'3BlackChicks Review...'
SWORDFISH (2001) Rated R; running time 95 minutes Genre: Action Seen at: Jack Lokes' Celebration Cinema (Lansing, Michigan) Official site: http://www.operationswordfish.com/ IMDB site: http://us.imdb.com/Details?0244244 Written by: Skip Woods Directed by: Dominic Sena Cast: John Travolta, Hugh Jackman, Halle Berry, Don Cheadle, Camryn Grimes, Vinnie Jones, Sam Shepard
Review Copyright Rose Cooper, 2001 Review URL: http://www.3blackchicks.com/bamsswordfish.html
Glory be, Halle was actually *good* in this one. Maybe she should loose her breastesses more often; removing that sling seemed to have had a freeing effect on her acting.
The Story (WARNING: **spoilers contained below**) Gabriel Shear (John Travolta) needs a few good men to help him liberate nine billion dollars from a high-security government computer, to fund a project which I will not spoil for you [unlike a few of my fellow reviewers. But that's Another Rant For Another Time]. Enter Stanley Jobson (Hugh Jackman), a former "hacker" [*cracker*, dammit!] who served two years in prison for doing Bad Things to a computer that didn't belong to him, and isn't allowed to see his daughter Holly (Camryn Grimes) because her drunk shrew of a mother got a court order against him.
Gabriel sends his assistant, Ginger (Halle Berry), off to recruit Stan to break into the supercomputer, with promises of helping Stan regain custody of Holly - not to mention a few million dollars of his own - as incentive. But Stan, who could go to prison for simply *touching* a computer again, must elude the agent who put him away in the first place - burnt-out cybercrimes supersluth Agent Roberts (Don Cheadle) - and try to figure out how to survive Gabriel, aka The World's Most Dangerous Spy.
The Upshot: Oh, I reckon I could kvetch about how SWORDFISH slung around TechnoBabble like it was going out of style, and how laughingly AOL-ish Stan's Graphical Hydra was ["You've Got Worms!"], and how Dell is making beaucoup bux from product placement, and how this movie was chock full of gratuitous dialogue and shots (and nope, I'm not just playa-hatin' on Halle's Friends), and ultimately, how derivative SWORDFISH was of any number of Summer Action Flicks (pick one, *any* one; start with John Travolta's BROKEN ARROW, mix in DIE HARD, work a little SPEED in there...you get my drift).
I reckon I could, but I won't - because SWORDFISH was exactly what it set out to be: a straight-ahead Summer Testosterone Rush wrapped up in Action Flick clothing. I can diggit.
I have to admit, too, that Halle Berry really surprised me; she worked this flick like nobody's business. Berry and John Travolta left poor Hugh Jackman in the dust (much in the way Christopher Walken walked all over doe-eyed Johnny Depp in the similar daddy-struggles-to-save-his-kid actioner, NICK OF TIME). None of their characters were all that deep, though at least they weren't completely predictable, or written wholly in good/evil tones. Yes, I gave a bah humbug to Gabriel's Declaration of exactly who he was, but by that point in the movie, even the blatant compugeek name-dropping ["Torvalds"? Guffaw!] or the underuse of Don Cheadle and Vinnie Jones (Marco), didn't phase me anymore.
I do have one true complaint, though: the first 15 or so minutes, set a "Matrix"-like pace that the next 80 or so minutes lived up to only sporadically; let's just say that director Dominic Sena blew too much of his action wad in the trailer (yes, I know; not his fault). Still, SWORDFISH was interesting - ok, I'll admit it: fun - even when it was downright silly.
And the irony of Gabriel's monologue about Bad Movies - especially considering Travolta's last two contributions to the world of Ugly Cinema: LUCKY NUMBERS ad BATTLEFIELD EARTH - was completely delicious.
The "Black Factor" [ObDisclaimer: We Are Not A Monolith]: If you've visited the 3BC "Viewer Voices" webboard lately (and if you haven't, you should), you'll notice that some of us have been discussing Halle Berry's decision to bare her breasts, for - as rumor would have it (a rumor she's since denied) - $500,000 [another irony, considering what the Stan character was paid to talk to her character's boss. But I digress]. Much of the discussion on the VV board centered around a statement Berry was said to have made as to why she did her first semi-nude movie scene; a 3BC reader saw an interview in which Berry was quoted as saying:
"For the first ten years of my film career, I've always said no to nudity. I wouldn't even read a script that called for nudity. But a lot has changed in my life...So, I finally feel free to explore myself as an artist. Not to say that the minute I got that revelation I decided to take my clothes off. But I feel free to make choices from an artistic standpoint, and that's a very empowered place to be. But instead of focusing on a role you might not approve of, I'd like people to note that this was a role written for a white woman, opposite a big star like John Travolta. Doesn't this take us to another level in the industry as black women?"
My take on the matter? First, as long as she's not hurting anyone in the process, I don't think Halle Berry owes anybody any explanations for what she chooses to do with her body, on- or off-screen.
But please, Ms. Berry, don't be fooled into thinking that showing your Perky Tits (tm, alt.tv.homicide) is any Giant Leap For Blackwomankind, especially as done in the (mostly gratuitous, though still effective) SWORDFISH scene. Political Statement, it ain't. Not that Hugh Jackman and half the men (and some of the women) in America, mind. But you go, girl, and don't sweat about having to Uplift The Race; uplift your asking salary, even if you have to uplift your breasts to do it. I ain't mad atcha.
Bammer's Bottom Line: Call it derivative, call it an homage, but SWORDFISH made me hungry [nyuk nyuk] for a little DOG DAY AFTERNOON action. I wonder if (ObProductPlacement) Netflix's open this late at night...
SWORDFISH (rating: greenlight): Wanna bet that Halle's Pups'll get nominated for two MTV Movie Awards?
Rose "Bams" Cooper Webchick and Editor, 3BlackChicks Review Entertainment Reviews With Flava! Copyright Rose Cooper, 2001 EMAIL<EMAIL_ADDRESS>http://www.3blackchicks.com/
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
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Related links: index of all rec.arts.movies.reviews reviews


With the ShakeAlert system, there are hundreds
of seismometers installed throughout California,
Oregon, and Washington along the many faults that
can produce earthquakes. When shaking begins, the
location and magnitude of an earthquake is rapidly
estimated by analyzing the first shaking measured
by sensors near the source. All earthquakes start
small and initially grow at the same rate. It is not
possible to determine immediately after an earthquake
starts how large it will eventually become. Once
an earthquake is detected, the expected ground-
shaking severity across a region is estimated,
and alerts are sent to local populations before
larger, more damaging shaking arrives. The
ShakeAlert System continues to refine these
ground motion estimates and updates its alert
as the earthquake grows and more sensor data
become available. Typically, more distant
locations will have more time to act but will
experience less intense shaking. The USGS has
been developing the ShakeAlert System for the
West Coast since 2006, jointly with partners from
state governments, universities, and private
foundations. ShakeAlert centers in Seattle, the
San Francisco Bay area and the Los Angeles area,
but are not fully integrated across the West Coast,
but the system is not yet issuing public alerts.
The ShakeAlert system provides real time
earthquake alerting. Because the system is in
real time, occasionally it can behave in ways
that we may not expect it to. You might feel
shaking but did not get an alert or you might
get an alert and not feel shaking.
Types of alerts you may see:
| Intensity | Shaking |
|---|---|
| I | Not felt |
| II | Weak |
| III | Weak |
| IV | Light |
| V | Moderate |
| VI | Strong |
| VII | Very Strong |
| VIII | Severe |
| IX | Violent |
| X | Extreme |


|
Steam Audio API
2.0-beta.18
|
Functions for controlling an Environment object, which is used to export data to the audio engine. More...
Functions | |
| IPLAPI IPLerror | iplCreateEnvironment (IPLhandle context, IPLhandle computeDevice, IPLSimulationSettings simulationSettings, IPLhandle scene, IPLhandle probeManager, IPLhandle *environment) |
| Creates an Environment object. More... | |
| IPLAPI IPLvoid | iplDestroyEnvironment (IPLhandle *environment) |
| Destroys an Environment object. More... | |
| IPLAPI IPLvoid | iplSetNumBounces (IPLhandle environment, IPLint32 numBounces) |
| Sets the number of bounces to use for real-time simulations that use an Environment object. More... | |
Functions for controlling an Environment object, which is used to export data to the audio engine.
A typical usage scenario for Phonon involves a game engine that must specify geometry and material information to DSP effects that are applied by the audio engine. The Environment object is the mechanism for doing so. It is the only object that must be passed from the game engine into the audio engine, and it encapsulates all information that DSP effects may need from the game engine. If you are not using physics-based sound propagation features, you still need to create an Environment object. After you create an Environment object, how you pass it from the game engine to the audio engine depends on how your game engine and audio engine are designed.
| IPLAPI IPLerror iplCreateEnvironment | ( | IPLhandle | context, |
| IPLhandle | computeDevice, | ||
| IPLSimulationSettings | simulationSettings, | ||
| IPLhandle | scene, | ||
| IPLhandle | probeManager, | ||
| IPLhandle * | environment | ||
| ) |
Creates an Environment object.
It is necessary to call this function even if you are not using the sound propagation features of Phonon.
| context | The Context object used by the game engine. |
| computeDevice | Handle to a Compute Device object. Only required if using Radeon Rays for ray tracing, or if using TrueAudio Next for convolution, may be NULL otherwise. |
| simulationSettings | The settings to use for simulation. This must be the same settings passed to iplCreateScene or iplLoadScene , whichever was used to create the Scene object passed in the scene parameter to this function. |
| scene | The Scene object. May be NULL , in which case only direct sound will be simulated, without occlusion or any other indirect sound propagation. |
| probeManager | The Probe Manager object. May be NULL if not using baked data. |
| environment | [out] Handle to the created Environment object. |
Destroys an Environment object.
If any other API objects are still referencing the Environment object, it will not be destroyed; destruction occurs when the object's reference count reaches zero.
| environment | [in, out] Address of a handle to the Environment object to destroy. |
Sets the number of bounces to use for real-time simulations that use an Environment object.
Calling this function overrides the value of bounces
set on the IPLSimulationSettings
structure passed when calling iplCreateEnvironment
to create this Environment object.
| environment | Handle to an Environment object. |
| numBounces | The number of bounces to use for all subsequent simulations in the Environment. |


