14th December 2014
Net Neutrality at its simplest
So, before starting to learn to code I had "net neutrality" referenced around the place and assumed (wrongly) that I sorta, maybe, kinda knew what it was about. I didn't. Net Neutrality in VERY simple terms is about ensuring that the traffic speed for accessing one kind of information on the net comes at the same speed as another. 'Net Neutrality' is the principle that Internet service providers and governments should treat all data on the Internet equally, not discriminating or charging differentially by user, content, site, platform, application, type of attached equipment, or mode of communication.
What does it really mean in practice? Well, at the moment traffic for any website (broadly speaking) will be provided to an end user at the same speed as any other. If you think of the web as a big highway then every car (website) can move along that highway at the same speed. However if we removed neutrality then companies (governments even) could pay an ISP additional money to ensure their website got a speeding permit and their website could be accessed faster than others. To be clear, internet speeds in rural areas are often slower than urban areas - that is not a net neutrality issue. (As long as the speed of access to all websites is equally slower in rural areas, that is an issue of infrastructure and access. )
So, why would it matter if there was faster access for some? Well, proponents of net neutrality argue that it would entrench large incumbents and reduce competition (imagine if youtube could have 5x the access speed of any other video streaming service). Or, as has happened in the past: free peer-peer music sharing sites are slowed down while their paid competitors receive speedy access. But overall? Those in favour or net neutrality tend to argue on the grounds of ensuring: freedom of data, democratic communications, competition & innovation. On the other hand those against net neutrality tend to argue based on a belief in: less regulation generally, improving infrastructure & investment & preventing the overuse of bandwidth.


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Assimp
5.0.1, master @ cd42b955
|
Classes | |
| struct | AnimBoneDesc |
| Represents a bone (joint) descriptor in a MD5Anim file. More... | |
| struct | BaseFrameDesc |
| Represents a base frame descriptor in a MD5Anim file. More... | |
| struct | BaseJointDescription |
| Basic information about a joint. More... | |
| struct | BoneDesc |
| Represents a bone (joint) descriptor in a MD5Mesh file. More... | |
| struct | CameraAnimFrameDesc |
| Represents a camera animation frame in a MDCamera file. More... | |
| struct | Element |
| Represents a single element in a MD5 file. More... | |
| struct | FrameDesc |
| Represents a frame descriptor in a MD5Anim file. More... | |
| class | MD5AnimParser |
| Parses the data sections of a MD5 animation file. More... | |
| class | MD5CameraParser |
| Parses the data sections of a MD5 camera animation file. More... | |
| class | MD5MeshParser |
| Parses the data sections of a MD5 mesh file. More... | |
| class | MD5Parser |
| Parses the block structure of MD5MESH and MD5ANIM files (but does no further processing) More... | |
| struct | MeshDesc |
| Represents a mesh in a MD5 file. More... | |
| struct | Section |
| Represents a section of a MD5 file (such as the mesh or the joints section) More... | |
| struct | VertexDesc |
| Represents a vertex descriptor in a MD5 file. More... | |
| struct | WeightDesc |
| Represents a vertex weight descriptor in a MD5 file. More... | |
Typedefs | |
| typedef std::vector< AnimBoneDesc > | AnimBoneList |
| typedef std::vector< BaseFrameDesc > | BaseFrameList |
| typedef std::vector< BoneDesc > | BoneList |
| typedef std::vector< CameraAnimFrameDesc > | CameraFrameList |
| typedef std::vector< Element > | ElementList |
| typedef std::vector< aiFace > | FaceList |
| typedef std::vector< FrameDesc > | FrameList |
| typedef std::vector< MeshDesc > | MeshList |
| typedef std::vector< Section > | SectionList |
| typedef std::vector< VertexDesc > | VertexList |
| typedef std::vector< WeightDesc > | WeightList |
Functions | |
| void | ConvertQuaternion (const aiVector3D &in, aiQuaternion &out) |
| typedef std::vector< AnimBoneDesc > Assimp::MD5::AnimBoneList |
| typedef std::vector< BaseFrameDesc > Assimp::MD5::BaseFrameList |
| typedef std::vector< BoneDesc > Assimp::MD5::BoneList |
| typedef std::vector< CameraAnimFrameDesc > Assimp::MD5::CameraFrameList |
| typedef std::vector< Element > Assimp::MD5::ElementList |
| typedef std::vector< aiFace > Assimp::MD5::FaceList |
| typedef std::vector< FrameDesc > Assimp::MD5::FrameList |
| typedef std::vector< MeshDesc > Assimp::MD5::MeshList |
| typedef std::vector< Section> Assimp::MD5::SectionList |
| typedef std::vector< VertexDesc > Assimp::MD5::VertexList |
| typedef std::vector< WeightDesc > Assimp::MD5::WeightList |
|
inline |


Example Class 4 Report (Project 4B)
Data
The data set of cities used for this lab is taken from a GitHub repository
Graph Implementation
In our implementation, we used adjacency lists to represent the graph (undirected, non-weighted). The Graph class holds all the functions to create and modify the graph, which are used by the Graph Generation class.
Methods:
- connect: Creates an undirected edge between 2 cities.
-
density: 2 * (number of non-stop flights (undirected graph)) / (size of the adjacency list)
- num of non-stop flights = density * maximum possible number of non-stop flights
- maximum possible number of non-stop flights = size * (size-1) / 2
- printGraph - Although the Graph is implemented as an adjacency list, we printed the graph out as an adjacency matrix allows us to easily see which cities are connected.
Graph Generation Implementation
In this implementation, we will be using size, density and number of non-stop flight to generate random graph by randomly generating linked list to each city.
Methods:
-
buildNonStopFlights: Edges are built on top of pre-existing graph.
- only cities that are not connected are selected
- selection of cities is done using an adjacency matrix - search time of O(1)
Implementation of Searching Algorithms
Our searching algorithms are implemented in the Searcher class.
-
the Searcher class make use of a linked list, L
- L is used as a queue in BFS
- L is used as a stack in DFS
Both BFS and DFS have the same code structure; they:
- visit the source
- place the source in L
-
while L is not empty (ie graph is not fully traversed)
- remove the first City in L
- visit the first City’s neighbouring Cities if they are not already visited
- add the neighbouring Cities to L
Differences in BFS and DFS
-
upon visiting a neighbouring City which is the destination
- BFS: return path to destination as the shortest route
- DFS: compare new path found to previously known shortest route - if the newly-found path is shorter than the current shortest route, or there is no shortest route currently, the new path found is stored as the shortest route
-
for adding of neighbouring Cities to L
- BFS: add neighbouring Cities to back of L (i.e. L is used as a queue)
- DFS: if neighbouring Cities are already in L, remove them from L first; add neighbouring Cities to front of L (i.e. L is used as a stack)
-
at the end of the function
- BFS: returns null since no path can be found
- DFS: returns the shortest route, or null if no path can be found
Analysis of Running Times
Based on number of cities (size of graph/ |V|) and number of non-stop flights (|E|):
Based on the graph, search time = O(0.1 (|V| +|E|) + 40000) = O(|V|+|E|).
Conclusion
DFS cannot be used in place of BFS as it does not guarantee that a node which is visited before another node is closer to the source node. This is also reflected in the backtracking nature of DFS in which it visits the “deeper” nodes further away from the source nodes first; going as far as it possibly can before returning to the unvisited adjacent nodes.
On the other hand, BFS visits nodes in increasing order of distance from the source; visiting all nodes at the same “level” before proceeding to the next. Therefore it would be more practical to search wide instead of deep and this can be seen empirically based on a better overall average search time by using BFS.
Nonetheless, DFS can also be used in place of BFS, but that would require the program to find all possible ways to reach the destination node from source node and updating the shortest path with each new discovery; however, this comes with high complexity and it is simply not recommended in this instance.
Authors
SE1 (Group 2)
- LYZ
- Ngo Jun Hao Jason
- TSF
- TYHK
- YHL


Balthisar Tidy Tidy’s the text in the “Source HTML” pane. When you open an existing document its text will be present in this pane.
Alternatively you can create a blank document and begin adding HTML markup in this area directly.
It’s often convenient to make quick-and-dirty, valid HTML documents by typing directly into this window without opening documents. We don’t recommend making this your primary HTML document editor, however, as there are many full-featured editors more adequate for working with text.


Perf Report:
Test (Frame #96)
Worker Thread 0
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Worker Thread 2
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CUMULATIVE
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Diff takes two texts and finds the differences. This implementation works on a character by character basis. The result of any diff may contain 'chaff', irrelevant small commonalities which complicate the output. A post-diff cleanup algorithm factors out these trivial commonalities.
Text Version 1: |
Text Version 2: |
seconds
If the mapping phase of the diff computation takes longer than this, then the computation
is truncated and the best solution to date is returned. While guaranteed to be correct,
it may not be optimal. A timeout of '0' allows for unlimited computation.


Ocean [ak51], ocean, in The Inner Sea
Last updated Turn #92
Ocean [ak51], ocean, in The Inner Sea
------------------------------------------------------------------------
21: The Savvy Aardvark [ha5r], ship, 2 hulls, 1 rowing port, 6 sails,
21: 13% damaged, arrived from Ocean [ak50], owner:
21: Phantasm [n4b], Imperial Empire, duke, with eight sailors,
21: one riding horse
22: The Savvy Aardvark [ha5r], ship, 2 hulls, 1 rowing port, 6 sails,
22: 13% damaged, departed for Ocean [ak52].
Routes leaving Ocean:
North, to Ocean [aj51], 6 days
East, to Ocean [ak52], 6 days
South, to Ocean [al51], 6 days
West, to Ocean [ak50], 6 days


|
SUBJECT INDEX Anthropology Architecture Art Black Studies Business Ecology Economics Education Film Healthcare History Law Linguistics Literature Mass Media Medicine Music Philosophy Political Science Psychology Religion Science Shakespeare Sociology Sports Recreation Urban Studies Women's Studies |
Medicine & Healthcare: Pediatric & Infant CareTo order a specific paper, click the Catalog Number button next to the Paper Title of interest. Send comments to<EMAIL_ADDRESS>Last Updated: 12/21/96 Copyright ©1996 ASM Communications, Inc. All Rights Reserved. |


--- title: OCHA Basic theme options: - include_cd - include_ocha_basic ---
This styleguide no longer accurately reflects the Common Design.
Guide for the OCHA Basic Drupal starter theme: https://github.com/UN-OCHA/ocha_basic
The Sass structure can also be used on non-Drupal sites.
Base styles and helpers
Useful helper styles such as sr-only for screen reader only text
Sass file: /sass/base/_helpers.scss
Styles for UI components
Drupal implementation of the Common Header
Sass file: /sass/components/cd-header
Drupal template: /templates/header.inc
Example: Common Header demo
Drupal implementation of the Common Footer
Sass file: /sass/components/_footer.scss
Drupal template: /templates/footer.inc
Example: Common Footer demo
Styles for Bootstrap dropdown
Sass file: /sass/components/_dropdown.scss
Example: Dropdown demo and markup
Uses a subset of the UNOCHA icon set
Sass file: /sass/components/_icons.scss
Example: UNOCHA icon set
Allows keybaord users to skip to the main content
Sass file: /sass/components/_skip-link.scss
Responsive and static table styles
Sass file: /sass/components/_tables.scss
Example: Tables demo and markup
Useful Sass mixins
Sets min-width media queries at specified breakpoints
Sass file: /sass/mixins/_media-queries.scss
Sass variables to use in styles
Color scheme based on the OCHA palette, see OCHA Graphics Style Book (pdf)
Sass file: /sass/variables/_colours.scss
Example: Colours demo
Includes a base unit to use for spacing, plus other reusable measurements
Sass file: /sass/variables/_measurements.scss
These component styles aren't included in the OCHA Basic theme, which is kept minimal, but can be added by downloading the .scss files and including in your version of the theme.
Styled checkboxes and radio buttons
Sass file: /sass/components/_clickies.scss
Example: Clickies demo
Chosen is a jQuery plugin for searchable selects that is used on several OCHA sites
Sass file: /sass/components/_chosen.scss
Example: Chosen demo
Styles for blocks of content (used on the TAAS site)
Sass file: /sass/components/_blocks.scss
Example: Blocks demo


