OpenPGP Online
Password for private key:
save the password in a safe place, private key can not be used without password
First name:
Last name:
User email:
Valid for (years):
Key size (strength) in bits:
Public Key:
| Key ID: |
|
| Fingerprint: |
|
| User ID: |
|
| Created: |
|
| Valid until: |
|
| Key size (strength) in bits: |
|
Private Key:
| Key ID: |
|
| Fingerprint: |
|
| User ID: |
|
| Created: |
|
| Valid until: |
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| Key size (strength) in bits: |
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Use your keys:
Text to encrypt or sign:
encrypted text:
signed text:
All operations with keys on this page are made only in the browser without transferring data to the server. You
can view the page code on
app/openPGPOnline/openPGPOnline.js
You can also use
ageyev.github.io/crypto/openpgp/ with
the same functionality.


Match Play. Red leads 5-0 to 11. How should Red play 42?
pips Red=102 White=130
(CorrectAnswer= 0/0, ErrorScore= 0)
This is the continuation of the previous position. Should Red run for home or play quietly?
Ahead in the race logic perhaps says that running might be best but (a) that leaves 21 shots and (b) at best there will be only one return shot.
If Red plays 11/5 then even if the blot on the 22-pt is hit, there will nearly always be return shots.
For once the quiet play is correct. 11/5 is the right move. Running 22/16 is a borderline error.
Ahead in the race logic perhaps says that running might be best but (a) that leaves 21 shots and (b) at best there will be only one return shot.
If Red plays 11/5 then even if the blot on the 22-pt is hit, there will nearly always be return shots.
For once the quiet play is correct. 11/5 is the right move. Running 22/16 is a borderline error.
1. Cubeful 2-ply 11/5 Eq.: -0.214 0.472 0.119 0.002 - 0.528 0.133 0.003 2. Cubeful 2-ply 22/16 Eq.: -0.220 (-0.006) 0.486 0.078 0.001 - 0.514 0.132 0.003 3. Cubeful 0-ply 22/18 11/9 Eq.: -0.363 (-0.149) 0.434 0.080 0.001 - 0.566 0.147 0.004 4. Cubeful 0-ply 11/7 9/7 Eq.: -0.679 (-0.465) 0.385 0.096 0.001 - 0.615 0.216 0.011 5. Cubeful 0-ply 9/7 9/5 Eq.: -0.766 (-0.552) 0.369 0.094 0.001 - 0.631 0.221 0.010


Handlebars Header
This is where the Handlebars template starts
This is where the Handlebars template ends.
This is some text.
Change Text


Tests that url(...) with space-delimited color names as filename segments do not contain color swatches. Bug 106770.


{{< layout}} {{$propositionHeader}}{{/propositionHeader}} {{$pageTitle}}Pick appointment time{{/pageTitle}} {{$header}} {{/header}} {{$main-content}}
Peterborough passport office Aragon Court Northminster Road Peterborough PE1 1QG
We’ve reserved this appointment while you apply. You’ll get an email with the details once you’re finished.
> {{/main-content}} {{/ layout}}


---
title: Bias-Variance Tradeoff
keywords: fastai
sidebar: home_sidebar
summary: "Example with code"
description: "Example with code"
nb_path: "nbs/07_concepts/bias-variance_tradeoff.ipynb"
---
{% raw %}
{% endraw %}
Preface
- It's tempting to think that "bias" refers to the feature selection process. It does not.
- Bias is how bad your model $E(T)$ is at predicting the true value of a parameter $\theta$. (i.e. $E(T)=\theta+bias(\theta)$, and if $bias(\theta)=0$, then $E(T)=\theta$ -- you have an unbiased model)
- Sometimes having bias is good. In machine learning, having a little bias can significantly reduce variance.
High Bias, Low Variance Models
- You have a procedure to generate models. This procedure builds simple models with few features.
- You chose those few features. Why not other features? (it's tempting to think this is "bias", but it's not. Bias how bad your model is at predicting the actual value -- i.e.)
- Since there are few features, changes to the dataset will have limited effects on the parameters of the model -- different models built using this procedure will look similar (low variance)
- Your model may not have enough parameters to learn the real underlying relationships (high bias, underfitting)
Low Bias, High Variance Models
- This represents most machine learning models today.
- You have a procedure to generate models. This procedure builds complex models with many features.
- You did not choose any features. Just throw everything in (low bias)
- Since there are many features, changes to the dataset can have large effects on the parameters of the model -- different models built using this procedure may look very different (high variance)
- Your model may also learn noise that only exists in the training data, but not the real world (overfitting)


Sponsors play a vital role in ensuring HCOMP's continuing success. By keeping registration fees affordable for academic researchers, especially students, sponsorships from corporations, universities, and other institutions help sustain HCOMP's economic viability and proud tradition of strong participation each year.
Whether you want to showcase your technology to the crowdsourcing community or tap into this incredible source of talent, HCOMP is the premier venue for sponsors to reach this unique audience of researchers, industry practitioners, & media, combining social scientists and influencers with technological innovators and adopters.
HCOMP is organized under the aegis of AAAI. To become a sponsor, please contact us at<EMAIL_ADDRESS>or telephone +1<PHONE_NUMBER> (USA).
To increase visibility and publicity for HCOMP presenters and attendees, HCOMP offers a free press pass for credentialed members of the press.
HCOMP offers four sponsorship levels: Platinum, Gold, Silver, and Bronze. Sponsors will be acknowledged in order by contribution level.
Platinum ($10,000 or greater contribution)
- Named event (4-6 available), such as a reception, poster session, student event, or industry panel
- 2 complimentary conference registrations (instead of 1), including all social events and main conference sessions
- Note: Conference registration was $650-850 per person in 2015 (based on date registered; TBD for 2016)
- All benefits of lower tier sponsors (see below)
Gold ($7,500 or greater contribution)
- Complimentary 1/4 black & white ad in AI Magazine
- Acknowledgement at all social events, including receptions, the conference banquet/party, coffee breaks, and student events
- Attendee resume book: all resumes will have the option to access company job descriptions and provide resumes directly as part of registration; interviews can be scheduled in advance with sponsoring companies
- Job descriptions provided to attendees
- All benefits of lower tier sponsors (see below)
Silver ($4,000 or greater contribution)
- 1 complimentary conference registration, including all social events and main conference sessions
- Note: Conference registration was $650-850 per person in 2015 (based on date registered; TBD for 2016)
- Invitation to Sponsors Dinner
- Attendee emails: two emails to all HCOMP16 attendees, one before and one after the conference
- Invitation to exhibit in poster/demo session
- All benefits of lower tier sponsors (see below)
Bronze ($500 or greater contribution)
- Conference packet insert
- Acknowedgement on the conference website, in printed materials, in opening and closing plenary sessions, and in onsite signage, as available.
HCOMP's industry sponsors welcome job applications from the HCOMP community. Please contact sponsors directly via the links below if you are interested in the following roles.
Spare5 (follow link for detailed job postings)
- Office Manager & Executive Assistant
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- Data Scientist, Natural Language
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|
Compile-Time Graph Library
Graph library that is based on metaprogramming
|
#include <is_base_of.h>
Static Public Attributes | |
| constexpr static bool | result |
Checks if TypeList "parent" is in fact parent of another TypeList "derived" "parent" is parent of "derived" if and only if for every class C in "derived", "parent" has parent of C
| parent | Template parameter |
| derived | Template parameter |
Definition at line 38 of file is_base_of.h.
|
staticconstexpr |
Definition at line 39 of file is_base_of.h.


Use this command to arrange the non-minimised windows in a non-overlapped manner, side by side.
Shortcuts
Toolbar:


Suspected serial killer, David West makes u-turn, pleads not guilty
by Ifeanyi NgeremSuspected serial killer, Gracious David West, alleged to have killed more than a dozen Women in different hotels in Rivers State and others, has made a u-turn and pleaded not guilty to the 10-count murder charge leveled against him.
Recall David West had earlier pleaded guilty to nine of the 10-count charge leveled against him.
The Attorney-General and Commissioner for Justice in Rivers, Dr Zaccheus Adango had last week announced appearance for the State, signalling the takeover of the prosecution of the celebrated case from the police.
The Attorney General’s also amended charges for the self-confessed serial killer, David West.


My First paragraph.
this is a paragraph.
this is another paragraph.
This is a paragraph
p1p
p2p
This is a para graph with line breaks


Before Change
AttributeError
If the header is of an unknown type or does not support the reading of the pixel spacing.
try:
if __is_header_nibabel(hdr):
return __get_pixel_spacing_nibabel(hdr)
elif __is_header_pydicom(hdr):
return __get_pixel_spacing_pydicom(hdr)
elif __is_header_itk(hdr):
return __get_pixel_spacing_itk(hdr)
else:
raise Exception()
except Exception:
raise AttributeError("The provided header {} is of unknown type or does not support queries for pixel spacing.".format(type(hdr)))
def get_offset(hdr):
r
Extracts the image offset from an image header.
After Change
def get_pixel_spacing(hdr):
rDepreciated synonym of `~medpy.io.header.get_voxel_spacing`.
warnings.warn("get_pixel_spacing() is depreciated, use set_voxel_spacing() instead", category=DeprecationWarning)
return get_voxel_spacing(hdr)
def get_offset(hdr):
r


phenoptrExamples
contains example code and extended data sets demonstrating the use of the phenoptr package to analyze data from multiple fields.
phenoptr
documentation.phenoptr
contains functions that make it easier to read and analyze data tables and images created by Akoya Biosciences’ inForm® software. phenoptr
and phenoptrExamples
are part of the Akoya Biosciences Phenoptics™ family of Quantitative Pathology Research Solutions.
Installation is from GitHub. Note: this package includes many large files. The entire package contains over 150 MB of data files.
# install.packages("devtools")
devtools::install_github("akoyabio/phenoptrExamples", build_vignettes=TRUE)
The Tutorials demonstrate aggregation of data across multiple fields and slides.
phenoptrExamples
contains selected inForm output from nine images taken from three samples of lung cancer tissue.
The tissue was stained with DAPI counterstain and Opal™ stains and imaged on a Vectra® Polaris™ Automated Quantitative Pathology Imaging System. The MSI images were unmixed to components, segmented and classified with inForm® image analysis software.
The sample cell data includes these phenotypes:
CD8+
(cytotoxic T cell)CD68+
(macrophage)FoxP3+
(regulatory T cell)CK+
(tumor)other
Four files are included for each image:
composite_image.jpg
)cell_seg_data.txt
)binary_seg_maps.tif
)image_with_tissue_seg.jpg
)To see a full list of all included files, use the command list.files(system.file("extdata", "samples", package = "phenoptrExamples"))
.
This table shows the stains used, the epitopes they were bound to, and the colors used to show the stains in the composite and phenotype views.
| Stain | Epitope | Composite | Phenotype |
|---|---|---|---|
| DAPI | Nucleus | Blue | N/A |
| Opal520 | PDL1 | Red | N/A |
| Opal540 | CD8 | Yellow | Yellow |
| Opal570 | FoxP3 | Orange | Orange |
| Opal620 | CD68 | Magenta | Magenta |
| Opal650 | PD1 | Green | N/A |
| Opal690 | CK | Cyan | Cyan |
See the Tutorials and the full phenoptr documentation.


