] | Optional | |
| 21 | externalIdType | External ID types | Note: Enter values in the externalId column and the externalIdType column or keep both column blank |
Alphanumeric Note: Ignore externalIdType, if userName is already provided |
Conditional |
| 22 | externalIdProvider | External ID provided by system administrator to users Note: Enter values in the externalId column and the externalIdProvider column or keep both column blank |
Alphanumeric Note: Ignore externalIdProvider, if userName is already provided |
Conditional |
Note: Ensure that you separate the values with a comma when you select more than one value for any column
9.Click UPLOAD USERS CSV.The explorer window is displayed
10.Select the csv file and click Open
11.The csv file is uploaded
12.On successful file upload, a process ID is generated, else an error message is displayed
13.Possible causes for failure of upload includes:
a. The csv file is not saved in the right format. Select CSV (Comma delimited) (.csv) as the file type while saving
b. Using the same email, phonenumber etc. for more than one user. Details must be unique for each user
c. Providing invalid values in the csv file. In such cases, the error message denotes the column name for which incorrect value is provided


| Page1 | Page2 | Page3 | ||
The Limited Editions ClubThe Limited Editions Club was started in 1929 by George Macy. Members paid a subscription for the classic titles, which were illustrated by contemporary artists. They were published in relatively small quantities, and are now highly prized by collectors. Art and LiteratureSome of the more well-known artists who illustrated these books include Henri Matisse (who illustrated Ulysses, by James Joyce), Pablo Picasso, Norman Rockwell and Edward Steichen. |
||
Links:The Limited Editions Club |


--- layout: archive title: Zulip Chat Archive permalink: /stream/113488-general/topic/rw.20under.20lambda.html ---
rw
refuses to perform rewrites inside a lambda, as far as I can tell. Is there a convenient way to do so?
For example, frequently my goal is of the form ∃ x, P x ∧ Q x
and I would like to rewrite it to ∃ x, P x ∧ Q' x
(where I know Q x ↔ Q' x
).
use simp
instead of rw
if you want to rewrite under lambda. If you don't want simp
to use default simp
rules, you can do simp only [my_rule]
Oops, I tried simp only
, but I mixed up .symm
and .mpr
so it didn't appear to work. Thanks!
See also https://github.com/leanprover/mathlib/blob/master/docs/extras/conv.md
I couldn't work out how to do this with conv
:
example (h : ∃ a b, a + b = 0) : ∃ a b, b + a = 0 := begin conv begin -- use rw add_comm somehow end, exact h end
I tried congr, funext, congr
but I got an error that I didn't understand on the second congr
try:
example : (∃ a b, a + b = 0) ↔ ∃ a b, b + a = 0 := by conv in (_ + _) begin rw add_comm, end
ah, interesting
This would also work, btw:
example (h : (∃ a b, a + b = 0)) : ∃ a b, b + a = 0 := begin conv in (_ + _) { rw add_comm }, exact h end
conv in ( _ = _)
would also work, but I would be interested in seeing a solution without pattern matching. It seems we lack some navigation tactic (like to_lhs
/to_rhs
, congr
). @Gabriel Ebner @Mario Carneiro any idea?
Last updated: Apr 24 2020 at 19:02 UTC


About me
I like to explore several areas in programming and mathematics. I share my findings as Jupyter notebooks, published through @paulsalden.
Notebooks
- example this is an example notebook, directly linked from here
Contact
Find my contact information through github. Additionally, you may reach me through facebook.


RobotBuilder
Created by:
Steven Rodenbaugh and David E. Orin
Department of Electrical Engineering
The Ohio State University
Columbus, OH 43210
RobotBuilder is a software application that can be
used to rapidly develop robotic dynamic simulations. It has an intuitive
Windows interface to make it easy to use, but can perform complex simulations.
The dynamic calculations are performed by DynaMechs, developed by Scott
McMillan. It can simulate tree structures and star topologies with O(n)
complexity. It also efficiently simulates robotic articulations with
closed-kinematic loops; this capability was developed by Duane Marhefka.
RobotBuilder operates in three main modes. The Build mode is
used to define the robotic articulation. The user defines the links and their
properties, and sees a 3D view of the current robot. The Simulate mode
accurately simulates the created model. The control for the Simulate mode is
provided by the user in a DLL. This provides a considerable amount of
flexibility and enables the user to develop arbitrary control techniques. While
the simulation is running, the 3D view shows the animated results. Finally, the
Playback
mode can be used to view the simulation results in approximately real time.
RobotBuilder in useful in a variety of situations. It has been utilized in an introductory robotics course at The Ohio State University. Skeleton projects were provided to the students, which they completed for assignments. It provided them individual "hands-on" experience, which helped enable them to understand important concepts in robotics. RobotBuilderhas also been used in research. Its flexible control design has made it useful in robotics control research. The ease-of-use of RobotBuilder has enabled researchers to focus on the control techniques and immediately see graphical results.
RobotModeler is a simple application to develop graphical models for RobotBuilder. It also has the ability to approximate the values of the dynamic (mass) parameters of the links modeled in RobotModeler.
The following screenshots are
taken from the example projects included in the RobotBuilder
distribution.
Bounding quadruped simulation developed by Duane Marhefka. The quadruped is
controlled by a heuristic-type controller.
Mitsubishi RM-501 manipulator.
Simple slider crank exemplifying closed-kinematic loop capabilities.
Simplified Whegs model discussed in the tutorial distributed with RobotBuilder.
RobotBuilder should run on all current Windows
platforms. The simulations are both graphically and computationally complex.
The application will perform better on faster machines (500 MHz and 128 MB RAM
minimum) with better graphics cards. On lower-end machines, the graphics may be
particularly jerky, and simulation very, very slow. In addition, there may be
periods of unresponsiveness from the mouse on slow machines.
The control for the simulation in RobotBuilder is specified by a
user-developed DLL. Consequently, a C++ compiler is required to create custom
control. Sample control code for Microsoft Visual C++ 6.0 has been included in
the Projects/Skeleton
Code subdirectory.
The current version of RobotBuilder is 1.1 and RobotModeler is 1.0. To view the changes, please see the changelog. The applications, example projects, and support files can be downloaded as a single archive here.
Unzip the archive to a directory on your hard drive where
you would like the RobotBuilder directory to be located (for example c:\Program Files).
When unzipping, please make sure the directory structure is maintained (for
Winzip, check the "Use Folder Names" check box on the Extract dialog
box).
There is no setup program. To run, simply execute RobotBuilder.exe from the RobotBuilder
folder. You may want to create a shortcut to the application to place on your
desktop.
Since there is no setup, simply delete the RobotBuilder folder.
User's Guides have been written for RobotBuilder and RobotModeler.
In addition, an Example System Tutorial has been written. This documentation is
in .pdf
format and is located in the Docs subdirectory and is also available from the
Help menu.
In addition, the algorithms utilized in the simulation and control have been
discussed in several publications:
Scott McMillan, David E. Orin, and Robert B. McGhee, "Object-Oriented Design
of a Dynamic Simulation for Underwater Robotic Vehicles," IEEE
International Conference on Robotics and Automation, pp. 1886-1893, 1995.
Duane W. Marhefka and David E. Orin, "Dynamic Simulation of Running
Machines Containing Kinematic Loops," submitted to IEEE Transactions on
Robotics and Automation, 2001.
Duane W. Marhefka, David E. Orin, James P. Schmiedeler, and Kenneth J. Waldron,
"Intelligent Control of Quadruped Gallops", Accepted for publication
in IEEE/ASME Transactions on Mechatronics, 2003.
While the applications have
been useful in our research, they are still under development. If you encounter
any problems, or have any questions please send an email to<EMAIL_ADDRESS>If a bug report is being submitted, please include the application version
number, your operating system, and the steps to reproduce the problem.
We appreciate your interest.
Last Updated Thursday, 12-Dec-2003 05:04:14 EST


Extravaganza May 16 2020 - Click HerePlaying an active role in the community and school spirit of Encinal High School as well the greater Alameda area
Promoting a student leadership structure as overseen by the music director which allows students to take responsibility for the program
Promoting cooperative learning through peer mentorship and collaboration
Fostering an environment where students feel safe, motivated, and supported in reaching their individual and collective musical goals
After clicking the link, there will be an “add a note” box. Please write the donation information in this box. The Band Boosters need this information so they can track donations for tax purposes and to ensure the students who pay their booster fees are properly credited.
Would you like to get more information on how to support Encinal High School's Band Boosters? Email our board President Rich Hall


