Functional vs Object Oriented Programming
The biggest difference between functional and object oriented programming is the notion of state. In functional programming, the output of a function depends only on the parameters passed into it. Functions can interact with other functions, but they stand alone, meaning they do not belong to a class. Without the notion of classes in functional programming, there there are no instance variables that can have an affect on the output of a function. Without insance variables, objects just are what they are - they cannot have multiple states. A simple exmaple can be illustrated with a character in a video game.
In object-oriented programming, our character would be represented by a class with built-in functions and instance variables that represent the state of the object:
  def initialize(name, race, weapon, hometown)
    @name = name
    @race = race
    @weapon = weapon
    @hometown = hometown
  end
  def attack
    case @weapon
    when "sword"
      puts "#{@name} Slashes their Enemy!"
    when "magic"
      puts "#{@name} Casts a Bolt of Acid at their Enemy!"
    when "bow"
      puts "#{@name} Fires a Flaming Arrow at their Enemy!"
  end
end
In this case, your character would be an instance of the Character class, and its state is represented by instance variables. Each character can have a name, a race, a weapon, and a hometown. If you want to use your character to attack an enemy, you just need to call the 'attack' method. Depending on your character's state, it will attack in a certain way - but you don't worry about that. You just tell it to attack, and the complexity of how it attacks is factored out. Changing that part requires updating the state of the object, or updating it's @weapon instance variable.
Functional programming is different. In functioanl programming, you could still create a character and tell it to attack, but you need to be more specific. Since your attack method doesn't belong to your character's class, you need to tell it who is doing the attacking and how they should attack
  case weapon
  when "sword"
    puts "#{character} Slashes their Enemy!"
  when "magic"
    puts "#{character} Casts a Bolt of Acid at their Enemy!"
  when "bow"
    puts "#{character} Fires a Flaming Arrow at their Enemy!"
  end
end
While it's sometimes easier for us to visualize real-world problems in object-oriented terms, there is a place for both Fundamental and Object Oriented Programming. OOP works well when there are a fixed number of actions that objects have to do, but objects are continuously being created or updated. OOP allows you to inherit properties from another class, giving programmers the ability to quickly create new types of objects that differ slightly from their predecessors. Fundamental programming works best when you have a small number of objects, but are continuously adding new functaionlity for the same objects. In this case, developers can update a function in one place, as opposed to updating different instance methods that belong to specific types of objects.


Obi-Wan was a Jedi Master and general during the Clone Wars era of Star Wars. He was the master of Anakin Skywalker, who would later fall into the Dark Side and transform into iconic villain, Darth Vader. After the fall of the Republic and Jedi massacre at the end of the Clone Wars, Obi-Wan retreated to a desert planet named Tatooine. He stayed here to watch over one of Anakin's children, Luke Skywalker. He'd eventually join Luke to battle the Empire and sacrifice himself on the Death Star.


General info
This page demonstrates simple data fetch from backend via WebSockets and how to show that data in simple list.
Within this example application fetches authors data with related book data populated to each
one. Example also covers data pagination, sort and search functions. Actual data is fetched from following backend
endpoint.
GET {{backendConfig.url}}/author
Note that all data communications to backend requires JSON Web Token JWT. This JWT is used to authenticate
current request to make sure that user is allowed to access that data.
Functions in this example
-
Data fetch
-
From backend via WebSockets using $sailsSocket service.
-
Search
-
Specify which columns are used in search and type your search words to see results while you're typing.
-
Pagination
-
By default, the page displays an example of ten books per page. And you can change the number to be
displayed per page.
-
Sorting data
-
Simple by clicking of column header. This will fetch data from backend again. Unfortunately not from
relation columns... yet.
-
Live updates
-
Data is updated automatic to GUI if someone changes data that is shown currently.
-
Navigation
-
Access to single author and book pages simply by click author or book name.


Home
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Our Products
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General Questions
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Contact Us
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SPFx is the futureWSP Farm/Sanbox solution is the pastAdd-In is our topic
CSS SharePoint 2019 Advanced Learning Program SharePoint Add-in Topicchunlonl@microsoft.com


6 February 2004
Investigation of possible human-to-human transmission in Viet Nam: new data are reassuring
NB: Please see correction in update 20
WHO has today received the results from studies of two viruses taken from members of a family cluster of H5N1 infection in Viet Nam. The family cluster has been under investigationas the first possible instance of limited human-to-human transmission of the H5N1 avian influenza strain. Virus genetic materials from two fatal cases in this cluster – sisters aged 23 and 30 years – have now been fully sequenced by the Government Virus Unit of Hong Kong’s Department of Health. Both viruses are of avian origin and contain no human influenza genes.
This finding, which indicates that the virus has not changed to a form easily transmitted from one person to another, is consistent with earlier findings from epidemiological investigations. No illness has been reported in other family members, in the local community, or in health workers involved in care of these patients.
China (poultry)
Chinese authorities have today confirmed H5N1 infection in poultry in an additional province. The H5N1 strain was detected in samples from infected chickens at two farms in the southern province of Jiangxi.
Altogether, H5N1 infection in poultry is confirmed or suspected at farms in 13 of China’s 31 provinces, autonomous regions, and municipalities.
No cases of human H5N1 infection have been reported in China to date.


Mode: {{chatroom.settings.mode}}
Website: {{chatroom.otherUser.website}}
Bio: {{chatroom.otherUser.bio}}


We help in-house teams make websites and mobile applications accessible to people with disabilities.
Simply put, Web accessibility is the inclusive practice of ensuring there are no barriers that prevent interaction with, or access to, websites on the World Wide Web by people with physical disabilities, situational disabilities, and socio-economic restrictions on bandwidth and speed. If you need help making your website accessible or find out accessible issues within an existing one, we’d love to talk with you about how we can help.
Glossary The words we use when we talk about accessibility.
Talks Videos and slide decks from conference talks about web accessibility.
Articles Curl up with a cozy tablet and read about our favorite subject.
Subscribe to the OpnLabs newsletter for infrequent, plain-text emails about our latest work and goings-on.


Roboto has a dual nature. It has a mechanical skeleton and the forms are largely geometric. At the same time, the font features friendly and open curves. While some grotesks distort their letterforms to force a rigid rhythm, Roboto doesnâ€™t compromise, allowing letters to be settled into their natural width. This makes for a more natural reading rhythm more commonly found in humanist and serif types.
This is the Condensed family, which can be used alongside the normalRoboto family and the Roboto Slab family.
Updated July 31 2013: Hinting has been improved and a fix made to á»¡, the Vietnamese 'o with horn and tilde' character. If you have installed the fonts on your computer, please download them again and re-install.


