Our development department has the idea to allow Knowzy app users to share images from other Windows 10 applications with the Knowzy app. For now, we just want you to implement the Windows 10 sharing code. To show that the image was shared with the Knowzy app, please display a toast with the image.
Requirements for this task: * Share an image from another Windows 10 App. The Knowzy app should appear as one of the options for Share Targets.
Display a XAML UI for sharing with the Knowzy app.
Display a Toast that displays the image after the sharing operation has completed.
Our research has found a starting point for the sharing idea here under the "Making your PC software a share target" section.
We also found some sample code.
This task has a dependency on Task 2.2.1 and all of it's prerequisites
You will need to add a sharing extension to the Extension section of the Application tag in Package.appxmanifest in the Microsoft.Knowzy.UWP project to enable the app to be an image share target. You also need to specify that you are a share target that supports Bitmap images.
<uap:Extension Category="windows.shareTarget" Executable="Microsoft.Knowzy.UWP.exe" EntryPoint="Microsoft.Knowzy.UWP.App">
<uap:ShareTarget>
<uap:SupportedFileTypes>
<uap:SupportsAnyFileType />
</uap:SupportedFileTypes>
<uap:DataFormat>Bitmap</uap:DataFormat>
</uap:ShareTarget>
</uap:Extension>
You will need to add an OnShareTargetActivated event handler to App.xaml.cs in the Microsoft.Knowzy.UWP project. This handler will be called when a user attempts to share an image to the Knowzy app. It should look something like:
protected override void OnShareTargetActivated(ShareTargetActivatedEventArgs e)
{
Frame rootFrame = new Frame();
Window.Current.Content = rootFrame;
rootFrame.Navigate(typeof(SharePage), e.ShareOperation);
Window.Current.Activate();
}
You will need to add a new XAML page to the Microsoft.Knowzy.UWP project. Right click on the project and select Add | New Item.... Choose the Blank Page template and name it SharePage.xaml.
You will need to add the Sharing UI to the SharePage.xaml file. For now, use something like:
<Grid Background="{ThemeResource ApplicationPageBackgroundThemeBrush}" Margin="12">
<StackPanel>
<Button Content="Share to Microsoft.Knowzy.WPF" Click="ShareButton_Click"/>
<TextBlock x:Name="tbFileName" />
<Image x:Name="img"/>
</StackPanel>
</Grid>
In the file SharePage.xaml.cs you will need to handle the OnNavigatedTo event. The NavigationEventArgs parameter will contain the shared image information. Display the shared image in the SharedPage UI. Pay attention to threading issues such as processing the image in a separate task. Also, you can only update the XAML UI image on the UI thread so you will need to use a dispacther to update the UI.
// add the following using directives
using System.Diagnostics;
using System.Threading.Tasks;
using Windows.ApplicationModel.DataTransfer;
using Windows.ApplicationModel.DataTransfer.ShareTarget;
using Windows.Storage;
using Windows.UI.Core;
using Windows.UI.Xaml.Media.Imaging;
// add the following private members to the SharePage class
private ShareOperation operation = null;
private StorageFile file = null;
// Add the following method to the SharePage class
protected override async void OnNavigatedTo(NavigationEventArgs args)
{
if (args.Parameter != null)
{
// It is recommended to only retrieve the ShareOperation object in the activation handler, return as
// quickly as possible, and retrieve all data from the share target asynchronously.
operation = (ShareOperation)args.Parameter;
await Task.Factory.StartNew(async () =>
{
if (operation.Data.Contains(StandardDataFormats.StorageItems))
{
var storageItems = await operation.Data.GetStorageItemsAsync();
file = (StorageFile)(storageItems[0]);
var stream = await file.OpenReadAsync();
// Get back to the UI thread using the dispatcher.
await Dispatcher.RunAsync(CoreDispatcherPriority.Normal, async () =>
{
var image = new BitmapImage();
img.Source = image;
await image.SetSourceAsync(stream);
});
}
});
}
}
Up to this point, the user has only shared the image with the UWP version of Knowzy. We need to share the image so it can be accessed by the WPF version of Knowzy. The SharePage UI includes a "Share to Knowzy WPF" button that will trigger this sharing operation. Add a "ShareButton_Click" event handler to SharePage.xaml.cs. Please note the location of the sharing folder. ApplicationData.Current.LocalFolder. More information on this folder is available here.
private async void ShareButton_Click(object sender, RoutedEventArgs e)
{
if (file != null)
{
// copy file to app's local folder. Desktop Bridge app will detect new file with its FileWatcher
try
{
await file.CopyAsync(ApplicationData.Current.LocalFolder, file.Name, NameCollisionOption.ReplaceExisting);
}
catch (Exception ex)
{
Debug.WriteLine("ShareButton_Click Error:" + ex.Message);
}
}
if (operation != null)
{
operation.ReportCompleted();
}
}
Now that the image has been copied to the ApplicationData.Current.LocalFolder, the Knowzy WPF app needs to be able to detect that an image has been shared. We will use a FileSystemWatcher to detect when an image has been to the ApplicationData.Current.LocalFolder. We will make this a feature that is only supported when the app is running as a Desktop Bridge app. Add the following code to Views\MainView.xaml.cs in the Microsoft.Knowzy.WPF project:
using System;
using System.Diagnostics;
using System.IO;
using Microsoft.Knowzy.UwpHelpers;
public MainView()
{
InitializeComponent();
if (ExecutionMode.IsRunningAsUwp())
{
try
{
// get the path to the App folder (WPF or UWP).
var path = AppFolders.Local;
FileSystemWatcher watcher = new FileSystemWatcher(path);
watcher.EnableRaisingEvents = true;
watcher.Changed += Watcher_Changed;
}
catch(Exception ex)
{
Debug.WriteLine("FileSystemWatcher Error:" + ex.Message);
}
}
}
Add the FileSystemWatcher event handler to MainView.xaml.cs in the Microsoft.Knowzy.WPF project:
private void Watcher_Changed(object sender, FileSystemEventArgs e)
{
if (ExecutionMode.IsRunningAsUwp())
{
if (File.Exists(e.FullPath))
{
var xml = "<toast><visual><binding template='ToastGeneric'><image src='" + e.FullPath + "'/><text hint-maxLines='1'>Microsoft.Knowzy.WPF received a new image</text></binding></visual></toast>";
Toast.CreateToast(xml);
}
}
}
You will need to add a getter to AppFolders.cs in Microsoft.Knowzy.UwpHelpers to return the path to Windows.Storage.ApplicationData.Current.LocalFolder.
Add the following code to AppFolders.cs
public static string Local
{
get
{
string path = null;
if (ExecutionMode.IsRunningAsUwp())
{
path = GetSafeAppxLocalFolder();
}
return path;
}
}
internal static string GetSafeAppxLocalFolder()
{
try
{
return Windows.Storage.ApplicationData.Current.LocalFolder.Path;
}
catch (Exception ex)
{
System.Diagnostics.Debug.WriteLine(ex.Message);
}
return null;
}
Once you have made all of your changes to to code, build and run the Microsoft.Knowzy.Debug project.
Open an Windows 10 application that is capable of sharing a picture (Microsoft Edge). Navigate to a picture you want to share.
Right click on the image and select Share picture
In the list of apps that are iamge share targets, select Microsoft.Know.UWP
The Microsoft.Knowzy.UWP SharePage will appear and display the image. Click on the Share to Microsoft.Knowzy.WPF button.
The FileSystemWatcher in the Microsoft.Knowzy.WPF app will be notified that a new image has been shared to the app. It will then display the toast with the image.
We will continue to add more Windows 10 UWP features to our app in the next task.


Api script for managing a cinema booking system
- /movies/all - returns all the movies in the database in a JSON format
- /movies - returns all the movies in the database in a HTML format
- /users - returns all the users in the database in a JSON format
- /movies/$id -returns the movie with the given id
- /users/$id -returns the user with the given id


Module Client
Discord Client Class
Functions
| initialize (options) | Internally initialize's the Client class. |
| login (email, password) | Logs the Client into Discord's servers. |
| logout (email, password) | Logs the Client out of the Discord server. |
| getToken () | Gets the current authentication token. |
| getGateway () | Gets the current Gateway we are connected to. |
| getCurrentUser () | Gets the current User information. |
| getServerList () | Gets a table of Servers the current User is connected to. |
| getChannelList (id) | Gets a table of Channels from the provided Server id. |
| sendMessage (message, id) | Sends a Message from the Client to a Channel. |
| editMessage (message, msgClass) | Edits a sent Message. |
| deleteMessage (msgClass) | Deletes a sent Message. |
| run () | Starts the Client loop. |
Functions
- initialize (options)
-
Internally initialize's the Client class.
Please use Client:new(options) instead.
Parameters:
- options Options table (Currently useless.)
- login (email, password)
-
Logs the Client into Discord's servers.
This is required to use most of the Clients functions.
Parameters:
- email E-mail Address of the account to log in.
- password Password of the account to log in. (WARNING: Do NOT store this password in a GitHub repo or anything of the sorts.)
Returns:
-
True or False depending on success.
- logout (email, password)
-
Logs the Client out of the Discord server.
(This is currently useless/does nothing)
Parameters:
- email E-mail Address of the account to log in.
- password Password of the account to log in. (WARNING: Do NOT store this password in a GitHub repo or anything of the sorts.)
Returns:
-
True or False depending on success.
- getToken ()
-
Gets the current authentication token.
(Only if logged in of course.)
Returns:
-
Authentication Token
- getGateway ()
-
Gets the current Gateway we are connected to.
(Only if logged in of course.)
Returns:
-
Gateway URL
- getCurrentUser ()
-
Gets the current User information.
(Only if logged in of course.)
Returns:
-
User Table
- getServerList ()
-
Gets a table of Servers the current User is connected to.
(Only if logged in of course.)
Returns:
-
Server Table
- getChannelList (id)
-
Gets a table of Channels from the provided Server id.
(Only if logged in of course.)
Parameters:
- id Server ID
Returns:
-
Channel Table
- sendMessage (message, id)
-
Sends a Message from the Client to a Channel.
(Only if logged in of course.)
Parameters:
- message Message to be sent.
- id ID for Channel to send to.
Returns:
-
Message Class
- editMessage (message, msgClass)
-
Edits a sent Message.
(Only if logged in of course.)
Parameters:
- message The new message to replace the old one.
- msgClass Message Class to edit.
Returns:
-
Message Class
- deleteMessage (msgClass)
-
Deletes a sent Message.
(Only if logged in of course.)
Parameters:
- msgClass Message Class to delete.
Returns:
-
Message Class
- run ()
- Starts the Client loop. (Does nothing of real use at the moment, will interact with WebSockets in the future)


Find the first file matching a given pattern in the current directory or the nearest ancestor directory.
Matching is done with micromatch, please report any matching related issues on that repository.
var findup = require('findup-sync');
findup(patternOrPatterns [, micromatchOptions]);
// Start looking in the CWD.
var filepath1 = findup('{a,b}*.txt');
// Start looking somewhere else, and ignore case (probably a good idea).
var filepath2 = findup('{a,b}*.txt', {cwd: '/some/path', nocase: true});
findup(patterns, [options])
patterns
{String|Array}: Glob pattern(s) or file path(s) to match against.options
{Object}: Options to pass to micromatch. Note that if you want to start in a different directory than the current working directory, specify a cwd
property here.returns
{String}: Returns the first matching file.MIT


