|
Tree Options (1 of 1)
|
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Choose Tree options. This will insert a sample Tree into the document with the properties
set from the options below.
|
|
Id: |
The id is required.
The id to apply to the Tree. Must be unique.
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Css Class:
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The css class specifies the theme to apply to the Tree. Choose from the list of
included themes, or type the name of a custom theme into the field.
|
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Root Enabled:
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Choose true if you wish to have a special root style applied to the top root
node of the tree.
|
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Expanded:
|
If set to true, every node in the tree will be expanded to show its children.
If set to false, every node will be collapsed. Individual nodes can override this property
by setting their own expanded attributes.
|
|
Hover Highlight:
|
Specifies whether or not a hover class is added to nodes when they are hovered over.
|


Instead of a split RPC and writing heaps of code, I added this.
For example:
utxovalue = 30;
30% of the value of the staking utxo is added to the coinbase the same as fees,returning the remaining 70% to the address that staked.
utxovalue can be adjusted from any number 0 to 100 via the setstakingsplit RPC.
Can also be set with -splitperc= command line arg, or conf file.
0 means that it functions as it did previously, and you can use external scripts.
100 means it automates the pos64staker in the daemon (current default), combining the stake tx and the coinbase to an address. Either to -pubkey or a new address from the keystore.
Mining with some optimal % inbetween and without pubkey will over time create varied sized utxos, and evenly distribute them over many addresses and segids.
Does this sound useful for PoS64? I already made it and it works perfectly


Layout modules are more complex than utilities and are tied to markup structure. They are designed to be highly reusable and to inter-operate with other styles.
The utility-based grid allows a lot of flexibility in creating complex layouts.
Start by using a .clearfix
container.
Optionally use a .container
to set a max-width.
Adjust the container width with the --container-width
variable.
Add columns using the .col
and grid width .col-N
classes.
.col
floats elements left and sets box-sizing to border-box.
.col-N
sets width according to a 12 column grid.
The total number of columns in a row should add up to 12.
Use breakpoint-prefixed column utilities to change the grid at different screen widths. Each breakpoint applies to that screen width and up. Unprefixed styles apply to all screen widths.
Use padding and negative margin utilities to create gutters based on the white space scale. When using negative margin, be sure to compensate for the extra width created with a padded parent element or by using overflow hidden. Otherwise, horizontal scrolling may occur.
Nest whole grid structures within columns to created nested grids.
To reverse the order of columns, use the .col-right
class to float right
Use the .mx-auto
class to center columns within their containers.
The grid is also available as a standalone NPM module.
npm install basscss-grid
Use the table object to vertically center content.
These styles can be combined with grid width and white-space utilities for a wide range of layout options.
Apply padding to .table-cell
elements to contol spacing.
The flag object
can be emulated by adding .full-width
to one of the cells.
To add padding to the body, nest another div within the full-width cell.
Use the .table-fixed
extension to create equal-width cells.
Use breakpoint prefixes to keep table objects stacked at smaller screen sizes. This is useful for things like navigation.
The table object can be combined with grid width utilities to create vertically centered columns.
The table object is also available as a standalone NPM module.
npm install basscss-table-object


{% extends "layout.html" %} {% block content %} {% include "includes/v2/nav.html" %} Search for customer Enter a National Insurance Number {% endblock %}


TRON Will Flip Ethereum Next Year, Udi Wertheimer Calls
by Ali RazaBitcoin developer, known as Udi Wertheimer, recently announced his predictions for the future of Ethereum and Tron, stating his opinion that TRON will overcome Ethereum in about a year or so.
Ethereum is the second-largest cryptocurrency by market cap, and has been one of the most important crypto projects to ever be invented. It brought about the era of second generation blockchains, created the first ecosystem of decentralized applications (DApp), and became the first functional smart contracts platform.
TRON to flip Ethereum in a year
However, along the way, Ethereum saw a number of competitors emerge, and while most of them disappeared as years went by, some did stick around. TRON is today one of the project’s main competitors, and according to Bitcoin developer, Udi Wertheimer, TRON might even flip Ethereum sometime in 2020.
Naturally, this seems like a rather bold claim at first. However, Wertheimer came up with this prediction after listening to TRON CEO and founder, Justin Sun, discuss the new partnership between TRON and Poloniex.
Sun has mentioned many plans for the partnership between his project and the exchange, such as listings of additional assets, and more. However, he also stated that some additional partnerships — which he is not able to discuss just yet — would come in the near future, as well.
Wertheimer also states that TRON boasts faster development, better censorship resistance and greater transactions, than the largest altcoin.
Can Poloniex be trusted?
Justin Sun is quite well-known for his major announcements and raising hype, which is why many have taken his statements and plans with a grain of salt. In addition, a lot of people do not think much of Poloniex anymore, after the incident from over half a year ago, when Poloniex supposedly took 1800 BTC from its customers and did not pay them back, as some were complaining.
Others also noted that the exchange is not addressing their issues and that it is not to be trusted, which also implies that its partnership with TRON is equally untrustworthy.
Meanwhile, Sun addressed his followers, encouraging them to use Poloniex and help the exchange expand its business. He praises it as the first exchange that allowed the crypto community to buy coins like ETH or TRX, which is partially a reason why it has his support.
As for the future, Sun has announced that Poloniex will start offering more TRC-10 and TRC-20 coins listed, announcing big things to come. Plans like these are what makes Wertheimer believe that TRON will overcome Ethereum in the next year.
Image via Shutterstock: Twitter @UDIWERTHEIMER @nejelnejel @spacecitychan
The Rundown


We help you find your Dream House..
We help you find your Dream Office..
We help you find your Office Space..
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Experienced Event Coordinator with a demonstrated history of working in the higher education industry. Skilled in Python (Programming Language), C++, Communication, Presentation Skills, and Public Speaking. Strong operations professional with a B.Tech focused in Computer Science from Hemvati Nandan Bahuguna Garhwal University ( A Central University ).
Real programmers don't comment their code. If it was hard to write, it should be hard to understand.
One of the best parts of communication is being a good listener, understanding the need of client to help them expand their Web-enterprise is my speciality.


Navs available in this framework have shared markup, starting with the base .nav
class, as well as shared states. Swap modifier classes to switch between each style.
Note the .tabs
class requires the .nav
base class.
For tabs with tabbable areas, you must use the tabs JavaScript plugin.
Take that same HTML, but use .pills
instead:
Pills are also vertically stackable. Just add .stacked
.
Easily make tabs or pills equal widths of their parent at screens wider than 768px with .justified
. On smaller screens, the nav links are stacked.
As of v7.0.1, Safari exhibits a bug in which resizing your browser horizontally causes rendering errors in the justified nav that are cleared upon refreshing.
For any nav component (tabs or pills), add .disabled
for gray links and no hover effects.
This class will only change the <a>
's appearance, not its functionality. Use custom JavaScript to disable links here.
Flip the order of the HTML and add a class to put tabs on the bottom.
I'm in Section A.
Howdy, I'm in Section B.
Hello there, this is Section C.
I'm in Section A.
Howdy, I'm in Section B.
Hello there, this is Section C.
Swap the class to put tabs on the left.
I'm in Section A.
Howdy, I'm in Section B.
Hello there, this is Section C.
Swap the class to put tabs on the right.
I'm in Section A.
Howdy, I'm in Section B.
Hello there, this is Section C.
Add dropdown menus with a little extra HTML and the dropdowns JavaScript plugin.
This simple sub nav is great for moving between different states of a page, and they're also handy for filters like these.
{% highlight html %} {% endhighlight %}


A modulator is a collection of zero or more oscillators and zero or more submodulators. Modulators are used to play single tones.
Modulators mostly exist to be composed into Synthesizers. However, they are still useful on their own if you need more individual control over sounds.
Modulators can implement any number of submodulators, which inherit the highest ancestor's frequency, and play and stop when it does.


