|
Boat Wallet
0.0.1
An Ethereum compatible wallet C SDK for IoT
|
Define Basic Boatwallet types and include external header files. More...
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <stdarg.h>
#include <stdbool.h>
#include <unistd.h>
#include <time.h>
#include "sha3.h"
#include "secp256k1.h"
#include "wallet/boatoptions.h"
#include "wallet/boatexception.h"
Go to the source code of this file.
Data Structures | |
| struct | TAccountInfo |
| Account information. More... | |
| struct | TNetworkInfo |
| Blockchain network information. More... | |
| struct | TBoatWalletInfo |
| Wallet information. More... | |
| struct | TTxFieldVariable |
| common struct for variable length transaction fields More... | |
| struct | TTxFieldMax4B |
| common struct for 4-byte (32-bit) length transaction fields More... | |
| struct | TTxFieldMax32B |
| common struct for 32-byte (256-bit) length transaction fields More... | |
| struct | TTxFieldSig |
| ECDSA signature struct. More... | |
| struct | TRawtxFields |
| RAW transaction fields. More... | |
| struct | TTxInfo |
| Transaction information. More... | |
Macros | |
| #define | BOAT_OUT |
| #define | BOAT_IN |
| #define | BOAT_INOUT |
| #define | BOAT_TRUE 1 |
| #define | BOAT_FALSE 0 |
| #define | BOAT_REASONABLE_MAX_LEN 8192u |
Typedefs | |
| typedef bool | BOATBOOL |
| typedef char | CHAR |
| typedef unsigned char | UINT8 |
| typedef unsigned short | UINT16 |
| typedef unsigned int | UINT32 |
| typedef unsigned long long int | UINT64 |
| typedef signed char | SINT8 |
| typedef signed short | SINT16 |
| typedef signed int | SINT32 |
| typedef signed long long int | SINT64 |
| typedef UINT8 | UINT256ARRAY[32] |
| typedef SINT32 | BOAT_RESULT |
| typedef UINT8 | BoatAddress[20] |
| typedef struct TAccountInfo | AccountInfo |
| Account information. More... | |
| typedef struct TNetworkInfo | NetworkInfo |
| Blockchain network information. More... | |
| typedef struct TBoatWalletInfo | BoatWalletInfo |
| Wallet information. More... | |
| typedef struct TTxFieldVariable | TxFieldVariable |
| common struct for variable length transaction fields More... | |
| typedef struct TTxFieldMax4B | TxFieldMax4B |
| common struct for 4-byte (32-bit) length transaction fields More... | |
| typedef struct TTxFieldMax32B | TxFieldMax32B |
| common struct for 32-byte (256-bit) length transaction fields More... | |
| typedef struct TTxFieldSig | TxFieldSig |
| ECDSA signature struct. More... | |
| typedef struct TRawtxFields | RawtxFields |
| RAW transaction fields. More... | |
| typedef struct TTxInfo | TxInfo |
| Transaction information. More... | |
Define Basic Boatwallet types and include external header files.
boattypes.h defines types used in boatwallet.
| #define BOAT_FALSE 0 |
| #define BOAT_IN |
| #define BOAT_INOUT |
| #define BOAT_OUT |
| #define BOAT_REASONABLE_MAX_LEN 8192u |
Define a resonable max length in bytes for general checking for memory allocation related validation. The lower end the embedded system is, the smaller the length is.
| #define BOAT_TRUE 1 |
| typedef struct TAccountInfo AccountInfo |
Account information.
An account's only identifier is its private key. An address is calculated from the public key and the public key is calculated from the private key.
| typedef SINT32 BOAT_RESULT |
| typedef UINT8 BoatAddress[20] |
| typedef bool BOATBOOL |
| typedef struct TBoatWalletInfo BoatWalletInfo |
Wallet information.
Wallet information consists of account and block chain network information. Currently only one account per wallet is supported.
| typedef char CHAR |
| typedef struct TNetworkInfo NetworkInfo |
Blockchain network information.
EIP-155 (https://github.com/ethereum/EIPs/blob/master/EIPS/eip-155.md) requires chain ID of the network being part of the transaction before it's signed. If the network is NOT EIP-155 compatible, <eip155_compatibility> must be FALSE and <chain_id> is ignored. Otherwise the chain ID must be set.
<node_url_ptr> must include the protocol descriptor, IP address or URL name and port. For example, http://a.b.com:8545
| typedef struct TRawtxFields RawtxFields |
RAW transaction fields.
| typedef signed short SINT16 |
| typedef signed int SINT32 |
| typedef signed long long int SINT64 |
| typedef signed char SINT8 |
| typedef struct TTxFieldMax32B TxFieldMax32B |
common struct for 32-byte (256-bit) length transaction fields
| typedef struct TTxFieldMax4B TxFieldMax4B |
common struct for 4-byte (32-bit) length transaction fields
| typedef struct TTxFieldSig TxFieldSig |
ECDSA signature struct.
| typedef struct TTxFieldVariable TxFieldVariable |
common struct for variable length transaction fields
| typedef unsigned short UINT16 |
| typedef UINT8 UINT256ARRAY[32] |
| typedef unsigned int UINT32 |
| typedef unsigned long long int UINT64 |
| typedef unsigned char UINT8 |


[ aws . lex-runtime ]
Sends user input text to Amazon Lex at runtime. Amazon Lex uses the machine learning model that the service built for the application to interpret user input.
In response, Amazon Lex returns the next message to convey to the user (based on the context of the user interaction) and whether to expect a user response to the message (dialogState ). For example, consider the following response messages:
See also: AWS API Documentation
post-text
--bot-name <value>
--bot-alias <value>
--user-id <value>
[--session-attributes <value>]
--input-text <value>
[--cli-input-json <value>]
[--generate-cli-skeleton <value>]
Name of the Amazon Lex bot.
Alias of the Amazon Lex bot.
User ID of your client application. Typically, each of your application users should have a unique ID. Note the following considerations:
- If you want a user to start a conversation on one mobile device and continue the conversation on another device, you might choose a user-specific identifier, such as a login or Amazon Cognito user ID (assuming your application is using Amazon Cognito).
- If you want the same user to be able to have two independent conversations on two different devices, you might choose a device-specific identifier, such as device ID, or some globally unique identifier.
A session represents the dialog between a user and Amazon Lex. At runtime, a client application can pass contextual information (session attributes) in the request. For example, "FirstName" : "Joe" . Amazon Lex passes these session attributes to the AWS Lambda functions configured for the intent (see dialogCodeHook and fulfillmentActivity.codeHook in CreateIntent ).
In your Lambda function, you can use the session attributes for customization. Some examples are:
- In a pizza ordering application, if you can pass user location as a session attribute (for example, "Location" : "111 Maple street" ), your Lambda function might use this information to determine the closest pizzeria to place the order.
- Use session attributes to personalize prompts. For example, you pass in user name as a session attribute ("FirstName" : "Joe" ), you might configure subsequent prompts to refer to this attribute, as $session.FirstName" . At runtime, Amazon Lex substitutes a real value when it generates a prompt, such as "Hello Joe, what would you like to order?"
Note
Amazon Lex does not persist session attributes.
If the intent is configured without a Lambda function to process the intent (that is, the client application to process the intent), Amazon Lex simply returns the session attributes back to the client application.
If the intent is configured with a Lambda function to process the intent, Amazon Lex passes the incoming session attributes to the Lambda function. The Lambda function must return these session attributes if you want Amazon Lex to return them back to the client.
Shorthand Syntax:
KeyName1=string,KeyName2=string
JSON Syntax:
{"string": "string"
...}
input-text user entered (Amazon Lex interprets this text).
--cli-input-json (string) Performs service operation based on the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton. If other arguments are provided on the command line, the CLI values will override the JSON-provided values.
--generate-cli-skeleton (string) Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value input, prints a sample input JSON that can be used as an argument for --cli-input-json. If provided with the value output, it validates the command inputs and returns a sample output JSON for that command.
intentName -> (string)
Intent Amazon Lex inferred from the user input text. This is one of the intents configured for the bot.
slots -> (map)
Intent slots (name/value pairs) Amazon Lex detected so far from the user input in the conversation.
key -> (string)
value -> (string)
sessionAttributes -> (map)
Map of key value pairs representing the session specific context information.
key -> (string)
value -> (string)
message -> (string)
Prompt (or statement) to convey to the user. This is based on the application configuration and context. For example, if Amazon Lex did not understand the user intent, it sends the clarificationPrompt configured for the application. In another example, if the intent requires confirmation before taking the fulfillment action, it sends the confirmationPrompt . Suppose the Lambda function successfully fulfilled the intent, and sent a message to convey to the user. In that situation, Amazon Lex sends that message in the response.
dialogState -> (string)
Represents the message type to be conveyed to the user. For example:
- ElicitIntent – Amazon Lex wants to elicit user intent. For example, Amazon Lex did not understand the first utterances such as "I want to order pizza", which indicates the OrderPizza intent. If Amazon Lex doesn't understand the intent, it returns this dialogState . Another example is when your intent is configured with a follow up prompt. For example, after OrderPizza intent is fulfilled, the intent might have a follow up prompt such as " Do you want to order a drink or desert?" In this case, Amazon Lex returns this dialogState .
- ConfirmIntent – Amazon Lex is expecting a yes/no response from the user indicating whether to go ahead and fulfill the intent (for example, OK to go ahead and order the pizza). In addition to a yes/no reply, the user might provide a response with additional slot information (either new slot information or changes to the existing slot values). For example, "Yes, but change to thick crust." Amazon Lex understands the additional information and updates the intent slots accordingly. Consider another example. Before fulfilling an order, your application might prompt for confirmation such as "Do you want to place this pizza order?" A user might reply with "No, I want to order a drink." Amazon Lex recognizes the new OrderDrink intent.
- ElicitSlot – Amazon Lex is expecting a value of a slot for the current intent. For example, suppose Amazon Lex asks, "What size pizza would you like?" A user might reply with "Medium pepperoni pizza." Amazon Lex recognizes the size and the topping as the two separate slot values.
- Fulfilled – Conveys that the Lambda function has successfully fulfilled the intent. If Lambda function returns a statement/message to convey the fulfillment result, Amazon Lex passes this string to the client. If not, Amazon Lex looks for conclusionStatement that you configured for the intent. If both the Lambda function statement and the conclusionStatement are missing, Amazon Lex throws a bad request exception.
- ReadyForFulfillment – conveys that the client has to do the fulfillment work for the intent. This is the case when the current intent is configured with ReturnIntent as the fulfillmentActivity , where Amazon Lex returns this state to client.
- Failed – Conversation with the user failed. Some of the reasons for this dialogState are: after the configured number of attempts the user didn't provide an appropriate response, or the Lambda function failed to fulfill an intent.
slotToElicit -> (string)
If dialogState value is ElicitSlot , returns the name of the slot for which Amazon Lex is eliciting a value.
responseCard -> (structure)
Represents the options that the user has to respond to the current prompt. Amazon Lex sends this in the response only if the dialogState value indicates that a user response is expected.
version -> (string)
Version of response card format.contentType -> (string)
Content type of the response.genericAttachments -> (list)
An array of attachment objects representing options.
(structure)
Represents an option rendered to the user when a prompt is shown. It could be an image, a button, a link, or text.
title -> (string)
Title of the option.subTitle -> (string)
Subtitle shown below the title.attachmentLinkUrl -> (string)
imageUrl -> (string)
URL of an image that is displayed to the user.buttons -> (list)
List of options to show to the user.
(structure)
Represents an option to be shown on the client platform (Facebook, Slack, etc.)
text -> (string)
input-text visible to the user on the button.value -> (string)
Value sent to Amazon Lex when user clicks the button. For example, consider button text "NYC". When the user clicks the button, the value sent can be "New York City".