Package org.drip.graph.heap
Class BinaryTreeNode<KEY extends java.lang.Comparable<KEY>,ITEM>
java.lang.Object
org.drip.graph.heap.BinaryTreeNode<KEY,ITEM>
public class BinaryTreeNode<KEY extends java.lang.Comparable<KEY>,ITEM>
extends java.lang.Object
BinaryTreeNode implements a Node in a Binary Tree. The References are:
- Brodal, G. S., G. Lagogiannis, and R. E. Tarjan (2012): Strict Fibonacci Heaps Proceedings on the 44th Symposium on the Theory of Computing - STOC '12 1177-1184
- Cormen, T., C. E. Leiserson, R. Rivest, and C. Stein (2009): Introduction to Algorithms 3rd Edition MIT Press
- Hayward, R., and C. McDiarmid (1991): Average Case Analysis of Heap-building by Repeated Insertion Journal of Algorithms 12 (1) 126-153
- Suchanek, M. A. (2012): Elementary yet Precise Worst-case Analysis of Floyd's Heap Construction Program Fundamenta Informaticae 120 (1) 75-92
- Wikipedia (2020): Binary Heap https://en.wikipedia.org/wiki/Binary_heap
- Module = Computational Core Module
- Library = Graph Algorithm Library
- Project = Graph Optimization and Tree Construction Algorithms
- Package = Heap Based Priority Queue Implementations
- Author:
- Lakshmi Krishnamurthy
-
Constructor Summary
Constructors Constructor Description BinaryTreeNode(PriorityQueueEntry<KEY,ITEM> entry)
BinaryTreeNode Constructor -
Method Summary
Modifier and Type Method Description PriorityQueueEntry<KEY,ITEM>
entry()
Retrieve the Entryboolean
isLeaf()
Indicate if the Node is Leafboolean
isRightChild()
Indicate if the Node is a Right Child of the ParentBinaryTreeNode<KEY,ITEM>
largerChild()
Retrieve the Child Node with the Larger KeyBinaryTreeNode<KEY,ITEM>
left()
Retrieve the Left Childint
level()
Retrieve the LevelBinaryTreeNode<KEY,ITEM>
parent()
Retrieve the ParentBinaryTreeNode<KEY,ITEM>
right()
Retrieve the Right Childboolean
setAsRightChild(boolean isRightChild)
Set the Node as the Right Child of the Parentboolean
setKey(KEY key)
Set the Key of the Nodeboolean
setLeft(BinaryTreeNode<KEY,ITEM> left)
Set the Left Child of the Nodeboolean
setLevel(int level)
Set the Level of the Nodeboolean
setParent(BinaryTreeNode<KEY,ITEM> parent)
Set the Parent of the Nodeboolean
setRight(BinaryTreeNode<KEY,ITEM> right)
Set the Right Child of the NodeBinaryTreeNode<KEY,ITEM>
smallerChild()
Retrieve the Child Node with the Smaller Valuejava.lang.String
toString()
boolean
zeroOrOneChildren()
Indicate if the Node has 0 or 1 ChildrenMethods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait
-
Constructor Details
-
BinaryTreeNode
BinaryTreeNode Constructor- Parameters:
entry
- Entry- Throws:
java.lang.Exception
- Thrown if the Inputs are Invalid
-
-
Method Details
-
level
public int level()Retrieve the Level- Returns:
- The Level
-
parent
Retrieve the Parent- Returns:
- The Parent
-
left
Retrieve the Left Child- Returns:
- The Left Child
-
right
Retrieve the Right Child- Returns:
- The Right Child
-
entry
Retrieve the Entry- Returns:
- The Entry
-
isRightChild
public boolean isRightChild()Indicate if the Node is a Right Child of the Parent- Returns:
- TRUE - Node is a Right Child
-
setKey
Set the Key of the Node- Parameters:
key
- The Key- Returns:
- TRUE - The Node's Key successfully set
-
setLevel
public boolean setLevel(int level)Set the Level of the Node- Parameters:
level
- The Level- Returns:
- TRUE - The Node's Level successfully set
-
setParent
Set the Parent of the Node- Parameters:
parent
- The Parent- Returns:
- TRUE - The Node's Parent successfully set
-
setLeft
Set the Left Child of the Node- Parameters:
left
- The Left Child- Returns:
- TRUE - The Node's Left Child successfully set
-
setRight
Set the Right Child of the Node- Parameters:
right
- The Right Child- Returns:
- TRUE - The Node's Right Child successfully set
-
setAsRightChild
public boolean setAsRightChild(boolean isRightChild)Set the Node as the Right Child of the Parent- Parameters:
isRightChild
- TRUE - The Node is a Right Child- Returns:
- TRUE - The Node as the Right Child of the Parent is successfully set
-
zeroOrOneChildren
public boolean zeroOrOneChildren()Indicate if the Node has 0 or 1 Children- Returns:
- TRUE - The Node has 0 or 1 Children
-
isLeaf
public boolean isLeaf()Indicate if the Node is Leaf- Returns:
- TRUE - The Node is Leaf
-
smallerChild
Retrieve the Child Node with the Smaller Value- Returns:
- The Child Node with the Smaller Value
-
largerChild
Retrieve the Child Node with the Larger Key- Returns:
- The Child Node with the Larger Key
-
toString
public java.lang.String toString()- Overrides:
toString
in classjava.lang.Object
-


If you love Telegram but don't want to leave Discord then you'll be pleased to find we've built a bridge in this channel. If you'd like to join the group in the Telegram app you can find it here: https://t.me/KomodoPlatform_Official.
100 messages
Before 05-Dec-19 12:00 AM
GatewayBOT02-Dec-18 01:22 PM
[telegram] <Crassuss> What to do if you have them on Ledger nano s? (re @Seko: Please don't let the word "HardFork" irritate you. It is not a fork from which two coins spring. It's just an update. All you have to do is update Agama. More information will follow in the next days.
The Exchanges all get the daemon and do the same, they update their wallets.
So chill and keep cool!)
SHossain02-Dec-18 01:24 PM
Ledger will update their backend daemon as well like any other service providers. So, should be ok.
GatewayBOT02-Dec-18 01:25 PM
[telegram] <Crassuss> Thank you (re @Matterbridge_kmdbot: [discord] <SHossain> Ledger will update their backend daemon as well like any other service providers. So, should be ok.)
GatewayBOT02-Dec-18 03:04 PM
[telegram] <Cryptoralph2> Please check pm (re @Seko: Please don't let the word "HardFork" irritate you. It is not a fork from which two coins spring. It's just an update. All you have to do is update Agama. More information will follow in the next days.
The Exchanges all get the daemon and do the same, they update their wallets.
So chill and keep cool!)
GatewayBOT02-Dec-18 04:08 PM
[telegram] <Blackbits> It pumped when a signal group posted about KMD update of 15 th dec (re @Piet: Why is komodo pumping?)
GatewayBOT02-Dec-18 04:47 PM
[telegram] <J> Yes, but it doesn’t work reliably which is why mm2 is being made to make it usable. (re @Seko: We have a GUI...)
[telegram] <Fuconee> What if I have my KMD on Guarda wallet? (re @Seko: Please don't let the word "HardFork" irritate you. It is not a fork from which two coins spring. It's just an update. All you have to do is update Agama. More information will follow in the next days.
The Exchanges all get the daemon and do the same, they update their wallets.
So chill and keep cool!)
GatewayBOT02-Dec-18 05:11 PM
[telegram] <Seko> I’m sure that Guarda will also be updated. You have to update actively.
GatewayBOT02-Dec-18 05:58 PM
[telegram] <saidovicrypt> is there a new coin after hardfork
$ARRR me mateys! With #Sapling activation in less than 2 weeks make sure you give us a follow to stay up to date
@PirateChain @PiratechainRUS @PiratechainDE @PirateChainSlo
#PirateChain
Join the discord channel to get the updates fresh outta th' oven
https://t.co/epxqV...
GatewayBOT02-Dec-18 06:47 PM
[telegram] <RAFAO81> Is cryptopia giving suport for this fork? And, what if I have my KMD on Exodus Wallet at the fork?
Hermes02-Dec-18 07:07 PM
It's not a fork is an update ...all wallet and providers or exchanges will be updating their wallets.
Komodo is preparing to activate a major update to the Komodo code base. Learn more about all the new tech features coming to Komodo on December 15, 2018.
Here is more information about the update.
GatewayBOT02-Dec-18 07:08 PM
[telegram] <RAFAO81> Ah, I did not know. Tks man (re @Matterbridge_kmdbot: [discord] <Hermes> It's not a fork is an update ...all wallet and providers or exchanges will be updating their wallets.)
Visit our website: https://altcoinbuzz.io In this video, Mattie talks about Intel's news bitcoin patent. He also gives you the latest from our Community Spea...
[telegram] <Regnar> Exodus doesn't have KMD (re @RAFAO81: Is cryptopia giving suport for this fork? And, what if I have my KMD on Exodus Wallet at the fork?)
Komodo is preparing to activate a major update to the Komodo code base. Learn more about all the new tech features coming to Komodo on December 15, 2018.
[telegram] <tese22> How can I solve this error? I cant access to my wallet...Ive uninstalled .41 version and installed the latest but I still get the same error
[telegram] <tese22> nice thanks! excuse me for asking insted of not searching myself
GatewayBOT03-Dec-18 04:20 AM
[telegram] <May> Does anyone know of fmz quant? I heard that normal users could write trading bot on their platform for selling profit. How does they do that?
Komodo is preparing to activate a major update to the Komodo code base. Learn more about all the new tech features coming to Komodo on December 15, 2018.
GatewayBOT03-Dec-18 05:55 AM
[telegram] <Hegemon1> I can't find this anywhere, if I don't plan on moving coins for a while I don't need to do anything, right?
[telegram] <Hegemon1> If I take no action my coins won't be lost, right? Private key format is the same?
[telegram] <J> True (re @Hegemon1: If I take no action my coins won't be lost, right? Private key format is the same?)
[telegram] <Hegemon1> Thanks!
[telegram] <J> :)
GatewayBOT03-Dec-18 06:48 AM
[telegram] <Hermes08> Correct there is no change ...this is just an update
[telegram] <golovka4lena> 2030 (re @mailfreebtc: When 100 dolar)
[telegram] <Umitkara48> End of century (re @mailfreebtc: When 100 dolar)
GatewayBOT03-Dec-18 07:59 AM
[telegram] <Revolvermann> Hi. Is there a list of Komodo Telegram groups in any other languages?
GatewayBOT03-Dec-18 08:11 AM
[telegram] <Seko> t.me/komodo_ru (re @Revolvermann: Hi. Is there a list of Komodo Telegram groups in any other languages?)
[telegram] <Seko> Hi. Is there a list of Komodo Telegram groups in any other languages? (re @Revolvermann: Hi. Is there a list of Komodo Telegram groups in any other languages?)
[telegram] <Seko> t.me/komodogermanytalk (re @Revolvermann: Hi. Is there a list of Komodo Telegram groups in any other languages?)
[telegram] <Seko> I think there's a Turkish one, too.
[telegram] <Seko> And a trading group:
t.me/komodoplatform
GatewayBOT03-Dec-18 08:30 AM
[telegram] <Umitkara48> Any komodo turlish group (re @Seko: I think there's a Turkish one, too.)
[telegram] <Revolvermann> Only needed the german group (re @Seko: I think there's a Turkish one, too.)
[telegram] <Seko> They have a turkish channel on Twitter. Maybe it’s possible together with this guys create a group on Telegram...
https://mobile.twitter.com/KomodoTurk (re @Umitkara48: Any komodo turlish group)
GatewayBOT03-Dec-18 08:54 AM
[telegram] <Member212121> which version agama is good before hardfork?
[telegram] <Seko> Always the latest.
GatewayBOT03-Dec-18 09:36 AM
[telegram] <Constantini21> When will be the update?
[telegram] <Acura360> there will be an new agama update soon for that (re @Member212121: which version agama is good before hardfork?)
[telegram] <Acura360> 15th december (re @Constantini21: When will be the update?)
[telegram] <Member212121> Ok thanks
GatewayBOT03-Dec-18 10:40 AM
[telegram] <Sajeelahmad88> Down to the down more why
[telegram] <Sesinho> Patience. There are many good things about to arrive.
Komodo is preparing to activate a major update to the Komodo code base. Learn more about all the new tech features coming to Komodo on December 15, 2018.
[telegram] <Constantini21> Will Binance suport hard fork of KMD?
[telegram] <Sajeelahmad88> Yes but you will get nothing it's a normal hard fork just updating their blockchain (re @Constantini21: Will Binance suport hard fork of KMD?)
[telegram] <Constantini21> Ok
[telegram] <Constantini21> Thanks
[telegram] <Sesinho> The Komodo rebrand and full site design is coming soon too.
[telegram] <Sesinho> Soon Komodo very bullish. Patience
[telegram] <borntobe4live> I think so too
[telegram] <Sajeelahmad88> When (re @Sesinho: Soon Komodo very bullish. Patience)
[telegram] <Sajeelahmad88> This week (re @borntobe4live: Soon)
[telegram] <borntobe4live> cool
[telegram] <Sesinho>
[telegram] <tese22> Ive been reading this word Bout future prices from this project since sept 17. My experience is: its better to expect nothing and be happy with every new given by the team than worry about that. (re @borntobe4live: Soon)
GatewayBOT03-Dec-18 11:59 AM
[telegram] <borntobe4live> "Soon" was more a joke, since the word was mentioned in the original remark.
But I agree. We never know when it happens. But I'm bullish on Komodo and will hold (re @tese22: Ive been reading this word Bout future prices from this project since sept 17. My experience is: its better to expect nothing and be happy with every new given by the team than worry about that.)
GatewayBOT03-Dec-18 12:46 PM
[telegram] <tese22> I feel the same as u, that why Im recollectin my rewards every month :p I was joking with you because is boring to see everyday the same question
GatewayBOT03-Dec-18 01:34 PM
[telegram] <DanielSulMiners> hi can i mine kmdice whit z9minis?
[telegram] <yorklab> Yes you can. (re @DanielSulMiners: hi can i mine kmdice whit z9minis?)
[telegram] <DanielSulMiners> thanks mate
[telegram] <DanielSulMiners> the pre mine scared me 50% ! what you could to say about that to me ?