For the open help schedule, see Open Student Hours.
For the detailed weekly schedule for each cohort, see one of the week postings (e.g., Week 1).
| Introduction | |
| Wed 26 August | Materials Posted, TCS Chapter 0, TCS Chapter 1 |
| Wed 26 August (3:30-4:45pm) | Full Class Welcome Meeting |
| Tue 1 Sept – Mon 7 Sept | Assessed Cohort Meetings |
| Wed 2 September | Materials Posted, TCS Chapter 2 |
| Tue 8 Sept – Mon 14 Sept | Assessed Cohort Meetings |
| Finite Computation | |
| Wed 9 September | Materials Posted, TCS Chapter 3 |
| Tue 15 Sept – Mon 21 Sept | Assessed Cohort Meetings |
| Wed 16 September | Materials Posted, TCS Chapter 4 |
| Tue 22 Sept – Mon 28 Sept | Assessed Cohort Meetings |
| Wed 23 September | Materials Posted, TCS Chapter 5 |
| Tue 29 Sept – Mon 5 Oct | Assessed Cohort Meetings |
| Uniform Computation | |
| Wed 30 September | Materials Posted, TCS Chapter 6 |
| Tue 6 Oct – Mon 12 Oct | Assessed Cohort Meetings |
| Wed 7 October | Materials Posted |
| Tue 13 Oct – Mon 19 Oct | Assessed Cohort Meetings |
| Wed 14 October | Materials Posted, TCS Chapter 7 |
| Tue 20 Oct – Mon 26 Oct | Assessed Cohort Meetings |
| Wed 21 October | Materials Posted, TCS Chapter 9 |
| Tue 27 Oct – Mon 2 Nov | Assessed Cohort Meetings |
|
Tuesday, 3 November is Election Day. We will not have any assessed cohort meetings on November 3. The Tuesday cohorts will have their Week 10 cohort meeting on November 10 (effectively having 2 weeks between meetings, and switching from being the first cohort to meet to being the last one to meet for the remainder of the semester. |
|
| Wed 28 October | Materials Posted, TCS Chapter 12, 13 |
| Wed 4 Nov – Tue 10 Nov | Assessed Cohort Meetings |
| Tractable and Intractable Computation | |
| Wed 4 November | Materials Posted, TCS Chapter 14, 15 |
| Wed 11 Nov – Tue 17 Nov | Assessed Cohort Meetings |
| Mon 9 November | Materials Posted |
| Wed 18 Nov – Tue 24 Nov | Assessed Cohort Meetings |
| Finals Week | |
| Monday 7 December (2-5pm) | The registrar has scheduled a final exam for this course on Monday, 7 December 2020 (2-5:00 pm). We do not anticipate using this for an exam or anything that would be required, but may use it for a different end-of-course activity. |


| 1280 | (A) | alle that thaire bodies wiłł by or bargans of þam make |
| 1274 | (C) | Alle þat her wyłł bodyes bye . or marchaundyse make |
| 1267 | (D) | Al þat her bodies bye wole or bargaynes make |
| 1243 | (E) | who þat weele here bodyes bye . y graunte hem þis tyme |
| (Ex) | ---- no text ---- | |
| 1309 | (L) | alle þat here bodyes wol by or bargaynes make |
| (P) | ---- no text ---- | |
| 1250 | (U) | Alle that her bodys wille bye / or bargayns make |
| 345 | (V) | All þat her bodies wołł bye . or bargaine make |