WaveDec: a tool for wavefield decomposition¶
WaveDec is a software for the analysis of seismic surface waves. It provides maximum likelihood estimates of wave parameters for Love and Rayleigh waves. All the sensor components are analysed jointly. The simultaneous presence of multiple modes of propagation and multiple wave types (i.e., Love and Rayleigh) is accounted for. Estimated wave parameters include: Love and Rayleigh wave wavenumber, Rayleigh wave ellipticity angle, wave amplitude, and direction of arrival.
An overview of the method is available in the Scientist’s Documentation, more details can be found in the referenced literature. See also the frequently asked questions.
The are are two main scripts:
WaveDec.py can be used for the analysis of Love and Rayleigh waves and relies on the assumption of plane wavefronts (e.g. at large distance from the source). Translational and rotational motions can be jointly analysed. Applications include the analysis of ambient vibrations. See User’s guide: WaveDec.
WaveDecActive.py can be used for the analysis of Rayleigh waves with circular wavefronts (e.g. at small distance from the source). Applications include the analysis of active surveys. See User’s guide: WaveDecActive.
Look at the Installation and at the A very quick start sections to run WaveDec as quickly as possible. A simple tool for picking, filtering and plotting is also provided, see User’s guide: wdPicker.
Some Usage Examples are also provided.
The algorithm was developed at the Swiss Seismological Service of ETH Zurich.
Download¶
The code can be cloned from the GitHub repository github.com/StefanoMarano/WaveDec
git clone https://github.com/StefanoMarano/WaveDec.git
or downloaded as ZIP archive.
Documentation and examples are available in these pages. For any questions related to the software, feel free to email me: .
Usage of the software is limited to non-commercial use (that is, educational and research purposes). If you use the software in your work, please acknowledge us, see How to cite us.
Last Changes¶
26/4/2020: GitHub repository and documentation are online
15/7/2017: Created a new page: Frequently asked questions (FAQ).
15/6/2017: Updated the examples concerning rotational motions, see Section Plane waves (translational and rotational motions).
29/5/2017: Following the acceptance for publication of our article “Analysis of Rayleigh Waves with Circular Wavefront: a Maximum Likelihood Approach”, the code WaveDecActive.py is released in the main distribution together with WaveDec.py.
12/5/2017: Added support for the option
Tstart
in WaveDec. See configuration file section.
Contents¶
- Scientist’s Documentation
- Frequently asked questions (FAQ)
- Installation
- A very quick start
- User’s guide: WaveDec
- User’s guide: WaveDecActive
- User’s guide: wdPicker
- Usage Examples
- Scientific publications related to WaveDec
- Code Documentation


Topics;
Web App Front-End Best Practices 2017
How to: (The Basics): 1. Apply design guidelines 2. Make your CSS unbreakable 3. Create clean HTML 4. Accelerate load times and reduce bandwidth
(The Bricks and Mortar) 5. Obtain SPA/rich client feel 6. Reduce Time to Glass 7. Choose HTML vs. JavaScript 8. Integrate business logic
(The Perspectives) 9. Do Web Components right 10. Fast-track mobile apps
//11. Next: SSR
Why Best Practices: - Develop quality web apps - faster/more efficiently - future-safe
Why X?
The 10 commandments:
The Basics 1. Apply Design Guidelines (e.g. Material Design, MUICSS) for beauty and consistency 2. Use SASS and Preprocessors for clean, maintainable CSS 3. Use Pug for clean, maintainable HTML 4. Go (max) static, deploy to CDN edge cache to scale for performance
The Bricks and Mortar 5. Use AppShell and page transitions to improve perceived performance 6. Use AMP and please visitors 7. Be DOM-centric and designer-friendly 8. Use PageBusiness, Promises and Fetch microservices for cleaner code
The Perspectives 9. Use web components to be LEGO 10. Use Phonegap/in-app browser for efficiency
"Always code for the least amount of astonishment."
Web App Front-End Best Practices 2017 (Or: How to create stunning web apps that are maintainable and future-safe with 2017 technology)
How to: - Ensure a great looking design - Make your CSS unbreakable - Create clean HTML - Accelerate load times and reduce bandwidth - Obtain SPA/rich client feel - Reduce Time to Glass [with early completion] - Pick between HTML and JavaScript - Integrate business logic - Do Web Components right AND right now - Fast-track mobile apps


Ensj HealthCheck Changes
Version 1.2, 2nd May 2002
Many new tests. An up-to-date list of tests can be found
here
.
Integration with the
EnsJ
EnsEMBL Java API - provides the ability to write tests using the functionality provided by EnsJ.
Much more Javadoc documentation.
Added several new methods to the base test class; e.g. tests can now have a description field.
Reorganised package structure.
Various bug fixes, performance improvements and code cleanup.


Pick Things to Do
x
Things to Do in ABQ Parks
What do you want to do?
About
Play at a Playground
Have a Picnic
Go for a Swim
Play Tennis
Go for a Run
Play Basketball
Play Soccer
All Parks


Data Migration Tool can only know a job fails if the control members are set correctly. Hence, it depends on if the templates are set correctly, and the error is not a JCL error.


Welcome to the Volunteer Scheduler. This is an application in which you can find volunteer organization to volunteer for. We are a software engineering of 5 total people that have worked on this application. The purpose that came behind this project was to bring together volunteer and volunteer organizations. This website application is trying to remove any middle men needed in the process. If you don't have an account sign up here. If you do have an account you may also login here.


class LinkedList::Node(T)
- LinkedList::Node(T)
- Reference
- Object
Overview
A node is the building block of linked lists consisting of a values and a pointer to the next node in the linked list.
To create a node:
node = Node.new(5)
puts node.value
The above produces:
5
Check the value of the node with #value
.
Get the next node in the list with #next
.
Defined in:
linked_list.crConstructors
-
.new(value : T)
Creates a node with the specified value.
-
.new
Creates a node with no value.
Instance Method Summary
-
#next
Returns the next node in the linked list, or nil if it is the tail.
-
#next=(next_node : LinkedList::Node(T)?)
Sets the next node in the linked list to next_node
-
#value
Returns the value of the node, or nil if no value was supplied
Constructor Detail
Instance Method Detail
def next
#
Returns the next node in the linked list, or nil if it is the tail.
node = Node.new(1)
node.next = Node.new(2)
node.next.value # => 2
def next=(next_node : LinkedList::Node(T)?)
#
Sets the next node in the linked list to next_node
node = Node.new(1)
node.next = Node.new(2)
node.next.value # => 2


Your Dynamo Server is now running...
This
Dynamo extension
allows bi-directional communication and control of Dynamo as a REST API.
Check out what you can do with it by browsing and testing the endpoints below.
Github
Twitter
Workspaces
Open file
Instructs Dynamo to open the file found at the supplied filepath.
URL
http://localhost:1234/
Workspace/Open/
{filepath}
Test this endpoint
Open file
Result :
...
Get open filename
Asks Dynamo what the name of the currently open file is.
URL
http://localhost:1234/
Workspace/Current
Test this endpoint
Get open filename
Result :
...
Upload file
Instructs Dynamo to open the file found at the supplied filepath.
URL
http://localhost:1234/
Workspace/Upload
Test this endpoint
Choose a file…
No file selected.
Result :
...
Save file
Instructs Dynamo to save the currently open file.
URL
http://localhost:1234/
Workspace/Save
Test this endpoint
Save file
Result :
...
Close file
Instructs Dynamo to close the currently open file and returns the name of the file it closed.
URL
http://localhost:1234/
Workspace/Close
Test this endpoint
Close file
Result :
...
Run graph
Instructs Dynamo to run the currently open graph.
URL
http://localhost:1234/
Workspace/Run
Test this endpoint
Run graph
Result :
...
Nodes
Get nodes on canvas.
Get a list of all the nodes on the Dynamo canvas.
URL
http://localhost:1234/
Nodes/
Test this endpoint
Get nodes
Result :
...
Add node
Instructs Dynamo to add the specified node to the canvas.
URL
http://localhost:1234/
Nodes/Add/
{nodeName}
Test this endpoint
Add node
Result :
...
Clear
Instructs Dynamo to completely clear the canvas, deleting all nodes, annotations & groups.
URL
http://localhost:1234/
Nodes/Clear
Test this endpoint
Add node
Result :
...
Packages
Get packages
Gets the list of installed packages from Dynamo.
URL
http://localhost:1234/
Packages/
Test this endpoint
Get packages
Result :
...
Install package
Instructs Dynamo to install the specified package from the Dynamo Package Manager.
URL
http://localhost:1234/
Packages/Install/
{packagename}
Test this endpoint
Install package
Result :
...
Remove package
Instructs Dynamo to remove the specified package, using the Dynamo Package Manager.
URL
http://localhost:1234/
Packages/Remove/
{packagename}
Test this endpoint
Remove package
Result :
...


Fetches data from DataMarket.com, either as timeseries in zoo form (dmseries) or as long-form data frames (dmlist). Metadata including dimension structure is fetched with dminfo, or just the dimensions with dmdims.
| Version: | 0.6.5 |
| Depends: | R (≥ 2.10.0), zoo |
| Imports: | RCurl, RJSONIO |
| Published: | 2014-11-24 |
| Author: | Gunnlaugur Thor Briem |
| Maintainer: | Gunnlaugur Thor Briem <gthb at datamarket.com> |
| License: | MIT + file LICENSE |
| URL: | http://datamarket.com/api/lib/rdatamarket |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| In views: | TimeSeries |
| CRAN checks: | rdatamarket results |
| Reference manual: | rdatamarket.pdf |
| Package source: | rdatamarket_0.6.5.tar.gz |
| Windows binaries: | r-devel: rdatamarket_0.6.5.zip, r-release: rdatamarket_0.6.5.zip, r-oldrel: rdatamarket_0.6.5.zip |
| OS X binaries: | r-release: rdatamarket_0.6.5.tgz, r-oldrel: rdatamarket_0.6.5.tgz |
| Old sources: | rdatamarket archive |
| Reverse suggests: | LSTS |
Please use the canonical form https://CRAN.R-project.org/package=rdatamarket to link to this page.


