|
|
| config_value_reader (const config_value *input, actor_system &sys) |
| |
|
| config_value_reader (const config_value *input, execution_unit *ctx) |
| |
|
| config_value_reader (const config_value *input) |
| |
|
| config_value_reader (const config_value_reader &)=delete |
| |
|
config_value_reader & | operator= (const config_value_reader &)=delete |
| |
|
value_type & | top () |
| |
|
void | pop () |
| |
| bool | fetch_next_object_type (type_id_t &type) override |
| | Reads run-time-type information for the next object if available.
|
| |
| bool | begin_object (type_id_t type, string_view name) override |
| | Begins processing of an object, may perform a type check depending on the data format.
|
| |
| bool | end_object () override |
| | Ends processing of an object.
|
| |
| bool | begin_field (string_view) override |
| |
| bool | begin_field (string_view name, bool &is_present) override |
| |
| bool | begin_field (string_view name, span< const type_id_t > types, size_t &index) override |
| |
| bool | begin_field (string_view name, bool &is_present, span< const type_id_t > types, size_t &index) override |
| |
| bool | end_field () override |
| |
| bool | begin_tuple (size_t size) override |
| | Begins processing of a fixed-size sequence.
|
| |
| bool | end_tuple () override |
| | Ends processing of a sequence.
|
| |
| bool | begin_key_value_pair () override |
| | Begins processing of a tuple with two elements, whereas the first element represents the key in an associative array.
|
| |
| bool | end_key_value_pair () override |
| | Ends processing of a key-value pair after both values were written.
|
| |
| bool | begin_sequence (size_t &size) override |
| | Begins processing of a sequence.
|
| |
| bool | end_sequence () override |
| | Ends processing of a sequence.
|
| |
| bool | begin_associative_array (size_t &size) override |
| | Begins processing of an associative array (map).
|
| |
| bool | end_associative_array () override |
| | Ends processing of an associative array (map).
|
| |
| bool | value (byte &x) override |
| | Reads x from the input.
|
| |
| bool | value (bool &x) override |
| | Reads x from the input.
|
| |
| bool | value (int8_t &x) override |
| | Reads x from the input.
|
| |
| bool | value (uint8_t &x) override |
| | Reads x from the input.
|
| |
| bool | value (int16_t &x) override |
| | Reads x from the input.
|
| |
| bool | value (uint16_t &x) override |
| | Reads x from the input.
|
| |
| bool | value (int32_t &x) override |
| | Reads x from the input.
|
| |
| bool | value (uint32_t &x) override |
| | Reads x from the input.
|
| |
| bool | value (int64_t &x) override |
| | Reads x from the input.
|
| |
| bool | value (uint64_t &x) override |
| | Reads x from the input.
|
| |
| bool | value (float &x) override |
| | Reads x from the input.
|
| |
| bool | value (double &x) override |
| | Reads x from the input.
|
| |
| bool | value (long double &x) override |
| | Reads x from the input.
|
| |
| bool | value (std::string &x) override |
| | Reads x from the input.
|
| |
| bool | value (std::u16string &x) override |
| | Reads x from the input.
|
| |
| bool | value (std::u32string &x) override |
| | Reads x from the input.
|
| |
| bool | value (span< byte > x) override |
| | Reads a byte sequence from the input.
|
| |
|
| deserializer (actor_system &sys) noexcept |
| |
|
| deserializer (execution_unit *ctx=nullptr) noexcept |
| |
|
auto | context () const noexcept |
| |
|
bool | has_human_readable_format () const noexcept |
| |
| virtual bool | fetch_next_object_type (type_id_t &type)=0 |
| | Reads run-time-type information for the next object if available.
|
| |
| virtual bool | fetch_next_object_name (string_view &type_name) |
| | Reads run-time-type information for the next object if available.
|
| |
|
bool | next_object_name_matches (string_view type_name) |
| | Convenience function for querying fetch_next_object_name comparing the result to type_name in one shot.
|
| |
|
bool | assert_next_object_name (string_view type_name) |
| | Like next_object_name_matches , but sets an error on the deserializer on a mismatch.
|
| |
| virtual bool | begin_object (type_id_t type, string_view pretty_class_name)=0 |
| | Begins processing of an object, may perform a type check depending on the data format.
|
| |
| virtual bool | end_object ()=0 |
| | Ends processing of an object.
|
| |
|
virtual bool | begin_field (string_view name)=0 |
| |
|
virtual bool | begin_field (string_view, bool &is_present)=0 |
| |
|
virtual bool | begin_field (string_view name, span< const type_id_t > types, size_t &index)=0 |
| |
|
virtual bool | begin_field (string_view name, bool &is_present, span< const type_id_t > types, size_t &index)=0 |
| |
|
virtual bool | end_field ()=0 |
| |
| virtual bool | begin_tuple (size_t size)=0 |
| | Begins processing of a fixed-size sequence.
|
| |
| virtual bool | end_tuple ()=0 |
| | Ends processing of a sequence.
|
| |
| virtual bool | begin_key_value_pair () |
| | Begins processing of a tuple with two elements, whereas the first element represents the key in an associative array.
|
| |
| virtual bool | end_key_value_pair () |
| | Ends processing of a key-value pair after both values were written.
|
| |
| virtual bool | begin_sequence (size_t &size)=0 |
| | Begins processing of a sequence.
|
| |
| virtual bool | end_sequence ()=0 |
| | Ends processing of a sequence.
|
| |
| virtual bool | begin_associative_array (size_t &size) |
| | Begins processing of an associative array (map).
|
| |
| virtual bool | end_associative_array () |
| | Ends processing of an associative array (map).
|
| |
| virtual bool | value (byte &x)=0 |
| | Reads x from the input.
|
| |
| virtual bool | value (bool &x)=0 |
| | Reads x from the input.
|
| |
| virtual bool | value (int8_t &)=0 |
| | Reads x from the input.
|
| |
| virtual bool | value (uint8_t &)=0 |
| | Reads x from the input.
|
| |
| virtual bool | value (int16_t &)=0 |
| | Reads x from the input.
|
| |
| virtual bool | value (uint16_t &)=0 |
| | Reads x from the input.
|
| |
| virtual bool | value (int32_t &)=0 |
| | Reads x from the input.
|
| |
| virtual bool | value (uint32_t &)=0 |
| | Reads x from the input.
|
| |
| virtual bool | value (int64_t &)=0 |
| | Reads x from the input.
|
| |
| virtual bool | value (uint64_t &)=0 |
| | Reads x from the input.
|
| |
| template<class T > |
| std::enable_if_t< std::is_integral< T >::value, bool > | value (T &x) noexcept |
| | Reads x from the input.
|
| |
| virtual bool | value (float &)=0 |
| | Reads x from the input.
|
| |
| virtual bool | value (double &)=0 |
| | Reads x from the input.
|
| |
| virtual bool | value (long double &)=0 |
| | Reads x from the input.
|
| |
| virtual bool | value (std::string &)=0 |
| | Reads x from the input.
|
| |
| virtual bool | value (std::u16string &)=0 |
| | Reads x from the input.
|
| |
| virtual bool | value (std::u32string &)=0 |
| | Reads x from the input.
|
| |
| virtual bool | value (span< byte > x)=0 |
| | Reads a byte sequence from the input.
|
| |
| virtual bool | list (std::vector< bool > &xs) |
| | Adds each boolean in xs to the output.
|
| |
Extracts objects from a config_value.


FOODS
Description: {{currentMenuItemIngredient.ingredientDescription}}
Update
Delete
Add Food
Search Foods


| CS 111 - Introduction to Computer Science
Homework #10 |
1. Dice Histogram: Call your class DiceHistogram.java. In this exercise, you will simulate the throwing of 2 standard six-sided dice a given number of times and display the resulting distribution as a text-based histogram. First, ask the user how many time to roll the dice. Then simulate the dice rolling and print the maximum number of times a sum was rolled. Next print lines for each possible dice roll showing a number of asterisks proportional to the number of times the sum was rolled. Scale the number of asterisks such that the sum rolled the most will have 60 asterisks. Example transcript (user input underlined):
How many rolls? 1000000 Max count: 166039 2 ********** 3 ******************** 4 ****************************** 5 **************************************** 6 ************************************************** 7 ************************************************************ 8 ************************************************** 9 **************************************** 10 ****************************** 11 ******************** 12 *********
Possible "stepping stones" towards the goal: (1) Print the given number of roll sums. Remember: The sum of two 6-sided dice is different than a single roll of an 11-sided die numbered 2 through 12. (Why?) (2) Use an array to count the number of rolls for each sum and print a table (i.e. numbers instead of histogram asterisks above). (3) Compute and print the maximum count. (4) Round (60.0 * count / maximum) for each count to compute the number of asterisks, and print the histogram as shown.
2. ChompGame: Chomp is a Nim-type game in which two players take bites of a gridded cookie in turn. Each bite at a given row and column consumes the cookie at, below, and to the right of that position. The player taking the last bite in the first row and first column loses.
Implement ChompGame.java according to this specification. This class will model the game, and could serve as a basis for a text-based game interface (next exercise), a graphical user interface (GUI), game simulation for analysis/machine learning, etc. No scanning of input or printing of output will take place in this class, so you'll need another class (see next exercise) to effectively test this code.
Chomp Resources:
3. Chomp: For this exercise, design and implement Chomp.java
according to this specification such that two
players can play a text-based version of chomp for a given board size up to at
least size 10-by-10. Use class ChompGame for modeling the game state itself. All
input/output for text-based play should take place in the main method of this class.
First, print instructions with the following lines: {"CHOMP", "In the game of Chomp, players bite a rectangular cookie in turn.", "The player chomping the last bite (0,0) loses.", "Each chomp, a row and column, bites off all below and to the right."}. Then prompt the user for the number of rows and columns with prompts "Rows? " and "Columns? ". Read these in as integers presumed to be in the range 1-10. Create a ChompGame object using this information.
Then, while the game is not over, do the following: Print the game board produced by the object toString() and preceded and
followed with blank lines. Prompt the user for a row and column for
chomping with "Player # chomp? ", where "#" is the games current player number. Attempt the chomp move, making the move and changing the player if the chomp
move is legal, and just printing the message "That is not a legal chomp
position." otherwise.
After the game is over, print a blank line and the
message "Player # wins!", where "#" is the winning player.
No input/output should take place in class Chomp. Whenever possible, use the computation of the Chomp class to perform the modeling (i.e. play, logic) of the game.
Example transcript (input underlined):
CHOMP In the game of Chomp, players bite a rectangular cookie in turn. The player chomping the last bite (0,0) loses. Each chomp, a row and column, bites off all below and to the right. Rows? 3 Columns? 5 01234 0***** 1***** 2***** Player 1 chomp? 1 4 01234 0***** 1**** 2**** Player 2 chomp? 2 1 01234 0***** 1**** 2* Player 1 chomp? 0 1 01234 0* 1* 2* Player 2 chomp? 1 0 01234 0* 1 2 Player 1 chomp? -1 0 That is not a legal chomp position. 01234 0* 1 2 Player 1 chomp? 0 5 That is not a legal chomp position. 01234 0* 1 2 Player 1 chomp? 1 1 That is not a legal chomp position. 01234 0* 1 2 Player 1 chomp? 0 0 Player 2 wins!