The handling of trivial matters was now over . Along with the members of the Knight Order Guild, Jin-Woo moved to the front of the Gate
Before they were about to enter, though .
"Please wait . ".
Chairman Park Jong-Su and his deputy, Vice-Chair Jeong Yun-Tae, began going through their equipment as well as the conditions of the team members for the last time
Maybe because they were now standing before the entrance, the noisy atmosphere from before was now long gone, replaced by weighty silence
'… . '.
He wasn't sure from when it started, but Jin-Woo began liking this state of tension just before entering a dungeon . It felt as if the inside of his head was settling down
Such a thing would've been totally unimaginable back in the past when he avoided answering phone calls out of the fear he felt for the Hunter Association's periodic call-ups
"Hyung-nim, there are no problems . ".
"Very good . ".
Park Jong-Su nodded his head and walked over to Jin-Woo, standing a step away from the rest of the raid team . The latter shifted his gaze to the leader of this raid
"Seong Jin-Woo Hunter-nim?".
"Yes?".
Jin-Woo uncrossed his arms and stared directly into Park Jong-Su's eyes, and the older man lowered his head right away
"We'll be in your care from now on . ".
Although short, those words contained many of Park Jong-Su's feelings and worries . Jin-Woo used similar words as his reply
"I'll be in your care, as well . ".
Park Jong-Su and Jeong Yun-Tae entered the Gate first, and the rest of the Hunters entered one by one after them .
[You have entered a dungeon . ].
As usual, the System message no one else could see beside him welcomed Jin-Woo before anything else could happen . But then .
'Mm?'.
Jin-Woo tilted his head
He was greeted by a dungeon with passageways large enough to accommodate giants passing by
He hadn't entered a lot of high-ranked dungeons before, but he was lucky enough to be inside one this huge . That was why Jin-Woo wasn't puzzled by the size of the dungeon . No, it had to do with this strange feeling he got from the air of the dungeon itself
'What's this ?'.
For some reason, he felt incomparably comfortable inside here
He felt ominous sensations being carried in the air of the dungeons countless times, but this would be his first time feeling like this
However
"It's the Ogre!".
Somewhat different from Jin-Woo's own premonition, the assault team was greeted by huge trouble from the entrance, instead
"It's the Twin-Head Ogre!!".
"Everyone, be careful!!".
A monster that would typically appear as a boss in other high-ranked dungeons was standing in the entrance, its bloodshot eyes glaring at the Hunters
"Grooooaaaar!!!".
A Twin-Head Ogre was about twice the size of a regular Ogre . But it was difficult to quantify how many times greater the creature's powers were
If it were any other 'regular' assault team that had to face off against a Twin-Head Ogre in a dungeon, they would have been utterly frightened out of their senses and have tried to escape right away, but .
"Let's go!".
… . It was a different story with the elites of the Knight Order
Park Jong-Su the tanker raised his shield up and rushed towards the Ogre
Discovering the human approaching it, the monster raised above its two heads a huge club that looked as if it was made from a tree yanked straight out of the ground, roots and all
SLAM!!.
The impact force actually shook the interior of the dungeon!.
However, Park Jong-Su activated his skill in time to balloon up his muscle mass and managed to endure against the incredible physical strength of the Twin-Head Ogre without being brought down to his knees
"Hyung-nim!".
"I'm fine!".
"Then, I'm coming, too!".
The sub-tanker, Jeong Yun-Tae, stood next to Park Jong-Su
Succeeding in his mission to get the Ogre's attention locked firmly onto himself, Park Jong-Su yelled out loudly, veins in his neck standing up
"Attack!!".
With that, the counteroffensive of the Knight Order commenced . Arrows, magic spells, swords, and spears rained down on the Twin-Head Ogre
Krrroooaar!!.
The Twin-Head Ogre became agitated and began rampaging around . However, Park Jong-Su didn't give the monster a chance to divert its attention elsewhere
Meanwhile, Jeong Yun-Tae quickly ran over and defended the others whenever they were targetted by the Ogre
THUD!!.
Just now, Jeong Yun-Tae defended against the Ogre's kick and was shoved back greatly as two lines were gouged on the ground by his feet . Thanks to him, though, other Hunters suffered almost no damage at all
"K-krooar, Kheu-uh-uhrk!".
The body of the Ogre was gradually shaved away due to the combined attacks of the damage dealers . It was a spectacular teamwork!.
From this spectacle alone, Jin-Woo could now understand why the Knight Order Guild managed to lock down on the position of Yeong-Nam district's number one for such a long time
"Gheo-uh-uhrk!".
Eventually, the Ogre fell backwards, bubbles foaming in its mouths
THUD!.
It was the moment when a boss-level monster fell without injuring a single person . A perfect victory, in other words
"We did it!".
The leader of the team, Park Jong-Su, tightly clenched both of his fists
Was it because they had a guest today? Not just him, but even the rest of his teammates were much more motivated than usual
How would they have looked in Hunter Seong Jin-Woo's eyes just now?.
'I'd be beyond ecstatic if he got moved by our teamwork and suddenly decides to join our Guild '.
Sneak
Park Jong-Su sneaked a glance and immediately encountered Jin-Woo's gaze
Feeling as if his inner thoughts had been laid bare, Park Jong-Su became a bit sheepish and began wondering what he should do next, before deciding to approach Jin-Woo with a warm smile
"We'll stay here for a bit longer to recheck our equipment before advancing forward . ".
"Ah, okay . Please do . ".
Jin-Woo nodded his head
While he only needed to drink potions to refill his magic energy or stamina, other Hunters clearly suffered from a physical limit to their magical energy reserve or fatigue . It was a must to take a break, even if it was a short one, after fighting against a powerful monster like that
Park Jong-Su was now standing next to Jin-Woo . He stared at the dead body of the Ogre and spoke with an awkward look on his face
"This is going to be big trouble . ".
" . ?".
Jin-Woo shifted his gaze over to Park Jong-Su . The latter continued on
"It seems likely that this raid won't be easy, unfortunately . To think, we'd end up running into a Twin-Head Ogre right from the start . ".
He rubbed his chin before turning to look at Jin-Woo with a grin
"Do you know what the nickname of a Twin-Head Ogre is, by any chance?".
Jin-Woo shook his head, and the older man replied as if he expected that answer
"It's the 'grave keeper' . ".
Did that nickname come about because it was such a powerful monster that killed a lot of people? However, Park Jong-Su's explanation was far off Jin-Woo's estimations
"The thing is ".
The older man cast his gaze deeper into the cavern's interior . An ominous aura seemed to be oozing out from the other side of the cavern still enshrouded in darkness, at least in his eyes
" When you meet one as the boss of a dungeon, it's fine, but when you run into one right at the beginning, then well, you'll find that this dungeon . ".
 ".
***.
An urgent call came through to the Hunter's Association emergency hotline . The caller's voice belonged to a young teenage girl
- "Is, is this the Association?!".
The call centre employee heard the scared sobbing coming from the other side of the line as soon as the call got connected, and realised something was wrong
"Yes, it is . Please speak . ".
- "This, I'm in, sob, my school, but . There are, sob, there are monsters outside . ".
"Outside? Where are you making this call from?".
- "I'm hiding, I was with, my f-friend, but my friend, I, sob, I'm in the bathroom . ".
Her sobbing meant that her words were constantly being cut off and it was hard to carry on a conversation . However, the call centre employee was experienced enough to piece together those stuttering words and figured out what this girl was trying to say
Immediately, an urgent message was sent to the Association's main building
[Monsters appeared in the local school, one confirmed victim, the informant in hiding . ].
Could it be that a dungeon break occurred inside a school? The employee shuddered from the horrifying images taking root in his head and focused all of his being in trying to keep this female student alive
"How many monsters are there? Are they any near you right now?".
- "I don't know, I really don't know . Ah, ah! I hear screams . Sob, sob . I can hear so many screams . I, am I, sob, am I going to die?".
"Please calm down and listen to my voice . ".
This employee knew very well from his extensive experience about how weak-kneed humans could get when faced with life-threatening situations . He knew he had to be calm and collected in such situations while answering the call
He had to calm the caller down sufficiently enough and then, had to suggest some kind of a plan for the current situation . That was his role
"Right now, Hunters from the Association are headed your way . These Hunters will not give up on you guys . That is why you need to stay calm and rational, okay? Can you hear me?".
- "Really? I-in that case, sob, can I, can I survive?".
The voice coming from the other side of the line was gradually recovering from the panicked state . That was a good sign
The employee thought that he succeeded in calming the female student down, and then asked the question that could prove to be most important in saving the girl's life
"By any chance, those monsters . do you know what kind of monsters those are?".
- "Yes, yes . I know . I know . I saw them . On TV . ".
"Which monsters are they?".
If the monsters possessed weak senses and chased after humans using their eyes, then hiding in a bathroom would work as a suitable solution for the time being . The employee prayed that such monsters had invaded the school, instead
- "They . they have human bodies, but, sob, but they have ugly faces . Ah, and their skin is green . ".
'Can it be?!'.
The eyes of the employee grew wider and wider
"Orcs . are they Orcs?".
- "Yes, I think it was what they were called . Orcs . ".
'N-no, this can't be!!'.
The employee shot up from his seat before he realised it and cried out
"You need to run away from there! Hurry! Orcs can . ".
It was then
Despite the employee's earnest prayer, he could hear the sound of the bathroom door being destroyed, followed soon by a sorrowful scream
- "Kyyaaaahk!".
***.
The Knight Order's raid was trucking along quite smoothly
As a matter of fact, things were working out so well that the Hunters felt the whole thing was strangely too easy
For instance, there encountered yet another monster, but .
"Kuwaaahk!".
A rotting creature the size of a house tried to escape from the assault team, only to get ensnared by the restriction magic spell cast by the Mage-type Hunter, and soon, it too met with a grisly end
And when the exact same thing repeated itself over and over again, the Hunters were getting progressively more puzzled
"Isn't this weird?".
"Why are these monsters running away when they see us?".
"Isn't it like they were being chased away?".
Powerful undead creatures, such as Vampires, Lichs, Dread Worms, Red Ghouls, etc . , continued to pop up inside this dungeon
Undeads were difficult opponents to fight against
Not only were they difficult to kill, but even after killing them, Hunters couldn't let their guards down . Because no one knew when they would regenerate or get revived to start attacking again
However, these creatures couldn't do much to display their prowess for some reason, and continued to get powerlessly massacred at the assault team's hands
'It's like they are too scared and can't even think about resisting us . '.
That was Park Jong-Su's assessment after observing the monsters and their strange behaviour . He even thought that maybe there was no need to bring Hunter Seong Jin-Woo along when things were this easy
'Seriously, man . You really can't tell what's going to happen inside a dungeon . '.
Who'd have imagined that they were clearing a highest-difficult rank A dungeon this painlessly?.
'Even still '.
Being able to end a raid without a single person getting injured was always a good thing . There might have been an unnecessary loss of profit here, but result-wise, it sure was a big relief
On the other hand, Jin-Woo was inwardly feeling quite disappointed
'Here I was, really hyped up because this place was supposed to be the hardest rank A dungeon there could be '.
There was still that enormous magic energy leaking out from the deeper part of the dungeon, but would he even be able to earn any experience points if things continued on at this rate?.
Because of the spirited attacks by the members of the Knight Order Guild, he didn't even have a single chance to step forward at all
'… . '.
Jin-Woo inwardly sighed out . But then, he abruptly halted his steps
'Uh?'.
When Jin-Woo looked behind him, Healer Jeong Ye-Rim also came to a stop as well
"What's the matter, Seong Hunter-nim? Is something following us?".
Jin-Woo didn't answer her . As a matter of fact, his heart was beating so madly that he didn't even have any leeway to answer her questions
'Could it be . ?'.
Jin-Woo's eyes, as they stared towards the outside of this dungeon, began quaking violently . Only then did Jeong Ye-Rim also realise that something was wrong as well
"Seong Hunter-nim??".
It was then
Jin-Woo's expression hardened like stone
***.
"Uwaahhk!".
"Kyaahhk!".
Heartbreaking screams rose up from all corners of the school
Less than half of the students managed to escape from the school alive . As for the rest, either they had all ended up as corpses, or were busy running around inside the school's premise trying to evade the Orcs . Unfortunately, their futile resistance could only buy them a brief respite
The hunts of the Orcs that started from the lowest floor continued on to higher floors and drove all victims caught in their wake to gruesome deaths
"Uwaaahk!".
The students who couldn't run away in time and remained trapped in their classrooms could only cover their ears as more screams rose up from the lower floors
The classrooms for the third year students were located on the top floor of the school building . Jin-Ah was also among those 3rd-year students who couldn't run away in time . The doorway shoddily blocked up with junk was the only thing that could defend them against the marauding Orc horde
"Ah ".
" F*ck me . ".
The male students grabbed onto chairs and mops or whatever that could serve as weapons with their trembling hands . But, none of them helped to instil a sense of confidence in the scared students
No, all they could do was to wait and pray fervently for the Hunters to show up before those Orcs stepped foot inside their classroom
KWANG!.
The bent classroom door was flung away
"Uwaaahk!".
"Kyaaahk!".
As the screams of the frightened students resounded out, two Orcs covered in the blood of the countless number of people they had murdered stepped into the classroom
"U-uwaaahk!".
A male student holding a mop near the door threw away his make-shift weapon and ran to the back entrance, before yanking it open
However, another Orc was lying in wait there, and it slammed an axe down on the forehead of this fleeing male student
Kwajeeck!.
The male student fell powerlessly, the light of life leaving his eyes
"Kyaaaahk!".
"Uwak!".
Both entrances of the classroom were now blocked off by the Orcs
The remaining students screamed out loudly and crowded against the windows, but they all knew that the results would largely end up the same regardless of whether they chose to jump out from a sixth-story window or get caught by the Orcs
'Oppa, oppa!!'.
Finding herself stuck in the middle of the students fleeing towards the corners of the classroom as they tried to get away from the Orcs, Jin-Ah squeezed her eyes shut and called out to Jin-Woo
Her oppa, the rank S Hunter . If she called out to him, it felt as if he'd show up here right away . That was her only hope
"Kurururuk . ".
"Ku-euk?".
The Orcs stopped advancing after they surrounded the students from all corners . They began conversing to each other in their native tongue
"Boss . There is a human with magic energy coming off . ".
"Kill that one first . ".
Unlike regular humans, those that knew how to wield magic energy were dangerous opponents . Therefore, these Orcs had to deal with a threat like that first
The Orc, having received the boss's order, began scanning the students before eventually locking onto Jin-Ah's location
"Ah!".
The Orc grabbed her wrist and dragged her out to the middle of the classroom
"Is this female the one?".
"It is, boss . ".
The underling was right . Although faint, they could sense magic energy coming from somewhere on this girl . Whether that came from this female's abilities or some sort of a weapon she possessed, it didn't change the fact that she had to be eliminated first before everyone else
The boss raised its axe up
"Ah, ah !".
Jin-Ah saw the axe rising up high above her head, and eventually squeezed her eyes shut
"Kuruk . ".
The boss twitched its nose and swung the axe down with a disinterested face
Swiiiish-!.
'Oppa!'.
But then, this happened
Rumble-!.
A veil of black smoke suddenly exploded out from Jin-Ah's shadow and took on a solid shape
Grab
The brows of the advanced scout's boss shot up high in surprise
Because, it just realised that a High Orc wearing black armour suddenly appeared out of nowhere to grab onto its wrist, that was why
"Kuruk?".
Before the puzzled Orc could say something .
The High Orc threw a simple punch and shattered the head of the monster like an exploding watermelon
Kwajeeck!!.
< Chapter 140 > Fin


'Allo, 'Allo!
You now have Yeoman webapp scaffolded and ready to rock.
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Wrapper of DataWarehouse variables.
More...
#include <DWView.h>
template<typename Field, VarType VAR, DimType DIM>
class Uintah::PhaseField::DWView< Field, VAR, DIM >
Wrapper of DataWarehouse variables.
Factory Implementation for dynamic instantiation
- Template Parameters
-
| Field | type of field (ScalarField < T > or VectorField < T, N >) |
| VAR | type of variable representation |
| DIM | problem dimension |
◆ DWView() [1/3]
template<typename Field, VarType VAR, DimType DIM>
Constructor.
Instantiate view components without gathering info from the DataWarehouse
- Parameters
-
| label | list of variable labels for each component |
| material | material index |
◆ DWView() [2/3]
template<typename Field, VarType VAR, DimType DIM>
Constructor.
Instantiate view components and gather info from dw
- Parameters
-
| dw | DataWarehouse from which data is retrieved |
| label | list of variable labels for each component |
| material | material index |
| patch | grid patch |
◆ ~DWView()
template<typename Field, VarType VAR, DimType DIM>
◆ DWView() [3/3]
template<typename Field, VarType VAR, DimType DIM>
Prevent copy (and move) constructor.
◆ operator=()
template<typename Field, VarType VAR, DimType DIM>
Prevent copy (and move) assignment.
◆ Name
template<typename Field, VarType VAR, DimType DIM>
The documentation for this class was generated from the following file:


Retrospective: Lawrence of Arabia (1962) Directed by: David Lean Starring: Peter O'Toole (T.E. Lawrence), Alec Guinness (Prince Feisal) Anthony Quinn (Auda abu Tayi), Jack Hawkins (General Allenby) Omar Sharif (Sherif Ali ibn el Kharish), Josť Ferrer (Bey of Deraa) Anthony Quayle (Colonel Harry Brighton), Claude Rains (Mr. Dryden) Arthur Kennedy ( Jackson Bentley). Running Time: 216 minutes. Reviewed by Michael A. Turton
This awesome epic, recently re-released in letterbox format after a loving restoration, is simply one of the most greatest movies ever made. Not merely a great epic, this is a painting whose tremendous canvas hides a universe of hidden detail and subtle symbolism that give the film its oddly uncommunicable emotional power.
_Lawrence of Arabia_ is a rather strange epic; indeed, one might profitably ask whether it is a heroic epic at all and not simply a very long movie about Lawrence of Arabia. There are no redemptive moments in _Lawrence of Arabia_, because almost everything Lawrence tries his hand at flops. His dream of Arab freedom is betrayed by his superiors and by his disciples. His death -- a failed attempt to avoid a bicycle while riding a motorcycle -- redeems nothing and no one. His followers melt away as time goes on. His close friends cannot comprehend him, his supporters are using him and in the end those around him admire him without understanding him. An assurance from Lawrence ("There's enough time.   And unlike the heroes of _Dr. Zhivago_ or _Spartacus_, Lawrence is neither caught up in or the mover of great events, he is merely the leader of "a sideshow of a sideshow."
Much of the critical commentary on _Lawrence of Arabia_ has focused on the fierce, obsessive acting of Peter O'Toole in the starring role, the homosexual overtones of the film's womanless universe and sadomasochism and the wondrous directing skill of David Lean in using the desert as the backdrop for his story. But many of the critics have missed the deft hints that stitch together what otherwise might be a canvas too big for the viewer to take in. For though the pace of the story is slow, it never stops; a great many changes in the characters take place; but none seem absurd or unheralded; we empathize with that impossible creature, T. E. Lawrence, yet he has not a single monologue. How can this be?
The story is not about T. E. Lawrence, and critics who complain that it is some kind of (failed) psychological exploration of Lawrence's life a la _Citizen Kane_ have missed the boat. The film tells the story of another person, half-legend, half-autochthonic creation of a godlike will, Lawrence of Arabia. Lawrence of Arabia does not even have a first name; his parentage is uncertain and we are told again and again that he is a man who may create himself. Regardless of who is doing the talking, he is invariably addressed as "Lawrence." Further, we are never permitted to see him alone. Whenever Lawrence is on the screen, he is with someone, and we know him only through the eyes of his disciples, as if Lean were some modern-day Luke who had decided to film his gospel rather than jot it down in Amharic. Thus, the commentary at his funeral is not some announcement to the moviegoer that we are about to go on a journey into the psyche of a hero, but rather, it is a clue to the way in which we will come to know Lawrence of Arabia, as much a creation of those around him as he is the realization of his own flawed genius. Lawrence has no past (his dossier gives no hint of his extraordinary gifts) and, as we know from the beginning, no future. He wanders through an eternal present made manifest both in the vastness of the desert wastes and in the utter lack of references to time in the film. This is compounded by the weird rootlessness of Lawrence's universe, whose turbulence is an illusion hiding an eternal and unbreakable stability which rests on the pillars of mutual hatred and mistrust between Arab and Arab and Turk, and its absence of a future, with the British moving in and nary a woman in sight.
So Lawrence is to become a hero, a prophet even. And when do we see Lawrence awaken as a prophet? He is ushered into the tent of Feisal and there, suddenly begins speaking from the Koran and urging his plans on Feisal. And what are King Feisal's plans? Why, he dreams of going to Damascus! The Arab revolt is set on the road to Damascus. Wasn't there another man too who became a prophet on his way to Damascus? Thus we are forewarned, in an allusion that is more like an echo than a statement, of the fate of Lawrence. At one point Feisal remarks that with Lawrence, "mercy is a passion, with me, it is merely good manners. You may judge which is the more reliable." Not just a sample of his suave wit, it foreshadows the changes which will take place in Lawrence after his experiences in Deraa. Yet another reason we unquestioningly accept Lawrence's transition to sainthood is the allusions to the biblical travails of Jesus, as when Lawrence is tormented in the desert by Sherif Ali ibn el Kharish (Omar Sharif), then left alone, just as Jesus was, or when he brings back a man from the dead, just as Jesus did. And of course, the film takes place in the Holy Land, with its powerful associations for Westerners, with the Turks for latter-day Romans and the Arabs incongruously cast as Jews.
_Lawrence of Arabia_ is layered with such understated allusions. As Lawrence enters Cairo, whose deafening cacophony and crowds contrast harshly with the stillness and solitude of the desert, he is followed by an officer on a motorcycle, an officer whose voice we hear but whose face we never see. As he leaves Damascus another man on a motorcycle passes him, leaving Lawrence in his dust. We see him fading away, in the distance. Both are linked to the motorcycle which kills Lawrence, and both are harbingers of his ultimate doom. The motorcycles relate to another theme whose recurrence helps bind the film together, that of the constant and jarring juxtaposition of the world of machines and the world of the desert, which almost always results in chaos and death, as when the Turkish planes attack Feisal's camp as Lawrence arrives, or the absurd horror of the broken trains spilling their mechanical guts across the pristine cleanliness of the desert, or the slaughter of the Arabs before the Turkish guns at Medina. Another interesting touch is the strong use of color: the Arabs in blue, the British in Khaki, Dryden the diplomat (it goes without saying) in gray, Lawrence always in unearthly white (which gets symbolically dirtier as he approaches Cairo after taking Aqaba). Even when Lawrence wears a uniform as he attempts to become an ordinary man after Deraa, we can rest assured: the uniform belongs to *another man.*
Another way Lean keeps the movie from sprawling from his grasp is his use of the small. Details provide moments of transcendent clarity, like the clanking of kitchen utensils in the Turkish column moments before it is wiped out by Lawrence's cutthroats, or Lawrence's goggles hanging from the bush after his death. Muscular personalities, brilliant acting, an unforgettable score and an often underappreciated script complete a movie of staggering emotional power.
_Lawrence of Arabia_ is the finest work of an artist of almost terrifying skill. No greater homage can be paid to Lean than to say that he made a sweeping film which is almost too subtle to understand, yet so powerful that it does not need to be understood.
Copyright 1998 Michael A. Turton
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
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Related links: index of all rec.arts.movies.reviews reviews


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| DOSE: T+ 0:00 |
2 tablets |
oral |
MDMA |
(pill / tablet) |
| T+ 1:45 |
2 tablets |
oral |
MDMA |
(pill / tablet) |
| T+ 3:00 |
1 tablet |
oral |
MDMA |
(pill / tablet) |
| T+ 5:00 |
2 tablets |
oral |
MDMA |
(pill / tablet) |
Having previously ingested up-to 4 pills of known oomph before, I considered myself ready to ascend to the higher realms of MDMA consumption. This brash cockiness was alas my downfall as the potency of my roll was indeed far too high in retrospect.
The pills, which I ate with my friend Dave, were renowned for being potent and highly hallucinogenic (possibly even leading me to believe the it was MDA) from personal experience and the word of others.
In trips gone by we had noticed that these particular pills were much more euphoric and gave an orgasmic feeling throughout the trip from all over the body. Especially when moving the legs.
The week prior I had been scouring over the internet to ascertain as much information I could concerning the effects and mal-effects of the drug and so was in a highly anticipative mood. On the day of the trip Dave and I had wandered over to a “friends” house to sell him some of the contraband. To our delight we arrived to see him rolling and megalomaniacal. As Dave pulled out his sack of 50 pills “the friend” snatched at them and proceed to rob him and punch him in the face, acquiring around 30 pills. The door was then slammed in our faces and we were never to see the pills again – revenge was sought but it’s irrelevant.
As we walked to the bus stop - defeated - we vowed not to let this get to us and that we would merely take 1 pill as to alleviate the trauma endured. This pretty much outlines our mindset, which was of course very shitty.
We got into my house – where we normally rolled – and waited till everybody else in the house was sound asleep, distant from our ecstasy adventures. We set about and ate 1. The acrid taste was sickening, but I got it down me. We then talked for about five minutes and decided that as we had around 20 left we might as well take 2. So we repeated the arduous act of swallowing washing up powder and sat back and waited for the results.
At T:00:30 I noticed the first effects – excitement and anxiety entwined in a very childlike and magical sensation, I noticed my pupils had already dilated and I put this down to my fast metabolism and the strength of the pills. Dave by then had felt no effect.
Fast-forward to T:01:00 and we by now were both now peaking the come-up (the best part about it). Everything became racy and stupendous, from inanimate objects such as keyboards to even our own voices, which became high pitched and fast. We decided to record such marvel and set-up a tape recorder (greatly recommended). As usual we turned off the lights, lay in our respective beds, me lying on my stomach, and Dave on his side.  Thus creating essence of creativity, which to us anyway, is the goal of our entheogenic quests.
We carried that on for around fifteen minutes, taking advantage of the ludicrous thought patterns we had incurred and decided that after all, tonight was going to be marvellous.
As usual we discarded the task of notation and embraced the idea of going outside for a brisk walk in my fields at near 1.a.m. on a cold English morn. As we reached the backdoor we stood side-by-side looking at each other, observing our alert eyes and jittery disposition. So we dropped two more.
T:01:45 This time they went down like good old PG Tips, and my obsessive infatuation with exceeding the boundaries of psychoactives became quenched, or at least at this point equalled.
Outside was warm, beautiful and my back garden (which I have lived in since I was born) brought back a multitude of nostalgia. For brief moments I cared to regress to my childhood and was caught gleefully skipping the lengths of the grass. In reality the weather was atrocious and it was bitter February night, but owing to my drug intake, this was irrelevant.
We hiked over to the fields and gazed to the moon, which was full and also was to my surprise was on fire. There was a very distinct blue flame rising above from it, and it flickered with the wind. Even when I blinked and rubbed my eyes like they do in cartoons the flame remained, and did so for the next few days. Call it my guide or call it a reaction in the brain the flame still became a figure of stability for me, which I could turn to later on in times of adversity to remind of the good I was feeling.
We then reached a long track that divided to fields. To picture it, imagine a “soccer” or football field, the halfway line being the track, each half being a field. We proceeded to stand around 10 feet away from the track and stared at each other in the light of the lit moon to hallucinate. The visuals came instantaneously for both of us as the figure of Dave’s body raced backwards and forwards, as if he were being catapulted toward me but not hitting me then immediately reverting to his original position. Like “next frame” kind of.
Another hallucinations was him just standing there, then suddenly (again next frame) both of his arms would be unnaturally at right angles with his torso, as if adopting a crucifixion pose. Quite surprisingly these very powerful, full-blown hallucinations were off a mere two tabs, the other two had not yet had an effect.
We carried on walking down the track till we came to a bridge, we were talking to each other and I turned my head to look at him and he stopped still (visually) but carried on speaking. I stopped, looking at the frozen image of him, as his voice grew weaker, then again next frame I saw that he had moved some 2 metres in front of me. It was like a computer glitch had transcended into my vision. The last two tabs were kicking in. I felt the racy, speedy effect of the come up again and begged that we turned back.
We had walked quite a while for about 30 minutes so in a more ecstatic state of mind it was only going to take us 30 seconds to get back. In fits of renewed energy from the latest does and just sheer excitement I offered Dave a race back to my garden. We began to run and my clouded up chest (owing to chronic MJ inhalation) was gone and I was able to run like a demon. We ran about 500m, which was in fact all we had actually walked and as we stopped we found that we weren’t out of breath. Despite breaking the world land speed record.
Back in the garden we went into my conservatory, which is situated at the back of the garden. We stuck on some music that would satisfy our mood – Supercat – Too Greedy. There was some water there from earlier that day, and being the obsessive bastards we are we ate another 1 at T:03:00, declaring it to DEFINTELY be the last.
This is where the memories start to get real sketchy. The other two had not yet peaked, and we ingested yet another disco-biscuit, (or lectroom as it is known around these parts). I can remember looking at the circulator fan – made of five spindles - and seeing the normally rigid pieces of wood oscillate with the music, and effervesce all sorts of multi-coloured bubbles.
About 1hour must have passed we just sat there not saying much, when I looked out into the now dark abyss of my back garden and saw what was in reality a towel on a washing line, and saw a man hanging. The vision construed fear in me and I began to have a psychedelic crisis, with all the trademarks. The empathic nature of the drug meant that when I relayed the information of corpse only metres away from our position to Dave, he completely agreed. We stayed there for a long while tripping our tits off, enjoying the physical body sensations, but growing weary of the hallucinations. However, as I looked up and saw the moon aflame I remembered the good times, and that I was only on MDMA (which I had forgotten) and valiantly strode back into the house.
For some unknown reason as we sat at the dinner table rolling, frying or whatever I proposed that we take 2 more, as the effects were likely to wear off soon (so I thought). We did, (T:05:00).
This is where I cannot remember a THING. I can remember VERY VAGUELY us both sitting on a bed talking complete nonsense, immersed in UTTER CONFUSION.
That’s all I can remember of the night. We woke up around 11.a.m having gone to sleep at God knows when to the proposition of a good ‘ol English fry up (except black pudding).
I had a ball of phlegm lodged in my Adams apple (no pun intended) that I was too feeble to cough out. I felt really dirty and weak, and looked it too. I stunk of sweat like I had been wearing the same clothes for days, and every time I got up I felt my stomach turn.
As part of therapy Dave and I retraced our steps from the night before and reminisced of our mad visuals. But it was painful to move quickly. The day was long, and was very typical burnout hangover, except greatly magnified. Mentally I was dull, and could not muster up any sort of creative output. My speech was fucked, and voice strained.  The day passed and I went to bed and dreamt lucidly with no apparent meaning (I usually try to interpret my own dreams with a bit of Freudian literature).
The next day (the day after the day after the experience) I was completely refreshed and my deep negative feelings had completely changed to profound positive feelings, mainly as I found a way to describe what had happened and had metaprogrammed the event. By the way of a poem.
Today’s sorrow is never tomorrow,
As the light will rise at dawn.
And the sickness placed upon us,
Will not be there for more.
Just an inkling of an idea,
A bright spark to say the least.
Gives me the freedom,
Me the power,
To kill the seventh beast.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