MITOSOL- mitomycin
Mobius Therapeutics LLC
HIGHLIGHTS OF PRESCRIBING INFORMATIONThese highlights do not include all the information needed to use Mitosol® (mitomycin for solution) safely and effectively. See full prescribing information for Mitosol® (mitomycin for solution).
Mitosol® (mitomycin for solution) Initial U.S. Approval: 1974 INDICATIONS AND USAGEMitosol® is an antimetabolite indicated as an adjunct to ab externo glaucoma surgery. (1) DOSAGE AND ADMINISTRATIONMitosol® is intended for topical application to the surgical site of glaucoma filtration surgery. It is not intended for intraocular administration. (2)
DOSAGE FORMS AND STRENGTHSEach vial contains a sterile lyophilized mixture of 0.2 mg mitomycin and 0.4 mg mannitol; when reconstituted with Sterile Water for Injection, the solution contains 0.2 mg/mL mitomycin. (3) CONTRAINDICATIONSWARNINGS AND PRECAUTIONS
ADVERSE REACTIONSThe most frequent adverse reactions to Mitosol® occur locally and include hypotony, hypotony maculopathy, blebitis, endophthalmitis, vascular reactions, corneal reactions, and cataract. (6.1) To report SUSPECTED ADVERSE REACTIONS, contact Mobius Therapeutics LLC at 1-877-393-6486 or FDA at 1-800-FDA-1088 or www.fda.gov/medwatch See 17 for PATIENT COUNSELING INFORMATION and FDA-approved patient labeling. Revised: 1/2012 |
Mitosol® is an antimetabolite indicated for use as an adjunct to ab externo glaucoma surgery.
Mitosol® is intended for topical application to the surgical site of glaucoma filtration surgery. It is not intended for intraocular administration. If intraocular administration occurs, cell death leading to corneal infarction, retinal infarction, and ciliary body atrophy may result.
Each vial of Mitosol® contains 0.2 mg of mitomycin and mannitol in a 1:2 concentration ratio. To reconstitute, add 1 ml_ of Sterile Water for Injection, then shake to dissolve. If product does not dissolve immediately, allow to stand at room temperature until the product dissolves into solution.
Sponges provided within the Mitosol® Kit should be fully saturated with the entire reconstituted contents in the manner prescribed in the Instructions for Use. A treatment area approximating 10mm x 6mm +/-2mm should be treated with the Mitosol®. Apply fully saturated sponges equally to the treatment area, in a single layer, with the use of a surgical forceps. Keep the sponges on the treatment area for two (2) minutes, then remove and return to the Mitosol® Tray for defined disposal in the Chemotherapy Waste Bag provided.
Lyophilized Mitosol® stored at controlled room temperature (i.e., 20 - 25°C or 68° - 77° F) is stable for the shelf life indicated on the package. Avoid excessive heat. Protect from light.
Reconstituted with Sterile Water for Injection at a concentration of 0.2 mg/ml, mitomycin is stable for one (1) hour at room temperature.
Mitosol® is a sterile lyophilized mixture of mitomycin and mannitol, which, when reconstituted with Sterile Water for Injection, provides a solution for application in glaucoma filtration surgery. Mitosol® is supplied in vials containing 0.2 mg of mitomycin. Each vial also contains mannitol 0.4 mg, at a 1:2 ratio of mitomycin to mannitol. Each mL of reconstituted solution contains 0.2 mg mitomycin and has a pH between 5.0 and 8.0.
Mitosol® is contraindicated in patients that have demonstrated a hypersensitivity to mitomycin in the past.
Mitosol® may cause fetal harm when administered to a pregnant woman. Mitomycin administered parenterally has been shown to be teratogenic in mice and rats when given at doses equivalent to the usual human intravenous dose. Mitosol® is contraindicated in women who are or may become pregnant during therapy. If this drug is used during pregnancy, or if the patient becomes pregnant while taking this drug, the patient should be apprised of the potential hazard to the fetus.
Mitomycin is cytotoxic. Use of mitomycin in concentrations higher than 0.2 mg/mL or use for longer than 2 minutes may lead to unintended corneal and/or scleral damage including thinning or perforation. Direct contact with the corneal endothelium will result in cell death.
The most frequent adverse reactions to Mitosol® occur locally, as an extension of the pharmacological activity of the drug. These reactions include:
Blebitis: bleb ulceration, chronic bleb leak, encapsulated/cystic bleb, bleb-related infection, wound dehiscence, conjunctivial necrosis, thin-walled bleb
Cornea: corneal endothelial damage, epithelial defect, anterior synechiae, superficial punctuate keratitis, Descemet's detachment, induced astigmatism
Endophthalmitis
Hypotony: choroidal reactions (choroidal detachment, choroidal effusion, serous choroidal detachment, suprachoroidal hemorrhage, hypotony maculopathy, presence of supraciliochoroidal fluid, hypoechogenic suprachoroidal effusion)
Inflammation: iritis, fibrin reaction
Lens: cataract development, cataract progression, capsule opacification, capsular constriction and/or capsulotomy rupture, posterior synechiae
Retina: retinal pigment epithelial tear, retinal detachment (serous and rhegatogenous)
Scleritis: wound dehiscence
Vascular: hyphema, central retinal vein occlusion, hemiretinal vein occlusion, retinal hemorrhage, vitreal hemorrhage and blood clot, subconjunctival hemorrhage, disk hemorrhage
Additional Reactions: macular edema, sclera thinning or ulceration, intraocular lens capture, disk swelling, malignant glaucoma, lacrimal drainage system obstruction, ciliary block, corneal vascularization, visual acuity decrease, cystic conjunctival degeneration, upper eyelid retraction, dislocated implants, severe loss of vision.
It is not known whether this drug is excreted in human milk. Because many drugs are excreted in human milk, and because of the potential for serious adverse reactions in nursing infants from Mitosol®, a decision should be made whether to discontinue nursing or to discontinue the drug, taking into account the importance of the drug to the mother. It is recommended that women receiving Mitosol® not breast feed because of the potential for serious adverse reactions in nursing infants.
Mitomycin is an antibiotic isolated from the broth of Streptomyces verticillus Yingtanensis which has been shown to have antimetabolic activity.
Mitomycin is a blue-violet crystalline powder with the molecular formula of C15H18N405 and a molecular weight of 334.33. Its chemical name is 7-amino-9α-methoxymitosane and it has the following structural formula:
Mitosol® is a sterile lyophiliized mixture of mitomycin and mannitol, which, when reconstituted with Sterile Water for Injection, provides a solution for application in glaucoma filtration surgery. Mitosol® is supplied in vials containing 0.2 mg of mitomycin. Each vial also contains mannitol 0.4 mg, at a 1:2 ratio of mitomycin to mannitol. Each mL of reconstituted solution contains 0.2 mg mitomycin and has a pH between 5.0 and 8.0.
Mitosol® inhibits the synthesis of deoxyribonucleic acid (DNA). The guanine and cytosine content correlates with the degree of mitomycin-induced cross-linking. Cellular RNA and protein synthesis may also be suppressed.
Absorption
The systemic exposure of mitomycin following ocular administration of Mitosol® in humans is unknown. Based on a comparison of the proposed dose of up to 0.2 mg to intravenous (IV) doses of mitomycin used clinically for treatment of oncologic indications (up to 20 mg/m2), systemic concentrations in humans upon ocular administration are expected to be multiple orders of magnitude lower than those achieved by IV administration.
Metabolism
In humans, mitomycin is cleared from ophthalmic tissue after intraoperative topical application and irrigation, as metabolism occurs in other affected tissues. Systemic clearance is affected primarily by metabolism in the liver. The rate of clearance is inversely proportional to the maximal serum concentration because of saturation of the degradative pathways.
Adequate long-term studies in animals to evaluate carcinogenic potential have not been conducted with Mitosol®. Intravenous administration of mitomycin has been found to be carcinogenic in rats and mice. At doses approximating the recommended clinical injectable dose in humans, mitomycin produces a greater than 100 percent increase in tumor incidence in male Sprague-Dawley rats, and a greater than 50 percent increase in tumor incidence in female Swiss mice. The effect of Mitosol® on fertility is unknown.
In placebo-controlled studies reported in the medical literature, mitomycin reduced intraocular pressure (IOP) by 3 mmHg in patients with open-angle glaucoma when used as an adjunct to ab externo glaucoma surgery by Month 12. In studies with a historical control reported in the medical literature, mitomycin reduced intraocular pressure (IOP) by 5 mmHg in patients with open-angle glaucoma when used as an adjunct to ab externo glaucoma surgery by Month 12.
Mitosol® (mitomycin for solution) is available in a kit containing:
One Vial containing 0.2 mg mitomycin
One 1 mL syringe (Sterile Water For Injection) with Connector
One Plunger Rod
One Vial Adapter with Spike
One 1 mLTB Syringe, Luer Lock
One Sponge Container
Six 3 mm Absorbent Sponges
Six 6 mm Absorbent Sponges
Six Half Moon Sponges
One Instrument Wedge Sponge
One Alcohol Prep Pad, Sterile
One Chemotherapy Waste Bag
Three kits are supplied in each carton (NDC49771-002-03).
Manufactured for:
Mobius Therapeutics, LLC
4041 Forest Park Avenue
St. Louis, MO 63108
Mitosol®
(mitomycin for solution)
0.2 mg/vial
Kit for Ophthalmic Use
Read INSTRUCTIONS FOR USE Before Proceeding
Instructions for Use
A. Black Outer Pack (Figure A)
|
Figure A: Black Outer Pack |
B. STERILE Inner Tray (Figure B)
This tray and its contents are STERILE. |
Figure B: Sterile Inner Tray |
1. Getting Started
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|
|
|
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3. Preparing sponges
|
|
|
|
|
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4. Using Mitosol®
|
DISPOSE OF CHEMOTHERAPY WASTE BAG AND ITS CONTENTS AS CHEMOTHERAPY WASTE
MOB0022 Rev. D
Principal Display Panel – Carton Label
Mitosol®
(mitomycin for solution)
0.2 mg/vial
Kit for Ophthalmic Use
Manufactured for:
Mobius Therapeutics, LLC
4041 Forest Park Avenue
St. Louis, MO 63108 USA
+1<PHONE_NUMBER>
1-877-EYE-MITO (1-877-393-6486)
Rx ONLY
US Pat #: 7,806,265;
other US and Int'l Patents Pending
©2010 Mobius Therapeutics, LLC
Mobius
therapeutics™
MOB0020 Rev. C
NDC #49771-002-03
Re-Order #MOB.2
Contains 3 Kits
Each Mitosol® Kit Contains:
One Chemotherapy Waste Bag
One Instructions for Use
One Package Insert
One Inner Tray
Inner Tray Contains:
One Vial Containing 0.2 mg mitomycin
One 1 mL Syringe (Sterile Water for Injection) with Connector
One Plunger Rod
One Vial Adaptor with Spike
One 1 mL TB Syringe, Luer Lock
One Sponge Container
Six 3 mm Absorbent Sponges
Six 6 mm Absorbent Sponges
Six Half Moon Sponges
One Instrument Wedge Sponge
One Alcohol Prep Pad, Sterile
Contents STERILE in unopened undamaged package.
Storage: Store kits at 20° - 25° C (68° - 77° F). Protect from light.
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mitomycin kit | ||||||||||||||||||||
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| Labeler - Mobius Therapeutics LLC (805642118) |
| Establishment | |||
| Name | Address | ID/FEI | Business Operations |
|---|---|---|---|
| Mobius Therapeutics LLC | 805642118 | MANUFACTURE(49771-002) |


My iOS Toolbox
11 Oct 2013An Obligatory post (so it seems) for iOS developers to list all the tools they use (and sometmes dont use) to make thier development life easier. Heres mine, the ones I actually use...
Designing
Sketch -- Sketch is amazing, Designed with Mac/iOS in mind it takes designing for iOS to another level. Sketch really reminds me of MX Fireworks -- you know, before Adobe got thier hands on it. Simple yet powerful; vector editing, easy exporting. It will do all you need.
Pixelmator -- For things non vector, Pixelmator is a great alternative to Photoshop and to Gimp.
The HIG -- Apple's Human Interface Guideline. This should be printed and on your desk at all times.
Developing
Xcode -- Apple's flagship Objective-C development product. Xcode and I have a love hate relationship but I always come back to Xcode.
App Code -- Jetbrains ultimate-all-in-one IDE for Objective-C development and it really is good. It provides features like; a refactorer that works, code completion that works, linting, automatic imports and import optimsation. It does however; lack an Interface Builder which for me, a dealbreaker.
Sublime Text 2 -- No, I do not write Objective-c in sublime but part of my process is making little scripts in ruby to make my integrating and deploying tasks automated.
Cocoapods -- The Dependency manager for Objective-C. NO more linker errors, no more importing projects or dealing with submodules. Enough said.
Testing
Kiwi -- This was almost OCUnit but I have switch whole heartedly to Kiwi and BDD. It's not just about changing frameworks, its about changing the way you test.
Zucchini -- Acceptance testing, define flows, detect UI discrepancies and Integrate with CI.
Integrating
xctool -- Released by Facebook, xctool provides a nicer interface than xcodebuild with better test integration and reporting built in.
xcrun -- Ships with Xcode, generate .ipa from .app with code signing, all you need really.
Testflight -- Lucklily I had an account before apple's aquistion of testflight. Upload builds, add release notes, notify people.
A CI Server -- Choose one, They all do basically the same thing. Define a workflow, add build steps and go, I use Jenkins.
note
Although this did not make the list because it is still under beta, Github's Atom editor has quickly became a replacement for Sublime text 2.


Sorrento F11L - Battery Life
Document Id: KBDOC-00263
Created: 2010-04-10
Updated: 2010-04-14
Sorrento F11L Battery Life
Just like any other electric device, the Sorrento F11L must be charged. If it seems to be discharging quickly, you are using the phone too much.
Charging the phone
- Rub a baloon on your head and discharge the charge on the phone.
- Plug in to charger.
- Use the Raiden Lightning move to charge the phone instantaneously.
Tags: mobilephone, battery life, under, together, themselves


{% extends "comparison_page.html" %} {% load wagtailcore_tags %} {% block table_content %} {% include "partials/compare_committees_over_congresses_table.html" with committees=house_committees title="House of Representatives"%} {% include "partials/compare_committees_over_congresses_table.html" with committees=senate_committees title="Senate"%}


A handy tip from lifehacker:
Google Reader seems pretty neat, but it's always bugged me that using the "v" key to view a link opens that link in a new tab. I usually like to browse all feed items, open interesting links in the background, and then view the opened links [all at once].
In order to force all links that open in a new window to load in a background tab, type about:config in the URL bar and change browser.tabs.loadDivertedInBackground to true. While you're at it, be sure to grab some other Firefox tweaks, too. Thanks, J! — Kyle Pott
First thing I needed after installing a fresh firefox. Firefox 3 Alpha seems stable enough for my purpose, and uses lesser RAM than Firefox 2.