Hax Development Quick Start
If you want to work on individual components inside hax you need to link the node_modules folders.
cd HAXcms/
# link node_modules directory to your clone of lrnwebcomponents
ln -s ../lrnwebcomponents/node_modules/
If you want to see your element changes in a haxcms site we need to setup some sym links to the haxcms directory.
cd sites/my-site/
# link dist, build, and node_modules
ln -s ../../dist/
ln -s ../../build/
ln -s ../../node_modules/
Include HAX in your project
The developers docs will lay out the many specifications that make HAX possible including core concepts, different schema's it leverages ad how to define app store spec in order to take integrations further.
# get the code
npm install --save @lrnwebcomponents/h-a-x
yarn add @lrnwebcomponents/h-a-x
# reference it in your project
import<EMAIL_ADDRESS># use it in your template with an appstore definition if you like
< h-a-x >
Now this paragraph is editable
< / h-a-x >
Uhh, is that it?
Yeah, that's it. Behold the power of a thousand open source suns raining down all their hate on the editors of the past and their complex integrations or ecosystem lock in.


--- layout: post title: Peplum storyboard date: '2015-01-28T07:30:35+01:00' categories: - Storyboards - Horses picture_url: https://film-Storyboards.tumblr.com/post/109389824373 ---


Glossary
The following are selected terms relevant to the Oracle Database implementation of RDF Semantic Graph support. This is not a comprehensive RDF and OWL glossary.
apply pattern
Part of a data access constraint defines additional graph patterns to be applied on the resources that match the match pattern before they can be used to construct the query results. See also: match pattern
basic graph pattern (BGP)
A set of triple patterns. From the W3C SPARQL Query Language for RDF Recommendation: "SPARQL graph pattern matching is defined in terms of combining the results from matching basic graph patterns. A sequence of triple patterns interrupted by a filter comprises a single basic graph pattern. Any graph pattern terminates a basic graph pattern."
clique
A graph in which every node of it is connected to, bidirectionally, every other node in the same graph.
Cytoscape
An open source bioinformatics software platform for visualizing molecular interaction networks and integrating these interactions with gene expression profiles and other state data. (See http://www.cytoscape.org/
.) An RDF viewer (available for download) is provided as a Cytoscape plug-in.
entailment
An object containing precomputed triples that can be inferred from applying a specified set of rulebases to a specified set of models. See also: rulebase
extractor policy
A named dictionary entity that determines the characteristics of a semantic index that is created using the policy. Each extractor policy refers, directly or indirectly, to an instance of an extractor type.
graph pattern
A combination of triples constructed by combining triple patterns in various ways, including conjunction of triple patterns into groups, optionally using filter conditions, and then combining such groups using connectors similar to disjunctions, outer-joins, and so on. SPARQL querying is based around graph pattern matching.
inferencing
The ability to make logical deductions based on rules. Inferencing enables you to construct queries that perform semantic matching based on meaningful relationships among pieces of data, as opposed to just syntactic matching based on string or other values. Inferencing involves the use of rules, either supplied by Oracle or user-defined, placed in rulebases.
information extractor
An application that processes unstructured documents and extract meaningful information from them, often using natural-language processing engines with the aid of ontologies.
match pattern
Part of a constraint that determines the type of access restriction it enforces and binds one or more variables to the corresponding data instances accessed in the user query. See also: apply pattern
model
A user-created semantic structure that has a model name, and refers to triples stored in a specified table column. Examples in this manual are the Articles and Family models.
ontology
A shared conceptualization of knowledge in a particular domain. It consists of a collection of classes, properties, and optionally instances. Classes are typically related by class hierarchy (subclass/ superclass relationship). Similarly, the properties can be related by property hierarchy (subproperty/ superproperty relationship). Properties can be symmetric or transitive, or both. Properties can also have domain, ranges, and cardinality constraints specified for them.
OWLPrime
An Oracle-defined subset of OWL capabilities; refers to the elements of the OWL standard supported by the RDF Semantic Graph native inferencing engine.
RDF Semantic Graph support for Apache Jena
An Oracle-supplied adapter (available for download) for Apache Jena, which is a Java framework for building Semantic Web applications.
semantic index
An index of type MDSYS.SEMCONTEXT, created on textual documents stored in a column of a table, and used with information extractors to locate and extract meaningful information from unstructured documents. See also: information extractor
Simple Knowledge Organization System (SKOS)
A data model that is especially useful for representing thesauri, classification schemes, taxonomies, and other types of controlled vocabulary. SKOS is based on standard semantic web technologies including RDF and OWL, which makes it easy to define the formal semantics for those knowledge organization systems and to share the semantics across applications.
triple pattern
Similar to an RDF triple, but allows use of a variable in place of any of the three components (subject, predicate, or object). Triple patterns are basic elements in graph patterns used in SPARQL queries. A triple pattern used in a query against an RDF graph is said to match if, substitution of RDF terms for the variables present in the triple pattern, creates a triple that is present in the RDF graph. See also: graph pattern


This is a record of one player's experience of No Man's Sky! It will be a combination of screenshots, recordings, and descriptions of events, encounters, and amazing vistas seen while playing. If you don't know what No Man's Sky is, check out the developer's own explanation below:
Description
No Man’s Sky is a game about exploration and survival in an infinite procedurally generated galaxy.
History
No Man's Sky has been in our heads for a very long time. In fact, it has its roots in Sean Murray's experiences growing up on a ranch in the Australian outback. It was the true middle of nowhere, where if something went wrong you were told to just stay where you were and light a fire at an exact time every day, and hope that someone would find you. The night sky was filled with more stars than you’ve ever seen, and we've all thought that this is exactly where videogames would go, videogames that contained the whole universe, and you’d be able to visit it all. No Man's Sky takes that jump - it's the game we've always wanted to make.
Features
- A TRULY OPEN UNIVERSE If you can see it, you can go there. You can fly seamlessly from the surface of a planet to another, and every star in the sky is a sun that you can visit.
- EXPLORATION IS SEEING THINGS THAT NO-ONE ELSE HAS EVER SEEN BEFORE Every creature, geological formation, plant and spaceship is unique.
- SURVIVE ON A DANGEROUS FRONTIER You are alone and vulnerable, and will face threat everywhere, from deep space to thick forests, barren deserts to dark oceans.
- BUILD FOR AN EPIC JOURNEY Collect precious materials and trade them for better spacecraft and upgrades for your suit and equipment and prepare for your journey to the centre of the galaxy.
- A SHARED UNIVERSE Choose to share with other players your discoveries on a map of the galaxy. Strike out for unexplored frontiers or build your strengths in known space.
- 65DAYSOFSTATIC SOUNDTRACK Our favourite band, 65daysofstatic, is producing a soundtrack album especially for No Man's Sky, which will be featured in the game as a procedurally generated soundscape.


--- layout: default title: "Security Concerns Initiate Move To New Servers" author: name: Jon Cram url: http://webignition.net ---
We recently upgraded to the latest verion of cPanel to address some potential security concerns. This is a regular preventative measure to ensure that the cPanel software is as secure as it currently can be.
We subsequently discovered we were unable to upgrade some server software due to our systems being a little old. This presents no immediate problems but will eventually.
In order to ensure we can continue to apply all necessary security updates, we've decided to move to fresh, new hosting servers.
As a consequence of moving to new hardware, all of our hosting servers will be upgraded to feature:
Still the same number of processor cores, but with more processing power.
4 times the amount of RAM, an increase from 8GB per server.
Twice the current data throughput, up from 100 Mbit.
We've already provisioned new hosting servers and these are in the process of having all the relevant pieces of server software installed.
When ready, we'll first move our own hosting accounts over to new new servers and check that all is working as expected.
We will then be ready to move all user accounts to the new systems. We'll post regular updates regarding how this is going and will be in touch via email if we have any specific concerns or if there is anything specific that you need to do.


manifests.Rmd
Most of the examples in the accesstocare
package can be deployed to RStudio Connect by using the RStudio IDE’s button push deployment. All of the examples are designed to be deployed using RStudio Connect’s Git Backed Deployment. This means that we tell RStudio Connect where the code repository exists, and then have RStudio Connect download the latest code everytime the repository is updated.
A major step to accomplish this, is to have a “manifest” file. It contains the metadata of the example, such as package versions, R version, primary file, etc. It is produced using the rsconnect
package. In accesstocare
, there are two utility functions to make it easier to create the manifest files.
There are two functions included in accesstocare
to help with creating the manifests:
atc_write_manifest()
creates the manifest for a single exampleatc_write_all_manifests()
batch creates all of the manifestsWe will the fs
package to make it easy to see the changes in the directories.
For the usage examples, we will copy all of the accesstocare
examples into a temporary folder.
temp_folder <- path(tempdir(), "temp")
atc_copy_all_content(temp_folder, silent = TRUE)
To show how to create the manifest of a single example, we will point to the “flexdashboard” sub-folder. The atc_copy_all_content()
command created that sub-folder.
/var/folders/l8/v1ym1mc10_b0dftql5wrrm8w0000gn/T/RtmpBkacCE/temp/flexdashboard
├── access-to-care.Rmd
└── metadata.yml
The folder contains the example, a metadata.yml
, and a .gitignore
file.
Now, we run create the manifest using atc_write_manifest()
. The function will automatically identify the primary document, and process the files listed in.gitignore
file.
atc_write_manifest(dashboard_path)
Full path: /var/folders/l8/v1ym1mc10_b0dftql5wrrm8w0000gn/T/RtmpBkacCE/temp/flexdashboard
Application files
--- access-to-care.Rmd
--- metadata.yml
Primary file: access-to-care.Rmd
Compiling manifest...
Manifest complete
/var/folders/l8/v1ym1mc10_b0dftql5wrrm8w0000gn/T/RtmpBkacCE/temp/flexdashboard/manifest.json
The manifest.json
file is now available in the sub-folder.
dir_tree(dashboard_path)
/var/folders/l8/v1ym1mc10_b0dftql5wrrm8w0000gn/T/RtmpBkacCE/temp/flexdashboard
├── access-to-care.Rmd
├── manifest.json
└── metadata.yml
To create the manifests for all of the sub-folders, use atc_write_all_manifests()
. This function will silently run the manifest writer for each sub-folder. For those that it fails for, it skips the creation. The function returns a list
object with all of the results. Printing the object on the R Console shows which were skipped, and which were created.
atc_write_all_manifests(temp_folder)
# A tibble: 16 × 2
content created
<chr> <chr>
1 RMarkdown-DataPrep YES
2 RMarkdown-html YES
3 RMarkdown-pdf YES
4 RNotebook YES
5 connectwidgets YES
6 dash YES
7 flexdashboard YES
8 htmlwidgets SKIPPED
9 jupyter YES
10 launcher-programatic YES
11 plot SKIPPED
12 plumber-api YES
13 powerpoint YES
14 powerpoint-state YES
15 presentation YES
16 shiny YES