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Design elements, playground and code snippets for Bootstrap HTML/CSS/JS framework
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My name is {{ name }}.
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Dict:
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AAAAAAAAAAAAAAAAAAAAAAA!{{age+2}}
{{ say() }}
My name is {{ name }}.
My age is {{ age + 1 }}.
My skills are:
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AAA
BBB
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Kevin Hart gets behind wheel of car 'without a seat belt' weeks after crash
The actor and comedian, 40, narrowly cheated death back in September and he's now reportedly been spotted sitting in a car without strapping himself in
by Brogan-Leigh HurstKevin Hart has reportedly been spotted getting behind the wheel of a muscle car without a seat belt just two months after breaking his spine in a near-fatal crash.
The comedian, 40, was seen smiling as he got into a '69 Camaro in Calabasas, California.
The vintage car was of similar era to the one he almost died in a few weeks back on September 1.
According to TMZ , Kevin pulled away without having put on a seatbelt just two months after his near-death experience.
The incident comes just days after the Hollywood funnyman shared an emotional video telling fans that he is "thankful for simply still being here".
Explaining the traumatic crash, he said: "After my accident I see things differently, I see life from a whole new perspective.
"My appreciation for life is through the roof. I'm thankful for my family, my friends."
He thanked fans for their "love and support," adding: "Don't take today for granted because tomorrow's not promised.
"More importantly I'm thankful for God, I'm thankful for life. I'm thankful for simply still being here."
The actor was a passenger in a 1970 Plymouth Barracuda when the driver lost control, sped down an embankment and smashed into a tree near Malibu.
He was left with major back injuries from the accident, which authorities blamed on reckless driving.
As he recovered, Kevin had to use a walking frame to stand up, and was also filmed undergoing physical therapy lessons at his home.
Mirror Online has contacted a representative for Kevin for comment.
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{% extends 'core/base.html' %} {% block title %}Edit coordinator | {% endblock %} {% block content %}
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events
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This is not the same as the username!


Welcome!
Hi there, thank you for checking out my website. I was born in Philadelphia, Pennsylvania and grew up in an entirely Spanish speaking school environment. I gained an interest in Music at an early age, and began playing piano at age 10. At age 14, I was accepted into and attended a performing arts school in Midland, PA with a focus in piano.
After graduating high school, I moved to Cleveland, OH for a short period of time until going to Berklee College of Music in Boston. I was accepted into the study abroad program in Valencia, Spain and studied music production as well as Piano/Bass performance. Around this time, my interest was equally as much in computers as it was in music, and I enjoyed learning beginners programming courses in my spare time while involved with music. I decided to move to Seattle after returning from Spain because of the opportunities for a career in technology as well as having a great music scene. I am grateful to be pursuing a meaningiful career in back-end software development, and believe that I can succeed.
Education History
- Lincoln Park Performing Arts Charter School - High School
- Berklee College of Music, Boston - B.S. in Professional Music
- Stanford Online - Certificate in Machine Learning from Coursera
- Code Fellows - Certificate in Software Development
Work Experience
- Music Instructor
- Works for Moore Brothers Music in Sammamish, WA. Manages a set of weekly students and develops a plan for each. Schedules projects and goals for students every semester.
- Member Consultant
- Worked for Boeing Employees Credit Union. Coordinated with teams to ensure success of branch. Operated back-end systems to complete operations for members.
- University IT Tech
- Carried out computer hardware/software troubleshooting inside of university classrooms. Worked with both MacOS and Windows.
Long-term goals
- Create a full-stack inventory management system from scratch.
- Run a marathon in the Seattle Area.
- Implement machine learning into a full-stack project.
- Work for/with the Raspberry Pi Foundation
Top Ten American Musicians
- Prince
- Dolly Parton
- Amy Winehouse
- Brad Paisley
- Lady Gaga
- Freddie Mercury
- Joni Mitchell
- Frank Sinatra
- Janis Joplin
- Jimi Hendrix


Class a.state.helper.tree
Class defined in:..\framework\appstorm\plugin\state.js:986
INTERNAL USE Tree manipulation used by state
Examples: here
flat
( tree, filler, converter
)
..\framework\appstorm\plugin\state.js:997
Flat a tree structure into an array one... Ex filler (must return an array, so send back empty array in case of problem) : function(item){return item.children;} Ex converter (must return something, even null) : function(item){return item.id;}
Parameters:-
tree
<Array>A tree structure to transform
-
filler
<Function>From an item, give back the potential list of children to add...
-
converter
<Function | null>Used to transform every items before they get into array
A flatten modified array
getItem
( tree, filler, tester
)
..\framework\appstorm\plugin\state.js:1034
Recursive search inside tree to find the first good element Ex : tester (id come from other scope) : function(item){if(item.id === id){return true;}; return false;} Ex : filler (must return an array, so send back empty array in case of problem) : function(item){return item.children;}
Parameters:-
tree
<Array>A tree structure to search inside
-
filler
<Function>From an item, give back the potential list of children to search inside...
-
tester
<Function>The function to test if item is the good one or not
An object selected, or null if no item found
isInBranch
( tree, filler, tester
)
..\framework\appstorm\plugin\state.js:1067
Check if the given tester found in the given tree
Parameters:-
tree
<Array>A tree structure to search inside
-
filler
<Function>From an item, give back the potential list of children to search inside...
-
tester
<Function>The function to test if item is the good one or not
True if the selected item is in given tree, false in other case
selectBranch
( tree, filler, tester
)
..\framework\appstorm\plugin\state.js:1083
Keep only branch where specific item appears Note : there is no return value because tree will be modified as a "pointed tree", so use tree after. Note : If you need to keep original tree, you need to duplicate the tree before using this function (use a.clone for that) Ex : tester (hash come from other scope) : function(item){if(item.hash === hash || item.hash === "*"){return true;}; return false;} Ex : filler (must return an array, so send back empty array in case of problem) : function(item){return item.children;}
Parameters:-
tree
<Array>A tree structure to select inside
-
filler
<Function>From an item, give back the potential list of children to search inside...
-
tester
<Function>The function to test if item is the good one or not
selectLevel
( tree, filler, level
)
..\framework\appstorm\plugin\state.js:1125
Get the given level inside a tree structure : example 1 => 2 => 4 => "something" 3 => 5 => "something"
If we want level 1, we get array [2, 3] (and 2, 3 contains 4, 5), if we want level 2, we get [4, 5] (nothing inside). This function is used to know loading/unloading sequence priority (we must unload 4 before 2, we must load 3 before 5...)
Parameters:-
tree
<Array>A tree structure to select inside
-
filler
<Function>From an item, give back the potential list of children to search inside...
-
level
<Integer>The level we are searching for


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--- layout: page weight: 100 title: Marketing Campaigns navigation: show: true seo: title: Marketing Campaigns override: true description: With SendGrid Marketing Campaigns, you will be able to load in contacts, create segments, create and send campaigns, view your stats, and so much more. ---
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{% anchor h2 %} Marketing Campaigns APIs {% endanchor %}Contact Database API - Create, manage, and segment your email lists via our Contacts API.
Campaigns API - Build and send Marketing Campaigns via our Campaigns API.


---
layout: post
title: Some Java Puzzlers in a powerpoint
date: '2013-04-19T15:32:00.001-05:00'
author: Steve Ash
tags:
modified_time: '2013-04-20T09:09:22.272-05:00'
blogger_id: tag:blogger.com,1999:blog-4471109663192942674.post-5471328281456014735
blogger_orig_url: http://blog.manycupsofcoffee.com/2013/04/some-java-puzzlers-in-powerpoint.html
---
Every week our team gets together on friday afternoons and have a presentation. The presenter rotates each week, and the topic can be programming language related, cool new libraries, theoretical -- or whatever related to our work.
I love doing Java Puzzlers since they do a great job of enriching your understanding of the language in a fun way. I've already done all of the Java Puzzlers that I could find from slides from Josh Bloche himeself. So this time I created my own, lifting the examples from the book.
In case this benefits anyone else-- here is mine: Java Puzzlers


THE FIRST WIVES CLUB
A film review by Michael Dequina
Copyright 1996 Michael Dequina
(PG) ** (out of ****)
Walking out of the big press screening for The First Wives Club, I couldn't help but feel as if I missed something. While the bulk of the audience, which had been laughing heartily during the film, left the theatre all aglow with laughter and smiles, I left thinking it wasn't anything remotely special, a light comedy that at best had its moments and at worst was trite, labored, and much too nice.
Goldie Hawn, Bette Midler, and Diane Keaton are ceaselessly energetic as three pushing-50 lifelong friends whose husbands who left them for younger women. Film producer Bill (Victor Garber) left aging, vain starlet Elise (Hawn) for an untalented ingenue (Elizabeth Berkley--'nuff said); electronics salesman Morty (Dan Hedaya) left the brash, zaftig Brenda (Midler) for sassy, svelte Shelly (a perfectly catty Sarah Jessica Parker); and ad exec Aaron (Stephen Collins) ditched the whiny, wimpy Annie (Keaton) for her psychotherapist, Leslie (Marcia Gay Harden). After an old friend (Stockard Channing) kills herself after her hubby (James Naughton) leaves her for a young trophy wife (Heather Locklear, wasted in a wordless cameo), the three form the First Wives Club, determined to exact painful revenge on their exes.
Problem is, the revenge isn't painful enough. For a feminist revenge fantasy, The First Wives Club is much too nice; the script by Robert Harling (based on Olivia Goldsmith's novel) doesn't have enough of a venomous edge: the trio's revenge antics aren't that nasty, and there aren't nearly enough acid one-liners--something is wrong if the best insults are those the three women direct toward each other, not the men. What makes this a greater shame is that the three stars are in peak form, obviously enjoying working with each other, having a ball. Hawn takes top acting honors, so very funny and convincing as a poster girl for plastic surgery; Keaton next, hilariously playing Annie's neuroses to the hilt; then Midler, who is no comic slouch but just has less of a character to work with than her co-stars.
There are some funny moments to be had, such as a couple of good one-liners and slapstick gags here and there, but for every one of those, there are a handful that don't quite work. An interlude at a lesbian bar is ripe with comic potential, but so little time is spent there that it does not pay off as well as it could have. One of the more crowd-pleasing sequences has the trio riding an out-of-control window-washing scaffold, but the rhythm of the scene is interrupted by a gratuitous, forced bit where a couple in bed recognizes Elise through the window and compliments her appearance. Director Hugh Wilson also attempts to add some seriousness to the proceedings, throwing in moments where the music grows more somber and the audience is cued to "feel" for the lead characters; these moments are at odds with the majority of the film, which often asks the viewer to not just laugh with, but at, the over-the-top heroines.
It would not surprise me if The First Wives Club became a word-of-mouth hit with women, especially older ones; the feminist message, the three stars, and the outrageous comedy will probably be enough. But for this (yes, male) viewer, it wasn't quite enough.
Michael Dequina<EMAIL_ADDRESS>Visit Mr. Brown's Movie Site at http://members.tripod.com/~MrBrown/
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


This site is a project to put together an animated slide show to be displayed at the 20x2 Chicago series of shows. The HTML and JavaScript files being used here are available for your use at Github.
Features of this slide show framework:
Images can be displayed with arbitrary text and graphics as overlays.
I use Animate.css for transitions, so this project already has several animation options out of the box.
You have some control over the randomness in choosing the next slide to display.
You can mark certain slides as "sponsor slides," so that they are shown more often (useful to advertise events, the venue, general information, etc.)
If you want to see a sample slide show, just click the button and away we go!