High School Dating
(Bearman, Moody, and Stovel, 2004)
(Image by Mark Newman)
|
|
Corporate E-Mail Communication
(Adamic and Adar, 2005)
.
|
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Trails of Flickr Users
in Manhattan
(Crandall et al. 2009)
|
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Prediction Market for the
2008 U.S. Presidential Election
(Iowa Electonic Markets, 2008)
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Networks, Crowds, and Markets:
Reasoning About a Highly Connected World
Over the past decade there has been a growing public fascination with
the complex "connectedness" of modern society. This connectedness
is found in many incarnations: in the rapid growth of the Internet and
the Web, in the ease with which global communication now takes place,
and in the ability of news and information as well as epidemics and
financial crises to spread around the world
with surprising speed and intensity.
These are phenomena that involve networks, incentives, and the
aggregate behavior of groups of people; they are based
on the links that connect us and the ways in which each of
our decisions can have subtle consequences for the outcomes of everyone else.
Networks, Crowds, and Markets
combines different scientific perspectives in its approach
to understanding networks and behavior. Drawing on ideas from
economics, sociology, computing and information science, and
applied mathematics, it describes the emerging field of study that
is growing at the interface of all these areas, addressing fundamental
questions about how the social, economic, and technological worlds
are connected.
The book is based on an inter-disciplinary course entitled
Networks
that we teach at Cornell.
The book, like the course, is designed at the introductory undergraduate level
with no formal prerequisites.
To support deeper explorations, most of
the chapters are supplemented with optional advanced sections.
The book is published by Cambridge University Press (2010);
for more information, please see
Cambridge's page for the book.
You can download a complete pre-publication draft of
Networks, Crowds, and Markets
here.
We welcome your feedback on the manuscript.
Contents (with links to individual chapters)
- Chapter 1. Overview
- 1.1 Aspects of Networks
- 1.2 Central Themes and Topics
Part I Graph Theory and Social Networks
- Chapter 2. Graphs
- 2.1 Basic Definitions
- 2.2 Paths and Connectivity
- 2.3 Distance and Breadth-First Search
- 2.4 Network Datasets: An Overview
- Chapter 3. Strong and Weak Ties
- 3.1 Triadic Closure
- 3.2 The Strength of Weak Ties
- 3.3 Tie Strength and Network Structure in Large-Scale Data
- 3.4 Tie Strength, Social Media, and Passive Engagement
- 3.5 Closure, Structural Holes, and Social Capital
- 3.6 Advanced Material: Betweenness Measures and Graph Partitioning
- Chapter 4. Networks in Their Surrounding Contexts
- 4.1 Homophily
- 4.2 Mechanisms Underlying Homophily: Selection and Social Influence
- 4.3 Affiliation
- 4.4 Tracking Link Formation in On-Line Data
- 4.5 A Spatial Model of Segregation
- Chapter 5. Positive and Negative Relationships
- 5.1 Structural Balance
- 5.2 Characterizing the Structure of Balanced Networks
- 5.3 Applications of Structural Balance
- 5.4 A Weaker Form of Structural Balance
- 5.5 Advanced Material: Generalizing the Definition of Structural Balance
Part II Game Theory
- Chapter 6. Games
- 6.1 What is a Game?
- 6.2 Reasoning about Behavior in a Game
- 6.3 Best Responses and Dominant Strategies
- 6.4 Nash Equilibrium
- 6.5 Multiple Equilibria: Coordination Games
- 6.6 Multiple Equilibria: The Hawk-Dove Game
- 6.7 Mixed Strategies
- 6.8 Mixed Strategies: Examples and Empirical Analysis
- 6.9 Pareto-Optimality and Social Optimality
- 6.10 Advanced Material: Dominated Strategies and Dynamic Games
- Chapter 7. Evolutionary Game Theory
- 7.1 Fitness as a Result of Interaction
- 7.2 Evolutionarily Stable Strategies
- 7.3 A General Description of Evolutionarily Stable Strategies
- 7.4 Relationship Between Evolutionary and Nash Equilibria
- 7.5 Evolutionarily Stable Mixed Strategies
- Chapter 8. Modeling Network Traffic using Game Theory
- 8.1 Traffic at Equilibrium
- 8.2 Braess's Paradox
- 8.3 Advanced Material: The Social Cost of Traffic at Equilibrium
- Chapter 9. Auctions
- 9.1 Types of Auctions
- 9.2 When are Auctions Appropriate?
- 9.3 Relationships between Different Auction Formats
- 9.4 Second-Price Auctions
- 9.5 First-Price Auctions and Other Formats
- 9.6 Common Values and The Winner's Curse
- 9.7 Advanced Material: Bidding Strategies in First-Price and All-Pay Auctions
Part III Markets and Strategic Interaction in Networks
- Chapter 10. Matching Markets
- 10.1 Bipartite Graphs and Perfect Matchings
- 10.2 Valuations and Optimal Assignments
- 10.3 Prices and the Market-Clearing Property
- 10.4 Constructing a Set of Market-Clearing Prices
- 10.5 How Does this Relate to Single-Item Auctions?
- 10.6 Advanced Material: A Proof of the Matching Theorem
- Chapter 11. Network Models of Markets with Intermediaries
- 11.1 Price-Setting in Markets
- 11.2 A Model of Trade on Networks
- 11.3 Equilibria in Trading Networks
- 11.4 Further Equilibrium Phenomena: Auctions and Ripple Effects
- 11.5 Social Welfare in Trading Networks
- 11.6 Trader Profits
- 11.7 Reflections on Trade with Intermediaries
- Chapter 12. Bargaining and Power in Networks
- 12.1 Power in Social Networks
- 12.2 Experimental Studies of Power and Exchange
- 12.3 Results of Network Exchange Experiments
- 12.4 A Connection to Buyer-Seller Networks
- 12.5 Modeling Two-Person Interaction: The Nash Bargaining Solution
- 12.6 Modeling Two-Person Interaction: The Ultimatum Game
- 12.7 Modeling Network Exchange: Stable Outcomes
- 12.8 Modeling Network Exchange: Balanced Outcomes
- 12.9 Advanced Material: A Game-Theoretic Approach to Bargaining
Part IV Information Networks and the World Wide Web
- Chapter 13. The Structure of the Web
- 13.1 The World Wide Web
- 13.2 Information Networks, Hypertext, and Associative Memory
- 13.3 The Web as a Directed Graph
- 13.4 The Bow-Tie Structure of the Web
- 13.5 The Emergence of Web 2.0
- Chapter 14. Link Analysis and Web Search
- 14.1 Searching the Web: The Problem of Ranking
- 14.2 Link Analysis using Hubs and Authorities
- 14.3 PageRank
- 14.4 Applying Link Analysis in Modern Web Search
- 14.5 Applications beyond the Web
- 14.6 Advanced Material: Spectral Analysis, Random Walks, and Web Search
- Chapter 15. Sponsored Search Markets
- 15.1 Advertising Tied to Search Behavior
- 15.2 Advertising as a Matching Market
- 15.3 Encouraging Truthful Bidding in Matching Markets: The VCG Principle
- 15.4 Analyzing the VCG Procedure: Truth-Telling as a Dominant Strategy
- 15.5 The Generalized Second Price Auction
- 15.6 Equilibria of the Generalized Second Price Auction
- 15.7 Ad Quality
- 15.8 Complex Queries and Interactions Among Keywords
- 15.9 Advanced Material: VCG Prices and the Market-Clearing Property
Part V Network Dynamics: Population Models
- Chapter 16. Information Cascades
- 16.1 Following the Crowd
- 16.2 A Simple Herding Experiment
- 16.3 Bayes' Rule: A Model of Decision-Making Under Uncertainty
- 16.4 Bayes' Rule in the Herding Experiment
- 16.5 A Simple, General Cascade Model
- 16.6 Sequential Decision-Making and Cascades
- 16.7 Lessons from Cascades
- Chapter 17. Network Effects
- 17.1 The Economy Without Network Effects
- 17.2 The Economy with Network Effects
- 17.3 Stability, Instability, and Tipping Points
- 17.4 A Dynamic View of the Market
- 17.5 Industries with Network Goods
- 17.6 Mixing Individual Effects with Population-Level Effects
- 17.7 Advanced Material: Negative Externalities and The El Farol Bar Problem
- Chapter 18. Power Laws and Rich-Get-Richer Phenomena
- 18.1 Popularity as a Network Phenomenon
- 18.2 Power Laws
- 18.3 Rich-Get-Richer Models
- 18.4 The Unpredictability of Rich-Get-Richer Effects
- 18.5 The Long Tail
- 18.6 The Effect of Search Tools and Recommendation Systems
- 18.7 Advanced Material: Analysis of Rich-Get-Richer Processes
Part VI Network Dynamics: Structural Models
- Chapter 19. Cascading Behavior in Networks
- 19.1 Diffusion in Networks
- 19.2 Modeling Diffusion through a Network
- 19.3 Cascades and Clusters
- 19.4 Diffusion, Thresholds, and the Role of Weak Ties
- 19.5 Extensions of the Basic Cascade Model
- 19.6 Knowledge, Thresholds, and Collective Action
- 19.7 Advanced Material: The Cascade Capacity
- Chapter 20. The Small-World Phenomenon
- 20.1 Six Degrees of Separation
- 20.2 Structure and Randomness
- 20.3 Decentralized Search
- 20.4 Empirical Analysis and Generalized Models
- 20.5 Core-Periphery Structures and Difficulties in Decentralized Search
- 20.6 Advanced Material: Analysis of Decentralized Search
- Chapter 21. Epidemics
- 21.1 Diseases and the Networks that Transmit Them
- 21.2 Branching Processes
- 21.3 The SIR Epidemic Model
- 21.4 The SIS Epidemic Model
- 21.5 Synchronization
- 21.6 Transient Contacts and the Dangers of Concurrency
- 21.7 Genealogy, Genetic Inheritance, and Mitochondrial Eve
- 21.8 Advanced Material: Analysis of Branching and Coalescent Processes
Part VII Institutions and Aggregate Behavior
- Chapter 22. Markets and Information
- 22.1 Markets with Exogenous Events
- 22.2 Horse Races, Betting, and Beliefs
- 22.3 Aggregate Beliefs and the ``Wisdom of Crowds''
- 22.4 Prediction Markets and Stock Markets
- 22.5 Markets with Endogenous Events
- 22.6 The Market for Lemons
- 22.7 Asymmetric Information in Other Markets
- 22.8 Signaling Quality
- 22.9 Quality Uncertainty On-Line: Reputation Systems and Other Mechanisms
- 22.10 Advanced Material: Wealth Dynamics in Markets
- Chapter 23. Voting
- 23.1 Voting for Group Decision-Making
- 23.2 Individual Preferences
- 23.3 Voting Systems: Majority Rule
- 23.4 Voting Systems: Positional Voting
- 23.5 Arrow's Impossibility Theorem
- 23.6 Single-Peaked Preferences and the Median Voter Theorem
- 23.7 Voting as a Form of Information Aggregation
- 23.8 Insincere Voting for Information Aggregation
- 23.9 Jury Decisions and the Unanimity Rule
- 23.10 Sequential Voting and the Relation to Information Cascades
- 23.11 Advanced Material: A Proof of Arrow's Impossibility Theorem
- Chapter 24. Property Rights
- 24.1 Externalities and the Coase Theorem
- 24.2 The Tragedy of the Commons
- 24.3 Intellectual Property
Bibliography