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JavaScript is used increasingly to provide a native-like application experience in the web. One major avenue of this has been in the use of Single Page Applications or SPAs. SPAs are generated, rendered, and updated using JavaScript. Because SPAs don’t require a user to navigate away from a page to do anything, they retain a degree of user and application state.
There are millions of websites that utilise SPAs in part of, or all of their web applications.
The assignment intends to teach students to build a simple SPA which can fetch dynamic data from a HTTP/S API. Your task will be to provide an implemention of an SPA that can provide a number of key features.
Some of the skills/concepts this assignment aims to test (and build upon):
The backend server will be where you’ll be getting your data. Don’t touch the code in the backend; although we’ve provided the source,
it’s meant to be a black box. Final testing will be done with our own backend. Use the instructions provided in the backend/README.m
d
to get it started.
For the full docs on the API, start the backend server and navigate to the root (localhost:5000
). You’ll see
all the endpoints, descriptions and expected responses.
Your site should be compatible with ‘modern’ Chrome, Safari, and Mozilla browsers. We will assume your browser has JavaScript enabled, and supports ES6 syntax.
Clone the gitlab repository using the instructions below. It has a code, full documentation, and a working server you’ll need for developing your frontend application.
Please read the relevant docs for setup in the folders backend/
and frontend/
of the provided repository.
Each folder outlines basic steps to get started. There are also some comments provided in the frontend source code.
Level 0 focuses on the basic user interface and interaction building of the site. There is no need to implement any integration with the backend for this level.
Login The site presents a login form and a user can log in with pre-defined hard coded credentials. You can use the provided users.json so you can create a internal non persistent list of users that you check against.
Once logged in, the user is presented with the home page which for now can be a blank page with a simple “Not Yet implemented” message.
Registration An option to register for “Instacram” is presented on the login page allowing the user to sign up to the service. This for now updates the internal state object described above.
Feed Interface
The application should present a “feed” of user content on the home page derived from the sample feed.json provided. The posts should be displayed in reverse chronological order (most recent posts first). You can hardcode how this works for this milestone.
Although this is not a graphic design exercise you should produce pages with a common and somewhat distinctive look-and-feel. You may find CSS useful for this.
Each post must include:
Level 1 focuses on fetching data from the API.
Login
The site presents a login form and verifies the provided credentials with the backend (POST /login
). Once logged in, the user can see the home page.
Registration
An option to register for “Instacram” is presented allowing the user to sign up to the service. The user information is POSTed to the backend to create the user in the database. (POST /signup
)
Feed Interface
The content shown in the user’s feed is sourced from the backend. (GET /user/feed
)
Level 2 focuses on a richer UX and will require some backend interaction.
Show Likes Allow an option for a user to see a list of all users who have liked a post. Possibly a modal but the design is up to you.
Show Comments Allow an option for a user to see all the comments on a post. Same as above.
Like user generated content
A logged in user can like a post on their feed and trigger an API request (PUT /post/like
)
For now it’s ok if the like doesn’t show up until the page is refreshed.
Post new content
Users can upload and post new content from a modal or seperate page via (POST /post
)
Pagination
Users can page between sets of results in the feed using the position token with (GET user/feed
).
Note users can ignore this if they properly implement Level 3’s Infinite Scroll.
Profile
Users can see their own profile information such as username, number of posts, sum of likes they received on all their posts, etc.
You may choose to utilise the information from the api in more creative ways such as displaying their most liked post etc.
Get this information from (GET /user
)
Level 3 focuses on more advanced features that will take time to implement and will involve a more rigorously designed app to execute.
Infinite Scroll Instead of pagination, users can infinitely scroll through results. For infinite scroll to be properly implemented you need to progressively load posts as you scroll.
Comments
Users can write comments on “posts” via (POST post/comment
)
Live Update If a user likes a post or comments on a post, the posts likes and comments should update without requiring a page reload/refresh.
Update Profile
Users can update their personal profile via (PUT /user
) E.g:
User Pages Let a user click on a user’s name/picture from a post and see a page with the users name, and other info. The user should also see on this page all posts made by that person. The user should be able to see their own page as well.
This can be done as a modal or as a seperate page (URL fragmentation can be implemented if desired.)
Follow
Let a user follow/unfollow another user to add/remove their posts to their feed via (PUT user/follow
)
Add a list of everyone a user follows in their profile page.
Add just the count of followers / follows to everyones public user page
To allow users to find other users implement some functionality to check if a username exists and allow the user to follow them. This may be as simple as a text box in the navbar which signals when a inputted username is wrong or if it's right gives you a option to follow the user. You do not need to implement anything more advanced such as searching etc.
Delete/Update Post
Let a user update a post they made or delete it via (DELETE /post
) or (PUT /post
)
Slick UI The user interface looks good, is performant, makes logical sense, and is usable.
Push Notifications Users can receive push notifications when a user they follow posts an image.
Offline Access Users can access the “Instacram” at all times by using Web Workers to cache the page (and previous content) locally.
Fragment based URL routing Users can access different pages using URL fragments:
/#profile=me
/#feed
/#profile=janecitizen
Don't panic this is easy to do and will ensure you have a complete backup of all work on your assignment and can return to its state at any stage.
It will also allow your tutor to check you are progressing on the assignment as they can access your gitlab repository
cat ~/.ssh/id_rsa.pub ssh-rsa AAAAB3NzaC1yc2EAAAABIwAAAQEAyNSzIDylSPAAGLzUXdw359UhO+tlN6wWprSBc9gu6t3IQ1rvHhPoD6wcRXnonY6ytb00GpS4XRFuhCghx2JNVkXFykJYt3XNr1xkPItMmXr/DRIYrtxTs5sn9el3hHZIgELY8jJZpgIo303kgnF0MsB7XpqCzg7Iv6JGkv7aEoYC/MNr07hXE8iQjYIHDMdO9HxGI80GyMqb1hF+RSpQTNvXQvH56juu9VXt5OwJjOqSVa4SfsEICqdn+3k9w8Z4EaD93Eeog3hz0RoTrme8h/sJenXydJ0w9ZOs0By4fjqKFYPsYEs1K6SHma+kPByZM9COgKHZwOZHH1m24HOITQ== z5555555@williams
ssh-keygen Generating public/private rsa key pair. Enter file in which to save the key (/import/kamen/3/z5555555/.ssh/id_rsa): Created directory '/import/kamen/3/z5555555/.ssh'. Enter passphrase (empty for no passphrase): Enter same passphrase again: Your identification has been saved in /import/kamen/3/z5555555/.ssh/id_rsa. Your public key has been saved in /import/kamen/3/z5555555/.ssh/id_rsa.pub. The key fingerprint is: b8:02:31:8b:bf:f5:56:fa:b0:1c:36:89:ad:e1:cb:ad z5555555@williams The key's randomart image is: ...
cat ~/.ssh/id_rsa.pub
) into the "Key" field.
Don't cut-and paste z5555555's ssh key above - cut-and-paste your ssh-key!
A repository has been created for your assignment on gitlab.cse.unsw.edu.au
.
You need to add your CSE ssh key to your gitlab.cse.unsw.edu.au
.
After you have done that create a git repository for the assignment in your CSE account.
These commands will create a copy of the gitlab repository in your CSE account.
Make sure you replace 5555555 below by your student number!
mkdir -m 700 -p ~/ass2 cd ~/ass2 git clone gitlab@gitlab.cse.unsw.EDU.AU:z5555555/18s2-comp2041-ass2 . Cloning into '.'... ....If the git clone above fails - redo the instructions above for adding your ssh key to gitlab.
 Username for 'https://gitlab.cse.unsw.edu.au': z5555555 Password for<EMAIL_ADDRESS>vi frontend/main.js git commit -a -m 'bugs in subset 0 fixed' git push .... vi frontend/my.js git add frontend/my.js git commit -a -m 'initial version of subset 1' git push
gitlab.cse.unsw.edu
(see above).
You must implement this assignment in Javascript.
You may use small amounts (< 10 lines) of general purpose code (not specific to the assignment) obtained from a site such as Stack Overflow or other publically available resources. You should attribute clearly the source of this code in a comment with it.
You can not otherwise use code written by another person.
Do not use NPM to install libraries other than as indicated in the specifcation.
You can not, for example, use the popular Javascript framework such as Angular or React.
You are permitted to use CSS from external sources as long as it properly attributed.
For example, you are permitted to use the popular Bootstrap CSS framework.
Some Bootstrap functionality relies on accompanying Javascript. You are permitted to include this Javascript.
The Javascript accompanying Bootstrap requires the popular general purpose Javascrpt library jQuery. You are permitted to include jQuery so bootstrap can use it. However you are not permitted to use jQuery in the code you write for the assignment.
This is an individual assignment. The work you submit must be your own work and only your work apart from the exception above. Joint work is not permitted.
You should follow discussion about the assignment in the course forum. All questions about the assignment should be posted there unless they concern your private circumstances. This allows all students to see all answers to questions.
| Date | Start | Stop | Activity | Comments |
|---|---|---|---|---|
| 15/10 | 16:00 | 17:30 | coding | implemented creation of accounts |
| 20/10 | 20:00 | 10:30 | debugging | found bug in handling of posts |
Some students choose to store this information in git commit messages
and use a script to generate diary.txt
from git log
before they submit.
You are welcome to do this.
Joint work is not permitted.
You are only permitted to request help with the assignment in the course forum, help sessions or from course lecturers or tutors.
Do not provide or show your assignment work to any other person (including by posting it on the forum) apart from the teaching staff of COMP[29]041.
The work you submit must otherwise be entirely your own work. Submission of work partially or completely derived from any other person or jointly written with any other person is not permitted. The penalties for such an offence may include negative marks, automatic failure of the course and possibly other academic discipline. Assignment submissions will be examined both automatically and manually for such submissions.
We are required to inform scholarship authorities if students holding scholarships are involved in an incident of plagiarism or other misconduct, and this may result in a loss of the scholarship.
Plagiarism or other misconduct can also result in loss of student visas.
If you knowingly provide or show your assignment work to another person for any reason, and work derived from it is submitted you may be penalized, even if the work was submitted without your knowledge or consent. This may apply even if your work is submitted by a third party unknown to you.
Note, you will not be penalized if your work is taken without your consent or knowledge.
tar -Jcf files.tar --exclude node_modules frontend give cs2041 ass2_instacram diary.txt files.tarYou can't submit the backend because you are not permitted to change the backend. Your frontend will be run with the backend you have been given. Please do not include the folder
node_modules
in this tar as the
folder contains package information and is usually quite large.
Unlike the last assignment you don't need to run give everytime you work on the assignment, you do need to run git push very time your work on the assignment, so your repo on gitlab.cse.unsw.edu.au is updated.
You may still run give multiple times, only the final submitted version of your assignment will be marked.
Assignment 2 has been reduced in scope because it is late being released. Given this, and the large amount of work most students did on assignment 1, instead assignment 1 will contribute 20 marks to your final mark and assignment 2 will contribute 10 marks.
However to ensure students can not be disadvantaged by this late change, we will also calculate your final mark with the original assignment weighting (15 marks each) and if this result in a better overall mark for you we will use the original assignment weighting.
Assignment 2 marking occurs in peer assessment sessions. Details of the peer assessment sessions will be announced in week 13. Your must attend one peer assessment sessions.
80% of the marks for assignment 2 will come from your code against a specified set of operations and assessed by fellow students. You will be present to assist in determining what features are and are not working, you will also be able to indicate any extra features you have implemented.
20% of the marks for assignment 2 will be awarded on the basis of clarity, commenting, elegance and style of your code. In other words, your fellow students will assess how easy it is for a human to read and understand your program.
Here is an indicative marking scheme .
| 100% | Elegant Javascript with an excellent implementation of levels 0-4) features |
| HD++% | Very well written Javascript which implements levels 0-3 successfully |
| HD (85+) | Well written Javascript which implements most of levels 0-3 successfully |
| DN (75+) | Readable Javascript which implements of levels 0-2 successfully |
| CR (65+) | Reasonably readable code which implements level 0-1 successfully |
| PS (55+) | Reasonably readable code which implements level 0 successfully |
| 45% | Major progress on the assignment with some things working/almost working |
| -70% | Knowingly supplying work to any other person which is subsequently submitted by another student. |
| 0 FL for COMP2041/9041 | Submitting any other person's work with their consent. This includes joint work. |
| academic misconduct | Submitting another person's work without their consent. |
The lecturer may vary the assessment scheme after inspecting the assignment submissions but its likely to be broadly similar to the above.
If your assignment is submitted after this date, each hour it is late reduces the maximum mark it can achieve by 0.5% per hour for 24 hours, then 2% per hour after that. For example if an assignment worth 84% was submitted 20 hours late, the late submission would have no effect. If the same assignment was submitted 30 hours late it would be awarded 76%, the maximum mark it can achieve at that time.