Bala is just a step away from entering the Rs 100 crore club
by Vedanshi PathakAyushmann Khurrana has been rightly deemed as the King of content in Bollywood. The actor has since day one picked scripts that are socially relevant and at the same time are woven in a way which is entertaining for the audience. The stars has a string of hits attached to his name and another blockbuster is surely on the cards as his latest release Bala is all set to enter the Rs 100 crore club.
After earning Rs 72.24 crore during its first week, the Ayushman, Bhumi Pednekar and Yami Gautam starrer earned Rs 3.74 crore on its second Friday, Rs 6.73 crore on Saturday, Rs 8.01 crore on Sunday, Rs 2.25 crore on Monday and finally Rs 2.05 crore on Tuesday making the total an enormous Rs 95.04 crore. With the film being inches away from the Rs 100 crore club, we say team Bala, take a bow!


radius:'auto' - Sets the radius of the pie. If
value is between 0 and 1 (inclusive) then it will use that as a
percentage of the available space (size of the container), otherwise
it will use the value as a direct pixel length. If set to 'auto', it
will be set to 1 if the legend is enabled and 3/4 if not.
innerRadius:0 - Sets the radius of the donut
hole. If value is between 0 and 1 (inclusive) then it will use that
as a percentage of the radius, otherwise it will use the value as a
direct pixel length.
startAngle:3/2 - Factor of PI used for the
starting angle (in radians) It can range between 0 and 2 (where 0 and
2 have the same result).
tilt:1 - Percentage of tilt ranging from 0 and
1, where 1 has no change (fully vertical) and 0 is completely flat
(fully horizontal -- in which case nothing actually gets drawn).
offset:
top:0 - Pixel distance to move the pie up
and down (relative to the center).
left:'auto' - Pixel distance to move the pie
left and right (relative to the center).
stroke:
color:'#FFF' - Color of the border of each
slice. Hexadecimal color definitions are prefered (other formats
may or may not work).
width:1 - Pixel width of the border of each
slice.
label:
show:'auto' - Enable/Disable the labels.
This can be set to true, false, or 'auto'. When set to 'auto', it
will be set to false if the legend is enabled and true if not.
radius:1 - Sets the radius at which to place
the labels. If value is between 0 and 1 (inclusive) then it will
use that as a percentage of the available space (size of the
container), otherwise it will use the value as a direct pixel
length.
threshold:0 - Hides the labels of any pie
slice that is smaller than the specified percentage (ranging from 0
to 1) i.e. a value of '0.03' will hide all slices 3% or less of the
total.
formatter:[function] - This function
specifies how the positioned labels should be formatted, and is
applied after the legend's labelFormatter function. The labels can
also still be styled using the class "pieLabel" (i.e. ".pieLabel"
or "#graph1 .pieLabel").
radius:1 - Sets the radius at which to place
the labels. If value is between 0 and 1 (inclusive) then it will
use that as a percentage of the available space (size of the
container), otherwise it will use the value as a direct pixel
length.
background:
color:null - Backgound color of the
positioned labels. If null, the plugin will automatically use the
color of the slice.
opacity:0 - Opacity of the background for
the positioned labels. Acceptable values range from 0 to 1, where
0 is completely transparent and 1 is completely opaque.
combine:
threshold:0 - Combines all slices that are
smaller than the specified percentage (ranging from 0 to 1) i.e. a
value of '0.03' will combine all slices 3% or less into one slice).
color:null - Backgound color of the
positioned labels. If null, the plugin will automatically use the
color of the first slice to be combined.
label:'Other' - Label text for the combined
slice.
highlight:
opacity:0.5 - Opacity of the highlight
overlay on top of the current pie slice. Currently this just uses a
white overlay, but support for changing the color of the overlay
will also be added at a later date.
Changes/Features
v1.0 - November 20th, 2009 -
Brian Medendorp
The pie plug-in is now part of the Flot repository! This
should make it a lot easier to deal with.
Added a new option (innerRadius) to add a "donut hole" to the
center of the pie, based on comtributions from Anthony Aragues. I was
a little reluctant to add this feature because it doesn't work very
well with the shadow created for the tilted pie, but figured it was
worthwhile for non-tilted pies. Also, excanvas apparently doesn't
support compositing, so it will fall back to using the stroke color
to fill in the center (but I recommend setting the stroke color to
the background color anyway).
Changed the lineJoin for the border of the pie slices to use
the 'round' option. This should make the center of the pie look
better, particularly when there are numerous thin slices.
Included a bug fix submitted by btburnett3 to display a
slightly smaller slice in the event that the slice is 100% and being
rendered with Internet Explorer. I haven't experienced this bug
myself, but it doesn't seem to hurt anything so I've included it.
The tilt value is now used when calculating the maximum
radius of the pie in relation to the height of the container. This
should prevent the pie from being smaller than it needed to in some
cases, as well as reducing the amount of extra white space generated
above and below the pie.
Hover and Click functionality are now availabe!
Thanks to btburnett3 for the original hover functionality
and Anthony Aragues for the modification that makes it compatable
with excanvas, this was a huge help!
Added a new option (highlight opacity) to modify the
highlight created when mousing over a slice. Currently this just
uses a white overlay, but an option to change the hightlight color
will be added when the appropriate functionality becomes available.
I had a major setback that required me to practically
rebuild the hover/click events from scratch one piece at a time (I
discovered that it only worked with a single pie on a page at a
time), but the end result ended up being virtually identical to the
original, so I'm not quite sure what exactly made it work.
Warning: There are some
minor issues with using this functionality in conjuction with some
of the other more advanced features (tilt and donut). When using a
donut hole, the inner portion still triggers the events even though
that portion of the pie is no longer visible. When tilted, the
interactive portions still use the original, untilted version of
the pie when determining mouse position (this is because the
isPointInPath function apparently doesn't work with
transformations), however hover and click both work this way, so
the appropriate slice is still highlighted when clicking, and it
isn't as noticable of a problem.
Included a bug fix submitted by Xavi Ivars to fix array
issues when other javascript libraries are included in addition to
jQuery
v0.4 - July 1st, 2009 -
Brian Medendorp
Each series will now be shown in the legend, even if it's
value is zero. The series will not get a positioned label because it
will overlap with the other labels present and often makes them
unreadable.
Data can now be passed in using the standard Flot method
using an array of datapoints, the pie plugin will simply use the
first y-value that it finds for each series in this case. The plugin
uses this datastructure internally, but you can still use the old
method of passing in a single numerical value for each series (the
plugin will convert it as necessary). This should make it easier to
transition from other types of graphs (such as a stacked bar graph)
to a pie.
The pie can now be tilted at an angle with a new "tilt"
option. Acceptable values range from 0-1, where 1 has no change
(fully vertical) and 0 is completely flat (fully horizontal -- in
which case nothing actually gets drawn). If the plugin determines
that it will fit within the canvas, a drop shadow will be drawn under
the tilted pie (this also requires a tilt value of 0.8 or less).
v0.3.2 - June 25th, 2009 -
Brian Medendorp
Fixed a bug that was causing the pie to be shifted too far
left or right when the legend is showing in some cases.
v0.3.1 - June 24th, 2009 -
Brian Medendorp
Fixed a bug that was causing nothing to be drawn and
generating a javascript error if any of the data values were set to
zero.
v0.3 - June 23rd, 2009 -
Brian Medendorp
The legend now works without any modifications! Because of
changes made to flot and the plugin system (thanks Ole Laursen!) I
was able to simplify a number of things and am now able to use the
legend without the direct access hack that was required in the
previous version.
v0.2 - June 22nd, 2009 -
Brian Medendorp
The legend now works but only if you make the necessary
changes to jquery.flot.js. Because of this, I changed the default
values for pie.radius and pie.label.show to new 'auto' settings that
change the default behavior of the size and labels depending on
whether the legend functionality is available or not.
v0.1 - June 18th, 2009 -
Brian Medendorp
Rewrote the entire pie code into a flot plugin (since that is
now an option), so it should be much easier to use and the code is
cleaned up a bit. However, the (standard flot) legend is no longer
available because the only way to prevent the grid lines from being
displayed also prevents the legend from being displayed. Hopefully
this can be fixed at a later date.
Restructured and combined some of the options. It should be
much easier to deal with now.
Added the ability to change the starting point of the pie
(still defaults to the top).
Modified the default options to show the labels to compensate
for the lack of a legend.
Modified this page to use a random dataset. Note: you may need to refresh the page to
see the effects of some of the examples.
May 21st, 2009 - Brian
Medendorp
Merged original pie modifications by Sergey Nosenko into the
latest SVN version (as of May 15th, 2009) so that it will work
with ie8.
Pie graph will now be centered in the canvas unless moved
because of the legend or manually via the options. Additionally it
prevents the pie from being moved beyond the edge of the canvas.
Modified the code related to the labelFormatter option to
apply flot's legend labelFormatter first. This is so that the labels
will be consistent, but still provide extra formatting for the
positioned labels (such as adding the percentage value).
Positioned labels now have their backgrounds applied as a
seperate element (much like the legend background) so that the
opacity value can be set independently from the label itself
(foreground). Additionally, the background color defaults to that of
the matching slice.
As long as the labelOffset and radiusLimit are not set to
hard values, the pie will be shrunk if the labels will extend outside
the edge of the canvas
Added new options "radiusLimitFactor" and "radiusLimit" which
limits how large the (visual) radius of the pie is in relation to the
full radius (as calculated from the canvas dimensions) or a
hard-pixel value (respectively). This allows for pushing the labels
"outside" the pie.
Added a new option "labelHidePercent" that does not show the
positioned labels of slices smaller than the specified percentage.
This is to help prevent a bunch of overlapping labels from small
slices.
Added a new option "sliceCombinePercent" that combines all
slices smaller than the specified percentage into one larger slice.
This is to help make the pie more attractive when there are a number
of tiny slices. The options "sliceCombineColor" and
"sliceCombineLabel" have also been added to change the color and name
of the new slice if desired.
Tested in Firefox (3.0.10, 3.5b4), Internet Explorer
(6.0.2900, 7.0.5730, 8.0.6001), Chrome (1.0.154), Opera (9.64), and
Safari (3.1.1, 4 beta 5528.16).