The following options are also available both as function parameters or data attributes:
container
(new in v1.3.3) default is null (body). You can specify the container.
For example if you want to put it inside a modal box, you can set it to #myModal > .modal-dialog
placement
backdrop
if "false" there will be no backdrop,
if "invisible" backdrop will become invisible, otherwise visible
fixed
whether slider should be fixed or not
background
whether background should be dark or white
offset
whether slider should be below navbar or cover it
body_scroll
determines if body scroll is allowed when slider is visible
transition
disables or enables CSS3 transition of sliders
scroll_style
specifies scrollbar style if it's expected
...
or
$('.aside').ace_aside({
placement: 'top',
offset: true,
background: true,
body_scroll: false
});


Dear friend, Thanks for your concern to my proposal. I am Mr Mark Hernandez the linkman between the Organization For Petroleum Exporting Countries - OPEC and World Bank. I also attend OPEC meetings constantly in Geneva Switzerland on the auspices of World Bank. Through the sale of our allocated oil quota in OPEC, I was able to makeS$22.2million, which is currently deposited in a Security firm abroad. I want you to assist me to claim this money as I cannot claim it directly because i am still a Civil servant in active service, and the code of conduct bureau forbids me to acquire such huge amount of money. It is on this basis that I am contacting you for assistance, If You will be interested, and all claim documents will be processed, and sent to you. The documents with which the fund is deposited will be changed to reflect you as the new beneficiary so that you will be eligible to collect the fund on my behalf. I will give you 30% of the fund for this assistance, while 60% will be for me and 10% will be for expenses that may be incurred on both sides. I am aware of the international monitoring of all large-scale financial movements after the September 11th 2001 Terrorist attack on America (USA) and to avoid any state of financial Investigation I will provide a classified clearance paper from the relevant body, which will exonerate the money from drug, money laundered or terrorist related funds. Kindly respond to my proposal through this my private email on the receipt of your mail indicating interest. I want to assure you that this is 100% risk free. I will give you more details concerning this as soon as I received your swift response which must include your full names, address, occupation, age phone and fax number. Expecting your response. Yours sincerely, Mr Mark Hernandez.


Bafana Player Ratings v Sudan
by Soccer LadumaSoccer Laduma rates the individual performances of the Bafana Bafana players following a 1-0 win over Sudan in a 2021 Africa Cup of Nations qualifier on Sunday afternoon.
Tired of reading? Click through the gallery to see the ratings of the Bafana players.
RATINGS:
Ronwen Williams: 5/10
Didn't have much to do between the sticks on the day.
Thapelo Morena: 7/10
Morena was drafted to the right full-back position and he did not disappoint, especially going forward as he pace caused a lot of problems down the right flank.
Sifiso Hlanti: 5/10
Similarly to Morena, he did push forward on a few occasions, although his final ball was not at its usual standard on the day.
Erick Mathoho: 6/10
Mathoho made a few interceptions whenever Sudan embarked on a counter-attack and was always comfortable in possession of the ball.
Thulani Hlatshwayo: 6/10
The Bafana defence did not have much deal with on the day, but Hlatshwayo, like Mathoho, was alert to any danger on the counter.
Kamohelo Mokotjo: 6.5/10
Restored to the line-up after missing out on Thursday, Mokotjo dictated play from the onset and had a good understanding with the fellow attackers, which was evident in the link-up play.
Dean Furman: 6/10
Was a little guilty of giving possession away on a couple occasions in the first half, but it was another consistent showing from the SuperSport United midfielder overall.
Lebogang Phiri: 7/10
The French-based midfielder certainly gave a good account of himself in a rare start for Bafana. He linked up well with the other attackers and netted an impressive goal in the first half.
Percy Tau: 6.5/10
Much more livelier than he was on Thursday evening and was real nuisance to the Sudan right-back. Tau's link-up play with Phiri and Serero was impressive to watch.
Thulani Serero: 6.5/10
Serero was lively in the Bafana attack from the onset and was involved in a couple good attacking moves in the opening 45 minutes.
Lebogang Mothiba: 5/10
Replaced Grobler at the summit of the attack, but looked down on confidence after squandering two good chances in the first half. He was replaced just after the hour mark.
Substitutions:
Lebohang Manyama: 4/10
Replaced Phiri for the final 20 minutes, but didn't too much in the final third.
Kermit Erasmus: 4/10
Had a couple good sights at goal in his second-half cameo, but was denied by Sudan goalkeeper Ali Aboeshren.
Bradley Grobler: NA
Only played 15 minutes of the second half, but he did have a goal disallowed for offside in the final five minutes.


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| {{project.priority}} | {{project.techStack}} | {{project.projectCode}} | {{project.title}} | {{project.productOwner}} | {{project.sprints[0].sprintNo}} |
{{teamMember.role}}
{{teamMember.forename}} {{teamMember.surname}}
({{teamMember.email}})
- Certs: {{certification.shortDesc}} ({{certification.percentComplete}}%) - Stories: BA - {{baAllocations.length}} Dev - {{devAllocations.length}} Test - {{testAllocations.length}} - Story Points: BA - {{teamMember.baStoryPoints}} Dev - {{teamMember.devStoryPoints}} Test - {{teamMember.testStoryPoints}} Team of {{project.sprints[0].members.length || 0}} email the team |
|
| Total number of individuals this week: {{totalIndividualCount}} |


AWS EC2 Setup + node.js
Create Amazon Web Services(AWS) EC2 instance
General Outline
- Sign-up for free AWS account
- Follow guidelines (Steps 1 to 5) here
- Follow steps(1-3) here
- Open command line tool and connect to your instance
- Create filesystems on new device and mount it
- Install node.js and mongodb
- Configure system to save data to new EBS
Installing node.js
If you have followed general outlines up to step 3, then you should have your terminal open. If you haven't please do so now.
Next steps are from Kostas MAVROPALIAS blog (link at the bottom). Getting packages necessary for compiling node.js and clone from git. In terminal:
sudo yum install gcc-c++ make
sudo yum install openssl-devel
sudo yum install git
git clone git://github.com/joyent/node.git
cd node
After installing node.js we are installing Express for web framework. As of today, Jan 16, 2015, most current and stable version of node.js was v0.10.9. Side Note
Type 'git tag -l' to see list of all versions. If there are later versions just replace the version number following 'checkout' command. Node.js follows versioning schema of "even numbers are stable". So, v0.10.x are stable not v0.11.x In terminal:
git checkout v0.10.9
./configure
make
sudo make install
If your are familiar with Vi text editor:
sudo vi /etc/sudoers
#find the line that has:
#Defaults secure_path = /sbin:/bin:/usr/sbin:/usr/bin
#and add at the end. After '/urs/bin'
:/usr/local/bin
If not use nano text editor.
sudo nano /etc/sudoers
#it should open up text editor within terminal
#use arrow keys to navigate to line that has:
Defaults secure_path = /sbin:/bin:/usr/sbin:/usr/bin
#and add the follwoing at the end of the line after "/usr/bin"
:/usr/local/bin
#hit control x (to save and exit)
#overwrite? yes
#file name sudoers? enter
Next we need to install node package manager NPM.
git clone https://github.com/isaacs/npm.git
cd npm
sudo make install
If it gives you an error at "sudo make install" try again to force install. Or try using sudo make install -g
And that's it for installing node.js and npm. However, you still need to install Express and mongoDB on EBS volume.
Click herefor next step.
Sources from:
KOSTAS MAVROPALIAS's blog


Breakfast
| Eggs Benedict | $18 |
| Croque Monsieur | $18 |
| Croque Madame | $18 |
| Salmon Plate | $18 |
| Fruit Plate | $18 |
| Poached Eggs | $18 |
| Avocado Toast | $18 |
| Vegetarian Omelette | $18 |
| Cottage Cheese | $18 |
| Oats | $18 |
| Avocado Toast | $18 |
| Vegetarian Omelette | $18 |
| Cottage Cheese | $18 |
| Oats | $18 |
| Hash Browns | $6 |
| Waldorf Salad | $6 |
| Ham | $6 |
| Bacon | $6 |
| Cantelope | $6 |
| Milk | $4 |
| Chocolate Milk | $4 |
| Orange Juice | $4 |
| Cafe au lait | $4 |
Lunch
| Squash Soup | $18 |
| Al Pastor Taco | $18 |
| Polo Asado Taco | $18 |
| Salmon Sandwich | $18 |
| Rubber Chicken a la King | $18 |
| Battered Cod | $18 |
| Avocado Chicken Sandwich | $18 |
| Vegetarian Hot Dog | $18 |
| Kraft Dinner | $18 |
| California Rolls (2) | $18 |
| Prime Rib | $18 |
| Linquine a al Rubber Chicken | $18 |
| Roasted Newt Spleen | $18 |
| Puréed Oreos in Ghee | $18 |
| French Fries | $6 |
| Pounds of Poutine | $6 |
| Tons of Poutine | $16 |
| Galub Jamun | $6 |
| Laddu | $6 |
| Milk | $4 |
| Chocolate Milk | $4 |
| Orange Juice | $4 |
| Cafe au lait | $4 |
Dinner
| Ahi Tuna | $24 |
| Tofu Steak | $28 |
| Couscous With Beets | $14 |
| Salmon Carpachio | $28 |
| Bibimbap | $19 |
| Roast Beef | $18 |
| Kim Chi Udon | $12 |
| Soy Marinated Salmon | $28 |
| Octopus | $38 |
| Scallop Mayo Pizza | $18 |
| Avocado Toast | $11 |
| Vegetarian Omelette | $11 |
| Cottage Cheese | $6 |
| Oats | $18 |
| French Onion Soup | $10 |
| Waldorf Salad | $6 |
| Bregadeiro | $11 |
| Bacon | $6 |
| Cantelope | $6 |
| Milk | $4 |
| Chocolate Milk | $4 |
| Orange Juice | $4 |
| Cafe au lait | $4 |
Book a Table
Name
Phone Number
Date
Time
Number of Guests
LeCafe Restaurant
100 49th Street,
Vancouver BC
Open 24 hours.
For special
arrangements, please
604-323-5941.