V
Name
Kind
Description
v
relation
vecUp
attribute
VisionSynthesis
class view
VsFactory
class
VsFactory_2
class
VsXmlEntry
class
VsXmlEntry
operation
VsXmlEntry_2
class
VsXmlEntry_2
operation


--- creation_epoch:<PHONE_NUMBER> lastmod_epoch:<PHONE_NUMBER> categories: ['Tech Tricks'] title: Grub 2 for booting ISOs on USB disks --- I like being able to boot various Linux distros from USB sticks. It makes it easy to update to newer versions, is faster, and doesn't require using up DVD-R discs. Previously this required extracting the ISO contents to a USB disk and setting up special boot loaders. I have found a new way using grub2 to just copy the unmodified ISO file to the USB stick without extraction.
menuentry "Ubuntu 11.10 Desktop x86 (toram)" { set isofile="/boot/isos/ubuntu-11.10-desktop-i386.iso" loopback loop $isofile linux (loop)/casper/vmlinuz boot=casper toram iso-scan/filename=$isofile quiet splash noprompt -- initrd (loop)/casper/initrd.lz } menuentry "Ubuntu 11.10 Desktop AMD64" { set isofile="/boot/isos/ubuntu-11.10-desktop-amd64.iso" loopback loop $isofile linux (loop)/casper/vmlinuz boot=casper iso-scan/filename=$isofile quiet splash noprompt -- initrd (loop)/casper/initrd.lz } set isofilename="systemrescuecd-x86-2.4.1.iso" # Because System Rescue CD's boot loader adds a / when searching as it really likes it in the root of the drive set isorelativepath="boot/isos/$isofilename" set isofullpathname="/$isorelativepath" menuentry "systemrescuecd-x86-2.4.1 (docache setkmap=us)" { loopback loop $isofullpathname linux (loop)/isolinux/rescuecd isoloop=$isorelativepath docache setkmap=us initrd (loop)/isolinux/initram.igz } menuentry "systemrescuecd-x86-2.4.1 x64 Mode (docache setkmap=us)" { loopback loop $isofullpathname linux (loop)/isolinux/rescue64 isoloop=$isorelativepath docache setkmap=us initrd (loop)/isolinux/initram.igz } menuentry "System Rescue CD MemTest86+" { loopback loop $isofullpathname linux16 (loop)/bootdisk/memtestp } # Not working yet, not sure how to get multiple initramfs working in grub2 like grub1 # See http://savannah.gnu.org/bugs/?35238 which has a pushed fix not yet released #menuentry "System Rescue CD NTPASSWD" { # loopback loop $isofullpathname # # linux (loop)/ntpasswd/vmlinuz rw # initrd (loop)/ntpasswd/initrd.cgz # initrd (loop)/ntpasswd/scsi.cgz #} #


1.2.8 khgqx7ua
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On this page we explain how do you can use our restservice in your Webshop.
In the following part you can test our Webservice. Enter for example Robert Mugabe for an invalid example and hopefully your name for an valid example ;-)
Is User {{firstName}} {{lastName}} allowed ?
max. Score {{response.getMaxScore()}}
max. Score {{response.getMaxScore()}}


Abstract: Plasma is a proposed framework for incentivized and enforced execution of smart contracts which is scalable to a significant amount of state updates per second (potentially billions) enabling the blockchain to be able to represent a significant amount of decentralized financial applications worldwide. These smart contracts are incentivized to continue operation autonomously via network transaction fees, which is ultimately reliant upon the underlying blockchain (e.g. Ethereum) to enforce transactional state transitions.
We propose a method for decentralized autonomous applications to scale to process not only financial activity, but also construct economic incentives for globally persistent data services, which may produce an alternative to centralized server farms.
Plasma is composed of two key parts of the design: Reframing all blockchain computation into a set of MapReduce functions, and an optional method to do Proof-of-Stake token bonding on top of existing blockchains with the understanding that the Nakamoto Consensus incentives discourage block withholding.
This construction is achieved by composing smart contracts on the main blockchain using fraud proofs whereby state transitions can be enforced on a parent blockchain. We compose blockchains into a tree hierarchy, and treat each as an individual branch blockchain with enforced blockchain history and MapReducable computation committed into merkle proofs. By framing one's ledger entry into a child blockchain which is enforced by the parent chain, one can enable incredible scale with minimized trust (presuming root blockchain availability and correctness).
The greatest complexity around global enforcement of non-global data revolves around data availability and block withholding attacks, Plasma has mitigations for this issue by allowing for exiting faulty chains while also creating mechanisms to incentivize and enforce continued correct execution of data.
As only merkleized commitments are broadcast periodically to the root blockchain (i.e. Ethereum) during non-faulty states, this can allow for incredibly scalable, low cost transactions and computation. Plasma enables persistently operating decentralized applications at high scale.
Draft is in-progress and may be frequently updated in the next week(s).


About Minergate
Minergate is a mining pool created by a group of cryptocoin enthusiasts.
It is the first pool which provides service for merged mining. This means that while mining on our pool you can mine different coins simultaniously without decrease of hashrate for major coin


Arduino Lesson
Goals ordered by lesson
- Install Arduino development environment and configuration
- Program technical ( coding style )
- General Purpose Input and Output ( GPIO )
- LCD Module Control ( text mode )
- Communication to PC ( via Arduino IDE )
- Communication via Bluetooth
- Communication to other Systems ( UART, SPI, I2C )
- Analog and Digital conversion ( read variable voltage )
- Motor control ( DC motor with H bridge )
- Motor control ( Servo motor - PWM )
Textbook
Reference Textbook
- 超圖解 Arduino 互動設計入門
- ISBN<PHONE_NUMBER>841
- 作者： 趙英傑
- 出版社：旗標
- 出版日期：2013/04/03
- 語言：繁體中文
- 定價：680元
- Arduino Cookbook
- By: Michael Margolis
- Publisher: O’Reilly Media
- Formats: Print, Ebook, Safari Books Online
- Print: March 2011
- Ebook: 2011
- Page: 662
- Print ISBN: 978-0-596-80247-9 or ISBN 10: 0-596-80247-1
- Ebook ISBN: 978-1-4493-0310-5 or ISBN 10: 1-4493-0310-2
Experiment Tools
- Arduino uno
- Variable Resistor
- LCD Module ( 1602 )
- Bluetooth Module
- DC Motor
- H Bridge IC
- Servo Motor
- ( PS. detail in the share document )
- https://docs.google.com/spreadsheets/d/1Y1PTgxhtIhFZrencz5vZvdUB5lhoaTXEYblf2OkUYG0/edit?usp=sharing
Lecture Design
Lecture 01. Introducing Arduino
- What’s Arduino?
- What’s the different between Software, Firmware and Hardware
- The world of Open Source
- License
- How do I get started with Arduino?
- Why does it run like that?
Lecture 02. Programming Coding
- What’s Program?
- How to Read and Write?
- Programming Style
- Add your information to program
Lecture 03. Basic Input and Output
- What’s GPIO?
- How to output 1s and 0s?
- How to read an input digital signal?
Lecture 04. LCD
- What’s an LCD?
- How does it works?
- Display a string on it
Lecture 05. Communication
- Why does Arduino need communication?
- What’s UART?
- Communication to PC with example
- What’s SPI?
- What’s I2C?
- What’s Bluetooth?
- Send data to android via Bluetooth
Lecture 06. Analog and Digital
- What’s the difference between analog and digital
- What’s Photo-resistor ( Light dependent resistor )
- Read analog signal and convert it into digital data
- What’s PWM?
- How to generate PWM signals?
- Read analog signal and output in the form of PWM
Lecture 07. Motor control
- What’s DC Motor?
- How does it work?
- Drive DC motor with H bridge
- What’s Servo Motor?
- How to control it? ( PWM )
Projects ( design for three weeks activity )
- 自走車 or 遙控車
- 機械手臂
- 指針式時鐘
- 連線遊戲機


MOVIE FLIX
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package lexer
- Alphabetic
- Public
- All
Type Members
- case class Field[T](value: T) extends Lexeme[T] with Product with Serializable
-
class
GenericCSVLexer[T] extends Lexer[T] with Iterator[Lexeme[T]]
Generic lexer consuming tokens from tokenizer and build lexemes.
Generic lexer consuming tokens from tokenizer and build lexemes.
Lexer using final state automate when considering what lexeme it should build from token's stream
Slightly simplified graph of FSA used in lexer
Does not include escaped block and escaped quoted block states which are essentially capture the next token and convert it into block before returning to block or quoted block states
The main method is the tryFetch which is feeding the tokens into FSA and calling itself recursively until at least one lexeme is found, or end of file or FinalState is reached.
Some threadsafety and synchronization is attempted but not guaranteed
- T
type contained in tokens and to be produced in fields
-
sealed
trait
Lexeme[+T] extends AnyRef
Represents Lexeme in CSV file.
Represents Lexeme in CSV file. As quoting and escaping is syntactic sugar they are not represented as Lexeme
Lexer is supposed to take them into account when building fields and breaks. For examples of how tokens are translated into lexemes please look at SimpleLexerTest
- T
data stored in fields
-
trait
Lexer[T] extends AnyRef
Any iterator providing lexemes are lexer
-
class
LexerException extends RuntimeException
Thrown when lexer ended up in the unexpected state
-
class
MinimalMemoryLexer extends GenericCSVLexer[ByteSeq]
Experimental lexer operating on ua.kyiv.tinedel.csvparser.ByteSeqtokenizer allowing to avoid keeping strings and storing only ByteRange to be able to read needed bytes later on
-
class
SimpleLexer extends GenericCSVLexer[String]
Simple lexer extending ua.kyiv.tinedel.csvparser.lexer.GenericCSVLexer and operating on string tokenizers providing string Lexemes
Value Members
- object FieldBreak extends Lexeme[Nothing] with Product with Serializable
- object MinimalMemoryLexer
- object RecordBreak extends Lexeme[Nothing] with Product with Serializable
-
object
SimpleLexer
Factory object producing SimpleLexers


8 references to _syncObject
System.Management.Automation (8)
utils\ObjectStream.cs (8)
1639
lock (
_syncObject
)
1687
lock (
_syncObject
)
1712
lock (
_syncObject
)
1734
lock (
_syncObject
)
1759
lock (
_syncObject
)
1785
lock (
_syncObject
)
1891
lock (
_syncObject
)
1952
lock (
_syncObject
)


PlaceIQ Branding
I joined PlaceIQ as the first full time designer, so needless to say the branding needed work. The CEO was very fond of the logo, so instead of fully rebanding I just updated the logo. My goal was to give it a friendlier, more modern look, and still keep the basic structure in place.
(original)
(updated)
Colors
The previous materials were scattered with every hue and shade of purple and gray, sprinkled with neon green, a color already in use by a competitor. When deciding colors, I originally played around with softer, less vivid purples, but decided that a strong unique purple would be memorable and stand out in the market. It was also apparent that with so many detailed maps, diagrams, and charts, having a nice selection of supporting colors would be necessary.
(primary)
(supporting)
Style Guide
I worked in collaboration with my team to develop the style guide for PlaceIQ. I wanted the end result to be a comprehensive brand book that would function as a strong reference when building materials, and ultimately keep materials consistant in an ever changing company.
Type
Being a B2B company, the primary marketing material at first, was PowerPoint slides that were often emailed. The only way to preseve the appearance when sending these materials would be to use web safe fonts. However, I still wanted to have the ability to use more refined fonts that would work for future materials. So after deciding on the web fonts, I selected similar style fonts for print.
Photography
Due to small budgets and an ever evolving business, there was a heavy reliance on stock imagery. However, we needed to ensure our materials would look consistant without looking generic. I worked to hand select and refine the photos we were using, and develop the overall photo style.


---
title: Pac-Man
period: 2014
genre: Multiplayer Pac-Man
development: Uni. of Pretoria
categories: Games
---
Final year project with the requirement to make a multiplayer version of Pac-Man.
I implemented the game using Three.js on the client and a Node.js server.
I used WebSockets to allow seamlessly playing over a network, with each player sending a small JSON object containing their current movements, and the server broadcasting to keep everyone in sync. The game pits 2 or more
Pac-Man players against 4 ghost players, and adds some skills to balance out the scales.


Home
About
Passion
My Music
__Studio Versions__
Bewan Martino
606-8205 Kyoto, Kyoto-Shi, Sakyoku Tanaka Kamiyangicho 16, Heights Kamo 313 Contact: 090-8053-7048
BewanM Music -All Rights Reserved-


Mongoose in the Wild
LearnBoost is a free online gradebook, lesson planner, attendance, and reporting application for Teachers, Parents, and Students.
Geeklist is an achievement-based social portfolio builder where all bad-ass code monkeys around the globe can communicate, brag, build their street cred and get found.
Storify lets you curate social networks to build social stories, bringing together media scattered across the Web into a coherent narrative.
Scotty App allows you to create data driven backends for your apps in minutes instead of weeks.
Bozuko is an exciting customer rewards program.