Do you want to make an immediate impact? We'll give you meaningful projects from your first day onward.
Apply Today


An illustrated, infographic map showcasing the independent cafés situated around Canterbury's city center
Concept created in collaboration with Laura Azzopardi, Jadesola AB and Harry Duffy.


Exercises: Visual Information
Evaluate these two examples. They are also available as image files on the workshop website - use the NoCoffee Chrome extension or the Colblinder Color Blindness Simulator to check the use of colors in each example.
Example 1: The Trillion Dollar Tech Summit chart
Think about:
How can this information be represented differently?
Annotate the image with suggestions for improvements.
Example 2: Glucose Tracker App
Think about:
- What do the colors mean?
- Which parts are interactive?
Annotate the screenshot with suggestions for improvements.


Silahkan Check YOUTUBE{} a hacker doesn't claim to be a hacker. keep trying not to be seen, formed and fused as a system. because that's the life of a hacker. they are not trying to make everyone know that they are a hacker
a hacker doesn't claim to be a hacker. keep trying not to be seen, formed and fused as a system. because that's the life of a hacker. they are not trying to make everyone know that they are a hacker
Business Enquirer<EMAIL_ADDRESS>Instagram: @y?n!?? Endorse IG Line: @r???i!?!o (use @) POBOX Kirim Kepada: CYBER{}INDO SXmaxrx xelaxax , Jangan Lupa Follow Twiter Me : y?n!??


Google Kubernetes Engine (GKE) is the simplest and most common way of setting up a Kubernetes Cluster. You may be able to receive free credits for trying it out (though note that a free account comes with limitations). Either way, you will need to connect your credit card or other payment method to your google cloud account.

Go to and enable the Kubernetes Engine API.
Choose a terminal.
You can either to use a web based terminal or install and run the required command line interfaces on your own computer’s terminal. We recommend starting out by using the web based terminal. Choose one set of instructions below.
Use a web based terminal:
Start Google Cloud Shell from console.cloud.google.com by clicking the button shown below. You are now in control of a virtual machine with various tools preinstalled. If you save something in a user folder they will remain available to you if you return at a later stage. Additional documentation about Google Cloud shell is available here
Use your own computer’s terminal:
Download and install the gcloud command line tool at its install page. It will help you create and communicate with a Kubernetes cluster.
gcloud
Install kubectl (reads kube control), it is a tool for controlling Kubernetes clusters in general. From your terminal, enter:
kubectl
gcloud components install kubectl
Create a managed Kubernetes cluster and a default node pool.
Ask Google Cloud to create a managed Kubernetes cluster and a default node pool to get nodes from. Nodes represents hardware and a node pool will keep track of how much of a certain type of hardware that you would like.
gcloud container clusters create \ --machine-type n1-standard-2 \ --num-nodes 2 \ --zone <compute zone from the list linked below> \ --cluster-version latest \ <CLUSTERNAME>
Replace <CLUSTERNAME> with a name that can be used to refer to this cluster in the future.
<CLUSTERNAME>
--machine-type specifies the amount of CPU and RAM in each node within this default node pool. There is a variety of types to choose from.
--machine-type
--num-nodes specifies how many nodes to spin up. You can change this later through the cloud console or using the gcloud command line tool.
--num-nodes
--zone specifies the data center zone where your cluster will be created. You can pick something from this list that is not too far away from your users.
--zone
A region in GCP is a geographical region with at least three zones, where each zone is representing a datacenter with servers etc.
A regional cluster creates pods across zones in a region(three by default), distributing Kubernetes resources across multiple zones in the region. This is different from the default cluster, which has all its resources within a single zone(as shown above).
A regional cluster has Highly Available (HA) kubernetes api-servers, this allows jupyterhub which uses them to have no downtime during upgrades of kubernetes itself.
They also increase control plane uptime to 99.95%.
To avoid tripling the number of nodes while still having HA kubernetes, the --node-locations flag can be used to specify a single zone to use.
--node-locations
To test if your cluster is initialized, run:
kubectl get node
The response should list two running nodes (or however many nodes you set with --num-nodes above).
Give your account permissions to perform all administrative actions needed.
kubectl create clusterrolebinding cluster-admin-binding \ --clusterrole=cluster-admin \ --user=<GOOGLE-EMAIL-ACCOUNT>
Replace <GOOGLE-EMAIL-ACCOUNT> with the exact email of the Google account you used to sign up for Google Cloud.
<GOOGLE-EMAIL-ACCOUNT>
Did you enter your email correctly? If not, you can run kubectl delete clusterrolebinding cluster-admin-binding and do it again.
kubectl delete clusterrolebinding cluster-admin-binding
[optional] Create a node pool for users
This is an optional step, for those who want to separate user pods from “core” pods such as the Hub itself and others. See Optimizations for details on using a dedicated user node pool. The nodes in this node pool are for the users only. The node pool has autoscaling enabled along with a lower and an upper scaling limit. This means that the amount of nodes is automatically adjusted along with the amount of users scheduled. The n1-standard-2 machine type has 2 CPUs and 7.5 GB of RAM each of which about 0.2 CPU will be requested by system pods. It is a suitable choice for a free account that has a limit on a total of 8 CPU cores. Note that the node pool is tainted. Only user pods that are configured with a toleration for this taint can schedule on the node pool’s nodes. This is done in order to ensure the autoscaler will be able to scale down when the user pods have stopped. gcloud beta container node-pools create user-pool \ --machine-type n1-standard-2 \ --num-nodes 0 \ --enable-autoscaling \ --min-nodes 0 \ --max-nodes 3 \ --node-labels hub.jupyter.org/node-purpose=user \ --node-taints hub.jupyter.org_dedicated=user:NoSchedule \ --zone us-central1-b \ --cluster <CLUSTERNAME>
This is an optional step, for those who want to separate user pods from “core” pods such as the Hub itself and others. See Optimizations for details on using a dedicated user node pool.
The nodes in this node pool are for the users only. The node pool has autoscaling enabled along with a lower and an upper scaling limit. This means that the amount of nodes is automatically adjusted along with the amount of users scheduled.
The n1-standard-2 machine type has 2 CPUs and 7.5 GB of RAM each of which about 0.2 CPU will be requested by system pods. It is a suitable choice for a free account that has a limit on a total of 8 CPU cores.
n1-standard-2
Note that the node pool is tainted. Only user pods that are configured with a toleration for this taint can schedule on the node pool’s nodes. This is done in order to ensure the autoscaler will be able to scale down when the user pods have stopped.
gcloud beta container node-pools create user-pool \ --machine-type n1-standard-2 \ --num-nodes 0 \ --enable-autoscaling \ --min-nodes 0 \ --max-nodes 3 \ --node-labels hub.jupyter.org/node-purpose=user \ --node-taints hub.jupyter.org_dedicated=user:NoSchedule \ --zone us-central1-b \ --cluster <CLUSTERNAME>
Congrats. Now that you have your Kubernetes cluster running, it’s time to begin Setup JupyterHub.


Added: · UI system and components · Main menu with input box and button to start. Once pressed the screen fades away. · Ingame options window that has an option to activate / deactivate vsync with a checkbox. · Ingame window can be dragged around inside window limits. Crosshair in the middle of the screen.
DownloadAdded: · GameObject Parent-Child structure · Own File Formats · Scene Serialization · Quadtree including · Resource Management · Transform component · Load transformations from assimp · New Camera editor and Component · Mouse Picking and Gizmos · Time management including Gamemode · Anything including ImGui.
DownloadAdded: · Bake_house automatically loads once the engine is opened. · Two models in FBX format with one channel diffuse texture in DDS format. · Accepts drag&drop of FBX files from anywhere in the Hard Drive. · Accepts drag&drop of DDS/PNG files. The texture applies to the selected GameObject. · GameObject structure, one for each loaded mesh. · Unity-like camera controls. · Editor Windows.
Download


@HeatherNorvell
Associate Software Engineer at Modea. Lifetime member of Girl Scouts. Lover of cats, code, and crafts.
Reneé Alarid is a highly creative, multifaceted Interaction Designer with extensive experiences in multimedia, marketing, branding and print design. She currently works as an Interaction Designer at Modea.
Kara studies Psychology and Computer Science at Radford University. She loves cats and Skyrim. Her goal is to become a programmer or an artist for a video game company, and she is currently teaching herself C++ and C#. Coding is fun!
From Winchester, Va. Played volleyball and was in DECA in High School, which got me interested in marketing. Majored in Marketing Management at Virginia Tech. I love marketing because it’s so vast. You must use all parts of a business along with analytics to decide how to present your product and to which audience – which can all be backed up with analytics! I love Mill Mountain coffee, Papa Johns, Hokie football and cats.
Casey is designer on the Duke team at Modea. She graduated this past spring with a BFA in Visual Communication Design and a minor in business, and has now turned her focus toward web and interaction design. She feels that her education as a business minor allows her to understand the logical side of projects and marketing, while her design background and creative mind enable her to come up with inventive solutions to problems.
<EMAIL_ADDRESS>Hi, I’m Karen.  My degree was in Communication, but I pursued a career in content development. I had some experience from attempting websites before, but committing to a full time job is a big deal. I was confident I could learn quickly because of the countless times I’ve tried new things in the past. It’s important to know yourself, and the rest will fall into place.
Born and raised in Texas! Attended Baylor University. Sic’em Bears! I have a poodle-schnauzer named Maggie who gets stuff stuck in her beard. I use to be a Social Worker and worked with some hilarious old people. Now I’m the Admin Assistant at Modea and they call me “Mom”. I like to put mayo on my hot dogs (I know it’s sounds gross but it’s so good!) and I hate the cold weather.
Shannon has been working in the project management space for over 8 years and over 5 of those years has been working with computer programmers on innovative, technological projects. She plans to stay in the digital technology space because of her love of collaboration, coaching, training, and team mentality.
Meena Lohani is a Blacksburg resident. She received an M.S. in civil engineering from Virginia Tech and has worked in the area of Information Technology (IT). She is passionate about IT applications and continues to explore/develop her interests in computer programming, how latest technologies work, health informatics, and big data technologies. She likes to: travel, exercise, taste different ethnic food, and spend time with family and friends.
I grew up in Christiansburg and Dublin, Virginia but just recently became a Bobcat (Radford) and I love it! Attended the University of Tennessee and Radford University because it took me a while to figure out what I wanted to do when I grew up. I currently work as an Account Manager at Modea — or well…whatever we are calling ourselves these days. Did you hear we are spinning off?! So cool!