Code: Depression Depression
Depression involves recurrent, severe periods of clear-cut changes in mood, thought processes and motivation
lasting for a minimum of two weeks. Changes in thought processes typically include negative thoughts and
hopelessness. Depression also involves affects sleep/energy, appetite or weight.


---
layout: talk_reveal4
title: Evolutionary forecasting for SARS-CoV-2
venue: Northwest PGCoE
event: Monthly Meeting
author: Trevor Bedford
widescreen: true
---
Fred Hutchinson Cancer Center / Howard Hughes Medical Institute
$x' = \frac{x \, (1+s)}{x \, (1+s) + (1-x)}$ for frequency $x$ over one generation with selective advantage $s$ $x(t) = \frac{x_0 \, (1+s)^t}{x_0 \, (1+s)^t + (1-x_0)}$ for initial frequency $x_0$ over $t$ generations Trajectories are linear once logit transformed via $\mathrm{log}(\frac{x}{1 - x})$
Multinomial logistic regression across $n$ variants models the probability of a virus sampled at time $t$ belonging to
variant $i$ as
$$\mathrm{Pr}(X = i) = x_i(t) = \frac{p_i \, \mathrm{exp}(f_i \, t)}{\sum_{1 \le j \le n} p_j \, \mathrm{exp}(f_j \, t) }$$
with $2n$ parameters consisting of $p_i$ the frequency of variant $i$ at initial timepoint
and $f_i$ the growth rate or fitness of variant $i$.
The model is fit to minimize "log loss" of predicted variant vs observed variant across observations in
dataset.
Roughly 1 in 3 infections detected in 2021, while 1 in 40 in 2023
The hierarchical model allows pooling of growth advantages across locations. This allows us to
include locations with fewer sequences and to better estimate growth advantage of rare lineages.
Escape from antibodies that potently neutralize BA.2
{{ page.title }}
Trevor Bedford
{{ page.date | date: "%-d %b %Y" }}
{{ page.event }}
{{ page.venue }}
Slides at: bedford.io/talks
SARS-CoV-2 continues to show remarkable capacity for evolution
Mutations at spike S1 propel escape from population immunity
These mutations are accruing much more rapidly than other endemic viruses
New variants emerge that escape from existing population immunity and spread rapidly
Variant frequency dynamics
Population genetic expectation of variant frequency under selection
Variants show consistent frequency dynamics in logit space
Variants show consistent frequency dynamics in logit space
Multinomial logistic regression
MLR implemented in evofr package
location variant date sequences
Japan 22B 2023-02-10 242
Japan 22B 2023-02-11 56
Japan 22B 2023-02-12 70
Japan 22E 2023-02-10 80
Japan 22E 2023-02-11 21
Japan 22E 2023-02-12 27
USA 22B 2023-02-10 41
USA 22B 2023-02-11 23
USA 22B 2023-02-12 23
USA 22E 2023-02-10 368
USA 22E 2023-02-11 236
USA 22E 2023-02-12 246
...
Multinomial logistic regression fits variant frequencies well
Original VOC viruses had substantially increased transmissibility
Variant frequencies across countries from Feb 2022 to present
We find that recent variants like XBB.1.5 are ~300% fitter than original Omicron BA.1
Evolution driving epidemics
Many fewer reported cases in England post-Omicron
ONS Infection Survey provides rare source of ground truth
Partitioning ONS incidence based on sequencing data shows variant-driven epidemics
~110% population attack rate from March 2022 to March 2023
Post-Omicron period shows consistent IFR of 0.04%
Forecasting
Assessing MLR models for short-term frequency forecasting
MLR models generate accurate short-term forecasts
Now have clade and lineage forecasts continuously updated
Hierarchical MLR model
Initial frequency
Growth advantage
Japan
$p_{23A}$
$p_{23B}$
$f_{23A}$
$f_{23B}$
USA
$p_{23A}$
$p_{23B}$
$f_{23A}$
$f_{23B}$
hierarchical
$f_{23A}$
$f_{23B}$
Multinomial logistic regression should work well for SARS-CoV-2 prediction, except new variants have been emerging
fast enough that the prediction horizon is really quite short
Could we predict the spread of new mutations using DMS data?
Can calculate escape of arbitrary RBD against antibodies known to neutralize BA.2
Strong correlation between DMS immune escape and lineage-level MLR growth advantage
Continued research
SARS-CoV-2 genomic epi: Data producers from all over the world, GISAID and the Nextstrain team
Bedford Lab: John Huddleston,   James Hadfield,   Katie Kistler,   Thomas Sibley,   Jover Lee,   Cassia Wagner,   Miguel Paredes,   Nicola Müller,   Marlin Figgins,   Victor Lin,   Jennifer Chang,   Allison Li,   Eslam Abousamra,   Donna Modrell,   Nashwa Ahmed,   Cécile Tran Kiem


Constructor
new Network(socksPort, torController)
Initialize the downloader class
Parameters:
| Name | Type | Description |
|---|---|---|
socksPort |
number | - The proxy port for the tor network. |
torController |
Object | The torController controls all the tor instances and can be used to instantiate, kill or rotate IPs of instances. |
- Source:
Methods
addDataToPool(newData)
Add new data entries to the pool and notify the appropriate functions
Parameters:
| Name | Type | Description |
|---|---|---|
newData |
Array.<DbResult> | Contains new pool data to be downloaded |
- Source:
(async) detectMimeType(inputBuffer) → {Promise}
Try to detect the mimeType of the input buffer. This is useful
in cases where no content-type header is not set. This function is
basically an async wrapper for the callback based detection method
of mmmagic.
Parameters:
| Name | Type | Description |
|---|---|---|
inputBuffer |
String | Buffer | The buffer containing the data |
- Source:
Returns:
If the promise will be resolved, the
return string contains the mimeType.
If the promise is rejected, we were
not able to detect the mimeType and
therefor throw away the data.
- Type
- Promise
(async) download(dbResult) → {NetworkHandlerResponse}
Download a single webpage and handle the events around it.
Parameters:
| Name | Type | Description |
|---|---|---|
dbResult |
DbResult | Contains the DB result to be downloaded |
- Source:
Returns:
Return the downloaded and parsed
result
freeUpSlot()
Free up a slot and notify the appropriate functions
- Source:
(async) get(url, path, secure) → {NetworkHandlerResponse}
Make a get request to the specified host and path
Eventual url parameters are currently contained within the path
Parameters:
| Name | Type | Description |
|---|---|---|
url |
string | This is the hosts url |
path |
string | This is the path to the document |
secure |
boolean | Indicate whether to use http or https |
- Source:
Returns:
Contains all information needed from the
response @type{NetworkHandlerResponse}.
(async) getAsync(settingsObj, secure, ttl) → {Promise}
Initiate the request specified by the settings object.
Parameters:
| Name | Type | Description |
|---|---|---|
settingsObj |
object | Settings object according to nodejs docu. |
secure |
boolean | Indicate whether to use http or https. |
ttl |
number | Maximum time in ms that a request is allowed to live |
- Source:
Returns:
Returns a promise object, resolves to a response object
- Type
- Promise
(async) getPoolEntry() → {Promise}
As soon as a entry is available from the pool, one will be returned
upon request.
- Source:
Returns:
Return a DbResult entry from the pool, as soont as one
is available.
- Type
- Promise
(async) getSlot() → {Promise}
Reserve a slot for a request. This is necessary to ensure a maximal
number of parallel requests.
- Source:
Returns:
Return nothing, but return only if a slot is available.
- Type
- Promise
(async) responseHandler(response, url, path, startTime) → {NetworkHandlerResponse}
Handle the response of a get request to a unknown resource.
Parameters:
| Name | Type | Description |
|---|---|---|
response |
object | The response object from getAsync |
url |
string | The url to which the request was made |
path |
string | The path to which the request was made |
startTime |
number | Timestamp when the request was started |
- Source:
Returns:
result - Contains
a) The body of the response
b) The returned status code
c) MIME type of the response