These pages are for people interested in using the development copy of PETSc or contributing to the PETSc libraries. This information is intended only for people who are experienced with building, using, and debugging PETSc. If you cannot use makefiles, a debugger, and EMACS etags, then please don't access these pages.
Consider joining the PETSc developers mailing-list.How to:
- browse sources in the repository
- obtain the development version of PETSc
- compile the developement version
- build documentation for the development version
- submitting code for inclusion in PETSc
- check nightlybuild logs
- add a new PC type
- add a new KSP type
- add a new subclass of a matrix type (implementation inheritence)
Browsing source:
One can browse the development repositories at the following locationObtaining the development version of PETSc:
Install Git if it is not already installed on your machine, then obtain PETSc with the following:git clone https://bitbucket.org/petsc/petsc
cd petsc
git pull
make reconfigure all
(shorthand version of./$PETSC_ARCH/lib/petsc/conf/reconfigure-$PETSC_ARCH.py && make all
)
- git help [or]
- man git
- [developer instructions at our wiki]
- [Pro Git book]
Building documentation:
The documentation tools listed below (except for pdflatex) are automatically downloaded and installed by ./configure.
- Sowing: a text processing tool developed by Bill Gropp. This produces the PETSc manual pages see sowing documentation
- C2html: A text processing package. This generates the HTML versions of all the source code.
- A version of pdflatex (for example in TeX Live): This package might already be installed on most systems. It is required to generate the users manual (part of the PETSc documentation).
Once pdflatex (e.g., from TeX Live) is in your PATH, you can build the documentation with:
make alldoc LOC=${PETSC_DIR}
Submitting code for inclusion in PETSc:
See https://bitbucket.org/petsc/petsc/wiki/Home for how to contribute code to PETSc.Please read the code standards chapter of the developer guide before submitting code.
Once you have gained experience with developing PETSc source code, you can become an active member of our development and push changes directly to the petsc repository. Send mail to<EMAIL_ADDRESS>to arrange it.
Developer guide:
The developer guide gives an overview of the design and detailed style specifications.Nightly builds:
The logs for the nightly builds at
Other ways to obtain PETSc:
Getting a Tarball of the git master branch of PETSc
Use the following URL:This mode is useful if you are on a machine where you cannot install Git or if it has a firewall blocking http downloads.
After the tarballs is obtained - do the following:tar zxf petsc-petsc-CHANGESET.tar.gz
mv petsc-petsc-CHANGESET petsc
To update this copy of petsc, re-download the above tarball. The URL above gets the latest changes immediately when they are pushed to the repository.
Getting the Nightly tarball of the git master branch of PETSc
The nightly tarball will be equivalent to the release
tarball - with all the documentation built. Use the following URL:


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Software
Webserver
Database
Mailserver
FTP-Server
Hardware
Operating System
Kernel
CPU / Load average
RAM / SWAP
Network
IP Address
External IP Address
Download Speed
Upload Speed


ABOUT
Unnath H.R
Unnath H.R, son of Mr. H.B Rathnaraju and Jayapadma and the disciple of Vidhusi Ambale Rahjeshwari, is a well known name in the field of dance in India and Abroad. He is a post graduate in both Dance and English Literature, Vidwath in dance (professional graduate in Dance from the Karnataka State Board) and has been presented on stage in the major cities of India as well as in the U.S., Russia, Belarus, Malaysia and Thailand, and made his Sri Lanka debut to great acclaim in 2016. Unnath has won many prestigious awards and titles such as “Ekalabya Sanman” in 2009 from Orissa, “Natya Koustuba” in 2009, from Andhra Pradesh, “Abhinaya Nrutya Koumudhi” in 2010, from Andhra Pradesh, “Natraj Gopi Krishana Samman” in 2010, from Mumbai, Maharashtra, “Kalamandir Puruskaram”in 2013 at Peravoor, Kerala and “Natya Mayooram” for the best performance in 2014, April, Bhilai, Chattisghar. He stood “First Best Season Performer” of India in 2012, Pune.Unnath is an ‘A’ grade Artist at Dooradarshan (Indian Government headed Television channel). Has directed many dance ballets, and choreographed various dance repertory in Bharathanatyam, specializing in the Mysore school, and folk styles. He is the Principal and Artistic Director of Natyakala Nivas, which was awarded the best culture revival centre for 2014, Travel Puruskar, from Maldives arts Council and GCC, Karnataka. He is training more than 150 students, and serves as the Managing Trustee for “Rathnakala Padma Kuteera Trust”. The credit of choreographing thousands of students for Republic Day and Independence Day from past 3 years goes to Unnath. Today he has crossed training more than 20,000 school students. Unnath is a member of esteemed group Prayathnam, classical dance exponents based in Chennai. ...read more
Major Projects and Dance Festivals.
⦁ Hampi Utsav, Hampi,Karnataka.
⦁ Hoysala Utsav, Halebedu and Belur, Karnataka
⦁ Natarani, Darpana Dance Festival, Ahmedabad, Gujarat
⦁ Uttarayan at Delhi, IIT Kharagpur (WB), Kolkata.
⦁ Natraj Gopi Krishan Dance Festival, Mumbai
⦁ Ekalabya festival, Bhubhaneswar, Orissa.
⦁ Nitya Nrutya, Bangalore, Karnataka.
⦁ Nrithyanruthyati 3rd Edition, Bhilai, Chattisghar.
⦁ Natraj Dance Festival, Nrutya Kala Parishat, Bangalore
⦁ ICCR, Friday Events, Bangalore
⦁ Kannada and Culture Programs at Mysore, Bangalore, Hassan.
⦁ Abhinaya Nrutya Festival, Elooru, Andhra Pradesh.
⦁ Peravoor Vaibhava, Peravoor, Kerala
⦁ Rasa Samaroha, IIT Kharagpur, West Bengal.
⦁ Sringeri Sabha, Sringeeri
⦁ Nrutya Parishat, Godhavari,Andhra Pradesh
⦁ Noopra Festival, Bangalore.
⦁ Hoysala Sambrama, Hassan.
⦁ Nrutya Edition 5, Mysore.
⦁ Shravana, Bijapur
⦁ Shankara Festival, Shankara Foundation , Bangalore.
⦁ Ratyatra, Julan etc., at various religious sites including Dharamsala, Moodabidre, Kalasa, Sulya, Puttooru,Shravanabelagola, Tumkur, Bijapur, Belguam, Hubli,etc.,
⦁ UNG programs at Russia and Belarus.
⦁ Workshop at Woman’s University , Bijapur with Bharatiya Vidya Bhavan, Bangalore.
⦁ South zone Cultural center performances at Eloor, Andhra Pradesh.
⦁ ICCR every Friday program at Yavanika, Bangalore
Ensembled with various dance troupes and companies, such as Nadam of Bangalore, Sahaj Padma of West Bengal, Invocation Dance Company Malaysia, Shankara Dance Ensemble Bangalore, Nrutya Dance Company, Bangalore, Noopura Dance School, Bangalore. Prasiddha Foundation, New Delhi. Shanaka foundation , Bangalore.
INTERNATIONAL PROGRAMS AND WORKSHOPS:
⦁ Battery Dance Festival 2016, NEW YORK, USA at Robert F. Wagner Park and Schimmel Center of Arts, PACE University.⦁ Battery Dance Company 40th Anniversary 2016 New York, USA.
⦁ Incredible India 2016 , Huston, Texas, USA at Miller open air theater.
⦁ Indian Culture Heritage Foundation, Dallas, Texas, USA at Dallas City Performance Hall.
⦁ Ganga Production at Temple of Fine Arts, Kuala Lampur , Malaysia.
⦁ Workshop for SARA Knight Ballet school, NYC, USA.
⦁ Workshop at Irving school, NYC, USA
⦁ Workshop at Dallas, Asiatic Society of USA.
⦁ Workshop for Army Band, Colombo , SRILANKA
⦁ Workshop for Dancers guiled, Colombo SRILANKA
⦁ Workshop for Chanadana Dancers Colombo SRILANKA
⦁ Performance for Rabi Chaya , St. Xavier’s Auditorium , Colombo SRILANKA January 2016.
⦁ Performance for ICCR, Colombo , SRILANKA.
⦁ Provincetown dance festival Massachusetts, U.S.
⦁ U.S. Embassy program at Kandy, Sri Lanka, Grand college Auditorium
⦁ Drums and Dance December 2016, st. Xavier’s Auditorium College auditorium.
Script, Music and Choreographies.
Major Highlights are, Dashamaha Vidya ( 10 forms of shakti)Asta Lakshmi (8 forms of laskhmi)
Soma, the survivor (folk based )
Dasaavataram (10 incarnation of lord Vishnu)
Punyakoti (Folk based)
Shiavaasta, classical production
Sri Krishna Tatva Darshana
Bhakthi, gnana and viraagya a philosophical adoration to the bhakthi movement
Smrithi Namana 2014 (shasanokta mahileyaru)
Prathisthe 2014
Shasana Namana
read less
EVENTS
AS FESTIVAL AND EVENT ORGANISER :
PAST PRODUCTIONS :
IN COLLABURATION WITH HERITAGE GROUP: INDIAN ART FESTIVLA AT HOYSALA RESORT.
ARTS FESTIVAL FROM NKN AND RKPKT WITH KANNADA AND CULTURE
⦁ NRUTYA MILINDA :
The festival aims in meeting the international standards for Indian performing arts, inviting professional artists from various parts of India. Its an annual festival.⦁ SUPRAJAVATH :
A festival for budding Children. As the name say, Suprajavath literally means A group of Children. It’s a 6 monthly program. Concentrates on developing skills among children by providing bigger platforms.⦁ MASIKA :
A monthly festival for local or native artists , which invites arts from Hassan District. It includes forms such as Light Music, Hindusthani and Carnatic Music, Classical Dance forms, fine arts, etc.,⦁ TRIMASIKA :
Literally means a 3 monthly program for state level performers. Trimasika provides platforms for traditional dance and music.  Forum provides performance opportunities for artists coming from various background.AIMS FOR THE COMING YEARS :
⦁ To create a forum of psychiatry , psychology with doctors ,councilors and arts to over come the basic child problems such as Asperger’s syndrome, Autism , Bipolar disorders, Dyslexia etc.,
⦁ Aims to organize school programs to cultivate balanced , social and freedom education .
Contact Me
Hassan,India
Phone: +91 –<PHONE_NUMBER>
Email<EMAIL_ADDRESS>natyakalanivas@gmail.com