Acknowledgements
- Lmod
- Gonzalo Garcia, Luca Venturini, Matthew Hartley and Chris Bridson
- DMTCP
- Tim Stitt, Michael Burrell, Chris Bridson, Sam Gallop and Adam Carrgilson
- BioNano pipeline
- Graham Etherington, Ricardo Ramirez, Pirita Paajanen and the CiS Team
- STRUCTURE
- Tim Stitt, Diane Saunders, Pillar Corredor-Moreno, Antoine Persoons, Vanessa Bueno, Ricardo Ramirez
Many thanks to all for your help


{% extends "global/Page.html" %}
{% load otree %}
{% block title %}
End of round, Results
{% endblock %}
{% block content %}
{% if player.role == 'P1' %}
print
| Role |
Transfer |
Earnings |
| Receiver |
{{p2_transfer}} |
{{p1_receiver}} |
| Payoff |
{{player.payoff}} |
{% elif player.role == 'P2' %}
| Role |
Transfer |
Earnings |
| Decider |
{{p2_transfer}} |
{{p2_decider}} |
| Receiver |
{{p3_transfer}} |
{{p2_receiver}} |
| Payoff |
{{player.payoff}} |
{% elif player.role == 'P3' %}
| Role |
Transfer |
Earnings |
| Decider |
{{p3_transfer}} |
{{p3_decider}} |
| Receiver |
{{p4_transfer}} |
{{p3_receiver}} |
| Payoff |
{{player.payoff}} |
{% elif player.role == 'P4' %}
| Role |
Transfer |
Earnings |
| Decider |
{{p4_transfer}} |
{{p4_decider}} |
| Receiver |
{{p5_transfer}} |
{{p4_receiver}} |
| Payoff |
{{player.payoff}} |
{% elif player.role == 'P5' %}
| Role |
Transfer |
Earnings |
| Decider |
{{p5_transfer}} |
{{p5_decider}} |
| Receiver |
{{p6_transfer}} |
{{p5_receiver}} |
| Payoff |
{{player.payoff}} |
{% elif player.role == 'P6' %}
| Role |
Transfer |
Earnings |
| Decider |
{{p6_transfer}} |
{{p6_decider}} |
| Receiver |
{{p7_transfer}} |
{{p6_receiver}} |
| Payoff |
{{player.payoff}} |
{% elif player.role == 'P7' %}
| Role |
Transfer |
Earnings |
| Decider |
{{p7_transfer}} |
{{p7_decider}} |
| Receiver |
{{p8_transfer}} |
{{p7_receiver}} |
| Payoff |
{{player.payoff}} |
{% else %}
| Role |
Transfer |
Earnings |
| Decider |
{{p8_transfer}} |
{{p8_decider}} |
| Payoff |
{{player.payoff}} |
{% endif %}
{% next_button %}
{% include Constants.table_template %}
{% endblock %}


SHOCKER A Review in the Public Domain by The Phantom<EMAIL_ADDRESS>The Phantom takes some of the blame for the letdown his phans will surely feel upon leaving SHOCKER; truthfully, he added to the unwarranted hype surrounding the film by encouraging his readers to save their money for Wes Craven's latest by avoiding the dismal HALLOWEEN 5 two weeks ago.
But surely no one could be more disappointed than the Phantom himself, who has admired Craven since his horror debut -- THE HILLS HAVE EYES -- over a decade ago, and who has followed his career avidly ever since, from the original A NIGHTMARE ON ELM STREET to THE SERPENT AND THE RAINBOW. Of course, there have been some duds along the way (DEADLY BLESSING comes to mind), but even the ones that weren't standouts were generally a cut above the usual horror fare.
Pholks, there's good news and (mostly) bad news with this one. The good news is that Craven still makes some of the most interesting horror films around; the creator of Freddy Kruger and the atmospheric SERPENT has returned with Horace Pinker, a truly loathsome character who has as much personality as Freddy, but who spends considerably less time talking and considerably more time killing. Horace, you see, is a television repairman with a taste for murdering people -- whole families, actually -- and although he cracks a joke now and then, he is to Freddy Kruger what Dolph Lundgren is to Bruce Willis.
But sadly Craven doesn't seem to know what to do with Horace; during the first half of the film, Horace is strictly a devil worshiping maniac (actually, a television worshiping manic, though the Phantom has long believed them to be one in the same), but as the film progresses, Horace becomes more and more like Freddy, thus doing himself and his audience no favor at all: if we wanted Freddy (and after the disappointing NIGHTMARE ON ELM STREET 5 it's not clear that we do any more), we'd head for our local Blockbusters.
This brings us to the bad news, of which there is plenty. We'll start with the plot, although even with his Official Phantom Film Reviewer's Notebook (R), the Phantom was unable to jot down all of the loose ends, false starts, missed opportunities, and what looked to be the outcome of a few too many script conferences with nervous studio executives. It boils down to this: quite simply, somewhere along the way someone lost faith in this film. Someone decided that audiences don't really want to see horror films that are filled with horror; instead, they'd rather watch a watered-down "Elm Street" clone. So a film that begins with a great good many killings (some quite messy indeed) transforms itself about half way through into an "Elm Street" retread, complete with the requisite "Is this a dream or isn't it?" sequences and cut-rate ELM STREET special effects.
The plot goes hither and yon, never quite settling down into anything we can sink our fangs into. For a while, Horace is a run-of-the-mill mass murderer. Yet Our Hero Jonathan Parker can sense him in his dreams (shades of "Elm Street" here), and even join him as he stalks and kills various family members in a house miles away. Why is this? We never find out, because after about 30 minutes, Horace is captured by the police and the film comes to a screeching halt as we wait for Horace to get the chair (though once the action shifts to the prison, things pick up a bit). Needless to say, Horace survives this in one form or another, and the film lurches onward for a while in a completely different vein. Then, after another 30 minutes have passed, the film transforms itself yet again, as Horace finds a way to live on by inhabiting and using the bodies of those around him.
This lack of pacing and continuity is one of the biggest problems with SHOCKER. As Craven picks up and discards ideas -- how television violence (especially television news) affects us, a couple of dream sequences, some possessions, a bit of NIGHT OF THE LIVING DEAD, a couple of gross-out scenes, some flirting with the tired "love conquers all" theme -- the film goes all over the place and ends up nowhere. Why Craven didn't just start the film with a brief introduction and then 50,000 volts is a mystery. Why waste half an hour on a traditional Hero Chasing Murderous Lunatic plot when it turns out to be almost entirely irrelevant to the remainder of the film, which is anything *but* traditional and in fact borders occasionally on the truly weird?
Along with its continuity problems, SHOCKER also suffers from too many scenes that misfire -- scenes that may have worked better on paper than they do in the theater, where they generally had the audience and the Phantom himself hooting in both laughter and derision.
And there's still more bad news, phans. With the exception of Horace, the characters -- and the actors who portray them -- are uniformly bad, as is the dialogue (although Horace does get in a few good lines, Freddy-style, toward the end). Worst is Jonathan's father, a police lieutenant (more shades of ELM STREET), who despite overwhelming evidence that something out of the ordinary is happening steadfastly refuses to believe that Horace isn't just your garden variety, fully human, non-electrified lunatic. True, most horror films are filled with people who wander innocently down basement steps or say "There must be a logical explanation for all this" without cracking a smile, but the lieutenant truly tries our patience and makes nearly every one of his scenes an agony of bad acting, bad delivery, and bad scripting. The same can be said of Jonathan's girlfriend Alison; after taking leave of the movie early on, she returns later to appear in some of the most awful scenes in the film, during which time the audience prayed fervently, repeatedly, and vocally for her timely death.
Lest the Phantom make SHOCKER out to be a complete disappointment, he will say that although it doesn't always succeed in its goals; although it misses too many payoffs; and although it loses its way -- and its audience -- about half way through, SHOCKER remains one of the year's better horror films.  Certainly it's worth 2 stars, and it's certainly more entertaining than the rather tedious HALLOWEEN 5, which is it's only competition at the moment.
See it for its top-notch camera work and for the way Craven can set up a scene, be it a FRIDAY THE 13TH-like attack in a bathroom or a NIGHT OF THE LIVING DEAD-like chase through a park. See it for an original and entertaining new horror personality, though one who won't have his own 900 number, television series, or merchandising blitz this Halloween because despite the occasional wisecrack, he is just too loathsome, too vicious, and too cruel to attract the mass-market audience that Freddy can. And see it because it will most likely be a long, cold winter before we get another horror film that's substantially better. For all it's flaws, SHOCKER is mostly fun, and if you don't mind the lumbering plot, it's almost never boring.
So go, phans, but keep your expectations in check and your hopes among the popcorn littering the theater's floor. Don't expect a film as original or as well executed as the the first "Elm Street," but if your nature is more forgiving than The Phantom's, you might find it quite enjoyable.
: The Phantom<EMAIL_ADDRESS>: {cmcl2,uunet}!esquire!baumgart
.
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


mouse
Documentation
engine
system
input
mouse
Description
Overview
Groups
Globals
Graph
Examples
Classes
Brief description
Mouse
Mouse
device
.
MouseButton
Mouse
button
.