--- layout: post title: shpank crøss stöck flat pack on your back date: '2009-11-09T22:10:22+00:00' tags: [] tumblr_url: http://backlog.robbevan.com/post/238436470/shpank-crøss-stöck-flat-pack-on-your-back ---
SHPANK, CRØSS & STÖCK: Flat-pack on your back — Bookkake


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Images successfully uploaded.
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This functions generates a scatter plot and projected histograms to both axes.
Plots age versus a given quantity.
Plots luminosity functions at different redshifts. Pulls data from an sqlite3 database.
| author: | Sami Niemi |
|---|
| Parameters: |
|
|---|
| Parameters: |
|
|---|
| Parameters: |
|
|---|
| Parameters: |
|
|---|
Calculates a differential function from data.
160 (arcminutes squared) = 0.0444444444 square degrees Simulation was 10 times the GOODS realization, so area = 0.44444444, thus, the weighting is 1/0.44444444 i.e. 2.25.
| Parameters: |
|
|---|
160 (arcminutes squared) = 0.0444444444 square degrees Simulation was 10 times the GOODS realization, so area = 0.44444444, thus, the weighting is 1/0.44444444 i.e. 2.25.
| Parameters: |
|
|---|
160 (arcminutes squared) = 0.0444444444 square degrees Simulation was 10 times the GOODS realization, so area = 0.44444444, thus, the weighting is 1/0.44444444 i.e. 2.25.
| Parameters: |
|
|---|
Plots
Plots
Plots
Plots pacs 160 flux versus bolometric luminosity
Plots pacs 160 flux versus dust luminosity
Plots
Plots
Plots
Plots
Plots
Plots
Plots SFR
Plots SSFR.
Plots
Plots
Plots
Plots star formation rate as a function of total IR luminosity. Uses KDE to plot contours using the probability density function.
Plots size versus a given quantity.
Plots size versus a given quantity.
| todo: | fix the comoving volume calculation. |
|---|
Take a look the luminosity function plotting...
| author: | Sami Niemi |
|---|
160 square arcminutes in steradians = 1.354*10**-5 sr (steradians) Simulation was 10 times the GOODS realization, so the solid angle is 1.354*10**-4
| Parameters: |
|
|---|


{% load i18n %}
{% trans 'In this example we call an asynchronous task on the server that counts to the provided number and sleeps for 1 second in every iteration.' %}
{% trans 'Using AJAX we will create an asynchronous task on the client that will check the status of the task in the server in intervals of 500ms until it is completed.' %}
{% trans 'This text will change when the AJAX process starts...' %}


Welcome!
From this page you can begin your journey in many ways
- You can go through the adventure
- You can read the about page
- You can contemplate how to pronounce the word "Encyclopædia"
- You can view the map, which acts as a guide through the pages
- You can view the land of abandoned things, where I'm going to put objectives that I don't actually want to use
- ... and finally, can you find the secret?


Recipes
py2app includes a mechanism for working around package incompatibilities,
and stripping unwanted dependencies automatically. These are called recipes.
A future version of py2app will support packaging of Python Eggs. Once
this is established, recipes will be obsolete since eggs contain all of the
metadata needed to build a working standalone application.
Common causes for incompatibility
Some Python packages are written in such a way that they aren’t compatible
with being packaged. There are two main causes of this:
- Using __import__ or otherwise importing code without usage of the
import statement.
- Requiring in-package data files
Built-in recipes
- cjkcodecs:
- All codecs in the package are imported.
- docutils:
- Several of its internal components are automatically imported
(languages, parsers, readers, writers,
parsers.rst.directives, parsers.rst.langauges).
- matplotlib:
- A dependency on pytz.zoneinfo.UTC is implied, and the matplotlib
package is included in its entirety out of the zip file.
- numpy:
- The numpy package is included in its entirety out of the zip file.
- PIL:
- Locates and includes all image plugins (Python modules that end with
ImagePlugin.py), removes unwanted dependencies on Tkinter.
- pydoc:
- The implicit references on the several modules are removed (Tkinter,
tty, BaseHTTPServer, mimetools, select, threading,
ic, getopt, nturl2path).
- pygame:
- Several data files that are included in the zip file where pygame can
find them (freesansbold.ttf, pygame_icon.tiff,
pygame_icon.icns).
- PyOpenGL:
- If the installed version of PyOpenGL reads a version file to determine
its version, then the OpenGL package is included in its entirety out of
the zip file.
- scipy:
- The scipy and numpy packages are included in their entirety
out of the zip file.
- sip:
- If sip is detected, then all sip-using packages are included
(e.g. PyQt).
Developing Recipes
py2app currently searches for recipes only in the py2app.recipes module.
A recipe is an object that implements a check(py2app_cmd, modulegraph)
method.
- py2app_cmd:
- The py2app command instance (a subclass of setuptools.Command).
See the source for py2app.build_app for reference.
- modulegraph:
- The modulegraph.modulegraph.ModuleGraph instance.
A recipe should return either None or a dict instance.
If a recipe returns None it should not have performed any actions with
side-effects, and it may be called again zero or more times.
If a recipe returns a dict instance, it will not be called again. The
returned dict may have any of these optional string keys:
- filters:
- A list of filter functions to be called with every module in the
modulegraph during flattening. If the filter returns False, the module
and any of its dependencies will not be included in the output. This is
similar in purpose to the excludes option, but can be any predicate
(e.g. to exclude all modules in a given path).
- loader_files:
- Used to include data files inside the site-packages.zip. This is a
list of 2-tuples: [(subdir, files), ...]. subdir is the path
within site-packages.zip and files is the list of files to include
in that directory.
- packages:
- A list of package names to be included in their entirety outside of the
site-packages.zip.
- prescripts:
- A list of additional Python scripts to run before initializing the main
script. This is often used to monkey-patch included modules so that they
work in a frozen environment. The prescripts may be module names,
file names, or file-like objects containing Python code (e.g. StringIO).
Note that if a file-like object is used, it will not currently be scanned
for additional dependencies.


"use strict";
/**************************
* Import important stuff *
**************************/
const InstructionPointer = require("./InstructionPointer");
/********************************
* The DirectionChangers object *
********************************/
/**
* Helper object for direction changers. Usage: `DirectionChangers[symbol](currentDirection)`. Returns the new direction
*/
const DirectionChangers = {
">": () => {
// New direction is east
return InstructionPointer.DIRECTION_EAST;
},
"<": () => {
// New direction is west
return InstructionPointer.DIRECTION_WEST;
},
"^": () => {
// New direction is north
return InstructionPointer.DIRECTION_NORTH;
},
"v": () => {
// New direction is south
return InstructionPointer.DIRECTION_SOUTH;
},
"/": (currentDirection) => {
// Diagonal mirror. Find new direction
let newDirection = null;
switch (currentDirection) {
case InstructionPointer.DIRECTION_EAST:
// New direction: North
newDirection = InstructionPointer.DIRECTION_NORTH;
break;
case InstructionPointer.DIRECTION_WEST:
// New direction: South
newDirection = InstructionPointer.DIRECTION_SOUTH;
break;
case InstructionPointer.DIRECTION_NORTH:
// New direction: East
newDirection = InstructionPointer.DIRECTION_EAST;
break;
case InstructionPointer.DIRECTION_SOUTH:
// New direction: West
newDirection = InstructionPointer.DIRECTION_WEST;
break;
}
return newDirection;
},
"\\": (currentDirection) => {
// Diagonal mirror the other way. Find new direction
let newDirection = null;
switch (currentDirection) {
case InstructionPointer.DIRECTION_EAST:
// New direction: South
newDirection = InstructionPointer.DIRECTION_SOUTH;
break;
case InstructionPointer.DIRECTION_WEST:
// New direction: North
newDirection = InstructionPointer.DIRECTION_NORTH;
break;
case InstructionPointer.DIRECTION_NORTH:
// New direction: West
newDirection = InstructionPointer.DIRECTION_WEST;
break;
case InstructionPointer.DIRECTION_SOUTH:
// New direction: East
newDirection = InstructionPointer.DIRECTION_EAST;
break;
}
return newDirection;
},
"|": (currentDirection) => {
// Vertical mirror. Ignore if current direction is north or south. Reverse otherwise
let newDirection = null;
switch (currentDirection) {
case InstructionPointer.DIRECTION_WEST:
// Reverse to east
newDirection = InstructionPointer.DIRECTION_EAST;
break;
case InstructionPointer.DIRECTION_EAST:
// Reverse to west
newDirection = InstructionPointer.DIRECTION_WEST;
break;
default:
// Keep going the current direction
newDirection = currentDirection;
break;
}
return newDirection;
},
"_": (currentDirection) => {
// Horizontal mirror. Ignore if current direction is east or west. Reverse otherwise
let newDirection = currentDirection;
switch (currentDirection) {
case InstructionPointer.DIRECTION_NORTH:
// Reverse to south
newDirection = InstructionPointer.DIRECTION_SOUTH;
break;
case InstructionPointer.DIRECTION_SOUTH:
// Reverse to north
newDirection = InstructionPointer.DIRECTION_NORTH;
break;
default:
// Keep going the current direction
newDirection = currentDirection;
break;
}
return newDirection;
},
"#": (currentDirection) => {
// Omnidirectional mirror. Reverse no matter what the current direction is
let newDirection = null;
switch (currentDirection) {
case InstructionPointer.DIRECTION_NORTH:
// Reverse to south
newDirection = InstructionPointer.DIRECTION_SOUTH;
break;
case InstructionPointer.DIRECTION_SOUTH:
// Reverse to north
newDirection = InstructionPointer.DIRECTION_NORTH;
break;
case InstructionPointer.DIRECTION_EAST:
// Reverse to west
newDirection = InstructionPointer.DIRECTION_WEST;
break;
case InstructionPointer.DIRECTION_WEST:
// Reverse to east
newDirection = InstructionPointer.DIRECTION_EAST;
break;
}
return newDirection;
},
"x": () => {
// Pick a new direction at random
const directions = [
InstructionPointer.DIRECTION_NORTH,
InstructionPointer.DIRECTION_SOUTH,
InstructionPointer.DIRECTION_WEST,
InstructionPointer.DIRECTION_EAST
];
const i = Math.floor(Math.random() * directions.length);
return directions[i];
}
};
/*************
* Export it *
*************/
module.exports = DirectionChangers;


def parse_defences(self, defences):
if "labsmooth" in defences:
self.labsmooth = True
else:
self.labsmooth = False
self.defences = defences
if defences:
pattern = re.compile("featsqueeze[1-8]?")
for d in defences:
if pattern.match(d):
self.feature_squeeze = True
try:


Chocolate Pizza
POSTED ON 15 DEC 2013/ DESSERTS.
For the flg-swirl:melt butter over medium heat in a saucepan.Add brown sugar and stir to dissolve. Halve
all of the figs and ross in the saucepan with water and lemon juice.Cook over medium, heat,stirring
frequently, until
you have a chunky-jammy mixture.Add salt with one or twp stirs,set aside and let cool completely.
Ice creamL in a small pot over medium heat, combine milk,and granulated sugar until sugar is completely
dissolved and the milk is just barely lukewarm. whisk in the egg yolks.set mixture in the fridge
and wit until the fig mixture is cooled.
using an ice cream machine,pure liquids into the frozen basin and process according to manufacture instruction,i.e,let pin and thicken for 20 minuets before adding mascarpone, fog jam mixture and the nuts. continue to process for +/- 10 minuets. pour semi-froze mixture into a pyrex dish or glass tupperware.freeze for at least two hours before serving.
Food enthusiast,photography fan. Add a pinch of raw foodism and that's
pretty much who i am