You get the API token on todoist.com in the settings under Integration.
Every run creates log entries. Witing log events can be opted out here.


I thought I might give a report on my unusual mixtures of drugs since I can never really find people taking the same things at the same time. Let's start off with the basics:
Zopiclone - Comes in 7.5mg tablets (blue) here in New Zealand. They are used in the treatment of insomnia, slowing down activity in the brain so one can doze off to la la land.
Citalopram - Come in 20mg, round tablets (white) in New Zealand. They are used in the treatment of depression and are classified as SSRI's (selective serotonin re-uptake inhibitors).
Marijuana - Some of the local AK-47 variety. New Zealand weed is very potent. I visited my home country (Canada) a few years ago and found the weed there had nothing on the stuff grown here.
Beforehand: Anyways, it was my 20th birthday so we decided to get wasted, being Uni students with nothing better to do. I had went out the previous night with my friend and drank quite a bit, but was feeling ok in the morning. I went to my doc to have my prescription re-filled since I was running out of Citalopram. Since he had prescribed me Zopiclone before, he gave me some when I asked for it, even though I had always faked my insomnia just to get the stuff. At this time I had just stopped using Citalopram for my depression, having just broken up with my gf, convinced she was the making of my sadness.
The Drug Taking: I headed back to my flat around 1:30 pm to share my new found drug wealth with my friends. We had all been stoners for years, but nowadays we were tending to get into harder substances and experimentation, since weed was getting a bit boring. We cut up some Zopiclone and Citalopram (1 pill of each for 4 of us) and chopped it into a fine powder before snorting it. We waited 30 minutes for effects, when my friends said they felt rather tired and relaxed. I was used to both drugs so I popped 2 more Citalopram and another half a Zopiclone. After another 30 minutes I too felt rather tired and sat down for 2 hours to play some Battlefield 2.
I had never taken this much Zopiclone before and felt rather drowsy. As I was sitting playing BF 2, I felt my hands moving over the keyboard and mouse as if on their own, disconnected from my body. My whole body felt numb and limbs felt heavy, but I managed to stay awake. I had basically no thoughts, acting much like a zombie. Whenever somebody was blown sky high by a rocket, I'd just crack up laughing for awhile and then get back to the game.
Around 4 pm - 2 1/2 hours after the first dose - effects started to subside, my mind coming back to life but still feeling rather drowsy. I went into our lounge and found my friends smoking up and listening to Zeppelin. I thought why not, sat down with them and smoked a few bowls. I had given up weed over a year ago, only smoking it once or so a month because of the paranoia it brought on in me. This time, however, I felt relaxed and even more mellowed out than ever. Absolutely no paranoia. We continued listening to Zeppelin, Floyd and The Doors, when we realised it was 7 pm. We had to head out to my party at my friends place, and everyone was already wondering where we were.
I headed downstairs and had a shower. Since I was the first one to do so, when I got out and dressed, I cut up some more Zopiclone and Citalopram for my friends. I was still buzzing a bit on both the weed and Zopiclone by 7.30. When we were all ready by 8, we all had our snorts of the drugs (1 pill of each) and were ready to head out. This is where things started to go wrong.
I headed downstairs and checked my stash. I realised 2 more pills than what I had dished out were missing. Being that I had just snorted more of the stuff, which was starting to take hold buoyed by yet more pot, I thought I was just being paranoid and ignored it.
Now the city I live in has big hills, perfect for bombing on skateboards. My friend and I were way ahead of my 4 other friends, and we arrived at my friends place first. Everyone was there waiting for us. We totally forgot about my other friends behind us and we started the party. 30 minutes later, around 9 pm, my other friends walked in. It had taken them an hour to skate a 10 minute trip, with good reason. One of my friends had totally mangled his face and hands because he bombed down a huge hill and forgot to slow down for the speed bumps at the bottom of the hill. He hit the bumps around 50 kmh and bailed off his board, smashing one side of his head into the pavement.  We sat him down and realised he had a concussion, not knowing where he was and kept asking for me, when I was right at his side. It was then that I realised where my other 2 pills had gone that night. Bastard I thought.
By this time, 9:30 pm, I was pretty gone too. I headed into the bathroom, my other friends at the party not being to accepting of drugs, legal or illegal, and popped another zopiclone. The next 30 minutes were pretty hazy, and after that I cannot remember anything. This next part is going on my friends reckoning. I just sat in the single chair for the rest of the night, staring at the walls. People started giving me presents and I would open them and just stare at them with the most glazed over look in my eyes and say 'thanks maaaaaaan'. Occasionally I would laugh at absolutely nothing. Around 10:30 pm I attempted to go to the toilet, but I kept banging into the walls, hardly being able to stand up and looking 'like a zombie'. I wouldn't say anything and just wander off in another stupor til I banged into someone else. Someone finally sat me down around everyone drinking and talking. I, needless to say, did not participate.
Around 11:30 pm my friends started tearing the place apart, throwing chairs and everything that wasn't bolted down at each other. I apparently just stared at everything going around me, not even flinching when something heavy went flying past my face. We eventually left at 12 am to take my friend to the hospital for his skateboarding accident. Since the hospital was close by, we also headed home. I woke up in the morning having no clue how I ended up in my own bed.
Aftermath: My friend had pretty serious injuries. He had fractured his face in 3 places, needing plastic surgery to fix it. He had broken both wrists and nearly dislocated his shoulder. His face was bruised badly for nearly a month afterwards, but made a full recovery in all respects after 3 months.
On the other hand, I was a wreck for the next 2 days. I felt hungover and groggy the first day, preferring to skip Uni and just sleep it off. The second day I woke up with the most horrible depression.  Since I now had ample stores of Citalopram, I was very nearly considering committing suicide. I broke open every packet, counted out every pill (216) and thought of taking them. Luckily, I have great friends who were concerned for me, telling me to come over and talk it out with them. I also remembered promising never to try to commit suicide again, being the absolutely stupidest idea ever. I went to a party that night, took absolutely nothing, although people noticed one of my pupils was bigger than the other. Whether this was a side effect of the drug taking (unlikely) or massive crying bout of 4 hours (likely) I don't know. I was back to normal the next day.
I think this happened because I did drugs in a bad frame of mind. I'm sure I used the little serotonin I had in my brain by doing so, then had none left afterwards, leaving me susceptible to depression and suicidal thoughts. Thanks for reading.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


{{rating.member}} → {{rating.teammate}}
{{rating.date | humanize }}
That's all. You may close this window now.
If you notice a mistake in your ratings, you can use the back button to make a new evaluation. I will use only the most recent evaluation.


run package¶
This package provides different example pre-configured executions of Cnerator.
Submodules¶
run.1-function-each-type module¶
Example execution of Cnerator to create a particular number of functions.
It creates a program using the 1_function-each-type-10.json
file, running different visitors.
Run it from the parent folder with python -m run.1_function_each_type
.
run.15-function-each-type module¶
Example execution of Cnerator to create a particular number of functions.
It creates a program using the 15-function-each-type.json
file, running different visitors.
Run it from the parent folder with python -m run.15_function_each_type
.
run.2000-function-void-no-void module¶
Example execution of Cnerator to create a particular number of functions.
It creates a program using the 2000-function-void-no-void.json
file, running different visitors.
Run it from the parent folder with python -m run.2000_function_void_no_void
.
run.300-function-each-type module¶
Example execution of Cnerator to create a particular number of functions.
It creates a program using the 300-function-each-type.json
file, running different visitors.
Run it from the parent folder with python -m run.300_function_each_type
.
run.article module¶
Example execution of Cnerator to create particular functions.
It creates a program using the article.json
file, running different visitors.
Run it from the parent folder with python -m run.article
.
run.defaults module¶
Example execution of Cnerator passing no parameters. It creates a random program considering the default probabilities. Run it from the parent folder with ``python -m run.defaults`.
run.defaults_one_file module¶
Example execution of Cnerator passing no parameters but generation in one file (-n 1
).
Run it from the parent folder with python -m run.defaults_one_file
.
run.help module¶
Example execution of Cnerator passing the --help
parameter.
Run it from the parent folder with python -m run.help
.
run.probs module¶
Example execution of Cnerator passing the -p
parameter to specify the probabilities of two language constructs.
Run it from the parent folder with python -m run.probs
.
run.probs_file module¶
Example execution of Cnerator specifying probabilities in a json file (example_probs.json
).
Run it from the parent folder with python -m run.probs_file
.