Static Pages Using Tiddlywiki
Icons made by Freepik from www.flaticon.com
The Holy Grail Layout using CSS Grids made by Ire Aderinokun


With a background in mathematics, I have a strong love of problem solving, and I enjoy nothing more than working hard to find the best and most efficient solutions in order to grow your business.
I enjoy learning about the vision for your business and designing a website that fits your style and that will attract customers to your site.
The best part of my job is turning a design into a user-friendly, attractive website that fits your needs and keeps your customers coming back.


Ex-Peru President Wins Hearing on Jail Conditions
by MATTHEW RENDA(CN) – A federal judge will grant a hearing to the former Peruvian president accused of accepting bribes to determine whether the leader is being subjected to conditions akin to solitary confinement as he awaits extradition proceedings in a San Francisco Bay Area jail.
U.S. District Judge Vince Chhabria said he will hold a hearing on Dec. 13 to consider evidence regarding conditions at the jail where former Peruvian President Alejandro Toledo Manrique is being held as well as Toledo’s current mental health and whether he poses a significant flight risk.
Toledo says he is being held in conditions tantamount to solitary confinement and his mental health is rapidly deteriorating as a result. The former president is asking to be released on bond while the U.S. government decides whether to send him back to his native Peru to stand trial on charges of accepting approximately $20 million from a Brazilian construction company. Toledo was the president of Peru from 2001 to 2005.
Toledo denies the corruption allegations, saying they are part of a politically motivated smear campaign orchestrated by opponents still active in Peru.
Authorities held Toledo in solitary confinement in an Alameda County jail before moving him to a jail in San Mateo County after he complained.
Despite the change, Toledo’s defense lawyer argues the new conditions are “strikingly similar” to solitary confinement.
“Dr. Toledo spends approximately 23 hours a day in a cell smaller than the average parking space,” Toledo’s attorney, Graham Archer, wrote in a court brief last month.
The sheriff’s deputy who oversees Toledo’s incarceration says the ex-president gets three to four hours outside the cell per day, including an hour outdoors, and access to a room with couches and a television.
He also said in a declaration that Toledo is free to interact with other inmates. Toledo’s attorney says he is only permitted to talk to one other inmate – a convicted rapist.
U.S. Magistrate Judge Thomas Hixson has previously ruled that keeping Toledo in jail while he awaits the outcome of his extradition hearings is necessary because he has money and international connections, making him a flight risk.
Toledo was arrested on July 16 by U.S. marshals after the Peruvian government requested his extradition. He previously worked as a visiting scholar at Stanford University. Chhabria was assigned the case after an appeal was filed challenging a magistrate judge’s Sept. 12 decision to keep Toledo in jail despite concerns about solitary confinement.
Eight people from three states have offered a $1 million bond to help secure Toledo’s release. The government now contends that bond package is inadequate, claiming new evidence shows Toledo’s wife has $1 million in assets.
Copyright © 2019 courthousenews.com


Date & Time:
{{appointment.prettyDate}}
Location:
{{appointment.location}}
Duration:
{{appointment.duration}} minutes
Experiment:
{{appointment.experiment.experiment_name}}: {{appointment.experiment.experiment_conditions}}
Comments:
{{appointment.comments}}