Connect to BIOLOGICAL BASIS OF BEHAVIOR-LPS in the Course Register.
BIOLOGICAL BASIS OF BEHAVIOR
BIBB-109 INTRO TO BRAIN & BEHAV 1 CU REGISTRATION REQUIRED FOR LEC, LAB LIVING WORLD SECTOR 601 LEC TR 5-6:30PM MCNB 110 MCLEAN J CROSS LISTED: PSYC-109 SECTION MAX: 10 MAX W/CROSS LIST: 20 LABORATORY 0 CU 602 LAB W 5-6:30PM TBA MCLEAN J CROSS LISTED: PSYC-109 SECTION MAX: 10 MAX W/CROSS LIST: 20 BIBB-249 COGNITIVE NEUROSCIENCE 1 CU ONLY OPEN TO LPS PB PRE-HEALTH STUDENTS 601 LEC M 4:30-7:30PM PSYL A30 NELSON H CROSS LISTED: PSYC-149 SECTION MAX: 0 MAX W/CROSS LIST: 0 BIBB-430 NEURO BASIS OF AUTISM 1 CU 601 LEC R 5-8PM WILL 24 LEITMAN V MAX: 0 BIBB-482 CLINICAL PSYCHOPHARMACOL 1 CU 601 SEM W 5-8PM PSYL C41 LEXOW N MAX: 0
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Room 221 Franklin Building
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Phone:<PHONE_NUMBER> Fax:<PHONE_NUMBER>
<EMAIL_ADDRESS>Updated: Sat Jan 17 08:30:02 2015


Andrew Burton
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Account# 30-123456789
Meter# 123456789
Account Alert: Threshold Exceeded
Dear Andrew Barton,
As of July 30, 2016, your account has exceeded the usage threshold of 214 kWh you established for your electrical service.
Cost-to-date
$26.12
Number of days into your billing cycle
20 days
Usage-to-date
214 kWh
For more account information, to find tips on lowering your bills, to make an online payment or modify your alerts, sign into MyAccount.
This is not your final bill. Account Alerts is a notification service of cost and/or energy usage threshold limits that you may customize on your account. Your regularly monthly bill is delivered via email or USPS as determined by your account preferences. If you would like to unsubscribe from email alerts, please log in to MyAccount and go to your Account Overview page.


Never give up on your dreams


In order to delete a category, a user right clicks the category to be deleted and is presented with the menu shown in Figure 1.
Figure 1: Right clicking a category.
Figure 2: Delete category dialog.
The user is presented with a prompt to verify that they want to delete the category.


Changeset 677 for mystic/examples
- Timestamp:
- 06/04/13 19:54:18 (3 years ago)
- Location:
- mystic/examples
- Files:
-
- 6 edited
-
TEST_ffitPP.py (modified) (1 diff)
-
TEST_ffitPP_b.py (modified) (1 diff)
-
buckshot_example06.py (modified) (1 diff)
-
ezmap_desolve_rosen.py (modified) (1 diff)
-
lattice_example06.py (modified) (1 diff)
-
mpmap_desolve_rosen.py (modified) (1 diff)
Legend:
- Unmodified
- Added
- Removed
-
mystic/examples/TEST_ffitPP.py
r674 r677 18 18 #from pathos.multiprocessing import ProcessingPool as Pool 19 19 from pathos.pp import ParallelPythonPool as Pool 20 pp_map = Pool().map21 20 22 21 solver = DifferentialEvolutionSolver2(ND, NP) 23 solver.SetMapper( pp_map)22 solver.SetMapper(Pool().map) 24 23 solver.SetRandomInitialPoints(min = [-100.0]*ND, max = [100.0]*ND) 25 24 solver.SetEvaluationLimits(generations=MAX_GENERATIONS) -
mystic/examples/TEST_ffitPP_b.py
r674 r677 45 45 #from pathos.multiprocessing import ProcessingPool as Pool 46 46 from pathos.pp import ParallelPythonPool as Pool 47 pp_map = Pool().map48 47 49 48 solver = DifferentialEvolutionSolver2(ND, NP) 50 solver.SetMapper( pp_map)49 solver.SetMapper(Pool().map) 51 50 solver.SetRandomInitialPoints(min = [-100.0]*ND, max = [100.0]*ND) 52 51 solver.SetEvaluationLimits(generations=MAX_GENERATIONS) -
mystic/examples/buckshot_example06.py
r630 r677 74 74 solver = BuckshotSolver(ndim, npts) 75 75 solver.SetNestedSolver(PowellDirectionalSolver) 76 #solver.SetMapper(ez_map) 76 #from pathos.multiprocessing import ProcessingPool as Pool 77 #solver.SetMapper(Pool().map) 77 78 solver.SetGenerationMonitor(stepmon) 78 79 solver.SetStrictRanges(min=[-300]*ndim, max=[300]*ndim) -
mystic/examples/ezmap_desolve_rosen.py
r674 r677 30 30 from mystic.tools import random_seed 31 31 32 #from raw_rosen import rosen as myCost # ez_map needsa helper function33 from mystic.models import rosen as myCost # ez_map2 doesn't require help32 #from raw_rosen import rosen as myCost # with a helper function 33 from mystic.models import rosen as myCost # without a helper function 34 34 35 35 ND = 3 -
mystic/examples/lattice_example06.py
r630 r677 75 75 solver = LatticeSolver(ndim, nbins) 76 76 solver.SetNestedSolver(PowellDirectionalSolver) 77 #solver.SetMapper(ez_map) 77 #from pathos.multiprocessing import ProcessingPool as Pool 78 #solver.SetMapper(Pool().map) 78 79 solver.SetGenerationMonitor(stepmon) 79 80 solver.SetStrictRanges(min=[-300]*ndim, max=[300]*ndim) -
mystic/examples/mpmap_desolve_rosen.py
r674 r677 29 29 from mystic.tools import random_seed 30 30 31 #from raw_rosen import rosen as myCost # ez_map needsa helper function32 from mystic.models import rosen as myCost # ez_map2 doesn't require help31 #from raw_rosen import rosen as myCost # with a helper function 32 from mystic.models import rosen as myCost # without a helper function 33 33 34 34 ND = 3
Note: See TracChangeset
for help on using the changeset viewer.


As a longtime user of coffee and yerba mate for my get-up-n-go.
In combination with
- Bupropion tapered off in preceding weeks
- soy lecithin/flax oil/fruit smoothy 1x day
Day 1 - 100 mg and I noticed very subtle increase in alertness and attention. Had some trouble falling to sleep that night, including some minor heart palpitations.
Then I took from 100 to 400 mg a day in 1-2 doses, for about 2 weeks.
Side Effects
Minor headache a couple of times (possible caffeine withdrawal or just dehydration?) and odd smelling pee after taking Modafinil on empty stomach. Slight reduction in appetite also. The appetite reduction also could be caffeine cessation related. In my experience caffeine use causes cravings of starch and carbs.
I went 1 week without have a single coffee and very little yerba mate and experienced no caffeine headaches or coffee urges. That is highly unusual for me.
Having sans-coffee 'fresh breath'! Ccoffee is a much stronger stimulant for me - it amps me up and slams me down more so than modafinil.
Coworker made a comment about the strong intensity of my concentration during this time (coincidence?)
Several instances I definitely noticed being 'in the zone' for a extended periods of time. This is surprising considering I was sleep deprived and not drinking coffee.
Metabolism
During exercise, the Modafinil really kicked in. A serious adrenaline rush and cheshire cat grin on my face after only a few minutes of bicycling.
Sleep
Unlike amphetamines and caffeine, modafinil does not conflict with my sleep at all, that is, after night 1. In fact I think I had a heightened sensitivity to sleep requirements. I think I pulled only 1 all nighter during this 2 week period. Other nights I slept anywhere from 2 hours to 10 hours. It's a strange feeling to be physically and mentally tired but not feeling drowsy at all. At those times I was able to acknowledge that feeling and lay down for some easy sleep. Even if dose had recently been taken! If I want to sleep it's no problem. If I don't want to sleep, then it's no problem to stay up.
Motivation, Creativity
Although it gets rid of drowsiness very effectively, it does not do much for my motivation and creativity. This is worse in a sleep deprived state- in fact it's quite boring to be awake for a long time unless I am motivated and creative as well.
Conversely my peak experiences with modafinil were definitely when taking it in combination with good sleep, exercise, and meals. This is reassuring - for me it could fit into a daily regimen very easily.
Looking forward to generic modafinil in the meantime I plan to try adrafinil.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


Validation
When your transformed cohort data has been uploaded into the joint database, please log in to the database and confirm that your data are inserted correctly.
For information on how to log in, please see
Please compare your locally transformed data to the insert in the database and validate the:
To validate the above, you can create a summary report by selecting the relevant data table and clicking Tools and Export > Reports > Summary. This summary report can be compared to the local summary statistics, sent with transformed data. If so desired, Simon Mathis Kønig will assist you in this process
Be aware that the number of variables might differ from the transformed data as all variables from the ESCAPE-NET variable lists are included in the database. Any additionally included variables not present in transformed data will be coded as “-2: not recorded” in the database.
Please fill in the validation document found here and send to data manager.


Presish Bhattachan
Biomedical Engineering at the University of Waterloo.
Searching for wonder in every turn.


digital HD video, color, sound. 5'03". Madeira (Portugal). 2013 - 2020
Where is your Happy Place? The Happy Madeira Map mapped Happy Places in Madeira in September 2013.
Today, the Happy Madeira Map will teach you how to build a Happy Place on earth.
First of all, you need earth.


Mauricio Toro wrote: > Can you give some information about how to run the BAB search with a > time limit? > I am interesting in that too. Please read the documentation on BAB and Stop objects, in particular TimeStop. Cheers, Guido


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{{ref improve|date=March 2013}} {{Infobox prepared food | name = Tom kha kai | image = | caption = | alternate_name = Chicken coconut soup, galangal soup | country = Thailand and Laos | region = | creator = | course = | type = Soup | served = hot | main_ingredient = Coconut milk, galangal, lemon grass, kaffir lime leaves, mushrooms and chicken | variations = | calories = | other = }}
Tom kha kai, tom kha gai or Thai coconut soup<ref>Crocker, B. (2014). Betty Crocker 20 Best Slow Cooker Soup and Stew Recipes. Houghton Mifflin Harcourt.</ref><ref>Tennefoss, K. (Ed.). (2010). 20 Awesome Soups You Can't Live Without. Kathleen Tennefoss.</ref><ref>BF Recipes. (2008). Just Wing It: Recipes Using Pre-Baked Rotisserie Chicken. AuthorHouse.</ref> ({{lang-th|ต้มข่าไก่}}, {{RTGS|tom kha kai}}, {{IPA-th|tôm kʰàː kàj|pron}}; Lao: ຕົ້ມຂ່າໄກ່, tom kha kai, {{IPA-lo|tôm.kʰāː.kāj|pron}}), literally "chicken galangal soup") is a spicy and sour hot soup with coconut milk in Thai cuisine and Lao cuisine.
Contents |
In Thailand, most tom kha kai recipes typically include coconut milk, galangal, kaffir lime leaves, lemongrass, Thai chili peppers, coriander (or dill weed), straw mushrooms (or shiitake or other mushrooms), chicken, fish sauce, and lime juice. Fried chilies are sometimes added.
In a Thai-style tom kha kai, dill weed is not used, whereas in a Lao-style tom kha kai, dill weed (phak si, {{lang-lo|ຜັກຊີ}}) is used. Dill weed is a common herb which is used in Lao cuisine. The Thais' answer to dill weed (known in Thailand as phak chi Lao ({{lang-th|ผักชีลาว}}), since it is known locally as a Lao herb) in Thai tom kha is coriander or cilantro (phak chi, {{lang-th|ผักชี}}).
There are other versions of tom kha kai made with seafood (tom kha thale, {{lang-th|ต้มข่าทะเล}}), mushrooms (tom kha het, {{lang-th|ต้มข่าเห็ด}}), pork (tom kha mu, {{lang-th|ต้มข่าหมู}}) and tofu (tom kha taohu, {{lang-th|ต้มข่าเต้าหู้}}).<ref>Der kleine Thaispeisen Katalog von khon_jaidee & Low</ref>
<references />
{{cookbook}}
{{Thai soups}} {{Cuisine of Thailand}} {{Lao cuisine}}


--- layout: page title: About header-img: "img/about-bg.png" ---
A former public policy professional turned web developer. Documenting my adventures in learning to code for your enjoyment. Enjoy!