Last time I updated this was in February of 2022. Whew.

However, I can honestly say that I think I’m going to commit to updating this way more frequently (for real this time.)
With all of the business happening on twitter, and my new belief in my comic making / other skills, I think it’s time I really use this as a hub for all of my creative projects (both comics, and tech).
Here are some updates.
SITE UPDATES.
I finally added a email-list! Go to the About Me page, enter your email and click "Submit" to keep up with project releases. I promise I won't spam your inbox...I'll only be using it to let people know about the releases of new projects...such as...RAZR is OUT.
I’ve been procrastinating the release of a comic I wrote and commissioned a great artist to draw. I wasn’t sure how I wanted to release it. Did I want to put it out for free? Did I want to charge people for it?
I definitely think it’s the best story I’ve ever written, and wanted to make sure I got eyes on it…but I also know it was pretty expensive to make.
After taking a lot of thinking time, and finding others who had works online, I realized that it was possible to charge folks to download it, but upload onto tapas for people to read for free. So, I decided to move in that direction. (PLUS, life is finite. Money will not follow me to my grave… So why not put it out for free? I want others to feel the good I felt when I wrote it…and I think Enzo did an AMAZING job capturing those feelings in the artwork. COMMISSION them!)
Tanktop Owl is on indefinite hiatus.
After finishing chapter 1, I realized that my drawing skills were way better than I was demonstrating with LYON (aka Tanktop Owl)…and I wanted to draw more relatable things. I still like the idea of Tanktop Owl, but I think it’s time I move away from drawing circles as Owls, and start drawing more human things…where humans overcome great challenges. It’ll still be available to read on Tapas (I won’t delete it from there), but I don’t think I’ll be updating it any time soon. It was a great learning experience, but I’m ready to move on to other things… Is this…growth?
New Graphic Novel Coming 2023?
Maybe? I started a story called FRACTION and I’m enjoying the process of creating it. As of right now, it doesn’t have an end…I’m just coming up with it as I go. I’ve realized that my skills are steadily improving, and I want to try my hand at creating a longer form, complete story…hence the birth of a new idea that I’m currently working through! I’ve finished the general outline…and I love the story. Next steps are to type up the outline, and then convert it to a comic script.
Usually, when I am working on my own project, I go from outline to thumbnails…but for this, I want to take the same process I used to write RAZR…hopefully it’ll yield the same results (story and pacing wise), rather than turning into something LYON did, where the pacing wasn’t exactly as I wanted it to be. We shall see as time goes on!
The thumbnail for this post is of the main character and one of the antagonists.
I’m excited for how it’s looking. I’m aiming for about 50 pages minimum. We’ll see how it goes.
Final thanks and farewell.
With that all being said, thanks for reading up to here! It’s been a long update…and I promise others won’t be as long.
I’ll try updating this MONTHLY (at minimum)…just to keep myself consistent..especially as I focus more on the GN. I’m excited to get back into a creative groove.


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Predicting Flight Delays with a Random Forest
July 6, 2016
Contents:
1. The airline data set
2. Categorical features
3. Intrinsic discrepancies
4. Fitting Strategy
5. Grid search
6. Classifier performance
7. Technical note
On Sunday June 5 of this year, the NYC meetup group Women in Machine Learning and Data Science organized a workshop on random forests led by Anita Schmid and Christine Hurtubise from OnDeck. They started with a theoretical review of the random forest algorithm, followed with some practical tips, and after that we all broke up into small groups to try our hands on a data set of flight delays. Some of us used Python, others R.
There wasn’t really enough time to complete the analysis during the workshop, so I finished it at home and report the results here.
The airline data set
The data set consists of 100,000 flight records (this is actually a subsample of a large public data set). After some basic cleanupThe cleanup consisted in converting the “Month”, “DayofMonth”, and “DayOfWeek” fields from string to integer, and mapping “DepTime” values larger than 2400 back to the interval [0,2400]. , each record contains the following fields:
Table 1: Features of the airline data set; the last row (dep_delayed_15min) is the response variable; the type column indicates whether a feature is binary (bin), integer (int), or categorical (cat).
| Feature | Description | Type | |
|---|---|---|---|
| 1. | Year | A number between 2004 and 2007 | int |
| 2. | Month | A number between 1 and 12 | int |
| 3. | DayofMonth | A number between 1 and 31 | int |
| 4. | DayOfWeek | A number between 1 and 7 | int |
| 5. | DepTime | A number between 0 and 2400 | int |
| 6. | UniqueCarrier | Two-character airline code | cat |
| 7. | Origin | Three-letter departure airport code | cat |
| 8. | Dest | Three-letter destination airport code | cat |
| 9. | Distance | Flight distance in miles | int |
| 10. | dep_delayed_15min | Y/N flag indicating a delay of ≥15 min. | bin |
The purpose of the exercise is to construct a predictor of the binary delay variable (“dep_delay_15min”) based on the nine available features. The input data set is unbalanced: 80,726 flights out of 100,000 had no delay.
To gain some insight into the features it is helpful to plot their normalized distributions separately for the “delay” and “no-delay” cases. This is shown below in Figures 1, 2, and 3. Because of their normalization, these plots have a simple statistical interpretation: at any point along the X-axis, the ratio of the two distributions is a likelihood ratio. The top-left panel of Figure 1 for example, indicates that the likelihood of a delay increased from 2004 to 2007.
Several other effects are visible in these plots: delays tend to be more likely during summer months and in December, in the second half of any given month, in the middle of the week, and at the end of the day. Short flights seem less likely to be delayed than long ones. Perhaps the sharpest difference between delay and no-delay is exhibited by the histogram of departure times.
The remaining features are categorical, and their distributions can be represented with bar charts. First the airline codes, ordered alphabetically. There are 23 of them:
Next, the airports of departure and destination. There are 307 of the former and 306 of the latter, so these are long charts. For readability I have chosen to display them vertically, and ordered alphabetically. The main thing one learns from them is that some airports are busier than others. Busyness may correlate with delays (see for example ATL-Atlanta, EWR-Newark, and ORD-Chicago), but not in a systematic way (DFW-Dallas/Fort Worth, IAH-Houston, and LAX-Los Angeles). Enjoy the scroll down, and I’ll see you on the other side of YUM (Yuma, AZ)…
Categorical features
To prepare the data for the classifier, the categorical features (“UniqueCarrier”, “Origin”, and “Dest”, see Table 1) must be converted to dummy variables using one-hot encoding. Pandas has an easy method for this:
df2 = pd.get_dummies(df1, drop_first=False)
This results in data frame df1
, with 9 feature variables, being replaced by data frame df2
, which has 642 feature variables! The drop_first=False
argument indicates that we do not wish to drop one dummy variable per categorical variableSee for example Galit Shmueli, “The use of dummy variables in predictive algorithms”. . This is only necessary for regression problems, where input multicollinearity is an issue (“dummy variable trap”). For tree-based classification models, removing a dummy variable may actually reduce efficiency.
Intrinsic discrepancies
For future reference I find it useful to summarize with one number the effectiveness of a feature to distinguish between delay and no-delay. A relatively simple, information-based measure to achieve this is the so-called intrinsic discrepancySee for example J. Bernardo, “Reference Analysis”, Handbook of Statistics 25 (D. K. Dey and C. R. Rao, eds.), 17-90, Elsevier, 2005. between two probability distributions and :
For discrete distributions the integrals become sums. After sorting them in decreasing order, the top ten intrinsic discrepancies between delay and no-delay are as follows:
Table 2: Intrinsic discrepancies between the delay and no-delay distributions of the features in the airline data set. The features “Origin_ORD”, “UniqueCarrier_HA”, “UniqueCarrier_EV”, and “Origin_HNL” are some of the dummy variables created by one-hot encoding of the categorical features in the original data set.
| Feature | Intrinsic Discrepancy |
|---|---|
| DepTime | 0.2400 |
| Month | 0.0205 |
| Distance | 0.0114 |
| DayOfWeek | 0.0069 |
| Year | 0.0063 |
| Origin_ORD | 0.0058 |
| UniqueCarrier_HA | 0.0056 |
| DayofMonth | 0.0050 |
| UniqueCarrier_EV | 0.0046 |
| Origin_HNL | 0.0036 |
It is again clear that departure time is by far the most discriminating feature, followed by month and distance. The Chicago airport (ORD) as point of origin is a noteworthy feature by itself, as are Hawaiian Airlines (HA), Express Jet (EV), and Honolulu airport (HNL).
Fitting strategy
When fitting a classifier to training data, an important concern is to avoid overfitting, in order to keep the generalization error under control. This is a measure of the accuracy of the classifier when applied to previously unseen data.
This concern leads to the distinction between parameters and hyper-parameters. Parameters are quantities that are adjusted to fit a classifier to training data, whereas hyper-parameters are used to control overfitting. In the case of a random forest for example, parameters specify what happens at each node of each decision tree, whereas hyper-parameters specify the number of trees and the maximum depth of a tree.
A common strategy to determine the hyper-parameters is to maximize the classifier accuracy, defined as the fraction of cases that are correctly classified. However this is not a good strategy for unbalanced classes, as is the case in the airline data set, where we have 19% “positives” (delayed flights) versus 81% “negatives” (non-delayed flights). To see this, note that accuracy can be written as:
where is the prevalence, the fraction of positives in the sample. Since the recall (the fraction of positives that are correctly classified) and specificity (the fraction of negatives that are correctly classified) are independent of , the above equation shows that accuracy does depend on and is therefore not an intrinsic property of the classifier.
A better measure to maximize is AUC, the area under the Receiver Operating CharacteristicSee for example Tom Fawcett, “An Introduction to ROC Analysis”, Pattern Recognition Letters 27, no. 8 (June 2006), 861–874. (ROC). It is independent of the prevalence and can be interpreted as the probability for the classifier to produce a higher score for a randomly drawn positive than for a randomly drawn negative.
A good fitting strategy, then, starts with a three-fold cross-validated search over a grid of hyper-parameters, and follows with testing on a holdout sample. Here are the steps:
-
Randomly split the entire data set into a training set and a test set, in the ratio of 70% to 30%.
-
Specify a “reasonable” search grid in hyper-parameter space.
-
Using the training set, perform a three-fold cross validation fit at each point of the search grid. Use AUC to determine the optimal point.
-
Refit the random forest to the entire training set, using the hyper-parameter values at the optimal point from the grid search.
-
Evaluate the properties of the fitted classifier on the test set.
In the next sections I describe the grid search and the result of applying the refitted classifier from step 4 to the test set.
Grid search
Scikit-learn provides method GridSearchCV
to search a grid in hyper-parameter space for the optimal classifier of a given type in a given problem. In the present case we are interested in a RandomForestClassifier
. As was emphasized at the WiMLDS workshop, random forests can and do sometimes overfit. Scikit-learn provides three parameters to control overfitting, and these are the ones I used in the grid search:
-
n_estimators: the number of trees in the forest; more trees reduces overfitting but takes longer to run; I tried the values 50, 100, 200.
-
max_depth: the maximum depth of a tree in the forest; the deeper a tree, the more it risks overfitting; I tried the values 5, 10, 20.
-
min_samples_leaf: the minimum number of training examples in a newly created leaf in a tree; the smaller this number, the higher the risk of overfit; I tried the values 1, 2, 3, 4, 5, 10, 20.
The remaining random forest parameters were set to their scikit-learn default values, except for class_weight, which was set to “balanced_subsample”. Among the grid search parameters, scoring was set to “roc_auc”, which is the AUC defined in the previous section.
The result of the grid search is n_estimators = 200, max_depth = 20, and min_samples_leaf = 2, which yields an AUC of (as obtained by the 3-fold cross validation). There is relatively little variation across the grid, the lowest point having , a 4% difference.
Classifier performance
The grid search was performed on 70% of the total sample. I used the remaining 30% as a test sample to compute the confusion matrix and make summary plots. Here then is the confusion matrix, where I assigned the label “positive” to “flight delay” (since that’s the effect of interest) and the label “negative” to “no delay”:
Table 3: Confusion matrix for the random forest classifier found with the grid search, showing the number of true negatives (tn), false positives (fp), false negatives (fn), and true positives (tp). A 50% threshold on the classifier output is assumed.
| Predicted No-Delay | Predicted Delay | Total | ||
|---|---|---|---|---|
| Actual No-Delay | tn = 15458 | fp = 8747 | 24205 | |
| Actual Delay | fn = 1881 | tp = 3914 | 5795 | |
| Total | 17339 | 12661 | 30000 |
From this matrix we can estimate some of the standard quantities that are used to evaluate the performance of a classifier:
Table 4: Performance indicators for the random forest classifier used to predict flight delays. “Sensitivity” is also known as “recall”, and the two types of precision are sometimes referred to as positive and negative predictive values.
| Sensitivity | (probability to identify a true positive): | 67.5% |
| Specificity | (probability to identify a true negative): | 63.9% |
| Precision | (probability that a positive id is true): | 30.9% |
| Precision | (probability that a negative id is true): | 89.2% |
| Accuracy: | (probability of a correct identification): | 64.6% |
All the above numbers are relative to a 50% threshold on the output of the classifier. Here is how this output is distributed, separately for delayed and non-delayed flights, in the training and test samples:
The histograms are centered around 50% because I set the parameter “class_weight” to “balanced_subsample” in scikit-learn’s random forest classifier. Had I not done so, the histograms would have been centered around the fraction of positives in the dataset, which is about 20%, and all bins above 50% would have been empty. As a result the precision and sensitivity would have been zero, and the specificity 100%, due to the 50% threshold on the classifier output.
For predicting flight delays, thresholds other than 50% can be chosen from the left panel of Figure 5. The queue rate is the fraction of instances that pass the threshold cut. As the threshold increases, fewer true positives pass the cut, leading to a decrease in recall that follows the decrease in queue rate. On the other hand the purity of the sample of instances passing the cut increases, as shown by the precision curve.
Note how the precision curve in the left panel becomes more jagged for thresholds above 0.60. This is due to a lack of statistics, as can be inferred from the right panel of Figure 4. To explore the variability of the precision, recall, and queue-rate curves as a function of threshold, I generated independent random forest models from 50 different random splittings of the original data set into training and test subsets (still maintaining a 70/30 ratio). I used this ensemble of models to compute and draw median curves and 90% confidence belts, which are shown in Figure 5’s right panel.
The confidence belts are generally quite narrow, the only exception being the precision curve for thresholds above 0.60. This type of plot can be used to guide business decisionsFor a nice introduction to thresholding, see this blog post by Slater Stich, “Visualizing Machine Learning Thresholds to Make Better Business Decisions”. .
As mentioned earlier, our random forest classifier uses 642 features (after converting categorical features to binary ones). It is therefore interesting to check which ones are important, and how much impact important features have compared to the other ones. Scikit-learn provides a RandomForestClassifier attribute to extract feature importances. Each feature importance measures the decrease in classification accuracy when the corresponding feature values are randomly permuted over all trees in the forest.
Figure 7: Receiver Operating Characteristic for the random forest classifier used to predict flight delays. The curve is shown both for the training data set (orange) and the testing data set (blue).Figure 6 shows that departure time is by far the most important feature, in agreement with the intrinsic discrepancy calculation shown earlier.
The last plot I’d like to show is that of the Receiver Operating Characteristic (ROC). This is a plot of the true positive rate versus the false positive rate, and is shown in Figure 7. The orange curve is the ROC calculated on the data set on which the random forest was trained, whereas the blue curve was obtained from the testing data set. The area under the orange ROC is 0.786, that under the blue ROC 0.717. The fact that both curves are not too far from each other indicates that there is little overfitting.
Technical note
The Jupyter notebook for this analysis can be found in my GitHub repository RandomForests.