optwrf package¶
optwrf.linuxhelper¶
optwrf.optimize_wrf_physics¶
A framework to run the simple genetic algorithm for optimizing the WRF model physics. All simulation parameters and fitness values are saved in an SQL database.
Known Issues/Wishlist:
-
optwrf.optimize_wrf_physics.
close_conn_to_db
(db_conn)¶ Closes the connection to a SQL database.
- Parameters
db_conn – database connection object created using the conn_to_db() function.
-
optwrf.optimize_wrf_physics.
conn_to_db
(db_name='optwrf.db')¶ Opens the connection to a SQL database.
- Parameters
db_name – SQL database name (string). Can be ‘:memory:’ if you only want the database to be held in memory. Otherwise, it will take the form <database_name>.db.
- Returns db_conn
database connection object that allows for additional interactions with the SQL database when referenced.
-
optwrf.optimize_wrf_physics.
get_fitness
(param_ids, verbose=False)¶ This function produces a random fitness value between 0 - 100
- Parameters
param_ids – list of ints corresponding to each WRF physics parameterization.
verbose – boolean (default = False) instructing the program to print everything or just key information to the screen.
- Return fitness
int randomly generated, and between 1 and 100.
-
optwrf.optimize_wrf_physics.
get_individual_by_genes
(individual, db_conn)¶ Looks for an indivual set of genes in an SQLite database.
***NOTE: I’m not sure if I want to remove the first where clause contianing the start date.
- Parameters
individual – simplega.Chromosome instance describing the simulation that you would to extract from the SQL simulation database if it exists there.
db_conn – database connection object created using the conn_to_db() function.
- Return past_sim
simplega.Chromosome instance describing the simulation that was run previously and stored in the SQL simulation database, and corresponding to the input individual function parameter.
-
optwrf.optimize_wrf_physics.
get_wrf_fitness
(param_ids, start_date='Jan 15 2011', end_date='Jan 16 2011', bc_data='ERA', n_domains=1, correction_factor=0.00033806364898425066, setup_yaml='dirpath.yml', verbose=False)¶ Using the input physics parameters, date, boundary condition, and domain data, this function runs the WRF model and computes the error between WRF and ERA5.
- Parameters
param_ids – list of integers corresponding to each WRF physics parameterization.
start_date – string specifying a desired start date.
end_date – string specifying a desired end date.
bc_data – string specifying the boundary condition data to be used for the WRF forecast. Currently, only ERA data (ds627.0) is supported.
n_domains – integer specifing the number of WRF model domains. 1 - 3 domains are currently supported.
correction_factor – float capuring the relationship between GHI and wind power density (WPD) errors averaged across an entrie year. Calculated using opwrf/examples/Fitness_correction_factor.py.
setup_yaml – string defining the path to the yaml file where input directory paths are specified.
verbose – boolean (default = False) instructing the program to print everything or just key information to the screen.
- Return fitness
float value denoting how well the WRF model run performed. Fitness is a measure of accumlated error, so a lower value is better.
-
optwrf.optimize_wrf_physics.
insert_sim
(individual, db_conn, verbose=False)¶ Inserts a simulation into the SQL database held in memory or written to a .db file.
- Parameters
individual – simplega.Chromosome instance describing the simulation that you would like to add to the SQL simulation database.
db_conn – database connection object created using the conn_to_db() function.
verbose – boolean (default = False) instructing the program to print everything or just key information to the screen.
-
optwrf.optimize_wrf_physics.
print_database
(db_conn)¶ Prints the entire SQLite simulation database.
- Parameters
db_conn – database connection object created using the conn_to_db() function.
-
optwrf.optimize_wrf_physics.
run_simplega
(pop_size, n_generations, testing=False, initial_pop_file=None, restart_file=True, verbose=False)¶ Runs the simple genetic algorithm specified in simplega either to optimize the WRF model physics or with a test fitness function that randomly selects a fitness value for each individual Chromosome.
- Parameters
pop_size – int describing population size for the genetic algorithm. Must be >= 1
n_generations – int corresponding to the total number of generations after which the genetic algorithm will time out.
testing – boolean (default = False) flag that uses a random number generator as the fitness function when True.
initial_pop_file – string (default = None) of a csv file path containing the populaition you would like to begin the simulation with.
restart_file – boolean (default = True) determining whether restart CSV files will be written before the fitness is calculated for each generation.
verbose – boolean (default = False) instructing the program to print everything or just key information to the screen.
- Return WRFga_winner
simplega.Chromosome instance corresponding to the simulation preforming the best in the genetic algorithm.
-
optwrf.optimize_wrf_physics.
seed_initial_population
(input_csv)¶ Reads the input csv file, which contains the dates and/or parameter combinations that you would like to see in the initial population. The CSV file should be formatted as follows (i.e., this function looks for these column names):
- Line 1: start_date, mp_physics, ra_lw_physics, ra_sw_physics, sf_surface_physics,
bl_pbl_physics, cu_physics
Line 2: Feb 28 2011, 1, 24, 99, 4, 11, 2
Line 3: Aug 31 2011, 28, 4, 5, 2, 10, 93
Line 4: Dec 10 2011, 7, 24, 3, 4, 9, 4
Line 5: Jul 22 2011, 11, 24, 2, 1, 4, 10
Line 6: May 23 2011, 1, 4, 5, 2, 10, 93
Line 7: Mar 31 2011, 28, 24, 99, 4, 11, 2
.
.
.
- Parameters
input_csv – string defines the file name from which dates/parameters will be read.
- Return intial population
list of Chromosome instances made from the information specified in the input file.
-
optwrf.optimize_wrf_physics.
sql_to_csv
(csv_file_path, db_conn)¶ Writes the contents of a SQL database to a CSV file. The SQL database must be in the directory that you are running this function from.
- Parameters
csv_file_path – string Exact path to where you would like to csv to be saved ending with the file name. e.g., csv_file_path = ‘/home/jas983/data/test.csv’
db_conn – database connection object created using the conn_to_db() function.
-
optwrf.optimize_wrf_physics.
update_sim
(individual, db_conn)¶ Inserts a simulation into the SQL database held in memory or written to a .db file.
- Parameters
individual – simplega.Chromosome instance describing the simulation that you would like to update in the SQL simulation database.
db_conn – database connection object created using the conn_to_db() function.
optwrf.runwrf¶
Class and supporting functions to run WRF within other scripts and process WRF output data.
Known Issues/Wishlist: - My username/password are currently hard-coded into this function. I SHOULD CHAGE THIS! - I’m unhappy with the output to screen from rda_download(). Perhaps edit that and check_file_status() as well. - A better way to set the command aliai would be nice. - Better Documentation
-
class
optwrf.runwrf.
WRFModel
(param_ids, start_date, end_date, bc_data='ERA', n_domains=1, setup_yaml='dirpath.yml', verbose=True)¶ Bases:
object
This class provides a framework for running the WRF model
-
get_bc_data
()¶ Downloads boundary condition data from the RDA if it does not already exist in the expected data directory (self.DIR_DATA). Then, it creates a temporary data directory (self.DIR_DATA_TMP) and copies data from the central data directory to the temporary data directory.
The justificaion for this approach is that the link_grib.csh script doesn’t contain a good way of picking files out of many. Therefore, it is much easier to link all the files in the temporary data directory than to link indidivdual files out of the central data directory.
NOTE Currently, only ERA data (ds627.0) is supported!
- Return vtable_sfx
string WPS variable table suffix – tells subsequent methods which boundary condidtion data is being used so that ungrib can successfully unpack data.
-
prepare_namelists
()¶ Writes dates, the geographical data path, number of domains, runtime duration, and physics options to the WPS and/or WRF namelist files.
-
process_era5_data
()¶ Downloads ERA5 data from the Research Data Archive if it doesn’t already exist in ERA5_ROOT, and processes the data – reduces the size of the ERA5 files using ncks and calculates the wind power density at 100m and the GHI – and writes these variables to a montly ERA5 NetCDF data file named ERA5_EastUS_WPD-GHI_YYYY-MM.nc.
Unfortunately, the ERA5 surface solar radiation downward (ssrd) data is provided in incredibly inconvenient temporal windows, so to build a montly file, we must download three ssrd files and two wind files (U and V wind components). For example, the following filelist would be built for January 2011:
- filelist = [‘e5.oper.an.sfc/201101/
e5.oper.an.sfc.228_246_100u.ll025sc.2011010100_2011013123.nc’,
- ‘e5.oper.an.sfc/201101/
e5.oper.an.sfc.228_247_100v.ll025sc.2011010100_2011013123.nc’,
- ‘e5.oper.fc.sfc.accumu/201012/
e5.oper.fc.sfc.accumu.128_169_ssrd.ll025sc.2010121606_2011010106.nc’,
- ‘e5.oper.fc.sfc.accumu/201101/
e5.oper.fc.sfc.accumu.128_169_ssrd.ll025sc.2011010106_2011011606.nc’,
- ‘e5.oper.fc.sfc.accumu/201101/
e5.oper.fc.sfc.accumu.128_169_ssrd.ll025sc.2011011606_2011020106.nc’]
which means there are three separate directories on RDA that files must be downloaded from.
***NOTE that this method currently only supports simulations within a single month i.e., YYYY-MM-01 00:00:00 - YYYY-MM-<end day> 23:00:00. Otherwise, wrf_era5_diff() will fail. Times are in UTC.
***NOTE that this method does not currently support running on Cheyenne; it’s about halfway there…
-
process_wrfout_data
()¶ Processes the wrfout file – calculates GHI and wind power denity (WPD) and writes these variables to wrfout_processed_d01.nc data file to be used by the regridding script (wrf2era_error.ncl) in wrf_era5_diff().
This method makes use of two different packages that are not endogeneous to optwrf. The first is pvlib.wrfcast, which is a module for processing WRF output data that I have customized based on the pvlib.forecast model. The purpose of this is to eventually be able to use this method to calculate PV output from systems installed at any arbitrary location within your WRF model domain (this is not yet implemented). I have use this wrfcast module to calculate the GHI from WRF output data The second package is the wrf module maintained by NCAR, which reproduces some of the funcionality of NCL in Python. I use this to interpolate the wind speed to 100m.
With the help of these two packages, the remaineder of the methods claculates the WPD, formats the data to be easily compatible with other methods, and writes the data to a NetCDF file.
-
run_real
(disable_timeout=False)¶ Runs real.exe and checks to see if it was successful.
- Returns
boolean (True/False) If runwrf_finish_check for real returns ‘complete’ (‘failed’), this function returns True (False).
-
run_wps
(disable_timeout=False)¶ Runs the WRF preprocessing executables and confirms thier success.
- Returns
boolean (True/False) If runwrf_finish_check for geogrid and metgrid returns ‘complete’ (‘failed’), this function returns True (False).
-
run_wrf
(disable_timeout=False, timeout_hours=6, save_wps_files=False)¶ Runs wrf.exe and checks to see if it was successful.
- Parameters
disable_timeout – boolean (True/False) desribing if timeout of this function is allowed. Note that this parameter only breaks you out of this method - it does not kill WRF jobs that are already running.
timeout_hours – integer defining the number of hours this method will wait before returning a failure (False) flag.
- Returns
boolean (True/False) If runwrf_finish_check for wrf returns ‘complete’ (‘failed’), this function returns True (False).
- Return elapsed
string specifying the amount of time it took for the WRF simulation to run.
-
runwrf_finish_check
(program, nprocs=8)¶ Check if a specified WRF subprogram has finished running. Does this specifically by checking the first and the last rsl.out.* file created by each processor running either wrf.exe or real.exe via OpenMPI.
***NOTE: It’s not currently possible for geogrid or metgrid to fail, because I don’t know what failure message to look for in the log.
- Parameters
program – string WRF or WPS subprogram name whose status is to be checked.
nprocs – integer Number of processors that you are using to run real.exe and wrf.exe.
- Returns
‘running’ or ‘complete’ or ‘failed’ string Run status of the program.
-
wrf_era5_diff
()¶ Computes the difference between the wrf simulation and ERA5 by calling the wrf2era_error.ncl script from the command line. NCL (short for NCAR Command Language) will be deprecated at some point in the future, and will be replaced by wrf-python, but the regridding functionality has not been ported to this package currently. Therefore, this function is a somewhat clumsy workaround.
wrf2era_error.ncl reads the previously-processed ERA and wrfout files, regrids the wrfout global horizontal irradiance (GHI) and wind power density (WPD) to match that of the ERA data, and then computes the difference across the entire d01 WRF domain for every time period.
This method waits while the regridding and error calculation is being completed by NCL, which can take some seconds to complete.
***NOTE: I don’t need to copy the wrf2era_error.ncl script into each WRFOUT directory, but that’s how I currently get the error file for each simulation to be written into the correct dirctory.
- Return total_error
list Sum of the mean absolute error accumulated for each grid cell during each time period in the WRF simulation.
-
wrfdir_setup
(vtable_sfx)¶ Sets up the WRF run directory by copying scripts, data files, and executables.
- Parameters
vtable_sfx – string variable table suffix specific to the boundary condition data; required to run WPS.
-
-
optwrf.runwrf.
check_file_status
(filepath, filesize)¶ Checks the file status during a download from the internet.
This is currently not implemented because I don’t like the way it prints information to the command line.
- Parameters
filepath – string Path to remote data file
- :param filesizeint
Size of the file as found by req.headers[‘Content-length’]
-
optwrf.runwrf.
determine_computer
()¶ Determines which computer you are currently working on.
- Return on_aws
boolean True if working on the mzhang AWS account where the group name is ‘ec2-user’
- Return on_cheyenne
boolean True if working on the NCAR Cheyenne super computer where the group name is ‘ncar’
- Return on_magma
boolean True if working on Jeff Sward’s account on the Cornell Magma cluster where the group name is ‘pug-jas983’
-
optwrf.runwrf.
format_date
(in_date)¶ Formats an input date so that it can be correctly written to the namelist.
- :param in_datestring
string specifying the date
- Returns
datetime64 array specifying the date
-
optwrf.runwrf.
print_last_3lines
(file_name)¶ Prints the last three lines of a file.
- Parameters
file_name – string Complete path of the file that you would like print.
-
optwrf.runwrf.
rda_download
(filelist, dspath)¶ Logs into the NCAR research data archive (RDA) and downloads specified files.
NOTE: My username/password are currently hard-coded into this function. I SHOULD CHAGE THIS!
- Parameters
filelist – list of strings List of all the files that you would like downloaded from the RDA.
- :param dspathstring
Full path to file on the RDA. You can obtain this from
- Returns
a boolean (True/False) success flag.
-
optwrf.runwrf.
read_2nd2_last_line
(file_name)¶ Reads the second to last line of a file.
- Parameters
file_name – string Complete path of the file that you would like read.
- Returns
second2_last_line: string Second to last line of the input file.
-
optwrf.runwrf.
read_last_3lines
(file_name)¶ Reads the last three lines of a file.
- Parameters
file_name – string Complete path of the file that you would like print.
- Returns
last_3lines: string Last three lines of the input file.
-
optwrf.runwrf.
read_last_line
(file_name)¶ Reads the last line of a file.
- Parameters
file_name – string Complete path of the file that you would like read.
- Return last_line
string Last line of the input file.
optwrf.simplega¶
A simple genetic algorithm for optimizing the WRF model physics.
Known Issues/Wishlist:
-
class
optwrf.simplega.
Chromosome
(genes, start_date, end_date, fitness=None, runtime=None)¶ Bases:
object
This class provides information about each unique individual to be placed within populations used in the genetic algorithm (e.g., parent population, mating population, or offspring population). Four pieces of information are associated with each individual:
1. A set of genes corresponding to six major physics parameters that be changed within the WRF model (microphysics, longwave radiation, shortwave radiation, land surface, planetary boundary layer, and cumulus). 2. A start date defining when the WRF forecast will begin running. 3. An end date defining when the WRF forecast will finish running. 4. A fitness value that will be used to determine how well each instance preforms.
-
optwrf.simplega.
crossover
(mating_population)¶ The crossover operator takes in the genes of two parent individuals and randomly exchanges one gene between the two producing two offspring.
- Parameters
mating_population – list of Chromosome instances population of individuals that have been deemed fit enough by the selection operator.
- Returns
offspring_population: list of Chromosome instances population of individuals created from the genes of mating population.
-
optwrf.simplega.
display
(individual, start_time)¶ Aids in display of an individual Chromosome instanceby printing useful information to the screen.
- Parameters
individual – Chromosome instance
start_time – datetime object defining when the simiulation began running.
-
optwrf.simplega.
display_pop
(population, fn_display)¶ Aids in display of an entire population by printing useful information to the screen.
- Parameters
population – list of Chromosome instances
fn_display – function defining how to display eah individual in the population.
-
optwrf.simplega.
find_elites
(population, n_elites, fn_display_pop, verbose=False)¶ Finds elites within the population by sorting the members of the population from best (numerically lowest) to worst (numerically highest) fitness value, and returns a list (with the nuber of individuals specified by the user) containing the individuals with the best fitness.
- Parameters
population – list of Chromosome instances.
n_elites – integer specifying the number of individuals you want to keep from the population.
fn_display_pop – function for printing information about the population to the screen.
verbose – boolean (default=False) determining whether or not to print lots of model information to the screen.
- Returns
elites: list of Chromosome instances specifying the elite individuals extracted from the population.
-
optwrf.simplega.
generate_genes
()¶ Generates genes for a new individual to be placed within a population.
- Returns
- new individual: list
list of WRF model physics parameters
-
optwrf.simplega.
generate_population
(pop_size, initial_population=None)¶ This method provides a way to randomly generate an initial population for the GA.
- Parameters
pop_size – integer specifies the number of individuals in the population to be generated.
initial_population – list of Chromosome instances allows users to seed the population with individuals of desired parameter combinations and start/end dates. If more inidividuals than the population size are specified, the ones listed first will be placed into the population.
- Returns
population: list of Chromosome instances
-
optwrf.simplega.
generate_random_dates
(year=2011, n_days=1, input_start_date=None)¶ Generates a random start date and end date for running the WRF model. Start and end dates are offset by the parameter n_days, which is set to 1 as default
- Parameters
year – integer or None specifying the year within which you want random days to be selected. If this is specified as None, random dates between Jan 1, 2000 and today can be selected.
n_days – integer specifying the nuber of days between the start and the end dates of the simulation. The default is set to 1 day.
input_start_date – string specifying a desired start date.
- Return random_start_date
string specifying the simulation start date.
- Return random_end_date
string specifying the simulation end date.
-
optwrf.simplega.
get_best
(population, verbose=False)¶ Finds the location of the individual within the population with the best (lowest) fitness.
- Parameters
population – list of Chromosome instances.
verbose – boolean (default=False) determining whether or not to print lots of model information to the screen.
- Returns
best_individual: single Chromosome instance individual within a population with the lowest fitness.
-
optwrf.simplega.
mutate
(offspring_population, verbose=False)¶ The mutate operator takes in the genes of one offspring and randomly replaces one of the genes from the set of choices.
- Parameters
offspring_population – list of Chromosome instances population of individuals created from the genes of mating population.
verbose – boolean (default=False) determining whether or not to print lots of model information to the screen.
- Returns
offspring_population: list of Chromosome instances mutated offspring population.
-
optwrf.simplega.
selection
(population, pop_size)¶ The selection operator carries out a tournament selection, by selecting the fittest individual among a group of randomly selected individuals, to create the mating population.
- Parameters
population – list of Chromosome instances specifies the population that the selection operator will select from.
pop_size – integer number of individuals within the population
- Returns
mating population: list of Chromosome instances population of individuals that have been deemed fit enough by the selection operator and will be sent to the crossover operator.
optwrf.wrfparams¶
Generates sets of WRF physics parameters, finds corresponding numeric identifies, and writes the numeric paramter options to a CSV.
Known Issues/Wishlist: - It would be better if I could read in the parameters from the in_yaml file only once, but I’m not sure how variables across different functions in the same module work.
-
optwrf.wrfparams.
apply_dependencies
(param_ids)¶ Applies depependencies among parameters. Generally, these were discovered by attempting to run an incompatible combination of parameters or from the WRF User’s Guide.
- Parameters
param_ids – list of integers corresponding to the namelist.input values of each input parameterization.
- Return param_ids
list of integers corresponding to the namelist.input values of each input parameterization after known dependencies have been applied.
-
optwrf.wrfparams.
combine
(lst1, lst2)¶ Combines two lists where at LEAST one of the two entries in the i’th position is None. The out_list contains values that are not None contained in either list. If both lists have None in the i’th position, then the out_list will also contain None.
- Parameters
lst1 – list
lst2 – list
- Return out_list
list combined from lst1 and lst2.
-
optwrf.wrfparams.
filldefault
(in_yaml, in_param_ids)¶ Fills an incomplete list (None values) of paramerization IDs with the defaults. The default value of these parameterization schemes is set by those that were originally used by ICF in the study over NYC.
- Parameters
in_yaml – string specifying the name of the yaml file containing parameter name integer pairs in sections by parameterization option.
in_param_ids – list of integers containing some Nones corresponding to the namelist.input values of each input parameterization.
- Return param_ids
list of integers corresponding to the namelist.input values of each input parameterization.
-
optwrf.wrfparams.
flexible_generate
(generate_params=True, mp=None, lw=None, sw=None, lsm=None, pbl=None, cu=None, in_yaml='params.yml', verbose=False)¶ Generate a parameter combination of the 6 core parameters if the user has specified this option. Otherwise, use specified input parameters and use defaults (determined by the fill_default() method) for the remaining paramters.
- Parameters
generate_params – boolean (default=True) specifying if parameters should be randomly generated or if some/all parameters will be user-specified. In the event that generate_params=False and not all parameters are specified, the remaining parameters will be filled with defaults.
mp – string or integer (default=None) specifying the microphysics parameterization name or namelist.input value.
lw – string or integer (default=None) specifying the longwave radiation parameterization name or namelist.input value.
sw – string or integer (default=None) specifying the shortwave radiation parameterization name or namelist.input value.
lsm – string or integer (default=None) specifying the land surface parameterization name or namelist.input value.
pbl – string or integer (default=None) specifying the planetary boundary layer parameterization name or namelist.input value.
cu – string or integer (default=None) specifying the cumulus parameterization name or namelist.input value.
in_yaml – string specifying the name of the yaml file containing parameter name integer pairs in sections by parameterization option.
verbose – boolean (default=False) determining whether or not to print lots of model information to the screen.
- Return param_ids
list of integers corresponding to the namelist.input values of each input parameterization.
-
optwrf.wrfparams.
generate
(in_yaml='params.yml')¶ Generates a random set of WRF physics parameters. These physics parameters include: 1. Microphysics 2. Longwave radiation 3. Shortwave Radieation 4. Land Surface 5. Planetary Boundary Layer 6. Cumulus (clouds)
- Parameters
in_yaml – string specifying the name of the yaml file containing parameter name integer pairs in sections by parameterization option.
- Return param_list
list specifying the integer assoicated with each parameter option.
-
optwrf.wrfparams.
ids2str
(param_ids)¶ Takes the parameterization IDs and combines them to form a string for appending to directory and file names for easy identification.
- Parameters
param_ids – list of integers corresponding to the namelist.input values of each input parameterization.
- Returns
paramstr: string combining each integer and associated abbreviation for all the parameterization options.
-
optwrf.wrfparams.
name2num
(in_yaml='params.yml', use_defaults=True, mp_in='morrison2mom', lw_in='rrtm', sw_in='dudia', lsm_in='noah', pbl_in='myj', clo_in='grell-freitas')¶ Maps the name of the physics parameterization, which is defined generally by the name of the individual or institution that designed the scheme, to the namelist.input value. The default value of these parameterization schemes is set by those that were originally used by ICF in the study over NYC.
- Parameters
in_yaml – string specifying the name of the yaml file containing parameter name integer pairs in sections by parameterization option.
use_defaults – boolean (default=True) determining wether or not you would like to return the default parameterization option if none is specified or if you would rather return None.
mp_in – string specifying the microphysics parameterization name.
lw_in – string specifying the longwave radiation parameterization name.
sw_in – string specifying the shortwave radiation paramterization name.
lsm_in – string specifying the land surface model parameterization name.
pbl_in – string specifying the planetary boundary layer parameterization name.
clo_in – string specifying the cumulus parameterization name.
- Return param_ids
list of integers corresponding to the namelist.input values of each input parameterization.
-
optwrf.wrfparams.
num2name
(param_ids, physics_type, in_yaml='params.yml')¶ Takes a list of param_ids and maps them to the physical parameterization name. Note that this only works for one type of physics at a time (i.e., microphysics, lw radiation, sw radiation, land surface, PBL, cumulus).
- Parameters
param_ids – list of integers corresponding to the namelist.input values of each input parameterization.
physics_type – string specifying a parameterization category. Options include: microphysics, lw radiation, sw radiation, land surface, PBL, and cumulus.
in_yaml – string specifying the name of the yaml file containing parameter name integer pairs in sections by parameterization option.
- Return param_names
list of strings corresponding to the physical parameterization names.
-
optwrf.wrfparams.
pbl2sfclay
(id_pbl, rnd=False)¶ Assigns the surface layer scheme based on the specified or randomly selected PBL scheme. If multiple surface layer schemes are available, one may be selected at random by setting rnd = True. Otherwise, id_sfclay defaults to option 1 (revised MM5 scheme).
- Parameters
id_pbl – integer corresponding to the namelist.input value of the planetary boundary layer parameterization.
rnd – boolean (default=False) that dictates whether or not compatible id_sfclay parameterization options are selected randomly or if the default value, id_sfclay = 1, is used.
- Return id_sfclay
integer corresponding to the namelist.input value of the surface layer parameterization.