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Frequently asked questions
Why is a Restaurant Business Plan Important?
Taking the time to put together a well thought out restaurant business plan is not something many wannabe restaurant operators do. The process might be a bit difficult and time consuming, but without a proper restaurant business plan, no investor will give you the funding to open your restaurant and even if they do you'll already be off to a rough start without the right mindset.
How to Write a Restaurant Business Plan?
Restaurant business plans vary from person to person, depending on the type of restaurant and and location. Below, we have highlighted the key steps you need to take when writing a restaurant business plan that are common across most restaurants.
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Book App
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About
Cohorted Voluntary Self Quarantine (CVSQ)
This is the page meant to provide you with additional information about the CVSQ initiative in several key areas.
Mission Statement
Website mission
- Enroll interested Health Care Workers (HCW) in CVSQ
- Provide information on this community-driven effort
Initiative's effort
- To offer physical and psychosocial support to healthcare workers (HCWs) and protection for their families and communities by providing dedicated HCW housing for HCWs in cities implementing CVSQ throughout the COVID-19 pandemic surge.
- Main service
- Quarantined housing (separate areas for 1) asymptomatic and working 2) symptomatic with testing pending, 3) +Covid19 not working, and 4) Post-tour of duty quarantine awaiting re-entry into home
- Secondary service
- Instrumental support (food, laundry, etc) Social support, pysch support, monitoring (epi surveillance)
Why is CVSQ housing important?
- The ability to protect physicians and their families is a big factor in the resilience of the healthcare system. Cohorted volunteer self quarantine (CVSQ) can reduce transmission in the Healthcare Workforce (HCW) families.
- Psychosocial support in CVSQ may also reduce trauma and PTSD in the HCW and among their families.
- The way the COVID-19 outbreak was ended in China was by isolating healthcare workers.
Research Highlights
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Articles on self-quarantine
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First Move engages young minds and teaches critical and creative thinking skills through the game of chess. While chess can be used at any age, First Move is not a “one size fits all” program. First Move is targeted to the academic standards of 2nd and 3rd grade students. Taught one hour per week by The Chess Lady (via video), classroom teachers facilitate the exercises; no chess experience is necessary.
STEM skills; critical and creative thinking. Students learn to analyze, plan and execute.
To 2nd and 3rd grade students, helping develop cognitive thinking skills.
Intellectual self-esteem and positive social behavior.
An academic and social advantage to all kids in every sub-group.
Research and standards based, “First Move increases math and reading aptitude.”
Students in fun, hands-on learning while connecting them to core subjects.
Our Chess Lady teaches, classroom teachers facilitate, one 50 minute lesson per week.
Students for success in school, the workplace and throughout life.
Chairman/CEO
Executive Director
Chief Financial Officer
Administrative Assistant
President WestRiver Capital, LLC
The Brinson Foundation
Founder and CEO Opera Solutions, LLC
Portfolio Manager BGI/Cascade Investments, Inc.
President MCM Financial
Founder, Oki Developments Co-Founder, Oki Foundation
(Shaun Alexander Fellow) Author, Principal Stoddart Fleischer Middle School
President and CEO ZMD AG Dresden
Managing Partner SVB Capital Funds
Partner Simonsen Vogt Wiig
Managing Partner Seneca Capital
President
Tudor Investment Corporation
President and CEO
DDB Worldwide Communications
Call Us Toll Free: 1.866.973.2342
Email us<EMAIL_ADDRESS>Send us a fax: 1.425.671.5009
Write to us: 13620 Ne 20th Street, Suite J Bellevue, WA 98005
Need help?: Email our webmaster


CARTOON: Trump and Schiff
by Michael RamirezInvestigating corruption.
Review-Journal editorial cartoonist Michael Ramirez is a two-time winner of the Pulitzer Prize and a three-time winner of the Sigma Delta Chi Award.
Investigating corruption.
Review-Journal editorial cartoonist Michael Ramirez is a two-time winner of the Pulitzer Prize and a three-time winner of the Sigma Delta Chi Award.


(Message filed_mail:754)
To: panz
cc: cdaniel, rwarritt, dptodey, zekai, jhodson, gutowski, flory
Subject: NFS
Date: Thu, 11 Sep 1997 09:33:10 CDT
From: "Douglas R. Fils"
Situation: NFS not working or working oddly
Reason: I had turned NFS during the file recovery to prevent people from trying to change files via NFS (plus has the item mounted read only without informing the NFS mount points that its status had changed) and not turned it back on, sorry.
Solution: Restarted NFS on the server and fixed the problem on all the UNIX machines in the ESSL lab including vincent stations.


Movies
Series
Kids
Watch List
Accounts
Klaus Peter
create
new
account
+
Login Name
First Name
Surname
Password
Day of birth
Age restriction
Enabled
Disabled


Please refer to TEP 115 for more information about the components
this application is used to test.
This application is used to test the functionality of the non mcu power
management component for non-virtualized devices. Changes to
MyComponentC
allow one to choose between different Power
Management policies.


Somewhere in time
When Mary Lennox was sent to Manor to live with her uncle everybody said she was the most disagreeablelooking child ever seen. It was true, too.  Her hair was yellow, and her face was yellow because she Read more


| Modifier and Type | Method and Description |
|---|---|
Replication.Action |
Replication.IDocumentOpenCallback.documentOpened(Document doc,
int noteId,
Optional<DominoException> status)
Called for each document retrieved
|
Replication.Action |
Replication.IObjectAllocCallback.objectAllocated(Document doc,
int oldRRV,
Optional<DominoException> status,
int objectSize)
Called exactly once for each object to provide the caller with information
about the object's size and ObjectID
|
Replication.Action |
Replication.IObjectWriteCallback.objectChunkWritten(Document doc,
int oldRRV,
Optional<DominoException> status,
ByteBuffer buffer,
int bufferSize)
Called for each "chunk" of each object
|
void |
Replication.saveDocument(Document doc,
boolean force,
boolean noRevisionHistory,
boolean keepModTime)
Saves a document with additional flags
|
| Modifier and Type | Method and Description |
|---|---|
Document |
Calendaring.openCalendarEntryDocument(Database dbMail,
String uid,
String recurId,
Collection<CalendarDocumentOpen> flags)
This is a method to get a document for an entry on the calendar.
The intent is that the note handle can be used to get information about an entry or instance or to write additional information to the entry or instance (beyond what is defined in iCalendar and/or available in this API). |
| Modifier and Type | Method and Description |
|---|---|
String |
Calendaring.getUIDfromDocument(Document document)
This is a convinience method that returns a UID for a calendar entry document.
NOTEID->UID is a many to one mapping since one or several documents may represent a calendar entry (especially if it repeats) and its related notices. |
| Modifier and Type | Interface and Description |
|---|---|
interface |
AutoCloseableDocument |
| Modifier and Type | Method and Description |
|---|---|
Document |
Document.appendItemValue(String itemName,
Object value)
Appends an item value to the document, leaving any other items of the same name in place.
|
Document |
Document.appendItemValue(String itemName,
Set<Item.ItemFlag> flags,
Object value)
Appends an item value to the document, leaving any other items of the same name in place.
|
Document |
Document.appendItemValue(String itemName,
Set<Item.ItemFlag> flags,
Object value,
boolean allowDataTypeChanges)
Appends an item value to the document, leaving any other items of the same name in place.
|
Document |
Document.copyAndEncrypt(UserId id,
Collection<Document.EncryptionMode> encryptionMode)
This function copies and encrypts (seals) the encryption enabled fields in a document
(including the document's file objects), using a
UserId .It can encrypt a document in several ways -- by using the Domino public key of the caller, by using specified secret encryption keys stored in the caller's ID, or by using the Domino public keys of specified users, if the document does not have any mime parts. The method decides which type of encryption to do based upon the setting of the flag passed to it in its encryptionMode argument.If the Document.EncryptionMode.ENCRYPT_WITH_USER_PUBLIC_KEY flag is set, it uses the
caller's public ID to encrypt the document.In this case, only the user who encodes the document can decrypt it. This feature allows an individual to protect information from anyone else. If, instead, the Document.EncryptionMode.ENCRYPT_WITH_USER_PUBLIC_KEY flag is not set,
then the function expects the document to contain a field named "SecretEncryptionKeys"
a field named "PublicEncryptionKeys", or both.Each field is either a ItemDataType.TYPE_TEXT or ItemDataType.TYPE_TEXT_LIST field."SecretEncryptionKeys" contains the name(s) of the secret encryption keys in the calling user's ID to be used to encrypt the document. This feature is intended to allow a group to encrypt some of the documents in a single database in a way that only they can decrypt them -- they must share the secret encryption keys among themselves first for this to work. "PublicEncryptionKeys" contains the name(s) of users, in canonical format. The document will be encrypted with each user's Domino public key. The user can then decrypt the document with the private key in the user's ID. This feature provides a way to encrypt documents, such as mail documents, for another user. The document must contain at least one encryption enabled item (an item with the Item.ItemFlag.ENCRYPTED flag set)
in order to be encrypted.If the note has mime parts and flag Document.EncryptionMode.ENCRYPT_SMIME_IF_MIME_PRESENT
is set, then it is SMIME encrypted.If the document is to be signed as well as encrypted, you must sign the document before using this method. |
Document |
Document.copyToDatabase(Database otherDb)
Copies the document to another database.
|
Document |
Database.createDocument() |
Document |
Database.createDocument(Set<Database.CreateFlags> flags) |
Document |
Attachment.getParent()
Returns the parent document of this attachment
|
Document |
Document.replaceItemValue(String itemName,
Object value)
Sets the value of an item value to the document, replacing any other items of the same name.
|
Document |
Document.replaceItemValue(String itemName,
Object value,
boolean allowDataTypeChanges)
Sets the value of an item value to the document, replacing any other items of the same name.
|
Document |
Document.replaceItemValue(String itemName,
Set<Item.ItemFlag> flags,
Object value)
Sets the value of an item value to the document, replacing any other items of the same name.
|
Document |
Document.replaceItemValue(String itemName,
Set<Item.ItemFlag> flags,
Object value,
boolean allowDataTypeChanges)
Sets the value of an item value to the document, replacing any other items of the same name.
|
Document |
Document.setDocumentClass(DocumentClass docClass)
Sets the class of this document.
|
| Modifier and Type | Method and Description |
|---|---|
Optional<Document> |
Agent.getAgentSavedData()
The returned document is created when you save an agent, and it is stored in
the same database as the agent.
The document replicates, but is not displayed in views. Each time you edit and re-save an agent, its saved data document is deleted and a new, blank one is created. |
Optional<Document> |
Database.getAgentSavedData(String agentName)
The returned document is created when you save an agent, and it is stored in
the same database as the agent.
The document replicates, but is not displayed in views. Each time you edit and re-save an agent, its saved data document is deleted and a new, blank one is created. |
Optional<Document> |
Database.getDocumentById(int noteId)
Opens a document in the database
|
Optional<Document> |
Database.getDocumentById(int noteId,
Set<Database.OpenDocumentMode> flags)
Opens a document in the database
|
Optional<Document> |
Database.getDocumentByPrimaryKey(String category,
String objectId)
Uses an efficient NSF lookup mechanism to find a document that
matches the primary key specified with
category and
objectKey . |
Optional<Document> |
Database.getDocumentByUNID(String unid)
Opens a document in the database
|
Optional<Document> |
Database.getDocumentByUNID(String unid,
Set<Database.OpenDocumentMode> flags)
Opens a document in the database
|
Optional<Document> |
Agent.AgentRunContext.getDocumentContext()
Returns the Document for Session.DocumentContext as a
Document |
Stream<Document> |
DbQueryResult.getDocuments() |
Optional<Document> |
Database.getProfileDocument(String profileName) |
Optional<Document> |
Database.getProfileDocument(String profileName,
String userName) |
Optional<Document> |
Database.getSoftDeletedDocumentById(int noteId)
Opens a soft deleted document in the database
|
Optional<Document> |
Database.getSoftDeletedDocumentByUNID(String unid)
Opens a soft deleted document in the database
|
Optional<Document> |
CollectionEntry.openDocument()
Open the database document for this collection entry
|
| Modifier and Type | Method and Description |
|---|---|
boolean |
Document.convertRichTextItem(String itemName,
Document targetNote,
String targetItemName,
IRichTextConversion... conversions)
Applies one of multiple conversions to a rich text item, writing the new version in the target document and item.
|
void |
Item.copyToDocument(Document doc,
boolean overwrite)
Copies this item to a new document, retaining the current name.
|
void |
Item.copyToDocument(Document doc,
String newItemName,
boolean overwrite)
Copies this item to a new document, with a new Item name.
|
List<Object> |
Formula.evaluate(Document doc)
Runs a formula on a document
|
Double |
Formula.evaluateAsNumber(Document doc,
Double defaultValue)
Runs a formula on a document and converts the result to a number
|
String |
Formula.evaluateAsString(Document doc)
Runs a formula on a document and converts the result to a string
|
Formula.FormulaExecutionResult |
Formula.evaluateExt(Document doc)
Formula execution that returns more information about the computation
result
|
void |
Document.makeResponse(Document doc)
Makes the document a response to another document.
|
Agent.AgentRunContext |
Agent.AgentRunContext.setDocumentContext(Document doc)
|
| Modifier and Type | Method and Description |
|---|---|
void |
DominoCollection.forEachDocument(int skip,
int count,
BiConsumer<Document,Loop> consumer) |
void |
CollectionSearchQuery.forEachDocument(int skip,
int count,
BiConsumer<Document,Loop> consumer) |
void |
DbQueryResult.forEachDocument(int skip,
int count,
BiConsumer<Document,Loop> consumer)
Iterates over each document in the search result
|
void |
Database.forEachProfileDocument(BiConsumer<Document,Loop> consumer)
Iterates over all profile documents in the database
|
void |
Database.forEachProfileDocument(String profileName,
BiConsumer<Document,Loop> consumer)
Iterates over all profile documents of the specified type in
the database
|
void |
Database.forEachProfileDocument(String profileName,
String userName,
BiConsumer<Document,Loop> consumer)
Iterates over all profile documents of the specified type/username in
the database
|
| Modifier and Type | Method and Description |
|---|---|
Document |
DesignElement.getDocument() |
| Modifier and Type | Method and Description |
|---|---|
default void |
DxlExporter.exportDocument(Document doc,
OutputStream out)
Export a single document into XML format.
|
void |
DxlExporter.exportDocument(Document doc,
Writer out)
Export a single document into XML format.
|
| Modifier and Type | Method and Description |
|---|---|
void |
RichTextHTMLConverter.readEmbeddedImage(Document doc,
String itemName,
Collection<String> options,
int itemIndex,
int itemOffset,
EmbeddedImage.HTMLImageReader callback)
Method to access images embedded in HTML conversion result.
|
RichTextHTMLConverter.Builder |
RichTextHTMLConverter.render(Document doc)
Renders a document as HTML (including its form) and gives access to embedded images.
|
RichTextHTMLConverter.Builder |
RichTextHTMLConverter.renderItem(Document doc,
String itemName)
Renders a rich text item as HTML and gives access to embedded images
|
| Modifier and Type | Method and Description |
|---|---|
default Document |
JsonDeserializer.fromJson(Object json)
Deserializes the provided implementation-specific JSON object into a document.
|
Document |
JsonDeserializer.fromJson(String json)
Deserializes the provided JSON object string into a document.
|
| Modifier and Type | Method and Description |
|---|---|
JsonDeserializer |
JsonDeserializer.target(Document document)
Sets the deserialization target to be an existing document in the target database.
|
Object |
JsonSerializer.toJson(Document doc)
Serializes the provided document as a JSON object using the implementation's
native JSON type.
|
default String |
JsonSerializer.toJsonString(Document doc)
Serializes the provided document as a JSON string.
|
| Modifier and Type | Method and Description |
|---|---|
void |
MimeWriter.convertToMime(Document doc,
RichTextMimeConversionSettings convertSettings)
This function converts all rich text items (type
ItemDataType.TYPE_COMPOSITE ) in the
document to MIME items (type ItemDataType.TYPE_MIME_PART ).It does not update the database; to update the database, save the document. |
Reader |
MimeReader.getMIMEReader(Document doc,
String itemName,
Set<MimeReader.ReadMimeDataType> dataType)
Returns a
Reader to read the MIME content |
jakarta.mail.internet.MimeMessage |
MimeReader.readMIME(Document doc,
String itemName,
Set<MimeReader.ReadMimeDataType> dataType)
Reads MIME content from a document and returns it as a
MimeMessage . |
void |
MimeReader.readMIME(Document doc,
String itemName,
Set<MimeReader.ReadMimeDataType> dataType,
Writer targetWriter)
Reads MIME content from a document into a
Writer in a streaming fashion. |
void |
MimeWriter.writeMime(Document doc,
String itemName,
jakarta.mail.Message mimeMessage,
Set<MimeWriter.WriteMimeDataType> dataType)
Writes the content of a
Message to a document. |
void |
MimeWriter.writeMime(Document doc,
String itemName,
Reader reader,
Set<MimeWriter.WriteMimeDataType> dataType)
Writes raw MIME content to a document.
|
| Modifier and Type | Method and Description |
|---|---|
Document |
RichTextWriter.getParentDocument()
Returns the document that will contain the
rich text data
|
| Modifier and Type | Method and Description |
|---|---|
RichTextWriter |
RichTextWriter.addDocLink(Document doc,
String comment)
This function inserts a DocLink for the specified
Document . |
RichTextWriter |
RichTextWriter.addRichText(Document doc,
String itemName)
Appends a rich text item from another document
|
| Modifier and Type | Method and Description |
|---|---|
Set<ECLCapability> |
Ecl.trustSignerOfDocument(Document doc,
DominoClient.ECLType type,
Collection<ECLCapability> capabilities,
boolean sessionOnly)
Method to modify the ECL for the signer of the specified document and add trusted
capabilities
|
Copyright © 2019–2021 HCL. All rights reserved.