NAME¶
sql-lint - Lint MySQL files.
SYNOPSIS¶
sql-lint [OPTION]…
DESCRIPTION¶
-V, –version
output the version number
-f, –file
The .sql file to lint
-q, –query
The query to lint
-v, –verbose
Brings back information on the what it’s linting and the tokens generated
–host
The host for the MySQL server connection
–user
The user for the MySQL server connection
–password
The password for the MySQL server connection
-h, –help
Output usage information


We are a group of Kingdom Coders.
An avid follower of the kingdom and a lover of the code. Founder of HelpIsOnTheWay.co.uk UX & UI
The man under the bonnet. Web-backend Developer
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Class: Innsights::Config::Base
- Inherits:
-
Object
- Object
- Innsights::Config::Base
- Includes:
- Helpers::Config
- Defined in:
- lib/innsights/config/base.rb
Overview
Parent class that holds the basic DSL information and how to setup a report within a controller or model
Direct Known Subclasses
Instance Attribute Summary (collapse)
-
- (Object) condition
Returns the value of attribute condition.
-
- (String, Symbol) created_at_method
timestamp attribute of the watched class.
-
- (Hash) metrics
hash of metrics where the key is the name of the metric, and the value is the method of the record that gets the metric.
-
- (String, Symbol) name
report name being sent to Service.
-
- (Object) report_group
Returns the value of attribute report_group.
-
- (String, Symbol) report_user
attribute of the watched class.
Instance Method Summary (collapse)
- - (Object) created_at
- - (Object) group
-
- (Object) measure(name, options = {})
DSL attribute that sets any number of metrics measured in the given report optionally receives the :with option with the name of the method to call.
-
- (Object) report(name, options = {})
DSL attribute to set the report name optionally receives an if condition block that evaluates whether or not to send the report.
-
- (Object) run(instance)
Creates a prepared report for the service and runs it.
-
- (Proc) setup(receiver)
Sets up the configured report and returns the prepared proc for callback works for either active_record style callbacks or after_filters.
-
- (Object) user($1(value, &block))
DSL method that takes the $1 value, method name or eval block and sets the $2 property.
-
- (False) valid_for_push?
By default all reports are invalid for push.
Methods included from Helpers::Config
Instance Attribute Details
- (Object) condition
Returns the value of attribute condition
12 13 14 |
# File 'lib/innsights/config/base.rb', line 12 def condition @condition end |
- (String, Symbol) created_at_method
timestamp attribute of the watched class
9 10 11 |
# File 'lib/innsights/config/base.rb', line 9 def created_at_method @created_at_method end |
- (Hash) metrics
hash of metrics where the key is the name of the metric, and the value is the method of the record that gets the metric
9 10 11 |
# File 'lib/innsights/config/base.rb', line 9 def metrics @metrics end |
- (String, Symbol) name
report name being sent to Service
9 10 11 |
# File 'lib/innsights/config/base.rb', line 9 def name @name end |
- (Object) report_group
Returns the value of attribute report_group
12 13 14 |
# File 'lib/innsights/config/base.rb', line 12 def report_group @report_group end |
- (String, Symbol) report_user
attribute of the watched class
9 10 11 |
# File 'lib/innsights/config/base.rb', line 9 def report_user @report_user end |
Instance Method Details
- (Object) created_at
19 |
# File 'lib/innsights/config/base.rb', line 19 dsl :created_at, :created_at_method |
- (Object) group
18 |
# File 'lib/innsights/config/base.rb', line 18 dsl :group, :report_group |
- (Object) measure(name, options = {})
DSL attribute that sets any number of metrics measured in the given report optionally receives the :with option with the name of the method to call
63 64 65 66 67 |
# File 'lib/innsights/config/base.rb', line 63 def measure(name, ={}) ||= {with: name} metrics.merge!({name.to_sym => [:with]}) self end |
- (Object) report(name, options = {})
DSL attribute to set the report name optionally receives an if condition block that evaluates whether or not to send the report
45 46 47 48 49 |
# File 'lib/innsights/config/base.rb', line 45 def report(name, ={}) @name = name @condition = [:if] self end |
- (Object) run(instance)
Creates a prepared report for the service and runs it
30 31 32 33 |
# File 'lib/innsights/config/base.rb', line 30 def run(instance) instance = Innsights::Fetchers::Record.new(instance, self) Innsights::Report.new(instance.name, instance.).run if instance.run? end |
- (Proc) setup(receiver)
Sets up the configured report and returns the prepared proc for callback works for either active_record style callbacks or after_filters
78 79 80 81 82 83 84 85 |
# File 'lib/innsights/config/base.rb', line 78 def setup(receiver) Innsights.reports << self receiver.cattr_accessor :innsights_reports unless receiver.respond_to?(:insights_reports) receiver.innsights_reports ||= {} receiver.innsights_reports[name] = self name = self.name lambda {|instance| innsights_reports[name].run(instance) } end |
- (Object) user($1(value, &block))
DSL method that takes the $1 value, method name or eval block and sets the $2 property
17 |
# File 'lib/innsights/config/base.rb', line 17 dsl :user, :report_user |
- (False) valid_for_push?
By default all reports are invalid for push
90 91 92 |
# File 'lib/innsights/config/base.rb', line 90 def valid_for_push? false end |


Track Suggester
Do you like making pretty things?
--Select--
Yes
No
I'm indifferent
Do you like solving complex logic problems?
--Select--
Yes
No
How are your organizational skills?
--Select--
Perfect
Terrible
Ok
How are you feeling today?
--Select--
Great
Moderate
Dreadful
Do you believe hamburgers should be actually from ham rather than beef?
--Select--
Yes. I like my food nomenclature to be sensible
No. I just can't accept that that world view.
Why are you asking this?
Submit my answers
Clear my results


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Howdy! Welcome to connichiwah!
Connichiwah is the easiest way to share the stuff you like online.
This super-ultra-quick tutorial will show you how to use all of the features of connichiwah, and will get you started sharing with friends.
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Double Degree in maths and Computer Science by the University of Granada (UGR), Master´s Degree in Information Security by the International University of La Rioja (UNIR), CPHE Certified, and PhD Student by the University of Granada. Santiago works as a Cybersecurity and Distributed Ledger Technologies Researcher at Tecnalia Research & Innovation in Bilbao, Spain.
Pentesting, Privacy, CTFs, Honeypots, Cryptography, Databases, Web Security, Forensics...
Git, Python, C, C++, Bash, assembler, Node, Go, Java, R...
Advanced knowledge in Distributed Ledger Technologies such as Hyperledger, Ethereum, IOTA...
Security in industrial network, involving SCADA systemas, RTUs and industrial components
It was my second web project and it let me learn a lot of stuff about web development, no-SQL databases and python in general. The project is an unfinished photography social network.
Check it outHoneynet deployment in the UGR network for data and malware analysis. This project corresponds to my Final Degree Project.


Interested in becoming a partner? Email us at<EMAIL_ADDRESS>{% extends "base.html" %} {% load static %} {% block title %} MADcon || MAD {% endblock title %} {% block madcon_tab %}active{% endblock %} {% block css %} {% endblock %} {% block content %}
At the core of MAD is our drive to help those learn, develop, and grow. These workshops symbolize those ideals and bring the best and brightest from the industry to make you the best you can be.
Teach a WorkshopMAD gives students the opportunity to show off their projects they've made and to potentially win a prize.
Apply for ShowcaseThis is ultimately a conference, which you can meet new people from industry or from campus to help you change and empower the world.
RegisterNo, we are a developers conference.
All UT Austin students are allowed to attend. You will be notified in late January.
Nothing, it's completely free.
Just yourself, your computer, and your conference badge.
Nope, there will be courses for both beginners and advanced folks.
Email us at mad@cs.utexas.edu


this implements a file-based ‘file index’, an simple index of all of the reachable commits in a repo, along with the parents and which files were modified during each commit
this class looks for a file named ’[.git]/file-index’, generated via:
git log —pretty=oneline —name-only —parents —reverse —all > file-index
for this to work properly, you’ll want to add the following as a post-receive hook to keep the index up to date
git log —pretty=oneline —name-only —parents —reverse [old-rev]..[new-rev] >> file-index
converted from the gitrb project
authors:
Matthias Lederhofer<EMAIL_ADDRESS>Simon 'corecode' Schubert<EMAIL_ADDRESS>Scott Chacon<EMAIL_ADDRESS>provides native ruby access to git objects and pack files
Required Files
- benchmark
Classes and Modules
- MODULE Grit


{{extend 'layout.html'}}
| You can contact us through our two public google groups: opentreeoflife and opentreeoflife-software. | |
| All of our software is on GitHub, and you can leave bug reports and feature request as an issue in our feedback repo. | |
| The developer team hangs out at IRC: #opentreeoflife on Freenode. Clicking the button at left will join the channel as user guest, using the web-based KiwiIRC client. This is a logged channel. |


Documentation by YARD 0.9.5
Alphabetic Index
File Listing
README
adjuster
boundary
Home
maker
narita
optparse_vs_thor
README_ja
relax_Al
relax_res
CODE_OF_CONDUCT
Namespace Listing A-Z
Top Level Namespace
B
Bar
Baz
Boundary
BoundaryModelAdjuster
BoundaryModelMaker
BoundaryMove
BoundaryView
C
CLI
(Boundary)
Command
(Boundary)
F
Foo


| Apartment ID | Stairway | Ownership Date | Is rented out | Rented since | Residents | |
|---|---|---|---|---|---|---|
| {{ apartment.apartmentId }} | {{ apartment.stairway }} | {{ apartment.ownershipDate }} | {{ apartment.isRented | checkmark }} | {{ apartment.rentedSinceDate }} | {{ resident.name }} , | Edit |


Diagnostics packages¶
AMWG diagnostics¶
Internal resources:
Diagnostics from beta0 simulations:
On Edison, the AMWG OBS data are available here:
/global/project/projectdirs/acme/inputdata/amwg_data
E3SM diagnostics¶
See the documentation here and the source code here
Examples: DECK Simulations (internal)
ARM diagnostics¶
A Python based ARM data-oriented diagnostics package for climate model evaluation.