ClickDummy is a rapid mockup prototyping application for designers and dummies.
Call List helps you maintain a todo list for people you need to call.
Linkr is a service for saving links for reading later.
AtticTV is Music Television (MTV) for the web.
Lists is a service for saving links for reading later.
LocalResponse helps marketers respond to real-time consumer intent.
Select Vids is a collection of amazing, funny, and creative videos for you to discover.
ShareLatex is a real-time LaTeX collaboration tool.
cldfy delivers mail to your app.
nextdays let's you share plans with friends and discover what is happening around you.
The applications shown above are not listed in any specific order. To have your app added or removed please contact aaronheckmann@gmail.com.


Gatliff 50 km
Edenbridge ENG
Website: www.copsecroydon.co.uk/copse2007/gatliffmarathon.php
Race Winners
(32 runnings)
6:02:12 6:20:02 25 Nov 2007
4:44:17
6:04:13
26 Nov 2006
5:45:38
8:23:26
27 Nov 2005
5:19:05
6:41:09
28 Nov 2004
5:23:13
6:26:24
30 Nov 2003
5:19:15
7:02:56
2002
5:34:
7:04:
2001
5:54:
7:29:
2000
5:28:
7:39:
1999
5:30:
6:55:
1998
5:13:
7:24:
1997
5:20:
6:39:
1996
4:43:
6:23:
1995
4:43:
5:27:
1994
5:36:
7:48:
1993
4:55:
6:54:
1992
5:03:
6:14:
1991
4:35:
6:41:
1990
4:47:
5:40:
1989
4:57:
6:44:
1988
5:29:
8:30
1987
4:59:
7:11:
1986
5:21:
8:29:
1985
5:15:
8:25:
1984
6:02:
6:50:
Notes: 1984 was the inaugural year. The actual route varies from year to year but generally follows footpaths and
tracks.
29 Nov
2015
5:11:14
Keith MacIntosh (ENG)
6:28:22
Lisa Joanne (Barry) Walbridge-4
30 Nov
2014
5:42:13
David Wakeling-20
6:38:53
Lisa Joanne (Barry) Walbridge-3
24 Nov
2013
4:32:53
Keith Macintosh (GBR)
6:13:22
Edwina Sutton (GBR)
25 Nov
2012
6:02:54
Keith Macintosh (GBR)
7:16:43
Lisa Joanne (Barry) Walbridge-2
27 Nov
2011
5:16:04
David Wakeling-19
7:07:33
Janet Cobby (ENG)
28 Nov
2010
4:54:34
Mark Braley
6:25:25
Priscilla Brunnine
29 Nov
2009
5:21:41
Gary Vallance (ENG)
Lisa Joanne (Walbridge) Barry (ENG)
30 Nov
2008
5:46:06
David Wakeling-18
Zoe Thornton (GBR)
Fabrice Leistner (ENG)
Annabelle Stearns (ENG)
David Wakeling-17
Jo Kilkenny
David Wakeling-16
Sue Ashley-2
David Wakeling-15
Summer Govan
David Wakeling-14
Jackie Smith
David Wakeling-13
Alexandra Langridge
David Wakeling-12
Shirley Hume-4
David Wakeling-11
Lindsay Turner
David Wakeling-10
Shirley Hume-3
David Wakeling-9
Shirley Hume-2
David Wakeling-8
Shirley Hume
David Wakeling-7
Sue Ashley
David Wakeling-6
Clare Mathews
Brian Cammell + Graham Tucker
Julie Stoddart-2
David Wakeling-5
+ Chris Boakes-3
Julie Stoddart + Eileen Buckley
David Wakeling-4
+ Chris Boakes-2
Sandra Brown
David Wakeling-3
+ Chris Boakes + Peter Tremain
Janet Crockford
Dave Wakeling-2
Debbie Cooper-3
David Wakeling +
Barrie Prince
Wendy Spear-2
Keith Rolfe + Steve Fawcett
Debbie Cooper-2
Martyn Greaves-4
Wendy Spear
Martyn Greaves-3 + Nigel Robinson
Debbie Cooper
Martyn Greaves-2
Sue Boyman
Martyn Greaves
Pauline Shore
Most Wins
(1984-date)
Men
20
Dave Wakeling
1989-93,1995-2006,2008,2012,2014
Women
4
Shirley Hume
1997-99,2001
Lisa Joanne Barry-Walbridge (ENG)
2009,2012,2014-15
Prize Money
(ADR qualified runners)
No prize money information has been received for this race.
Race Time Bias
(sec/km)
Insufficient data to calculate the race time bias.
Competitive Level (1990-date)
Insufficient data to calculate the competitive level.
Last Updated on
20 Jan 2016
Contributor: Klaas Loonstra (50), Juraj Gasparovic (47)


UIRating
open class UIRating : UIView
extension UIRating: UIRatingDelegate
A customizable rating view.
-
Sets the amount of option to rate from.
Declaration
Swift
open var numberOfOptions: Int { get set }
-
Allows the selection of half ratings if set to true.
Declaration
Swift
open var allowHalfSelection: Bool { get set }
-
Sets the spacing between options.
Declaration
Swift
open var spacing: CGFloat { get set }
-
The delegate for UIRating.
Declaration
Swift
open var delegate: UIRatingDelegate?
-
Sets the icon to use for an empty rating.
Declaration
Swift
lazy open var emptyIcon: UIImage? { get set }
-
Sets the icon to use for a half rating.
Declaration
Swift
lazy open var halfFullIcon: UIImage? { get set }
-
Sets the icon to use for a full rating.
Declaration
Swift
lazy open var fullIcon: UIImage? { get set }
-
The default initializer for UIRating.
Declaration
Swift
override public init(frame: CGRect)
Parameters
frame
Sets the frame for the UIRating instance.
-
The required coder initializer for UIRating.
Declaration
Swift
public required init?(coder: NSCoder)
Parameters
coder
NSCoder.
-
Declaration
Swift
public func currentRating(rating: Double)


Visualising diffusion-limited aggregation in pure JS
What is diffusion-limited aggregation?
Diffusion-limited aggregation (DLA) is the process whereby particles undergoing a random walk due to Brownian motion cluster together to form aggregates of such particles.
Above we can see a DLA cluster grown from a copper sulfate solution in an electrodeposition cell.
Above we can see cluster grown by our algorithm.
Model
To visualise DLA in browser we need to agree to some model. Let’s assume that:
-
Each particle performs a random walk in our system.
-
When particle is next to a cluster it sticks to it.
-
We start with a simple seed cluster consisting of one particle in the center of the visualisation.
Model is dead simple. Let’s see how we can implement it and generate some pretty pictures.
Code
First we need to to create initial parameters and fill the input with them. We need to do it after the DOM is loaded:
window.onload = function () {
var initialParameters = { width : 800, height:800, particle_density:0.25, stopping_fraction:0.5};
document.getElementById("parameters").value = JSON.stringify(initialParameters);
};
We have four parameters:
-
width and height of our simulation
-
particle_density indicating how many particles will we used ( particle_density x width x height )
-
stopping_fraction as we need to specify some stopping condition for our simulation, we will stop when specified fraction of all particles will be part of the cluster
First we need to create some default colors we will use:
var background_color = [50,50,50]; // dark gray
var particle_color = [52,152,219]; // ligh blue
// colormap which converts value from the 0..1 range into a color
// it looks like a heatmap
function colormap(v) {
return [
255 * ((v <= 0.5) ? v * 2.0 : 1.0), // red
255 * ((v > 0.25) ? ((v < 0.75) ? (v - 0.25) * 2.0 : 1.0) : 0.0), // green
255 * ((v > 0.5) ? (v - 0.5) * 2.0 : 0.0) // blue
];
}
Next we need to create field where particles will be moving:
var CLUSTER_SIZE = 0;
function createField(width, height) {
var field = { width:width, height:height, field: new Uint32Array(width * height) };
field.field[Math.floor(width / 2) + Math.floor(height / 2) * width] = 1;
return field;
}
We will use a lot of typed arrays in our project. Elements that are part of the cluster will be have CLUSTER value.
Next we need to create particles and initialize their positions.
function resetParticle(particles, field, i) {
var x = Math.floor(Math.random() * field.width);
var y = Math.floor(Math.random() * field.height);
while(field[y*field.width+x]) {
x = Math.floor(Math.random() * field.width);
y = Math.floor(Math.random() * field.height);
}
particles.x[i] = x;
particles.y[i] = y;
}
function createParticles(field, count) {
var particles = {
count: count,
stuck: new Uint32Array(count),
x: new Uint16Array(count),
y: new Uint16Array(count),
};
var i = count;
while (i--)
resetParticle(particles, field, i);
return particles;
}
Reset function generates new position for the particle until it’s a position that is not occupied by any cluster. We create three arrays, one for storing x coordinates of the particles, one for storing y coordinates of the particles and storing for the flag indicating whether the particle is stuck in a cluster.
Then we need a function that will perform random walk:
function updateParticle(particles,field, i) {
var xmove = Math.random();
var ymove = Math.random();
var x = particles.x[i] + (xmove > 2/3 ? 1 : xmove > 1/3 ? 0 : -1);
var y = particles.y[i] + (ymove > 2/3 ? 1 : ymove > 1/3 ? 0 : -1);
if ( (x < 0) || (y < 0) || (x >= field.width) || (y >= field.height)) {
resetParticle(particles, field, i);
}
particles.x[i] = x;
particles.y[i] = y;
if (isNextToCluster(particles, field, i)) {
particles.stuck[i] = ++CLUSTER_SIZE;
field.field[y*field.width + x] = CLUSTER_SIZE;
}
}
In first two lines we find new place for the particle by randomly moving it in any of 8 direction or not moving it all (with equal probability = 1/9). Then if particle ventured out of our field we reset its position.
If new position is a valid one we check if particle is next to a cluster:
function isNextToCluster(particles, field, i) {
var cx = particles.x[i], cy = particles.y[i];
var lx = cx - 1, rx = cx + 1;
var ty = cy - 1, by = cy + 1;
// if we are at boundary
if (lx < 0 || rx >= field.width || ty < 0 || by >= field.height) {
return false;
}
cy *= field.width;
by *= field.width;
ty *= field.width;
// the check if we have neighour
return field.field[cx + ty] || field.field[lx + cy] || field.field[rx + cy] || field.field[cx + by] ||
field.field[lx + ty] || field.field[lx + by] || field.field[rx + ty] || field.field[rx + by];
}
This is pretty much all the logic we need. The rendering function looks like this:
function render(field, canvas, particles, stopping_fraction) {
var i = particles.count;
while (i--) {
var index = (particles.y[i] * field.width + particles.x[i]) * 4;
var v = Math.sqrt(particles.stuck[i] / (stopping_fraction * particles.count));
var color = v > 0 ? colormap(v) : particle_color;
canvas[index] = color[0]; // red
canvas[++index] = color[1]; // green
canvas[++index] = color[2] ; // blue
canvas[++index] = 255; // alpha
}
}
The start function glues together functions above and triggers render function every frame.
Result
Rest of the code and markup for the sample can be viewed & downloaded here: You can download finished visualisation code here.
Below you can specify parameters and start simulation:


Thank you for taking my quiz.
If you didn't know me before the quiz, you do now.
I love movies, video games, sports, and the Eagles. Also, I am from portland.
I grew up here in the Portland area and went to Lake Oswego High School before spending about 6 years at Oregon State University.
I worked for Pacific Office Automation after school for about a year and a half before deciding to change my career a couple months ago.
I really want to learn a new craft. Especially one that surrounds the things i already enjoy (computers).