SPLICE:
Standards, Protocols, and Learning Infrastructure for Computing Education
Welcome to the home of the SPLICE project. Our mission is to support the CS Education community by supplying documentation and infrastructure to help with adopting shared standards, protocols, and tools. In this way we hope to promote
- development and broader re-use of innovative learning content that is instrumented for rich data collection;
- formats and tools for analysis of learner data; and
- best practices to make large collections of learner data and associated analytics available to researchers in the CSE, data science, and learner science communities.
Need technical assistance? If you need some help getting LTI to work with your application, or similar technology, our community might be able to give advice.
- Take a look at our tutorials
- Join the SPLICE Google Group, and ask the community.
- See our live catalog of smart learning objects, along with information on how to use them in your course. (Note: To see the catalog, you will need to register for an account on this site if you don't already have one.)
For a fuller description of our vision and goals, see the overview from our successful NSF proposal.
News and Upcoming Events
- 5th Educational Data Mining in Computer Science Education (CSEDM)Virtual Workshop @ EDM 2021, June 29th, 2021.
Previous Associated Workshops
- First SPLICE Workshop, June 2017 in Pittsburgh: "Community-building or data-intensive computer and computing science education infrastructure research"
- Second SPLICE Workshop, February 2018 in Baltimore: "CS Education Infrastructure for All: Interoperability for Tools and Data Analytics"
- 1st Educational Data Mining in Computer Science Education (CSEDM) Workshop @ EDM2018, July 15, 2018
- Third SPLICE Workshop, August 2018 in Espoo, Finland: "Computing Science Educational Infrastructure: Crossing the Borders"
- Fourth SPLICE Workshop at SIGCSE 2019, February 2019 in Minneapolis: "CS Education Infrastructure for All II: Enabling the Change"
- 2nd Educational Data Mining in Computer Science Education (CSEDM) Workshop @ LAK2019, March 5, 2019.
- 3rd Educational Data Mining in Computer Science Education (CSEDM) Workshop @ AIED 2019, June 25, 2019.
- Fifth SPLICE Workshop at ICER 2019, August 11, 2019, in Toronto: "Computing Science Education Infrastructure: From Tools to Data"
- Second Workshop on Intelligent Textbooks @ AIED 2020, July 6, 2020.
- 4th Educational Data Mining in Computer Science Education (CSEDM) Virtual Workshop @ EDM 2020, July 10, 2020.
- Sixth SPLICE Workshop at L@S 2020 (Virtual event), August 12, 2020: "Building an Infrastructure for Computer Science Education Research and Practice at Scale"
- Seventh SPLICE Workshop at SIGCSE 2021 (Virtual event), March 15-16: "CS Education Infrastructure for All III: From Ideas to Practice"
SPLICE Working Groups
- Small Code Snapshots. Leaders: Thomas Price and Ayaan Kazerouni.
- Programming Exercise Markup Language. Leaders: Phill Conrad, Cory Bart, and Stephen Edwards.
- Packaging Curricular Materials. Leaders: Cory Bart, Phill Conrad, Michael Hilton, Bob Edmison.
- Interoperable Data Collection. Leaders: Michael Yudelson.
Resources
- SPLICE Google group
- Repositories
- Documentation
- Best Practice Examples
Standards Documentation
Project Support
- SPLICE is supported by the National Science Foundation and by Virginia Tech's Technology-enhanced learning and Online Strategies unit (see more).


AxisType Class
AxisType is an abstract class that manages the data for an axis.
Item Index
Methods
Methods
_dataProviderChangeHandler
-
e
Handles changes to dataProvider
.
Parameters:
-
e
ObjectEvent object.
_getKeyArray
-
key
-
data
Gets an array of values based on a key.
Parameters:
-
key
StringValue key associated with the data array.
-
data
ArrayArray in which the data resides.
Returns:
_hasDataOverflow
()
protected
Checks to see if data extends beyond the range of the axis. If so, that data will need to be hidden. This method is internal, temporary and subject to removal in the future.
Returns:
_keyChangeHandler
-
e
Updates the Axis
after a change in keys.
Parameters:
-
e
ObjectEvent object.
_setDataByKey
-
key
-
data
Sets data by key
Parameters:
-
key
StringKey value to use.
-
data
ArrayArray to use.
_updateMinAndMax
()
private
Calculates the maximum and minimum values for the Axis
.
_updateTotalData
()
private
Updates the total data array.
addKey
-
value
Adds an array to the key hash.
Parameters:
-
value
ObjectIndicates what key to use in retrieving the array.
bindUI
()
private
getDataByKey
-
value
Returns an array of values based on an identifier key.
Parameters:
-
value
Stringvalue used to identify the array
Returns:
getEdgeOffset
-
ct
-
l
Gets the distance that the first and last ticks are offset from there respective edges.
Parameters:
-
ct
NumberNumber of ticks on the axis.
-
l
NumberLength (in pixels) of the axis.
Returns:
getKeyValueAt
-
key
-
index
Returns a value based of a key value and an index.
Parameters:
-
key
Stringvalue used to look up the correct array
-
index
Numberwithin the array
Returns:
getLabelByIndex
-
i
-
l
Calculates and returns a value based on the number of labels and the index of the current label.
Parameters:
-
i
NumberIndex of the label.
-
l
NumberTotal number of labels.
Returns:
getMajorUnitDistance
-
len
-
uiLen
-
majorUnit
Returns the distance between major units on an axis.
Parameters:
-
len
NumberNumber of ticks
-
uiLen
NumberSize of the axis.
-
majorUnit
ObjectHash of properties used to determine the majorUnit
Returns:
getMaximumValue
()
Returns a string corresponding to the last label on an axis.
Returns:
getMinimumValue
()
Returns a string corresponding to the first label on an axis.
Returns:
getTotalMajorUnits
()
Returns the total number of majorUnits that will appear on an axis.
Returns:
initializer
()
private
removeKey
-
value
Removes an array from the key hash.
Parameters:
-
value
StringIndicates what key to use in removing from the hash.
Properties
_data
Array
private
Reference to data array.
_dataMaximum
Object
private
Storage for dataMaximum
attribute.
_dataReady
Boolean
private
Storage for dataReady
attribute.
_setMaximum
Object
private
Storage for setMaximum
attribute.
_setMinimum
Object
private
Storage for setMinimum
attribute.
_type
String
private
Type of data used in Axis
.
_updateTotalDataFlag
Boolean
private
Indicates whether the all data is up to date.
GUID
String
private
Constant used to generate unique id.
Attributes
dataMaximum
Number
The maximum value contained in the data
array. Used for
maximum
when autoMax
is true.
dataMinimum
Number
The minimum value contained in the data
array. Used for
minimum
when autoMin
is true.
roundingMethod
String
Indicates how to round unit values.
- niceNumber
- Units will be smoothed based on the number of ticks and data range.
- auto
- If the range is greater than 1, the units will be rounded.
- numeric value
- Units will be equal to the numeric value.
- null
- No rounding will occur.
Default: niceNumber