LANG_EMAIL_USAGE=E-Mail Usage
LANG_SHOW_USAGE=Show usage from
LANG_TODAY=Today
LANG_THIS_MONTH=This month
LANG_THIS_MONTH_EXCLUDING=This month, excluding today
LANG_COUNT_NOTE=Note: Each delivery attempt is counted, including retries.
LANG_SENDER_NOTE=Sender: The 'From' value set in the email header. This value should not be considered accurate as a sender can specify any value they wish.
LANG_AUTH_NOTE=Authentication: If smtp authentication is used, this will show the login name used. Scripts will show the owner of the script. Can be considered accurate.
LANG_PATH_NOTE=Path: If the email was generated from a script, the path value will show the working directory the script was in. An email in the spool will have a path value of "retry" for each attempt.


This repository does not pretend to give you all answers for LinkedIn questions, rather it’s a starting guide to help you prepare for the LinkedIn skills quiz and to know what to expect in the main exam or which areas to target in your exam preparations. Should you have found some incorrect answers, or want to contribute your answers, please feel free to create any PR changes - all are welcome!
| Pluralsight IQ Skill quiz | Status |
|---|---|
| Angular | ok |
| Aws Big Data | ok |
| Aws Machine Learning | ok |
| Building Websites with HTML, CSS, and JavaScript | ok |
| Java | ok |
| Mysql | ok |
| Powershell | non-offical |
| Python | ok |
| Linkedin-quiz-questions | Status |
|---|---|
| Adobe-Illustrator | answers required |
| Adobe-Photoshop | answers required |
| Agile Methodologies | with answers |
| Android | answers required |
| AngularJs 🔥 | answers required |
| AWS | answers required |
| AWS-Lambda :fire: | with answers |
| Bash | partially answered |
| C# | answers required |
| C++ | with answers |
| CSS | with answers |
| Django | with answers |
| .NET Framework | partially answered |
| Git :star: | with answers |
| Google Analytics | answers required |
| Google Cloud Platform (GCP) | with answers |
| Hadoop | answers required |
| HTML | with answers |
| Java | with answers |
| Javascript | partially answered |
| jQuery :open_mouth: | with answers |
| JSON | with answers |
| Machine Learning | answers required |
| Kotlin | NO question and NO answers yet |
| MATLAB | with answers |
| Maven :fire: | with answers |
| Microsoft Azure | with answers |
| Microsoft Excel | with answers |
| Microsoft Power BI | answers required |
| Microsoft Power Point | partially answered |
| Microsoft Project | answers required |
| Microsoft Word | with answers |
| MongoDB :green_heart: | with answers |
| MySQL | answers required |
| node.js | with answers |
| NoSQL | with answers |
| objective-c | partially answered |
| OOP | with answers |
| PHP | partially answered |
| Python | with answers |
| R | partially answered |
| React.js :rose: | with answers |
| REST API :+1: | partially answered |
| Scala | answers required |
| Search Engine Optimization (SEO) | partially answered |
| SharePoint | with answers |
| Swift | with answers |
| Transact-SQL (T-SQL) | with answers |
| Windows Server | partially answered |
| WordPress | partially answered |
| XML | answers required |
We recommend to format files using Prettier code formatter. Prettier comes installed with the IDE Vscode which we recommend for preparing the md files. It works on all OS. If you want to run it independently, get npm and:
Thanks goes to these wonderful people (emoji key):
This project follows the all-contributors specification. Contributions of any kind welcome!


{% load static %}
All Copyrights Reserved by KOWI LIFESTYLES
-> 🔥 {{quantity.quantsets}} sets x {{quantity.quantreps}} reps
Burned : 300Kcal
To Burn : 800Kcal


|
Bullet Collision Detection & Physics Library
|
#include "BulletCollision/CollisionShapes/btConvexShape.h"
#include "BulletCollision/BroadphaseCollision/btBroadphaseProxy.h"
Go to the source code of this file.
Classes | |
| class | btConvex2dShape |
| The btConvex2dShape allows to use arbitrary convex shapes as 2d convex shapes, with the Z component assumed to be 0. More... | |


BrowserStack Support¶
Contents
Enabling BrowserStack support¶
Testing with BrowserStack can be configured for a project in
<test_package>/config/browserstack.py
. To enable BrowserStack support, first
set BrowserStackConfig.ENABLE
to True
:
class BrowserStackConfig(browserstack.BrowserStackConfig):
ENABLE = True
USERNAME = os.getenv('BROWSERSTACK_USERNAME', '')
ACCESS_KEY = os.getenv('BROWSERSTACK_ACCESS_KEY', '')
Next, you’ll need to set the following environment variables on your machine:
BROWSERSTACK_USERNAME
: BrowserStack account username
BROWSERSTACK_ACCESS_KEY
: The access key for the above account
Both of these values can be found on the BrowserStack Automate dashboard. You can add the following to your
.bashrc
file (replacing {USERNAME}
and {ACCESS_KEY}
with the actual
values):
export BROWSERSTACK_USERNAME='{USERNAME}'
export BROWSERSTACK_ACCESS_KEY='{ACCESS_KEY}'
Note
If for whatever reason you don’t want to use environment variables for these values, you can just assign them directly:
class BrowserStackConfig(browserstack.BrowserStackConfig):
ENABLE = True
USERNAME = '{USERNAME}'
ACCESS_KEY = '{ACCESS_KEY}'
However, it is not recommended to store credentials in a way that might be visible to users who should not have access, so using environment variables would be a more secure approach.
Running tests with BrowserStack¶
After enabling and configuring BrowserStack, use the --browserstack
(or
-B
) command line argument to run tests on BrowserStack instead of running
locally. Some examples:
<test_package> --browserstack
<test_package> --module <test_module> --browserstack
<test_package> --test <TestClass> --browserstack
<test_package> --browser <browser> --browserstack
Configuring Browsers¶
By default, BrowserStack tests are generated for Firefox and Chrome. Additional
browsers can be enabled in <test_package>/config/browserstack.py
. For
example, to enable test cases for Internet Explorer, set Browsers.IE
to
True
in BrowserStackConfig.ENABLED_BROWSERS
:
class BrowserStackConfig(browserstack.BrowserStackConfig):
...
ENABLED_BROWSERS = {
Browsers.FIREFOX: True,
Browsers.CHROME: True,
Browsers.SAFARI: False,
Browsers.IE: True,
Browsers.EDGE: False,
Browsers.CHROME_MOBILE: False,
}
Additional Configurations¶
BrowserStack tests support additional configurations using the
BrowserStackConfig.BS_CAPABILITIES
dictionary. For a list of BrowserStack’s
configurable capabilities, see their capabilities documentation.
Rename the Project¶
By default, the project name is set to the test package name. This can be
reconfigured by setting 'project'
to the desired name in BrowserStackConfig.BS_CAPABILITIES
:
BS_CAPABILITIES = {
...
'project': 'Custom Name',
...
}
Specifying the Build Name¶
BrowserStack supports grouping related project tests under a build name. To specify the build name for the group of tests being run:
<test_package> <args> --browserstack --build <name>
Note: Quotation marks must be used for build names containing spaces (e.g.
--build 'Example Build'
).
Enabling Video¶
Video recording can be enabled for tests run on BrowserStack by setting
'browserstack.video'
to True
in BrowserStackConfig.BS_CAPABILITIES
:
BS_CAPABILITIES = {
...
'browserstack.video': True,
...
}
This config option is set to False
by default as it slows down test
execution, but it can be useful to see what’s happening while testing.
To view the recorded videos, go to https://automate.browserstack.com and select the test on the left column.
Command Line Arguments¶
The video configuration can be overridden by using the --video
or
--no-video
arguments.
To enable video recording:
<test_package> <args> --browserstack --video
To disable video recording:
<test_package> <args> --browserstack --no-video