Python Brackets Jupyter Kernel
Today we published a Jupyter kernel to add Brackets support to Jupyter, so from now on you can use Jupyter’s qtconsole and Jupyter’s notebooks with Python Brackets.
To install you can do
pip install ibpykernel
and after install is finished
python -m ibpykernel install --user
and to use it with notebook
jupyter notebook
and it’s available in create file menu
You can view this project on PyPI or on Github.


CheckStyle Audit |
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| warning | Variable 'sellIn' must be private and have accessor methods. | 25 |
| warning | Variable 'quality' must be private and have accessor methods. | 34 |
| warning | 'name' hides a field. | 47 |
| warning | 'sellIn' hides a field. | 47 |
| warning | 'quality' hides a field. | 47 |
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| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
java.lang.Object coins.mdf.DeclareLocalVariables
Declaration of the local variables.
| Field Summary | |
(package private) Var |
allFinishVar
The variable `_MDF_ALL_FINISH' |
(package private) Var |
alreadyPut
The variable `_MDF_ALREADY_PUT' |
(package private) Var |
curStat
The variable `_MDF_CURRENT_STATUS' |
(package private) Var |
dataAccessCond
The variable `_MDF_ACCESS' |
(package private) Var |
execCond
The variable `_MDF_EXEC' |
(package private) Var |
finishCondition
The variable `_MDF_FINISH_COND' |
(package private) Var |
getPos
The variable `_MDF_GET_POS' |
(package private) Var |
nonExecCond
The variable `_MDF_NON_EXEC' |
(package private) Var |
ompLock
The variable `_MDF_OMP_LOCK' |
(package private) Var |
putPos
The variable `_MDF_PUT_POS' |
(package private) Var |
readyQueue
The variable `_MDF_READY_QUEUE' |
(package private) Var |
returnStatus
The variable `_mdf_return_status' |
static int |
THR
The threshold of debug output |
| Constructor Summary | |
(package private) |
DeclareLocalVariables(MdfEnvironment env,
MacroFlowGraph mfg)
Constructor |
| Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Field Detail |
public static final int THR
final Var putPos
final Var getPos
final Var allFinishVar
final Var execCond
final Var nonExecCond
final Var dataAccessCond
final Var curStat
final Var finishCondition
final Var readyQueue
final Var alreadyPut
final Var returnStatus
final Var ompLock
| Constructor Detail |
DeclareLocalVariables(MdfEnvironment env, MacroFlowGraph mfg)
env
- The environment of the MDF modulemfg
- The current macro flow graph
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Obtains critical values for the group and continuous sequential MaxSPRT test with Binomial data, using a Wald type upper boundary, which is flat with respect to the likelihood ratio function, and with a pre-specified upper limit on the sample size.
It is often not possible to select a critical value that corresponds to the exact alpha specified. Instead, this function will select the least conservative critical value having an alpha below the one specified, so the sequential analysis is conservative.
This function is a re-implementation of the CV.Binomial
function in the Sequential
package, using Monte-Carlo.
computeCvBinomial( groupSizes, z, minimumEvents = 1, alpha = 0.05, sampleSize = 1e+06 )
| groupSizes | Vector containing the expected number of events under H0 for each test. |
|---|---|
| z | For a matched case-control analysis, z is the number of controls matched to each case under the null hypothesis. For a self-controlled analysis, z is the control time divided by the time at risk. |
| minimumEvents | The minimum number of events needed before the null hypothesis can be rejected. |
| alpha | The significance level, or the type 1 error probability, which is the probability of rejecting the null hypothesis when it is true. |
| sampleSize | Sample size for the Monte-Carlo simulations. |
The computed critical value. The 'alpha' attribute of the result indicates the selected alpha.
#>#> [1] 3.064954 #> attr(,"alpha") #> [1] 0.049317