Welcome Aboard, Brave Space Traveler!
Mercury
Age:
Life Expectancy:
Years to Live:
Congrats! You've lived years longer than you should have!!
Venus
Age:
Life Expectancy:
Years to Live:
Congrats! You've lived years longer than you should have!!
Mars
Age:
Life Expectancy:
Years to Live:
Congrats! You've lived years longer than you should have!!
Jupiter
Age:
Life Expectancy:
Years to Live:
Congrats! You've lived years longer than you should have!!


Web interface & script by Landon Carter, concept by Victor Hung.
Questions? Bugs? Requests? Email us.


IsleService Objects¶
Template for creating models, schemas and errors for services, then installed for use in client apps and companion services.
This template is built off of islelib and shares it’s same tool suite.
Development Guide¶
Each objects package for a service should contain the following sub-packages:
models: Dataclass models for schema generation through `grahamcracker`_
schemas*: Any schemas which require custom implementation. Should always inherit from
grahamcracker.DataSchema
and be generated using thegrahamcracker.schema_for
decorator to tie it to a dataclass modelfields:
marshmallow.fields.Field
implementations required by the schemas.errors: All errors should inherit from
spanreed.APIError
A few development notes:
The purpose of having a separate package for these objects is that they can be shared between the service itself and other client applications / services. In some cases it may make sense to have one objects module contain the models / errors / schemas for a group of microservices.
The default pipeline is set up to test on Mac, Windows, and PC – unlike `isleservice`_, which by default only tests on Linux.


Dumpling plugin for Jenkins brings Dumpling DSL capabilities into Jenkins
Plugin Information |
|---|
View Use Dumpling from Jenkins groovy scripts on the plugin site for more information. |
This plugin make Dumpling DSL available for:
- Groovy scripts all over Jenkins
- Other plugins
Capturing current Jenkins thread state should be as easy as calling Dumpling.runtime
in script console/scriptler/groovy plugin step to investigate or periodically monitor Jenkins threads. See Dumpling DSL tutorial for more information on how to use dumpling. Note that the DSL differs a bit in Jenkins Groovy interpreters as the ability to configure is a bit limited.
Useful scripts
General jstack-like threadddump:
println D.runtime.threads // Or before 2.2 println Dumpling.runtime.threads
Detailed thread blockage report:
D.runtime.query(D.query.blockingTree().showStackTraces()) // Or before 2.2 import com.github.olivergondza.dumpling.query.*; println Dumpling.runtime.query(new BlockingTree().showStackTraces());
Brief blockage report focused on HTTP handling threads:
import com.github.olivergondza.dumpling.query.*; println Dumpling.runtime.threads.grep { it.name =~ /^Handling / }.query(new BlockingTree())
Capture threaddump of different java process (most likely on agent):
// List processes println 'jps -l'.execute().text // Print runtime D.load.process(PID_NUMBER) // Or before 2.2 new com.github.olivergondza.dumpling.factory.PidRuntimeFactory().fromProcess(PID_NUMBER);


GRILLED CHICKEN
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HTC revenue in October drops 49.84% year-on-year - Any hope for HTC? -
by Efe UdinHTC revenue in October drops 49.84% year-on-year – Any hope for HTC?
5 (100%) 1 vote
Over the past decade, HTC has gradually faded from one of the biggest players in the smartphone market. The company hopes to make a comeback one day, but its latest financial results prove that this goal is very difficult.
In October, HTC’s total revenue was NT$656 million ($21.6 million). Although HTC launched a series of entry devices in a number of markets a few months ago, HTC’s performance declined sharply in October. Compared with September, the figure in October dropped by 48.58%. In September, HTC’s revenue was NT$1,275 million ($42 million). When compared with NT$1,307 million ($43 million) in the same period last year, this is a decrease of 49.84%.
HTC’s original 2019 plan was to focus on turning around and regaining some market share in the smartphone space. However, it has not achieved the expected results. However, the company now has a new CEO and he seems optimistic about the future of the company.
Recently, Yves Maitre, CEO of HTC, said that HTC intends to focus on virtual reality and will stop the innovation of mobile hardware. At the same time, he also said that HTC will not completely abandon the mobile phone business, and will deploy the high-end 5G mobile phone in the future. Previously, Chen Baikou, general manager of HTC China-Taiwan, also said that HTC will face the iPhone with high-end smartphones in the first half of next year. It hopes to increase its market share and ensure that every mobile phone is profitable.


Jan Holod
Contacts
email:
<EMAIL_ADDRESS>github:
github.com/janholod
current location:
Prague, Czech Rebublic
phone:
+420 797 857 376
Summary
Senior Software Engineer with 8+ years of Java development experience.
Experience
IT Freelance
Prague, Czech Rebublic
Senior Software Engineer
Jan 2011 - present
Participating in different Java projects.
Using Spring Boot and Spring Cloud.
Skills and Qualifications
Programming skills
Java, Spring Boot, Spring Cloud, Gradle
JavaScript, React.js
Operation Systems
Linux, Windows
Databases
MySQL, PostgreSQL
Application servers
Tomcat, Jetty, Nginx
Development practices
BDD
TDD
CI/CD
Clean Code
Version Control
Git
Language
English


Today word
{{first_today_word.word}}
Examples
Other today words:
{{word.word}}{{number_today_words}} new words and 0 words to review
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Examples
Other today words:
{{word.word}}{{number_today_words}} new words and 0 words to review


<lomInstallationRemarks>
The <lomInstallationRemarks>
provides learning metadata about how to install
and needed resources.
Category: Learning and training: metadata elements


