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McDermott Library
University Commons
University Village Phase 5 & 6
University Village Phase 1 & 2
Rutford Avenue North-South
Date:
Hour
# of Riders
8-9am
10
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23
10-11am
35
11am-12pm
67
12-1pm
75
1-2pm
70
2-3pm
73
3-4pm
65
4-5pm
43
5-6pm
32
6-7pm
26
7-8pm
20
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10
9-10pm
13


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Vegetable Vagabonds is a company focused on providing plant-based food. It functions as a pop-up restaurant giving the business mobility and the possible benefit of catering events. Their online presence lacked a professional website. Their online social media presence was gaining traction but their linked website wasn’t fully developed due to the skills necessary to complete and lack of funding.
Using a structured but iterative design process by taking methods from agile, I deliver the full lifecycle of this design. From ideation to implementation, I promote congruity with the customer needs, user needs, and creative needs.
During discovery, I’m focused on understanding the client needs, user needs, and pain points. As I develop a general idea of where to being, I move to define the persona and user flows and interpret the old information archetecture to develop a new map. Once I am able to explore, I begin understanding the user directly using surveys and the client’s main competitors with competitive analysis. Finally, I have enough information to begin building and reiterating during the visual designing the wireframes, user testing, and prototypes. Once the client is satisfied, I code out the website using a Bootstrap framework and deploy on Netlify.
Vegetable Vagabonds focus on the comfort food culture more than the health food culture. With Portland, Oregon’s saturated plant-based restuarant market, Vegetable Vagabonds creates a niche market within plant-based restuarants offering pub and soul food.
Expectations: Build a simple single page website for new and returning customers to easily navigate. Include a life Instagram feed for recent updates and an event calendar using Google Calendar for customer awareness of availability and upcoming events.
Potential Users: Event hosts, wedding planners, community events, farmers markets.
Personas: Based on interviewing the owner, the target market has three distinct target markets; people who attend festivals, farmers market shoppers, and event hosts. Highlighted below are the top two personas that help make my design decisions.
Competitive Analysis: I use a simple SWOT analsis framework to evaluate the restaurant’s competitive position creates a strategic plan and identifying Vegetable Vagabonds opportunity to grow and capture a niche market.
Information Archetecture: Following a basic sitemap structure, the purpose was to create a simplified single page site. Instead of seperating each subpage, creating a single page with the basic information makes the website easy to find information. The site includes a menu with anchor links for easy navigation.
Originally, the site was going to include multiple pages. Considering the client wants the site to be accessed easily and quickly, I used a mobile-first design method for access on the go. When carving out rough ideas for the site, I focus on features first.
Client continued to approve multiple site ideation through high-fidelity wireframes. After reviewing the low-fidelity wireframes with the client, he provided me with feedback, edits and revisions. The high fidelity wireframes included a responsive calendar function and downloadable sample menu.
I coded the design using a Bootstrap framework and used an existing old template for speed. In addition, I included script from Instafeed.js and embedded Google Calendar in iframe for a responsive design.
Once satisfied with the coded site, I hosted on Github and deployed on Netlify. Creating a simple and affordable site is important for the client due to starting business with minimal capital.


Simple Binding
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Item 3.9.10.a. In a previous class, ask students to bring in graphs they find online. Partisan news organizations are a good place to look.


Who SUITS you?
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It's better to be blunt than hide your feelings.
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You see yourself as critical thinker more than a creative person.
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Giving back to the community is important.
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You value education and family life high
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People consider you to be easy going and spontaneous
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It is often difficult for you to relate to other people’s feelings.
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In a discussion, truth should be more important than people’s sensitivities.
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You rarely get carried away by fantasies and ideas.
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You think that everyone’s views should be respected regardless of whether they are supported by facts or not.
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You consider youself as a religious person.


| B_01_xyplot.ts {lattice} | R Documentation |
This function handles time series plotting, including cut-and-stack plots. Examples are given of superposing, juxtaposing and styling different time series.
## S3 method for class 'ts' xyplot(x, data = NULL, screens = if (superpose) 1 else colnames(x), ..., superpose = FALSE, cut = FALSE, type = "l", col = NULL, lty = NULL, lwd = NULL, pch = NULL, cex = NULL, fill = NULL, auto.key = superpose, panel = if (superpose) "panel.superpose" else "panel.superpose.plain", par.settings = list(), layout = NULL, as.table = TRUE, xlab = "Time", ylab = NULL, default.scales = list(y = list(relation = if (missing(cut)) "free" else "same")))
x |
an object of class |
data |
not used, and must be left as |
... |
additional arguments passed to |
screens |
factor (or coerced to factor) whose levels specify which
panel each series is to be plotted in. |
superpose |
overlays all series in one panel (via |
cut |
defines a cut-and-stack plot.
|
type, col, lty, lwd, pch, cex, fill |
graphical arguments, which are processed and eventually passed to
|
auto.key |
a logical, or a list describing how to draw a key. See the
|
panel |
the panel function. It is recommended to leave this alone, but one
can pass a |
par.settings |
style settings beyond the standard |
layout |
numeric vector of length 2 specifying number of columns and rows in the plot. The default is to fill columns with up to 6 rows. |
as.table |
to draw panels from top to bottom. The order is determined by the
order of columns in |
xlab, ylab |
X axis and Y axis labels; see |
default.scales |
|
The handling of several graphical parameters is more
flexible for multivariate series. These parameters can be
vectors of the same length as the number of series plotted or
are recycled if shorter. They can also be (partially) named list, e.g.,
list(A = c(1,2), c(3,4))
in which c(3, 4)
is the
default value and c(1, 2)
the value only for series A
.
The screens
argument can be specified in a similar way.
Some examples are given below.
An object of class "trellis"
. The
update
method can be used to
update components of the object and the
print
method (usually called by
default) will plot it on an appropriate plotting device.
Gabor Grothendieck, Achim Zeileis, Deepayan Sarkar and Felix Andrews<EMAIL_ADDRESS>The first two authors developed xyplot.ts
in their zoo
package, including the screens
approach. The third author
developed a different xyplot.ts
for cut-and-stack plots in the
latticeExtra package. The final author fused these together.
Sarkar, Deepayan (2008) Lattice: Multivariate Data Visualization with R, Springer. http://lmdvr.r-forge.r-project.org/ (cut-and-stack plots)
xyplot
,
panel.xyplot
,
plot.ts
,
ts
,
xyplot.zoo
in the zoo package.
xyplot(ts(c(1:10,10:1))) ### Figure 14.1 from Sarkar (2008) xyplot(sunspot.year, aspect = "xy", strip = FALSE, strip.left = TRUE, cut = list(number = 4, overlap = 0.05)) ### A multivariate example; first juxtaposed, then superposed xyplot(EuStockMarkets, scales = list(y = "same")) xyplot(EuStockMarkets, superpose = TRUE, aspect = "xy", lwd = 2, type = c("l","g"), ylim = c(0, max(EuStockMarkets))) ### Examples using screens (these two are identical) xyplot(EuStockMarkets, screens = c(rep("Continental", 3), "UK")) xyplot(EuStockMarkets, screens = list(FTSE = "UK", "Continental")) ### Automatic group styles xyplot(EuStockMarkets, screens = list(FTSE = "UK", "Continental"), superpose = TRUE) xyplot(EuStockMarkets, screens = list(FTSE = "UK", "Continental"), superpose = TRUE, xlim = extendrange(1996:1998), par.settings = standard.theme(color = FALSE)) ### Specifying styles for series by name xyplot(EuStockMarkets, screens = list(FTSE = "UK", "Continental"), col = list(DAX = "red", FTSE = "blue", "black"), auto.key = TRUE) xyplot(EuStockMarkets, screens = list(FTSE = "UK", "Continental"), col = list(DAX = "red"), lty = list(SMI = 2), lwd = 1:2, auto.key = TRUE) ### Example with simpler data, few data points set.seed(1) z <- ts(cbind(a = 1:5, b = 11:15, c = 21:25) + rnorm(5)) xyplot(z, screens = 1) xyplot(z, screens = list(a = "primary (a)", "other (b & c)"), type = list(a = c("p", "h"), b = c("p", "s"), "o"), pch = list(a = 2, c = 3), auto.key = list(type = "o"))


Form Verification Example
User:
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Email:
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Invalid Email Address


- The Internet was created by 2 men called Bob Kahn and Vint Cerf.
- The Internet was the result of ARPANET or Advanced Research Projects Agency Network.
- Paul Baran was trying to make something that could survive a nuclear attack and make it possible to communicate still.
- The internet is made up of large independently operated networks.
- There is no central control, there is no person that truly owns the internet.