Getting Go Going Continuously with Integration & Delivery on Codeship Pro - Stage III
In this article it’s time to dive into some heavier Go coding. Here are the key objectives.
- Gain some basic functionality that processes a basic JSON schema file as outlined in INSERT LINK TO PREVIOUS BLOG ENTRY HERE.
- Break out the code into some logical files to organize ongoing development.
- Add a few tests to confirm for the build & deployment as a gated step of the build.
Data Diluvii ad Populum
Now I’m going to pull together some basic processing for the data deluge for the people, or in Latin “data diluvii ad populum”. The first thing I’ll need is to add is one more dependency. By using Glide I’ll add that with the following command.
glide get github.com/Pallinder/go-randomdata
This will put the dependency into the glide.yaml
file. With this update the file now contents now look like this.
package: github.com/adron/datadiluvium
import:
- package: github.com/gorilla/mux
version: ^1.4.0
- package: github.com/Pallinder/go-randomdata
Once that’s added I’m going to also add the ingestion of a basic JSON schema file via one of the service end points.


Deprecated API(s) Dashboard
The audit tool output for the following packages were obtained by checking the image and the bundle manifests distributed. This report aims to try to identify the package distributions that can impact the users on 4.9.
Data from the image used
- Image name: registry.redhat.io/redhat/community-operator-index:v4.6
- Image ID: sha256:dec690587fa1aa70ae74fa2cb5adf8f7a54c6854971c0a4195070af89c28bd9e
- Image Created at: 2021-09-17T15:19:10.490020644Z
- From JSON report generated at: 2021-09-18
FAQ
1. Can my package still have bundles using deprecated API(s) that are not found by this check?
Yes. The check can only be made by looking at the manifests shipped in the bundle. Your operator might be using the deprecated/removed API(s) but not shipping its manifests on the bundle or have a dependency on another operator that is using them.
2. What action(s) should I take?
- Check Deprecated API Migration Guide (v1.22) and ensure that your projects have been migrated and are not using any deprecated/removed API(s)
- Ensure that any distribution which requires any deprecated API(s) in the OCP catalogs are configured with the Max OpenShift Version compatible (`olm.openShiftMaxVersion`) so it will only be distributed on OCP version(s) <= 4.8. Also, control which version the bundle is deployed to from OLM via the annotation/label `com.redhat.openshift.versions`. More info see: OKD/OpenShift Catalogs criteria and options
- OpenShift 4.8 introduces two new alerts that fire when an API that will be removed in the next release is in use. Check the event alerts of your Operators running on 4.8 and ensure that you do not find any warning about these API(s) still being used by it
3. What does it mean for a package to be in red, amber or green?


{{gettext('Attended calls.')}}
{{gettext('Calls not attended by agents.')}}
{{gettext('Call on line.')}}
{{gettext('Average time for answered calls.')}}
{{gettext('Average time waiting for calls.')}}


Snakypy is currently developing the website. In the meantime, you can keep an eye on our projects through Github.


Mapping with MapAttribute¶
A MapAttribute is used to define a mapping between the Class and its Properties into its equivalent database Object and Fields. Located at RepoDb.Attributes namespace.
Mapping a Class¶
By default, the Name of the Class is used as a default mapped Object from the database. However, if the database Object Name is different from the Class Name, then the MapAttribute is use to map it properly.
Below is a sample code that maps a class named Customer into a table named [dbo].[Customer] from the database.
[Map("[dbo].[Customer]")]
public class Customer : DataEntity
{
}
Mapping a Property¶
By default, the Name of the Property is used as a default mapped Field from the database Table, View or any ResultSet.
Below is a sample code that maps the property named Id into an CustomerId field of [dbo].[Customer] table.
[Map("[dbo].[Customer]")]
public class Customer : DataEntity
{
[Map("CustomerId")]
public int Id { get; set; }
}


This is development version of an experimental program written by a neuroscience academic, and therefore somewhat susceptible to coding bugs. Consequently, the author could not accept any responsibility for any bad things that might result from using it. But in effort to be helpful rather than legally defensive, I would be grateful for any suggestions or bug reports.


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xscreensaver-getimage(1) XScreenSaver manual xscreensaver-getimage(1) NAME xscreensaver-getimage - put some randomly-selected image on the root win‐ dow SYNOPSIS xscreensaver-getimage [-display host:display.screen] [--verbose] window- id [pixmap-id] DESCRIPTION The xscreensaver-getimage program is a helper program for the xscreen‐ saver hacks that manipulate images. This is not a user-level command. This program selects a random image, and puts it on the specified window or pixmap. This image might be a snapshot of the desktop; or a frame captured from the system's video input; or a randomly-selected image from disk. If only a window ID is specified, the image will be painted there. If both a window ID and a pixmap ID are specified, then the image will be painted on the pixmap; and the window may be modified as a side-effect. OPTIONS xscreensaver-getimage reads the ~/.xscreensaver file for configuration information. It uses these settings: grabDesktopImages Whether it is acceptable to grab snapshots of the desktop. The secu‐ rity paranoid might want to turn this off, to avoid letting people see (but not touch!) your desktop while the screen is locked. grabVideoFrames Whether it is acceptable to grab frames of video from the system's video input. Grabbing of video is done by invoking the xscreensaver- getimage-video(1) program. chooseRandomImages Whether it is acceptable to display random images found on disk. Selection and loading of images is done by invoking the xscreensaver- getimage-file(1) program. imageDirectory When loading images from disk, this is the directory to find them in. The directory will be searched recursively for images. It may also be the URL of an RSS or Atom feed, in which case a random image from that feed will be selected instead. The contents of the feed will be cached locally and refreshed periodically as needed. If none of the three options are set to True, then video colorbars will be displayed instead. BUGS When grabbing desktop images, the window argument will be unmapped and have its contents modified, causing flicker. (This does not happen when loading image files or video frames.) SEE ALSO X(1), xscreensaver(1) xscreensaver-demo(1) xscreensaver-getimage-file(1) xscreensaver-getimage-video(1) COPYRIGHT Copyright © 2001-2011 by Jamie Zawinski. Permission to use, copy, mod‐ ify, distribute, and sell this software and its documentation for any purpose is hereby granted without fee, provided that the above copyright notice appear in all copies and that both that copyright notice and this permission notice appear in supporting documentation. No representations are made about the suitability of this software for any purpose. It is provided "as is" without express or implied warranty. AUTHOR Jamie Zawinski<EMAIL_ADDRESS>14-Apr-01 X Version 11 5.15 (28-Sep-2011) xscreensaver-getimage(1)