Biological Sciences: Behavioral Neurobiology Concentration
This is the degree map for a Biological Sciences Behavioral Neurobiology at Hunter College. Please note that this is only a template and that some of the classes or requirements shown above can be taken in Winter or Summer Term
Please note that 6 of the 9 elective credits for the major must be psychology courses.
AP Credits can be used to satisfy some requirements. Science AP Credits cannot be used for major requirements.
*Dependent on Math Placement Exam Score
**Language course can be replaced with different course if you place out of language or do not have to take the first level. The class will then go towards a concentrated study/minor
***Physics 111 or 121 which are calculus based versions of Physics 110 and 120 can be taken instead if so wished
Freshman Year Fall Semester
Chemistry 102: General Chemistry I
Math 125: Precalculus or Math 150: Calculus I with Analytical Geometry*
English 120: Introduction to Expository Writing
Foreign Language Elementary Level I**
Individual & Society/Social Sciences
Freshman Year Spring Semester
Biology 100: Principles of Biology I (Can fufill Pluralism and Diversity Requirement if Biology 102 is taken (C or D)
Chemistry 104: General Chemistry II
Chemistry 106: General Chemistry Laboratory
English 220: Introduction to Writing about Literature (Writing Intensive)
Foreign Language Elementary Level II**
Sophomore Year Fall Semester
Biology 102: Principles of Biology II (Can fufill Pluralism and Diversity Requirement if Biology 102 is taken (C or D)
Chemistry 222: Organic Chemistry Lecture I
Chemistry 223: Organic Chemistry Laboratory I
Foreign Language Intermediate Level III**
Psychology 100: Introduction to Psychology
Sophomore Year Spring Semester
Biology 203: Molecular Biology and Genetics
Chemistry 224: Organic Chemistry Lecture II
Chemistry 225: Organic Chemistry Laboratory II
Foreign Language Intermediate Level IIII**
Junior Year Fall Semester
Biology 300: Biological Chemistry
Physics 110: General Physics: Introductory Course in Mechanics,Heat and Sound
Psychology 248: Statistical Methods in Psychological Research
Elective Can be either a Major Elective or fulfill other requirements
Major Electives approved listed below
Biology 380: Molecular Neurobiology
Psychology 301: Sensation and Perception
Psychology 309: Behavioral Neuroendocrinology (Fulfills Group C of Pluralism and Diversity)
Psychology 327: Motivation and Emotion
Psychology 369:Behavioral Pharmacology
Biology 480: Introduction to Experimental Biology
Junior Year Spring Semester
Biology 303: Cell Biology
Physics 120: General Physics: Introductory Course in Electricity,Magnetism, Light and Atomic Physics
Individual and Society/Humanities
Psychology 250: Experimental Psychology: General
Senior Year Fall Semester
Major Elective: One of the Approved Below
Biology 380: Molecular Neurobiology
Psychology 301: Sensation and Perception
Psychology 309: Behavioral Neuroendocrinology (Fulfills Group C of Pluralism and Diversity)
Psychology 327: Motivation and Emotion
Psychology 369:Behavioral Pharmacology
Biology 480: Introduction to Experimental Biology
Creative Expression
US Experience in its Diversity
World Cultures & Global Issues
Major Elective: One of the Approved Below
Biology 380: Molecular Neurobiology
Psychology 301: Sensation and Perception
Psychology 309: Behavioral Neuroendocrinology (Fulfills Group C of Pluralism and Diversity)
Psychology 327: Motivation and Emotion
Psychology 369:Behavioral Pharmacology
Biology 480: Introduction to Experimental Biology
Senior Year Spring Semester
Major Elective: One of the approved Below
Biology 370: Physiology of the Nervous System
Biology 376: Endocrinology
Psychology 301: Sensation and Perception
Psychology 309: Behavioral Neuroendocrinology (Fulfills Group C of Pluralism and Diversity)
Psychology 327: Motivation and Emotion
Psychology 369:Behavioral Pharmacology
Biology 480: Introduction to Experimental Biology
Elective (Fulfill Pluralism and Diveristy B)
Biology 47000/47100 Seminar Course
Elective (Fulfill Pluralism A)
Elective (If needed)


Numbers and texts that literally mean itself (⇔words)
5
3.1415926
'whatever
"whatever whatever"
'multiple 'literals "stack up" 1 2 3 4 5
1 2 +
1 2 3 4 5 * * * *
Anything in between [ and ] is pushed into the stack not being executed right away
[3 4 +]
['man 'in 'fridge]
Evaluate second one in stack and return first one in stack when the evaluation is not 0
0 ':-( if
1 ':^) if
8 0 * 99 if
[4 9 *] "evaluated" if
Make new word with the first text in the stack as a name and second one as its value
Words are nothing literal, and things that point certain values
2014 'year def year year +
'but "you cannot call this again" def you cannot call this again
6 9 def "don't do this too" pop 9
[dup *] "sq" def 5 sq
"duplicate" dup
'pop 'topmost 'one pop
Note that this entire page shares the same dictionary for words


Open Developer Tools > then under Images, click the Image, then type $0.naturalWidth to view the width of the image. To find the number of bits, multiply the Pixels by the Bits per Pixel. Less pixels x better compression = less bytes. Always use max-width: 100%; for the property of images in css. There is also a calc tool within the browser devtools. For example, width: calc((100% - 10px)/2);


Pannellum is a lightweight, free, and open source panorama viewer for the web. Built using HTML5, CSS3, JavaScript, and WebGL, it is plug-in free.
Pannellum is developed on GitHub by Matthew Petroff.CDN via KeyCDN.


Enzo Tutorial
- Algorithms in Enzo
- Adaptive Mesh Refinement
- Dark matter dynamics
- Root grid: Particle-Mesh (PM) Method
- Subgrids: Multigrid Method
- Hydrodynamics
- Piecewise Parabolic Method
- Zeus Hydrodynamic Method
- Cooling/Heating
- UV Background
- Radiative Cooling
- Simple cooling function
- Multispecies equilibrium
- Star Formation/Feedback
- Parallelization Strategies in Enzo
- Initial Conditions Generator
- Generating Initial Conditions
- Single-grid dark matter-only run
- Single-grid dark matter + hydrodynamics run
- Dark matter + hydrodynamics, nested grid initial conditions
- Writing Parameter Files
- Choose your cosmology
- Dark matter parameters
- Adiabatic hydrodynamics parameters
- Unigrid or AMR?
- General grid parameters (Unigrid and AMR)
- Setting up multiple initial grids
- AMR over the entire grid volume
- AMR in a small region (with and without multiple initial grids)
- Radiative Cooling and UV physics
- Star formation and feedback physics
- Parallelization options
Enzo Cookbook
Go to the Enzo home page
© 2004 Laboratory for Computational Astrophysics
last modified February 2004
by B.W. O'Shea


--- layout: post title: A more accurate name date: 2013-10-06 02:14:54.000000000 -07:00 type: post excerpt: Exploring the naming of the smart phone. published: true status: publish categories: ---
This object can do everything that you can imagine. It can browse the Internet, take great photographs and panoramas, record video and audio, you can check your email or what your friends are saying on their favorite social networks. This device can do everything! Ah, and also can make phone calls. The Smart Phone!
The reason we call it a phone it’s because it’s the only way to market without bewildering consumers. Calling it a phone or smart phone is misleading and outdated. It is the time to find a better name for the device, a name that is more accurate and especially marketable.
The name that I propose is the PocketBook.


| Created: | 03.02.2012 14:05:50 |
| Modified: | 03.02.2012 14:05:50 |
| Project: | |
| Advanced: |
| Attribute |
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Public <undefined> After |
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Public <undefined> Before |
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Public <undefined> Begins |
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Public <undefined> BegunBy |
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Public <undefined> TContains |
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Public <undefined> During |
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Public <undefined> TEquals |
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Public <undefined> TOverlaps |
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Public <undefined> Meets |
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Public <undefined> OverlappedBy |
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Public <undefined> MetBy |
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Public <undefined> EndedBy |
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Public <undefined> AnyInteracts |
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| Tag | Value |
| persistence | transient |
|
Details:
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| Property | Value |
| isFinalSpecialization: | 0 |


exact:
keyword
contains:
keyword and more
contains:
keyword and more2
exact + children :
keyword
exact + children :
keyword
children2
exact + children :
keyword
children3


NACOSS FULafia is the NACOSS Chapter for students studying Computer Science in Federal University of Lafia. NACOSS FULafia started out in the 2016/2017 session with Comr. Success Emmanuel Ibrahim as the Pioneer President. And the association in its totality has experience tremendous growth ever since.
The association strive to keep up with the aims and objectives of its parent association; NACOSS National. It does this by providing opportunities for its members to fulfill their in the IT industry both locally and globally. In order to achieve this, NACOSS FULafia organizes seminar and workshops for its members so as to enlighten their IT consciousness and bring them up-to-date with the latest trends in the IT industry.
Furthermore, in order to Foster the spirit of collaboration, NACOSS FULafia usually reach out to other NACOSS Chapters in other institutions by organizing/participating in activities such as inter-chapter football match; tech related activities such as hackathons, meetups, seminars and conferences; and a whole lots more.
NACOSS was founded by groups of students in July 1993 with the backing of Nigerian Computer Society (NCS) as its parent body. It provides avenues for students (in any IT related field) to highlight and champion issues of interest in a coordinated and organized manner.
NACOSS members (NACOSSites) are students studying in tertiary institutions in computer related disciplines including: Computer Science, Computer Engineering, Information Technology, etc.
Each member is essentially a member of the Association’s local chapter in his or her institution. As of April 2012, NACOSS states that it is the largest and most organized student body in West Africa, with registered members of about Two Hundred and Fifty thousand (250 000) in well over One Hundred and fifty local chapters (and more unregistered) in different Institutions (Universities, Polytechnics and Colleges of Education) across the six (6) Geo-political zones of Nigeria.
"NACOSS is the largest and most organized student body in West Africa, with registered members of about Two Hundred and Fifty thousand (250 000)"
Official website for NACOSS National » About the developers »


{% extends 'layout.html' %} {% block content %}
The prediction is 98% accurate. Decision Tree Classifier gave the best score.
Or


| Created: | 4/26/2018 9:45:53 AM |
| Modified: | 10/31/2018 12:24:58 AM |
| Project: | |
| Advanced: |
| Attribute | ||
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Public TM_Instant issueTime |
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Public Unit issuingSpaceWeatherCentre |
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Public StringWithNilReason advisoryNumber |
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Public SpaceWeatherAnalysis analysis |
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Public StringWithNilReason remarks |
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Public TM_Instant nextAdvisoryTime |
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| Tag | Value |
| byValuePropertyType | false |
|
Details:
Values: true | false
Default: false Description: Create a property type that requires that the instance is encoded inline (applies to ISO 19136:2007 encoding rule). |
|
| isCollection | false |
|
Details:
Values: true | false
Default: false Description: Identifies the feature type as a feature collection. |
|
| noPropertyType | false |
|
Details:
Values: true | false
Default: false Description: Surpress creation of a standard property type that supports inline or by-reference encoding (applies to ISO 19136:2007 encoding rule). |
| Constraint | Type | Status |
| Mandatory items in a report that failed translation | Invariant | Approved |
|
Details:
Pattern ID: SpaceWeatherAdvisory.SpaceWeatherAdvisory-1
Description: A report that failed translation should have as a minimum appropriately filled elements including Iwxxm:issueTime and iwxxm:issuingSpaceWeatherCentre
Assertion: ( if( string-length(@translationFailedTAC) gt 0 ) then( exists(iwxxm:issueTime) and exists(iwxxm:issuingSpaceWeatherCentre) ) else( true() ) )

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| Mandatory items in an ordinary report | Invariant | Approved |
|
Details:
Pattern ID: SpaceWeatherAdvisory.SpaceWeatherAdvisory-2
Description: An ordinary report should have appropriately filled elements including Iwxxm:issueTime, iwxxm:issuingSpaceWeatherCentre, iwxxm:advisoryNumber, iwxxm:phenomenon, iwxxm:analysis, iwxxm:remarks and iwxxm:nextAdvisoryTime
Assertion: ( if( string-length(@translationFailedTAC) eq 0 ) then( exists(iwxxm:issueTime) and exists(iwxxm:issuingSpaceWeatherCentre) and exists(iwxxm:advisoryNumber) and exists(iwxxm:phenomenon) and exists(iwxxm:analysis) and exists(iwxxm:remarks) and exists(iwxxm:nextAdvisoryTime) ) else( true() ) )

|
| Object | Type | Connection | Direction | Notes |
| «featureType» Report | Class | Generalization | To |


--- layout: about title: About ---
:art: Yet another theme for elegant writers with modern flat style and beautiful night mode.
Hey, nice to meet you, you found this Jekyll theme. Here the yet another theme is a modern theme, and it's quiet clear, clean and neat for writers and posts.