July 12th, Tom's work on chapter 9 and 10 exercises #TomsProjects
Chapter 9
E1: Whether tuple can be an argument to a function
def reverse_tuple (tu):
(a,b) = tu
return (b,a)
print (reverse_tuple(("Hello","World")))
Therefore, tuples can be arguments to functions.
E2: Is a pair a generalization of a tuple, or a tuple is a generalization of a pair?
Tuple is a generalization of a pair.
E3: Is a pair a kind of tuple, or a tuple is a kind of pair?
A pair is a kind of tuple.
Chapter 10
E1: Controlling turtle graphics using a combination of events handling
import turtle
Tom = turtle.Turtle()
wn = turtle.Screen()
pensi = 5
Tom.pencolor("black")
Tom.speed(0)
def color_red():
Tom.pencolor("red")
def color_green():
Tom.pencolor("green")
def color_blue():
Tom.pencolor("blue")
def increase_size():
global pensi
if pensi <= 19:
pensi += 1
Tom.pensize(pensi)
def decrease_size():
global pensi
if pensi >=2:
pensi -= 1
Tom.pensize(pensi)
def move(x, y):
Tom.goto(x, y)
wn.listen()
wn.onclick(move)
wn.onkey(color_red,"r")
wn.onkey(color_blue,"b")
wn.onkey(color_green,"g")
wn.onkeypress(increase_size,"=")
wn.onkeypress(decrease_size,"-")
wn.mainloop()
E2: Automatic traffic lights controller
import turtle # Tess becomes a traffic light.
turtle.setup(400,500)
wn = turtle.Screen()
wn.title("Tess becomes a traffic light!")
wn.bgcolor("lightgreen")
tess = turtle.Turtle()
def draw_housing():
""" Draw a nice housing to hold the traffic lights """
tess.pensize(3)
tess.color("black", "darkgrey")
tess.begin_fill()
tess.forward(80)
tess.left(90)
tess.forward(200)
tess.circle(40, 180)
tess.forward(200)
tess.left(90)
tess.end_fill()
draw_housing()
tess.penup()
# Position tess onto the place where the green light should be
tess.forward(40)
tess.left(90)
tess.forward(50)
# Turn tess into a big green circle
tess.shape("circle")
tess.shapesize(3)
tess.fillcolor("green")
# A traffic light is a kind of state machine with three states,
# Green, Orange, Red. We number these states 0, 1, 2
# When the machine changes state, we change tess' position and
# her fillcolor.
# This variable holds the current state of the machine
state_num = 0
wn.listen() # Listen for events
# red and green light will last for 3 seconds, while orange light will last for 1 second.
def advance_state_machine():
global state_num
if state_num == 0: # Transition from state 0 to state 1
tess.forward(70)
tess.fillcolor("orange")
state_num = 1
wn.ontimer(advance_state_machine, "1000")
elif state_num == 1: # Transition from state 1 to state 2
tess.forward(70)
tess.fillcolor("red")
state_num = 2
wn.ontimer(advance_state_machine, "3000")
else: # Transition from state 2 to state 0
tess.back(140)
tess.fillcolor("green")
state_num = 0
wn.ontimer(advance_state_machine, "3000")
wn.ontimer(advance_state_machine, "3000")
wn.mainloop()
E3: Alternative way of controlling traffic lights using multiple turtles
import turtle # Tess becomes a traffic light.
turtle.setup(400,500)
wn = turtle.Screen()
wn.title("Tess becomes a traffic light!")
wn.bgcolor("lightgreen")
tess = turtle.Turtle()
tess.speed(0)
red = turtle.Turtle()
green = turtle.Turtle()
orange = turtle.Turtle()
def draw_housing():
""" Draw a nice housing to hold the traffic lights """
tess.pensize(3)
tess.color("black", "darkgrey")
tess.begin_fill()
tess.forward(80)
tess.left(90)
tess.forward(200)
tess.circle(40, 180)
tess.forward(200)
tess.left(90)
tess.end_fill()
draw_housing()
def initialization(obj, color, position):
obj.hideturtle()
obj.speed(0)
obj.forward(40)
obj.left(90)
obj.forward(50)
obj.shape("circle")
obj.shapesize(3)
obj.fillcolor(color)
obj.forward(position)
initialization(red, "red", 140)
initialization(green, "green", 0)
initialization(orange, "orange", 70)
state_num = 0
wn.listen() # Listen for events
# red and green light will last for 3 seconds, while orange light will last for 2 second.
def advance_state_machine():
global state_num
if state_num == 0: # Transition from state 0 to state 1
orange.showturtle()
green.hideturtle()
wn.ontimer(advance_state_machine, "2000")
state_num = 1
elif state_num == 1: # Transition from state 1 to state 2
red.showturtle()
orange.hideturtle()
wn.ontimer(advance_state_machine, "3000")
state_num = 2
else: # Transition from state 2 to state 0
green.showturtle()
red.hideturtle()
wn.ontimer(advance_state_machine, "3000")
state_num = 0
wn.ontimer(advance_state_machine, "3000")
green.showturtle()
wn.mainloop()
E4: Modification of E3 on the visibility of traffic lights when not activated.
import turtle # Tess becomes a traffic light.
turtle.setup(400,500)
wn = turtle.Screen()
wn.title("Tess becomes a traffic light!")
wn.bgcolor("lightgreen")
tess = turtle.Turtle()
tess.speed(0)
red = turtle.Turtle()
green = turtle.Turtle()
orange = turtle.Turtle()
def draw_housing():
""" Draw a nice housing to hold the traffic lights """
tess.pensize(3)
tess.color("black", "darkgrey")
tess.begin_fill()
tess.forward(80)
tess.left(90)
tess.forward(200)
tess.circle(40, 180)
tess.forward(200)
tess.left(90)
tess.end_fill()
draw_housing()
def initialization(obj, color, position):
obj.speed(0)
obj.forward(40)
obj.left(90)
obj.forward(50)
obj.shape("circle")
obj.shapesize(3)
obj.fillcolor(color)
obj.forward(position)
initialization(red, "grey", 140)
initialization(green, "grey", 0)
initialization(orange, "grey", 70)
state_num = 0
wn.listen() # Listen for events
# red and green light will last for 3 seconds, while orange light will last for 2 second.
def advance_state_machine():
global state_num
if state_num == 0: # Transition from state 0 to state 1
orange.fillcolor("orange")
green.fillcolor("grey")
wn.ontimer(advance_state_machine, "2000")
state_num = 1
elif state_num == 1: # Transition from state 1 to state 2
red.fillcolor("red")
orange.fillcolor("grey")
wn.ontimer(advance_state_machine, "3000")
state_num = 2
else: # Transition from state 2 to state 0
green.fillcolor("green")
red.fillcolor("grey")
wn.ontimer(advance_state_machine, "3000")
state_num = 0
green.fillcolor("green")
wn.ontimer(advance_state_machine, "3000")
wn.mainloop()
E5: Advanced traffic lights controller with an additional state and an accurate timer
import turtle # Tess becomes a traffic light.
turtle.setup(400,500)
wn = turtle.Screen()
wn.title("Tess becomes a traffic light!")
wn.bgcolor("lightgreen")
tess = turtle.Turtle()
tess.speed(0)
red = turtle.Turtle()
green = turtle.Turtle()
orange = turtle.Turtle()
def draw_housing():
""" Draw a nice housing to hold the traffic lights """
tess.pensize(3)
tess.color("black", "darkgrey")
tess.begin_fill()
tess.forward(80)
tess.left(90)
tess.forward(200)
tess.circle(40, 180)
tess.forward(200)
tess.left(90)
tess.end_fill()
draw_housing()
def initialization(obj, color, position):
obj.speed(0)
obj.forward(40)
obj.left(90)
obj.forward(50)
obj.shape("circle")
obj.shapesize(3)
obj.fillcolor(color)
obj.forward(position)
initialization(red, "grey", 140)
initialization(green, "grey", 0)
initialization(orange, "grey", 70)
state_num = 0
wn.listen() # Listen for events
# 3 seconds in the Green state, followed by one second in the Green+Orange state,
# then one second in the Orange state, and then 2 seconds in the Red state.
def advance_state_machine():
global state_num
if state_num == 0:
orange.fillcolor("orange")
green.fillcolor("green")
wn.ontimer(advance_state_machine, "1000")
state_num = 1
elif state_num == 1:
green.fillcolor("grey")
wn.ontimer(advance_state_machine, "1000")
state_num = 2
elif state_num == 2:
red.fillcolor("red")
orange.fillcolor("grey")
wn.ontimer(advance_state_machine, "3000")
state_num = 3
elif state_num == 3:
red.fillcolor("grey")
green.fillcolor("green")
wn.ontimer(advance_state_machine, "3000")
state_num = 0
green.fillcolor("green")
wn.ontimer(advance_state_machine, "3000")
wn.mainloop()
E6: All intermediate states in tennis scoring
The image was automatically compressed by the server so its quality reduced.


---
layout: post
title: Really Funny Stuff - Must Read
tags:
- Articles
- General Photography
- humor
- inspiration
status: publish
type: post
published: true
meta:
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_edit_lock: "1321028779"
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ghostpool_post_template: Default
ghostpool_link: Full Size Image/Video
ghostpool_post_image: http://photo.rwboyer.com/wp-content/uploads/2011/11/2011-005-18cn.jpg
ghostpool_post_faded_image: http://photo.rwboyer.com/wp-content/uploads/2011/11/2011-005-18cn.jpg
ghostpool_circle_image: http://photo.rwboyer.com/wp-content/uploads/2011/11/2011-005-18cn.jpg
dsq_thread_id: "468564739"
aktt_tweeted: "1"
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---
Sorry for the foul mood and negativity of my last two posts - that is what dealing with the government does to me. On a lighter note but still on topic relative to not only the last two posts but a lot of the subtext in more than a few of my posts. Here are a few posts that you have to read, if these don't make you chuckle, I don't know what would. File this under funny because you know it's true.
On this post you can skip the mildly pedantic preface where the author (whom I really like) tries to explain how he has never been affected by biases of his generation. Go directly to the end where you will find a faux forum discussion on one of HCB's famous photographs. Hilarious.
Forum Discussion on an HCB image.
Here are some imagined comments on various famous icons of photography and their photographs.
Inspired comedy.
Enjoy
RB


QToolBox Class
The QToolBox class provides a column of tabbed widget items. More...
| Header: | #include <QToolBox> |
| qmake: | QT += widgets |
| Inherits: | QFrame |
Properties
- count : const int
- currentIndex : int
- 6 properties inherited from QFrame
- 59 properties inherited from QWidget
- 1 property inherited from QObject
Public Functions
| QToolBox(QWidget *parent = Q_NULLPTR, Qt::WindowFlags f = Qt::WindowFlags()) | |
| ~QToolBox() | |
| int | addItem(QWidget *widget, const QIcon &iconSet, const QString &text) |
| int | addItem(QWidget *w, const QString &text) |
| int | count() const |
| int | currentIndex() const |
| QWidget * | currentWidget() const |
| int | indexOf(QWidget *widget) const |
| int | insertItem(int index, QWidget *widget, const QIcon &icon, const QString &text) |
| int | insertItem(int index, QWidget *widget, const QString &text) |
| bool | isItemEnabled(int index) const |
| QIcon | itemIcon(int index) const |
| QString | itemText(int index) const |
| QString | itemToolTip(int index) const |
| void | removeItem(int index) |
| void | setItemEnabled(int index, bool enabled) |
| void | setItemIcon(int index, const QIcon &icon) |
| void | setItemText(int index, const QString &text) |
| void | setItemToolTip(int index, const QString &toolTip) |
| QWidget * | widget(int index) const |
- 14 public functions inherited from QFrame
- 214 public functions inherited from QWidget
- 32 public functions inherited from QObject
- 14 public functions inherited from QPaintDevice
Public Slots
| void | setCurrentIndex(int index) |
| void | setCurrentWidget(QWidget *widget) |
Signals
| void | currentChanged(int index) |
Protected Functions
| virtual void | itemInserted(int index) |
| virtual void | itemRemoved(int index) |
Reimplemented Protected Functions
| virtual void | changeEvent(QEvent *ev) |
| virtual bool | event(QEvent *e) |
| virtual void | showEvent(QShowEvent *e) |
- 4 protected functions inherited from QFrame
- 35 protected functions inherited from QWidget
- 9 protected functions inherited from QObject
- 1 protected function inherited from QPaintDevice
Additional Inherited Members
- 1 public variable inherited from QObject
- 5 static public members inherited from QWidget
- 10 static public members inherited from QObject
- 1 protected slot inherited from QWidget
- 2 protected variables inherited from QObject
- 1 protected type inherited from QPaintDevice
Detailed Description
The QToolBox class provides a column of tabbed widget items.
A toolbox is a widget that displays a column of tabs one above the other, with the current item displayed below the current tab. Every tab has an index position within the column of tabs. A tab's item is a QWidget.
Each item has an itemText(), an optional itemIcon(), an optional itemToolTip(), and a widget(). The item's attributes can be changed with setItemText(), setItemIcon(), and setItemToolTip(). Each item can be enabled or disabled individually with setItemEnabled().
Items are added using addItem(), or inserted at particular positions using insertItem(). The total number of items is given by count(). Items can be deleted with delete, or removed from the toolbox with removeItem(). Combining removeItem() and insertItem() allows you to move items to different positions.
The index of the current item widget is returned by currentIndex(), and set with setCurrentIndex(). The index of a particular item can be found using indexOf(), and the item at a given index is returned by item().
The currentChanged() signal is emitted when the current item is changed.
See also QTabWidget.
Property Documentation
count : const int
This property holds the number of items contained in the toolbox.
By default, this property has a value of 0.
Access functions:
| int | count() const |
currentIndex : int
This property holds the index of the current item
By default, for an empty toolbox, this property has a value of -1.
Access functions:
| int | currentIndex() const |
| void | setCurrentIndex(int index) |
Notifier signal:
| void | currentChanged(int index) |
Member Function Documentation
QToolBox::QToolBox(QWidget *parent = Q_NULLPTR, Qt::WindowFlags f = Qt::WindowFlags())
Constructs a new toolbox with the given parent and the flags, f.
QToolBox::~QToolBox()
Destroys the toolbox.
int QToolBox::addItem(QWidget *widget, const QIcon &iconSet, const QString &text)
Adds the widget in a new tab at bottom of the toolbox. The new tab's text is set to text, and the iconSet is displayed to the left of the text. Returns the new tab's index.
int QToolBox::addItem(QWidget *w, const QString &text)
This is an overloaded function.
Adds the widget w in a new tab at bottom of the toolbox. The new tab's text is set to text. Returns the new tab's index.
[virtual protected]
void QToolBox::changeEvent(QEvent *ev)
Reimplemented from QWidget::changeEvent().
[signal]
void QToolBox::currentChanged(int index)
This signal is emitted when the current item is changed. The new current item's index is passed in index, or -1 if there is no current item.
Note: Notifier signal for property currentIndex.
QWidget *QToolBox::currentWidget() const
Returns a pointer to the current widget, or 0 if there is no such item.
See also currentIndex() and setCurrentWidget().
[virtual protected]
bool QToolBox::event(QEvent *e)
Reimplemented from QObject::event().
int QToolBox::indexOf(QWidget *widget) const
Returns the index of widget, or -1 if the item does not exist.
int QToolBox::insertItem(int index, QWidget *widget, const QIcon &icon, const QString &text)
Inserts the widget at position index, or at the bottom of the toolbox if index is out of range. The new item's text is set to text, and the icon is displayed to the left of the text. Returns the new item's index.
int QToolBox::insertItem(int index, QWidget *widget, const QString &text)
This is an overloaded function.
Inserts the widget at position index, or at the bottom of the toolbox if index is out of range. The new item's text is set to text. Returns the new item's index.
bool QToolBox::isItemEnabled(int index) const
Returns true
if the item at position index is enabled; otherwise returns false
.
QIcon QToolBox::itemIcon(int index) const
Returns the icon of the item at position index, or a null icon if index is out of range.
See also setItemIcon().
[virtual protected]
void QToolBox::itemInserted(int index)
This virtual handler is called after a new item was added or inserted at position index.
See also itemRemoved().
[virtual protected]
void QToolBox::itemRemoved(int index)
This virtual handler is called after an item was removed from position index.
See also itemInserted().
QString QToolBox::itemText(int index) const
Returns the text of the item at position index, or an empty string if index is out of range.
See also setItemText().
QString QToolBox::itemToolTip(int index) const
Returns the tooltip of the item at position index, or an empty string if index is out of range.
See also setItemToolTip().
void QToolBox::removeItem(int index)
Removes the item at position index from the toolbox. Note that the widget is not deleted.
[slot]
void QToolBox::setCurrentWidget(QWidget *widget)
Makeswidget the current widget. The widget must be an item in this tool box.
See also addItem(), setCurrentIndex(), and currentWidget().
void QToolBox::setItemEnabled(int index, bool enabled)
If enabled is true then the item at position index is enabled; otherwise the item at position index is disabled.
See also isItemEnabled().
void QToolBox::setItemIcon(int index, const QIcon &icon)
Sets the icon of the item at position index to icon.
See also itemIcon().
void QToolBox::setItemText(int index, const QString &text)
Sets the text of the item at position index to text.
If the provided text contains an ampersand character ('&'), a mnemonic is automatically created for it. The character that follows the '&' will be used as the shortcut key. Any previous mnemonic will be overwritten, or cleared if no mnemonic is defined by the text. See the QShortcut documentation for details (to display an actual ampersand, use '&&').
See also itemText().
void QToolBox::setItemToolTip(int index, const QString &toolTip)
Sets the tooltip of the item at position index to toolTip.
See also itemToolTip().
[virtual protected]
void QToolBox::showEvent(QShowEvent *e)
Reimplemented from QWidget::showEvent().
QWidget *QToolBox::widget(int index) const
Returns the widget at position index, or 0 if there is no such item.