The COVID-19 pandemic has been raging across the country over the last year, and has only gotten worse
with this wave. As a consequence it left the country in a state of disarray, people were unable to gain
access to scarce resources like oxygen, medication, beds, food and tiffin services, ambulance services,
teleconsultation and the like. Directing people towards verified resources was the need of the hour, the
driving force behind our initiative, Tavissi Jain, took it upon herself to bridge this gap in
information. She played a pivotal role in helping direct people to oxygen cylinders in Delhi, where she
served as the Oxygen Support Coordinator for the Miranda House Covid Help Desk in New Delhi. After
watching Coimbatore succumb to the second wave of the pandemic, she decided to put her experience to
good use by starting the Coimbatore Covid Aid and directing the citizens in and around Coimbatore to
quintessential resources. She realised it wasn't enough and decided to recruit student volunteers to her
cause and expand the reach of Coimbatore Covid Aid in order to better aid fellow citizens. Our group has
been working tirelessly in order to keep up with the increasing demand in oxygen cylinders, attributed
to the expeditious rise in COVID-19 cases. Born out of this need was our “Help Tiruppur Breathe” project
that aims to raise funds in order to procure oxygen cylinders. The Tiruppur District administration has
graciously agreed to take up the responsibility of refilling the cylinders on rotation and their
subsequent delivery to hospitals, this will ensure a smooth supply. Another initiative that we have up
and running is our “Food Chapter” that is geared towards delivering connect families that are willing to
share food with those that are quarantined due to covid. We also realised the disadvantages of the
digital divide between a metropolitan cities and relatively smaller cities and decided to work on
breaking down crucial covid related information that is verified by a team of doctors, we publish this
information on all our social media platforms in Tamil as well as English to ensure accessibility to
all. To learn more about us and to stay updated, follow us on social media.
Learn more


package io
Linear Supertypes
Ordering
- Alphabetic
- By Inheritance
Inherited
- io
- AnyRef
- Any
- Hide All
- Show All
Visibility
- Public
- All
Type Members
-
case class
FileInputStream(filename: Option[String], consumed: BigInt) extends Product with Serializable
- Annotations
- @library()
-
case class
FileOutputStream(filename: Option[String]) extends Product with Serializable
- Annotations
- @library()
-
case class
State(seed: BigInt) extends Product with Serializable
- Annotations
- @library()


Manual: tokenizer
Converts strings into Lever tokens
This tokenizer is the first thing that happens to a Lever program that is about to be run. The tokenizer is invoked by the parser and the compiler.
To bootstrap Lever's compiler with Python, there is a ported implementation of this module in compiler/lever_parser/reader/.
Table of contents ↑Lever's tokenizer resembles Python's tokenizer a lot. The major difference is that the keywords and operators collected by the tokenizer are determined by the 'table' -argument passed in as an argument. This allows the parsing engine to have a last word on the keywords the tokenizer parses.
This tokenizer should understand..
- Comments starting with '#' that continue to the end of the line.
- Python's raw string syntax, eg. r"foo\bar", r'foo\bar'
- Symbols, eg. identifiers, regex. [a-zA-Z_][a-zA-Z0-9_]*
- Hexadecimals starting with 0x...
- Whole numbers, regex. [0-9]+
- Numbers with decimal point and exponent, eg. 1.23e-10, 1.2
- Strings with single or double quotes, eg. 'hello' or "world"
- Custom keywords or operators.
The tokenizer treats space as separator between tokens, and does not produce Literal -objects for it.
01. Keyword smearing
The keyword table given to the tokenizer may contain symbols such as '!='. For these to be correctly recognized, the non-alphabetic keywords have to be smeared.
Here's a smearing function you can use for that purpose:
default_smear = (keyword): for ch in keyword if ch.is_alpha() return [keyword] result = [] prefix = [] for ch in keyword prefix.append(ch) result.append("".join(prefix)) return result
02. API
| path | The path to the file to be tokenized. |
| table | Keyword table. |
| symtab | Symbol table. |
| returns | List of Literal -objects. |
| string | The string to be tokenized. |
| table | Keyword table. |
| symtab | Symbol table. |
| returns | List of Literal -objects. |
To create your own symbol table, create an object with attributes: 'string', 'symbol', 'hex', 'int', 'float'.
03. Internal details
The rest of this file isn't well-documented.
| start | start source location {col, lno} |
| stop | stop source location {col, lno} |
| name | 'name' of the token, retrieved from the symtab -object. |
| string | The string captured by this token. |
This object is likely unnecessary, and may be replaced by something with .col and .lno -attributes in the future.
Represents a character stream used by the parser. This is purely an internal detail.
| stream | not documented |
| table | not documented |
| symtab | not documented |
| returns | not documented |


Projects
Grant Byrne.com Redesign
October 2013
I shuffled around some projects to implement a NodeJS based development paradigm to show off how awesome I am.
Disposition - the homemade ambilight
October 2013
C#/Arduino interface for the IKEA Dioder to create mood lighting for the back of your monitor!
Dungeon Resource - Dungeons and Dragons references right at your fingertips.
July 2013
Dungeon Resource is a personal experiment with utilizing the latest and greatest technologies while providing useful tools to those happen to play Dungeons and Dragons v3.5


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If at any time you want to unsubscribe, there'll be a link you can follow at the bottom of every e-mail we send.
Thanks,
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synthetic asynchronous processing in javascript
(Now with extra anti-freeze!)
Browsers are synchronous. They have limits & can be slow. thaw.js defers processes
until the browser is ready for them.
thaw.js makes frozen browsers thaw(.js).
You could, if you don't care about the DOM. Unfortunately the DOM does exist, and it is synchronous. Web workers do not have access to anything synchronous, including the DOM.
You are in one right now! Scroll to bottom to see.
There are 2 million div elements being appended to this very document from
three separate thaw calls happening right now, 6 million total. Does your browser seem slow or sluggish? Of
course not! It is thaw(.js)ing.
With Array's:
thaw([], {
each:function(i) {
//this = item of array
},
done: function() {
//this = item of array
}
}, intervalToTryAgain);
With Single Object:
thaw.it({}, {
each:function(i) {
//this = item of array
},
done: function() {
//this = item of array
}
}, intervalToTryAgain);
MIT, Copyright Robert Lee Plummer Jr.


package
pull
Type Members
-
case class
EvComment
(text: String) extends XMLEvent with Product with Serializable
-
case class
EvElemEnd
(pre: String, label: String) extends XMLEvent with Product with Serializable
-
case class
EvElemStart
(pre: String, label: String, attrs: MetaData, scope: NamespaceBinding) extends XMLEvent with Product with Serializable
-
case class
EvEntityRef
(entity: String) extends XMLEvent with Product with Serializable
-
case class
EvProcInstr
(target: String, text: String) extends XMLEvent with Product with Serializable
-
case class
EvText
(text: String) extends XMLEvent with Product with Serializable
-
-
trait
XMLEvent
extends AnyRef
-
class
XMLEventReader
extends ProducerConsumerIterator[XMLEvent]
Classes needed to view an XML document as a series of events. The document is parsed by an XMLEventReader instance. You can treat it as an Iterator to retrieve the events, which are all subclasses of XMLEvent.


Toy Story
little boy named Andy loves to be in his room, playing with his toys, especially his doll named "Woody". But, what do the toys do when Andy is not with them, they come to life. Woody believes that his life (as a toy) is good. However, he must worry about Andy's family moving, and what Woody does not know is about Andy's birthday party. Woody does not realize that Andy's mother gave him an action figure known as Buzz Lightyear, who does not believe that he is a toy, and quickly becomes Andy's new favorite toy. Woody, who is now consumed with jealousy, tries to get rid of Buzz....
watch now


{% extends "fmd_dashboard/graph.html" %} {% block endpoint_menu %} {% macro endpoint_submenu(endpoint, name) -%}
| Endpoint | {{ details.endpoint }} |
| Rule(s) | {{ details.rules }} |
| Added since app version | {{ details.rule.version_added }} |
| Date added to app | {{ "{:%Y-%m-%d %H:%M:%S }".format(details.rule.time_added) }} |
| Link to endpoint | {{ details.url }} |
| Last accessed | {{ "{:%Y-%m-%d %H:%M:%S }".format(details.rule.last_requested) if details.rule.last_requested }} |
| Total number of hits | {{ "{:,d}".format(details.total_hits) }} |


| backend-mssql {dbplyr} | R Documentation |
See vignette("translate-function")
and vignette("translate-verb")
for
details of overall translation technology. Key differences for this backend
are:
SELECT
uses TOP
not LIMIT
Automatically prefixes #
to create temporary tables. Add the prefix
yourself to avoid the message.
String basics: paste()
, substr()
, nchar()
Custom types for as.*
functions
Lubridate extraction functions, year()
, month()
, day()
etc
Semi-automated bit <-> boolean translation (see below)
Use simulate_mssql()
with lazy_frame()
to see simulated SQL without
converting to live access database.
version |
Version of MS SQL to simulate. Currently only, difference is
that 15.0 and above will use |
SQL server uses two incompatible types to represent TRUE
and FALSE
values:
The BOOLEAN
type is the result of logical comparisons (e.g. x > y
)
and can be used WHERE
but not to create new columns in SELECT
.
https://docs.microsoft.com/en-us/sql/t-sql/language-elements/comparison-operators-transact-sql
The BIT
type is a special type of numeric column used to store
TRUE
and FALSE
values, but can't be used in WHERE
clauses.
https://docs.microsoft.com/en-us/sql/t-sql/data-types/bit-transact-sql?view=sql-server-ver15
dbplyr does its best to automatically create the correct type when needed, but can't do it 100% correctly because it does not have a full type inference system. This means that you many need to manually do conversions from time to time.
To convert from bit to boolean use x == 1
To convert from boolean to bit use as.logical(if(x, 0, 1))
library(dplyr, warn.conflicts = FALSE) lf <- lazy_frame(a = TRUE, b = 1, c = 2, d = "z", con = simulate_mssql()) lf %>% head() lf %>% transmute(x = paste(b, c, d)) # Can use boolean as is: lf %>% filter(c > d) # Need to convert from boolean to bit: lf %>% transmute(x = c > d) # Can use boolean as is: lf %>% transmute(x = ifelse(c > d, "c", "d"))


--- layout: post date: 2011-03-31 time: "10:00:00" authors: ["Greg Wilson"] title: Using Bein tags: ["Content"] ---
Many thanks to Frederick Ross for putting together a short screencast on Bein, a workflow manager and miniature laboratory information management system (LIMS) built in Python that fills the gap for the working scientist between the classical shell and big workflow managers like Galaxy and major LIMS systems like OpenBIS. Please have a look and see if it could help make your computational life easier.