CHAPTER 89A
OFFICE OF COLLECTIVE BARGAINING AND MANAGED COMPETITION
Section
89A-1 Office of collective bargaining and managed
competition
89A-2 Functions of the office of collective bargaining and
managed competition
Note
Chapter heading amended by L 2011, c 43, §2.


{{!-- The grid classes are defined in scss/global/_grid.scss. To use,
use both the "grid" and "grid-Ncol" class where "N" can be any number
from 1 to 12 and will create that number of columns. --}}
{{/each}}
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{{#each actor.gear_treasonous as |item id|}}
{{item.name}}
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{{item.name}}
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use both the "grid" and "grid-Ncol" class where "N" can be any number
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A curated collection of literature for philosophy of science and research methodologies with a focus on software engineering.
There are also a .bib file with all references and a Mendeley community to make citation easier. Literature suggestions per subsection are in alphabetical order. Pull requests or issues are welcome!
With suggestions from @dgraziotin
Download as .bib fileWith suggestions from @dgraziotin
Download as .bib file


A series of functions to calculate the split half reliability of RT based tasks. The core function performs a Monte Carlo procedure to process a user defined number of random splits in order to provide a better reliability estimate. The current functions target the dot- probe task, however, can be modified for other tasks.
| Version: | 0.3.1 |
| Depends: | R (≥ 3.3) |
| Imports: | tidyr, dplyr, stats |
| Suggests: | testthat, knitr, rmarkdown, tools, ggplot2 |
| Published: | 2018-03-17 |
| Author: | Sam Parsons [aut, cre] |
| Maintainer: | Sam Parsons <sam.parsons at psy.ox.ac.uk> |
| BugReports: | http://github.com/sdparsons/splithalf |
| License: | GPL-3 |
| URL: | http://github.com/sdparsons/splithalf |
| NeedsCompilation: | no |
| Citation: | splithalf citation info |
| Materials: | README NEWS |
| CRAN checks: | splithalf results |
| Reference manual: | splithalf.pdf |
| Vignettes: |
DPsplithalf() Vignette |
| Package source: | splithalf_0.3.1.tar.gz |
| Windows binaries: | r-devel: splithalf_0.3.1.zip, r-release: splithalf_0.3.1.zip, r-oldrel: splithalf_0.3.1.zip |
| OS X binaries: | r-release: splithalf_0.3.1.tgz, r-oldrel: splithalf_0.3.1.tgz |
| Old sources: | splithalf archive |
Please use the canonical form https://CRAN.R-project.org/package=splithalf to link to this page.