Girlscript Ranchi is the Ranchi chapter of the GirlScript Foundation, which was set up on 2nd June, 2017.
Web Development Workshop
12th - 17th July - Learn the
Skill
Live
hands-on session
Portfolio Making Competiton
18th - 20th July - Test your
Skill
Best Portfolio Certificate


my works
Doctor Proctor is an app that will help you locate doctors, in different specialties and different locations. You can also recommend doctors.
Link to GitHub Link to deployed projectWeather app that provides current and future weather forecasts in cities.
Link to GitHub Link to deployed projectQuarantine Media Recommender (QMR) delivers a list of books, movies, or songs to explore.
Link to GitHub Link to deployed projectBurger logger App with MySQL, Node, Express, Handlebars.
Link to GitHub Link to deployed projectTimed quiz on JavaScript fundamentals that stores high scores.
Link to GitHub Link to deployed project


--- layout: default title: "Members" permalink: /members/ ---
NYRIA is a network of young astronomers from all around the world, working in different areas of astronomical instrumention. Here you can find members as according to their country, research areas and more. The map illustrates the current reach of NYRIA. To search for individual members by country, research area and institute please click on the desired link.


Vision
As a team member
I want to be able to run activation and release code to different target platforms
so that I am not restricted in my integration to a single platform.
Roll-out occurs for development, test, UAT and production servers. The uSDLC master/slave support and scripting allows most roll-out tasks to be automatic with integrity checks. For required manual task, uSDLC can prompt for them to be done and then continue with validation aod further tasks.


| Constellation Action | Keyboard Shortcut | User Action | Menu Icon |
|---|---|---|---|
| Open Perspective Bookmarks | Experimental -> Views -> Perspective Bookmarks |
The Perspective Bookmarks View allows you to bookmark a viewing position so you can return to it later. It lets you keep different perspectives on your graph.
To add a perspective bookmark, move the camera in the graph window to the position you want to save and select "Add a graph-relative perspective". A new bookmark with a default name will be added. This new bookmark can be renamed by selecting the bookmark and then selecting "Rename selected perspective" to bring up the dialog allowing you to choose a new name. A bookmark can be removed by selecting the bookmark and then selecting "Remove a perspective".
Using a bookmark is as simple as double-clicking on the bookmark. This will change the camera in the graph window to the setting saved in the bookmark.


| PWG San Diego Meeting Details |
UPDF: December 4
uPnP Hosted Meeting: December 5/6
IPP: December 7
IPP FAX: December 8
Reservations: 1-800-228-9290
voice: +1-619-234-1500
Guest Fax: +1-619-234-8678
Hotel Cost: $189/night, single or double occupancy.
When making your reservation, the meeting will be listed under "PWG" and "IEEE-ISTO". Rooms are being held for the nights of December 3 - 8 if you wish to extend your stay at the PWG rate.
Deadline: Please make your reservations by Wednesday, November 15, 2000.
There will be a meeting charge of $70; participants are responsible for their own
lunch.
YOU MUST REGISTER AT: https://www.ieee-isto.org/pwg/registration.html
Please contact Cindy Tiritilli, IEEE-ISTO PWG Program Administrator at
+1-732-981-3434 or<EMAIL_ADDRESS>if you have any questions.


Version 4.16¶
Release date: 2019-12-12
This release contains a number of bug fixes and new features since the release of pgAdmin4 4.15.
Warning
Warning: This release includes a change to the container distribution to run pgAdmin as a non-root user. Those users of the container who are running with mapped storage directories may need to change the ownership on the host machine, for example:
sudo chown -R 5050:5050 <host_directory>
New features¶
Issue #4396 - Warn the user on changing the definition of Materialized View about the loss of data and its dependent objects.
Issue #4435 - Allow drag and drop functionality for all the nodes under the database node, excluding collection nodes.
Issue #4711 - Use a ‘play’ icon for the Execute Query button in the Query Tool for greater consistency with other applications.
Issue #4772 - Added aria-label to provide an invisible label where a visible label cannot be used.
Issue #4773 - Added role=”status” attribute to all the status messages for accessibility.
Issue #4939 - Run pgAdmin in the container as a non-root user (pgadmin, UID: 5050)
Issue #4944 - Allow Gunicorn logs in the container to be directed to a file specified through GUNICORN_ACCESS_LOGFILE.
Issue #4990 - Changed the open query tool and data filter icons.
Housekeeping¶
Issue #4696 - Add Reverse Engineered and Modified SQL tests for Materialized Views.
Issue #4807 - Refactored code of table and it’s child nodes.
Issue #4938 - Refactored code of columns node.
Bug fixes¶
Issue #3538 - Fix issue where the Reset button does not get enabled till all the mandatory fields are provided in the dialog.
Issue #4220 - Fix scrolling issue in ‘Users’ dialog.
Issue #4516 - Remove the sorting of table headers with no labels.
Issue #4659 - Updated documentation for default privileges to clarify more on the grantor.
Issue #4674 - Fix query tool launch error if user name contains HTML characters. It’s a regression.
Issue #4724 - Fix network disconnect issue while establishing the connection via SSH Tunnel and it impossible to expand the Servers node.
Issue #4761 - Fix an issue where the wrong type is displayed when changing the datatype from timestamp with time zone to timestamp without time zone.
Issue #4792 - Ensure that the superuser should be able to create database, as the superuser overrides all the access restrictions.
Issue #4818 - Fix server connection drops out issue in query tool.
Issue #4836 - Updated the json file name from ‘servers.json’ to ‘pgadmin4/servers.json’ in the container deployment section of the documentation.
Issue #4878 - Ensure that the superuser should be able to create role, as the superuser overrides all the access restrictions.
Issue #4893 - Fix reverse engineering SQL issue for partitions when specifying digits as comments.
Issue #4923 - Enhance the logic to change the label from ‘Delete/Drop’ to ‘Remove’ for the server and server group node.
Issue #4925 - Shown some text on process watcher till the initial logs are loaded.
Issue #4926 - Fix VPN network disconnect issue where pgAdmin4 hangs on expanding the Servers node.
Issue #4930 - Fix main window tab navigation accessibility issue.
Issue #4933 - Ensure that the Servers collection node should expand independently of server connections.
Issue #4934 - Fix the help button link on the User Management dialog.
Issue #4935 - Fix accessibility issues.
Issue #4947 - Fix XSS issue in explain and explain analyze for table and type which contain HTML.
Issue #4952 - Fix an issue of retrieving properties for Compound Triggers. It’s a regression of #4006.
Issue #4953 - Fix an issue where pgAdmin4 unable to retrieve table node if the trigger is already disabled and the user clicks on Enable All.
Issue #4958 - Fix reverse engineering SQL issue for triggers when passed a single argument to trigger function.
Issue #4964 - Fix an issue where length and precision are not removed from table/column dialog.
Issue #4965 - Fix an issue where the Interval data type is not displayed in the properties dialog of table/column.
Issue #4966 - Fix ‘Could not find the object on the server.’ error while refreshing the check constraint.
Issue #4975 - Fix issue where the user can not switch the UI language. It’s a regression of #4348.
Issue #4976 - Fix reverse engineering SQL issue where when clause is not visible for PG/EPAS 12.
Issue #4978 - Fix pgAdmin4 failed to start issue after upgrading to version 4.15.
Issue #4982 - Added statistics and storage information in reverse engineering SQL of table/column.
Issue #4985 - Fix an issue where the inherited table name with quotes did not escape correctly.
Issue #4991 - Fix an issue where context menu is open along with submenu and the focus is not on context menu or submenu.