Class: ActiveRecord::ConnectionAdapters::PoolConfig
Do not use. This class is for internal use only.
| Relationships & Source Files | |
| Super Chains via Extension / Inclusion / Inheritance | |
|
Instance Chain:
self,
Mutex_m
|
|
| Inherits: | Object |
| Defined in: | activerecord/lib/active_record/connection_adapters/pool_config.rb |
Constant Summary
-
INSTANCES =
private
# File 'activerecord/lib/active_record/connection_adapters/pool_config.rb', line 16ObjectSpace::WeakMap.new
Class Method Summary
Instance Attribute Summary
- #connection_class rw
- #db_config readonly
- #role readonly
- #schema_reflection rw
- #schema_reflection=(value) rw
- #shard readonly
Instance Method Summary
Constructor Details
.new(connection_class, db_config, role, shard) ⇒ PoolConfig
# File 'activerecord/lib/active_record/connection_adapters/pool_config.rb', line 29
def initialize(connection_class, db_config, role, shard) super() @connection_class = connection_class @db_config = db_config @role = role @shard = shard @pool = nil INSTANCES[self] = self end
Class Method Details
.discard_pools!
[ GitHub ]# File 'activerecord/lib/active_record/connection_adapters/pool_config.rb', line 20
def discard_pools! INSTANCES.each_key(&:discard_pool!) end
.disconnect_all!
[ GitHub ]# File 'activerecord/lib/active_record/connection_adapters/pool_config.rb', line 24
def disconnect_all! INSTANCES.each_key(&:disconnect!) end
Instance Attribute Details
#connection_class (rw)
[ GitHub ]# File 'activerecord/lib/active_record/connection_adapters/pool_config.rb', line 10
attr_accessor :connection_class
#db_config (readonly)
[ GitHub ]#role (readonly)
[ GitHub ]#schema_reflection (rw)
[ GitHub ]# File 'activerecord/lib/active_record/connection_adapters/pool_config.rb', line 12
def schema_reflection @schema_reflection ||= SchemaReflection.new(db_config.lazy_schema_cache_path) end
#schema_reflection=(value) (rw)
[ GitHub ]# File 'activerecord/lib/active_record/connection_adapters/pool_config.rb', line 9
attr_writer :schema_reflection
#shard (readonly)
[ GitHub ]Instance Method Details
#connection_name
[ GitHub ]# File 'activerecord/lib/active_record/connection_adapters/pool_config.rb', line 39
def connection_name if connection_class.primary_class? "ActiveRecord::Base" else connection_class.name end end
#discard_pool!
[ GitHub ]# File 'activerecord/lib/active_record/connection_adapters/pool_config.rb', line 68
def discard_pool! return unless @pool synchronize do return unless @pool @pool.discard! @pool = nil end end
#disconnect!
[ GitHub ]# File 'activerecord/lib/active_record/connection_adapters/pool_config.rb', line 47
def disconnect! ActiveSupport::ForkTracker.check! return unless @pool synchronize do return unless @pool @pool.automatic_reconnect = false @pool.disconnect! end nil end
#pool
[ GitHub ]# File 'activerecord/lib/active_record/connection_adapters/pool_config.rb', line 62
def pool ActiveSupport::ForkTracker.check! @pool || synchronize { @pool ||= ConnectionAdapters::ConnectionPool.new(self) } end


Adam Adam Adam Adam
That's my name don't wear it out
Home
My Town
Why Austin?
What to see.
Follow me on Twitter
My Town
Why Austin?
Because it is wicked fun y'all!
What to see.
TURTLES!


What you can do with Ant UX?
It can improve the efficiency of your work.
User Flow
Product architecture
Logic diagram
How to use it?
Download the file you need and open it with matching software
It can improve the efficiency of your work.
User Flow
Product architecture
Logic diagram
Download the file you need and open it with matching software


Howdy! Here's a list of awesome computer scientists. Do you know any others? Add to the list yourself.
Number of clicks: {{clicks}}
{{theUserSaid}}


{% if not devMode %} {% endif %}
This is
Jawher Moussa
's blog, in which he writes about technical stuff
{% block extra_links %}{% endblock %}
bookmarks
my projects
twitter
github
feed
{% block content %} Here be dragons ! {% endblock %}


Let me see your identification. You don't need to see his identification. We don't need to see his identification. These are not the droids your looking for. These are not the droids we're looking for. He can go about his business. You can go about your business. Move along. Move along. Move along.
Let me see your identification. You don't need to see his identification. We don't need to see his identification. These are not the droids your looking for. These are not the droids we're looking for. He can go about his business. You can go about your business. Move along. Move along. Move along.
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--- layout: newsstory title: THAT'S GOT ONE CUP OUT OF THE WAY match: WSC Moor Green 2 Yeltz 1 ---
I guess it's the least prestigious of all the cups we play in, so I reckon we can be pleased we lost 2-1 to Moor Green in the Worcester Senior Cup.Town scorer was Ian Reed, his 4th of the season. More details if I get any.