Home
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A
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G
H
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T
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W
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_
]
A
Adam
(in
paramz.optimization.optimization
)
add_observer()
(in
Observable
)
ArrayList
(in
paramz.core.lists_and_dicts
)
add()
(in
ParameterIndexOperations
)
add_tied_parameter()
(in
Tie
)
assertArrayListEquals()
(in
ListDictTestCase
)
add()
(in
ParameterIndexOperationsView
)
add_to_cache()
(in
Cacher
)
AssertionError
add()
(in
ObserverList
)
adjust_name_for_printing()
(in
paramz.core.nameable
)
assertListDictEquals()
(in
ListDictTestCase
)
add_index_operation()
(in
Indexable
)
ArrayCoreTest
(in
paramz.tests.parameterized_tests
)
B
Basis
(in
paramz.examples.ridge_regression
)
basis()
(in
Polynomial
)
build_pydot()
(in
Parameterized
)
basis()
(in
Basis
)
build_pydot()
(in
Param
)
C
Cache_this
(in
paramz.caching
)
combine_indices()
(in
paramz.core.index_operations
)
constrain_positive()
(in
ParamConcatenation
)
Cacher
(in
paramz.caching
)
combine_inputs()
(in
Cacher
)
constrainable
(in
paramz.core
)
cacher_tests
(in
paramz.tests
)
constrain()
(in
Constrainable
)
Constrainable
(in
paramz.core.constrainable
)
caching
(in
paramz
)
constrain()
(in
ParamConcatenation
)
copy()
(in
ParameterIndexOperations
)
callback()
(in
Remapping
)
constrain_bounded()
(in
Constrainable
)
copy()
(in
ParameterIndexOperationsView
)
change_priority()
(in
Observable
)
constrain_bounded()
(in
ParamConcatenation
)
copy()
(in
ObsAr
)
checkgrad()
(in
Gradcheckable
)
constrain_fixed()
(in
Constrainable
)
copy()
(in
Pickleable
)
checkgrad()
(in
ParamConcatenation
)
constrain_fixed()
(in
ParamConcatenation
)
copy()
(in
Param
)
clear()
(in
ParameterIndexOperations
)
constrain_negative()
(in
Constrainable
)
copy()
(in
Parameterized
)
clear()
(in
ParameterIndexOperationsView
)
constrain_negative()
(in
ParamConcatenation
)
core
(in
paramz
)
collate_gradient()
(in
Tie
)
constrain_positive()
(in
Constrainable
)
D
degree
(in
RidgeRegression
)
domain
(in
Logexp
)
domain
(in
NegativeLogexp
)
disable_cacher()
(in
Cacher
)
domain
(in
LogexpClipped
)
domain
(in
Square
)
disable_caching()
(in
FunctionCache
)
domain
(in
LogexpNeg
)
domain
(in
Transformation
)
disable_caching()
(in
Parameterizable
)
domain
(in
Logistic
)
domains
(in
paramz
)
domain
(in
Exponent
)
domain
(in
NegativeExponent
)
E
enable_cacher()
(in
Cacher
)
epsilon
(in
paramz.transformations
)
exponents()
(in
paramz.optimization.verbose_optimization
)
enable_caching()
(in
FunctionCache
)
examples
(in
paramz
)
extract_properties_to_index()
(in
paramz.core.index_operations
)
enable_caching()
(in
Parameterizable
)
examples_tests
(in
paramz.tests
)
ensure_cache_length()
(in
Cacher
)
Exponent
(in
paramz.transformations
)
F
f()
(in
Exponent
)
f()
(in
Transformation
)
finv()
(in
NormalTheta
)
f()
(in
Logexp
)
finish()
(in
VerboseOptimization
)
finv()
(in
Square
)
f()
(in
LogexpClipped
)
finv()
(in
Exponent
)
finv()
(in
Transformation
)
f()
(in
LogexpNeg
)
finv()
(in
Logexp
)
Fix
(in
paramz.ties_and_remappings
)
f()
(in
Logistic
)
finv()
(in
LogexpClipped
)
FIXED
(in
paramz.transformations
)
f()
(in
NegativeExponent
)
finv()
(in
LogexpNeg
)
flattened_parameters
(in
Param
)
f()
(in
NegativeLogexp
)
finv()
(in
Logistic
)
flattened_parameters
(in
Parameterized
)
f()
(in
NormalEta
)
finv()
(in
NegativeExponent
)
flush()
(in
ObserverList
)
f()
(in
NormalTheta
)
finv()
(in
NegativeLogexp
)
FunctionCache
(in
paramz.caching
)
f()
(in
Square
)
finv()
(in
NormalEta
)
G
get_optimizer()
(in
paramz.optimization.optimization
)
gradfactor()
(in
LogexpNeg
)
gradfactor()
(in
NormalTheta
)
get_property_string()
(in
Param
)
gradfactor()
(in
Logistic
)
gradfactor()
(in
Square
)
get_property_string()
(in
Parameterized
)
gradfactor()
(in
NegativeExponent
)
gradfactor()
(in
Transformation
)
getTieFlag()
(in
Tie
)
gradfactor()
(in
NegativeLogexp
)
gradfactor_non_natural()
(in
NormalNaturalThroughTheta
)
gradcheckable
(in
paramz.core
)
gradfactor()
(in
NormalEta
)
gradfactor_non_natural()
(in
Transformation
)
Gradcheckable
(in
paramz.core.gradcheckable
)
gradfactor()
(in
NormalNaturalAntti
)
gradient
(in
Parameterizable
)
gradfactor()
(in
Exponent
)
gradfactor()
(in
NormalNaturalThroughEta
)
gradient
(in
Param
)
gradfactor()
(in
Logexp
)
gradfactor()
(in
NormalNaturalThroughTheta
)
gradient_full
(in
OptimizationHandlable
)
gradfactor()
(in
LogexpClipped
)
gradfactor()
(in
NormalNaturalWhooot
)
grep_param_names()
(in
Parameterized
)
H
has_parent()
(in
Parentable
)
hierarchy_name()
(in
Nameable
)
heres_johnny()
(in
P
)
HierarchyError
(in
paramz.core
)
I
id()
(in
Cacher
)
initialize()
(in
Exponent
)
initialize()
(in
Square
)
index()
(in
ArrayList
)
initialize()
(in
Logexp
)
initialize()
(in
Transformation
)
index_empty()
(in
paramz.core.index_operations
)
initialize()
(in
LogexpClipped
)
initialize_parameter()
(in
Parameterizable
)
index_operations
(in
paramz.core
)
initialize()
(in
LogexpNeg
)
InitTests
(in
paramz.tests.parameterized_tests
)
index_operations_tests
(in
paramz.tests
)
initialize()
(in
Logistic
)
intarray_default_factory()
(in
paramz.core.lists_and_dicts
)
indexable
(in
paramz.core
)
initialize()
(in
NegativeExponent
)
IntArrayDict
(in
paramz.core.lists_and_dicts
)
Indexable
(in
paramz.core.indexable
)
initialize()
(in
NegativeLogexp
)
is_fixed
(in
Constrainable
)
indices()
(in
ParameterIndexOperations
)
initialize()
(in
NormalEta
)
is_fixed
(in
Param
)
indices()
(in
ParameterIndexOperationsView
)
initialize()
(in
NormalNaturalAntti
)
items()
(in
ParameterIndexOperations
)
init()
(in
Regularizer
)
initialize()