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|
Drake
|
Implementations of estimators that operate as Systems in a block diagram.
Algorithms that synthesize controllers are located in State Estimation.
Classes | |
| class | LuenbergerObserver< T > |
| A simple state observer for a dynamical system of the form: \[\dot{x} = f(x,u) \] \[y = g(x,u) \] the observer dynamics takes the form \[\dot{\hat{x}} = f(\hat{x},u) + L(y - g(\hat{x},u)) \] where \(\hat{x}\) is the estimated state of the original system. More... | |
Functions | |
| Eigen::MatrixXd | SteadyStateKalmanFilter (const Eigen::Ref< const Eigen::MatrixXd > &A, const Eigen::Ref< const Eigen::MatrixXd > &C, const Eigen::Ref< const Eigen::MatrixXd > &W, const Eigen::Ref< const Eigen::MatrixXd > &V) |
| Computes the optimal observer gain, L, for the linear system defined by \[ \dot{x} = Ax + Bu + w, \] \[ y = Cx + Du + v. \] The resulting observer is of the form \[ \dot{\hat{x}} = A\hat{x} + Bu + L(y - C\hat{x} - Du). \] The process noise, w, and the measurement noise, v, are assumed to be iid mean-zero Gaussian. More... | |
| std::unique_ptr< LuenbergerObserver< double > > | SteadyStateKalmanFilter (std::unique_ptr< LinearSystem< double >> system, const Eigen::Ref< const Eigen::MatrixXd > &W, const Eigen::Ref< const Eigen::MatrixXd > &V) |
| Creates a Luenberger observer system using the optimal steady-state Kalman filter gain matrix, L, as described above. More... | |
| std::unique_ptr< LuenbergerObserver< double > > | SteadyStateKalmanFilter (std::unique_ptr< System< double >> system, std::unique_ptr< Context< double >> context, const Eigen::Ref< const Eigen::MatrixXd > &W, const Eigen::Ref< const Eigen::MatrixXd > &V) |
| Creates a Luenberger observer system using the steady-state Kalman filter observer gain. More... | |
| Eigen::MatrixXd | ObservabilityMatrix (const LinearSystem< double > &sys) |
| Returns the observability matrix: O = [ C; CA; ...; CA^{n-1} ]. More... | |
| bool | IsObservable (const LinearSystem< double > &sys, std::optional< double > threshold=std::nullopt) |
| Returns true iff the observability matrix is full column rank. More... | |
| bool drake::systems::IsObservable | ( | const LinearSystem< double > & | sys, |
| std::optional< double > | threshold = std::nullopt |
||
| ) |
Returns true iff the observability matrix is full column rank.
| Eigen::MatrixXd drake::systems::ObservabilityMatrix | ( | const LinearSystem< double > & | sys | ) |
Returns the observability matrix: O = [ C; CA; ...; CA^{n-1} ].
| Eigen::MatrixXd drake::systems::estimators::SteadyStateKalmanFilter | ( | const Eigen::Ref< const Eigen::MatrixXd > & | A, |
| const Eigen::Ref< const Eigen::MatrixXd > & | C, | ||
| const Eigen::Ref< const Eigen::MatrixXd > & | W, | ||
| const Eigen::Ref< const Eigen::MatrixXd > & | V | ||
| ) |
Computes the optimal observer gain, L, for the linear system defined by
\[ \dot{x} = Ax + Bu + w, \]
\[ y = Cx + Du + v. \]
The resulting observer is of the form
\[ \dot{\hat{x}} = A\hat{x} + Bu + L(y - C\hat{x} - Du). \]
The process noise, w, and the measurement noise, v, are assumed to be iid mean-zero Gaussian.
This is a simplified form of the full Kalman filter obtained by assuming that the state-covariance matrix has already converged to its steady-state solution.
| A | The state-space dynamics matrix of size num_states x num_states. |
| C | The state-space output matrix of size num_outputs x num_states. |
| W | The process noise covariance matrix, E[ww'], of size num_states x num_states. |
| V | The measurement noise covariance matrix, E[vv'], of size num_. |
| std::runtime_error | if V is not positive definite. |
| std::unique_ptr<LuenbergerObserver<double> > drake::systems::estimators::SteadyStateKalmanFilter | ( | std::unique_ptr< LinearSystem< double >> | system, |
| const Eigen::Ref< const Eigen::MatrixXd > & | W, | ||
| const Eigen::Ref< const Eigen::MatrixXd > & | V | ||
| ) |
Creates a Luenberger observer system using the optimal steady-state Kalman filter gain matrix, L, as described above.
| system | A unique_ptr to a LinearSystem describing the system to be observed. The new observer will take and maintain ownership of this pointer. |
| W | The process noise covariance matrix, E[ww'], of size num_states x num_states. |
| V | The measurement noise covariance matrix, E[vv'], of size num_. |
| std::runtime_error | if V is not positive definite. |
| std::unique_ptr<LuenbergerObserver<double> > drake::systems::estimators::SteadyStateKalmanFilter | ( | std::unique_ptr< System< double >> | system, |
| std::unique_ptr< Context< double >> | context, | ||
| const Eigen::Ref< const Eigen::MatrixXd > & | W, | ||
| const Eigen::Ref< const Eigen::MatrixXd > & | V | ||
| ) |
Creates a Luenberger observer system using the steady-state Kalman filter observer gain.
Assuming system
has the (continuous-time) dynamics: dx/dt = f(x,u), and the output: y = g(x,u), then the resulting observer will have the form dx̂/dt = f(x̂,u) + L(y - g(x̂,u)), where x̂ is the estimated state and the gain matrix, L, is designed as a steady-state Kalman filter using a linearization of f(x,u) at context
as described above.
| system | A unique_ptr to a System describing the system to be observed. The new observer will take and maintain ownership of this pointer. |
| context | A unique_ptr to the context describing a fixed-point of the system (plus any additional parameters). The new observer will take and maintain ownership of this pointer for use in its internal forward simulation. |
| W | The process noise covariance matrix, E[ww'], of size num_states x num_states. |
| V | The measurement noise covariance matrix, E[vv'], of size num_. |
| std::runtime_error | if V is not positive definite. |


🥑 Developer Advocate 🥑
Made in western countries
“Computers aren't the thing. They're the thing that gets us to the thing.”
“How did we all get here today? The choices we made, the sheer force of our will, something like that? Here's another answer... the winds of fate. Random coincidence, some unseen hand just pushing us along. Destiny.”
(also density of packing)
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Font used is Magnetic Pro, by Olivier Gourvat


AAS Autoparts
Chun Huat Auto Supplies
Famous Auto Supplies
Contact:
03-4256 0885
Contact:
013-517 6688
Contact:
019-328 8324
Opening Hours:
- Saturday 8:30AM–6:30PM
- Sunday Closed
- Monday 8:30AM–6:30PM
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Opening Hours:
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Mark node as schedulable.
Examples:
# Mark node "foo" as schedulable.
$ kubectl uncordon foo
kubectl uncordon NODE [options]
Use "kubectl options" for a list of global command-line options (applies to all commands).


The term “autonomous things” is being used more and more in the technology world to talk about phenomena powered by the latest advancements in artificial intelligence and machine learning. Autonomous things are things that work autonomously without human guidance or direct intervention.
A space probe that is able to deal with the surface of a planet to collect samples. For example, if the ground is too hard for digging, the probe will decide to move an area that looks softer.
A dam that can autonomously respond to conditions to maintain water levels in reservoirs and prevent flooding.
A small cart that is able to navigate sidewalks, people and traffic to make a last mile package delivery to a customer.
A vertical garden system that can handle variable conditions. For example, if a plant looks like it's unhealthy the system might try a variety of things to try to save it.
An artificial intelligence that resembles a conveyor belt that can automatically find reusable and recyclable materials in garbage.
A vacuum cleaner that can navigate irregular spaces, people and pets to clean a floor.
Windows that autonomously adapt to light levels to achieve goals such as heating, cooling, growing plants or achieving indoor light parameters set by users.
For more information on Autonomous Things click here


Provides an API for validating internal consistency among attributes.
Many times, an attribute will only make sense in some context. For example, you may have one attribute that must either be applied to no methods, or to all methods in a class. An attribute may require the presence of another attribute.
The AttributeValidatorTask Ant task and its API enables you to define those rules and run them as part of your regular build.


Around the 2019 lockdowns, I started learning a bit of blender with intentions of diving into VJ’ing and creating WebGL assets.
i would say most of my 3d explorations are all around shapes, and not so much with modeling. (never really got into that yet)


Preparation time
30 mins to 1 hour
Cooking time
1 to 2 hours
Serves
Makes 1 three-tiered pie
Three stacked pork pies each flavoured with a hint of fruit. Try it as a centrepiece for a buffet or even as a savoury alternative to a wedding cake.
For this recipe you will need three springform cake tins (1 x 10cm/4in, 1 x 15cm/6in and 1 x 20cm/8in), three cake boards (1 x 10cm/4in, 1 x 15cm/6in and 1 x 20cm/8in), a mincer, a hand-held blender, three piping bags fitted with plain nozzles (or disposable piping bags with the corner snipped) and nine cake dowels.
Grease the cake tins (1 x 10cm/4in, 1 x 15cm/6in and 1 x 20cm/8in springform tins) and dust them with flour.
For the rhubarb, apple and prune flavourings, put the rhubarb and 50g/1¾oz sugar in a pan set over a medium heat. Bring to the boil, then reduce the heat and simmer for at least 10 minutes to allow any water in the rhubarb to evaporate. When the rhubarb is quite dry, set it aside to cool.
Place the remaining caster sugar and chopped apples in a saucepan set over a medium heat. Bring to the boil, then reduce the heat and simmer until the moisture has evaporated and the mixture is quite dry.
For the filling, mix all the ingredients together in a large bowl, then divide the mixture between three bowls - with just under half the mixture in one bowl, about a third in another and the remainder in the final bowl. Add the rhubarb, apple and prune flavourings, with the rhubarb in the large bowl, the apple in the middle and the prune in the smallest. Squish well with your fingers to mix.
Preheat the oven to 180C/350F/Gas 4.
For the hot water crust pastry, sieve the flours and salt into a large heatproof bowl.
Place 440ml/16fl oz water and the lard into a pan and bring to the boil.
Add the hot liquor gradually to the flour mixture and use a knife to bring the dough together.
While the dough is still hot (but cool enough to handle), use your hands to briefly knead the dough until smooth. Turn out onto a lightly floured work surface.
Pinch out a third of the dough to make the pie lids. Divide this into three pieces and roll them out (make sure that each lid is just a little larger than the circumference of the tin you are making it for). Use the off-cuts from the lids to make leaves to decorate the pies.

Using a rolling pin to help you, line all three tins with the pastry. Push the pastry up the sides of the tins to the top ensuring there are no holes or cracks anywhere.
Fill the pies with the respective fillings. Make sure the fillings reach about an inch from the top of the tins.
Brush the top of the pastry case with beaten egg then place the lids on top, crimping the edges well to seal.
Using a small sharp knife, make crosses in the middle of the lids and peel up the corners to reveal a hole. Stick a fresh bay leaf in each hole to keep it open whilst cooking and also to add flavour.
Bake the pies for 30 minutes, then remove the smallest pie. Turn the oven down to 160C/325F/Gas 3 and bake the medium-sized pie for a further hour and the largest for a further 1½ hours.
When the pies are cooked, carefully unfurl the sides of the springform tins and remove (keep the base in place) – if the pastry is too soft to hold its shape, secure the sides of the tin and return to the oven for a few minutes before testing again. Brush the sides with beaten egg and stick the reserved pastry leaves all around the outside then egg wash again. Return to the oven for a final 30 minutes, or until golden-brown.
Meanwhile, make the purées. Chop the prunes and mix them with a splash of water. Blend to a purée using a handheld blender. Taste and add approximately 10g/⅓oz sugar, or sweeten as desired. Transfer to a piping bag fitted with a plain nozzle and set aside.
Next make the apple purée. Put the apple in a pan with a few tablespoons of water and 10g/⅓oz sugar and cook until the apple is soft. Blend to a purée using a handheld blender and set aside to cool slightly. Spoon the purée into small serving dishes and set aside. Repeat the process using the rhubarb, but adding a little more sugar.
For the decoration, when the pies are cooked remove the bases of the tins and transfer to a cooling rack.
Remove the bay leaves and place each pie on its corresponding cake base.
Insert four dowels into the 20cm/8in pie and five into the 15cm/6in pie. Place the pies on top of each other on a circular wooden chopping board with the 10cm/4in pie at the top.
Decorate the tiers with edible flowers, bay leaves and fresh parsley. Serve the pies with the purées.