A small tutorial that explains how you can clip map tile layers based on an external GeoJSON boundary in Leaflet.
When designing maps for our projects here at KLL, a very common request that we receive in the early stages of development of any map-based app, is to make the geographical area that is the focus of the project stand out.
In this post, I am going to walk you through a series of steps that will allow you to clip the standard OSM tilelayer based on a geographic boundary.
So what are we doing again?
Here is an image that showcases what we are trying to achieve by the end of this tutorial.
Notice how areas outside the city has a reduced opacity, allowing us to draw the user’s attention to all of the content inside the boundary.
Before we begin
This tutorial assumes a basic understanding of LeafletJS and its API. If you are not familiar with this framework, I urge you to go through its well curated collection of tutorials and API reference documentation.
I have also uploaded all of the resources used for this tutorial in the form of a github gist. You can view the code in this github gist.
Step 1: Wiring up a basic map
Let’s start by quickly wiring up a basic leaflet map for our use. For this, we will be following the same procedure as outlined in Leaflet’s official quick start guide, with the following differences:
- The bounding box and the zoom level will be set to around that of Neelakantha municipality.
- The tilelayer that we will be using will be different to the one provided in the guide.
Before we proceed, here’s a screenshot of what the output currently looks like:
As you may have noticed, not much has happened so far.
Step 2: Adding the base tile layer
Inside the script tag, we now create a new tile layer and add it to the map as follows.
Notice how I’ve set the opacity of baseTileLayer
to 0.2
. Here’s what the output looks like now:
Step 3: Loading the external GeoJSON boundary.
The next step involves making the GeoJSON boundary file available for use within our index.html
. For this we will have to make use of the $.ajax()
method available in jQuery. To do so, we first load jQuery as an external dependency onto the head section of our document, like so:
After this, we can now access the GeoJSON as follows:
Step 4: Making it pop!
The final step involves adding one more tilelayer onto the original map. However, in this case, the tile layer will only be visible inside the boundary. This is achieved my making use of an external leaflet plugin called ‘BoundaryCanvas’, which allows us to draw tiled raster layers with an arbitrary boundary (in our case, boundary.geojson
). You can learn more about its capabilities here.
We begin by loading the boundary canvas script within the head section of index.html
.
Finally, we add the additional tile layer inside the $.ajax()
call as follows:
If all goes well, here’s what you will see:
To make the municipality stand out a little more, let’s modify the leaflet container’s background color. To do this, let’s add a style tag inside the <head>
section of index.html
In the end, this is what we should have:
Cheers, Arogya


[1]
second time is top-notch but easily to store.
[2]
second time is top-notch but easily to when Samsung for something.


| 1 | /* | |
| 2 | * Licensed to the Apache Software Foundation (ASF) under one or more | |
| 3 | * contributor license agreements. See the NOTICE file distributed with | |
| 4 | * this work for additional information regarding copyright ownership. | |
| 5 | * The ASF licenses this file to You under the Apache License, Version 2.0 | |
| 6 | * (the "License"); you may not use this file except in compliance with | |
| 7 | * the License. You may obtain a copy of the License at | |
| 8 | * | |
| 9 | * http://www.apache.org/licenses/LICENSE-2.0 | |
| 10 | * | |
| 11 | * Unless required by applicable law or agreed to in writing, software | |
| 12 | * distributed under the License is distributed on an "AS IS" BASIS, | |
| 13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| 14 | * See the License for the specific language governing permissions and | |
| 15 | * limitations under the License. | |
| 16 | */ | |
| 17 | ||
| 18 | package org.apache.commons.math3.stat.correlation; | |
| 19 | ||
| 20 | import org.apache.commons.math3.exception.DimensionMismatchException; | |
| 21 | import org.apache.commons.math3.exception.MathIllegalArgumentException; | |
| 22 | import org.apache.commons.math3.exception.util.LocalizedFormats; | |
| 23 | import org.apache.commons.math3.linear.BlockRealMatrix; | |
| 24 | import org.apache.commons.math3.linear.RealMatrix; | |
| 25 | import org.apache.commons.math3.stat.ranking.NaturalRanking; | |
| 26 | import org.apache.commons.math3.stat.ranking.RankingAlgorithm; | |
| 27 | ||
| 28 | /** | |
| 29 | *
Spearman's rank correlation. This implementation performs a rank | |
| 30 | * transformation on the input data and then computes {@link PearsonsCorrelation} | |
| 31 | * on the ranked data.
 | |
| 32 | * | |
| 33 | *
By default, ranks are computed using {@link NaturalRanking} with default | |
| 34 | * strategies for handling NaNs and ties in the data (NaNs maximal, ties averaged). | |
| 35 | * The ranking algorithm can be set using a constructor argument.
 | |
| 36 | * | |
| 37 | * @since 2.0 | |
| 38 | * @version $Id: SpearmansCorrelation.java 1422313 2012-12-15 18:53:41Z psteitz $ | |
| 39 | */ | |
| 40 | ||
| 41 | public class SpearmansCorrelation { | |
| 42 | ||
| 43 | /** Input data */ | |
| 44 | private final RealMatrix data; | |
| 45 | ||
| 46 | /** Ranking algorithm */ | |
| 47 | private final RankingAlgorithm rankingAlgorithm; | |
| 48 | ||
| 49 | /** Rank correlation */ | |
| 50 | private final PearsonsCorrelation rankCorrelation; | |
| 51 | ||
| 52 | /** | |
| 53 | * Create a SpearmansCorrelation without data. | |
| 54 | */ | |
| 55 | public SpearmansCorrelation() { | |
| 56 | this(new NaturalRanking()); | |
| 57 | } | |
| 58 | ||
| 59 | /** | |
| 60 | * Create a SpearmansCorrelation with the given ranking algorithm. | |
| 61 | * | |
| 62 | * @param rankingAlgorithm ranking algorithm | |
| 63 | * @since 3.1 | |
| 64 | */ | |
| 65 | public SpearmansCorrelation(final RankingAlgorithm rankingAlgorithm) { | |
| 66 | data = null; | |
| 67 | this.rankingAlgorithm = rankingAlgorithm; | |
| 68 | rankCorrelation = null; | |
| 69 | } | |
| 70 | ||
| 71 | /** | |
| 72 | * Create a SpearmansCorrelation from the given data matrix. | |
| 73 | * | |
| 74 | * @param dataMatrix matrix of data with columns representing | |
| 75 | * variables to correlate | |
| 76 | */ | |
| 77 | public SpearmansCorrelation(final RealMatrix dataMatrix) { | |
| 78 | this(dataMatrix, new NaturalRanking()); | |
| 79 | } | |
| 80 | ||
| 81 | /** | |
| 82 | * Create a SpearmansCorrelation with the given input data matrix | |
| 83 | * and ranking algorithm. | |
| 84 | * | |
| 85 | * @param dataMatrix matrix of data with columns representing | |
| 86 | * variables to correlate | |
| 87 | * @param rankingAlgorithm ranking algorithm | |
| 88 | */ | |
| 89 | public SpearmansCorrelation(final RealMatrix dataMatrix, final RankingAlgorithm rankingAlgorithm) { | |
| 90 | this.data = dataMatrix.copy(); | |
| 91 | this.rankingAlgorithm = rankingAlgorithm; | |
| 92 | 1 | rankTransform(data); |
| 93 | rankCorrelation = new PearsonsCorrelation(data); | |
| 94 | } | |
| 95 | ||
| 96 | /** | |
| 97 | * Calculate the Spearman Rank Correlation Matrix. | |
| 98 | * | |
| 99 | * @return Spearman Rank Correlation Matrix | |
| 100 | */ | |
| 101 | public RealMatrix getCorrelationMatrix() { | |
| 102 | 1 | return rankCorrelation.getCorrelationMatrix(); |
| 103 | } | |
| 104 | ||
| 105 | /** | |
| 106 | * Returns a {@link PearsonsCorrelation} instance constructed from the | |
| 107 | * ranked input data. That is, | |
| 108 | * new SpearmansCorrelation(matrix).getRankCorrelation() | |
| 109 | * is equivalent to | |
| 110 | * new PearsonsCorrelation(rankTransform(matrix)) where | |
| 111 | * rankTransform(matrix) is the result of applying the | |
| 112 | * configured RankingAlgorithm to each of the columns of | |
| 113 | * matrix. | |
| 114 | * | |
| 115 | * @return PearsonsCorrelation among ranked column data | |
| 116 | */ | |
| 117 | public PearsonsCorrelation getRankCorrelation() { | |
| 118 | 1 | return rankCorrelation; |
| 119 | } | |
| 120 | ||
| 121 | /** | |
| 122 | * Computes the Spearman's rank correlation matrix for the columns of the | |
| 123 | * input matrix. | |
| 124 | * | |
| 125 | * @param matrix matrix with columns representing variables to correlate | |
| 126 | * @return correlation matrix | |
| 127 | */ | |
| 128 | public RealMatrix computeCorrelationMatrix(RealMatrix matrix) { | |
| 129 | RealMatrix matrixCopy = matrix.copy(); | |
| 130 | 1 | rankTransform(matrixCopy); |
| 131 | 1 | return new PearsonsCorrelation().computeCorrelationMatrix(matrixCopy); |
| 132 | } | |
| 133 | ||
| 134 | /** | |
| 135 | * Computes the Spearman's rank correlation matrix for the columns of the | |
| 136 | * input rectangular array. The columns of the array represent values | |
| 137 | * of variables to be correlated. | |
| 138 | * | |
| 139 | * @param matrix matrix with columns representing variables to correlate | |
| 140 | * @return correlation matrix | |
| 141 | */ | |
| 142 | public RealMatrix computeCorrelationMatrix(double[][] matrix) { | |
| 143 | 1 | return computeCorrelationMatrix(new BlockRealMatrix(matrix)); |
| 144 | } | |
| 145 | ||
| 146 | /** | |
| 147 | * Computes the Spearman's rank correlation coefficient between the two arrays. | |
| 148 | * | |
| 149 | * @param xArray first data array | |
| 150 | * @param yArray second data array | |
| 151 | * @return Returns Spearman's rank correlation coefficient for the two arrays | |
| 152 | * @throws DimensionMismatchException if the arrays lengths do not match | |
| 153 | * @throws MathIllegalArgumentException if the array length is less than 2 | |
| 154 | */ | |
| 155 | public double correlation(final double[] xArray, final double[] yArray) { | |
| 156 | 1 | if (xArray.length != yArray.length) { |
| 157 | throw new DimensionMismatchException(xArray.length, yArray.length); | |
| 158 | 2 | } else if (xArray.length < 2) { |
| 159 | throw new MathIllegalArgumentException(LocalizedFormats.INSUFFICIENT_DIMENSION, | |
| 160 | xArray.length, 2); | |
| 161 | } else { | |
| 162 | 1 | return new PearsonsCorrelation().correlation(rankingAlgorithm.rank(xArray), |
| 163 | rankingAlgorithm.rank(yArray)); | |
| 164 | } | |
| 165 | } | |
| 166 | ||
| 167 | /** | |
| 168 | * Applies rank transform to each of the columns of matrix | |
| 169 | * using the current rankingAlgorithm | |
| 170 | * | |
| 171 | * @param matrix matrix to transform | |
| 172 | */ | |
| 173 | private void rankTransform(RealMatrix matrix) { | |
| 174 | 3 | for (int i = 0; i < matrix.getColumnDimension(); i++) { |
| 175 | 1 | matrix.setColumn(i, rankingAlgorithm.rank(matrix.getColumn(i))); |
| 176 | } | |
| 177 | } | |
| 178 | } | |
Mutations | ||
| 92 |
removed call to org/apache/commons/math3/stat/correlation/SpearmansCorrelation::rankTransform : KILLED -> org.apache.commons.math3.stat.correlation.SpearmansRankCorrelationTest.testLongly(org.apache.commons.math3.stat.correlation.SpearmansRankCorrelationTest) |
|
| 102 |
mutated return of Object value for org/apache/commons/math3/stat/correlation/SpearmansCorrelation::getCorrelationMatrix to ( if (x != null) null else throw new RuntimeException ) : KILLED -> org.apache.commons.math3.stat.correlation.SpearmansRankCorrelationTest.testLongly(org.apache.commons.math3.stat.correlation.SpearmansRankCorrelationTest) |
|
| 118 |
mutated return of Object value for org/apache/commons/math3/stat/correlation/SpearmansCorrelation::getRankCorrelation to ( if (x != null) null else throw new RuntimeException ) : NO_COVERAGE |
|
| 130 |
removed call to org/apache/commons/math3/stat/correlation/SpearmansCorrelation::rankTransform : KILLED -> org.apache.commons.math3.stat.correlation.SpearmansRankCorrelationTest.testConsistency(org.apache.commons.math3.stat.correlation.SpearmansRankCorrelationTest) |
|
| 131 |
mutated return of Object value for org/apache/commons/math3/stat/correlation/SpearmansCorrelation::computeCorrelationMatrix to ( if (x != null) null else throw new RuntimeException ) : KILLED -> org.apache.commons.math3.stat.correlation.SpearmansRankCorrelationTest.testConsistency(org.apache.commons.math3.stat.correlation.SpearmansRankCorrelationTest) |
|
| 143 |
mutated return of Object value for org/apache/commons/math3/stat/correlation/SpearmansCorrelation::computeCorrelationMatrix to ( if (x != null) null else throw new RuntimeException ) : KILLED -> org.apache.commons.math3.stat.correlation.SpearmansRankCorrelationTest.testConsistency(org.apache.commons.math3.stat.correlation.SpearmansRankCorrelationTest) |
|
| 156 |
negated conditional : KILLED -> org.apache.commons.math3.stat.correlation.SpearmansRankCorrelationTest.testConstant(org.apache.commons.math3.stat.correlation.SpearmansRankCorrelationTest) |
|
| 158 |
changed conditional boundary : SURVIVED negated conditional : KILLED -> org.apache.commons.math3.stat.correlation.SpearmansRankCorrelationTest.testConstant(org.apache.commons.math3.stat.correlation.SpearmansRankCorrelationTest) |
|
| 162 |
replaced return of double value with -(x + 1) for org/apache/commons/math3/stat/correlation/SpearmansCorrelation::correlation : KILLED -> org.apache.commons.math3.stat.correlation.SpearmansRankCorrelationTest.testConstant(org.apache.commons.math3.stat.correlation.SpearmansRankCorrelationTest) |
|
| 174 |
Changed increment from 1 to -1 : KILLED -> org.apache.commons.math3.stat.correlation.SpearmansRankCorrelationTest.testLongly(org.apache.commons.math3.stat.correlation.SpearmansRankCorrelationTest) negated conditional : KILLED -> org.apache.commons.math3.stat.correlation.SpearmansRankCorrelationTest.testLongly(org.apache.commons.math3.stat.correlation.SpearmansRankCorrelationTest) changed conditional boundary : KILLED -> org.apache.commons.math3.stat.correlation.SpearmansRankCorrelationTest.testLongly(org.apache.commons.math3.stat.correlation.SpearmansRankCorrelationTest) |
|
| 175 |
removed call to org/apache/commons/math3/linear/RealMatrix::setColumn : KILLED -> org.apache.commons.math3.stat.correlation.SpearmansRankCorrelationTest.testLongly(org.apache.commons.math3.stat.correlation.SpearmansRankCorrelationTest) |