(in
NormalTheta
)
items()
(in
ParameterIndexOperationsView
)
L
Lasso
(in
paramz.examples.ridge_regression
)
log_jacobian()
(in
Exponent
)
log_min_bound
(in
LogexpClipped
)
link_parameter()
(in
Parameterized
)
log_jacobian()
(in
Logexp
)
Logexp
(in
paramz.transformations
)
link_parameters()
(in
Parameterized
)
log_jacobian()
(in
Transformation
)
logexp
(in
NegativeLogexp
)
ListDictTestCase
(in
paramz.tests.pickle_tests
)
log_jacobian_grad()
(in
Exponent
)
LogexpClipped
(in
paramz.transformations
)
lists_and_dicts
(in
paramz.core
)
log_jacobian_grad()
(in
Logexp
)
LogexpNeg
(in
paramz.transformations
)
lists_and_dicts_tests
(in
paramz.tests
)
log_jacobian_grad()
(in
Transformation
)
logger
(in
paramz.parameterized
)
load()
(in
paramz
)
log_max_bound
(in
LogexpClipped
)
Logistic
(in
paramz.transformations
)
M
mapping()
(in
Remapping
)
min_bound
(in
LogexpClipped
)
Model
(in
paramz.model
)
max_bound
(in
LogexpClipped
)
model
(in
paramz
)
ModelTest
(in
paramz.tests.parameterized_tests
)
N
name
(in
Nameable
)
NormalEta
(in
paramz.transformations
)
NormalTheta
(in
paramz.transformations
)
nameable
(in
paramz.core
)
NormalNaturalAntti
(in
paramz.transformations
)
notify_observers()
(in
Observable
)
Nameable
(in
paramz.core.nameable
)
NormalNaturalThroughEta
(in
paramz.transformations
)
num_params
(in
OptimizationHandlable
)
NegativeExponent
(in
paramz.transformations
)
NormalNaturalThroughTheta
(in
paramz.transformations
)
num_params
(in
Parameterizable
)
NegativeLogexp
(in
paramz.transformations
)
NormalNaturalWhooot
(in
paramz.transformations
)
num_params
(in
Param
)
O
objective_function()
(in
RidgeRegression
)
opt()
(in
Opt_Adadelta
)
opt_simplex
(in
paramz.optimization.optimization
)
objective_function()
(in
Model
)
opt()
(in
Optimizer
)
opt_tnc
(in
paramz.optimization.optimization
)
objective_function_gradients()
(in
Model
)
opt()
(in
RProp
)
opt_wrapper()
(in
paramz.model
)
ObsAr
(in
paramz.core.observable_array
)
opt()
(in
opt_SCG
)
optimization
(in
paramz
)
observable
(in
paramz.core
)
opt()
(in
opt_bfgs
)
optimization
(in
paramz.optimization
)
Observable
(in
paramz.core.observable
)
opt()
(in
opt_lbfgsb
)
OptimizationHandlable
(in
paramz.core.parameter_core
)
observable_array
(in
paramz.core
)
opt()
(in
opt_simplex
)
optimize()
(in
Model
)
observable_tests
(in
paramz.tests
)
opt()
(in
opt_tnc
)
optimize_restarts()
(in
Model
)
ObserverList
(in
paramz.core.lists_and_dicts
)
Opt_Adadelta
(in
paramz.optimization.optimization
)
Optimizer
(in
paramz.optimization.optimization
)
on_cache_changed()
(in
Cacher
)
opt_bfgs
(in
paramz.optimization.optimization
)
optimizer_array
(in
OptimizationHandlable
)
one
(in
paramz.tests.index_operations_tests
)
opt_lbfgsb
(in
paramz.optimization.optimization
)
opt()
(in
Adam
)
opt_SCG
(in
paramz.optimization.optimization
)
P
P
(in
paramz.tests.parameterized_tests
)
ParameterizedTest
(in
paramz.tests.parameterized_tests
)
pickle()
(in
Pickleable
)
param
(in
paramz
)
parameters
(in
Param
)
pickle_tests
(in
paramz.tests
)
Param
(in
paramz.param
)
parameters_changed()
(in
Parameterizable
)
pickleable
(in
paramz.core
)
param_array
(in
Parameterizable
)
parameters_changed()
(in
Regularizer
)
Pickleable
(in
paramz.core.pickleable
)
param_array
(in
Param
)
parameters_changed()
(in
RidgeRegression
)
plot()
(in
Transformation
)
ParamConcatenation
(in
paramz.param
)
parameters_changed()
(in
ParamTestParent
)
Polynomial
(in
paramz.examples.ridge_regression
)
parameter_core
(in
paramz.core
)
parameters_changed()
(in
ParameterizedTest
)
predict()
(in
RidgeRegression
)
parameter_names()
(in
OptimizationHandlable
)
parameters_changed()
(in
Remapping
)
prepare_cache_id()
(in
Cacher
)
parameter_names()
(in
Param
)
parameters_changed()
(in
Tie
)
print_out()
(in
VerboseOptimization
)
parameter_names_flat()
(in
OptimizationHandlable
)
ParametersChangedMeta
(in
paramz.parameterized
)
print_status()
(in
VerboseOptimization
)
ParameterIndexOperations
(in
paramz.core.index_operations
)
params_changed_count
(in
ParameterizedTest
)
propagate_val()
(in
Tie
)
ParameterIndexOperationsView
(in
paramz.core.index_operations
)
ParamTestParent
(in
paramz.tests.observable_tests
)
properties()
(in
ParameterIndexOperations
)
Parameterizable
(in
paramz.core.parameter_core
)
paramz
properties()
(in
ParameterIndexOperationsView
)
parameterized
(in
paramz
)
parent_changed_count
(in
ParamTestParent
)
properties_dict_for()
(in
ParameterIndexOperations
)
Parameterized
(in
paramz.parameterized
)
parentable
(in
paramz.core
)
properties_dict_for()
(in
ParameterIndexOperationsView
)
parameterized_tests
(in
paramz.tests
)
Parentable
(in
paramz.core.parentable
)
properties_for()
(in
ParameterIndexOperations
)
ParameterizedTest
(in
paramz.tests.observable_tests
)
phi()
(in
RidgeRegression
)
properties_for()
(in
ParameterIndexOperationsView
)
R
randomize()
(in
OptimizationHandlable
)
remove_index_operation()
(in
Indexable
)
ridge_regression
(in
paramz.examples
)
Regularizer
(in
paramz.examples.ridge_regression
)
remove_indices()
(in
paramz.core.index_operations
)
RidgeRegression
(in
paramz.examples.ridge_regression
)
Remapping
(in
paramz.ties_and_remappings
)
remove_observer()
(in
Observable
)
RProp
(in
paramz.optimization.optimization
)
remove()
(in
ParameterIndexOperations
)
reset()
(in
Cacher
)
run()
(in
Optimizer
)
remove()
(in
ParameterIndexOperationsView
)
reset()
(in
FunctionCache
)
remove()
(in
ObserverList
)
Ridge
(in
paramz.examples.ridge_regression
)
S
save()
(in
Parameterizable
)
setUp()
(in
Test
)
shift_left()
(in
ParameterIndexOperations
)
scg
(in
paramz.optimization
)
setUp()
(in
Test
)
shift_left()
(in
ParameterIndexOperationsView
)
SCG()
(in
paramz.optimization.scg
)
setUp()
(in