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toyz.web package¶
Submodules¶
toyz.web.app module¶
Runs the webapp for Toyz
- class toyz.web.app.AuthHandler¶
Subclass for all secure handlers.
- get_current_user()¶
Load the name of the current user
- class toyz.web.app.AuthLoginHandler(application, request, **kwargs)¶
Bases: toyz.web.app.AuthHandler, tornado.web.RequestHandler
- get()¶
Send the login.html page to the client
- initialize()¶
When the handler is initialized, set the path to the template that needs to be rendered
- post()¶
Load the user_id and password passed to the server from the client and check authentication
- set_current_user(user_id)¶
Send a secure cookie to the client to keep the user logged into the system
- Parameters
- user_id (string ): User id of the current user
- class toyz.web.app.AuthLogoutHandler(application, request, **kwargs)¶
Bases: tornado.web.RequestHandler
- get()¶
Clear the users cookie and log them out
- class toyz.web.app.AuthMainHandler(application, request, **kwargs)¶
Bases: toyz.web.app.MainHandler
toyz.web.app.MainHandler extensions when using secure cookies.
- get(*args, **kwargs)¶
- class toyz.web.app.AuthStaticFileHandler(application, request, **kwargs)¶
Bases: toyz.web.app.AuthHandler, tornado.web.StaticFileHandler
Handles static files and checks for a secure user cookie and that the user has permission to view the file.
- get(*args, **kwargs)¶
- validate_absolute_path(root, full_path)¶
Check that the user has permission to view the file
- class toyz.web.app.AuthToyzStaticFileHandler(application, request, **kwargs)¶
Bases: toyz.web.app.AuthHandler, toyz.web.app.ToyzStaticFileHandler
Secure handler for all toyz added to the application. This handles security, such as making sure the user has a registered cookie and that the user has acces to the requested files.
- get(*args, **kwargs)¶
- class toyz.web.app.AuthToyzTemplateHandler(application, request, **kwargs)¶
Bases: toyz.web.app.AuthHandler, toyz.web.app.ToyzTemplateHandler
- get(*args, **kwargs)¶
- class toyz.web.app.MainHandler(application, request, **kwargs)¶
Bases: toyz.web.app.ToyzHandler
Main Handler when user connects to localhost:8888/ (or whatever port is used by the application).
- get(*args, **kwargs)¶
Render the main web page
- get_template_path()¶
Get the path for the main webpage
- initialize(template_name, template_path)¶
Initialize handler
- class toyz.web.app.ToyzHandler(application, request, **kwargs)¶
Bases: tornado.web.RequestHandler
Not yet implemented
- get_current_user()¶
Load the name of the current user
- get_toyz_path(path)¶
Given a toyz path, return the root path for the toy.
- get_user_id()¶
- class toyz.web.app.ToyzStaticFileHandler(application, request, **kwargs)¶
Bases: toyz.web.app.ToyzHandler, tornado.web.StaticFileHandler
Handler for all toyz added to the application.
- get(*args, **kwargs)¶
Called when the application recieves a get command from the client.
- class toyz.web.app.ToyzTemplateHandler(application, request, **kwargs)¶
Bases: toyz.web.app.ToyzHandler, tornado.web.RequestHandler
- Not yet implemented*
- get(*args, **kwargs)¶
- get_template_path()¶
- initialize(**options)¶
Initialize handler
- class toyz.web.app.ToyzWebApp¶
Bases: tornado.web.Application
Web application that runs on the server. Along with setting up the Tornado web application, it also processes jobs sent to the server from clients.
- close_session(session)¶
Close a websocket session and delete any temporary files or directories created during the session. To help ensure all temp files are deleted (in case of a server or client error), if the user doesn’t have any open session his/her temp directory is also deleted.
- find_open_port(port)¶
Begin at port and search for an open port on the server
- new_session(user_id, websocket)¶
Open a new websocket session for a given user
- Parameters
- user_id ( toyz.utils.core.ToyzUser ): User id websocket (toyz.web.app.WebSocketHandler ): new websocket opened
- process_job(msg)¶
Currently all jobs are run directly from the web app. Later a job server might be implemented that will maintain a queue of long duration jobs, so this function will be used to tag the batch jobs and send them to the job application.
- Parameters
- msg (dict): Message sent from web client (see toyz.utils.core.run_job() for the format of the msg)
- respond(response)¶
Once a job has completed, including jobs run by an external job application, send the response to the user. Also, update any objects that need to be updated.
- Parameters
- response (dict ): Message to send to the user. See toyz.utils.core.run_job() for the format of the msg.
- run_job(*args, **kwargs)¶
Run a job by opening a new process (possible on a new cpu) and passing the job and parameters to the process. This function is actually a generator of a Future() object, so the exception tornado.gen.Return is raised to return the result.
In the future this function will be modified to be threaded for certain types of web applications, allowing variables to be passed more easily and stored in work environments when that type of usage is prefereable.
- Parameters
- msg (dict): Message sent from web client (see toyz.utils.core.run_job() for the format of the msg)
- Returns
- result (future containing a dict ): Message to send back to the user. If there is no response, then result={}
- update(attr)¶
Certain properties of the application may be changed by an external job, for example a user may change his/her password, a new user may be created, a setting may be changed, etc. When this happens the job notifies the application that something has changed and this function is called to reload the property.
- Parameters
- attr (string ): Name of attribute that needs to be updated. So far only toyz_settings is supported
- class toyz.web.app.WebSocketHandler(application, request, **kwargs)¶
Bases: tornado.websocket.WebSocketHandler
Websocket that handles jobs sent to the server from clients
- on_close()¶
Called when the websocket is closed. This function calls the applications -toyz.web.app.ToyzWebApp.close_session)() function.
- on_message(message)¶
Called when the websocket recieves a message from the client. The user and session information is then extracted and processed before running the job initiated by the client. Only modules and toyz that the user has permission to view are accepted, all others return a toyz.utils.errors.ToyzJobError .
- Parameters
- message (JSON unicode string ): see( toyz.utils.core.run_job() for the format of the msg)
- toyz.web.app.init_web_app()¶
Run the web application on the server
toyz.web.tasks module¶
While each toy may contain a large number of functions, only the functions located in the tasks.py file will be callable from the job queue.
- toyz.web.tasks.add_new_user(toyz_settings, tid, params)¶
Add a new user to the toyz application.
- Parameters
- toyz_settings ( toyz.utils.core.ToyzSettings): Settings for the toyz application
- tid (string ): Task ID of the client user running the task
- params (dict ): Any parameters sent by the client (see params below)
- Params
- user_id (string ): Id of user to add
- Response
- id: ‘notification’
- func: ‘add_new_user’
- msg: ‘User/Group added correctly’
- toyz.web.tasks.change_pwd(toyz_settings, tid, params)¶
Change a users password.
- Parameters
- toyz_settings ( toyz.utils.core.ToyzSettings): Settings for the toyz application
- tid (string ): Task ID of the client user running the task
- params (dict ): Any parameters sent by the client (see params below)
- Params
- current_pwd (string ): Users current password. Must match the password on file or an exception is raised
- new_pwd (string ): New password
- confirm_pwd (string ): Confirmation of the the new password. If new_pwd and confirm_pwd do not match, an exception is raised
- Response
- id: ‘notification’
- func: ‘change_pwd’
- msg: ‘Password changed successfully’
- toyz.web.tasks.create_dir(app, id, params)¶
Creates a new path on the server (if it does not already exist).
- Parameters
- toyz_settings ( toyz.utils.core.ToyzSettings): Settings for the toyz application
- tid (string ): Task ID of the client user running the task
- params (dict ): Any parameters sent by the client (see params below)
- Params
- path (string ): path to create on the server
- Response
- id: ‘create_folder’, status (string ): ‘success’, path (string ): path created on the server
- toyz.web.tasks.load_directory(toyz_settings, tid, params)¶
Used by the file browser to load the folders and files in a given path.
- Parameters
- toyz_settings ( toyz.utils.core.ToyzSettings): Settings for the toyz application
- tid (string ): Task ID of the client user running the task
- params (dict ): Any parameters sent by the client (see params below)
- Params
- path (string ): Path to search
- Response
- id: ‘directory’
- path (string ): path passed to the function
- shortcuts (dict ): Dictionary of shortcut_name: shortcut_path ‘s for the user
- folders (list of strings): folders contained in the path
- files (list of strings): files contained in the path
- parent (string ): parent directory of current path
- toyz.web.tasks.load_user_info(toyz_settings, tid, params)¶
Load info for a given user from the database
- Parameters
- toyz_settings ( toyz.utils.core.ToyzSettings): Settings for the toyz application
- tid (string ): Task ID of the client user running the task
- params (dict ): Any parameters sent by the client (see params below)
- Params
- user_id or group_id (string ): User or group to load parameters for
- user_attr (list ): List of user attributes to load
- Response
- id: ‘user_info’
- Each attribute requested by the client is also returned as a key in the response
- toyz.web.tasks.load_user_settings(toyz_settings, tid, params)¶
Load settings for a given user
- Parameters
- toyz_settings ( toyz.utils.core.ToyzSettings): Settings for the toyz application
- tid (string ): Task ID of the client user running the task
- params (dict ): Any parameters sent by the client (None for this function)
- Response for all users
- id: ‘user_settings’
- shortcuts (dict ): Dictionary of shortcut_name: shortcut_path ‘s for the user
- workspaces (dict ): Dictionary of workspace_name: workspace_settings for the user
- Additional response keys for users in the modify_toyz group
- modules (list ): List of toyz modules the user can run
- toyz (dict ): Dictionary of toy_name: path_to_toy ‘s that the user can run
- Additional reponse keys for admins
- config (dict ): Configuration settings for the application
- db (dict ): Database settings
- web (dict): Web settings
- security (dict ): Security settings
- users (list ): list of all users in the database
- groups (list ): list of all groups in the database
- user_settings (dict ): Settings for a specified user (initially the admin)
- group_settings (dict ): Settings for a specified group (initially the admin group)
- toyz.web.tasks.save_user_info(toyz_settings, tid, params)¶
Save a users info. If any admin settings are being changed, ensures that the user is in the admin group.
- Parameters
- toyz_settings ( toyz.utils.core.ToyzSettings): Settings for the toyz application
- tid (string ): Task ID of the client user running the task
- params (dict ): Any parameters sent by the client (see params below)
Params can be any settings the user has permission to set on the server.
- Response
- id: ‘notification’
- func: ‘save_user_info’
- msg: ‘Settings saved for <user_id>’