hockey_scraper¶
The hockey_scraper module contains all of the functions used for scraping.
Scraping¶
There are three ways to scrape games:
1. Scrape by Season:
Scrape games on a season by season level (Note: A given season is referred to by the first of the two years it spans. So you would refer to the 2016-2017 season as 2016).
import hockey_scraper
# Scrapes the 2015 & 2016 season with shifts and stores the data in a Csv file (both are equivalent!!!)
hockey_scraper.scrape_seasons([2015, 2016], True)
hockey_scraper.scrape_seasons([2015, 2016], True, data_format='Csv')
# Scrapes the 2008 season without shifts and returns a dictionary with the DataFrame
scraped_data = hockey_scraper.scrape_seasons([2008], False, data_format='Pandas')
# Scrapes 2014 season without shifts including preseason games
hockey_scraper.scrape_seasons([2014], False, preseason=True)
2. Scrape by Game:
Scrape a list of games provided. All game ID’s can be found using this link (you need to play around with the dates in the url).
import hockey_scraper
# Scrapes the first game of 2014, 2015, and 2016 seasons with shifts and stores the data in a Csv file
hockey_scraper.scrape_games([2014020001,<PHONE_NUMBER>,<PHONE_NUMBER>], True)
# Scrapes the first game of 2007, 2008, and 2009 seasons with shifts and returns a a dictionary with the DataFrames
scraped_data = hockey_scraper.scrape_games([2007020001,<PHONE_NUMBER>,<PHONE_NUMBER>], True, data_format='Pandas')
3. Scrape by Date Range:
Scrape all games between a specified date range. All dates must be written in a “yyyy-mm-dd” format.
import hockey_scraper
# Scrapes all games between date range without shifts and stores the data in a Csv file (both are equivalent!!!)
hockey_scraper.scrape_date_range('2016-10-10', '2016-10-20', False)
hockey_scraper.scrape_date_range('2016-10-10', '2016-10-20', False, preseason=False)
# Scrapes all games between 2015-1-1 and 2015-1-15 without shifts and returns a a dictionary with the DataFrame
scraped_data = hockey_scraper.scrape_date_range('2015-1-1', '2015-1-15', False, data_format='Pandas')
# Scrapes all games from 2014-09-15 to 2014-11-01 with shifts including preseason games
hockey_scraper.scrape_date_range('2014-09-15', '2014-11-01', True, preseason=True)
Saving Files
The option also exists to save the scraped files in another directory. This would speed up re-scraping any games since we already have the docs needed for it. It would also be useful if you want to grab any extra information from them as some of them contain a lot more information. In order to do this one must specify a directory using the keyword argument ‘docs_dir’. If this is a valid directory, when scraping each page it would first check if it was already scraped (therefore saving us the time of scraping it). If it hasn’t been scraped yet, it will then grab it from the source and save it in the given directory.
Sometimes you may have already scraped and saved a file but you want to re-scrape it from the source and save it again (this may seem strange but the NHL frequently fixes mistakes so you may want to update what you have). This can be done by setting the keyword argument rescrape equal to True.
import hockey_scraper
# Path to the given directory
USER_PATH = /....
# Scrapes the 2015 & 2016 season with shifts and stores the data in a Csv file
# Also includes a path for an existing directory for the scraped files to be placed in or retrieved from.
hockey_scraper.scrape_seasons([2015, 2016], True, docs_dir=USER_PATH)
# Once could chose to re-scrape previously saved files by making the keyword argument rescrape=True
hockey_scraper.scrape_seasons([2015, 2016], True, docs_dir=USER_PATH, rescrape=True)
Additional Notes:
1. For all three functions you must specify if you want to also scrape shifts (TOI tables) with a boolean. The Play by Play is automatically scraped.
2. When scraping by date range or by season, preseason games aren’t scraped unless otherwise specified. Also preseason games are scraped at your own risk. There is no guarantee it will work or that the files are even there!!!
3. For all three functions the scraped data is deposited into a Csv file unless it’s specified to return the DataFrames
4. The Dictionary with the DataFrames (and scraping errors) returned by setting data_format=’Pandas’ is structured like:
{
# Both of these are always included
'pbp': pbp_df,
'errors': scraping_errors,
# This is only included when the argument 'if_scrape_shifts' is set equal to True
'shifts': shifts_df
}
5. When including a directory, it must be a valid directory. It will not create it for you. You’ll get an error message but otherwise it will scrape as if no directory was provided.
Functions¶
Scrape Functions¶
Functions to scrape by season, games, and date range
-
hockey_scraper.scrape_functions.
check_data_format
(data_format)¶ Checks if data_format specified (if it is at all) is either None, ‘Csv’, or ‘pandas’. It exits program with error message if input isn’t good.
Parameters: data_format – data_format provided Returns: Boolean - True if good
-
hockey_scraper.scrape_functions.
check_valid_dates
(from_date, to_date)¶ Check if it’s a valid date range
Parameters: - from_date – date should scrape from
- to_date – date should scrape to
Returns: Boolean - True if good
-
hockey_scraper.scrape_functions.
print_errors
()¶ Print errors with scraping.
 I could store it as I “should” print it but that isn’t how I want it).
Returns: None
-
hockey_scraper.scrape_functions.
scrape_date_range
(from_date, to_date, if_scrape_shifts, data_format='csv', preseason=False, rescrape=False, docs_dir=None)¶ Scrape games in given date range
Parameters: - from_date – date you want to scrape from
- to_date – date you want to scrape to
- if_scrape_shifts – Boolean indicating whether to also scrape shifts
- data_format – format you want data in - csv or pandas (csv is default)
- preseason – Boolean indicating whether to include preseason games (default if False) This is may or may not work!!!  Only applies if you supply a docs dir. (def. = None)
- docs_dir – Directory that either contains previously scraped docs or one that you want them to be deposited in after scraping. (default is None)
Returns: Dictionary with DataFrames and errors or None
-
hockey_scraper.scrape_functions.
scrape_games
(games, if_scrape_shifts, data_format='csv', rescrape=False, docs_dir=None)¶ Scrape a list of games
Parameters: - games – list of game_ids
- if_scrape_shifts – Boolean indicating whether to also scrape shifts
- data_format – format you want data in - csv or pandas (csv is default)
- rescrape – If you want to rescrape pages already scraped. Only applies if you supply a docs dir.
- docs_dir – Directory that either contains previously scraped docs or one that you want them to be deposited in after scraping
Returns: Dictionary with DataFrames and errors or None
-
hockey_scraper.scrape_functions.
scrape_list_of_games
(games, if_scrape_shifts)¶ Given a list of game_id’s (and a date for each game) it scrapes them
Parameters: - games – list of [game_id, date]
- if_scrape_shifts – Boolean indicating whether to also scrape shifts
Returns: DataFrame of pbp info, also shifts if specified
-
hockey_scraper.scrape_functions.
scrape_seasons
(seasons, if_scrape_shifts, data_format='csv', preseason=False, rescrape=False, docs_dir=None)¶ Given list of seasons it scrapes all the seasons
Parameters: - seasons – list of seasons
- if_scrape_shifts – Boolean indicating whether to also scrape shifts
- data_format – format you want data in - csv or pandas (csv is default)
- preseason – Boolean indicating whether to include preseason games (default if False) This is may or may not work!!!  Only applies if you supply a docs dir.
- docs_dir – Directory that either contains previously scraped docs or one that you want them to be deposited in after scraping
Returns: Dictionary with DataFrames and errors or None
-
hockey_scraper.scrape_functions.
to_csv
(file_name, pbp_df, shifts_df)¶ Write DataFrame(s) to csv file(s)
Parameters: - file_name – name of file
- pbp_df – pbp DataFrame
- shifts_df – shifts DataFrame
Returns: None
Game Scraper¶
This module contains code to scrape data for a single game
-
hockey_scraper.game_scraper.
check_goalie
(row)¶ Checks for bad goalie names (you can tell by them having no player id)
Parameters: row – df row Returns: None
-
hockey_scraper.game_scraper.
combine_espn_html_pbp
(html_df, espn_df, game_id, date, away_team, home_team)¶ Merge the coordinate from the espn feed into the html DataFrame
Can’t join here on event_id because the plays are often out of order and pre-2009 are often missing events.
Parameters: - html_df – DataFrame with info from html pbp
- espn_df – DataFrame with info from espn pbp
- game_id – json game id
- date – ex: 2016-10-24
- away_team – away team
- home_team – home team
Returns: merged DataFrame
-
hockey_scraper.game_scraper.
combine_html_json_pbp
(json_df, html_df, game_id, date)¶ Join both data sources. First try merging on event id (which is the DataFrame index) if both DataFrames have the same number of rows. If they don’t have the same number of rows, merge on: Period’, Event, Seconds_Elapsed, p1_ID.
Parameters: - json_df – json pbp DataFrame
- html_df – html pbp DataFrame
- game_id – id of game
- date – date of game
Returns: finished pbp
-
hockey_scraper.game_scraper.
combine_players_lists
(json_players, roster_players, game_id)¶ Combine the json list of players (which contains id’s) with the list in the roster html
Parameters: - json_players – dict of all players with id’s
- roster_players – dict with home and and away keys for players
- game_id – id of game
Returns: dict containing home and away keys -> which contains list of info on each player
-
hockey_scraper.game_scraper.
get_players_json
(players_json)¶ Return dict of players for that game
Parameters: players_json – players section of json Returns: dict of players->keys are the name (in uppercase)
-
hockey_scraper.game_scraper.
get_sebastian_aho
(player)¶ This checks which Sebastian Aho it is based on the position. I have the player id’s hardcoded here.
This function is needed because “get_players_json” doesn’t control for when there are two Sebastian Aho’s (it just writes over the first one).
Parameters: player – player info Returns: Player ID for specific Aho
-
hockey_scraper.game_scraper.
get_teams_and_players
(game_json, roster, game_id)¶ Get list of players and teams for game
Parameters: - game_json – json pbp for game
- roster – players from roster html
- game_id – id for game
Returns: dict for both - players and teams
-
hockey_scraper.game_scraper.
scrape_game
(game_id, date, if_scrape_shifts)¶ This scrapes the info for the game. The pbp is automatically scraped, and the whether or not to scrape the shifts is left up to the user.
Parameters: - game_id – game to scrap
- date – ex: 2016-10-24
- if_scrape_shifts – Boolean indicating whether to also scrape shifts
Returns: DataFrame of pbp info (optional) DataFrame with shift info otherwise just None
-
hockey_scraper.game_scraper.
scrape_pbp
(game_id, date, roster, game_json, players, teams)¶ Automatically scrapes the json and html, if the json is empty the html picks up some of the slack and the espn xml is also scraped for coordinates.
Parameters: - game_id – json game id
- date – date of game
- roster – list of players in pre game roster
- game_json – json pbp for game
- players – dict of players
- teams – dict of teams
Returns: DataFrame with info or None if it fails
-
hockey_scraper.game_scraper.
scrape_shifts
(game_id, players, date)¶ Scrape the Shift charts (or TOI tables)
Parameters: - game_id – json game id
- players – dict of players with numbers and id’s
- date – date of game
Returns: DataFrame with info or None if it fails
Html PBP¶
This module contains functions to scrape the Html Play by Play for any given game
-
hockey_scraper.html_pbp.
add_event_players
(event_dict, event, players, home_team)¶ Add players involved in the event to event_dict
Parameters: - event_dict – dict of parsed event stuff
- event – fixed up html
- players – dict of players and id’s
- home_team – home team
Returns: None
-
hockey_scraper.html_pbp.
add_event_team
(event_dict, event)¶ Add event team for event
Parameters: - event_dict – dict of event info
- event – list with parsed event info
Returns: None
-
hockey_scraper.html_pbp.
add_home_zone
(event_dict, home_team)¶ Determines the zone relative to the home team and add it to event.
Keep in mind that the ‘ev_zone’ recorded is the zone relative to the event team. And for blocks the NHL counts the ev_team as the blocking team (I like counting the shooting team for blocks). Therefore, when it’s the home team the zone only gets flipped when it’s a block. For away teams it’s the opposite. Think about it...
Parameters: - event_dict – dict of event info
- home_team – home team
Returns: None
-
hockey_scraper.html_pbp.
add_period
(event_dict, event)¶ Add period for event
Parameters: - event_dict – dict of event info
- event – list with parsed event info
Returns: None
-
hockey_scraper.html_pbp.
add_score
(event_dict, event, current_score, home_team)¶ Change if someone scored...also change current score
Parameters: - event_dict – dict of parsed event stuff
- event – event info from pbp
- current_score – current score in game
- home_team – home team for game
Returns: None
-
hockey_scraper.html_pbp.
add_strength
(event_dict, home_players, away_players)¶ Get strength for event -> It’s home then away
Parameters: - event_dict – dict of event info
- home_players – list of players for home team
- away_players – list of players for away team
Returns: None
-
hockey_scraper.html_pbp.
add_time
(event_dict, event)¶ Fill in time and seconds elapsed
Parameters: - event_dict – dict of parsed event stuff
- event – event info from pbp
Returns: None
-
hockey_scraper.html_pbp.
add_type
(event_dict, event, players, home_team)¶ Add “type” for event -> either a penalty or a shot type
Parameters: - event_dict – dict of event info
- event – list with parsed event info
- players – dict of home and away players in game
- home_team – home team for game
Returns: None
-
hockey_scraper.html_pbp.
add_zone
(event_dict, play_description)¶ Determine which zone the play occurred in (unless one isn’t listed) and add it to dict
Parameters: - event_dict – dict of event info
- play_description – the zone would be included here
Returns: Off, Def, Neu, or NA
-
hockey_scraper.html_pbp.
clean_html_pbp
(html)¶ Get rid of html and format the data
Parameters: html – the requested url Returns: a list with all the info
-
hockey_scraper.html_pbp.
get_pbp
(game_id)¶ Given a game_id it returns the raw html Ex: http://www.nhl.com/scores/htmlreports/20162017/PL020475.HTM
Parameters: game_id – the game Returns: raw html of game
-
hockey_scraper.html_pbp.
get_penalty
(play_description, players, home_team)¶ Get the penalty info
Parameters: - play_description – description of play field
- players – all players with info
- home_team – home team for game
Returns: penalty info
-
hockey_scraper.html_pbp.
get_player_name
(number, players, team, home_team)¶ This function is used for the description field in the html. Given a last name and a number it return the player’s full name and id.
Parameters: - number – player’s number
- players – all players with info
- team – team of player
- home_team – home team
Returns: dict with full and and id
-
hockey_scraper.html_pbp.
get_soup
(game_html)¶ Uses Beautiful soup to parses the html document. Some parsers work for some pages but don’t work for others....I’m not sure why so I just try them all here in order
Parameters: game_html – html doc Returns: “soupified” html
-
hockey_scraper.html_pbp.
if_valid_event
(event)¶ Checks if it’s a valid event (‘#’ is meaningless and I don’t like those other one’s) to parse
Don’t remember what ‘GOFF’ is but ‘EGT’ is for emergency goaltender. The reason I get rid of it is because it’s not in the json and there’s another ‘EGPID’ that can be found in both (not sure why ‘EGT’ exists then).
Events ‘PGSTR’, ‘PGEND’, and ‘ANTHEM’ have been included at the start of each game for the 2017 season...I have no idea why.
Parameters: event – list of stuff in pbp Returns: boolean
-
hockey_scraper.html_pbp.
parse_block
(description, players, home_team)¶ Parse the description field for a BLOCK
MTL #76 SUBBAN BLOCKED BY TOR #2 SCHENN, Wrist, Def. Zone
Parameters: - description – Play Description
- players – players in game
- home_team – Home Team for game
Returns: Dict with info
-
hockey_scraper.html_pbp.
parse_event
(event, players, home_team, current_score)¶ Receives an event and parses it
Parameters: - event – event type
- players – players in game
- home_team – home team
- current_score – current score for both teams
Returns: dict with info
-
hockey_scraper.html_pbp.
parse_fac
(description, players, ev_team, home_team)¶ Parse the description field for a face-off MTL won Neu. Zone - MTL #11 GOMEZ vs TOR #37 BRENT
Parameters: - description – Play Description
- players – players in game
- ev_team – Event Team
- home_team – Home Team for game
Returns: Dict with info
-
hockey_scraper.html_pbp.
parse_goal
(description, players, ev_team, home_team)¶ Parse the description field for a GOAL
TOR #81 KESSEL(1), Wrist, Off. Zone, 14 ft. Assists: #42 BOZAK(1); #8 KOMISAREK(1)
Parameters: - description – Play Description
- players – players in game
- ev_team – Event Team
- home_team – Home Team for game
Returns: Dict with info
-
hockey_scraper.html_pbp.
parse_hit
(description, players, home_team)¶ Parse the description field for a HIT
MTL #20 O’BYRNE HIT TOR #18 BROWN, Def. Zone
Parameters: - description – Play Description
- players – players in game
- home_team – Home Team for game
Returns: Dict with info
-
hockey_scraper.html_pbp.
parse_html
(html, players, teams)¶ Parse html game pbp
Parameters: - html – raw html
- players – players in the game (from json pbp)
- teams – dict with home and away teams
Returns: DataFrame with info
-
hockey_scraper.html_pbp.
parse_penalty
(description, players, home_team)¶ Parse the description field for a Penalty
MTL #81 ELLER Hooking(2 min), Def. Zone Drawn By: TOR #11 SJOSTROM
Parameters: - description – Play Description
- players – players in game
- home_team – Home Team for game
Returns: Dict with info
-
hockey_scraper.html_pbp.
parse_shot_miss_take_give
(description, players, ev_team, home_team)¶ Parse the description field for a: SHOT, MISS, TAKE, GIVE
MTL ONGOAL - #81 ELLER, Wrist, Off. Zone, 11 ft. ANA #23 BEAUCHEMIN, Slap, Wide of Net, Off. Zone, 42 ft. TOR GIVEAWAY - #35 GIGUERE, Def. Zone TOR TAKEAWAY - #9 ARMSTRONG, Off. Zone
Parameters: - description – Play Description
- players – players in game
- ev_team – Event Team
- home_team – Home Team for game
Returns: Dict with info
-
hockey_scraper.html_pbp.
populate_players
(event_dict, players, away_players, home_players)¶ Populate away and home player info (and num skaters on each side)
Parameters: - event_dict – dict with event info
- players – all players in game and info
- away_players – players for away team
- home_players – players for home team
Returns: None
-
hockey_scraper.html_pbp.
return_name_html
(info)¶ In the PBP html the name is in a format like: ‘Center - MIKE RICHARDS’ Some also have a hyphen in their last name so can’t just split by ‘-‘
Parameters: info – position and name Returns: name
-
hockey_scraper.html_pbp.
scrape_game
(game_id, players, teams)¶ Scrape the data for the game
Parameters: - game_id – game to scrape
- players – dict with player info
- teams – dict with home and away teams
Returns: DataFrame of game info or None if it fails
-
hockey_scraper.html_pbp.
shot_type
(play_description)¶ Determine which zone the play occurred in (unless one isn’t listed)
Parameters: play_description – the type would be in here Returns: the type if it’s there (otherwise just NA)
-
hockey_scraper.html_pbp.
strip_html_pbp
(td)¶ Strip html tags and such
Parameters: td – pbp Returns: list of plays (which contain a list of info) stripped of html
Json PBP¶
This module contains functions to scrape the Json Play by Play for any given game
-
hockey_scraper.json_pbp.
change_event_name
(event)¶ Change event names from json style to html (ex: BLOCKED_SHOT to BLOCK).
Parameters: event – event type Returns: fixed event type
-
hockey_scraper.json_pbp.
get_pbp
(game_id)¶ Given a game_id it returns the raw json Ex: http://statsapi.web.nhl.com/api/v1/game/2016020475/feed/live
Parameters: game_id – the game Returns: raw json of game or None if couldn’t get game
-
hockey_scraper.json_pbp.
get_teams
(pbp_json)¶ Get teams
Parameters: pbp_json – raw play by play json Returns: dict with home and away
-
hockey_scraper.json_pbp.
parse_event
(event)¶ Parses a single event when the info is in a json format
Parameters: event – json of event Returns: dictionary with the info
-
hockey_scraper.json_pbp.
parse_json
(game_json, game_id)¶ Scrape the json for a game
Parameters: - game_json – raw json
- game_id – game id for game
Returns: Either a DataFrame with info for the game
-
hockey_scraper.json_pbp.
scrape_game
(game_id)¶ Used for debugging. HTML depends on json so can’t follow this structure
Parameters: game_id – game to scrape Returns: DataFrame of game info
Espn PBP¶
This module contains code to scrape coordinates for games off of espn for any given game
-
hockey_scraper.espn_pbp.
event_type
(play_description)¶ Returns the event type (ex: a SHOT or a GOAL...etc) given the event description
Parameters: play_description – description of play Returns: event
-
hockey_scraper.espn_pbp.
get_espn_date
(date)¶ Get the page that contains all the games for that day
Parameters: date – YYYY-MM-DD Returns: response
-
hockey_scraper.espn_pbp.
get_espn_game
(date, home_team, away_team)¶ Gets the ESPN pbp feed Ex: http://www.espn.com/nhl/gamecast/data/masterFeed?lang=en&isAll=true&gameId=400885300
Parameters: - date – date of the game
- home_team – home team
- away_team – away team
Returns: raw xml
-
hockey_scraper.espn_pbp.
get_espn_game_id
(date, home_team, away_team)¶ Scrapes the day’s schedule and gets the id for the given game Ex: http://www.espn.com/nhl/scoreboard?date=20161024
Parameters: - date – format-> YearMonthDay-> 20161024
- home_team – home team
- away_team – away team
Returns: 9 digit game id as a string
-
hockey_scraper.espn_pbp.
get_game_ids
(response)¶ Get game_ids for date from doc
Parameters: response – doc Returns: list of game_ids
-
hockey_scraper.espn_pbp.
get_teams
(response)¶ Extract Teams for date from doc
Parameters: response – doc Returns: list of teams
-
hockey_scraper.espn_pbp.
parse_espn
(espn_xml)¶ Parse feed
Parameters: espn_xml – raw xml of feed Returns: DataFrame with info
-
hockey_scraper.espn_pbp.
parse_event
(event)¶ Parse each event. In the string each field is separated by a ‘~’. Relevant for here: The first two are the x and y coordinates. And the 4th and 5th are the time elapsed and period.
Parameters: event – string with info Returns: return dict with relevant info
-
hockey_scraper.espn_pbp.
scrape_game
(date, home_team, away_team)¶ Scrape the game
Parameters: - date – ex: 2016-20-24
- home_team – tricode
- away_team – tricode
Returns: DataFrame with info
Json Shifts¶
This module contains functions to scrape the Json toi/shifts for any given game
-
hockey_scraper.json_shifts.
fix_team_tricode
(tricode)¶ Some of the tricodes are different than how I want them
Parameters: tricode – 3 letter team name - ex: NYR Returns: fixed tricode
-
hockey_scraper.json_shifts.
get_shifts
(game_id)¶ Given a game_id it returns the raw json Ex: http://www.nhl.com/stats/rest/shiftcharts?cayenneExp=gameId=2010020001
Parameters: game_id – the game Returns: json or None
-
hockey_scraper.json_shifts.
parse_json
(shift_json, game_id)¶ Parse the json
Parameters: - shift_json – raw json
- game_id – if of game
Returns: DataFrame with info
-
hockey_scraper.json_shifts.
parse_shift
(shift)¶ Parse shift for json
Parameters: shift – json for shift Returns: dict with shift info
-
hockey_scraper.json_shifts.
scrape_game
(game_id)¶ Scrape the game.
Parameters: game_id – game Returns: DataFrame with info for the game
Html Shifts¶
This module contains functions to scrape the Html Toi Tables (or shifts) for any given game
-
hockey_scraper.html_shifts.
analyze_shifts
(shift, name, team, home_team, player_ids)¶ Analyze shifts for each player when using. Prior to this each player (in a dictionary) has a list with each entry being a shift.
Parameters: - shift – info on shift
- name – player name
- team – given team
- home_team – home team for given game
- player_ids – dict with info on players
Returns: dict with info for shift
-
hockey_scraper.html_shifts.
get_shifts
(game_id)¶ Given a game_id it returns a the shifts for both teams Ex: http://www.nhl.com/scores/htmlreports/20162017/TV020971.HTM
Parameters: game_id – the game Returns: Shifts or None
-
hockey_scraper.html_shifts.
get_soup
(shifts_html)¶ Uses Beautiful soup to parses the html document.  I’m not exactly sure how or why but it works.
Parameters: - html – cleaned up html
- player_ids – dict of home and away players
- game_id – id for game
Returns: DataFrame with info
-
hockey_scraper.html_shifts.
scrape_game
(game_id, players)¶ Scrape the game.
Parameters: - game_id – id for game
- players – list of players
Returns: DataFrame with info for the game
Schedule¶
This module contains functions to scrape the json schedule for any games or date range
-
hockey_scraper.json_schedule.
get_current_season
()¶ Get Season based on today’s date
Returns: season -> ex: 2016 for 2016-2017 season
-
hockey_scraper.json_schedule.
get_dates
(games)¶ Given a list game_ids it returns the dates for each game
Parameters: games – list with game_id’s ex:<PHONE_NUMBER> Returns: list with game_id and corresponding date for all games
-
hockey_scraper.json_schedule.
get_schedule
(date_from, date_to)¶ Scrapes games in date range Ex: https://statsapi.web.nhl.com/api/v1/schedule?startDate=2010-10-03&endDate=2011-06-20
Parameters: - date_from – scrape from this date
- date_to – scrape until this date
Returns: raw json of schedule of date range
-
hockey_scraper.json_schedule.
scrape_schedule
(date_from, date_to, preseason=False)¶ Calls getSchedule and scrapes the raw schedule JSON
Parameters: - date_from – scrape from this date
- date_to – scrape until this date
- preseason – Boolean indicating whether include preseason games (default if False)
Returns: list with all the game id’s
Playing Roster¶
This module contains functions to scrape the Html game roster for any given game
-
hockey_scraper.playing_roster.
fix_name
(player)¶ Get rid of (A) or (C) when a player has it attached to their name
Parameters: player – list of player info -> [number, position, name] Returns: fixed list
-
hockey_scraper.playing_roster.
get_coaches
(soup)¶ scrape head coaches
Parameters: soup – html Returns: dict of coaches for game
-
hockey_scraper.playing_roster.
get_content
(roster)¶ Uses Beautiful soup to parses the html document. Some parsers work for some pages but don’t work for others....I’m not sure why so I just try them all here in order
Parameters: roster – doc Returns: players and coaches
-
hockey_scraper.playing_roster.
get_players
(soup)¶ scrape roster for players
Parameters: soup – html Returns: dict for home and away players
-
hockey_scraper.playing_roster.
get_roster
(game_id)¶ Given a game_id it returns the raw html Ex: http://www.nhl.com/scores/htmlreports/20162017/RO020475.HTM
Parameters: game_id – the game Returns: raw html of game
-
hockey_scraper.playing_roster.
scrape_roster
(game_id)¶ For a given game scrapes the roster
Parameters: game_id – id for game Returns: dict of players (home and away) an dict for both head coaches
Save Pages¶
Saves the scraped docs so you don’t have to re-scrape them every time you want to parse the docs.
This only works if you specified a valid directory in hockey_scraper.shared.docs_dir. If not nothing will be saved or be retrieved (if it exists but you didn’t set it)
**** Don’t mess with this unless you know what you’re doing ****
-
hockey_scraper.save_pages.
check_file_exists
(file_info)¶ Checks if the file exists. Also check if structure for holding scraped file exists to. If not, it creates it.
Parameters: file_info – Dictionary containing the info on the file. Includes the name, season, file type, and the dir we want to deposit any data in. Returns: Boolean - True if it exists
-
hockey_scraper.save_pages.
create_file_path
(file_info)¶ Creates the file path for a given file
Parameters: file_info – Dictionary containing the info on the file. Includes the name, season, file type, and the dir we want to deposit any data in. Returns: path
-
hockey_scraper.save_pages.
create_season_dirs
(season)¶ Creates the infrastructure to hold all the scraped docs for a season
Parameters: season – given season Returns: None
-
hockey_scraper.save_pages.
get_page
(file_info)¶ Get the file so we don’t need to re-scrape
Parameters: file_info – Dictionary containing the info on the file. Includes the name, season, file type, and the dir we want to deposit any data in. Returns: Response or None
-
hockey_scraper.save_pages.
save_page
(page, file_info, docs_dir)¶ Save the page we just scraped.
Note: It’ll only get saved if the directory already exists!!!!!!.  That would involve checking if it’s even a valid path and creating it. Make sure you get it right.
Parameters: - page – File scraped
- file_info – Dictionary containing the info on the file. Includes the name, season, file type, and the dir we want to deposit any data in.
- docs_dir – Directory specified - either none or a valid dir
Returns: None