For records with one match:
Visit Sherpa's definitions and terms
Romeo Colors
{% for key, value in color.items() %}
| {{key}} | {{value}} | {{color_pct[key]}} |
{% endfor %}
Versioning
| Pre-print archiving allowed: | {{counts['pre']}} | {{counts['pct_pre']}} |
| Post-print archiving allowed: | {{counts['post']}} | {{counts['pct_post']}} |
| Final PDF archiving allowed: | {{counts['pdf']}} | {{counts['pct_pdf']}} |
Single-match journals that allow final PDF archiving
{% for record in matches %}
{% if record[6]=='can' %}
- {{record[1]}}
{% endif %}
{% endfor %}
Single-match journals that allow post-print archiving
{% for record in matches %}
{% if record[5]=='can' %}
- {{record[1]}}
{% endif %}
{% endfor %}
Titles successfully matched
These records were successfully identified in Sherpa-ROMEO
{% for record in matches %}
{{record[1]}} appears {{checkcount[record[1]][1]}} times in this file
{% for entry in zip(names, record[0:9]) %}
{% if entry[0] in ['prearchiving','postarchiving','pdfarchiving'] %}
{% if entry[1] =='can' %}
- {{entry[0]}} : {{entry[1]}}
{% else %}
- {{entry[0]}} : {{entry[1]}}
{% endif %}
{% else %}
- {{entry[0]}} : {{entry[1]}}
{% endif %}
{% endfor %}
- conditions:
{% for item in record[9:-1] %}
- {{item}}
{% endfor %}
{% for key, value in record[-1].items() %}
- {{key}} : {{value}}
{% endfor %}
{% endfor %}
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Titles with multiple matches
There was more than one possible match for these records
{% for record in multiple %}
- {{record}} appears {{checkcount[record[0]][1]}} times in this file
{% endfor %}
These titles were found in the database
{% for record in mult_detail %}
{{record[1]}}
{% for entry in zip(names, record[0:9]) %}
{% if entry[0] in ['prearchiving','postarchiving','pdfarchiving'] %}
{% if entry[1] =='can' %}
- {{entry[0]}} : {{entry[1]}}
{% else %}
- {{entry[0]}} : {{entry[1]}}
{% endif %}
{% else %}
- {{entry[0]}} : {{entry[1]}}
{% endif %}
{% endfor %}
- conditions:
{% for item in record[9:-1] %}
- {{item}}
{% endfor %}
{% for key, value in record[-1].items() %}
- {{key}} : {{value}}
{% endfor %}
{% endfor %}
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- {{record[1]}} appears {{checkcount[record[1]][1]}} times
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- {{record[1]}} appears {{checkcount[record[1]][1]}} times
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Ofono Class Reference
Connection class to all the DBus-Proxies.
More...
#include <ofono.h>
List of all members.
Detailed Description
Connection class to all the DBus-Proxies.
Member Function Documentation
| void Ofono::answerCall |
( |
QString |
id |
) |
[slot] |
To be executed from QML.
- Parameters:
-
| void Ofono::callsChanged |
( |
|
) |
[signal] |
Emited whenever oFono DBus sends "Calls". The list of current calls changed. Used internally to emit either incomingCall() or outgoingCall()
| void Ofono::dial |
( |
QString |
number |
) |
[slot] |
To be executed from QML. DBus VoiceCallManager.Dial
- Parameters:
-
| number | The number to dial. |
| void Ofono::hangupCall |
( |
QString |
id |
) |
[slot] |
To be executed from QML.
- Parameters:
-
| void Ofono::incomingCall |
( |
QString |
number, |
|
|
QString |
voicecallId | |
|
) |
| | [signal] |
Emited whenever an incoming call is announced via oFono DBus.
| void Ofono::outgoingCall |
( |
QString |
number, |
|
|
QString |
voicecallId | |
|
) |
| | [signal] |
Emited whenever an outgoing call is announced via oFono DBus.
| void Ofono::processChangedCalls |
( |
|
) |
[slot] |
Slot to process internal signals to emit simpler signals for QML
| void Ofono::PropertyChanged |
( |
const QString & |
name, |
|
|
const QDBusVariant & |
value | |
|
) |
| | [slot] |
Slot for incoming DBus oFono signals
| void Ofono::setPowerOff |
( |
|
) |
[slot] |
To be executed from QML. Set the oFono "powered" property to "false"
| void Ofono::setPowerOn |
( |
|
) |
[slot] |
To be executed from QML. Set the oFono "powered" property to "true"
| VoiceCallState Ofono::translateState |
( |
QString |
state |
) |
[static] |
Just map the oFono call states to the c++ state enum If there is no matching state, it returns the enum state NONE (0)
Member Data Documentation
Updated list of all the current VoiceCalls in the system.
The documentation for this class was generated from the following files:


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GETKEYCODES
Section: Keyboard Support (8)Updated: 8 Nov 1994
Index Return to Main Contents
NAME
getkeycodes - print kernel scancode-to-keycode mapping tableSYNOPSIS
getkeycodesDESCRIPTION
The getkeycodes command prints the kernel scancode-to-keycode mapping table.OPTIONS
None.SEE ALSO
setkeycodes (8)
Index
This document was created by man2html, using the manual pages.
Time: 05:34:26 GMT, December 24, 2015


Desired output card sequence
(H1 (Hearts 1), DK (Diamond King), CJ (Clubs Joker), S3 (Spades 3))
{{inputDuplicates ? 'You entered duplicate cards' : '----' }}
♥
♦
♣
♠
{{getCardNumber(c)}}
Starting card sequence (Solving)
♥
♦
♣
♠
{{getCardNumber(c)}}
Number of required rotations on total {{solvedOutput.length}} cards
{{r.length}} -
{{$index ? ',' : ''}}{{r2}}
How does it work?
Lets assume i have a stack of 10 cards, arranged in a secret sequence (Starting card sequence).
- 1. Take one card out of the stack, and place it on the table.
- 2. Take another card out of the stack and place it at the bottom of the same stack.
- 3. Goto step 1, and repeat until all cards are over.
The cards on the table are in sequential order.
This program generates the card sequence required to get the desired output.
Thanks to a friend @pranav
Fork it @ https://github.com/craftpip/card-rotation-sequence
License MIT


Future Value Calculator
Total Investment
Annual Interest Rate
Number of Years
Future Value
calculate


The basic tool used most often for spectral analysis is the Fourier series. This representation is particularly suited to periodic functions and indeed makes the assumption that the series is periodic. Consider a function that repeats with period T, such that f(t) = f(t + T) = f(t + 2T) = f(t + nT). We seek to represent this function by f*(t), a superposition of sine and cosine waves with various frequencies having amplitudes {ak} and {bk}:
where the angular frequencies are
with the wavelengths λk obtained from the frequencies νk for observations over a period T. Where the measurements are made during motion through the field with speed V , the wavelengths λk are found from V = νkλk. Alternately, if the field is a spatial field, the wavelength λk is the natural Fourier component and the representation in terms of the spatial coordinate s is f*(s) = ∑k=-∞∞ckei2πs∕λk.
The coefficients ck can be determined from
as can be demonstrated by substituting f*(t) for f(t) in (9) and using the orthogonality relationships for the exponential functions (or equivalently for sine and cosine functions). If there are N observations in the time series, N coefficients in the representation (6) or (7) can match those observations exactly.


Aston Martin shares climb as HSBC says investors should buy its stock
by Joe CurtisAston Martin’s share price climbed today after HSBC advised investors to buy the troubled luxury car maker’s stock despite its latest loss.
The manufacturers of James Bond’s favourite ride swung to a £13.5m loss in its latest quarter as Brexit fears dampened demand in the UK and EMEA.
Read more: Aston Martin is hoping next year’s James Bond movie will boost its share price
But HSBC gave the company’s stock a ‘Buy’ rating. The firm has said 2020’s Bond movie, No Time to Die, should give sales a lift in the key market of China.
Aston Martin’s share price rose 3.9 per cent to 485.3p in early trading, after sharp rises at the end of last week despite an underwhelming set of results.
But Markets.com’s chief market analyst, Neil Wilson, expressed scepticism of HSBC’s new rating.

Aston Martin is sitting on an £800m debt pile, up a third from last December’s £560m. Meanwhile third quarter revenue slumped 11 per cent, while car production sank 16 per cent.
The firm has seen its share price plunge 75 per cent since its October 2018 debut of 1,900p to today’s 485.3p value.
Last week it warned that demand for its least pricey model, the Aston Martin Vantage, remains below its original targets.
Read more: Aston Martin swings to £13.5m loss as demand starts to dry up
It is now pinning its hopes on its first SUV model, the DBX, as part of a plan to launch seven cars in just seven years.
Meanwhile, April’s Bond movie release will feature four Aston Martins – the FB5, the V8 Saloon, the new DBS Superleggera and the Valhalla.