tf_ops¶
Functions for building tensorflow computational graph models.
-
tf_ops.
batch_normalize
(tensor_in, epsilon=1e-05, decay=0.999)[source]¶ Batch Normalization: Batch Normalization Accelerating Deep Network Training by Reducing Internal Covariate Shift
An exponential moving average of means and variances in calculated to estimate sample mean and sample variance for evaluations. For testing pair placeholder is_training with [0] in feed_dict. For training pair placeholder is_training with [1] in feed_dict. Example:
Let train = 1 for training and train = 0 for evaluation
bn_deciders = {decider:[train] for decider in tf.get_collection('bn_deciders')} feed_dict.update(bn_deciders)
During training the running statistics are updated, and batch statistics are used for normalization. During testing the running statistics are not updated, and running statistics are used for normalization.
Parameters: - tensor_in – (tf.Tensor) Input Tensor.
- epsilon – (float) A float number to avoid being divided by 0.
- decay – (float) For exponential decay estimate of running mean and variance.
Returns: (tf.Tensor) Tensor with variance bounded by a unit and mean of zero according to the batch.
-
tf_ops.
batch_softmax_dist_loss
(truth, h, dimension, scale_range=1.0)[source]¶ This function paired with a tensorflow optimizer is multinomial logistic regression. It is designed for cotegorical predictions.
Parameters: - truth – (tf.Tensor) A tensorflow vector tensor of integer class labels.
- h – (tf.Tensor) A placeholder if doing simple multinomial logistic regression, or the output of some neural network.
- dimension – (int) Number of classes in output distribution.
- scale_range – (float) For scaling the weight matrices (by default weights are initialized two 1/sqrt(fan_in)) for tanh activation and sqrt(2/fan_in) for relu activation.
Returns: (tf.Tensor, shape = [MB, Sequence_length]) Cross-entropy of true distribution vs. predicted distribution.
-
tf_ops.
bidir_lm_rnn
(x, t, token_embed, layers, seq_len=None, context_vector=None, cell=<class 'tensorflow.python.ops.rnn_cell_impl.BasicLSTMCell'>)[source]¶ Token level bidirectional LSTM language model that uses a sentence level context vector.
Parameters: - x – Input to rnn
- t – Targets for language model predictions (typically next token in sequence)
- token_embed – (tensor) MB X ALPHABET_SIZE.
- layers – A list of hidden layer sizes for stacked lstm
- seq_len – A 1D tensor of mini-batch size for variable length sequences
- context_vector – (tensor) MB X 2*CONTEXT_LSTM_OUTPUT_DIM. Optional context to append to each token embedding
- cell – (class) A tensorflow RNNCell sub-class
Returns: (tensor) tuple-token_losses , (list of tensors) hidden_states, (tensor) final_hidden
-
tf_ops.
diag_mvn_loss
(truth, h, scale_range=1.0, variance_floor=0.1)[source]¶ Takes the output of a neural network after it’s last activation, performs an affine transform. It returns the mahalonobis distances between the targets and the result of the affine transformation, according to a parametrized Normal distribution with diagonal covariance. The log of the determinant of the parametrized covariance matrix is meant to be minimized to avoid a trivial optimization.
Parameters: - truth – (tf.Tensor) The targets for this minibatch.
- h – (tf.Tensor) The output of dnn. (Here the output of dnn , h, is assumed to be the same dimension as truth)
- scale_range – (float) For scaling the weight matrices (by default weights are initialized two 1/sqrt(fan_in)) for tanh activation and sqrt(2/fan_in) for relu activation.
- variance_floor – (float, positive) To ensure model doesn’t find trivial optimization.
Returns: (tf.Tensor shape=[MB X D], tf.Tensor shape=[MB X 1]) Loss matrix, log_of_determinants of covariance matrices.
-
tf_ops.
dnn
(x, layers=[100, 408], act=<function relu>, scale_range=1.0, norm=None, keep_prob=None, name='nnet')[source]¶ An arbitrarily deep neural network. Output has non-linear activation.
Parameters: - x – (tf.tensor) Input to the network.
- layers – List of integer sizes of network layers.
- act – Activation function to produce hidden layers of neural network.
- scale_range – (float) Scaling factor for initial range of weights (Set to 1/sqrt(fan_in) for tanh, sqrt(2/fan_in) for relu.
- norm – Normalization function. Could be layer_norm or other function that retains shape of tensor.
- keep_prob – (float) The percent of nodes to keep in dropout layers.
- name – (str) For naming and variable scope.
Returns: (tf.Tensor) Output of neural net. This will be just following a non linear transform, so that final activation has not been applied.
-
tf_ops.
dropout
(tensor_in, prob)[source]¶ Adds dropout node. Dropout A Simple Way to Prevent Neural Networks from Overfitting
Parameters: - tensor_in – Input tensor.
- prob – The percent of units to keep.
Returns: Tensor of the same shape of tensor_in.
-
tf_ops.
eyed_mvn_loss
(truth, h, scale_range=1.0)[source]¶ This function takes the output of a neural network after it’s last activation, performs an affine transform, and returns the squared error of this result and the target.
Parameters: - truth – A tensor of target vectors.
- h – The output of a neural network post activation.
- scale_range – For scaling the weight matrices (by default weights are initialized two 1/sqrt(fan_in)) for
tanh activation and sqrt(2/fan_in) for relu activation. :return: (tf.Tensor[MB X D], None) squared_error, None
-
tf_ops.
fan_scale
(initrange, activation, tensor_in)[source]¶ Creates a scaling factor for weight initialization according to best practices.
Parameters: - initrange – Scaling in addition to fan_in scale.
- activation – A tensorflow non-linear activation function
- tensor_in – Input tensor to layer of network to scale weights for.
Returns: (float) scaling factor for weight initialization.
-
tf_ops.
full_mvn_loss
(truth, h)[source]¶ Takes the output of a neural network after it’s last activation, performs an affine transform. It returns the mahalonobis distances between the targets and the result of the affine transformation, according to a parametrized Normal distribution. The log of the determinant of the parametrized covariance matrix is meant to be minimized to avoid a trivial optimization.
Parameters: - truth – Actual datapoints to compare against learned distribution
- h – output of neural network (after last non-linear transform)
Returns: (tf.Tensor[MB X D], tf.Tensor[MB X 1]) Loss matrix, log_of_determinants of covariance matrices.
-
tf_ops.
ident
(tensor_in)[source]¶ The identity function
Parameters: tensor_in – Input to operation. Returns: tensor_in
-
tf_ops.
join_multivariate_inputs
(feature_spec, specs, embedding_ratio, max_embedding, min_embedding)[source]¶ Makes placeholders for all input data, performs a lookup on an embedding matrix for each categorical feature, and concatenates the resulting real-valued vectors from individual features into a single vector for each data point in the batch.
Parameters: - feature_spec – A dict {categorical: [c1, c2, …, cp], continuous:[f1, f2, …,fk] which lists which features to use as categorical and continuous inputs to the model. c1, …, cp, f1, …,fk should match a key in specs.
- specs – A python dict containing information about which indices in the incoming data point correspond to which features. Entries for continuous features list the indices for the feature, while entries for categorical features contain a dictionary- {‘index’: i, ‘num_classes’: c}, where i and c are the index into the datapoint, and number of distinct categories for the category in question.
- embedding_ratio – Determines size of embedding vectors for each categorical feature: num_classes*embedding_ratio (within limits below)
- max_embedding – A limit on how large an embedding vector can be.
- min_embedding – A limit on how small an embedding vector can be.
Returns: A tuple (x, placeholderdict): (tensor with shape [None, Sum_of_lengths_of_all_continuous_feature_vecs_and_embedding_vecs], dict to store tf placeholders to pair with data, )
-
tf_ops.
layer_norm
(h)[source]¶ Parameters: h – (tensor) Hidden layer of neural network Returns: (tensor) Hidden layer after layer_norm transform
-
tf_ops.
layer_norm_rnn
(inputs, initial_state=None, layers=(10, ), sequence_lengths=None, state_index=-1)[source]¶ Parameters: - inputs – A list with length the number of time steps of longest sequence in the batch. inputs contains matrices of shape=[num_sequences X feature_dimension]
- initial_state – Initialized first hidden states. A tuple of len(layers) tuples of cell and hidden state tensors
- layers – list of number of nodes in each of stacked lstm layers
- sequence_lengths – A vector of sequence lengths of size batch_size
- state_index – If -1, last state is returned, if None all states are returned, if 1, second state is returned.
Returns: hidden_states, current_state
-
tf_ops.
lm_rnn
(x, t, token_embed, layers, seq_len=None, context_vector=None, cell=<class 'tensorflow.python.ops.rnn_cell_impl.BasicLSTMCell'>)[source]¶ Token level LSTM language model that uses a sentence level context vector.
Parameters: - x – (tensor) Input to rnn
- t – (tensor) Targets for language model predictions (typically next token in sequence)
- token_embed – (tensor) MB X ALPHABET_SIZE.
- layers – A list of hidden layer sizes for stacked lstm
- seq_len – A 1D tensor of mini-batch size for variable length sequences
- context_vector – (tensor) MB X 2*CONTEXT_LSTM_OUTPUT_DIM. Optional context to append to each token embedding
- cell – (class) A tensorflow RNNCell sub-class
Returns: (tuple) token_losses (tensor), hidden_states (list of tensors), final_hidden (tensor)
-
tf_ops.
multivariate_loss
(h, loss_spec, placeholder_dict, variance_floor=0.01)[source]¶ Computes a multivariate loss according to loss_spec.
Parameters: - h – Final hidden layer of dnn or rnn. (Post-activation)
- loss_spec –
A tuple of 3-tuples of the form (input_name, loss_function, dimension) where input_name is the same as a target in datadict,
loss_function takes two parameters, a target and prediction, and dimension is the dimension of the target. - placeholder_dict – A dictionary to store placeholder tensors for target values.
- variance_floor – (float) Parameter for diag_mvn_loss.
Return loss_matrix: (MB X concatenated_feature_size Tensor) Contains loss for all contributors for each data point.
-
tf_ops.
softmax_dist_loss
(truth, h, dimension, scale_range=1.0, U=None)[source]¶ This function paired with a tensorflow optimizer is multinomial logistic regression. It is designed for cotegorical predictions.
Parameters: - truth – A tensorflow vector tensor of integer class labels.
- h – A placeholder if doing simple multinomial logistic regression, or the output of some neural network.
- dimension – Number of classes in output distribution.
- scale_range – For scaling the weight matrices (by default weights are initialized two 1/sqrt(fan_in)) for tanh activation and sqrt(2/fan_in) for relu activation.
- U – Optional weight tensor (If you is not provided a new weight tensor is made)
Returns: (Tensor[MB X 1]) Cross-entropy of true distribution vs. predicted distribution.
-
tf_ops.
swapping_rnn
(inputs, initial_state=None, layers=(10, ), sequence_lengths=None, state_index=-1)[source]¶ Parameters: - inputs – A list with length the number of time steps of longest sequence in the batch. inputs contains matrices of shape=[num_sequences X feature_dimension]
- initial_state – Initialized first hidden states. A tuple of len(layers) tuples of cell and hidden state tensors
- layers – list of number of nodes in each of stacked lstm layers
- sequence_lengths – A vector of sequence lengths of size batch_size
- state_index – If -1, last state is returned, if None all states are returned, if 1, second state is returned.
Returns:
-
tf_ops.
true_bptt_rnn
(cell, inputs, initial_state=None, dtype=None, sequence_length=None, scope=None, state_index=1)[source]¶ Creates a recurrent neural network specified by RNNCell cell. The simplest form of RNN network generated is:
state = cell.zero_state(...) outputs = [] for input_ in inputs: output, state = cell(input_, state) outputs.append(output) return (outputs, state)
However, a few other options are available: An initial state can be provided. If the sequence_length vector is provided, dynamic calculation is performed. This method of calculation does not compute the RNN steps past the maximum sequence length of the minibatch (thus saving computational time), and properly propagates the state at an example’s sequence length to the final state output. The dynamic calculation performed is, at time t for batch row b,
(output, state)(b, t) = (t >= sequence_length(b)) ? (zeros(cell.output_size), states(b, sequence_length(b) - 1)) : cell(input(b, t), state(b, t - 1))
Parameters: - cell – An instance of RNNCell.
- inputs – A length T list of inputs, each a tensor of shape [batch_size, input_size].
- initial_state – (optional) An initial state for the RNN. If cell.state_size is an integer, this must be a tensor of appropriate type and shape [batch_size x cell.state_size]. If cell.state_size is a tuple, this should be a tuple of tensors having shapes [batch_size, s] for s in cell.state_size.
- dtype – (optional) The data type for the initial state. Required if initial_state is not provided.
- sequence_length – Specifies the length of each sequence in inputs. An int32 or int64 vector (tensor) size [batch_size], values in [0, T).
- scope – VariableScope for the created subgraph; defaults to “RNN”.
- state_index – (int) If -1 final state is returned, if 1 state after first rnn step is returned. If anything else all states are returned
Returns: A pair (outputs, state) where:
- outputs is a length T list of outputs (one for each input)
- state is the final state or a a length T list of cell states
Raise: TypeError: If cell is not an instance of RNNCell. ValueError: If inputs is None or an empty list, or if the input depth
(column size) cannot be inferred from inputs via shape inference.
-
tf_ops.
weights
(distribution, shape, dtype=tf.float32, initrange=1e-05, seed=None, l2=0.0, name='weights')[source]¶ Wrapper parameterizing common constructions of tf.Variables.
Parameters: - distribution – A string identifying distribution ‘tnorm’ for truncated normal, ‘rnorm’ for random normal, ‘constant’ for constant, ‘uniform’ for uniform.
- shape – Shape of weight tensor.
- dtype – dtype for weights
- initrange – Scales standard normal and trunctated normal, value of constant dist., and range of uniform dist. [-initrange, initrange].
- seed – For reproducible results.
- l2 – Floating point number determining degree of of l2 regularization for these weights in gradient descent update.
- name – For variable scope.
Returns: A tf.Variable.