Overview of Blowout Module¶
- Release
2.1
- Date
Jun 05, 2020
Blowout Module¶
This module provides a Blowout object to make creation of oil well blowout scenarios using the bent_plume_model simple. In particular, this object helps coordinate creation of the ambient.Profile data and the blowout initial conditions, including generation of the bubble and droplet size distributions. This module relies on the dbm_utilities module to do things like mixing natural gas into a dead oil to create a live oil, etc. and uses the particle_size_models to generate bubbles and droplets.
See Also¶
bent_plume_model, dbm, dbm_utilities, particle_size_models
Notes¶
This module provides the option to obtain oil properties from distillation cut data available from the National Oceanic and Atmospheric Administration (NOAA) Oil Library. To make use of this capability, you will need to install the OilLibrary package into your Python environment. You may access this package here:
https://github.com/NOAA-ORR-ERD/OilLibrary
Once this package is installed, you may load an oil into a dbm fluid object using the Adios ID Number (e.g., AD01554) index of the OilLibrary.
Class Objects and Methods¶
|
Class to facilitiate creating simulations using the bent_plume_model |
|
Run a bent_plume_model simulation for the present conditions |
|
Plot the bent_plume_model state space solution |
|
Plot all variables for the bent_plume_model solution |
|
Change the release depth (m) to use in a model simulation |
|
Change the orifice diametr (m) to use in a model simulation |
|
Change the OilLibrary ID number to use in a model simulation |
|
Change the oil flow rate (bbl/d) to use in a model simulation |
|
Change the gas-to-oil ratio (std ft^3/bbl) to use in a model simulation |
|
Change the amount of produced water (m/s) exiting with the oil and gas through the orifice |
|
Change the vertical orientation (rad) of the release |
Change the horizontal orientation (rad) of the release |
|
|
Change the number of gas bubbles to include in the simulation |
|
Change the number of oil droplets to include in the simulation |
|
Change the ambient temperature and salinity profile data |
|
Change the ambient current profile data |
|
Save the bent_plume_model complete solution in netCDF format |
|
Save the bent_plume_model state space in ascii text format |
Module Functions¶
The blowout object uses a few utility functions, as listed below:
|
Create particles to add to a bent plume model simulation |
|
Create an ambient.Profile object from the given ambient data |
|
Create an ambient.Profile object from a text file of ocean property data |
|
Create an ambient Profile object from given data |


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