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1. Introduction¶
1.1. What is machine learning¶
Machine learning is the science (and art) of programming computers so they can learn from data.
A slightly more general definition by Arthur Samuel in 1959:
Field of study that gives computers the ability to learn without beging explicitly programmed.
Common definition by Tom Mitchell in 1988:
A computer program is said to learn from experience E with respect to some task T and some performace measure P, if its performance on T, as measured by P, improves with experience E.
1.2. Why use machine learning¶
machine learning especially shines in these four fields:
problems for which existing solutions require a lot of fine-tuning or long lists of rules, e.g spam-filter.
complex problems for which using a traditional approach yields no good solution, e.g speech-recognition.
a machine learning system can adapt to new data.
getting insights about complex problems and large amounts of data.
1.3. Examples of applications¶
Basic machine learning:
basic regression
basic classification
dimension reduction & visualization
clustering
anomaly detection
Computer vision:
image classification, typically use CNNs.
semantic segmentation, e.g detecting tumors in scan, use CNNs.
Natural Language Processing:
text classification(include text sentiment analysis), typically use RNNs, Transformers.
text summerization, use RNNS, Transformers.
chatbot or personal assistant, this involves many NLP components, including NLU and question answering.
speech recognition
Recommender System
Reinforcement Learning, e.g AlphaGo.
1.4. Types of machine learning¶
by whether or not they are trained with human supervision:
supervised learning: the training set you feed to the algorithm includes the desired solutions, called labels.
unsupervised learning: the training data is unlabeled.
semi-supervised learning: can deal with data that’s partially labeled.
reinforcement learning: the learning system called an agent can observe the evironment, select and perform actions, and get reward in return. it must learn by itself what is the best strategy, called policy, to get the most reward over time.
by whether or not they can learn incrementally on the fly (online versus batch learning)
by whether they work by simply comparing new data points to known data points (like KNN), or instead by detecting patterns in the training data and build a predictive model. (instance-based versus model-based learning)
1.5. Main challenges of machine learning¶
“bad data” aspect:
insufficient quantity of training data.
nonrepresentative training data.
poor-quality data.
irrelevant features.
“bad algorithm” aspect:
overfitting: model performs well on the training data, but it does not generalize well.
underfitting: model is too simple to learn the underlying structure of the data.
1.6. Testing and Validation¶
the error rate on new cases is called the generalization error.
we split data into training set and test set, train the model using training set, test it using test set (use error on test set to estimate generalization error).
in hyperparameter tuning and model selection, once we use test set to select models, then test error can not be use to estimate generalization error.
because you adapted the model and hyperparameters to produce the best models for that particular set.
a common solution is called hold-out validation: hold out part of training set to evaluate several candidate models, after picking the best model, we typically retrain that best-model using the whole training set.
suppose we want to choose a model from \(\mathcal{M} = \left\{M_{1},...,M_{d}\right\}\).
hold-out validation:
randomly split dataset \(S\) into \(S_{train}\) (say 70% of the data) and \(S_{val}\) (say 30% of the data).
train each model \(M_{i}\) on \(S_{train}\) only, get \(h_{i}\).
use \(h_{i}\) to compute error on \(S_{val}\), choose the corresponding model that minimize this error.
problems: wastes \(S_{val}\) data, only evaluate on \(S_{val}\) may add bias.
1.6.1. k-fold cross validation¶
one solution of these problems is k-fold cross validation:
randomly split \(S\) into k even disjoint subsets \(S_{1},...,S_{k}\).
for each model \(M_{i}\)
\(\quad\) for \(j=1,...,k\), train on all data except \(S_{j}\) to get hypothesis \(h_{ij}\)
\(\quad\) test \(h_{ij}\) on \(S_{j}\) to get \(\hat\epsilon_{S_{j}}(h_{ij})\)
estimate generalization error on \(M_{i}\) as \(\sum_{j=1}^{k}\hat\epsilon_{S_{j}}(h_{ij})\).choose the model that minimize the estimated generalization error.
\(k=10\) is a commonly used choice.
disadvantage: computationally expensive.
1.6.2. data mismatch¶
in some cases, it’s easy to get a large amount of data for training, but this data won’t be perfectly representative of the data in production.
in this case, the most important rule is that validation set and test set must be as representative as possible.
typically, mismatch data is separated into train set and train-dev set. we first train the model no train set, then evaluate model on train-dev set.
when \(P(validation) << P(train)\)
\(\quad\)if \(P(train\_dev) << P(train):\)
\(\quad\quad\)overfitting is a cause
\(\quad\)elif \(P(train\_dev) \approx P(train):\)
\(\quad\quad\)cause is data mismatch
1.7. feature selection¶
we can use validation to select features.
foward search:
initialize \(\mathcal{F} = \emptyset\)
repeatedly:
\(\quad\)add each un-included feature to \(\mathcal{F}\), then use cross validation to pick the best feature, add this best feature to \(\mathcal{F}\).end until \(\mathcal{F}\) include all features.
disadvantage: computationally expensive.
other heuristic filter feature selection:
compute correlation between \(X_{i}\) and \(Y\), then pick \(k\) most correlated features.
in practice, we commonly replace correlation with mutual-information.
if \(X, Y\) are independent, \(I(X,Y)=0\).
1.8. no free lunch theorem¶
demonstrate that if you make absolutely no assumption about the data, then there is no reason to prefer one model over any other.


I am a Junior at Michigan State University. Currently, I am studying Media & Information with a specialization in IT. I plan to graduate at the end of next year. Over the summer I interned at a Saas and Cloud computing company in Jupiter, FL. I gained a lot of experience in Quality Assurance and in agile and waterfall work enviornments.
In TC349 we are learning how to build websites. This is part of the overall final assignment in creating a portfolio for ourselves. The class meets every Monday and Tuesday at 6pm until 7:30pm. On Tuesdays we have a lab to learn and to get help on assignments.


项目主页:
MojoTracker
此程序采用
BSD 开源协议，
如果您认为软件缺少一些重要的功能，请向我们贡献代码。
webOS系统的软件开发也不是件太难的事情！
如果您发现了程序缺陷或对程序有任何的意见和建议，请
提交问题.
更新日志
-
0.3.3
-
0.3.2
- Add Chinese translation
- Option for export all tracks
- Fix for map resolution on Pre^3
-
0.3.1
-
0.3.0
- Optionally discard nodes with high error from export
-
0.2.9
-
0.2.8
- Fix export for long tracks
- Fix time on graphs
-
0.2.7
- Some improvements around map preview
- Fixes for devices with different screen resolution
- Add Ohloh widget to "About" page
-
0.2.6
- Change track ordering
- Fix for webOS 2
-
0.2.5
- Fixed map drawing for south hemisphere
-
0.2.4
- Make possible rename track
- Fixed waypoint list handling on "info" page
-
0.2.3
- Draw waypoints on map preview
- Fix timezone handling
-
0.2.2
- Add option for export waypoints (to *.loc file)
- Add map preview to info page (use OpenStreetMap.org exports)
-
0.2.1
- Split export files is no longer needed
- Reduce nodes count when device isn't moving
-
0.2.0
- Add waypoints support
- Prevent sleep when tracking is on
- Make MojoTracker translatable
- Add popup menu to location (copy to clipboard, share via SMS/email)
- Fixed export to kml (null values issue)
-
0.1.29
- Added screen with detailed track info
- Added altitude and speed graphs
- Added export to kml data format
-
0.1.28
- Warning: DB format isn't compatible with previous release
- Displays and stores more information like altitude, position accuracy, speed...
- Added preference page, specify preferred units.
- Added page with list of saved tracks
- Added option to delete saved track
- Added export button,
FileMgr service
is required for this functionality (tested with FileMgr 0.5.1 api)
- Added compass
-
0.1.27
- First public release
- Display position information from internal GPS
- Store tracks to SQLite file on internal storage
- Exports tracks to gpx file - requires external conversion tool


This example demonstrates the containing document interacting with the iframe.
Back to Cross-Doc Index | Iframes Examples Index


Mothers Day Flowers Uk - Sending Flowers Online, Flowers Delivery ...
It has mid 1920s around its bouquet, organized to its mid order flowers online misdreavus. Eli does with jackie's recent shop to assassinate' their success tells.
http://flowersfordelivery.webs.com/mothers-day-flowers-uk.html
35 Miles from Center
problem with post office email connection


--- layout: post title: "Introducing the Smart Grid for ASP.NET MVC" postId: 28 ---
Edit: Some documentation for the Grid is now available at the MvcContrib Wiki.
I've recently been working on an equivalent of the ASP.NET GridView for use with ASP.NET MVC.
This is partially inspired by the SmartGrid component which is part of the Castle Contrib project, but uses lambdas in order to build up a set of columns that can be automatically turned into an HTML table. For example, I might have this in an ASP.NET MVC Controller:
public class HomeController { private UserRepository repository = new UserRepository(); public ActionResult Index() { ViewData["users"] = repository.FindAll(); return RenderView(); } }
Then in my View I could have this:
<% Html.Grid<Person>( "people", column => { column.For(p => p.Id); column.For(p => p.Name); column.For(p => p.Gender); column.For(p => p.RoleId); } ); %>
Which would create something like this:
Note how the column names are automatically generated from the lambda expressions. However, you can override a column heading:
column.For(p => p.Id, "ID Number");
You can also create custom columns using lambda statements...
column.For("Custom Column").Do(p => { %> A custom column...	 <% });
...and columns can have formatting applied to them:
column.For(p => p.DateOfBirth).Formatted("{0:d}");
Pagination is also fully supported by using the AsPagination extension method which works on any IEnumerable<T> or IQueryable<T>
public ActionResult Index(int? page) { ViewData["users"] = repository.FindAll().AsPagination(page ?? 1); return RenderView(); }
Which would produce something like this:
The source code is available in the mvccontrib trunk.


Dez Bryant throws shade at Jason Garrett in Cowboys loss
by TSD StaffThe Cowboys lost yet another close game on Sunday, this time against the Patriots, and it didn’t take long for those in the football world to weigh in about it.
Dallas’ defense played well, and the team was competitive from start to finish, with the Patriots never being able to extend their lead past one score — aside from a four-minute stretch in the second quarter, when it was a 10-point margin. As such, head coach Jason Garrett began falling in love with field goals, perhaps to a fault, even. That prompted criticism from fans and media members alike.
A former Cowboys player who knows Garett well also elected to share his thoughts. Dez Bryant took to Twitter during the game, and that’s when he posted the following message.
Here’s the thing: That tweet was posted late in the game, just after Garrett was ripped for kicking a field goal with six minutes left, and his team in the red zone. Garrett chose to kick, rather than going for it on 4th-and-7, and it hurt the team, as the offense failed to score a point after that time.
As such, it sure looks like Dez was throwing some shade at his former coach there in talking about “better coaches and game plan,” but you can judge for yourself.