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|
| void | rt_task_conf_init (rt_task_conf_t *conf) |
| | Initialize a task scheduler configuration with default values. More...
|
| |
| int | rt_task_cluster_init (rt_task_cluster_t *cluster, rt_task_conf_t *conf, rt_event_t *event) |
| | Open a cluster task scheduler. More...
|
| |
| void | rt_task_cluster_deinit (rt_task_cluster_t *cluster, rt_event_t *event) |
| | Close a cluster task scheduler. More...
|
| |
| static void | rt_task_init (rt_task_t *task, void(*entry)(rt_task_t *task, int id)) |
| | Initialize a task. More...
|
| |
| static void | rt_task_cores (rt_task_t *task, int nb_cores) |
| | Set the number of cores of a task. More...
|
| |
| static void | rt_task_stacks (rt_task_t *task, void *stacks, int size) |
| | Set the stacks of a task. More...
|
| |
| void | rt_task_fc_push (rt_task_cluster_t *cluster, rt_task_t *task, rt_event_t *event) |
| | Push a task from fabric controller side. More...
|
| |
| void | rt_task_cl_push (rt_task_t *task) |
| | Push a task from cluster side. More...
|
| |
| void | rt_task_cl_wait (rt_task_t *task) |
| | Wait for a task completion. More...
|
| |
The cluster task scheduler is an alternative to the default fork/join execution model used on the cluster side. It can be used when the cluster code can be better parallelized using task pipelining rather than the fork/join pattern. It provides the following features:
- A task is a structure which contains an entry point and arguments and can be pushed to cluster side for execution.
- Once popped by a core, it will be executed until completion, and the core can then proceed with another task.
- Tasks are popped by cluster cores in parallel.
- Tasks can be pushed to the cluster from either the fabric contoroller or the cluster.
- A task can be multicore. Several cores will pop it and will get assigned a different ID.
- Tasks can be assigned default global stacks or assigned specific stacks.
- Task termination for tasks pushed from fabric controller is managed through the usual event mechanism, and through explicit wait for tasks pushed from cluster side.
◆ rt_task_cl_push()
| void rt_task_cl_push |
( |
rt_task_t * |
task | ) |
|
This function can be called to push a task for execution from cluster side. The task is pushed to the cluster from which this function is called. Once this function is called, the task must not be modified anymore. This function must be called only from cluster side.
- Parameters
-
| task | A pointer to the task structure. |
◆ rt_task_cl_wait()
| void rt_task_cl_wait |
( |
rt_task_t * |
task | ) |
|
This function can be called to block execution until the specified task is over. This can be called only for tasks which has been pushed through rt_task_cl_push. This function must be called only from cluster side.
- Parameters
-
| task | A pointer to the task structure. |
◆ rt_task_cluster_deinit()
| void rt_task_cluster_deinit |
( |
rt_task_cluster_t * |
cluster, |
|
|
rt_event_t * |
event |
|
) |
| |
This function can be called to close a cluster task scheduler and free all allocated resources. Once it is called, the cluster can be used again with the default fork/join execution model. This function must be called only once no task is executing or ready to be executed in the scheduler. This function can only be called from fabric controller side.
- Parameters
-
| cluster | A pointer to the cluster structure. This structure can be freed once this call is over. |
| event | The event used for managing termination. |
◆ rt_task_cluster_init()
| int rt_task_cluster_init |
( |
rt_task_cluster_t * |
cluster, |
|
|
rt_task_conf_t * |
conf, |
|
|
rt_event_t * |
event |
|
) |
| |
This function can be called to setup the specified cluster so that it is ready to execute tasks. This function can only be called from fabric controller side.
- Parameters
-
| cluster | A pointer to the cluster structure. This structure must be kept alive until the task scheduler is closed. |
| conf | A pointer to the task scheduler configuration. |
| event | The event used for managing termination. |
- Returns
- 0 if the operation is successfull, or -1 if it failed.
◆ rt_task_conf_init()
This function can be called to get default values for all parameters before setting some of them. The structure containing the configuration must be kept alive until the task scheduler is opened. Calling this function will make sure that the task scheduler is created for all cores on cluster 0, with allocated stacks of 512 bytes per core.
- Parameters
-
| conf | A pointer to the task scheduler configuration. |
◆ rt_task_cores()
| static void rt_task_cores |
( |
rt_task_t * |
task, |
|
|
int |
nb_cores |
|
) |
| |
|
inlinestatic |
This function can be called to set the number of cores which will execute the task. The task will remain in the queue until the specified number of cores has popped the queue and each core will get a different task ID.
- Parameters
-
| task | A pointer to the task structure. |
| nb_cores | Number of cores |
◆ rt_task_fc_push()
| void rt_task_fc_push |
( |
rt_task_cluster_t * |
cluster, |
|
|
rt_task_t * |
task, |
|
|
rt_event_t * |
event |
|
) |
| |
This function can be called to push a task for execution from fabric controller side. Once this function is called, the task must not be modified anymore. This function must be called only from fabric controller side.
- Parameters
-
| cluster | A pointer to the cluster structure of the cluster where the task must be pushed. |
| task | A pointer to the task structure. |
| event | The event used for managing termination. |
◆ rt_task_init()
| static void rt_task_init |
( |
rt_task_t * |
task, |
|
|
void(*)(rt_task_t *task, int id) |
entry |
|
) |
| |
|
inlinestatic |
This function must be called before a task is pushed to initialize it. This is the only mandatory function to be called on a task before it is pushed. If no more function is called on the task, the task is configured as a single core task with no specific stack.
- Parameters
-
| task | A pointer to the task structure. This structure must be kept alive until the task has finished execution. |
| entry | The task entry point. |
◆ rt_task_stacks()
| static void rt_task_stacks |
( |
rt_task_t * |
task, |
|
|
void * |
stacks, |
|
|
int |
size |
|
) |
| |
|
inlinestatic |
This function can be called to set the stacks that the cores will use to execute the task. This must contain one stack for each core which will execute the task.
- Parameters
-
| task | A pointer to the task structure. |
| stacks | The lowest address of the area containing the stacks for all cores. |
| size | The size of the stack of one core. |


Welcome to your first coding challenge!
The purpose of this challenge is to help ensure you have grasped the material we have covered so far in this course. Please follow the steps below as best you can. Don't be afraid to raise your hand and ask if you are stuck on something - I'm here to help!
Please create a new project containing the two following pages:
- An index.html page
- A contact.html page
Your pages should both include AT LEAST the following elements (bonus points if you use more!):
- HTML5 [nav] with navigation linking to the other page (if on the index page, should link to the contact page, and vice versa)
- An HTML5 [section] that contains placeholder text and a 200x200px placeholder image
- In your contact page, create a [form] element with two different types of [inputs]
Please add 3 of the following style rules to either (or both!) of your pages:
- A fixed nav bar with a background color that takes up 100% of the browser length
- display: flex to style the content on your page
- A box-shadow or text-shadow on one of your elements
- Text with a :hover or :active effect
- A fun font from google fonts, applied to any or all elements
- A CSS reset
*You must use at least (1) element selector, (1) class selector, and (1) id selector in your code.*
Happy coding!


|
| string | uuid [get, set] |
| | A unique identifier for this Call. More...
|
| |
| string | conversation_uuid [get, set] |
| | A unique identifier for the Conversation this Call is part of. More...
|
| |
| Endpoint | to [get, set] |
| | The single or mixed collection of endpoint types you connected to.Possible value are: phone - phone numbers in e.164 format.Options are: number - the phone number to connect to in E.164 format. dtmfAnswer - Set the digits that are sent to the user as soon as the Call is answered.The* and # digits are respected. You create pauses using p. Each pause is 500ms. More...
|
| |
| Endpoint | from [get, set] |
| | The endpoint you called from. Possible values are the same as to More...
|
| |
| string | direction [get, set] |
| | Possible values are outbound or inbound. More...
|
| |
| string | recording_url [get, set] |
| | The URL to download a call or conversation recording from. More...
|
| |
| DateTime? | start_time [get, set] |
| | The time the Call started More...
|
| |
| string | network [get, set] |
| | The Mobile Country Code Mobile Network Code (MCCMNC) for the carrier network used to make this Call. More...
|
| |
| string | status [get, set] |
| | The status of the Call. Possible values are: started - Platform has stared the Call. ringing - the user's handset is ringing. answered - the user has answered your Call. timeout - your user did not answer your Call with ringing_timer. machine - Platform detected an answering machine. completed - Platform has terminated this Call. More...
|
| |
| decimal | rate [get, set] |
| | The price per minute for this Call. More...
|
| |
| decimal | price [get, set] |
| | The total price charged for this Call. More...
|
| |
| int | duration [get, set] |
| | The time elapsed for the Call to take place in seconds. More...
|
| |
| DateTime? | end_time [get, set] |
| | The time the Call ended More...
|
| |
◆ conversation_uuid
| string Nexmo.Api.Voice.Call.CallResponse.conversation_uuid |
|
getset |
A unique identifier for the Conversation this Call is part of.
◆ direction
| string Nexmo.Api.Voice.Call.CallResponse.direction |
|
getset |
Possible values are outbound or inbound.
◆ duration
| int Nexmo.Api.Voice.Call.CallResponse.duration |
|
getset |
The time elapsed for the Call to take place in seconds.
◆ end_time
| DateTime? Nexmo.Api.Voice.Call.CallResponse.end_time |
|
getset |
◆ from
| Endpoint Nexmo.Api.Voice.Call.CallResponse.from |
|
getset |
The endpoint you called from. Possible values are the same as to
◆ network
| string Nexmo.Api.Voice.Call.CallResponse.network |
|
getset |
The Mobile Country Code Mobile Network Code (MCCMNC) for the carrier network used to make this Call.
◆ price
| decimal Nexmo.Api.Voice.Call.CallResponse.price |
|
getset |
The total price charged for this Call.
◆ rate
| decimal Nexmo.Api.Voice.Call.CallResponse.rate |
|
getset |
The price per minute for this Call.
◆ recording_url
| string Nexmo.Api.Voice.Call.CallResponse.recording_url |
|
getset |
The URL to download a call or conversation recording from.
◆ start_time
| DateTime? Nexmo.Api.Voice.Call.CallResponse.start_time |
|
getset |
The time the Call started
◆ status
| string Nexmo.Api.Voice.Call.CallResponse.status |
|
getset |
The status of the Call. Possible values are: started - Platform has stared the Call. ringing - the user's handset is ringing. answered - the user has answered your Call. timeout - your user did not answer your Call with ringing_timer. machine - Platform detected an answering machine. completed - Platform has terminated this Call.
◆ to
| Endpoint Nexmo.Api.Voice.Call.CallResponse.to |
|
getset |
The single or mixed collection of endpoint types you connected to.Possible value are: phone - phone numbers in e.164 format.Options are: number - the phone number to connect to in E.164 format. dtmfAnswer - Set the digits that are sent to the user as soon as the Call is answered.The* and # digits are respected. You create pauses using p. Each pause is 500ms.
◆ uuid
| string Nexmo.Api.Voice.Call.CallResponse.uuid |
|
getset |
A unique identifier for this Call.
The documentation for this class was generated from the following file:
- C:/Users/slore/Documents/projects/slorello89/nexmo-dotnet/Nexmo.Api/Voice/Call.cs