Painlessly generate high-level visual comparisons of distributions between groups or data sets.
This package is for you if:
flyover
provides utilities to quickly generate and organize plots of distributions split by a grouping variable.
For detailed instructions, see the package website.
This package is largely powered by ggplot2 for building plots, and the awesome trelliscopejs by Ryan Hafen for providing a viewer to navigate them.
devtools::install_github("ataustin/flyover")
library(flyover)
Note that the dependencies are large (especially trelliscopejs) and may take a long time to install.
A typical flyover
workflow has the following steps:
If you are comparing distribtions of variables between an old data process and a new one, your workflow might look like this:
old_data <- read.csv("old-data.csv")
new_data <- read.csv("new-data.csv")
enlist_data(old_data, new_data, names = c("old data", "new data")) %>%
build_plots(flyover_histogram) %>%
build_display(display_name = "histograms", output_dir = "display-hist")
Get started with the articles in the documentation or jump right into the gallery of displays.
If you build a display from the console or as a batch job from an R script, you can point your browser directly at the output directory to render the display. You can also render the display inside an R Markdown document by making the call to build_display
the last line of a code chunk (ensure the output directory specification is a relative file path, or you will get a knitting error).
Please see contribute.md
.


Notts bar launches advent calendar full of drinks for party-goers this Christmas
You can open all the doors at once
by Lynette PinchessA bar has launched an advent calendar where revellers don't have to wait to find out what's behind each door.
The Botanist in West Bridgford has created a wooden calendar for party-goers this Christmas filled with tipples for groups to share.
The 24 mini cocktails come in 50mil silver bottles and the calendar is served at the table. The mix includes the New World Pornstar Martini, Bay Leaf and Apricot Mai Tai and Apricot and Peach Smash.
It's available for group bookings from November 28 to December 24 making it ideal for work parties and friends and family celebrations.
Jack Jolly, at The Botanist, said: "Advent calendars are massively popular and a real treat for adults who start celebrating Christmas right from the moment they open the first calendar door.
"We wanted all of our guests to be able to enjoy this magic of Christmas when they're having their Christmas meals and celebrations at The Botanist."
The limited-edition cocktail calendar costs £75 and should be pre-ordered by parties when booking or ahead of arriving for their reservation.
For more information contact the bar and restaurant, in Bridgford Road, on 0115 704 3700.


Quote: Posted 01/23/08 15:58 (GMT) -- Bromium
Can you Epic Dodge a breath weapon?

Quote: Posted 01/24/08 16:34 (GMT) -- Kail Pendragon
Petrification and other gazes are not affected by anything but immunities instead (or very good saves of course ).


Stencila has it's own language for reproducible, data-drive, research called Mini. An important aspect of reproducibility is readability. Mini aims to be as easy to read and understand as it is to write. Mini is meant to be only slightly more advanced that the expressions that your write in your calculator or into the cell of a spreadsheet
Mini has a simple type system that is similar to most high level languages. Each type can be constructed using literals...
| Type | Example literal |
| null | null |
| boolean | true, false |
| integer | 1, 2, 42 |
| float | 3.13 |
| array | [1, 2, 3] |
| object | { a: 1, b: '2'} |
| my_custom_type | { type: 'my_custom_type', ...} |
Tabular data is an important part of data analysis...
[object Object]
The plot
function takes tabular data, ....
[object Object]
Can set plot options of the Vega-Lite spec....
[object Object]
Or use convieience functions like title
to set options
[object Object]
An important feature of Mini is it's ability to interoperate with other languages. Mini can act as a glue language - for those times when you need to combine the strengths of several languages. For example, you might want to extract some data from a database using Structured Query Language (SQL), then perform a specialised statistical analysis on the data using R, then visualise the results using Mini's built in plotting functions.
Mini makes this possible through alternative execution contexts. Each context knows how to convert values to and from the Mini value types and how to execute snippets of code in the context's native language. Currently, only two execution contexts are supported: the JsContext
(for executing Javascript code in a browser or desktop window) and the NodeContext
(for executing Javascript code within Node.js). The RContext
and PythonContexts
are planned for the 0.26 release with more language contexts following soon.
There are two special functions in Mini for executing code in other languages: call
and run
.
call
functionThe call
function executes code within a function scope. That means that any variables that you declare within that function are local to the function and won't leak into the context's global scope. So, when you type call()
into a cell, your effectively saying to Mini take this code, make it into a function, execute the function, and give me back the value. Here's an example of a simple call
to some Javascript,
let names = ['Hiphop', 'opotamus', ' v ', 'Rhyme', 'noceros'] return names.join('')
Hiphopopotamus v Rhymenoceros
Notice that because we ended the JavaScript code, with a return
statement that the cell has an output. When you call()
some JavaScript code
it's like executing (function(){code})()
. The same is true for other external languages, it's just that the syntax differs.
Just like with other Mini cells, you can assign the output of a call()
to a document variable,
return Math.PI
3.141592653589793
A call to another language is not very useful unless you provide it with some data. This is where Mini's glueing comes in. Let's create an array in Mini,
apple,pear,kiwi
and then use Javascript to join it together,
return 'My favourite fruits: ' + fruits.map((fruit,index) => { return `${index + 1}. ${fruit}` }).join(', ')
My favourite fruits: 1. apple, 2. pear, 3. kiwi
The nice thing about this is that Mini's dependency analysis still works, so you can change the fruits array and the output above will change - try it!
Notice that our Javascript function got supplied an argument called fruits
- which is the same array of strings as in our documentent variable called fruits
. You can also provide named arguments to call,
return my_favourite_fruits[index]
kiwi
Here's an example, that puts this all together with an input, a Javascript call cell and an output to display the result...
The area of a circle can be calculated by a = pi r^2 . So, if the radius of a circle is m, then it's area is: 9852.03456165759 m2.
return Math.PI*Math.pow(r, 2)
9852.03456165759
run
function


Reports code blocks which are unnecessary to the semantics of the program, and can
be replaced by their contents. Code blocks which are the bodies of if, do,
while or for statements will not be reported by this
inspection.
Use the checkbox below if you wish this inspection to ignore code blocks which are used as branches of switch statements.
Powered by InspectionGadgets


--- layout: page title: "404" permalink: /404 ---
Uh Oh! There doesn't appear to be anything here. Sorry about that.
If you've followed a link expecting something to be here, please email me so I can fix it. I'll make sure to send a lot of good karma your way.
If you're so inclined, feel free to check out some of my recent blog posts below:
{% if site.posts.size == 0 %}
Nothing published yet!
{% elsif site.paginate %} {% for post in paginator.posts %} {% include blog-404.html %} {% endfor %} {% if site.paginate %} {% include pagination.html%} {% endif %} {% else %} {% for post in site.posts %} {% include blog-404.html %} {% endfor %} {% endif %}


inappropriate behavior is often laughed off as “boys will be boys,” women face higher conduct standards especially in the workplace. That’s why it’s crucial that, as women, our behavior on the job is beyond reproach. inappropriate behavior is often laughed.
inappropriate behavior is often laughed off as “boys will be boys,” women face higher conduct standards especially in the workplace.
View More DetailsIf you are looking at blank cassettes on the web, you may be very confused at the difference in price. You may see some for as low as $.17 each.


LOAN APPLICATIONS
| S/No. | Loan Id | Application Date | Name | Phone No. | Verification Status | Status | Format |
|---|---|---|---|---|---|---|---|
| 1 | #2841 | 20/3/2019 | John Okoro |<PHONE_NUMBER>1 | Verified | Approved | |
| 2 | #2481 | 20/3/2019 | Kelvin Preye |<PHONE_NUMBER>4 | Verified | Approved | |
| 3 | #2871 | 23/3/2019 | Adamu Mohammed |<PHONE_NUMBER>0 | Verified | Approved | |
| 4 | #2911 | 23/3/2019 | Bolaji Johnson |<PHONE_NUMBER>0 | Verified | Approved | |
| 5 | #2036 | 24/3/2019 | Chris David |<PHONE_NUMBER>1 | Verified | Approved | |
| 6 | #2938 | 22/3/2019 | Nora Pachok |<PHONE_NUMBER> | Unverified | Rejected | |
| 7 | #2901 | 22/3/2019 | Falilat Ahmed |<PHONE_NUMBER>1 | Unverified | Rejected | |
| 8 | #2519 | 23/3/2018 | Ngozi Okonkwo |<PHONE_NUMBER>1 | Unverified | Rejected | |
| 9 | #2291 | 23/3/2018 | Iwule Uche |<PHONE_NUMBER>1 | Unverified | Rejected | |
| 10 | #2391 | 24/3/2018 | Tega Umukoro |<PHONE_NUMBER>1 | Unverified | Rejected | |
| 11 | #2841 | 20/3/2019 | John Okoro |<PHONE_NUMBER>1 | Pending | ||
| 12 | #2481 | 20/3/2019 | Kelvin Preye |<PHONE_NUMBER>4 | Pending | ||
| 13 | #2871 | 23/3/2019 | Adamu Mohammed |<PHONE_NUMBER>0 | Pending | ||
| 14 | #2911 | 23/3/2019 | Bolaji Johnson |<PHONE_NUMBER>0 | Pending | ||
| 15 | #2036 | 24/3/2019 | Chris David |<PHONE_NUMBER>1 | Pending | ||
| 16 | #2938 | 22/3/2019 | Nora Pachok |<PHONE_NUMBER> | Pending | ||
| 17 | #2901 | 22/3/2019 | Falilat Ahmed |<PHONE_NUMBER>1 | Pending | ||
| 18 | #2519 | 23/3/2018 | Ngozi Okonkwo |<PHONE_NUMBER>1 | Pending | ||
| 19 | #2291 | 23/3/2018 | Iwule Uche |<PHONE_NUMBER>1 | Pending | ||
| 20 | #2391 | 24/3/2018 | Tega Umukoro |<PHONE_NUMBER>1 | Pending |


USC strongly promotes interdisciplinary activities within and across departments and schools. RASC research involves participants from a variety of backgrounds, and active synergies and collaboration with a variety of programs, including:
Institute for Creative Technologies
Information Sciences Institute (ISI)
Integrated Media Systems Center
Health Technology Engineering (HTE@USC)
USC Games
Graphics
Center for Interactive Smart Oilfield Technologies