Click on one of the examples to load and freely
edit the code for it in the editor.
Greatest Common Divisor
Compute the GCD of two numbers using Euclid's algorithm
Prime Sieve
Sieve of Eratosthenes is a simple, ancient algorithm for finding all prime numbers up to any given limit.
99 bottles of beer
Joining the ranks of 600 other programming languages by programmatically generating this popular folk song.
Data Structures: Maps
Play with immutable maps and the rich standard library functions.
Try it out!
// let's define a function
val sq = /\(x) => x * x;
// values and functions both
// can be optionally annotated
val sum: num = List.fold_left(
// lambda expressions
/\(x, y) => x + y, 0,
// the List module has
// a bunch of useful functions
List.map(sq, List.range(1, 10))
);
// show result
print(sum);


| Property | Value |
|---|---|
| version | PostgreSQL 9.6.2, compiled by Visual C++ build 1800, 64-bit |
| lc_collate | English_United States.1252 |
| lc_ctype | English_United States.1252 |
| server_encoding | UTF8 |
| block_size | 8192 |
| data_checksums | off |
| debug_assertions | off |
| integer_datetimes | on |
| max_function_args | 100 |
| max_identifier_length | 63 |
| max_index_keys | 32 |
| segment_size | 131072 |
| server_version | 9.6.2 |
| server_version_num | 90602 |
| wal_block_size | 8192 |
| wal_segment_size | 2048 |
| Author: DB Doc | Copyright 2014 - 2017 All Rights Reserved | Created on Jun 12, 2017 2:27 AM |


 Only applicable when allowMultiple is false. More...
|
| |
| virtual TBuilder | AllowMultiple (bool allowMultiple) |
| | Allow multiple pressed buttons. More...
|
| |
| virtual TBuilder | AllowToggle (bool allowToggle) |
| | True to enable pressed/not pressed toggling. Defaults to: true More...
|
| |
| virtual TBuilder | DefaultType (string defaultType) |
| | The default xtype of child Components to create in this Container when a child item is specified as a raw configuration object, rather than as an instantiated Component. Defaults to 'panel'. More...
|
| |
| virtual TBuilder | DefaultUI (string defaultUI) |
| | Default ui to use for buttons in this segmented button. Buttons can override this default by specifying their own UI More...
|
| |
| virtual TBuilder | ForceSelection (bool? forceSelection) |
| | If allowMultiple is true, this config may be set to true to indicate that at least one button in the set must remain pressed at all times. More...
|
| |
| virtual TBuilder | Value (string value) |
| | The value of this button. More...
|
| |
| virtual TBuilder | Values (string[] values) |
| | The value of this button. More...
|
| |
| virtual TBuilder | Vertical (bool vertical) |
| | True to align the buttons vertically. Defaults to: false More...
|
| |
| virtual TBuilder | SetValue () |
| |
| virtual TBuilder | SetValue (int index) |
| |
| virtual TBuilder | SetValue (int[] index) |
| |
| virtual TBuilder | SetValue (string value) |
| |
| virtual TBuilder | SetValue (string[] value) |
| |
| virtual TBuilder | SetValue (object value) |
| |


podman ps
List Podman containers.
More information: home page
- List currently running podman containers:
podman ps
- List all podman containers (running and stopped):
podman ps --all
- Show the latest created container (includes all states):
podman ps --latest
- Filter containers that contain a substring in their name:
podman ps --filter="name=name"
- Filter containers that share a given image as an ancestor:
podman ps --filter "ancestor=image:tag"
- Filter containers by exit status code:
podman ps --all --filter="exited=code"
- Filter containers by status (created, running, removing, paused, exited and dead):
podman ps --filter="status=status"
- Filter containers that mount a specific volume or have a volume mounted in a specific path:
podman ps --filter="volume=path/to/directory" --format "table home pageID\thome pageImage\thome pageNames\thome pageMounts"