The Edit menu
This menu handles finding strings in specific tabs, searching for strings across all
requests and responses and managing session tracking.
Find...
This opens the Find dialog which allows you to find a string in the currently selected window.
Enable Session Tracking (Cookie)
This allows session details stored in cookies to be tracked.
This option must be selected to enable the "Use current tracking session" checkbox
in the Resend and
Manual Request Editor dialogs.
Session tracking ensures that any requests are sent with the latest session
details.
For example you may record a session when logged in as one user and then logout
and login as another user.
If you resend a request from the first session without
session tracking then it will use the cookies from the first session.
If you resend the same request with session tracking then it will use the
cookies from the second session.
Reset Session State
This clears the session tracking.
Search...
This selects the Search tab which allows you to search for regular expressions
in all URLs, requests and responses..
Next
This selects the next occurrence of the last string searched for.
The relevant message will be selected in the Search tab and the string will be displayed
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This selects the previous occurrence of the last string searched for.
The relevant message will be selected in the Search tab and the string will be displayed
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Response tab as appropriate.
Note that add-ons can add additional menu items.
See also


TWILLI | Air
Changelog by “Twilli Themes”
Table of Contents
- Version 1.2.3
- Version 1.2.2
- Version 1.2.1
- Version 1.2
- Version 1.1
Version 1.2.3 - top
December 2014
Keep a separate backup of your current website before applying the following update.
Changes/Updates:
- Fixes a bug with the CAPTCHA refresh link.
- Forms can now be used inside modals (popups).
- Update of jQuery version 1.11.2
New Files:
Place the following new files inside your website's root.
- /assets/js/jquery-1.11.2.min.js
Updated Files:
First keep a separate backup of your current version of these files. Then it is recommended to use a file comparison tool (ex: WinMerge, FileMerge, etc) to separately merge the updated files with your current version of the same files.
- index.html and index_w_extra_comments.html
- Added "clearfix" class to .modal-body
- Changed references to jQuery 1.11.2 version (javascripts section)
- /assets/css/styles.css
- Updates to: all .form-style rules (Lines 1169 - 1350)
- /assets/js/functions.js
- Updated function: validate_and_submit_forms
- New functions: reset_forms, reset_captcha
- /assets/js/initialise-functions.js
- Updated function: initialise_document_ready_functions ('On Opening Popups', 'On Closing Popups' sections)
- js/functions.min.js - if you have made extra changes to functions.js before this update, you'll need to re-minify it again after applying this update, using a tool like Prepros
Version 1.2.2 - top
November 2014
Keep a separate backup of your current website before applying the following update.
Changes/Updates:
- Fixes a bug causing an incorrect image count when opening a gallery image with Lightbox.
- Embedding responsive video players (YouTube, Vimeo) is now possible.
- Update of Bootstrap to v3.3.1.
- Minor optimisations and fixes.
New Files:
Place the following new files inside your website's root.
- /assets/js/jquery.fitvids.js
Completely Replaced Files:
Replace your version of the following files with the new version of the following files.
Updated Files:
First keep a separate backup of your current version of these files. Then it is recommended to use a file comparison tool (ex: WinMerge, FileMerge, etc) to separately merge the updated files with your current version of the same files.
- index.html and index_w_extra_comments.html
- The main changes are in the bottom Javascripts section.
- /assets/css/styles.css
- Updates to: #outer-background-container, .backstretch, #main-content
- /assets/js/functions.js
- Updated function: populate_and_open_modal
- New function: modal_backdrop_height
- Removed function: fixed_bg_image_dimensions_on_mobile
- /assets/js/initialise-functions.js
- Updated function: initialise_document_ready_functions ('responsive videos', 'On Opening Popups' sections)
- js/functions.min.js - if you have made extra changes to functions.js before this update, you'll need to re-minify it again after applying this update, using a tool like Prepros
Version 1.2.1 - top
September 2014
Changes/Updates:
- Added CAPTCHA to contact form.
- New alternative image gallery carousel inside popup.
- Update of Bootstrap to v3.2.0
- Update of Font Awesome to v4.2.0
- Minor optimisations and fixes.
New Files:
Place the following new files inside your website's root.
- /assets/css/custom.css - include your custom styles for your website here.
- /assets/images/other_images/gallery-thumb-[1 to 6].jpg
- /assets/js/lightbox/
- /assets/php/form_captcha/
Completely Replaced Files:
Replace your version of the following files with the new version of the following files.
- /assets/bootstrap/
- /assets/css/font-awesome/
- /documentation/
Updated Files:
First keep a separate backup of your current version of these files. Then it is recommended to use a file comparison tool (ex: WinMerge) to separately merge the updated files with your current version of the same files.
- /assets/css/styles.css
- /assets/js/functions.js
- /assets/js/functions.min.js - if you have made extra changes to functions.js, you'll need to re-minify it again using a tool like Prepros
- /assets/js/initialise-functions.js
- /assets/php/mail.php
- index.html and index_w_extra_comments.html - the main changes are in the head section and at the bottom js scripts section.
Version 1.2 - top
22nd June 2014
Changes/Updates:
- New changelog page with more information about the TWILLI Air updates.
- Update of jQuery script version from 1.10.2 to 1.11.1
- Fixed problem with opening popups on IE8 (IE8 is still not supported).
- Linking to a section inside a popup is now possible.
- Minor optimisation to the contact form.
- Added subtle intro reveal animation (WOW.js + Animate.css), which can be applied to any sections.
- Improvements to Bootstrap Elements' styling.
- Added Font Awesome 4.1.0 for more scalable icons.
New Files:
- /documentation/changelog.html
- /assets/css/font-awesome/
- /assets/js/jquery-1.11.1.min.js
- /assets/js/wow/
Updated Files:
- /index.html
- /index_w_extra_comments.html
- /assets/css/styles.css
- /assets/js/functions.js
- /assets/js/functions.min.js
- /assets/php/mail.php
Version 1.1 - top
22nd March 2014
- Added an image gallery carousel/slider which can be used in popups (Owl Carousel)
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| DOSE: T+ 0:00 |
9.0 mg |
insufflated |
2C-E |
(powder / crystals) |
| T+ 0:15 |
1 hit |
smoked |
Cannabis |
(plant material) |
Subject: Healthy young adult male with a smattering (<30) of psychedelic experiences, this being the first with a phenethylamine.>
T +0) 9mg (insufflated) I don't like sniffing this stuff. Very fluffy crystals that don't do what I want them to. Immediately my nasal cavity is numbed and my eyes start to water. It feels like the right side of my face is vibrating/twitching/reacting unfavorably to the foreign junk. The pain sucks but it starts to fade slowly after about three or four minutes. As someone who very rarely likes sticking things up their nose, I can say that the pain is bearable. No, it is not mild, but yes, it is bearable. Some quick alerts are here and there.
T + :08) The pain subsides. No nausea either. My friends and I have noted that this typically occurs at the higher snorted doses, ~15mg or so.
T + :15) cannabis (1 waterfall) smoked
T + :20) I went outside with a friend who wanted to smoke a cigarette. Already this stuff is pleasing me, with patterns coming out of the concrete as cracks and oil spots on the well-traveled road breed and multiply. Some phlegm and mucus buildup make it a little hard to speak.
T + :30) Trying to text a friend on my phone, I keep getting distracted by patterns that are starting to encroach upon me all sideways style. Numbers and letters on the pad and display start to run away.
T + 1:00) This stuff is so freaking visual. It rivals pretty much everything I've seen from any long-lasting hallucinogenic, at once. It has the flowing, morphing patterns. It's got the tracers. And wonderfully curious changes in lighting that I am finding to be unique to this substance. Funnily enough, everything seems to move. If I disconnect focus from any particular object, everything in the room simply MOVES and responds with changes in direction and intensity when paid attention to. The whole room seems to blur or shake in its activity and the patterns or tricks just pop out on their own accord.
The oddity of being faced with this much movement is a little hard to get used to. EVERYTHING in the room has life: the blinds are melting, my roommate's desk bulges menacingly out of the far wall, the dirt in one of my posters turns into an sea of eyes, my overhead light seems to fade in and out at intervals, rainbow patterns float along the LCD monitor, and even the cursor has its own ghost. I must say that for the amount of material I put up my nose, I am impressed. It's not so fast to the extent of becoming overwhelming, but it is very fun to have every object in the vicinity worthy of a good gaze or two. The patterns seem to come at funny angles too, almost through the air (very weird).
T:+ 1:20) Continuing to listen to music on my bed. Very fun trip. Quite lucid mentally, just enjoying how awesomely visual it all is. The whole area is a disjointed dance of imagination, every pattern crashing into two others at once, each one in contention to be the most active or alluring. Out of what I have come across, the only thing that comes close to 2ce in regard to open-eye visuals is DMT, and those are of a completely other nature which isn't well contrasted with most exogenous psychedelics.  My bread's melting into its own bag, that's cool.
T:+ 1:30) The character of these visuals is hard to get a handle on. It has so many aesthetic little nooks and crannies. I tried to focus on CEVs. They became more intricate and detailed as I watched, but grew to a slow unfolding cinematic scene that, without any story, wasn't entertaining enough. It's much more fun to keep my eyes open with this drug. My steel bedframe is turned to putty, then squished from some magical squishing force from opposite sides. And the crooked stack of books on my bureau ALMOST rights itself, each and every time I look at it. Frustrating.
T:+ 2:00) I like how this substance isn't afraid to bend things. It's not afraid to put things through space either, rather than just plastering surfaces. The body load with it so far hasn't been bad. The headspace is not uncomfortable, if slightly stimulated. There was some jittery excess energy in the beginning, like it didn't know where to go. That subsided into the visuals. Music has been sounding great (as is typical with both cannabis and 2ce) but without any major distortion. It's entirely possible that I would have noticed more during the peak if I hadn't been so enamored by the visuals, ha—this is funny because that possibility wouldn't have come up with any other drug I've done. Things are starting to slow down. Back on my bed, the whole wall starts waving and shimmering again, wtf.
T + 2:30) This is a stupidly fun substance. I can't get over it. My .001 scale is more inaccurate than I should like and I fear for anyone trying to eyeball this stuff. It's powerful!
T + 2:45) 2ce still has no reservations about stretching or compressing whatever it wants. The mental portion of this trip has been quite clear, in fact I've been virtually sober the entire time, as far as thought processes go. While much of what you can see on 2ce is familiar (personally that includes stuff like the aforementioned sea of eyes, melting effects, or flow of woodgrain), a lot of it is pretty interesting and new.
T + 3:00) Strangely enough, the last two hours have FLOWN by. Quite surprised by this actually.
T + 3:20) The intensity has dropped a good few notches in the last half hour or so.
T + 4:30) Subtle effects remain.
Final Notes: I had a blast researching 2ce. Set and setting are still important though. Certainly not something I could suggest doing on a whim. It might catch someone off guard if they don't know what the chemical is all about.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