Elder Cronos:
Ha! Cheeky, aren't you? Well, if you are sure that you are ready... Don't hang around here bawling if you fail...
Take the test


J.R.R. Tolkien
Of his life and legendarium
Here is a short timeline of his personal and literary life:
Early Life
- 3 January 1892 Birth of John Ronald Reuel Tolkien in Bloemfontein, Orange Free State (now part of South Africa).
- Autumn 1907 Tolkien probably invents his private language ‘Naffarin’ based on Spanish and Latin.
- 1908 Tolkien meets Edith Bratt, another lodger.
- 17 December 1910 Tolkien obtains a scholarship at Oxford’s Exeter College.
- Summer 1911 Tolkien becomes school librarian, and the T.C.B.S. (Tea Club and Barrovian Society) is formed.
Oxford and Early Career
- October 1911 Tolkien begins studying at Oxford.
- 1913 Tolkien writes to Edith on his 21st birthday, and soon after they become engaged.
- January 1914 Tolkien and Edith become betrothed after she is received into the Catholic Church.
- 24 September 1914 Tolkien writes his first identifiable “Middle-earth” fragment ‘The Voyage of Éarendel the Evening Star’.
- 25-6 Sep 1915 Final meeting of all four main members of the T.C.B.S. in Lichfield.
- 22 March 1916 Ronald and Edith are married in Warwick.
- 1 July 1916 Battle of the Somme begins. Rob Gilson, close friend and member of the T.C.B.S. dies.
- 9 November 1916 Suffering from trench fever, Tolkien returns to England.
- 3 December 1916 G.B. Smith, a member of the T.C.B.S., dies from wounds received 4 days earlier.
- c. May 1917 Tolkien is inspired by watching Edith dance in a ‘hemlock’ glade near Roos. This is the germ for the meeting of Lúthien and Beren in his legendarium.
- November 1918 The Tolkiens return to Oxford. Tolkien obtains employment with the New English Dictionary[Oxford English Dictionary]. Tolkien probably begins work on the first version of ‘The Music of the Ainur’.
- Autumn 1920 He begins work as a Reader in English Language at Leeds University. Michael, the Tolkiens’ second son is born on 22 October.
- 21 November 1924 Christopher, the Tolkiens’ third son is born.
- Autumn 1925 Tolkien takes up an appointment as Rawlinson and Bosworth Professor of Anglo-Saxon at Oxford. He purchases a house in Oxford.
- 11 May 1926 First known meeting between C.S. Lewis and Tolkien, and they soon become friends.
- December 1929 C.S. Lewis reads and critiques the Lay of Leithian.
The Hobbit, The Lord of the Rings and Academic Career
- Summer 1930 About this time, Tolkien may have written the first sentence of The Hobbit: “In a hole in the ground there lived a hobbit“.
- 19-20 Sep 1931 Tolkien and Hugo Dyson talk with C.S. Lewis, who begins to shift from believing in God to accepting Christ. This event also inspires Tolkien to later write the poem ‘Mythopoeia’.
- Late? 1932 Tolkien probably lends the typescript of The Hobbit to C.S. Lewis, which at this time ends with the death of Smaug.
- Autumn 1933 The Inklings meetings under the auspices of C.S. Lewis become an important part of Tolkien’s social life.
- Early 1936 Susan Dagnall of Allen & Unwin reads the unfinished manuscript of The Hobbit. She urges him to finish the narrative, and it is accepted for publication.
- 21 September 1937 The Hobbit is published. Because of its success, Stanley Unwin subsequently urges Tolkien to write a sequel, which he begins. This is the germ of The Lord of the Rings.
- 23 June 1945 Tolkien becomes Oxford’s Merton Professor of English Language and Literature.
- Feb-Oct 1949 Tolkien types up The Lord of the Rings making corrections as he works.
- April 1950 Tolkien gives an ultimatum to Sir Stanley Unwin requesting an immediate response in answer to his suggestion to publish both The Lord of the Rings and The Silmarillion. Later that year Waldman informs Tolkien that The Lord of the Rings must be cut.
- Late 1951 Tolkien probably writes a long letter to Waldman explaining why The Silmarillion and The Lord of the Rings are indivisible and interconnected. During this year Tolkien probably works on a prose version of the later part of Narn i Chin Húrin from ‘The Return of Túrin’ to his death.
- April 1952 Collins, the publishers, decline to publish The Lord of the Rings.
- August 1953 The subtitles The Fellowship of the Ring, The Two Towers and The Return of the King are chosen for individual volumes of The Lord of the Rings.
- 29 July 1954 Publication of The Fellowship of the Ring.
- 11 November 1954 Publication of The Two Towers.
- 20 October 1955 Publication of The Return of the King.
- August 1957 Tolkien wins an International Fantasy Award.
- April 1959 Although he had toyed with the idea previously, at about this time, Tolkien begins developing his round-earth cosmology of Arda.
Retirement and Later Life
- 7 August 1961 Pamela Chandler photographs Tolkien for the first time.
- 12 December 1962 An interview with Tolkien is broadcast on BBC TV.
- 22 November 1963 Death of C.S. Lewis.
- 22-3 March 1966 The Tolkiens celebrate their Golden Wedding and enjoy a performance of Donald Swann’s song-cycle of The Road Goes Ever on.
- 7 August 1966 Tolkien is photographed by Pamela Chandler for the second time, this time entirely in colour.
- c. March 1967 Humphrey Carpenter visits Tolkien, and later describes the encounter in his biography.
- 6 November 1969 The ‘informal’ beginning of The Tolkien Society.
- 29 November 1971 Death of Edith Tolkien.
- 27 June 1972 The Tolkien Society’s founder, Vera Chapman, meets Tolkien at a reception at Allen & Unwin’s offices in London. Tolkien consents to becoming the Society’s Honorary President and states, “If I can help your society in any way, I will.”
- 2 September 1973 Death of J.R.R. Tolkien from a stomach ulcer.
Posthumous Events
- 5 May 1977 Publication of J.R.R. Tolkien: a Biography by Humphrey Carpenter.
- 15 September 1977 Publication of The Silmarillion, edited by Christopher Tolkien.
- 2 October 1980 Publication of Unfinished Tales of Númenor and Middle-earth, edited by Christopher Tolkien.
- 20 August 1981 Publication of The Letters of J.R.R. Tolkien, edited by Humphrey Carpenter with the assistance of Christopher Tolkien.
- 16 April 2007 Publication of The Children of Húrin, edited by Christopher Tolkien.
- 4 May 2017 Publication of Beren and Lúthien, edited by Christopher Tolkien.
- 23 August 2018 To be published - The Fall of Gondolin, edited by Christopher Tolkien.
One of my favorite quotes from the his most well-known and beloved novel is:
I don't know half of you half as well as I should like; and I like less than half of you half as well as you deserve.
― J.R.R. Tolkien, The Fellowship of the Ring.


Star System Design
Help Me Pick New Logo Through 3 April 2016!
I am in the process of running a logo design contest on 99designs and have created a poll with 6 of the best logo designs I've received. I would love for you to vote on the logo design. It only takes a minute.
Like Sci-Fi? Read My New Online Fiction Series.
Do you like Sci-Fi? While I finish up my next novel, I have started an online fiction series called Forbearance. Picking up from the canteen scene in Bellicose, we meet Keius Minjen, a postal marine, as he tries to survive the battle planet Guna to exact revenge and one day liberate his homeland.
Sign-up if you want me to send you news about upcoming installments of Forbearance or my other writings.
Core Attributes
These are attributes that no world can do without. The goal is to have as few as possible core attributes. We can then have suggested additional attributes. What are the fundamental attributes? I define fundamental as those needed to provide macro-interactivity. They could be sub-divided, but don’t have to be.
The four attributes below fall into two general categories: Survival and Material. Gravity and Habitat both discuss the survivability of a planet. Resources and Colony both discuss material availability. Habitat and Resources when certain resources make a planet habitable. However, the two categories (Survival and Material) may be a little too generic for regular game play.
These are the fundamental attributes that are essential for game play. The goal is to be minimalist: give just enough to spark a GM. Allow individual `GMs to flesh out their own attribute list if they chose to. They can be called “meta-attributes,” and closely relate to the meta-attributes in Vanilla Fudge (i.e., Body, Mind, Soul).
There are other planetary attributes that do not factor into game play. Two come readily to mind: Size and Density.
Gravity
Gravity is a fairly self-descriptive attribute, and affects game play in three ways: hyperspace travel, near-surface travel, and survivability.
Hyperspace travel requires that a ship be more than a minimum safe distance away from a gravity body. A planet with higher gravity has a further minimum safe distance. Initiating too close incurs penalties. When the gravity is higher and the distance is closer, then naturally the penalty is higher.
Non-Hypespace Travel is affected as well. When attempting to enter/leave a planet, gravity affects the efficiency and success. When travelling on the surface, the efficiency is influenced: if you are acclimated on a Fair Gravity planet, you won’t be able to walk as far, or carry as much, on a Good Gravity planet.
Survivability relates to other situations where gravity affects game play. When you fall off a cliff, how much damage you sustains is tightly coupled with gravity. If you are acclimated on a Good Gravity planet, and fall off a cliff on a Mediocre Gravity planet, you will probably not suffer as much damage (stronger bones, maximum velocity, etc.) Also, being acclimated on a higher gravity planet than the races home planet (e.g. Terrans and Earth’s Fair Gravity) suggests you are more densely built (tougher bones) and shorter. Also, living on a higher Gravity planet affects your ability to deliver melee damage.
Limits to Gravity
Additionally, races may have limits to the range of Gravity they are able to live on for protracted periods. Perhaps not more than one level above or below their native gravity. So, a human acclimated on Earth would have issues on more than a Good Gravity planet (or less than Mediocre). A human acclimated to living on the Moon (Poor Gravity), would probably not do well on Earth (Fair Gravity). Perhaps the best soldiers come from Great Gravity planets?
Habitat
Habitat describes survivability in the natural environment. It broadly covers factors contributing to survivability such as breathable atmosphere, presence and abundance of water, natural foodstuff, protection from radiation, as well as crazy weather, suitable climate, and other natural factors. When considering Habitat, as yourself how well could a Terran, for example, survive on the surface of the planet without extensive surivival gear? This doesn’t necessarily apply to the whole planet, as even on Earth we have our more difficult areas.
This attribute interrelates more closely with other attributes. Abundant Resources, for example, suggests higher plate techtonics which reduces survivability. A Good Habitat will encourage a larger Colony. Also, when certain resources make a planet more habitable, the Habitat trait level is use to determine availability.
| Factors Affecting Habitat |
|---|
| Atmosphere: can a species breath on this planet? |
| Climate: are the seasons, temperature, and weather patterns safe? |
| Firmament: can a species live on the surface? |
| Life: is there other compatible life (i.e. food) |
| Radiation: is there adequate protection but not too much? |
||align=center border=1 width=80% cellspacing=0
| Habitat | Most of planet is… | You will need… |
|---|---|---|
| Superb | paradise | a loincloth, the stars to sleep under |
| Great | Earth-like | a jacket, a hut |
| Good | problematic | extreme weather gear, an insulated house |
| Fair | unhealthy | breathing gear, an airtight structure |
| Mediocre | dangerous | environment suits, an airlocked structure |
| Poor | deadly | a specialized rover, a colony dome |
| Terrible | unsurvivable | a spacesuit and colony dome |
These factors are not all inclusive, but representative. Regions on any given planet are commonly as much as two levels above or below the planet’s general level.
Colony
Colony generally describes the size of a sentient population on the planet, as well as the availability of fabricated goods and specialty professions. Do you need a preplacement hyperdrive or a computer psychiatrist? You’re more likely to find either or both on a planet with a higher Colony. When multiple sentient aliens co-habitate, then there may be multiple Colony attributes, one for each species.
Below is a sample of how Colony generally speaks to population size. Older settlements are more likely to have higher Colony scores; although it is possible to have a smaller population but still have a higher availability of goods or specialists.
| Sample Colony Sizes | |
|---|---|
| Superb | >10B |
| Great | 1B |
| Good | 100M |
| Fair | 10M |
| Mediocre | 1M |
| Poor | 100K |
| Terrible | <1K |
Resources
Resources affects the ability to acquire natural, raw material. It suggests a higher level of geological turn over, which may reduce survivability (see Habitat). So, for example, if you need a certain quantity of bauxite, and the planet has Good Resources, then there’s a Good chance you’ll find it in a timely fashion. Resource affects the presence, quantity, and availability of a material.
With Earth as a baseline, for each level above Fair, it sould reasonably be said that a material is either more likely to be present, more of it, or easier to reach. Superb Resources may mean that there’s a lot of what you’re looking for everywhere you look. Great may mean there is an exotic element, and a lot of it, but you’ll have to work to harvest it, or that there is an exotic element that is easy to reach, but not much of it.
Sample Planet Squibs
Example(s):
| Plegeris III: | |
|---|---|
| Gravity: | Good |
| Resources: | Poor |
| Habitat: | Poor |
| Colony: | Fair (2.4M) |
| Squib: \ | |
||align=center border=1 width=50% cellspacing=0
| Gravity: | Fair |
| Resources: | Fair |
| Habitat: | Great |
| Colony: | Superb (6+B) |
| Squib: \ | |
||align=center border=1 width=50% cellspacing=0
| Gravity: | Poor |
| Resources: | Poor |
| |Habitat: | Terrible |
| Colony: | Poor (45k) |
| Squib: \ | |
||align=center border=1 width=50% cellspacing=0
| Gravity: | Mediocre |
| Resources: | Mediocre |
| Habitat: | Mediocre |
| Colony: | Fair (1.2M) |
| Squib: \ | |
Attributes and Other Sentient Life
Of course, this all seems a little too Terran specific. It is not, but Terrans are what we are, so it is easiest to use our common frame of reference. What if you have another sentient species? How do they fit into it?
Well, there is a bit of a kink, but not much. I will start with a sample planet
| Nipsvjut (Methos): | |
|---|---|
| Gravity: | Great |
| Resources: | Poor |
| Habitat: (Human) | Terrible |
| Habitat: (Methan) | Great |
| Colony: (Human) | Terrible (1,432) |
| Colony: (Methan) | Superb (12B) |
| Squib: \ | |
This is how we describe a planet that is not so habitable to humans, but is habitable to another sentient species. Factors that make a planet habitable for one species may not make it habitable for another. When it is relevant to discuss a planet in light of more than one Habitat or Colony, then list the differences in attributes. Of course, before a planet’s habitat can be determined, the species’ needs must be developed.
Or, one where two species are likely to conflict.
| Plegeris III: | |
|---|---|
| Gravity: | Good |
| Resources: | Poor |
| |Habitat: (Human) | Poor |
| Habitat: (Darit) | Fair |
| Colony: (Human) | Fair (2.4M) |
| Colony: (Darit) | Good (15M) |
| Squib: \ | |
Initially written.
— ~BenWilson – 07 Dec 2004
Cleaned up, clarified, and reorganized.
— ~BenWilson – 09 Dec 2004
Tweaked
— ~JohnUghrin – 10 Dec 2004
System Name:
Gravity: Level
Resources: Level
Habitat: Level
Colony: Level
Squib:


{% extends "ex01/base.html" %} {% load static %}
Web frameworks need a convenient way to generate HTML. Django relies on templates. Template files contains the static parts of the desired HTML output as well as some special syntax describing how other content will be inserted. Using the code editor, create a templates directory within the pages app and within that create the files called base.html, home.html, and about.html. In other words, your html templates should be at pages/templates/. By default, Django’s template loader will look in the templates folder to find a matching template. We could modify the loader settings but not on this project.


DC Collectibles Animated Batman Line Becomes ‘The Adventures Continue’
by Luke Y. ThompsonThe problem with any toy line based on an older TV show is that eventually, it runs out of characters to make. If no new episodes get made, no new personalities get added to the roster of potential figures. So what to do with a hugely successful collector line like DC Collectibles‘ Batman: The Animated Series? In DC’s case, the company is imagining the show kept going. Batman: The Adventures Continue gives the Bruce Timm-style treatment to villains and others who never appeared on the show. Plus a few comic-inspired variants on familiar heroes who did.
Rebranding next July, The Adventures Continue includes a familiar Robin and Joker. Joining them, we will see an all-new Deathstroke, and a deluxe “Super Armor” Batman. The latter, of course is based on the final battle with Superman from Frank Miller’s The Dark Knight Returns. With perhaps a touch of Ben Affleck’s armor additionally thrown in.
RELATED: DC Comics Heroes Get ‘DCeased’ Infected Action Figures
As the figures are in scale with each other and appropriately sized, the price points vary too. Joker and Robin run around $30, with $35 for Deathstroke and $40 for big Batman. So not only will the line not be limited by what appeared on TV; it also won’t be hamstrung by having to keep figures the same size. We look forward potentially to DC Collectibles making over characters like Batwoman and Damian Wayne this way.
Check the gallery below for the first four figures. Who would you like to see added to the line that never showed up in an episode? Let us know in comments.


Consultation outcome
MS Word Document , 624KB
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PDF , 272KB , 10 pages
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This targeted consultation opened on 10 October 2013 so that interested parties could consider our proposals in light of the final regulations.
Associated resources: Inspecting local authority children’s services: the framework
This consultation ran from
to
Consultation on proposals to review the effectiveness of the Local Safeguarding Children Board.
This consultation was held on another website .
MS Word Document , 622KB
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PDF , 275KB , 12 pages
If you use assistive technology (such as a screen reader) and need a version of this document in a more accessible format, please email<EMAIL_ADDRESS>. Please tell us what format you need. It will help us if you say what assistive technology you use.
We have already conducted a wider consultation about the contents of this review. This consultation is targeted at those who have a specific interest in, or expertise relating to, the effectiveness of Local Safeguarding Children Boards.
The closing date for the consultation is 23 October 2013.
Published: 10 October 2013
Updated: 11 October 2013
From: Ofsted


माँ सरस्वती निजी औद्योगिक प्रशिक्षण संस्थान
MAA SARASWATI PVT. INDUSTRIAL TRAINING INSTITUTE
An Institute Run and Govern by Experienced Technocrats
>
About Management
It is governend by Anishka Educational Society of Kota which is run by qulaified engineers of various streams. The president of society is an eminent personality of society Ms. Deepti Manoj Singh a great scholar. The secretary is Mr. Mahendra Kumar Verma, a production engineer from Government College, Kota and a well known educationalist. The treasurer is Mr. Nitin Verma a computer engineer from Government College, Kota and a great teacher. Their thoughts to do something for the society and common person gave rise to the ANISHKA EDUCATIONAL SOCIETY, dedicated for technical education for each and every person at no profit no loss concept.
About Principal
"Technical education is the key to closed doors of employment."
In order to implement this message, Maa Saraswati Pvt ITI takes full responsibility of the personality development and skill development of the students, which will help the students to get regular education and training. College is running successfully under the guidance of Er. Randeep Joshi.
About College
Maa Saraswati Pvt ITI is located in Kota in the state of Rajasthan. It was established in 2014 by Anishka Educational Society, Kota to enhance the technical education in the state.
The college has been established in the heart of Kota, Shrinath Puram Area about 12 kms from Kota Railway Station and 10 kms from Kota Bus Stand and just nearby Rajasthan Technical University-Kota
Our Objective
To train the youth into a skilled worker and to help him/her in employment/self-employment and open new ventures. To provide skilled technician having latest know-how of the latest equipments according to the need of industry & establishment in public and private sector.
Our Mission
This institute strives hard to achieve excellence in technical education & industrial training to maintain our number one position in the state. We believe in four cardinal points of achievements:
- To equip the students with latest emerging technologies, skills and knowledge up to the level of globally competitive standards.
- To maintain a continuous interface with industry and to bring changes with time according to the needs of industry.
- To enhance the ability to anticipate and shape further the skills of budding engineers though individual and group activities to include and encourage a life long thirst for learning in students.
- To encourage the conceptual, inter personnel and team work skills for technical decision making among the students.


RCE is a distributed integration environment for scientists and engineers to analyze, optimize, and design complex systems like aircraft, ships, or satellites. It is especially suited for multidisciplinary collaboration. Handling complex systems requires many experts and several tools for analysis, design, and simulation. Using RCE, these tools can be shared between team members and integrated into automated, executable workflows. RCE is extensible and supports different scientific applications with a wide range of requirements.


APC wins Nembe with 83,041 votes - The Nation Newspaper
By Mike Odiegwu, Yenagoa
The All Progressives Congress (APC) has won the Nembe Local Government Area, Bayelsa State with its candidate, Chief David Lyon, scoring 83,041 to trounce his PDP’s counterpart, Senator Douye Diri, who polled 874.
Nembe has a total registered voters of 92,546. Out of the number 85,103 were accredited to vote in the poll.


First of all, I would like to say a THANK YOU to all the people in the service of our country who have worked hard to protect us. My thoughts and prayers have been with you this day.
I know that these days have been discouraging to many political conservatives because of the ill-considered and, at times, immoral decisions made by our country’s leadership. This makes many of us understandably want to do something about it. There are three things you can do about it today:
1. Love God
Are we letting ourselves lose focus on who is the most important Person in our lives?

Deutoronomy 6:5 & Mark 12:30, ESV
2. Love Others
Are we letting ourselves focus so much on ourselves that we lose focus on the needs of others?