--- layout: page title: RFGeeks subtitle: A place about engineering, flying, travels, radios and just life. bigimg: - "/img/banner/lilu_bench.jpg" : "Lilu sleeping on the workbench" - "/img/banner/flying_FF.jpg" : "Flying near Fergus Falls, MN" - "/img/banner/rpi_adsb.jpg" : "Raspberry Pi ADS-B Receiver" - "/img/banner/howehall_ant.jpg" : "Antennas on Howe Hall - Ames, IA" - "/img/banner/bigben.JPG" : "Big Ben - London, UK" - "/img/banner/howehall_winter.JPG" : "Howe Hall - Ames, IA" - "/img/banner/cy_space.JPG" : "Cy at 70,000 feet" - "/img/banner/reiman.jpg" : "Reiman Gardens - Ames, IA" - "/img/banner/flying_az.JPG" : "Flying to Sedona, AZ" - "/img/banner/elcaptain.JPG" : "El Capitan - Yosemite National Park, CA" - "/img/banner/abc_computer.jpg" : "ISU ABC Computer at Computer History Museum - Mountain View, CA" - "/img/banner/japan_lego.jpg" : "Nano Blocks - Japan" - "/img/banner/bvi.jpg" : "British Virgin Islands" - "/img/banner/virgin_island.jpg" : "U.S. Virgin Islands" - "/img/banner/piper.jpg" : "Piper PA-28-180 flying near Jefferson, IA" - "/img/banner/boston.jpg" : "Boston, MA" - "/img/banner/cancun.JPG" : "Cancun, Mexico" - "/img/banner/madison.JPG" : "Covered Bridge - Madison County IA" - "/img/banner/bunratty.jpg" : "Bunratty, Ireland" - "/img/banner/japan_lantern.jpg" : "Kyoto, Japan" - "/img/banner/nova_scotia.jpg" : "Peggy's Cove, Nova Scotia, CA" - "/img/banner/habet.jpg" : "High Altitude Balloon Launch" - "/img/banner/roadtohana_waterfall.jpg" : "On the Road to Hana - Maui HI" - "/img/banner/maui_christmaseve.jpg" : "Christmas in Maui" - "/img/banner/lanaiair.jpg" : "Lanai Airport, HI" - "/img/banner/mauiflying.jpg" : "Flying around Maui, HI" - "/img/banner/kauai_monkseal.jpg" : "Monk Seal - Kauai, HI" - "/img/banner/kauai_pineappledump.jpg" : "Pineapple Dump Pier - Kauai, HI" - "/img/banner/kauai_kalalaulookout.jpg" : "Napali Coast - Kauai, HI" - "/img/banner/kauai_sunrise.jpg" : "Sunrise - Kauai, HI" - "/img/banner/cathedrals_erfurt.jpg" : "Twin Cathedral - Erfurt, Germany" - "/img/banner/deansvillage_scotland.jpg" : "Deans Village - Edinburgh, Scotland" - "/img/banner/edinburgh.jpg" : "Edinburgh - Scotland" - "/img/banner/erfurtbridge_germany.jpg" : "Krämerbrücke Bridge - Erfurt, Germany" - "/img/banner/glencoe_scotland.jpg" : "Glencoe - Scotland" - "/img/banner/wittenberg_germany.jpg" : "City Square - Wittenberg, Germany" - "/img/banner/maxwell_edinburgh.jpg" : "James Maxwell Statue - Edinburgh, Scotland" - "/img/banner/fll_2018.jpg" : "First Lego League (FLL) State Championships - Ames, IA" ---


My experience with writing in the digital realm starts in 2011 when having a WordPress blog for your every shower thought was considered a personality trait. Since then I have worked as a social media manager for small startups and big companies, however, coming up with clever wordplay or dad jokes are my specialty.
Bachelor of Biology • September 2017 - Present
Middle/High School • 2002 - 2014
Senior Digital Copywriter • April 2021 - Present
Copywriter • January 2020 - December 2020
Translator and Video Editor • September 2019 - December 2020
Junior Social Media Manager for "My wife's friends" • October 2017 - May 2019
Social Media Manager for "My Kitchen Rules Georgia" • March 2018 - August 2018
Social Media Manager • 2017 April - 2017 June
Freelance Journalist • 2017 January - 2017 February
Journalist • 2012 September - 2013 June
Duolingo Sage • Netflix Bingewatcher • glittery MUA


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1) Is it possible to cast spells while beeing in expertise mode?
Always, at most you'll drop out of Expertise mode as soon as the spell is cast if it was toggled so. _________________ Heavy metal Or no metal at all Whimps and posers Leave the hall!
thx _________________ K.M. aka Chillychill
"Y'a pire que ne pas pouvoir, y'a savoir qu'on peut et ne jamais tenter"


Summer is hottest among the four seasons. In this seasons, the days are longer than the nights. When summer arrives in the southern hemisphere, then it is winter in the northern hemisphere.
Summer is by far the best of the seasons. In summer there is so many things to do, boating, hiking, biking, camping, and of coure the most important part is those pasty white legs finally get some color.


--- layout: post status: publish published: true title: Hypothetical Expansion Draft - Episode 7.43 author: display_name: Corey Fineran login: Corey email<EMAIL_ADDRESS>url: '' author_login: Corey author_email<EMAIL_ADDRESS>wordpress_id: 11395 wordpress_url: http://ivyenvy.com/?p=11395 date: '2015-08-19 20:37:57 +0000' date_gmt: '2015-08-20 01:37:57 +0000' categories: - Podcast tags: [] comments: [] ---
There was only one Cubs game between our last episode and this one, so we answer some questions about Cubs players sent in by Laura. She asks us what Cubs player we think the Cardinals would swipe from the Cubs. We consulted a few Cardinals fans to get their input and their answer was not surprising.
Laura also brings up they hypothetical situation of an MLB expansion draft, similar to the 1997 draft when Tampa Bay and Arizona came into the league. Each existing MLB team was able to protect 15 players, organization-wide. We read Laura's list of the 15 players that she would protect and then share our own.
At the end of the episode, we play a song by Cubs fan, Katie Day. This is Katie's song "By the Lakeside" with words and Cubs images that may or may not make you tear up.


+++ title = "Matthias and Kanako" slug = "matthias-and-kanako" date = 2007-02-28T09:00:00+10:00 tags = ["eccentric-encounters", "fellow-travellers"] locations = ["mexico/merida"] draft = false summary = """
These crazy, married backpackers are two of the nicest and most streetwise people that I've travelled with so far. Both of them have spent over 10 years travelling to the most remote and out-of-the-way places on Earth. Matthias, a Frenchman, is an expert in cutting costs and in proving his favourite saying: "you have a lot to learn about the French". Kanako, a Japanese girl, is much more adventurous than your average Tokyo girl.
""" +++These crazy, married backpackers are two of the nicest and most streetwise people that I've travelled with so far. Both of them have spent over 10 years travelling to the most remote and out-of-the-way places on Earth. Matthias, a Frenchman, is an expert in cutting costs and in proving his favourite saying: "you have a lot to learn about the French". Kanako, a Japanese girl, is much more adventurous than your average Tokyo girl.
{{< galleryphoto "2007-02-28-09-00-00--matthias-the-swaggling-frenchman.jpg" >}}I spent today doing the Uxmal road trip with these and two more people.


Before Change
// logger.warning("Dumping to {}".format(""/Users/chaubold/Desktop/dump.h5""))
// vigra.impex.writeHDF5(reordered_feature_image[z,...], "data", "/Users/chaubold/Desktop/dump.h5")
result_slice = self._pytorch_net.forward([reordered_feature_image[z:z+1,...]])[0]
logger.info("Resulting slice {} has shape {}".format(z, result_slice.shape))
result[z, 0, ...] = result_slice
logger.info("Obtained a predicted block of shape {}".format(result.shape))
After Change
// vigra.impex.writeHDF5(reordered_feature_image[z,...], "data", "/Users/chaubold/Desktop/dump.h5")
// create batch of desired num slices. Multiple slices can be processed on multiple GPUs!
batch = [reordered_feature_image[zi:zi+1,...] for zi in range(z, min(z+self.BATCH_SIZE, reordered_feature_image.shape[0]))]
result_batch = self._pytorch_net.forward(batch)
logger.info("Resulting slices from {} to {} have shape {}".format(z, z+len(batch), result_batch[0].shape))


These are some of my brother's and my oldest MSX Basic programs (from the late 80s / early 90s) that survived! :-)
These programs were written for an MSX computer system which was powered by a 16 bit Z-80 microprocessor. It had 64 KBytes of RAM, half of which was taken by the MSX Basic interpreter and other system routines.
In those days we used to save our programs on cassette tapes. After MSX emulators started to emerge, I decided to give these programs new life. I wrote an Object Pascal program back in 2001 that did a frequency demodulation to the signals stored on the cassette tapes in order to extract the binary data and save it in CAS files which MSX emulators accept as a cassette modality.
- ASM001: Download | Run
- ASM002: Download | Run
- Draw Download | Run
- G&G001: Download | Run
- G&G002: Download | Run
- Ghost: Download | Run
- Gumy01: Download | Run
- Gumy02: Download | Run
- Haly1: Download | Run
- Haly2: Download | Run
- Hang: Download | Run
- Math1: Download | Run
- Math2: Download | Run
- Missile: Download | Run
- MMM: Download | Run
- Shabah1: Download | Run
- Shabah2: Download | Run
- Snale: Download | Run
- Tabi001: Download | Run
- Tabi002: Download | Run
- Untitled001: Download | Run
- Untitled002: Download | Run
- Untitled003: Download | Run


Safari IT Books Language Constructs Functional Programming Haskell Safari IT Books Programming Programming Programming Bryan O'Sullivan Donald Bruce Stewart John Goerzen O'Reilly Media, Inc. Real World Haskell, 1st Edition27.1. Basic NetworkingIn several earlier chapters of this book, we discussed services that
operate over a network. Two examples are client/server databases and web
services. When the need arises to devise a new protocol or to communicate
with a protocol that doesn't have an existing helper library in Haskell,
you'll need to use the lower-level networking tools in the Haskell
library. In this chapter, we will discuss these lower-level tools.
Network communication is a broad topic with entire books devoted to it. We
will show you how to use Haskell to apply the low-level network knowledge
you already have. Haskell's networking functions almost always correspond
directly to familiar C function calls. As most other languages also layer
on top of C, you should find this interface familiar.
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