Anna and The King (1999)
Thailand, 1862. Back then it was called Siam. A great monarchy ruled by the powerful King Mongkut (Chow Yun Fat). He did everything his ways. Until Anna Leonowens (Jodie Foster) came.
This movie is a remake of The King and I (which I haven't seen), and based on a true story. Anna comes with her son Louie to teach the King's children. All 68 of them, coming from 23 mothers. Surely makes me wish I was the King. But instead of just teaching the kids, Anna also tries to "show" the King the ways of the world, which is better known as the ways of the English. Anna storms in as if she were a Spice Girl yelling Girl Power, standing up in front of the King, while the whole country goes down on their knees, saying things in to the King that even the closest advisors don't dare to, and in the end even prevents a war. Wow, she must be related to either Margaret Tatcher or Wonder Woman.
The scenery is absolutely great. Shot in Malaysia, it shows the beauty of nature and the beauty of the Siamese kingdom. Too bad that the movie concentrates too much on Anna's views, and not on the King's. The cultural impact of an Anna seems too much, especially for a Monarchy who did survive colonialism (Siam is the only South East Asian country who was never been colonized by another country). The kingdom has is own way of doing stuff, and Anna was forcing change upon it. No wonder that this movie is banned in Thailand, because it was insulting them.
I feel the same way what the Thais are feeling. You cannot change a culture by handing out copies of Uncle Tom's Cabin, or by teaching how an egg can fit a bottle. The true story was probably during a long span, and the moviemakers are putting that into a 2-and-a-half hour movietape. Not that I'm saying that it was impossible to happen, but if you're going to show a movie about culture, please show both sides of all the cultures. Not just the bad ones and replace them by the good ones (which is always the Western way).
Jodie Foster is as though as always, while Chow Yun Fat without his long leather jacket and guns looked different. He did have the charisma of a king, but at sometimes he didn't show the powers of a king. Or maybe this girlpower is way too much for him. So guys, be careful. Even a king can be helpless against girlpower.
A movie worth watching because of the scenery. Because of the Siamese kingdom and culture. Because of the 68 kids from 23 wives. And to learn another language, Siamese.
Indra Moeljadi is also under the control of girlpower
for more reviews: http://www.geocities.com/anakzaman
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


Functions to create matrix population models from a combination of data on stage/age transitions and Bayesian prior information. This compensates for structural problems caused by missing observatons of rare transitions.
raretrans is not currently available from CRAN, but you can install from github.
Code and data used to produce Raymond L. Tremblay, Andrew J. Tyre , Maria-Eglée Pérez, James D. Ackerman (in review) Population projections from holey matrices: Using prior information to estimate rare transition events is tagged v1.0.0, so:
Alternatively, download a package archive file from the release page.
Get the development version from github with:
If you want the vignettes, you have to add some additional arguments.
There are two main functions in this package, fill_transitions()
and fill_fertility()
. Both of them take a list of two matrices as their first argument, the population projection matrix decomposed into a matrix of the probability of transitions between stages, and a matrix describing the contribution to the next census via reproduction. These matrices can be constructed by hand, or created with popbio::projection_matrix(..., TF = TRUE)
from a data frame with transitions between stages for individuals. By default, they return a matrix ‘filled in’ with uninformative or uniform priors. Informative priors can be specified as well.
For detailed examples of using these functions with a single population see the vignette Working with a single population and transition. The vignette Effect of prior information on transition probabilities and fertilities shows how to work with a dataset of many populations and transitions, and produces all the figures for Tremblay et al. (submitted).
For an overview of population projection models generally, see Hal Caswell, 2001, Matrix Population Models: Construction, Analysis, and Interpretation.
Please note that the ‘raretrans’ project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.


A mobile site skin package called DotNetNuke.DarkKnightMobile is included with DNN. These skins are suitable for use for a mobile website. This skin package includes skin objects appropriate for an independent mobile website and skin objects that are appropriate for a mobile microsite.
Mobile Friendly Menu
The mobile friendly skin will present the website menu in two different styles in order to maximize the viewing experience on mobile devices.
Landscape Mode
For devices with a wide aspect ratio, the menu will show across the top of the page with the direct children pages showing as links above the main menu.
Portrait Mode
For devices with narrower aspect ratio, the menu will initially be hidden with a button which will expand to show the top level pages. Direct child pages will be shown in a stacked styled-menu at the bottom of the page.
Mobile Website
The mobile skin package will contain two types of mobile friendly skins, one for use with standalone mobile websites and one for use with microsites. The only difference between the two types of skins is what shows in the menu.
Standalone Mobile Website
Using the DarkKnightMobile - Home and DarkKnightMobile - Interior page skins. All pages of the website are shown in the mobile skin menu.
Website using DarkKnightMobile Skin for standalone mobile website shows ALL pages
MicroSite
Using the DarkKnightMobile - Microsite_Home and DarkKnightMobile - Microsite_Interior page skins.
Only child pages of the parent mobile page will show in the mobile skin menu.
Products - Mobile is our parent mobile page for this MicroSite
Mobile menu only shows the child pages of the Products-Mobile parent mobile page


mysqlbinlog
Utility for processing MySQL binary log files.
More information: home page
- Show events from a specific binary log file:
mysqlbinlog path/to/binlog
- Show entries from a binary log for a specific database:
mysqlbinlog --database database_name path/to/binlog
- Show events from a binary log between specific dates:
mysqlbinlog --start-datetime='2022-01-01 01:00:00' --stop-datetime='2022-02-01 01:00:00' path/to/binlog
- Show events from a binary log between specific positions:
mysqlbinlog --start-position=100 --stop-position=200 path/to/binlog
- Show binary log from a MySQL server on the given host:
mysqlbinlog --host=hostname path/to/binlog


Bases: esmond.api.client.util.AlertMixin, object
Core class to pull data from the rest api.
alias of ApiConnectWarning
Bases: esmond.api.client.util.AlertMixin, object
Compose filters using the defaults combined with local filters.
The defaults will be overwritten by filters with the same name in the local filters.
Convert named property back to epoch. Generally just for sending cgi params to the api.
Class to hold filtering/query options. This will be used by ApiConnect and also passed to all the encapsulation objects.
alias of ApiFiltersWarning
Bases: api.client.snmp.DataPayload
Class to encapsulate bulk data payload
alias of BulkDataPayloadWarning
Bases: object
Class to encapsulate and differentiate data from different devices, interfaces and direction/traffic endpoints when getting data back from a bulk request for interface data.
Bases: api.client.snmp.NodeInfo
Class to encapsulate data payload
alias of DataPayloadWarning
Bases: api.client.snmp.NodeInfo
Issue a call to the API to get a list of interfaces (via a generator) associated with the device this object refers to.
Class to encapsulate device information
alias of DeviceWarning
Bases: api.client.snmp.ApiNotFound
Bases: api.client.snmp.ApiNotFound
Bases: api.client.snmp.NodeInfo
Retrieve the traffic data and return the json response in a DataPayload object. If there is something wrong with the response (status/content) then issue a warning and return an empty object.
Class to encapsulate endpoint information
alias of EndpointWarning
Bases: api.client.snmp.ApiNotFound
Bases: api.client.snmp.NodeInfo
Generate and return a list of endpoints (via a generator) associated with this interface. Even though this does not ‘do work’ by issuing a call to the API, it is a get_ method just for consistency.
Class to encapsulate interface information
alias of InterfaceWarning
Bases: api.client.snmp.ApiNotFound
Bases: esmond.api.client.util.AlertMixin, object
Base class for encapsulation objects
alias of NodeInfoWarning
Bases: api.client.timeseries.GetData
Class to Get base rate deltas to rest api.
alias of GetBaseRateWarning
Bases: api.client.timeseries.GetBulkData
Class to Get base rate deltas to rest api.
alias of GetBaseRateWarning
Bases: esmond.api.client.util.AlertMixin, object
alias of GetBulkWarning
Bases: api.client.timeseries.GetBulkData
Class to Get raw data to rest api.
alias of GetRawDataWarning
Bases: api.client.timeseries.TimeseriesBase
Base class for API write objects - writes data to the Get facility in the /timeseries/ REST interface namespace.
alias of GetWarning
Bases: api.client.timeseries.GetData
Class to Get raw data to rest api.
alias of GetRawDataWarning
Bases: api.client.timeseries.PostData
Class to post base rate deltas to rest api.
alias of PostBaseRateWarning
Bases: api.client.timeseries.TimeseriesBase
Base class for API write objects - writes data to the POST facility in the /timeseries/ REST interface namespace.
Format current payload, send to REST api and clear the payload. Payload is cleared after a write so as not to send duplicate data, and so the same instance can be used to send multiple times.
Sets object payload to a complete list of dicts passed in. This will overwrite the internal payload if any elements had been previously defined (and issue a warning).
alias of PostWarning
Bases: api.client.timeseries.PostData
Class to post raw data to rest api.
alias of PostRawDataWarning
Bases: object
docstring for TimeSeriesBulkDataRow
Bases: esmond.api.client.snmp.DataPayload


Cloud Vision V1 API - Class Google::Cloud::Vision::V1::ProductSet (v0.6.4)
Reference documentation and code samples for the Cloud Vision V1 API class Google::Cloud::Vision::V1::ProductSet.
A ProductSet contains Products. A ProductSet can contain a maximum of 1 million reference images. If the limit is exceeded, periodic indexing will fail.
Inherits
- Object
Extended By
- Google::Protobuf::MessageExts::ClassMethods
Includes
- Google::Protobuf::MessageExts
Methods
#display_name
def display_name() -> ::String
- (::String) — The user-provided name for this ProductSet. Must not be empty. Must be at most 4096 characters long.
#display_name=
def display_name=(value) -> ::String
- value (::String) — The user-provided name for this ProductSet. Must not be empty. Must be at most 4096 characters long.
- (::String) — The user-provided name for this ProductSet. Must not be empty. Must be at most 4096 characters long.
#index_error
def index_error() -> ::Google::Rpc::Status
-
(::Google::Rpc::Status) — Output only. If there was an error with indexing the product set, the field
is populated.
This field is ignored when creating a ProductSet.
#index_time
def index_time() -> ::Google::Protobuf::Timestamp
-
(::Google::Protobuf::Timestamp) — Output only. The time at which this ProductSet was last indexed. Query
results will reflect all updates before this time. If this ProductSet has
never been indexed, this timestamp is the default value
"1970-01-01T00:00:00Z".
This field is ignored when creating a ProductSet.
#name
def name() -> ::String
-
(::String) — The resource name of the ProductSet.
Format is:
projects/PROJECT_ID/locations/LOC_ID/productSets/PRODUCT_SET_ID
.This field is ignored when creating a ProductSet.
#name=
def name=(value) -> ::String
-
value (::String) — The resource name of the ProductSet.
Format is:
projects/PROJECT_ID/locations/LOC_ID/productSets/PRODUCT_SET_ID
.This field is ignored when creating a ProductSet.
-
(::String) — The resource name of the ProductSet.
Format is:
projects/PROJECT_ID/locations/LOC_ID/productSets/PRODUCT_SET_ID
.This field is ignored when creating a ProductSet.