Ryan Grosso. Example 2 from ML Coursera
In this part of the exercise, you will build a logistic regression model to predict whether a student gets admitted into a university.
Suppose that you are the administrator of a university department and you want to determine each applicant’s chance of admission based on their results on two exams. You have historical data from previous applicants that you can use as a training set for logistic regression. For each training example, you have the applicant’s scores on two exams and the admissions decision.
Your task is to build a classification model that estimates an applicant’s probability of admission based the scores from those two exams.
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
#import seaborn as sns#seaborn will make nice plots!
#matplotlib.style.use('seaborn-dark-palette')
#sns.set_style("white", {"axes.grid": True})
#sns.set_style("darkgrid", {"axes.grid": True})
#Use pandas
import pandas as pd
data_file_2 = 'data/ex2data1.txt'
df = pd.read_csv(data_file_2,delimiter=',',header=None)
df.columns=['exam1','exam2','admit']
def plot_rawdata(leg=False):
import seaborn as sns#seaborn will make nice plots!
matplotlib.style.use('seaborn-dark-palette')
sns.set_style("white", {"axes.grid": True})
g =sns.lmplot(x="exam1", y="exam2", hue="admit",data=df,fit_reg=None,legend=leg)
plt.xlim(30,100)
plt.ylim(30,100)
plt.title("Distribution of test scores")
plot_rawdata(True)
plt.show()
#First we need a sigmoid function, There are a few around like in scipy
#But we will define our own so we see what's happening
def my_sigmoid(x):
return 1./(1+np.exp(-1.*x))
#Quick check. x = 0 should return 0.5
print'I hope this is true 0.5 =', str(my_sigmoid(0))
def show_my_sig():
x = np.arange(-10,10,0.1)
y = my_sigmoid(x)
plt.plot(x,y,"b-")
plt.title("My Sigmoid function")
plt.grid(True)
plt.show()
show_my_sig()
# now implement a function to handle the cost and hypothesis
# Definition for hypothesis
def h(theta,x):
return my_sigmoid(np.dot(x,theta))
# Definition of function for cost
def cost_logistic(Theta_values,X,y,m):
# cost is 1/(m) sum( -y*log(h) - (1-y)*log(1-h))
first_term = np.dot( -np.transpose(y),np.log(h(Theta_values,X)))
second_term = np.dot((1-np.transpose(y)),np.log(1-h(Theta_values,X)))
j = (1./m)* np.sum(first_term-second_term)
return float(j)
#Bring the data into nparrays from pandas
preX = df[["exam1","exam2"]]
ones = pd.DataFrame({'x0' : pd.Series([1 for x in range(len(preX))])})
#here is my X
X = pd.concat([ones,preX],axis=1).as_matrix()
#here is my y
y = df[['admit']].as_matrix()
m= len(y)
print' Total events in the sample {}'.format(m)
#initialze with zero
Initial_theta = np.zeros((X.shape[1],1))
cost_logistic(Initial_theta,X,y,m) #should be .693
# in the coursera class they use octave.... we can use scipy
from scipy import optimize
def OptimizeTheta(thetas, X, y):
myret = optimize.fmin(cost_logistic, x0=thetas, args=(X, y,len(y)), maxiter=500, full_output=True)
return myret[0], myret[1]
Thetas , cost_val = OptimizeTheta(Initial_theta,X,y)
#IF we use the optimal values of theta we should get something like .20 co
print cost_logistic(Thetas,X,y,len(y))
#now we look at the descision boundary
def plot_dec():
#plot the pointsheta
plot_rawdata()
myx = np.arange(int(df["exam1"].min()-1),int(df["exam1"].max()+1))
myy = (-1./Thetas[2])*(Thetas[0] + Thetas[1]*myx)
plt.plot(myx,myy,"r--",label="Decision Boundary")
plt.legend(bbox_to_anchor=(1.45, 0.5), loc=7, borderaxespad=0.,frameon=True)
plot_dec()
plt.show()
# If I pick a pair of exams ... what does the model return
#pick 100,100
testpt = np.array([[1,100,100]])# yes I know it's sloppy
# So my model return is
np.dot(Thetas,testpt.T)
#Bring the data into nparrays from pandas should have organize this ealier
temp_df = df
ones = pd.DataFrame({'x0' : pd.Series([1 for x in range(len(temp_df))])})
#here is my X
X_df = pd.concat([ones,temp_df],axis=1)
#here is my y
prex_admit = X_df[X_df.admit==1]
x_admit = prex_admit[['x0','exam1','exam2']].as_matrix()
prex_rej = X_df[X_df.admit==0]
x_rej = prex_rej[['x0','exam1','exam2']].as_matrix()
#Now that we have made a model proceed to report the training accuracy of your classifier by computing the
#percentage of examples it got correct.
matrix_admit = df[df.admit==1].as_matrix()
matrix_rej = df[df.admit==0].as_matrix()
def makePrediction(mytheta, X):
return h(mytheta,X) >= 0.5
#Compute the percentage of samples I got correct:
pos_correct = float(np.sum(makePrediction(Thetas,x_admit)))
neg_correct = float(np.sum(np.invert(makePrediction(Thetas,x_rej))))
tot = len(matrix_admit)+len(matrix_rej)
prcnt_correct = float(pos_correct+neg_correct)/tot
print "Fraction of training samples correctly predicted: %f." % prcnt_correct
In this part of the exercise, you will implement regularized logistic regression to predict whether microchips from a fabrication plant passes quality assur- ance (QA). During QA, each microchip goes through various tests to ensure it is functioning correctly.
Suppose you are the product manager of the factory and you have the test results for some microchips on two different tests. From these two tests, you would like to determine whether the microchips should be accepted or rejected. To help you make the decision, you have a dataset of test results on past microchips, from which you can build a logistic regression model.
#Bring in the data
df2 = pd.read_csv('data/ex2data2.txt',header=None)
df2.columns = ['chip1','chip2','pass']
#print df2.head()
#append on the x0 terms
ones = pd.DataFrame({'x0' : pd.Series([1 for x in range(len(df2))])})
myMat = pd.concat([ones,df2],axis=1).as_matrix()
#here is my X
myX = myMat[:,:3]
#here is my y
myy = myMat[:,-1:]
We can show off a little bit with pandas... usually I have found that Pandas is good for showing technical people plots but is not as liberal as implementing plots directly with matplotlib.
def viz_data():
import seaborn as sns
sns.lmplot(x='chip1',y='chip2',hue='pass',data=df2,markers=["x", "o"],palette="Set1",fit_reg=None)
plt.show()
viz_data()
# We need a function to build the matrix for feature mapping.
def mapFeature( x1col, x2col ):
"""
Function that takes in a column of n- x1's, a column of n- x2s, and builds
a n- x 28-dim matrix of featuers as described in the homework assignment
"""
degrees = 6
out = np.ones( (x1col.shape[0], 1) )
for i in range(1, degrees+1):
for j in range(0, i+1):
term1 = x1col ** (i-j)
term2 = x2col ** (j)
term = (term1 * term2).reshape( term1.shape[0], 1 )
out = np.hstack(( out, term ))
return out
#Make my featured map... This will replace the design matrix X in our cost and minimization
myfeatX = mapFeature(myX[:,1],myX[:,2])
#Now let's learn the params for theta
Initial_theta = np.zeros((myfeatX.shape[1],1))# Remeber we need to shape agains the featX
cost_logistic(Initial_theta,myfeatX,myy,len(myy)) # we should exptect to see .693
#Run the minimization with regularization
# This is just adding a regularization term to the existing cost fucntion
def cost_logistic_reg(Theta_values,X,y,m,reg_lambda = 0 ): # Lambda = 0 means no reg applied
# cost is 1/(m) ( sum( -y*log(h) - (1-y)*log(1-h)) +lamb/2 theta*theta)
first_term = np.dot( -np.transpose(y),np.log(h(Theta_values,X)))
second_term = np.dot(np.transpose(1-y),np.log(1-h(Theta_values,X)))
reg_term = (reg_lambda /2.) * np.sum(np.dot(np.transpose(Theta_values[1:]),Theta_values[1:]))
j = (1./m)* (np.sum(first_term-second_term)+reg_term)
return float(j)
# Now Optimize
# note, we play around with different techniques. Feel free to uncomment and look at how perfomance varies
# fmin --> takes a lot of steps to converge, not a very low cost
# fmin_bfgs --> Converges pretty quick and gets a reasonable cost (use this for the example)
# fmin_cg --> take a little while, lots of steps and is not that greatbut reasonale cost either
def OptimizeTheta_reg(mytheta,myX,myy,mylambda=0.):
#myret = optimize.fmin(cost_logistic_reg, x0=thetas, args=(myX, myy,len(myy),mylambda), maxiter=20000, full_output=True)
myret = optimize.fmin_bfgs(cost_logistic_reg, x0=mytheta, args=(myX, myy,len(myy),mylambda), maxiter=600, full_output=True, disp=False)
#myret = optimize.fmin_cg(cost_logistic_reg, x0=thetas, args=(myX, myy,len(myy),mylambda), maxiter=20000, full_output=True)
return np.array([myret[0]]), myret[1]
theta, mincost = OptimizeTheta_reg(Initial_theta, myfeatX, myy,10)
print theta.shape # we should have 28 params
np.dot(theta,mapFeature(np.array([0]),np.array([0])).T)
# let's use matplotlib so things look reasonable
# Make two arrays for pass and fail
x_pass = np.array( [myX[i] for i in range(len(myX)) if myy[i]==1])
x_fail = np.array( [myX[i] for i in range(len(myX)) if myy[i]==0])
def make_dataplot():
# This is very useful if you need to make a pretty plot fast while working
#print(plt.style.available)
#pandas is nice if you want to see the labels for things and see whats going on
#but you don't have as much control to make plots pretty
# I find that matplitlibe is much better... for pretty plots...
# ok... i'll stop ranting on how much I like using Seaborn to get things done quickly
with plt.style.context(("seaborn-white")):
plt.plot(x_pass[:,1],x_pass[:,2],"bo",label='Pass')
plt.plot(x_fail[:,1],x_fail[:,2],"ro",label='Fail')
plt.xlabel("Chip1")
plt.ylabel("Chip2")
plt.grid(True)
plt.legend(frameon=True)
#For this we will use countour plot frompython.... There is an examle that I used in the first homework
from mpl_toolkits.mplot3d import axes3d
from matplotlib import cm
plt.style.context(("seaborn-white"))
def plot_decision_boundary(myX, myy, Mylambda,ab='contour'): # mapped feature space , myy, any lambda
#ab ==> {'both','surface' ,'contour'}
#run optimization
Initial_theta = np.zeros((myX.shape[1],1))
theta, cost_val = OptimizeTheta_reg(Initial_theta,myX,myy,mylambda=Mylambda)
c1val = np.arange(-1.,1.5,0.05)
c2val = np.arange(-1.,1.5,0.05)
cx = []
cy = []
cz = []
## NOTE!!!
#this isn't too big of a dataset so append is fine.
# later in the course I assume we will get larger datasets
#Then we will not want to use this method because append always has to move memory
# we will want to define some vector/matrix of zeros in advance with np and edit entries
for a in c1val:
tempx = []
tempy = []
tempz = []
for b in c2val:
tempx.append(a)
tempy.append(b)
#find the prediction from the model and put it in z
# to do this we need to do dot(theta,x) # remeber we have a bigger feature space
# So really this will be dot(theta,mapfeat(X)) ..
#make my test point
testpt = mapFeature(np.array([a]),np.array([b]))
model_val = np.dot(theta,testpt.T)# This is what we get from our model# it's in np form
if model_val[0]>=0:
#tempz.append(1)
tempz.append(model_val[0])
else:
tempz.append(0)# Crap hack
cx.append(tempx)
cy.append(tempy)
cz.append(tempz)
# Now we can start to see what this looks like.
# Remeber we will not be easily able to visualize the landscape of each parameter
# BUT. We will look at what the function returns in the region of the dataset
if ab=='both' or ab=='surface':
fig = plt.figure(figsize=(10,6))
#make the 3d surface
ax = fig.gca(projection='3d')
#manually set the normal for the cmap
# See... this is why we really should have used numpy...
#incase new people are reading this, we see how we always just revert back to np..
# we should always use np
npcz = np.asarray(cz)
ax.plot_surface(cx, cy, cz, rstride=1, cstride=1, alpha=0.3,cmap=cm.jet,vmin=0,vmax=npcz.max())
ax.set_zlim(0,npcz.max() )
if ab=='both':
plt.show()
if ab=='both' or ab=='contour':
#u, v = np.meshgrid( cx, cy )
#mylevel = np.arange(4.5,50,1)# how many levels for the contours
#plt.contour(cx, cy, cz, offset=0, cmap=cm.jet)#plot the contours below
plt.contour(cx, cy, cz, levels=[0],linewidths=3,colors='k',label='Decision')#plot the contours below
if ab=='both':
plt.show()
#u, v = np.meshgrid( xvals, yvals )
#mycontour = plt.contour( xvals, yvals, zvals, [0])
#make_dataplot()
plt.figure(figsize=(12,10))
plt.subplot(221)
make_dataplot()
lamb = 0.
plot_decision_boundary(myfeatX,myy,lamb)
plt.title('Decision Boundary lambda={}'.format(lamb))
plt.subplot(222)
make_dataplot()
lamb = 0.5
plot_decision_boundary(myfeatX,myy,lamb)
plt.title('Decision Boundary lambda={}'.format(lamb))
plt.subplot(223)
make_dataplot()
lamb = 1.
plot_decision_boundary(myfeatX,myy,lamb)
plt.title('Decision Boundary lambda={}'.format(lamb))
plt.subplot(224)
make_dataplot()
lamb = 100.
plot_decision_boundary(myfeatX,myy,lamb)
plt.title('Decision Boundary lambda={}'.format(lamb))
plt.show()
#look at the function for some of these.....
#No regularization
lamb=0
plot_decision_boundary(myfeatX,myy,lamb,ab='both')
#regularization =1
lamb=1
plot_decision_boundary(myfeatX,myy,lamb,ab='both')