ArrayCoreTest
)
shift_right()
(in
ParameterIndexOperations
)
set_updates()
(in
Observable
)
setUp()
(in
InitTests
)
shift_right()
(in
ParameterIndexOperationsView
)
setUp()
(in
Test
)
setUp()
(in
ModelTest
)
size
(in
ParameterIndexOperations
)
setUp()
(in
TestDecorator
)
setUp()
(in
ParameterizedTest
)
size
(in
ParameterIndexOperationsView
)
setUp()
(in
Test
)
setUp()
(in
Test
)
Square
(in
paramz.transformations
)
T
tearDown()
(in
Test
)
test_index_operations()
(in
ParameterizedTest
)
test_regular_expression_misc()
(in
ModelTest
)
Test
(in
paramz.tests.cacher_tests
)
test_index_view()
(in
Test
)
test_remove()
(in
Test
)
Test
(in
paramz.tests.index_operations_tests
)
test_indexview_remove()
(in
Test
)
test_remove_parameter()
(in
ParameterizedTest
)
Test
(in
paramz.tests.lists_and_dicts_tests
)
test_init()
(in
ArrayCoreTest
)
test_remove_parameter_param_array_grad_array()
(in
ParameterizedTest
)
Test
(in
paramz.tests.observable_tests
)
test_initialize()
(in
InitTests
)
test_reset()
(in
Test
)
Test
(in
paramz.tests.pickle_tests
)
test_likelihood_replicate()
(in
ModelTest
)
test_reset()
(in
TestDecorator
)
Test
(in
paramz.tests.verbose_optimize_tests
)
test_likelihood_set()
(in
ModelTest
)
test_reset_on_operation_error()
(in
Test
)
Test2D
(in
paramz.tests.examples_tests
)
test_load_initialized()
(in
InitTests
)
test_set_empty()
(in
ModelTest
)
test_add_parameter()
(in
ParameterizedTest
)
test_misc()
(in
Test
)
test_set_error()
(in
ModelTest
)
test_add_parameter_already_in_hirarchy()
(in
ParameterizedTest
)
test_name()
(in
Test
)
test_set_get()
(in
ModelTest
)
test_add_parameter_in_hierarchy()
(in
ParameterizedTest
)
test_names()
(in
ParameterizedTest
)
test_set_gradients()
(in
ModelTest
)
test_cached_atomic_int()
(in
Test
)
test_names_already_exist()
(in
ParameterizedTest
)
test_set_param_array()
(in
ParameterizedTest
)
test_cached_atomic_str()
(in
Test
)
test_num_params()
(in
ParameterizedTest
)
test_set_params()
(in
Test
)
test_cached_ObsAr()
(in
Test
)
test_observable()
(in
Test
)
test_shift_left()
(in
Test
)
test_cacher_cache()
(in
TestDecorator
)
test_observable_array()
(in
Test
)
test_shift_right()
(in
Test
)
test_caching_non_cachables()
(in
Test
)
test_offswitch()
(in
TestDecorator
)
test_signature()
(in
TestDecorator
)
test_caching_offswitch()
(in
ModelTest
)
test_opcalls()
(in
TestDecorator
)
test_slice()
(in
ArrayCoreTest
)
test_casting()
(in
TestMisc
)
test_optimize_ada()
(in
ModelTest
)
test_sum_ObsAr()
(in
Test
)
test_chached_ObsAr_atomic()
(in
Test
)
test_optimize_adam()
(in
ModelTest
)
test_timestrings()
(in
Test
)
test_checkgrad()
(in
ModelTest
)
test_optimize_cgd()
(in
ModelTest
)
test_traverse_parents()
(in
ParameterizedTest
)
test_checkgrad_hierarchy_error()
(in
ParameterizedTest
)
test_optimize_error()
(in
ModelTest
)
test_unfixed_param_array()
(in
ParameterizedTest
)
test_clear()
(in
Test
)
test_optimize_fix()
(in
ModelTest
)
test_updates()
(in
ModelTest
)
test_constraints()
(in
ParameterizedTest
)
test_optimize_org_bfgs()
(in
ModelTest
)
test_view_of_view()
(in
Test
)
test_constraints_in_init()
(in
paramz.tests.parameterized_tests
)
test_optimize_preferred()
(in
ModelTest
)
testArrayList()
(in
Test
)
test_constraints_link_unlink()
(in
ParameterizedTest
)
test_optimize_restarts()
(in
ModelTest
)
TestDecorator
(in
paramz.tests.cacher_tests
)
test_constraints_set_direct()
(in
ModelTest
)
test_optimize_rprop()
(in
ModelTest
)
testLassoRegression()
(in
Test2D
)
test_constraints_testmodel()
(in
ModelTest
)
test_optimize_scg()
(in
ModelTest
)
TestMisc
(in
paramz.tests.observable_tests
)
test_constraints_views()
(in
ParameterizedTest
)
test_optimize_simplex()
(in
ModelTest
)
testObsAr()
(in
Test
)
test_copy()
(in
Test
)
test_optimize_tnc()
(in
ModelTest
)
testPrintObserverListObj()
(in
Test
)
test_default_constraints()
(in
ParameterizedTest
)
test_original()
(in
ParameterizedTest
)
testPrintObserverListObsAr()
(in
Test
)
test_empty_parameterized()
(in
ModelTest
)
test_param()
(in
Test
)
testPrintObserverListParameterized()
(in
Test
)
test_finish()
(in
Test
)
test_param_names()
(in
ParameterizedTest
)
testPrintPriority()
(in
Test
)
test_fix_constrain()
(in
ModelTest
)
test_parameter_index_operations()
(in
Test
)
testRidgeRegression()
(in
Test2D
)
test_fix_unfix()
(in
ModelTest
)
test_parameter_modify_in_init()
(in
paramz.tests.parameterized_tests
)
tests
(in
paramz
)
test_fix_unfix_constraints()
(in
ModelTest
)
test_parameterized()
(in
Test
)
three
(in
paramz.tests.index_operations_tests
)
test_fixed_optimizer_copy()
(in
ParameterizedTest
)
test_pickling()
(in
Test
)
Tie
(in
paramz.ties_and_remappings
)
test_fixes()
(in
ParameterizedTest
)
test_print()
(in
Test
)
ties_and_remappings
(in
paramz
)
test_fixing_optimize()
(in
ModelTest
)
test_printing()
(in
ModelTest
)
toggle_update()
(in
Updateable
)
test_fixing_randomize()
(in
ParameterizedTest
)
test_printing()
(in
ParameterizedTest
)
Transformation
(in
paramz.transformations
)
test_fixing_randomize_parameter_handling()
(in
ParameterizedTest
)
test_priority()
(in
Test
)
transformations
(in
paramz
)
test_force_kwargs()
(in
Test
)
test_priority_notify()
(in
Test
)
traverse()
(in
Parameterizable
)
test_get_by_name()
(in
ModelTest
)
test_pydot()
(in
ModelTest
)
traverse_parents()
(in
Parameterizable
)
test_hierarchy_error()
(in
ModelTest
)
test_randomize()
(in
ParameterizedTest
)
trigger_update()
(in
Updateable
)
test_index_conversions()
(in
Test
)
test_raveled_index()
(in
ModelTest
)
two
(in
paramz.tests.index_operations_tests
)
U
unconstrain()
(in
Constrainable
)
unconstrain_positive()
(in
ParamConcatenation
)
update_error()
(in
Regularizer
)
unconstrain()
(in
ParamConcatenation
)
UNFIXED
(in
paramz.transformations
)
update_error()