--- layout: archive title: Zulip Chat Archive permalink: /stream/113488-general/topic/Showing.20automatically.20obtained.20typeclass.20instances.html ---
Is it possible to show which instance Lean is using when it successfully performs a typeclass inference?
For instance, I know from the fact that I can use neg_le_neg
with integers that Lean has silently performed a typeclass inference and found an instance of type ordered_comm_group int
. But I don't know exactly which instance Lean has found. Is there a way to display this information, similar to how I can jump to definitions using f12?
you can print the proof of your theorem
using #print
and you can set pp.implicit true
(there may be a better option) to see the implicit arguments, including the proof of the typeclass inference
set_option trace.class_instances true
well that displays too much information
Thanks!
you can also test instance problems with
theorem T : ordered_comm_group int := by apply_instance #print T
#check (by apply_instance : ordered_comm_group int)
do I win?
clever
{% endraw %}Last updated: Apr 24 2020 at 19:02 UTC


{{Infobox prepared food | name = Shrimp roe noodles | image = | caption = The very tiny black dots are a trademark of the noodle | alternate_name = Shrimp noodles | country = Hong Kong or Guangdong<ref>Youtube</ref> | region = Hong Kong | creator = | course = | type = Chinese noodles | served = | main_ingredient = Shrimp roe. wheat flour, salt, tapioca flour, monosodium glutamate | variations = | calories = | other = }} {{Chinese|t=蝦子麵|s=虾子面|j=haa1 zi2 min6|p=xiāzǐ<!--Should this be third or "fifth" tone?--> miàn|l=shrimp egg noodle}}
Shrimp roe noodles or Shrimp noodles are a variety of Chinese noodle popular in Hong Kong and Guangdong. One of the special characteristic that distinguish this noodle from the many other varieties of Chinese noodle is the salty shrimp roe forming tiny black spots on strips of the noodles.<ref>CNN Go 40 Hong Kong foods we can't live without 13 July 2011. Retrieved 2011-10-09</ref>
Contents |
The noodle is made of wheat flour, salt, tapioca flour, monosodium glutamate (MSG), and shrimp roe.<ref name="pack">Shrimp roe noodle packaging</ref> It comes in a palm-sized hard noodle bundle.
Because this noodle has some taste of its own, the most common method of cooking is directly boiling the noodles. Soy sauce or additional flavorings can still be added. Depending on the noodle brand, the black dots may disappear after cooking.
<gallery> Image:ShrimpRoeNoodle uncooked.jpg|Uncooked shrimp roe noodles </gallery>
{{reflist}}
{{Hong Kong cuisine}} {{Chinese noodles}} {{Cantonese cuisine}} {{seafood}}
{{China-cuisine-stub}}


DescriptionAmount of books in the OBA per language per publication year
DescriptionReset the chart to initial data: total amount of books in the OBA per language


addNode(self,
type,
contextUid,
id,
description=None)
| source code
|
Add a node to the existing tree underneath the node specified by the
context UID
- Parameters:
type (string) - Either 'class' or 'organizer'
contextUid (string) - Path to the node that will be the new node's parent (ex.
/zport/dmd/Devices)
id (string) - Identifier of the new node, must be unique in the parent context
description (string) - (optional) Describes this new node (default: None)
- Returns: dictionary
- Marshaled form of the created node
- Decorators:
|


No password can be considered secure anymore, the best way to store secrets is not to store secrets all in the same place. What you can do is to break the secret phrase in few words and obfuscate them by using this website. The result will be a generated url, you can store or share this url where you want. When you need to recover the words, visit that url and you will need to remember only a pattern and a color to recover the seed phrase. The phrase is not stored anywhere but it is obfuscated within the generated url.


--- layout: post title: Tracing paper date: '2013-08-15T18:39:00+02:00' categories: - Storyboards - Atoleiros Battle picture_url: https://film-Storyboards.tumblr.com/post/58371089408/tracing-paper-layers ---
Drawing over layers of tracing paper.


Syntax:
minnow ID exefile arg1 arg2 ...
Examples:
minnow 1 count minnow 5 filegen ${files} minnow myapp app 3 f1.txt 4.0
Description:
Minnow is a command that can be used in a PHISH input script which is recognized by the bait.py setup program. It defines a minnow application and assigns it an ID which can be used elsewhere in the input script. In PHISH lingo, a "minnow" is a stand-alone application which makes calls to the PHISH library to exchange data with other PHISH minnows.
The ID of the minnow can only contain alphanumeric characters and underscores.
The exefile is the name of the executable which will be launched when the PHISH program is run. It should reside in one of the directories specified by the -path command-line argument for bait.py.
The arg1, arg2, etc keywords are arguments that will be passed to the exefile program when it is launched.
Restrictions: none
Related commands:


openvidu-react-native
A client-side only application built with React Native framework using React and JavaScript. It can be compiled into a native Android app, a native iOS app .
If it is the first time you use OpenVidu, it is highly recommended to start first with openvidu-hello-world tutorial due to this being a native app and being a little more complex for OpenVidu starters.
Understanding this tutorial
OpenVidu is composed by the three modules displayed on the image above in its insecure version.
- openvidu-browser: NPM package for your Ionic app. It allows you to manage your video-calls straight away from your clients
- openvidu-server: Java application that controls Kurento Media Server
- Kurento Media Server: server that handles low level operations of media flow transmissions
Running this tutorial
1) You will need Node 8.3 or newer, NPM, React Native CLI to serve the app. Install them with the following command
sudo curl -sL https://deb.nodesource.com/setup_12.x | sudo bash -
sudo apt-get install -y nodejs
sudo npm install -g react-native-cli
2) Clone the repo
git clone https://github.com/OpenVidu/openvidu-tutorials.git
3) Install dependencies
cd openvidu-tutorials/openvidu-react-native
npm install
4) Install openvidu-browser with React Native support: Add the artifact in the root project
npm install openvidu-browser-Y.Y.Z.tgz
4) Start Metro Bundler :
npm start
Now depending on the platform you want to run your app...
In an Android device
To deploy the Android APK not only you need to have Java JDK8, Android Studio and Android SDK installed but also you have to set up the specific environment variables. Fortunately, React Native provide us a great guide to allows us to configure step by step all the requirements. This tutorial is made with React Native CLI Quickstart so you should select and check the React Native CLI requirements inside of React guide website.
After we have completed all the steps of the React Native CLI guide and performed steps 1) , 2), 3) and 4) stated above, we must continue with the following commands:
5) Connect the device to the PC. You must enable USB debugging and give permissions (check out first section here in React Native docs)
6) Run the tutorial. The app will be automatically launched in your Android device
# In openvidu-tutorials/openvidu-react-native
react-native run-android
In an iOS device
After we have completed all the steps of the performed steps 1), 2) and 3) stated above, we must continue with the following commands:
5) Plug in your device via USB
6) Configure code signing
7) Build and Run your app
To deploy the iOS app React has this guide to properly configure your development environment.
Understanding the code
This is a React Native project generated with React Native CLI tool, and therefore you will see lots of configuration files and other stuff that doesn't really matter to us. We will focus on the following files under App.js
file:
App.js
: defines App component, main component of the app. It contains the functionalities for joining a video-call and for handling the video-calls themselves.
Let's see first how App.js
uses NPM package openvidu-browser
:
We import the necessary objects from openvidu-browser
:
import { OpenVidu } from 'openvidu-browser';
App.js
declares the following properties in the state:
this.state = {
mySessionId: 'SessionReactNative',
myUserName: 'Participant' + Math.floor(Math.random() * 100),
session: undefined,
mainStreamManager: undefined,
publisher: undefined,
subscribers: [],
role: 'PUBLISHER',
};
OpenVidu
object will allow us to get a Session
object, which is declared just after it. publisher
will be our own local webcam stream and subscribers
array will store the active streams of other users in the video-call. Finally, mySessionId
and myUserName
params simply represent the video-call and your participant's nickname, as you will see in a moment.
Whenever a user clicks on the join button defined in App.js
, joinSession()
method is called:
We first get an OpenVidu object and initialize a session property inside the state.
// --- 1) Get an OpenVidu object ---
this.OV = new OpenVidu();
// --- 2) Init a session ---
this.setState({
session: this.OV.initSession(),
}, () => {
// See next step
}
);
Then we subscribe to the Session events that interest us.
// --- 3) Specify the actions when events take place in the session ---
var mySession = this.state.session;
// On every new Stream received...
mySession.on('streamCreated', (event) => {
// Subscribe to the Stream to receive it. Second parameter is undefined
// so OpenVidu doesn't create an HTML video by its own
var subscriber = mySession.subscribe(event.stream, undefined);
//We use an auxiliary array to push the new stream
var subscribers = this.state.subscribers;
subscribers.push(subscriber);
// Update the state with the new subscribers
this.setState({
subscribers: subscribers,
});
});
// On every Stream destroyed...
mySession.on('streamDestroyed', (event) => {
event.preventDefault();
// Remove the stream from 'subscribers' array
this.deleteSubscriber(event.stream.streamManager);
});
// See next step
Here we subscribe to the Session events that interest us. As we are using React Native framework, a good approach for managing the remote media streams is to loop across an array of them, feeding a common component with each Subscriber
object and let it manage its video. This component will be RTCView and is provided from react-native-webrtc library. To do this, we need to store each new Subscriber we received in array subscribers
, and we must remove from it every deleted subscriber whenever it is necessary. To achieve this, we use the following events:
-
streamCreated
: for each new Stream received by the Session object, we subscribe to it and store the returned Subscriber object in oursubscribers
array. Methodsession.subscribe
has undefined as second parameter so OpenVidu doesn't insert and HTML video element in the DOM due to, as it is a native application, the DOM does not exist. The render method of App.js will show the new video, as it contains a .map js function, declaring a RTCView for each subscriber. We get the reference to RTCView and we will run openvidu-browser method addVideoElement, passing the reference of the RTCView when it is defined.{this.state.subscribers.map((item, index) => { if(!!item){ return ( <View key={index}> <Text>{this.getNicknameTag(item.stream)}</Text> <RTCView zOrder={0} objectFit="cover" style={styles.remoteView} ref={(rtcVideo) => { if (!!rtcVideo){ item.addVideoElement(rtcVideo); } }} /> </View> ) }
-
streamDestroyed
: for each Stream that has been destroyed from the Session object (which means a user has left the video-call), we remove the associated Subscriber fromsubscribers
array, so React will automatically delete the required RTCView component.
Get a token from OpenVidu Server
// --- 4) Connect to the session with a valid user token ---
// 'getToken' method is simulating what your server-side should do.
// 'token' parameter should be retrieved and returned by your own backend
this.getToken().then((token) => {
// See next point to see how to connect to the session using 'token'
});
Now we need a token from OpenVidu Server. In a production environment we would perform this operations in our application backend, by making use of the REST API, OpenVidu Java Client or OpenVidu Node Client. Here we have implemented the POST requests to OpenVidu Server in a method getToken()
that returns a Promise with the token, using fetch
library. Without going into too much detail, this method performs two POST requests to OpenVidu Server, passing OpenVidu Server secret to authenticate them:
- First request performs a POST to
/api/sessions
(we send acustomSessionId
field to name the session with ourmySessionId
value retrieved from HTML input) - Second request performs a POST to
/api/tokens
(we send asession
field to assign the token to this same session)
You can inspect this method in detail in the GitHub repo.
Connect to the session:
// --- 4) Connect to the session with a valid user token ---
// 'getToken' method is simulating what your server-side should do.
// 'token' parameter should be retrieved and returned by your own backend
this.getToken().then((token) => {
// First param is the token got from OpenVidu Server. Second param can be retrieved by every user on event
// 'streamCreated' (property Stream.connection.data), and will be appended to DOM as the user's nickname
mySession.connect(token, { clientData: this.state.myUserName })
.then(() => {
if (Platform.OS == 'android') {
this.checkAndroidPermissions();
}
// --- 5) Get your own camera stream ---
if (this.state.role !== 'SUBSCRIBER') {
// Init a publisher passing undefined as targetElement (we don't want OpenVidu to insert a video
// element: we will manage it on our own) and with the desired properties
let publisher = this.OV.initPublisher(undefined, {
audioSource: undefined, // The source of audio. If undefined default microphone
videoSource: undefined, // The source of video. If undefined default webcam
publishAudio: true, // Whether you want to start publishing with your audio unmuted or not
publishVideo: true, // Whether you want to start publishing with your video enabled or not
resolution: '640x480', // The resolution of your video
frameRate: 30, // The frame rate of your video
insertMode: 'APPEND', // How the video is inserted in the target element 'video-container'
});
// --- 6) Publish your stream ---
// Set the main video in the page to display our webcam and store our Publisher
this.setState({
mainStreamManager: publisher
});
mySession.publish(publisher);
}
})
.catch((error) => {
console.log('There was an error connecting to the session:', error.code, error.message);
});
})
.catch((error) => console.log('Error', error));
In session.connect
method first param is the recently retrieved user token. Second param is the value every user will receive in event.stream.connection.data
property on streamCreated
event. (this value will be used to show the user's nickname to the his video).
If the method succeeds we will call to checkAndroidPermissions()
method. This method requests and checks the device permissions that our app currently has in the device. Once the permissions have been resolved, the OV.initPublisher()
method will be called. For iOS and web platforms, permissions will be handled automatically when camera and microphone access are requested. No need for extra steps in these cases, so we directly initialize our Publisher object.
We do further talk about Android permissions under section Android specific requirements.
Finally publish your webcam calling OV.initPublisher()
method:
let publisher = this.OV.initPublisher(undefined, {
audioSource: undefined, // The source of audio. If undefined default microphone
videoSource: undefined, // The source of video. If undefined default webcam
publishAudio: true, // Whether you want to start publishing with your audio unmuted or not
publishVideo: true, // Whether you want to start publishing with your video enabled or not
resolution: '640x480', // The resolution of your video
frameRate: 30, // The frame rate of your video
insertMode: 'APPEND', // How the video is inserted in the target element 'video-container'
});
// --- 6) Publish your stream ---
// Set the main video in the page to display our webcam and store our Publisher
this.setState({
mainStreamManager: publisher
});
mySession.publish(publisher);
We now proceed to publish our webcam to the session. To do so we get a Publisher
object with the desired properties and publish it to the Session through Session.publish()
method. The rest of users will receive our Stream object and will execute their streamCreated
event.
Also we store the Publisher object under this.state.mainStreamManager
variable. This way our webcam will be appended along all remote subscribers, in exactly the same way they are shown.
<View style={styles.container}>
<Text>Session: {this.state.mySessionId}</Text>
<Text>{this.getNicknameTag(this.state.mainStreamManager.stream)}</Text>
<RTCView zOrder={0} objectFit="cover"
ref={(rtcVideo) => {
if (!!rtcVideo) {
this.state.mainStreamManager.addVideoElement(rtcVideo);
}
}}
style={styles.selfView}
/>
</View>
Leaving the session
Whenever we want a user to leave the session, we just need to call session.disconnect
method in app.component.ts
:
leaveSession() {
// --- 7) Leave the session by calling 'disconnect' method over the Session object ---
const mySession = this.state.session;
if (mySession) {
mySession.disconnect();
}
// Empty all properties...
this.OV = null;
this.setState({
session: undefined,
subscribers: [],
mySessionId: 'SessionReactNative',
myUserName: 'Participant' + Math.floor(Math.random() * 100),
mainStreamManager: undefined,
publisher: undefined,
});
}
Android specific requirements
Android apps need to actively ask for permissions in the code to access camera and microphone using react-native-webrtc plugin. By following steps below we have been able to properly set up the optimal configuration your React Native app will need to work along OpenVidu.
These configurations are already included in this openvidu-react-native project, so if you start from here no further configurations are needed. Otherwise, if you want to start a new project with React Native and OpenVidu, you should follow these simple steps:
1) In android/app/src/main/AndroidManifest.xml
add these permissions
<uses-permission android:name="android.permission.CAMERA" />
<uses-feature android:name="android.hardware.camera" />
<uses-feature android:name="android.hardware.camera.autofocus"/>
<uses-permission android:name="android.permission.ACCESS_NETWORK_STATE"/>
<uses-permission android:name="android.permission.MODIFY_AUDIO_SETTINGS" />
<uses-permission android:name="android.permission.RECORD_AUDIO" />
<uses-permission android:name="android.permission.WAKE_LOCK" />
<uses-permission android:name="android.permission.WRITE_EXTERNAL_STORAGE"/>
2) In android/settings.gradle
, include WebRTCModule
include ':WebRTCModule', ':app'
project(':WebRTCModule').projectDir = new File(rootProject.projectDir, '../node_modules/openvidu-browser/node_modules/react-native-webrtc/android')
3) In android/app/build.gradle
, add WebRTCModule to dependencies
dependencies {
implementation project(':WebRTCModule')
...
}
4) In android/app/src/main/java/com/xxx/MainApplication.java
import and add WebRTCModulePackage:
If you are using a version prior to 0.60.0:
import com.oney.WebRTCModule.WebRTCModulePackage;
...
@Override
protected List<ReactPackage> getPackages() {
return Arrays.<ReactPackage>asList(
new MainReactPackage(),
new WebRTCModulePackage() // <-- Add this line
);
}
If you are using a version above to 0.60.0:
import com.oney.WebRTCModule.WebRTCModulePackage;
....
@Override
protected List<ReactPackage> getPackages() {
@SuppressWarnings("UnnecessaryLocalVariable")
List<ReactPackage> packages = new PackageList(this).getPackages();
// Packages that cannot be autolinked yet can be added manually here, for example:
// packages.add(new MyReactNativePackage());
packages.add(new WebRTCModulePackage()); // <-- Add this line
return packages;
}
iOS specific requirements
iOS apps need to include the WebRTC modules from react-native-webrtc plugin. We will do it by following the steps bellow.
These configurations are already included in this openvidu-react-native project, so if you start from here no further configurations are needed. Otherwise, if you want to start a new project with React Native and OpenVidu, you should follow these simple steps:
1) Add these files into your project
- in Xcode: Right click on
Libraries
andAdd Files to {project}
- Go to
node_modules/openvidu-browser/node_modules/react-native-webrtc/ios/RCTWebRTC.xcodeproj
and click onAdd
- Also add
node_modules/react-native-webrtc/ios/WebRTC.framework
toFrameworks
folder
2) iOS Podfile
You can use the included podspec in your podfile to take care of all dependencies instead of manually adding files to the project. If you prefer to add it manually, you should check the official tutorial.
Include in the Podfile in your react-native iOS directory:
pod 'react-native-webrtc', :path => '../node_modules/openvidu-browser/node_modules/react-native-webrtc'
You may have to change the platform
field in your Podfile, as react-native-webrtc doesn't support iOS 9 - set it to '10.0' or above (otherwise you get an error when doing pod install
):
platform :ios, '10.0'
3) Set up parameters
Under Build setting set Dead Code Stripping to No
also under Build Options set Enable Bitcode to No
as well
4) Add Permissions
* Navigate to <ProjectFolder>/ios/<ProjectName>/
* Edit Info.plist and add the following lines
<key>NSCameraUsageDescription</key>
<string>Camera Permission</string>
<key>NSMicrophoneUsageDescription</key>
<string>Microphone Permission</string>
5) Install pod
You will install the Podfile that we have set up in step 2:
cd ios
pod install