| Meeting time: | Thursdays 6-8pm and online components |
| Classroom: | PKI 155 |
| Instructor: | Dr. Harvey Siy |
| Office: | PKI 281B |
| Phone: |<PHONE_NUMBER> |
| Email: | hsiy at unomaha dot edu |
| Office Hours: | Thursdays 5-6pm, or by appointment (call or email ahead) |
| Textbook: | Software Engineering (10th edition) by Ian Sommerville, Addison-Wesley, 2010 |
| Companion website | |
| link to 8th Edition | |
| Optional: | Engineering Software as a Service: An Agile Approach Using Cloud Computing (1st edition) by Fox and Patterson, 2014. |
| http://www.saasbook.info/home | |
| Optional: | Object-Oriented Software Engineering (3rd edition) by Bruegge and Dutoit, Prentice Hall 2004. |
| Companion website |
The course focuses on the engineering and development of real-world software products. It provides a pragmatic introduction into the fundamentals of software engineering. Basics of software project management are presented and are practiced in the term project.
Students who complete this course will:
The lecture slides will mostly come from the Sommerville textbook's companion website plus a few changes of my own. The originals can be downloaded from companion website
Some lectures will also be taken from Fox and Patterson (aka ESaaS book) and Bruegge and Dutoit (aka OOSE book).
The lecture slides will be posted on Canvas.
| Week | Topic | Background Readings and References | Project-related Discussions |
|---|---|---|---|
| 5/17 | What is Software Engineering? | Sommerville Ch. 1 (Introduction) | Team formation |
| 5/24 | Software process models | Sommerville Ch. 2 (Software Processes), Ch. 3 (Agile Software Development) | Trello and other project tracking tools |
| 5/31 | Requirements engineering | Sommerville Ch. 4 (Software Requirements), ESaaS Ch. 7 (Requirements: BDD and User Stories) | How web frameworks work |
| 6/7 | System perspectives and models | Sommerville Ch. 5 (System Models), OOSE Ch. 2 (Modeling with UML), OOSE Ch. 5 (Analysis) | Git and Github |
| 6/14 | Architecture | Sommerville Ch. 6 (Architectural Design) | Web application deployment |
| 6/21 | Design principles and patterns | Sommerville Ch. 7 (Design and Implementation), OOSE Ch. 8 (Design Patterns) | Object modeling discussion |
| 6/28 | Midterms | ||
| 7/5 | Testing | Sommerville Ch. 8 (Software Testing), ESaaS Ch. 8 (Test-Driven Development) | Automated testing tools |
| 7/12 | Software evolution | Sommerville Ch. 9 (Software Evolution), ESaaS Ch. 9 (Maintenance: Legacy, Refactoring, and Agile) | Configuration management tools |
| 7/19 | Project management revisited (critical paths) | Sommerville Ch. 22 (Project Management) and 23 (Project Planning) | Architecture presentations and discussion |
| 7/26 | Design principles revisited (SOLID) | ESaaS Ch. 11 (Design Patterns) | |
| 8/2 | Dependability and critical systems Recap of SE Code of Ethics | Sommerville Ch. 10 (Dependable Systems) Sommerville Ch. 1 (Introduction) | |
| 8/9 | Finals |
| Term Project: | 40% |
| Midterm: | 20% |
| Final: | 20% |
| Quizzes/ Homeworks/ Exercises: |
20% |
Students taking the class as CSCI8836 will also be required to submit a 10-15 page, graduate-level research paper. (Please make an appointment to see me within the first two weeks of class to discuss appropriate topics.)
The term project is discussed in a separate page.
Late homeworks will get a 20% deduction per day, for each day past the due date.
For online submissions, we will follow the time stamp as reported by Blackboard. For example, if the due date is Aug, 24, a submission on Aug. 25 12:01am will get a 20% deduction.
Paper submissions must be handed directly to me on the day it is due.
Cheating will not be tolerated for project assignments, exams and other assignments. For formal policies about cheating and plagiarism, consult the UNO Student Policies and Department of Computer Science Policies and Procedures.


Destination measures statistics team
Email<EMAIL_ADDRESS>Telephone: Stephen Harris 0161 600 1595
Official Statistics
Students in further education, employment and training destinations in the 2011 to 2012 academic year.
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This publication shows the percentage of young people progressing to specified educational or employment destinations in the academic year 2011 to 2012.
These are young people in key stage 4 ( KS4 ) and key stage 5 ( KS5 ) in the academic year 2010 to 2011.
The data is available at:
Email<EMAIL_ADDRESS>Telephone: Stephen Harris 0161 600 1595
Published: 26 June 2014
Updated: 14 November 2014


This project was developed as an assignment for INFO 474: Interactive Information Visualization at the University of Washington Information School.
By Andrey Butenko, February 2020. GitHub.


Three Seasons ****
rated PG-13 October Films in Vietnamese with English subtitles starring Don Duong, Ngoc Hiep Nguyen, Manh Cuong Tran, Harvey Keitel, Zoe Bui, Huu Duoc Nguyen story by Tony Bui and Timothy Linh Bui written and directed by Tony Bui
"Three Seasons" is being billed as the most acclaimed film in the history of the Sundance Film Festival, having won three top awards, including the prestigious Grand Jury Prize. Writer/director Tony Bui and his film deserve all the praise that they have gotten for making this breathtaking, heartbreaking drama.
The film is about dreamers; people with hopes and aspirations. However, in war-torn Vietnam, the dreamers are constrained by their poverty-stricken fate. "Three Seasons" intertwines the stories of a cyclo driver, a prostitute, an American G.I., a young woman, and a little boy. At first glance, the bunch would seem to have nothing in common, but "Three Seasons" takes the time to prove that they all are lost souls.
"Three Seasons'" cast is composed almost entirely of Vietnamese newcomers, but Harvey Keitel (also one of the film's producers) shines in a small role as a former American G.I. searching for his long-lost daughter. The role is a small one, but Keitel's presence and warmth add an extra layer of heartfelt emotion to an already complex, multilayered production.
Among the Vietnamese cast, Don Duong radiates as a cyclo driver named Hai who falls in love with a prostitute, and desires her love in return. It is such a sweet, quiet performance, but it is one that, like the rest of the film, is subtly heartbreaking.
Every character in "Three Seasons" has a desire; a hope. Whether it be love, stability, or family that the character needs, writer/director Tony Bui makes us feel just the right amount of compassion for each one. In a way, "Three Seasons" leaves the viewer feeling somewhat depressed. Each character will indeed fulfill their dream, but not necessarily in the way in which one would expect.
The thing, however, that makes "Three Seasons" so groundbreaking, apart from the fact that it's the first American film filmed entirely in Vietnam, is that the Vietnamese, who, in modern American cinema have been portrayed as the enemy we know nothing about (in so many Vietnam War movies), finally get their own movie; a movie that proves that even they have some heart and soul.
Tony Bui has handcrafted a flawless masterpiece; a gem that deserves much more than its 3 Sundance Film Festival awards. "Three Seasons" is a quiet film that will reward multiple viewers with its symbolism and subtlety, and it will provide an emotional, but unsentimental experience.
a review by Akiva Gottlieb, The Teenage Movie Critic<EMAIL_ADDRESS>http://www.angelfire.com/mo/film watch me on TBS' "Dinner And A Movie" May 21, 8:05pm EST
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
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to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


Michelle Visage slams 'deplorable' James Jordan after Strictly 'fake crying' claims
The pair have been taking pot shots at each other online after Michelle, 51, and Giovanni Pernice landed in the bottom two and were sent home - but she isn't going quietly
by Irishmirror.ieWar has broken out between axed Michelle Visage and former Strictly Come Dancing star James Jordan.
The pair have gone in on each other on twitter after she became the the eighth celebrity to leave the show.
James alleges the Drag Race star only performed to iconic Madonna hit Vogue to win 'the LGBT vote'.
He then called out her 'fake tears' before the 51-year-old hit back.
She tweeted: "That's deplorable. Gross" after being directed to his post - before telling him: "Also James, you should @ people when you talk about them! That's all."
He then claimed she was trolling him after saying the American was "boring!!!".
James said her choice backfired, adding: "Not for me sorry... not dancing, just posing. Obviously needs the LGBTQIA community's vote".
The dancer then put it was an "EASY EASY decision" to get rid of the her.
She later responded: "The only way to change the world is by taking risks. I'm SOOOOOO proud of this dance and going out on this one."
James hit back, saying: "I love the fact I’m being trolled by @michellevisage for my honest opinions on Twitter and never once “@“ her in any tweet Didn’t realise I wasn’t allowed my own opinion on my own account.
"Think she’s still upset “her” community didn’t save her. Don’t blame me."
Fans were split on twitter.
"I like u James but sometimes you don't help yourself, yes have an opinion but when you write stuff like "her community" etc your obviously gunna get people's backs up" one wrote.
Another put: "You're right, correct decision for her to leave."
But one said: "Stop attention seeking James."
While another posted: "You got fired from the show and wouldn't qualify to be a celebrity enough to be on it."


{% extends "transcription/layout.html" %} {% block content %}
The Radboud University Oral History Metadata Registry provides an interface to list, correct and add metadata specifications for Oral History recordings. Each OH metadata item contains administrative and descriptive information about a specific recording (typically an interview). The description of an OH metadata item is defined by the Clarin Component Registry.
The OH-Metadata Registry has been designed by the Technical Service Group of the Humanities Lab at the Radboud University Nijmegen. Any researcher is invited to registrate (create an account) and maintain his or her own collection of OH metadata. Collections of one researcher are by default not visible to other researchers, but it is possible to specify a different accessibility level.
{% if user.is_authenticated %} (See the Extra menu for logout and other options) {% else %} Log in Sign up {% endif %}


Former Israeli policewoman charged with shooting Palestinian
JERUSALEM (AP) - A former policewoman in Israel has been charged with assault and reckless use of a weapon for allegedly shooting an unarmed Palestinian man in the back with a sponge-tipped bullet as he walked away from a West Bank checkpoint.
The case has drawn widespread attention since Channel 13 TV broadcast a video of the May 2018 incident earlier this month.
In the video, the Palestinian is shot in the back nearly 20 seconds after walking away from the checkpoint.
Border police often use sponge-tipped bullets as a “nonlethal” tool to disperse crowds, but the bullets are painful and can cause serious injury.
The Palestinian, Karam Qawasmi, said on Thursday that other officers also abused him and should have been charged. He says he fears she’ll receive a “very light punishment.”
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Get information for alternate Twitch accounts you may have linked to LioranBoard.
For Channel ID to be available, the Transmitter must be connected for at least a few seconds already to retrieve it.
| Box Name | Type | Description |
|---|---|---|
| Variable | String | Variable to store the data into |
| Account Slot | Int | Slot of the account (between 1 and 10). Found in Link Your Twitch menu. |
| Type | Channel ID/Login Name/Oauth Token | Type of data to get |