Babakzy
Babak Sadeghzadeh
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SciAuth is supported by the National Science Foundation under Grant No. 2114989. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.


# Panoptic Culture
![](assets/panoptic.png)
# Who are we ## Callum Fay ## Kevin Cameron ## Chris Skaaning
## What is DevOps to us - A *mindset* - Something that is never complete
## Living and breathing DevOps practices
## Learning to challenge our ways of thinking
## Learning to challenge peoples perception of stable
## The journey to a better way
## You're never really done
## Start small
## Embrace and understand failure
## Multiple paths and multiple tools
## Keep learning
## Keep pushing for change
## Where do we go from here? - Keep the drive relevant - Keep the message positive - Keep delivering business value from autonomy
## Things to follow - Always improve the way you work - Keep your CICD pipeline upto date with your code base and **not** seperate - Don't have a permenant "DevOps" team
## The current state of DevOps Groups | Adoption :-------------------------:|:-------------------------: ![groups](assets/groups.png) | ![adoption](assets/adoption.png)
## How does DevOps compare ![salary](assets/salary.png)


Main¶
Kecleon; cacheing through a simple store interface.
The design is based on a store where you only interact with one clerk. That clerk then goes off to get the items that you desire. This is similar to Argos’ model for customer service.
The clerk at the front desk only checks the warehouse for the item you want. If it’s not in the warehouse then they can check with a deliveries clerk if there are any that have yet to be unpacked. Finally if it’s not in deliveries then a transport clerk will be asked to get the product from another store into the current one. Finally if none are available then you’ll be instructed to come back another time.
This contrived example can be easily mapped to this library. The first
clerk could be a jobs.FileClerk
, the deliveries clerk can be
a jobs.Zip7Clerk
and finally the transport clerk can be a
jobs.WebClerk
.
After defining how the store moves goods internally, we can focus on where each item comes from. The good we want could be always be stored in aisle 1, shelf 2. It’s deliveries stored in deliveries section A and finally always come from strore #2.
In our example the item we want is post information, Posts.xml
.
It’s stored in the following archive codereview.stackexchange.com.7z
and is available from https://archive.org/download/stackexchange/codereview.stackexchange.com.7z
.
This would be simple to build with Kecleon.
from kecleon import Store, FileClerk, WebClerk
from kecleon.jobs import Zip7Clerk
store = Store(
warehouse=FileClerk(),
deliviers=Zip7Clerk(),
provider=WebClerk(),
)
posts = store.get(
warehouse='.cache/codereview/Posts.xml',
deliviers=('.cache/codereview/codereview.stackexchange.com.7z', 'Posts.xml'),
provider='https://archive.org/download/stackexchange/codereview.stackexchange.com.7z',
)
A lot of the terminology maps to store related terms.
- Clerk
An object that inherits from
base.Clerk
and interacts with their department’s items.- Department
Each clerk works in a set department. In the above example the
jobs.FileClerk
works in thewarehouse
department.- Location / Item
This is the location of the item. To be able to function properly clerks and departments needs to know where the item’s location is.
Kecleon allows importing some of the most common clerks from the top
level package. Some clerks it doesn’t include. These are accessible
from the kecleon.jobs
module. If this doesn’t include a clerk
you need then you can build your own by extending the objects in
kecleon.base
.