### Traffic and Urban Planning
- SmartAdP: Visual Analytics of Large-scale Taxi Trajectories for Selecting Billboard Locations, Dongyu Liu, Di Weng, Yuhong Li, Jie Bao, Yu Zheng, Huamin Qu, Yingcai Wu
- SemanticTraj: A New Approach to Interacting with Massive Taxi Trajectories, Shamal AL-Dohuki, Farah Kamw, Ye Zhao, Chao Ma, Yingyu Wu, Jing Yang, Xinyue Ye, Fei Wang, Xin Li, Wei Chen
### SmartAdP
Identifying the optimal billboard locations using massive trajectory data.
![](./assets/smartadp-1.png)
#### Backgrounds
- Finding befitting areas to place billboards.
- Selecting proper locations in the specified areas.
- Evaluating a solution and convincing customers.
- Providing customers with multiple solutions.
#### Tasks and Models
**Spatio-temporal distribution and location recommendation**: Road network data, GPS trjectory and POI data. MongoDB indexes. Two interactive queries.
![](./assets/smartadp-2.png)
#### Tasks and Visual Designs
- **Results' assessment**: Locations and solutions, distributions and detailed information.
- **Solution comparison, classification and ranking**: A quick overview of the solutions can obtained by grouping solutions, ranking can help planners quickly find the desired solutions.
#### Tasks and Visual Designs
**Glyph Design**
![smartadp_visdes](./assets/smartadp-3.png)
#### Case studies
- Exploring the solution space
- Exploring the distribution of target trajectories
- Comparing solution areas for billboard placements
- Improving and editing solutions
- Finding the optimal solution
- Weekday and weekend
- Dispersed Strategy vs Clustered Strategy
- Domain Expert Interview
#### Case studies
![smartadp_visdes](./assets/smartadp-5.png)
![](./assets/smartadp-6.png)
### SemanticTraj
- Typical approach to explore taxi trajectory data: Require users to select and brush geospatial region on a map: tedious and time consuming
- The method: manage visualize taxi trajectory data in an intuitive, semantic rich and efficient means.
#### Components
- Textualization transformation process
- Text search engine with a corpus of taxi documents
- Semantic labels and meta-summaries of results are integrated with a set of visualizations
- Feedback from domain experts and a preliminary user study to evaluate the visual system
![](./assets/semantictraj-1.png)
#### Visual Exploration: semantic trips search
![](./assets/semantictraj-2.png)
#### Visual Exploration: study individual trajectory
![](./assets/semantictraj-3.png)
#### Provide shuttle buses for tourists
![](./assets/semantictraj-4.png)
#### Study traffic information over streets
![](./assets/semantictraj-5.png)
## vis.cs.kent.edu
- [NY Taxi Trip](http://vis.cs.kent.edu/NYTaxi/): Data of taxi trips. Taxi trip refers to a taxi carrying its passengers from their origin (pickup) location to destination (dropoff) location.
- [Porto Taxi Trip](http://vis.cs.kent.edu/PortoTrajectories/): Real-world mobility data of taxi trajectories. Taxi trajectory is the recording of the positions of a taxi at specific space-time domain, for a given taxi and a given time interval, it is presented as a sequence of geometric location in 2D spatial system (xi, yi, ti).
## Posters and Arts Program
### Poster: Analyzing Hillary Clinton’s Emails
![](./assets/poster-1.png)
### Poster: Towards Combining Mobile Devices for Visual Data Exploration
![](./assets/poster-2.png)
### Workshop on Visualization in Practice
**vega**: Vega is a visualization grammar. With Vega, you can describe the visual appearance and interactive behavior of a visualization in a JSON format, and generate views using HTML5 Canvas or SVG.
![](./assets/poster-3.png)
### Urban Radiance, East Asia 1992-2013
![](./assets/frame_31-1.jpg)


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Language of instruction
The language of instruction in all departments is Arabic, English, or according to specializations, and faculty members are bound by them.
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The study is conducted remotely, as most of the study programs are offered by the teacher, and compulsory attendance of students is required in a number of hours and subjects, which are predetermined by the subject teacher during one semester. Students are notified at the beginning of the semester.
In some subjects, students must submit individual assignments or group research and reports during the semester. There are also scientific and practical exams and an exam at the end of each semester that can be a written and oral exam. Students who are in the Kingdom of Sweden can come in person to the Academy Center and take the tests.
Examinations of students who are in other countries are based on their presence in any country and the number of students studying at the university. Either the student attends personally at the university’s headquarters in Sweden (if he can) or takes the test in one of the public and private universities that have a cooperation agreement with the Swedish International University, Or at the Swedish embassy located in that country, and it is also possible to send a representative from the university to the country where the students are located and to supervise the examinations in person at a university center that has a joint cooperation agreement with the university. If the student is not able to take the test, or if he is not able to pass the test, the student has the right to retake the test.
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After completing the study at the Swedish International University, the student can obtain a scientific certificate issued by the university or college, each according to his specialization, and the certificate is attested by the Swedish Foreign Ministry and the embassy of the country specified by the student. The student is provided with a copy of the certificate by registered international mail.


ECS | Sem 5 | IISER Pune
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