reports_helper.rb
Hipposoft 2008
Support functions for views related to report generation. See controllers/reports_controller.rb for more.
18-Feb-2008 (ADH): Created.
Return appropriate list view actions for the given report
# File app/helpers/reports_helper.rb, line 341 def reporthelp_actions( report ) if ( @current_user.admin? || report.user_id == @current_user.id ) return [ 'edit', 'delete', 'show' ] else return [] end end
Report a terse number of hours with an ‘overrun’ span if negative or a ‘no_overrun’ span if >= 0 in two sections separated by a “/” - the idea is to pass actual and potential remaining hours for a task in here.
# File app/helpers/reports_helper.rb, line 302 def reporthelp_decorated_hours( actual, potential ) class_name = actual < 0 ? 'overrun' : 'no_overrun' output = "#{ apphelp_terse_hours( actual ) } / " class_name = potential < 0 ? 'overrun' : 'no_overrun' output << "#{ apphelp_terse_hours( potential ) }" return output.html_safe() end
List helper - formatted end date for the given report
# File app/helpers/reports_helper.rb, line 335 def reporthelp_end_date( report ) apphelp_date( report.generate_report().range.max ) end
Use the Calendar Date Select plug-in to generate a selector for the end time of a report. Pass the form instance upon which to operate.
# File app/helpers/reports_helper.rb, line 123 def reporthelp_end_time( form ) return form.calendar_date_select( :range_end, { :embedded => false, :year_range => Timesheet.used_range() } ) end
Return HTML suitable for inclusion in the form passed in the first parameter (i.e. the ‘f’ in “form for … do |f|” ), which provides a selection list allowing the user to choose a report frequency (weekly, monthly etc.).
# File app/helpers/reports_helper.rb, line 180 def reporthelp_frequency_selection( form ) collection = [] Report.labels.each_index do | index | collection.push( [ Report.labels[ index ], index ] ) end form.select( :frequency, collection ) end
Generate a menu for the given form allowing the user to choose a grouping option.
# File app/helpers/reports_helper.rb, line 233 def reporthelp_grouping_selector( form ) return apphelp_select( form, :task_grouping, [ [ 'No special grouping', 'default' ], [ 'Group billable tasks together', 'billable' ], [ 'Group active tasks together', 'active' ], [ 'Group both kinds of tasks together', 'both' ] ], false ) end
Return HTML suitable for an ‘hours’ field which gives a total amount, then a committed and not-committed amount wrapped in SPANs to give the correct committed/uncommitted text styles. If the overall total time is zero, “ ” is returned instead. Pass any object subclassing TrackRecordReport::ReportElementaryCalculator and, optionally, ‘true’ to show “0.0” rather than “ ” in the zero hours total case.
# File app/helpers/reports_helper.rb, line 269 def reporthelp_hours( calculator, show_zero = false ) if ( calculator.has_hours? ) output = '' output << apphelp_terse_hours( calculator.total ) if ( @report.include_totals != false ) output << ' (' if ( @report.include_totals != false and ( @report.include_committed != false or @report.include_not_committed != false ) ) if ( @report.include_committed != false ) output << '' output << apphelp_terse_hours( calculator.committed ) output << '' end output << '/' if ( @report.include_committed != false and @report.include_not_committed != false ) if ( @report.include_not_committed != false ) output << '' output << apphelp_terse_hours( calculator.not_committed ) output << '' end output << ')' if ( @report.include_totals != false and ( @report.include_committed != false or @report.include_not_committed != false ) ) return output.html_safe() else return ( show_zero ? '0' : ' ' ).html_safe() end end
Return HTML suitable for inclusion in a form which provides a pull-down menu of years for the full permitted time range subdivided into months. Pass the form being constructed and “:range_month_start” or “:range_month_end”.
# File app/helpers/reports_helper.rb, line 138 def reporthelp_month_selection( form, method ) start_or_end = ( method == :range_month_start ) ? :start : :end form.grouped_collection_select( method, get_year_array(), # Use years for groups :months, # A years's "months" method returns its month list :title, # Use the year 'title' for the group labels :id, # A month's "id" method returns the value for an option tag start_or_end, # A month's "start" or "end" method is used for the option contents { :include_blank => '-' } ) end
List helper - owner of the given report
# File app/helpers/reports_helper.rb, line 317 def reporthelp_owner( report ) return link_to( report.user.name, user_path( report.user ) ) end
Generate a sort field selector menu for the given form which will use the given method to set the chosen option in the report - one of “:customer_sort_field”, “:project_sort_field” or “:task_sort_field”.
# File app/helpers/reports_helper.rb, line 217 def reporthelp_sorting_selector( form, method ) return apphelp_select( form, method, [ [ 'Sort by name', 'title' ], [ 'Sort by code', 'code' ], [ 'Sort by addition date', 'created_at' ] ], false ) end
List helper - formatted start date for the given report
# File app/helpers/reports_helper.rb, line 329 def reporthelp_start_date( report ) apphelp_date( report.generate_report().range.min ) end
Use the Calendar Date Select plug-in to generate a selector for the start time of a report. Pass the form instance upon which to operate.
# File app/helpers/reports_helper.rb, line 110 def reporthelp_start_time( form ) return form.calendar_date_select( :range_start, { :embedded => false, :year_range => Timesheet.used_range() } ) end
List helper - formatted ‘updated at’ date for the given report
# File app/helpers/reports_helper.rb, line 323 def reporthelp_updated_at( report ) return apphelp_date( report.updated_at ) end
Return HTML suitable for inclusion in the form passed in the first parameter (i.e. the ‘f’ in “form for … do |f|” ), based on the user array given in the second parameter, which provides:
A <select> tag with options listing all users in the array in the order in which they are stored in that array.
An empty string if the input users array is itself empty.
# File app/helpers/reports_helper.rb, line 199 def reporthelp_user_selection( form, users ) if ( users.empty? ) return '' else return apphelp_collection_select( form, 'reportable_user_ids', users, :id, :name ) end end
Return HTML suitable for inclusion in a form which provides a pull-down menu of years for the full permitted time range subdivided into weeks. Pass the form being constructed and “:range_week_start” or “:range_week_end”.
# File app/helpers/reports_helper.rb, line 159 def reporthelp_week_selection( form, method ) start_or_end = ( method == :range_week_start ) ? :start : :end form.grouped_collection_select( method, get_year_array(), # Use years for groups :weeks, # A years's "weeks" method returns its week list :title, # Use the year 'title' for the group labels :id, # A week's "id" method returns the value for an option tag start_or_end, # A week's "start" or "end" method is used for the option contents { :include_blank => '-' } ) end
Pass a hash. The “:item” entry is read. If a User, a string of “by <name>” is returned. Otherwise, a string of “on ‘<title>’” is returned. Useful for indicating hours are done by a user, or were worked on some task.
# File app/helpers/reports_helper.rb, line 252 def reporthelp_work_breakdown_item_name( item ) item = item[ :item ] if ( item.class == User ) return "by #{ h( item.name ) }".html_safe() else return "on '#{ h( item.augmented_title ) }'".html_safe() end end


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{# ------------------------------------------------------- #} {# INDIVIDUAL VIEW FOR EACH shows #} {# This page can use any data from http:localhost:2000/cms/#/form/shows/ #} {# Webhook uses the SWIG.js (like Djagno/Twig) templating system. Their documentation is here: #} {# http://paularmstrong.github.io/swig/docs/tags/ #} {# Learn about calling data into Webhook pages here: #} {# http://www.webhook.com/docs/template-rules-and-filters/ #} {# ------------------------------------------------------- #} {# Confused what extends and blocks do? Watch a primer: #} {# http://www.webhook.com/docs/template-inheritance-blocks/ #} {% extends "templates/partials/base.html" %} {# This sets our page


"""
@brief Loader class for importing xml based packet dictionaries
@date Created July 12, 2018
@author R. Joseph Paetz
@bug No known bugs
"""
from fprime_gds.common.data_types import exceptions
# Custom python modules
from fprime_gds.common.loaders.xml_loader import XmlLoader
from fprime_gds.common.templates.pkt_template import PktTemplate
[docs]class PktXmlLoader(XmlLoader):
"""Class to load xml packet dictionaries"""
# Constants for use when parsing the xml
[docs] PKT_LIST_TAG = "packet_list" # tag on the root list of packets
[docs] PKT_TAG = "packet" # tag on each packet object
[docs] CH_TAG = "channel" # tag on each channel element of the packet
[docs] NAME_FIELD = "name" # key to retrieve the packet name
[docs] ID_FIELD = "id" # key to retrieve the packet id
[docs] CH_NAME_FIELD = "name" # key to retrieve the name from each ch elem
[docs] def get_id_dict(self, path, ch_name_dict):
"""
Returns the python dictionary keyed by ids for the given path
This function will return the same dictionary originally computed for
the given path or will construct new dictionaries if the path has never
been passed to the get_id_dict or the get_name_dict functions.
Args:
path (string): Path to the xml pkt spec to convert to a python dict
ch_name_dict (dict()): Channel dictionary with names as keys and
ChTemplate objects as values.
Returns:
The id dictionary associated with the given path
"""
if path in self.saved_dicts:
(id_dict, name_dict) = self.saved_dicts[path]
else:
(id_dict, name_dict) = self.construct_dicts(path, ch_name_dict)
self.saved_dicts[path] = (id_dict, name_dict)
return id_dict
[docs] def get_name_dict(self, path, ch_name_dict):
"""
Returns the python dictionary keyed by names for the given path
This function will return the same dictionary originally computed for
the given path or will construct new dictionaries if the path has never
been passed to the get_id_dict or the get_name_dict functions.
Args:
path (string): Path to the xml pkt spec to convert to a python dict
ch_name_dict (dict()): Channel dictionary with names as keys and
ChTemplate objects as values.
Returns:
The name dictionary associated with the given path
"""
if path in self.saved_dicts:
(id_dict, name_dict) = self.saved_dicts[path]
else:
(id_dict, name_dict) = self.construct_dicts(path, ch_name_dict)
self.saved_dicts[path] = (id_dict, name_dict)
return name_dict
[docs] def construct_dicts(self, path, ch_name_dict):
"""
Constructs and returns python dictionaries keyed on id and name
This function should not be called directly, instead, use
get_id_dict(path) and get_name_dict(path)
Args:
path (string): Path to the packet definition xml file to parse into
a dictionary.
ch_name_dict (dict()): Channel dictionary with names as keys and
ChTemplate objects as values.
Returns:
A tuple with two packet dictionaries (type==dict()):
(id_dict, name_dict). The keys should be the packets' id and name
fields respectively and the values should be PktTemplate objects.
"""
packet_list = self.get_xml_tree(path)
if packet_list.tag != self.PKT_LIST_TAG:
raise exceptions.GseControllerParsingException(
"expected packet list to have tag %s, but found %s"
% (self.PKT_LIST_TAG, packet_list.tag)
)
id_dict = dict()
name_dict = dict()
for packet in packet_list:
# check if this is actually a packet, and not something to ignore
if packet.tag != self.PKT_TAG:
continue
pkt_name = packet.attrib[self.NAME_FIELD]
pkt_id = int(packet.attrib[self.ID_FIELD])
ch_list = []
for ch in packet:
ch_name = ch.attrib[self.CH_NAME_FIELD]
if ch_name not in ch_name_dict:
raise exceptions.GseControllerParsingException(
"Channel %s in pkt %s, but cannot be found in channel dictionary"
% (ch_name, pkt_name)
)
ch_list.append(ch_name_dict[ch_name])
pkt_temp = PktTemplate(pkt_id, pkt_name, ch_list)
id_dict[pkt_id] = pkt_temp
name_dict[pkt_name] = pkt_temp
return (id_dict, name_dict)


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