Luke 10:27, ESV
Do nothing from selfish ambition or conceit, but in humility count others more significant than yourselves.
Philippians 2:3, ESV
But if anyone has the world’s goods and sees his brother in need, yet closes his heart against him, how does God’s love abide in him?
1 John 3:17, ESV
3. Keep Praying!
The Lord can change those who oppose what is good. He changed a vehement anti-Christian activist into an apostle:
But Saul, still breathing threats and murder against the disciples of the Lord, went to the high priest and asked him for letters to the synagogues at Damascus, so that if he found any belonging to the Way, men or women, he might bring them bound to Jerusalem. Now as he went on his way, he approached Damascus, and suddenly a light from heaven shone around him. 4 And falling to the ground he heard a voice saying to him, “Saul, Saul, why are you persecuting me?” And he said, “Who are you, Lord?” And he said, “I am Jesus, whom you are persecuting.
Acts 9:1-5, ESV
And immediately he proclaimed Jesus in the synagogues, saying, “He is the Son of God.” And all who heard him were amazed and said, “Is not this the man who made havoc in Jerusalem of those who called upon this name? And has he not come here for this purpose, to bring them bound before the chief priests?” But Saul increased all the more in strength, and confounded the Jews who lived in Damascus by proving that Jesus was the Christ.
Acts 9:20-22, ESV


See: Description
| Class | Description |
|---|---|
| MSXMLActiveXObjectFactory |
ActiveXObjectFactory for the MSXML ActiveX library.
|
| MSXMLConfiguration |
A container for all the JavaScript configuration information.
|
| MSXMLJavaScriptEnvironment |
JavaScript environment for the MSXML ActiveX library.
|
| MSXMLScriptable |
Base class for MSXML's (ActiveX) JavaScript host objects in HtmlUnit.
|
| XMLDOMAttribute |
A JavaScript object for MSXML's (ActiveX) XMLDOMAttribute.
Represents an attribute of the IXMLDOMElement. |
| XMLDOMCDATASection |
A JavaScript object for MSXML's (ActiveX) XMLDOMCDATASection.
Used to quote or escape blocks of text to keep that text from being interpreted as markup language. |
| XMLDOMCharacterData |
A JavaScript object for MSXML's (ActiveX) XMLDOMCharacterData.
Provides text manipulation methods that are used by several objects. |
| XMLDOMComment |
A JavaScript object for MSXML's (ActiveX) XMLDOMComment.
Represents the content of an XML comment. |
| XMLDOMDocument |
A JavaScript object for MSXML's (ActiveX) XMLDOMDocument.
Represents the top level of the XML source. |
| XMLDOMDocumentFragment |
A JavaScript object for MSXML's (ActiveX) XMLDOMDocumentFragment.
A lightweight object that is useful for tree insert operations. |
| XMLDOMDocumentType |
A JavaScript object for MSXML's (ActiveX) XMLDOMDocumentType.
Contains information associated with the document type declaration. |
| XMLDOMElement |
A JavaScript object for MSXML's (ActiveX) XMLDOMElement.
Represents the element object. |
| XMLDOMImplementation |
A JavaScript object for MSXML's (ActiveX) XMLDOMImplementation.
Provides methods that are independent of any particular instance of the Document Object Model (DOM). |
| XMLDOMNamedNodeMap |
A JavaScript object for MSXML's (ActiveX) XMLDOMNamedNodeMap.
Adds support for namespaces and iteration through the collection of attribute nodes. String comparisons in this class are case-insensitive when used with an HtmlElement ,
but case-sensitive when used with a DomElement . |
| XMLDOMNode |
A JavaScript object for MSXML's (ActiveX) XMLDOMNode.
Extends the core node with support for data types, namespaces, document type definitions (DTDs), and schemas. |
| XMLDOMNodeList |
A JavaScript object for MSXML's (ActiveX) XMLDOMNodeList.
Supports iteration through the live collection, in addition to indexed access. |
| XMLDOMParseError |
A JavaScript object for MSXML's (ActiveX) XMLDOMParseError.
Returns detailed information about the last parse error, including the error number, line number, character position, and a text description. |
| XMLDOMProcessingInstruction |
A JavaScript object for MSXML's (ActiveX) XMLDOMProcessingInstruction.
Represents a processing instruction, which XML defines to keep processor-specific information in the text of the document. |
| XMLDOMSelection |
A JavaScript object for MSXML's (ActiveX) XMLDOMSelection.
Represents the list of nodes that match a given XML Path Language (XPath) expression. |
| XMLDOMText |
A JavaScript object for MSXML's (ActiveX) XMLDOMText.
Represents the text content of an element or attribute. |
| XMLHTTPRequest |
A JavaScript object for MSXML's (ActiveX) XMLHTTPRequest.
Provides client-side protocol support for communication with HTTP servers. |
| XMLSerializer |
A JavaScript object for XMLSerializer.
|
| XSLProcessor |
A JavaScript object for MSXML's (ActiveX) XSLProcessor.
Used for transformations with compiled style sheets. |
| XSLTemplate |
A JavaScript object for MSXML's (ActiveX) XSLTemplate.
Used for caching compiled XSL Transformations (XSLT) templates. |
| Enum | Description |
|---|---|
| XMLDOMNodeList.EffectOnCache |
Cache effect of some changes.
|
Copyright © 2002–2015 Gargoyle Software Inc.. All rights reserved.


CONCLUSION
Given that the presidential race has been so close, either winner may be tempted to crack down on the press in order to control opposition to his rule. Already Zyuganov is filing formal complaints with the Central Electoral Commission about unfair media coverage and lack of television access, and revenge will certainly be on his mind if he loses. Fending off angry charges of election fraud, Yeltsin may be inclined to limit coverage of the Communist opposition on television or temporarily close Communist newspapers as he did after suppressing the 1993 parliamentary rebellion. Since then, faced with an even more contentious parliament and an unending war in Chechnya, Yeltsin has strengthened the president's security apparatus and allowed the FSB, Interior Ministry and military to harass journalists unchecked. Meanwhile, investigations have languished or have not even been started on 13 assassinations--sending a grim signal to would-be assassins dissatisfied with journalists' work.
CPJ urges the Russian government to fully investigate the murders and disappearances of the following journalists, and to bring the perpetrators of these crimes to justice.
MURDERED
Yuri Soltis, Interfax, June 12, 1994
Dmitry Kholodov, Moskovsky Komsomolets, Oct. 17, 1994
Viatcheslav Rudnev, Free-lancer, Feb. 17, 1995
Vladislav Listyev, Russian Public Television (ORT), March 1, 1995
Farkhad Kerimov, Associated Press, May 29, 1995
Natalya Alyakina, RUFA and Focus, June 17, 1995
Vadim Alferyev, Segodnyashnyaya, Dec. 27, 1995
Oleg Slabynko, Russian Television Channel 2, Jan. 25, 1996
Felix Solovyov, Free-lancer, Feb. 27, 1996
Viktor Pimenov, Vaynakh, March 11, 1996
Nadezhda Chaikova, Obshchaya Gazeta, March 30, 1996
Nina Yefimova, Vozrozhdeniye, May 8, 1996
Viktor Mikhailov, Zabaikalsky Rabochiy, May 12, 1996
MISSING
Maxim Shabalin, Nevskoye Vremya, last seen Feb. 27, 1995
Felix Titov, Nevskoye Vremya, last seen Feb. 27, 1995
Sergei Ivanov, Nevskoye Vremya, last seen June 16, 1995
Andrew Shumack, Free-lancer, last seen July 28, 1995
| (c) 1996 Committee Protect Journalists | | Front Page | CPJ Website| |


Follow along with your own computer!
We’re going to now work as a groups. Find two other people and practice commiting, pushing, and pulling.
git add – adds a file to the tracked files and stages it for commit
- Common use - git add “file.py” or git add * (To add everything)
git status – shows you the current status of your repository (like changed / added / deleted files)
git log – shows you the n last commit messages with some other data
git commit – it will “save” current state of files locally, and prepare them for git push
- Common use - git commit -m ‘Commit Message’ or git commit -am ‘Commit Messge’
git push – it will collect all of your current commits that havent been commited and push them to remote repository
- Common use - Git push origin master
git pull – combination of git fetch and git merge
- Common use - Git pull origin master
git fetch – it fetches the remote changes to your local repository, but it doesn’t change your current source contents
git merge – it’s used for merging 2 branches into one, if theres no need for 2 anymore
git branch <new-branch-name> – creates a branch with name “new-branch-name”
git diff – if you fetch the changes from remote, you can then see the difference between your code current version and last one on remote


Definition: Localization (l10n), is the process of adapting applications and text to enable their usability in a particular cultural or linguistic market.


Get in touch
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Presentation
Slides
What is UX?
UX / UI Principles
Lean UX & Agile
Frontend Development Best Practices


Sketch -- scribble with canvasTo draw, click and drag on the area within the black border to the left. You can save a drawing by clicking 'Show JSON' and saving as a text file. To load a saved drawing, you can copy and paste the JSON text into the box below, and click 'Apply JSON' button. |