The following exposure cohorts were compared:
- SGLT2i-BROAD: New users of any SGLT2i with prior T2DM (broad definition)
- Canagliflozin-BROAD: New users of canagliflozin with prior T2DM (broad definition)
- Dapagliflozin-BROAD: New users of dapagliflozin with prior T2DM (broad definition)
- Empagliflozin-BROAD: New users of empagliflozin with prior T2DM (broad definition)
- DPP-4i-BROAD: New users of any DPP-4i with prior T2DM (broad definition)
- GLP-1a-BROAD: New users of any GLP-1a with prior T2DM (broad definition)
- SU-BROAD: New users of any SU with prior T2DM (broad definition)
- TZDs-BROAD: New users of any TZD with prior T2DM (broad definition)
- Insulin-BROAD: New users of insulin with prior T2DM (broad definition)
- Metformin-BROAD: New users of metformin with prior T2DM (broad definition)
- Insul. AHAs-BROAD: New users of insulinotropic AHAs with prior T2DM (broad definition)
- Other AHAs-BROAD: New users of other AHAs with prior T2DM (broad definition)
- SGLT2i-NARROW: New users of any SGLT2i with prior T2DM (narrow definition)
- Canagliflozin-NARROW: New users of canagliflozin with prior T2DM (narrow definition)
- Dapagliflozin-NARROW: New users of dapagliflozin with prior T2DM (narrow definition)
- Empagliflozin-NARROW: New users of empagliflozin with prior T2DM (narrow definition)
- DPP-4i-NARROW: New users of any DPP-4i with prior T2DM (narrow definition)
- GLP-1a-NARROW: New users of any GLP-1a with prior T2DM (narrow definition)
- SU-NARROW: New users of any SU with prior T2DM (narrow definition)
- TZDs-NARROW: New users of any TZD with prior T2DM (narrow definition)
- Insulin-NARROW: New users of insulin with prior T2DM (narrow definition)
- Metformin-NARROW: New users of metformin with prior T2DM (narrow definition)
- Insul. AHAs-NARROW: New users of insulinotropic AHAs with prior T2DM (narrow definition)
- Other AHAs-NARROW: New users of other AHAs with prior T2DM (narrow definition)
These specific ingredients are included in the drug classes mentioned above:
- SGLT2 inhibitors: canagliflozin, dapagliflozin, empagliflozin
- DPP-4 inhibitors: alogliptin, linagliptin, saxagliptin, sitagliptin, vildagliptin
- GLP-1 agonists: albiglutide, dulaglutide, exenatide, liraglutide, lixisenatide
- Sulfonylureas: acetohexamide, carbutamide, chlorpropamide, glibornuride, gliclazide, glimepiride, glipizide, gliquidone, glyburide, glymidine, tolazamide, tolbutamide
- TZDs: pioglitazone, rosiglitazone, troglitazone
- Insulinotropic AHAs: alogliptin, linagliptin, saxagliptin, sitagliptin, vildagliptin, albiglutide, dulaglutide, exenatide, liraglutide, lixisenatide, acetohexamide, carbutamide, chlorpropamide, glibornuride, gliclazide, glimepiride, glipizide, gliquidone, glyburide, glymidine, tolazamide, tolbutamide, nateglinide, repaglinide
- Other AHAs: arcabose, bromocriptine, miglitol, nateglinide, repaglinide
Type 2 diabetes mellitus definitions:
- Broad definition: Diagnosis of type 2 diabetes mellitus with no diagnosis of type 1 diabetes mellitus or secondary diabetes mellitus on or before index drug exposure
- Narrow defintion: Diagnosis of type 2 diabetes mellitus with no diagnosis of type 1 diabetes mellitus or secondary diabetes mellitus on or before or after index drug exposure, and excludes patients taking insulin monotherapy before index drug exposure and excludes patients under 40 years of age at index drug exposure
Key - T2DM: type 2 diabetes mellitus; SGLT2i: sodium glucose co-transporter 2 inhibitor; DPP-4i: dipeptidyl peptidase-4 inhibitor; GLP-1a: Glucagon-like peptide-1 agonist; SU: sulfonylureas; TZD: thiazolidinedione; Insul. AHA: insulinotropic antihyperglycemic agent; AHA: antihyperglycemic agent


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Welcome to my portfolio.
My name is Gloria but I go by Ale. I am an aspiring software developer residing in the Twin Cities area. I have a deep passion for learning about new tech and I enjoy coding and building cool stuff.
◘ I am currently teaching myself how to use Linux and Python.
Also, here is me on paper
PDF
However, if you'd like the complete picture take a look at some of my work here
You can also see what one of my professors said about me!
Academic RecommendationI am familiar with Java, SQL, PHP / CSS/ HTML, C++ and C++ and I have experience using Visual Studio 2017, Eclipse, IntelliJ, BlueJ, and MS SQL Server Management Studio 17.
I am fluent in English and Spanish and have professional experience in customer-facing roles using both.
MS Access, Excel, Visio, and SharePoint are office applications I use on a regular basis.
I have experience mentoring others, collaborating with teams and writing technical documentation.
I love to work and learn about new challenges so don't be shy, I am just an email away.


Original code by bipedalshark Parser code : Github Website code : Github Contributors : SlenderPlays, Tsudico & Turanar


Create a new Alloy tuple.
The unique identifier for this tuple
The ordered array of atoms that comprise this tuple
Returns the number of atoms in this tuple.
Returns the ordered array of atoms that comprise this tuple.
Returns true if this tuple is equivalent to the provided tuple. Tuples are equivalent if they contain the same set of atoms in the same order.
Returns AlloyType.Tuple
Returns the unique ID of this tuple.
Returns the name of this element.
Returns the size of this tuple. Tuples always have size 1, as they are considered a single 'row' in a field.
Return an array of skolems that include an element equivalent to this element.
Returns a printable string.
Returns an ordered array of the types of the atoms in this tuple.
Assemble the array of atoms that comprise a tuple.
The XML tuple element
The array of types for this tuple
Add a skolem to the provided witness.
The witness
The skolem
Assemble a tuple for a field.
The XML tuple element
The array of types for this tuple
Assemble a tuple for a skolem.
The name of the skolem
The XML tuple element
The array of types for this tuple
Generated using TypeDoc
AlloyTuple
In Alloy, a tuple is a sequence of one or more atoms. As part of an Alloy instance, tuples can either reside in a field or exist as a free variable that makes an existentially quantified formula true, known as a skolemization.


Software Engineer.
Find Out More!Master of Science in Computer Science from Pune University
Master of Science in Computer Science from Pune University
Java Javascript Python
SQL HTML
Cloud Microservices Database NoSQL Docker
Security Networking
August 2017 to Present: Nice Incontact
June 2016 to August 2017: GS Lab
July 2007 to June 2016: Harbinger Systems
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EXCLUSIVE: DeHaven: The Judge Tossed My Case to Protect The Feds' 95% Conviction Rate
by VladTVIn this clip, DeHaven spoke about the culmination of his drug case coming in the form of a mistrial after the judge threw out the case for lack of substantial evidence. As DeHaven explains, this was due in large part by the judge to protect the Feds' 95% conviction rate and the prosecutor's personal conviction rate which was no less flawless.


Can you differentiate between @realDonaldTrump and @dril Tweets?
Click start to start the test!
Who made this tweet?
just fired 300 journalists. and it feels so good
Who made this tweet?
my twitter has become so powerful that i can actually make my enemies tell the truth.
Who made this tweet?
you realize the haters are so bad because i'm doin' soooo great!
Who made this tweet?
thank you for the follow @nbcsports
Who made this tweet?
who can figure out the true meaning of "covefefe"??? enjoy!
Who made this tweet?
much like they do with investments, professional ties, etc, journalists should be expected to disclose how mad they are,
Who made this tweet?
i do what i do out of pure enjoyment. hopefully, nobody does it better. theres a beauty to making a great deal. it's my canvas
Who made this tweet?
these hoes think they classy, well that's the class i'm skippen
Who made this tweet?
protected from all hater energy
Who made this tweet?
from here on, i will refer to the upcoming super bowl as the "treason bowl"
Who made this tweet?
we
Who made this tweet?
i would like the extend my best wishes to all, even the haters and losers, on this special date, september 11th.
Who made this tweet?
people are going crazy with my comments on diet coke (soda). let's face it -- this stuff just doesn't work. it makes you hungry.
Who made this tweet?
the economy is changing the way people think about culture.....
Who made this tweet?
"@YoungBasedGod_g: @??? your dad gives good brain?? damn" it's called genes!
Who made this tweet?
@greggturkington glad to see james, friend to cinema, returning to us at long last. thank you
Who made this tweet?
@ninetek then why do you follow me like a little puppy, moron?


Join any of the exciting trips below!
Castle Hopping GERMANY
2 of 4
2nd Feb >> 21st Feb
Main Attractions
- Neuschwanstein Castle
- Hohenzollern Castle
- Heidelberg Castle
- Wartburg
Local Attractions LONDON
3 of 8
3rd Mar >> 7th Mar
Main Attractions
- Big Ben
- British Museum
- St. James's Park
Look See Look See LONDON
3 of 8
3rd Mar >> 7th Mar
Main Attractions
- Big Ben
- British Museum
- St. James's Park


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About Us
Nicholas Carignan
Nicholas is a Full Stack Web Developer whose interest in code was sparked by a love for problem solving and a yearning to build. He has lived both as a teacher and law enforcement and neither satisfied his ambition to make a difference. Coding allows him to reach a wide audience and affect a more meaningful change.
GitHubMatthew LeBlanc
Matt is a former sous chef whose coding skills are as sharp as the knives he once loved. While he doesn't sharpen those as much as he'd like, he spends plenty of time sharpening his Javascript full stack abilities. Like a well-pepared stew, he brings all of the ingredients to the table.
GitHubFred Rapp
Fred is a formerly homeless, retired Navy K9 handler, currently self-employed as a handyman and am now working on becoming a savvy coder.
GitHubKerry Nordstrom
Kerry is a former bicycle mechanic whose daily tasks involved solving complicated problems with a series of simple solutions. This desire to elegantly fix the squeaky wheel in the machine has led him to become a Javascript full stack developer.
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