Time Series Analysis by State Space Methods statespace
¶
statsmodels.tsa.statespace
contains classes and functions that are
useful for time series analysis using state space methods.
A general state space model is of the form
where \(y_t\) refers to the observation vector at time \(t\), \(\alpha_t\) refers to the (unobserved) state vector at time \(t\), and where the irregular components are defined as
The remaining variables (\(Z_t, d_t, H_t, T_t, c_t, R_t, Q_t\)) in the equations are matrices describing the process. Their variable names and dimensions are as follows
Z : design \((k\_endog \times k\_states \times nobs)\)
d : obs_intercept \((k\_endog \times nobs)\)
H : obs_cov \((k\_endog \times k\_endog \times nobs)\)
T : transition \((k\_states \times k\_states \times nobs)\)
c : state_intercept \((k\_states \times nobs)\)
R : selection \((k\_states \times k\_posdef \times nobs)\)
Q : state_cov \((k\_posdef \times k\_posdef \times nobs)\)
In the case that one of the matrices is time-invariant (so that, for example, \(Z_t = Z_{t+1} ~ \forall ~ t\)), its last dimension may be of size \(1\) rather than size nobs.
This generic form encapsulates many of the most popular linear time series models (see below) and is very flexible, allowing estimation with missing observations, forecasting, impulse response functions, and much more.
Example: AR(2) model¶
An autoregressive model is a good introductory example to putting models in state space form. Recall that an AR(2) model is often written as:
This can be put into state space form in the following way:
Where
and
There are three unknown parameters in this model: \(\phi_1, \phi_2, \sigma^2\).
Models and Estimation¶
The following are the main estimation classes, which can be accessed through statsmodels.tsa.statespace.api and their result classes.
Seasonal Autoregressive Integrated Moving-Average with eXogenous regressors (SARIMAX)¶
The SARIMAX class is an example of a fully fledged model created using the statespace backend for estimation. SARIMAX can be used very similarly to tsa models, but works on a wider range of models by adding the estimation of additive and multiplicative seasonal effects, as well as arbitrary trend polynomials.
sarimax.SARIMAX (endog[, exog, order, …]) |
Seasonal AutoRegressive Integrated Moving Average with eXogenous regressors model |
sarimax.SARIMAXResults (model, params, …[, …]) |
Class to hold results from fitting an SARIMAX model. |
For an example of the use of this model, see the SARIMAX example notebook or the very brief code snippet below:
# Load the statsmodels api
import statsmodels.api as sm
# Load your dataset
endog = pd.read_csv('your/dataset/here.csv')
# We could fit an AR(2) model, described above
mod_ar2 = sm.tsa.SARIMAX(endog, order=(2,0,0))
# Note that mod_ar2 is an instance of the SARIMAX class
# Fit the model via maximum likelihood
res_ar2 = mod_ar2.fit()
# Note that res_ar2 is an instance of the SARIMAXResults class
# Show the summary of results
print(res_ar2.summary())
# We could also fit a more complicated model with seasonal components.
# As an example, here is an SARIMA(1,1,1) x (0,1,1,4):
mod_sarimax = sm.tsa.SARIMAX(endog, order=(1,1,1),
seasonal_order=(0,1,1,4))
res_sarimax = mod_sarimax.fit()
# Show the summary of results
print(res_sarimax.summary())
The results object has many of the attributes and methods you would expect from other Statsmodels results objects, including standard errors, z-statistics, and prediction / forecasting.
Behind the scenes, the SARIMAX model creates the design and transition matrices (and sometimes some of the other matrices) based on the model specification.
Unobserved Components¶
The UnobservedComponents class is another example of a statespace model.
structural.UnobservedComponents (endog[, …]) |
Univariate unobserved components time series model |
structural.UnobservedComponentsResults (…) |
Class to hold results from fitting an unobserved components model. |
For examples of the use of this model, see the example notebook or a notebook on using the unobserved components model to decompose a time series into a trend and cycle or the very brief code snippet below:
# Load the statsmodels api
import statsmodels.api as sm
# Load your dataset
endog = pd.read_csv('your/dataset/here.csv')
# Fit a local level model
mod_ll = sm.tsa.UnobservedComponents(endog, 'local level')
# Note that mod_ll is an instance of the UnobservedComponents class
# Fit the model via maximum likelihood
res_ll = mod_ll.fit()
# Note that res_ll is an instance of the UnobservedComponentsResults class
# Show the summary of results
print(res_ll.summary())
# Show a plot of the estimated level and trend component series
fig_ll = res_ll.plot_components()
# We could further add a damped stochastic cycle as follows
mod_cycle = sm.tsa.UnobservedComponents(endog, 'local level', cycle=True,
damped_cycle=true,
stochastic_cycle=True)
res_cycle = mod_cycle.fit()
# Show the summary of results
print(res_cycle.summary())
# Show a plot of the estimated level, trend, and cycle component series
fig_cycle = res_cycle.plot_components()
Vector Autoregressive Moving-Average with eXogenous regressors (VARMAX)¶
The VARMAX class is an example of a multivariate statespace model.
varmax.VARMAX (endog[, exog, order, trend, …]) |
Vector Autoregressive Moving Average with eXogenous regressors model |
varmax.VARMAXResults (model, params, …[, …]) |
Class to hold results from fitting an VARMAX model. |
For an example of the use of this model, see the VARMAX example notebook or the very brief code snippet below:
# Load the statsmodels api
import statsmodels.api as sm
# Load your (multivariate) dataset
endog = pd.read_csv('your/dataset/here.csv')
# Fit a local level model
mod_var1 = sm.tsa.VARMAX(endog, order=(1,0))
# Note that mod_var1 is an instance of the VARMAX class
# Fit the model via maximum likelihood
res_var1 = mod_var1.fit()
# Note that res_var1 is an instance of the VARMAXResults class
# Show the summary of results
print(res_var1.summary())
# Construct impulse responses
irfs = res_ll.impulse_responses(steps=10)
Dynamic Factor Models¶
The DynamicFactor class is another example of a multivariate statespace model.
dynamic_factor.DynamicFactor (endog, …[, …]) |
Dynamic factor model |
dynamic_factor.DynamicFactorResults (model, …) |
Class to hold results from fitting an DynamicFactor model. |
For an example of the use of this model, see the Dynamic Factor example notebook or the very brief code snippet below:
# Load the statsmodels api
import statsmodels.api as sm
# Load your dataset
endog = pd.read_csv('your/dataset/here.csv')
# Fit a local level model
mod_dfm = sm.tsa.DynamicFactor(endog, k_factors=1, factor_order=2)
# Note that mod_dfm is an instance of the DynamicFactor class
# Fit the model via maximum likelihood
res_dfm = mod_dfm.fit()
# Note that res_dfm is an instance of the DynamicFactorResults class
# Show the summary of results
print(res_ll.summary())
# Show a plot of the r^2 values from regressions of
# individual estimated factors on endogenous variables.
fig_dfm = res_ll.plot_coefficients_of_determination()
Custom state space models¶
The true power of the state space model is to allow the creation and estimation of custom models. Usually that is done by extending the following two classes, which bundle all of state space representation, Kalman filtering, and maximum likelihood fitting functionality for estimation and results output.
mlemodel.MLEModel (endog, k_states[, exog, …]) |
State space model for maximum likelihood estimation |
mlemodel.MLEResults (model, params, results) |
Class to hold results from fitting a state space model. |
For a basic example demonstrating creating and estimating a custom state space model, see the Local Linear Trend example notebook. For a more sophisticated example, see the source code for the SARIMAX and SARIMAXResults classes, which are built by extending MLEModel and MLEResults.
In simple cases, the model can be constructed entirely using the MLEModel class. For example, the AR(2) model from above could be constructed and estimated using only the following code:
import numpy as np
from scipy.signal import lfilter
import statsmodels.api as sm
# True model parameters
nobs = int(1e3)
true_phi = np.r_[0.5, -0.2]
true_sigma = 1**0.5
# Simulate a time series
np.random.seed(1234)
disturbances = np.random.normal(0, true_sigma, size=(nobs,))
endog = lfilter([1], np.r_[1, -true_phi], disturbances)
# Construct the model
class AR2(sm.tsa.statespace.MLEModel):
def __init__(self, endog):
# Initialize the state space model
super(AR2, self).__init__(endog, k_states=2, k_posdef=1,
initialization='stationary')
# Setup the fixed components of the state space representation
self['design'] = [1, 0]
self['transition'] = [[0, 0],
[1, 0]]
self['selection', 0, 0] = 1
# Describe how parameters enter the model
def update(self, params, transformed=True, **kwargs):
params = super(AR2, self).update(params, transformed, **kwargs)
self['transition', 0, :] = params[:2]
self['state_cov', 0, 0] = params[2]
# Specify start parameters and parameter names
@property
def start_params(self):
return [0,0,1] # these are very simple
# Create and fit the model
mod = AR2(endog)
res = mod.fit()
print(res.summary())
This results in the following summary table:
Statespace Model Results
==============================================================================
Dep. Variable: y No. Observations: 1000
Model: AR2 Log Likelihood -1389.437
Date: Wed, 26 Oct 2016 AIC 2784.874
Time: 00:42:03 BIC 2799.598
Sample: 0 HQIC 2790.470
- 1000
Covariance Type: opg
==============================================================================
coef std err z P>|z| [0.025 0.975]
------------------------------------------------------------------------------
param.0 0.4395 0.030 14.730 0.000 0.381 0.498
param.1 -0.2055 0.032 -6.523 0.000 -0.267 -0.144
param.2 0.9425 0.042 22.413 0.000 0.860 1.025
===================================================================================
Ljung-Box (Q): 24.25 Jarque-Bera (JB): 0.22
Prob(Q): 0.98 Prob(JB): 0.90
Heteroskedasticity (H): 1.05 Skew: -0.04
Prob(H) (two-sided): 0.66 Kurtosis: 3.02
===================================================================================
Warnings:
[1] Covariance matrix calculated using the outer product of gradients (complex-step).
The results object has many of the attributes and methods you would expect from other Statsmodels results objects, including standard errors, z-statistics, and prediction / forecasting.
More advanced usage is possible, including specifying parameter transformations, and specifing names for parameters for a more informative output summary.
State space representation and Kalman filtering¶
While creation of custom models will almost always be done by extending MLEModel and MLEResults, it can be useful to understand the superstructure behind those classes.
Maximum likelihood estimation requires evaluating the likelihood function of the model, and for models in state space form the likelihood function is evaluted as a byproduct of running the Kalman filter.
There are two classes used by MLEModel that facilitate specification of the state space model and Kalman filtering: Representation and KalmanFilter.
The Representation class is the piece where the state space model representation is defined. In simple terms, it holds the state space matrices (design, obs_intercept, etc.; see the introduction to state space models, above) and allows their manipulation.
FrozenRepresentation is the most basic results-type class, in that it takes a “snapshot” of the state space representation at any given time. See the class documentation for the full list of available attributes.
representation.Representation (k_endog, k_states) |
State space representation of a time series process |
representation.FrozenRepresentation (model) |
Frozen Statespace Model |
The KalmanFilter class is a subclass of Representation that provides
filtering capabilities. Once the state space representation matrices have been
constructed, the filter
method can be called, producing a FilterResults instance; FilterResults is
a subclass of FrozenRepresentation.
The FilterResults class not only holds a frozen representation of the state
space model (the design, transition, etc. matrices, as well as model
dimensions, etc.) but it also holds the filtering output, including the
filtered state
and
loglikelihood (see the class documentation for the full list of available
results). It also provides a
predict
method, which allows
in-sample prediction or out-of-sample forecasting. A similar method,
predict
, provides
additional prediction or forecasting results, including confidence intervals.
kalman_filter.KalmanFilter (k_endog, k_states) |
State space representation of a time series process, with Kalman filter |
kalman_filter.FilterResults (model) |
Results from applying the Kalman filter to a state space model. |
kalman_filter.PredictionResults (results, …) |
Results of in-sample and out-of-sample prediction for state space models generally |
The KalmanSmoother class is a subclass of KalmanFilter that provides
smoothing capabilities. Once the state space representation matrices have been
constructed, the filter
method can be called, producing a SmootherResults instance; SmootherResults
is a subclass of FilterResults.
The SmootherResults class holds all the output from FilterResults, but
also includes smoothing output, including the
smoothed state
and
loglikelihood (see the class documentation for the full list of available
results). Whereas “filtered” output at time t refers to estimates conditional
on observations up through time t, “smoothed” output refers to estimates
conditional on the entire set of observations in the dataset.
kalman_smoother.KalmanSmoother (k_endog, k_states) |
State space representation of a time series process, with Kalman filter and smoother. |
kalman_smoother.SmootherResults (model) |
Results from applying the Kalman smoother and/or filter to a state space model. |
Statespace diagnostics¶
Three diagnostic tests are available after estimation of any statespace model, whether built in or custom, to help assess whether the model conforms to the underlying statistical assumptions. These tests are:
A number of standard plots of regression residuals are available for the same
purpose. These can be produced using the command
plot_diagnostics
.
Statespace Tools¶
There are a variety of tools used for state space modeling or by the SARIMAX class:
tools.companion_matrix (polynomial) |
Create a companion matrix |
tools.diff (series[, k_diff, …]) |
Difference a series simply and/or seasonally along the zero-th axis. |
tools.is_invertible (polynomial[, threshold]) |
Determine if a polynomial is invertible. |
tools.constrain_stationary_univariate (…) |
Transform unconstrained parameters used by the optimizer to constrained parameters used in likelihood evaluation |
tools.unconstrain_stationary_univariate (…) |
Transform constrained parameters used in likelihood evaluation to unconstrained parameters used by the optimizer |
tools.constrain_stationary_multivariate (…) |
Transform unconstrained parameters used by the optimizer to constrained parameters used in likelihood evaluation for a vector autoregression. |
tools.unconstrain_stationary_multivariate (…) |
Transform constrained parameters used in likelihood evaluation to unconstrained parameters used by the optimizer |
tools.validate_matrix_shape (name, shape, …) |
Validate the shape of a possibly time-varying matrix, or raise an exception |
tools.validate_vector_shape (name, shape, …) |
Validate the shape of a possibly time-varying vector, or raise an exception |


Superagent's error response is very verbose, and tends to "drown" the actual JSON response received from the API. It might be advantageous to define our own error format that includes only a common subset of superagent's properties, so that the response value is less dependent on the transport library (relevant if we go the route of making this library transport-agnostic or multi-transport, e.g. if you can use it in the browser with jQuery for your AJAX instead of superagent)
Superagent's error response is very verbose, and tends to "drown" the actual JSON response received from the API. It might be advantageous to define our own error format that includes only a common subset of superagent's properties, so that the response value is less dependent on the transport library (relevant if we go the route of making this library transport-agnostic or multi-transport, e.g. if you can use it in the browser with jQuery for your AJAX instead of superagent)


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■ Application Name : CareWoker National Exam JP
■ Version Information : ver.2.0.0
■ Released: 2014/5
■ Development : YUKIKO NAGAOKA
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