GOMOS_L2
Variables
The table below lists the variables that are present in the HARP product that results from an ingestion of GOMOS_L2
data.
| field name | type | dimensions | unit | description |
|---|---|---|---|---|
| datetime | double | {time} | [seconds since 2000-01-01] | time of the profile |
| datetime_start | double | {time} | [seconds since 2000-01-01] | start time of the profile |
| datetime_stop | double | {time} | [seconds since 2000-01-01] | stop time of the profile |
| orbit_index | int32 | absolute orbit number | ||
| altitude | double | {time, vertical} | [m] | altitude |
| latitude | double | {time, vertical} | [degree_north] | latitude |
| longitude | double | {time, vertical} | [degree_east] | longitude |
| O3_number_density | double | {time, vertical} | [molec/cm3] | Ozone local density |
| O3_number_density_uncertainty | double | {time, vertical} | [molec/cm3] | standard deviation for the ozone local density |
| O3_number_density_validity | int16 | {time, vertical} | PCD (product confidence data) value for the ozone local density | |
| NO2_number_density | double | {time, vertical} | [molec/cm3] | NO2 local density |
| NO2_number_density_uncertainty | double | {time, vertical} | [molec/cm3] | standard deviation for the NO2 local density |
| NO2_number_density_validity | int16 | {time, vertical} | PCD (product confidence data) value for the NO2 local density | |
| NO3_number_density | double | {time, vertical} | [molec/cm3] | NO3 local density |
| NO3_number_density_uncertainty | double | {time, vertical} | [molec/cm3] | standard deviation for the NO3 local density |
| NO3_number_density_validity | int16 | {time, vertical} | PCD (product confidence data) value for the NO3 local density | |
| O2_number_density | double | {time, vertical} | [molec/cm3] | O2 local density |
| O2_number_density_uncertainty | double | {time, vertical} | [molec/cm3] | standard deviation for the O2 local density |
| O2_number_density_validity | int16 | {time, vertical} | PCD (product confidence data) value for the O2 local density | |
| H2O_number_density | double | {time, vertical} | [molec/cm3] | H2O local density |
| H2O_number_density_uncertainty | double | {time, vertical} | [molec/cm3] | standard deviation for the H2O local density |
| H2O_number_density_validity | int16 | {time, vertical} | PCD (product confidence data) value for the H2O local density | |
| OClO_number_density | double | {time, vertical} | [molec/cm3] | OClO local density |
| OClO_number_density_uncertainty | double | {time, vertical} | [molec/cm3] | standard deviation for the OClO local density |
| OClO_number_density_validity | int16 | {time, vertical} | PCD (product confidence data) value for the OClO local density | |
| aerosol_extinction_coefficient | double | {time, vertical} | [1/km] | aerosol extinction coefficient |
| aerosol_extinction_coefficient_uncertainty | double | {time, vertical} | [1/km] | standard deviation for the aerosol extinction coefficient |
| pressure | double | {time, vertical} | [Pa] | atmospheric pressure from external model |
| temperature | double | {time, vertical} | [K] | temperature |
| temperature_uncertainty | double | {time, vertical} | [K] | standard deviation for the local temperature |
| number_density | double | {time, vertical} | [molec/cm3] | air density |
| number_density_uncertainty | double | {time, vertical} | [molec/cm3] | standard deviation for the local air density |
| number_density_validity | int16 | {time, vertical} | PCD (product confidence data) value for the local air density | |
| sensor_altitude | double | {time, vertical} | [m] | altitude of the satellite |
| sensor_latitude | double | {time, vertical} | [degree_north] | latitude of the satellite position |
| sensor_longitude | double | {time, vertical} | [degree_east] | longitude of the satellite position |
| scene_type | int8 | {time} | illumination condition for the profile; enumeration values: dark (0), bright (1), twilight (2), straylight (3), twilight_straylight (4) | |
| index | int32 | {time} | zero-based index of the sample within the source product |
Ingestion options
The table below lists the available ingestion options for GOMOS_L2
products.
| option name | legal values | description |
|---|---|---|
| temperature | local, model | can be either ‘local’ or ‘model’; ‘local’ (the default) will retrieve the locally measured temperature and ‘model’ will return the temperature from the external model |
| air | local, model | can be either ‘local’ or ‘model’; ‘local’ (the default) will retrieve the locally measured air density and ‘model’ will return the air density from the external model |
Mapping description
GOMOS Level 2 products only contain a single profile; all measured profile points will be provided in reverse order (from low altitude to high altitude) in the profile
The table below details where and how each variable was retrieved from the input product.
| field name | mapping description | |
|---|---|---|
| datetime | path | /nl_geolocation[]/dsr_time |
| description | time of mid record | |
| datetime_start | path | /nl_geolocation[]/dsr_time |
| description | time of first record | |
| datetime_stop | path | /nl_geolocation[]/dsr_time |
| description | time of last record | |
| orbit_index | path | /mph/abs_orbit |
| altitude | path | /nl_geolocation[]/tangent_alt |
| latitude | path | /nl_geolocation[]/tangent_lat |
| longitude | path | /nl_geolocation[]/tangent_long |
| O3_number_density | path | /nl_local_species_density[]/o3 |
| O3_number_density_uncertainty | condition | CODA product version < 2 |
| path | /nl_local_species_density[]/o3_std | |
| description | values equal to 6553.5% will be set to NaN; value will be converted to an uncertainty by multiplying with the absolute value of the measured concentration | |
| condition | CODA product version >= 2 | |
| path | /nl_local_species_density[]/o3_std | |
| description | values equal to 6554 will be set to NaN; value will be converted to an uncertainty by using the log10(v)/0.005 conversion | |
| O3_number_density_validity | path | /nl_local_species_density[]/pcd[0] |
| NO2_number_density | path | /nl_local_species_density[]/no2 |
| NO2_number_density_uncertainty | condition | CODA product version < 2 |
| path | /nl_local_species_density[]/no2_std | |
| description | values equal to 6553.5% will be set to NaN; value will be converted to an uncertainty by multiplying with the absolute value of the measured concentration | |
| condition | CODA product version >= 2 | |
| path | /nl_local_species_density[]/no2_std | |
| description | values equal to 6554 will be set to NaN; value will be converted to an uncertainty by using the log10(v)/0.005 conversion | |
| NO2_number_density_validity | path | /nl_local_species_density[]/pcd[1] |
| NO3_number_density | path | /nl_local_species_density[]/no3 |
| NO3_number_density_uncertainty | condition | CODA product version < 2 |
| path | /nl_local_species_density[]/no3_std | |
| description | values equal to 6553.5% will be set to NaN; value will be converted to an uncertainty by multiplying with the absolute value of the measured concentration | |
| condition | CODA product version >= 2 | |
| path | /nl_local_species_density[]/no3_std | |
| description | values equal to 6554 will be set to NaN; value will be converted to an uncertainty by using the log10(v)/0.005 conversion | |
| NO3_number_density_validity | path | /nl_local_species_density[]/pcd[2] |
| O2_number_density | path | /nl_local_species_density[]/o2 |
| O2_number_density_uncertainty | condition | CODA product version < 2 |
| path | /nl_local_species_density[]/o2_std | |
| description | values equal to 6553.5% will be set to NaN; value will be converted to an uncertainty by multiplying with the absolute value of the measured concentration | |
| condition | CODA product version >= 2 | |
| path | /nl_local_species_density[]/o2_std | |
| description | values equal to 6554 will be set to NaN; value will be converted to an uncertainty by using the log10(v)/0.005 conversion | |
| O2_number_density_validity | path | /nl_local_species_density[]/pcd[4] |
| H2O_number_density | path | /nl_local_species_density[]/h2o |
| H2O_number_density_uncertainty | condition | CODA product version < 2 |
| path | /nl_local_species_density[]/h2o_std | |
| description | values equal to 6553.5% will be set to NaN; value will be converted to an uncertainty by multiplying with the absolute value of the measured concentration | |
| condition | CODA product version >= 2 | |
| path | /nl_local_species_density[]/h2o_std | |
| description | values equal to 6554 will be set to NaN; value will be converted to an uncertainty by using the log10(v)/0.005 conversion | |
| H2O_number_density_validity | path | /nl_local_species_density[]/pcd[5] |
| OClO_number_density | path | /nl_local_species_density[]/oclo |
| OClO_number_density_uncertainty | condition | CODA product version < 2 |
| path | /nl_local_species_density[]/oclo_std | |
| description | values equal to 6553.5% will be set to NaN; value will be converted to an uncertainty by multiplying with the absolute value of the measured concentration | |
| condition | CODA product version >= 2 | |
| path | /nl_local_species_density[]/oclo_std | |
| description | values equal to 6554 will be set to NaN; value will be converted to an uncertainty by using the log10(v)/0.005 conversion | |
| OClO_number_density_validity | path | /nl_local_species_density[]/pcd[6] |
| aerosol_extinction_coefficient | path | /nl_aerosols[]/local_ext |
| aerosol_extinction_coefficient_uncertainty | path | /nl_aerosols[]/local_ext_std |
| description | values equal to 6553.5% will be set to NaN; value will be converted to an uncertainty by multiplying with the absolute value of the measured concentration | |
| pressure | path | /nl_geolocation[]/tangent_atm_p |
| temperature | condition | temperature=local or temperature unset |
| path | /nl_geolocation[]/local_temp | |
| condition | temperature=model | |
| path | /nl_geolocation[]/tangent_temp | |
| temperature_uncertainty | available | optional |
| condition | temperature=local or temperature unset | |
| path | /nl_geolocation[]/local_temp_std | |
| number_density | available | optional |
| condition | air=local or air unset | |
| path | /nl_local_species_density[]/air | |
| condition | air=model and CODA product version > 0 | |
| path | /nl_geolocation[]/tangent_density | |
| number_density_uncertainty | available | optional |
| condition | air=local or air unset and CODA product version < 2 | |
| path | /nl_local_species_density[]/air_std | |
| description | values equal to 6553.5% will be set to NaN; value will be converted to an uncertainty by multiplying with the absolute value of the measured concentration | |
| condition | air=local or air unset and CODA product version >= 2 | |
| path | /nl_local_species_density[]/air_std | |
| description | values equal to 6554 will be set to NaN; value will be converted to an uncertainty by using the log10(v)/0.005 conversion | |
| number_density_validity | available | optional |
| condition | air=local or air unset | |
| path | /nl_local_species_density[]/pcd[3] | |
| sensor_altitude | path | /nl_geolocation[]/tangent_alt |
| sensor_latitude | path | /nl_geolocation[]/lat |
| sensor_longitude | path | /nl_geolocation[]/longit |
| scene_type | condition | CODA product version 0 |
| path | /nl_summary_quality[0]/limb_flag | |
| condition | CODA product version 1 and higher | |
| path | /nl_summary_quality[0]/obs_illum_cond |