(in
Ridge
)
unconstrain_bounded()
(in
Constrainable
)
unfixed_param_array
(in
Parameterizable
)
update_model()
(in
Updateable
)
unconstrain_bounded()
(in
ParamConcatenation
)
unlink_parameter()
(in
Parameterized
)
update_toggle()
(in
Updateable
)
unconstrain_fixed()
(in
Constrainable
)
update()
(in
ParameterIndexOperations
)
updateable
(in
paramz.core
)
unconstrain_fixed()
(in
ParamConcatenation
)
update()
(in
ParameterIndexOperationsView
)
Updateable
(in
paramz.core.updateable
)
unconstrain_negative()
(in
Constrainable
)
update()
(in
VerboseOptimization
)
util
(in
paramz
)
unconstrain_negative()
(in
ParamConcatenation
)
update_all_params()
(in
ParamConcatenation
)
unconstrain_positive()
(in
Constrainable
)
update_error()
(in
Lasso
)
V
values
(in
ObsAr
)
values()
(in
ParamConcatenation
)
verbose_optimize_tests
(in
paramz.tests
)
values
(in
Param
)
verbose_optimization
(in
paramz.optimization
)
VerboseOptimization
(in
paramz.optimization.verbose_optimization
)
W
weights
(in
RidgeRegression
)
_
__array_finalize__()
(in
ObsAr
)
__isub__()
(in
ObsAr
)
__str__()
(in
NormalTheta
)
__array_finalize__()
(in
Param
)
__isub__()
(in
ParamConcatenation
)
__str__()
(in
Square
)
__array_priority__
(in
ObsAr
)
__iter__()
(in
ObserverList
)
__str__()
(in
Transformation
)
__array_priority__
(in
Param
)
__itruediv__()
(in
ObsAr
)
__version__'
(in
paramz
)
__array_wrap__()
(in
ObsAr
)
__itruediv__()
(in
ParamConcatenation
)
_add_io()
(in
Indexable
)
__call__()
(in
Cache_this
)
__ixor__()
(in
ObsAr
)
_add_parameter_name()
(in
Parameterizable
)
__call__()
(in
Cacher
)
__ixor__()
(in
ParamConcatenation
)
_add_to_index_operations()
(in
Indexable
)
__call__()
(in
ParametersChangedMeta
)
__le__()
(in
ParamConcatenation
)
_allowed_failures
(in
Model
)
__contains__()
(in
ArrayList
)
__len__()
(in
ObserverList
)
_BOUNDED
(in
paramz.domains
)
__deepcopy__()
(in
Cacher
)
__lt__()
(in
ParamConcatenation
)
_callback()
(in
Test
)
__deepcopy__()
(in
ParameterIndexOperations
)
__name__
(in
Cacher
)
_check_change()
(in
Tie
)
__deepcopy__()
(in
ParameterIndexOperationsView
)
__ne__()
(in
ParamConcatenation
)
_check_for_climin()
(in
paramz.optimization.optimization
)
__deepcopy__()
(in
ObsAr
)
__new__()
(in
ObsAr
)
_checkgrad()
(in
Gradcheckable
)
__deepcopy__()
(in
Pickleable
)
__new__()
(in
Param
)
_checkgrad()
(in
Model
)
__deepcopy__()
(in
Param
)
__new__()
(in
LogexpClipped
)
_connect_fixes()
(in
Constrainable
)
__delitem__()
(in
ParameterIndexOperations
)
__new__()
(in
Logistic
)
_connect_parameters()
(in
OptimizationHandlable
)
__delitem__()
(in
ParameterIndexOperationsView
)
__new__()
(in
NormalEta
)
_connect_parameters()
(in
Parameterized
)
__enter__()
(in
VerboseOptimization
)
__new__()
(in
NormalNaturalAntti
)
_description_str
(in
Param
)
__eq__()
(in
ParamConcatenation
)
__new__()
(in
NormalNaturalThroughEta
)
_description_str
(in
Parameterized
)
__exit__()
(in
VerboseOptimization
)
__new__()
(in
NormalNaturalThroughTheta
)
_disconnect_parent()
(in
Indexable
)
__fixed__
(in
paramz.transformations
)
__new__()
(in
NormalNaturalWhooot
)
_disconnect_parent()
(in
Parentable
)
__ge__()
(in
ParamConcatenation
)
__new__()
(in
NormalTheta
)
_ensure_fixes()
(in
Constrainable
)
__getitem__()
(in
ParameterIndexOperations
)
__new__()
(in
Transformation
)
_ensure_fixes()
(in
Param
)
__getitem__()
(in
ParameterIndexOperationsView
)
__package__
(in
paramz
)
_exp_lim_val
(in
paramz.transformations
)
__getitem__()
(in
ObserverList
)
__package__
(in
paramz.__version__'
)
_expand_label_buf()
(in
Tie
)
__getitem__()
(in
Param
)
__package__
(in
paramz.caching
)
_expandTieParam()
(in
Tie
)
__getitem__()
(in
ParamConcatenation
)
__package__
(in
paramz.core
)
_fail_count
(in
Model
)
__getitem__()
(in
Parameterized
)
__package__
(in
paramz.core.constrainable
)
_filter_index()
(in
ParameterIndexOperationsView
)
__getslice__()
(in
ObsAr
)
__package__
(in
paramz.core.gradcheckable
)
_fixes_
(in
Param
)
__getstate__()
(in
Cacher
)
__package__
(in
paramz.core.index_operations
)
_format_spec()
(in
Param
)
__getstate__()
(in
ParameterIndexOperationsView
)
__package__
(in
paramz.core.indexable
)
_format_spec()
(in
Parameterized
)
__getstate__()
(in
Pickleable
)
__package__
(in
paramz.core.lists_and_dicts
)
_get_original()
(in
Constrainable
)
__getstate__()
(in
Optimizer
)
__package__
(in
paramz.core.nameable
)
_get_original()
(in
Param
)
__getstate__()
(in
NormalTheta
)
__package__
(in
paramz.core.observable
)
_grads()
(in
Model
)
__gt__()
(in
ParamConcatenation
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__package__
(in
paramz.core.observable_array
)
_has_fixes()
(in
Constrainable
)
__iadd__()
(in
ObsAr
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__package__
(in
paramz.core.parameter_core
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_highest_parent_
(in
Parentable
)
__iadd__()
(in
ParamConcatenation
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__package__
(in
paramz.core.parentable
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_indices()
(in
Param
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__iand__()
(in
ObsAr
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__package__
(in
paramz.core.pickleable
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_inherit_doc()
(in
paramz.util
)
__iand__()
(in
ParamConcatenation
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__package__
(in
paramz.core.updateable
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_init_labelBuf()
(in
Tie
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__idiv__()
(in
ObsAr
)
__package__
(in
paramz.domains
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_instance
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Logexp