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java.lang.Object android.support.v4.app.NavUtils
public class NavUtils
NavUtils provides helper functionality for applications implementing recommended Android UI navigation patterns. For information about recommended navigation patterns see Tasks and Back Stack from the developer guide and Navigation from the design guide.
| Field Summary | |
|---|---|
static java.lang.String |
PARENT_ACTIVITY
|
| Method Summary | |
|---|---|
static Intent |
getParentActivityIntent(Activity sourceActivity)
Obtain an Intent that will launch an explicit target activity
specified by sourceActivity's PARENT_ACTIVITY <meta-data>
element in the application's manifest. |
static Intent |
getParentActivityIntent(Context context,
java.lang.Class<?> sourceActivityClass)
Obtain an Intent that will launch an explicit target activity
specified by sourceActivityClass's PARENT_ACTIVITY <meta-data>
element in the application's manifest. |
static Intent |
getParentActivityIntent(Context context,
ComponentName componentName)
Obtain an Intent that will launch an explicit target activity
specified by sourceActivityClass's PARENT_ACTIVITY <meta-data>
element in the application's manifest. |
static java.lang.String |
getParentActivityName(Activity sourceActivity)
Return the fully qualified class name of sourceActivity's parent activity as specified by a PARENT_ACTIVITY <meta-data> element within the activity element in
the application's manifest. |
static java.lang.String |
getParentActivityName(Context context,
ComponentName componentName)
Return the fully qualified class name of a source activity's parent activity as specified by a PARENT_ACTIVITY <meta-data> element within the activity element in
the application's manifest. |
static void |
navigateUpFromSameTask(Activity sourceActivity)
Convenience method that is equivalent to calling . |
static void |
navigateUpTo(Activity sourceActivity,
Intent upIntent)
Navigate from sourceActivity to the activity specified by upIntent, finishing sourceActivity in the process. |
static boolean |
shouldUpRecreateTask(Activity sourceActivity,
Intent targetIntent)
Returns true if sourceActivity should recreate the task when navigating 'up' by using targetIntent. |
| Methods inherited from class java.lang.Object |
|---|
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Field Detail |
|---|
public static final java.lang.String PARENT_ACTIVITY
| Method Detail |
|---|
public static boolean shouldUpRecreateTask(Activity sourceActivity, Intent targetIntent)
If this method returns false the app can trivially call
navigateUpTo(Activity, Intent)
using the same parameters to correctly perform
up navigation. If this method returns false, the app should synthesize a new task stack
by using TaskStackBuilder
or another similar mechanism to perform up navigation.
sourceActivity
- The current activity from which the user is attempting to navigate uptargetIntent
- An intent representing the target destination for up navigation
public static void navigateUpFromSameTask(Activity sourceActivity)
navigateUpTo
(sourceActivity,
getParentActivityIntent
(sourceActivity))
.
sourceActivity will be finished by this call.
Note: This method should only be used when sourceActivity and the corresponding
parent are within the same task. If up navigation should cross tasks in some cases, see
shouldUpRecreateTask(Activity, Intent)
.
sourceActivity
- The current activity from which the user is attempting to navigate uppublic static void navigateUpTo(Activity sourceActivity, Intent upIntent)
Intent#FLAG_ACTIVITY_CLEAR_TOP
set
by this method, along with any others required for proper up navigation as outlined
in the Android Design Guide.
This method should be used when performing up navigation from within the same task
as the destination. If up navigation should cross tasks in some cases, see
shouldUpRecreateTask(Activity, Intent)
.
sourceActivity
- The current activity from which the user is attempting to navigate upupIntent
- An intent representing the target destination for up navigationpublic static Intent getParentActivityIntent(Activity sourceActivity)
Intent
that will launch an explicit target activity
specified by sourceActivity's PARENT_ACTIVITY
<meta-data>
element in the application's manifest. If the device is running
Jellybean or newer, the android:parentActivityName attribute will be preferred
if it is present.
sourceActivity
- Activity to fetch a parent intent for
public static Intent getParentActivityIntent(Context context, java.lang.Class<?> sourceActivityClass) throws NameNotFoundException
Intent
that will launch an explicit target activity
specified by sourceActivityClass's PARENT_ACTIVITY
<meta-data>
element in the application's manifest.
context
- Context for looking up the activity component for sourceActivityClasssourceActivityClass
- Class
object for an Activity class
NameNotFoundException
- if the ComponentName for sourceActivityClass is invalidpublic static Intent getParentActivityIntent(Context context, ComponentName componentName) throws NameNotFoundException
Intent
that will launch an explicit target activity
specified by sourceActivityClass's PARENT_ACTIVITY
<meta-data>
element in the application's manifest.
context
- Context for looking up the activity component for the source activitycomponentName
- ComponentName for the source Activity
NameNotFoundException
- if the ComponentName for sourceActivityClass is invalidpublic static java.lang.String getParentActivityName(Activity sourceActivity)
PARENT_ACTIVITY
<meta-data> element within the activity element in
the application's manifest.
sourceActivity
- Activity to fetch a parent class name for
public static java.lang.String getParentActivityName(Context context, ComponentName componentName) throws NameNotFoundException
PARENT_ACTIVITY
<meta-data> element within the activity element in
the application's manifest. The source activity is provided by componentName.
context
- Context for looking up the activity component for the source activitycomponentName
- ComponentName for the source Activity
NameNotFoundException
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WITNESS LIST State Affairs Committee March 16, 1999-11:00A SJR 1 ON: Colbert, Paul (Self), Houston Montford, John T. (Self), Lubbock Wisnoski, Joe (Texas Education Agency), Austin Written materials submitted: On: Grusendorf, Bill (The Equity Center), San Saba


current CTC : {{ salary | currency:"INR"}}
The Shiba Inu is the smallest of the six original and distinct spitz breeds of dog from Japan. A small, agile dog that copes very well with mountainous terrain, the Shiba Inu was originally bred for hunting.


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I'm a Systems Engineer and Python developer in love with Django, Docker and Linux.
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pangea.core.views package¶
Submodules¶
pangea.core.views.analysis_result_views module¶
-
class
pangea.core.views.analysis_result_views.
SampleAnalysisResultCreateView
(**kwargs)[source]¶ Bases:
pangea.core.views.utils.PermissionedListCreateAPIView
-
filterset_fields
= ['uuid', 'sample_id', 'module_name', 'replicate']¶
-
permission
¶ alias of
pangea.core.permissions.SampleAnalysisResultPermission
-
permission_classes
= (<class 'rest_framework.permissions.IsAuthenticatedOrReadOnly'>,)¶
-
queryset
¶
-
serializer_class
¶ alias of
pangea.core.serializers.SampleAnalysisResultSerializer
-
-
class
pangea.core.views.analysis_result_views.
SampleAnalysisResultDetailsView
(**kwargs)[source]¶ Bases:
rest_framework.generics.RetrieveUpdateDestroyAPIView
-
permission_classes
= (<class 'pangea.core.permissions.SampleAnalysisResultPermission'>,)¶
-
queryset
¶
-
serializer_class
¶ alias of
pangea.core.serializers.SampleAnalysisResultSerializer
-
-
class
pangea.core.views.analysis_result_views.
SampleAnalysisResultFieldCreateView
(**kwargs)[source]¶ Bases:
pangea.core.views.utils.PermissionedListCreateAPIView
-
filterset_fields
= ['uuid', 'name', 'analysis_result_id']¶
-
permission
¶ alias of
pangea.core.permissions.SampleAnalysisResultFieldPermission
-
permission_classes
= (<class 'rest_framework.permissions.IsAuthenticatedOrReadOnly'>,)¶
-
queryset
¶
-
serializer_class
¶ alias of
pangea.core.serializers.SampleAnalysisResultFieldSerializer
-
-
class
pangea.core.views.analysis_result_views.
SampleAnalysisResultFieldDetailsView
(**kwargs)[source]¶ Bases:
rest_framework.generics.RetrieveUpdateDestroyAPIView
-
permission_classes
= (<class 'pangea.core.permissions.SampleAnalysisResultFieldPermission'>,)¶
-
queryset
¶
-
serializer_class
¶ alias of
pangea.core.serializers.SampleAnalysisResultFieldSerializer
-
-
class
pangea.core.views.analysis_result_views.
SampleGroupAnalysisResultCreateView
(**kwargs)[source]¶ Bases:
pangea.core.views.utils.PermissionedListCreateAPIView
-
filterset_fields
= ['uuid', 'sample_group_id', 'module_name', 'replicate']¶
-
permission
¶ alias of
pangea.core.permissions.SampleGroupAnalysisResultPermission
-
permission_classes
= (<class 'rest_framework.permissions.IsAuthenticatedOrReadOnly'>,)¶
-
queryset
¶
-
serializer_class
¶ alias of
pangea.core.serializers.SampleGroupAnalysisResultSerializer
-
-
class
pangea.core.views.analysis_result_views.
SampleGroupAnalysisResultDetailsView
(**kwargs)[source]¶ Bases:
rest_framework.generics.RetrieveUpdateDestroyAPIView
-
permission_classes
= (<class 'pangea.core.permissions.SampleGroupAnalysisResultPermission'>,)¶
-
queryset
¶
-
serializer_class
¶ alias of
pangea.core.serializers.SampleGroupAnalysisResultSerializer
-
-
class
pangea.core.views.analysis_result_views.
SampleGroupAnalysisResultFieldCreateView
(**kwargs)[source]¶ Bases:
pangea.core.views.utils.PermissionedListCreateAPIView
-
filterset_fields
= ['uuid', 'name', 'analysis_result_id']¶
-
permission
¶ alias of
pangea.core.permissions.SampleGroupAnalysisResultFieldPermission
-
permission_classes
= (<class 'rest_framework.permissions.IsAuthenticatedOrReadOnly'>,)¶
-
queryset
¶
-
serializer_class
¶ alias of
pangea.core.serializers.SampleGroupAnalysisResultFieldSerializer
-
-
class
pangea.core.views.analysis_result_views.
SampleGroupAnalysisResultFieldDetailsView
(**kwargs)[source]¶ Bases:
rest_framework.generics.RetrieveUpdateDestroyAPIView
-
permission_classes
= (<class 'pangea.core.permissions.SampleGroupAnalysisResultFieldPermission'>,)¶
-
queryset
¶
-
serializer_class
¶ alias of
pangea.core.serializers.SampleGroupAnalysisResultFieldSerializer
-
-
pangea.core.views.analysis_result_views.
post_sample_ar_complete_multipart_upload_url
(self, request, *args, **kwargs)[source]¶ Reply with a sample group manifest.
-
pangea.core.views.analysis_result_views.
post_sample_ar_upload_url
(self, request, *args, **kwargs)[source]¶ Reply with a sample group manifest.
pangea.core.views.organization_views module¶
-
class
pangea.core.views.organization_views.
OrganizationCreateView
(**kwargs)[source]¶ Bases:
rest_framework.generics.ListCreateAPIView
-
filterset_fields
= ['uuid', 'name']¶
-
permission_classes
= (<class 'rest_framework.permissions.IsAuthenticatedOrReadOnly'>,)¶
-
queryset
¶
-
serializer_class
¶
-
-
class
pangea.core.views.organization_views.
OrganizationDetailsView
(**kwargs)[source]¶ Bases:
rest_framework.generics.RetrieveUpdateDestroyAPIView
This class handles the http GET, PUT and DELETE requests.
-
permission_classes
= (<class 'pangea.core.permissions.OrganizationPermission'>,)¶
-
queryset
¶
-
serializer_class
¶
-
-
class
pangea.core.views.organization_views.
OrganizationUsersView
(**kwargs)[source]¶ Bases:
rest_framework.generics.ListAPIView
This class handles managing membership of users within organizations.
-
get_serializer_class
()[source]¶ Return the class to use for the serializer. Defaults to using self.serializer_class.
You may want to override this if you need to provide different serializations depending on the incoming request.
(Eg. admins get full serialization, others get basic serialization)
-
permission_classes
= (<class 'rest_framework.permissions.IsAuthenticatedOrReadOnly'>,)¶
-
pangea.core.views.project_views module¶
-
class
pangea.core.views.project_views.
ProjectCreateView
(**kwargs)[source]¶ Bases:
pangea.core.views.utils.PermissionedListCreateAPIView
-
filterset_fields
= ['uuid', 'organization_id', 'name']¶
-
permission
¶
-
permission_classes
= (<class 'rest_framework.permissions.IsAuthenticatedOrReadOnly'>,)¶
-
queryset
¶
-
serializer_class
¶
-
-
class
pangea.core.views.project_views.
ProjectDetailsView
(**kwargs)[source]¶ Bases:
rest_framework.generics.RetrieveUpdateDestroyAPIView
This class handles the http GET, PUT and DELETE requests.
-
permission_classes
= (<class 'pangea.core.permissions.ProjectPermission'>,)¶
-
queryset
¶
-
serializer_class
¶
-
-
class
pangea.core.views.project_views.
ProjectSampleGroupsView
(**kwargs)[source]¶ Bases:
rest_framework.generics.ListAPIView
This class handles managing membership of sample groups within projects.
-
filter_queryset
(queryset)[source]¶ Given a queryset, filter it with whichever filter backend is in use.
You are unlikely to want to override this method, although you may need to call it either from a list view, or from a custom get_object method if you want to apply the configured filtering backend to the default queryset.
-
get_serializer_class
()[source]¶ Return the class to use for the serializer. Defaults to using self.serializer_class.
You may want to override this if you need to provide different serializations depending on the incoming request.
(Eg. admins get full serialization, others get basic serialization)
-
permission_classes
= (<class 'pangea.core.permissions.ProjectPermission'>,)¶
-
queryset
¶
-
pangea.core.views.s3_views module¶
-
class
pangea.core.views.s3_views.
S3ApiKeyCreateView
(**kwargs)[source]¶ Bases:
rest_framework.generics.ListCreateAPIView
-
get_queryset
()[source]¶ Get the list of items for this view. This must be an iterable, and may be a queryset. Defaults to using self.queryset.
This method should always be used rather than accessing self.queryset directly, as self.queryset gets evaluated only once, and those results are cached for all subsequent requests.
You may want to override this if you need to provide different querysets depending on the incoming request.
(Eg. return a list of items that is specific to the user)
-
permission_classes
= (<class 'rest_framework.permissions.IsAuthenticated'>, <class 'pangea.core.permissions.S3ApiKeyPermission'>)¶
-
serializer_class
¶
-
-
class
pangea.core.views.s3_views.
S3ApiKeyDetailsView
(**kwargs)[source]¶ Bases:
rest_framework.generics.RetrieveUpdateDestroyAPIView
-
get_queryset
()[source]¶ Get the list of items for this view. This must be an iterable, and may be a queryset. Defaults to using self.queryset.
This method should always be used rather than accessing self.queryset directly, as self.queryset gets evaluated only once, and those results are cached for all subsequent requests.
You may want to override this if you need to provide different querysets depending on the incoming request.
(Eg. return a list of items that is specific to the user)
-
permission_classes
= (<class 'pangea.core.permissions.S3ApiKeyPermission'>, <class 'rest_framework.permissions.IsAuthenticated'>)¶
-
serializer_class
¶
-
-
class
pangea.core.views.s3_views.
S3BucketCreateView
(**kwargs)[source]¶ Bases:
rest_framework.generics.ListCreateAPIView
-
get_queryset
()[source]¶ Get the list of items for this view. This must be an iterable, and may be a queryset. Defaults to using self.queryset.
This method should always be used rather than accessing self.queryset directly, as self.queryset gets evaluated only once, and those results are cached for all subsequent requests.
You may want to override this if you need to provide different querysets depending on the incoming request.
(Eg. return a list of items that is specific to the user)
-
permission_classes
= (<class 'rest_framework.permissions.IsAuthenticated'>, <class 'pangea.core.permissions.S3BucketPermission'>)¶
-
serializer_class
¶
-
-
class
pangea.core.views.s3_views.
S3BucketDetailsView
(**kwargs)[source]¶ Bases:
rest_framework.generics.RetrieveUpdateDestroyAPIView
-
get_queryset
()[source]¶ Get the list of items for this view. This must be an iterable, and may be a queryset. Defaults to using self.queryset.
This method should always be used rather than accessing self.queryset directly, as self.queryset gets evaluated only once, and those results are cached for all subsequent requests.
You may want to override this if you need to provide different querysets depending on the incoming request.
(Eg. return a list of items that is specific to the user)
-
permission_classes
= (<class 'pangea.core.permissions.S3BucketPermission'>, <class 'rest_framework.permissions.IsAuthenticated'>)¶
-
serializer_class
¶
-
pangea.core.views.sample_group_views module¶
-
exception
pangea.core.views.sample_group_views.
AnalysisResultFieldDownloadError
[source]¶ Bases:
Exception
-
class
pangea.core.views.sample_group_views.
SampleGroupCreateView
(**kwargs)[source]¶ Bases:
pangea.core.views.utils.PermissionedListCreateAPIView
-
filterset_fields
= ['uuid', 'organization_id', 'name', 'is_public']¶
-
permission
¶
-
permission_classes
= (<class 'rest_framework.permissions.IsAuthenticatedOrReadOnly'>,)¶
-
queryset
¶
-
serializer_class
¶
-
-
class
pangea.core.views.sample_group_views.
SampleGroupDetailsView
(**kwargs)[source]¶ Bases:
rest_framework.generics.RetrieveUpdateDestroyAPIView
This class handles the http GET, PUT and DELETE requests.
-
permission_classes
= (<class 'pangea.core.permissions.SampleGroupPermission'>,)¶
-
queryset
¶
-
serializer_class
¶
-
-
class
pangea.core.views.sample_group_views.
SampleGroupSamplesView
(**kwargs)[source]¶ Bases:
rest_framework.generics.ListAPIView
This class handles managing membership of samples within sample groups.
-
filter_queryset
(queryset)[source]¶ Given a queryset, filter it with whichever filter backend is in use.
You are unlikely to want to override this method, although you may need to call it either from a list view, or from a custom get_object method if you want to apply the configured filtering backend to the default queryset.
-
get_serializer_class
()[source]¶ Return the class to use for the serializer. Defaults to using self.serializer_class.
You may want to override this if you need to provide different serializations depending on the incoming request.
(Eg. admins get full serialization, others get basic serialization)
-
permission_classes
= (<class 'rest_framework.permissions.IsAuthenticatedOrReadOnly'>,)¶
-
queryset
¶
-
-
pangea.core.views.sample_group_views.
get_sample_ar_counts_in_group
(self, request, *args, **kwargs)[source]¶ Reply with counts for all types of sample analysis results in the group.
-
pangea.core.views.sample_group_views.
get_sample_data_in_group
(self, request, *args, **kwargs)[source]¶ Reply with metadata for samples in group.
-
pangea.core.views.sample_group_views.
get_sample_group_manifest
(self, request, *args, **kwargs)[source]¶ Reply with a sample group manifest.
-
pangea.core.views.sample_group_views.
get_sample_metadata_in_group
(self, request, *args, **kwargs)[source]¶ Reply with metadata for samples in group.
pangea.core.views.sample_views module¶
-
class
pangea.core.views.sample_views.
SampleCreateView
(**kwargs)[source]¶ Bases:
pangea.core.views.utils.PermissionedListCreateAPIView
-
filterset_fields
= ['uuid', 'library_id', 'name']¶
-
permission
¶
-
permission_classes
= (<class 'rest_framework.permissions.IsAuthenticatedOrReadOnly'>,)¶
-
queryset
¶
-
serializer_class
¶
-
pangea.core.views.utils module¶
-
class
pangea.core.views.utils.
PermissionedListCreateAPIView
(**kwargs)[source]¶ Bases:
rest_framework.generics.ListCreateAPIView
-
filter_queryset
(queryset)[source]¶ Given a queryset, filter it with whichever filter backend is in use.
You are unlikely to want to override this method, although you may need to call it either from a list view, or from a custom get_object method if you want to apply the configured filtering backend to the default queryset.
-


+++ date = "2015-09-01T16:34:27-07:00" title = "NATS Community | Get involved in the NATS Cloud Native Community" cssid = "community" type = "community" description = "NATS is a high performance messaging system that acts as a distributed messaging queue for cloud native applications, IoT device messaging, and microservices architecture." +++
If you’d like to help make NATS and its resources better, here are some ways. Chances are, if you find a feature useful, others will too. This website pulls documentation from GitHub so once you update the readme on GitHub, changes will show up here as well.
The best way to get started contributing to NATS is to read our Contributor's Guide. Here are some examples of how you can contribute:
Please contact us with any other suggestions.
Join NATS Cloud Native Meetup.com Group to receive updates on upcoming meetups.
We work with a variety of companies to ensure NATS is delivered in a broad range of solutions used by our community
The ecosystem of companies using NATS varies from rapidly growing startups to some of the largest companies in the world.
Social


Treetable's height, by default, is dynamic - determined by the content. Restricting the height can be done by
providing the
bodyStyle
object containing the height
attribute
(or max-height
if body needs to shirnk in absence of records):
If defined, treetable will populate parent element's height (even though no enough data is present to populate that height).
examples and docs for scrolling nested tables using max-height attribute..
Horizontal scrolling can be enabled with 'expand' resize mode.


3. What do I do if it all goes wrong?
Tell Norm<EMAIL_ADDRESS>There is also an XProc developers mailing list<EMAIL_ADDRESS>which may provide useful advice.
Tell Norm<EMAIL_ADDRESS>There is also an XProc developers mailing list<EMAIL_ADDRESS>which may provide useful advice.


typealias SgfNode = MutableList<SgfProperty<SgfType>>
Representation of the SGF Node, which is a list of Propertys.
SGF Node
Property