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__idiv__()
(in
ParamConcatenation
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__package__
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paramz.examples
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_instance
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Transformation
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__ifloordiv__()
(in
ObsAr
)
__package__
(in
paramz.examples.ridge_regression
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_instances
(in
LogexpClipped
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__ifloordiv__()
(in
ParamConcatenation
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__package__
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paramz.model
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_instances
(in
Logistic
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__ilshift__()
(in
ObsAr
)
__package__
(in
paramz.optimization
)
_instances
(in
NormalEta
)
__ilshift__()
(in
ParamConcatenation
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__package__
(in
paramz.optimization.optimization
)
_instances
(in
NormalNaturalAntti
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__imod__()
(in
ObsAr
)
__package__
(in
paramz.optimization.scg
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_instances
(in
NormalNaturalThroughEta
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ParamConcatenation
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(in
paramz.optimization.verbose_optimization
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(in
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(in
ObsAr
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paramz.param
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(in
NormalNaturalWhooot
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Param
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Constrainable
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__package__
(in
paramz.tests.lists_and_dicts_tests
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(in
Param
)
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(in
Gradcheckable
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(in
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(in
Tie
)
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(in
ParameterIndexOperations
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_name_changed()
(in
Parameterizable
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(in
ParameterIndexOperationsView
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__package__
(in
paramz.tests.pickle_tests
)
_name_digit
(in
paramz.core.parameter_core
)
__init__()
(in
Indexable
)
__package__
(in
paramz.tests.verbose_optimize_tests
)
_NEGATIVE
(in
paramz.domains
)
__init__()
(in
IntArrayDict
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__package__
(in
paramz.ties_and_remappings
)
_notify_parent_change()
(in
Parameterizable
)
__init__()
(in
ObserverList
)
__package__
(in
paramz.transformations
)
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(in
Parentable
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__init__()
(in
Nameable
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__package__
(in
paramz.util
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(in
Model
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__init__()
(in
Observable
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__precision__
(in
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__init__()
(in
OptimizationHandlable
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__print_threshold__
(in
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(in
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__init__()
(in
Parameterizable
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__reduce__()
(in
ObsAr
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_offset_for()
(in
Indexable
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__init__()
(in
Parentable
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__repr__()
(in
ObserverList
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_parameters_changed_notification()
(in
Parameterizable
)
__init__()
(in
Pickleable
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__repr__()
(in
Param
)
_parent_
(in
Parentable
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__init__()
(in
Updateable
)
__repr__()
(in
ParamConcatenation
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_parent_changed()
(in
Indexable
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__init__()
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Basis
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(in
Transformation
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_parent_changed()
(in
Parentable
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(in
Lasso
)
__setattr__()
(in
Parameterized
)
_parent_index_
(in
Parentable
)
__init__()
(in
Polynomial
)
__setitem__()
(in
ObsAr
)
_pass_through_notify_observers()
(in
Parameterizable
)
__init__()
(in
Regularizer
)
__setitem__()
(in
ParamConcatenation
)
_phi
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RidgeRegression
)
__init__()
(in
Ridge
)
__setitem__()
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Parameterized
)
_POSITIVE
(in
paramz.domains
)
__init__()
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RidgeRegression
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__setslice__()
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ObsAr
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_propagate_param_grad()
(in
OptimizationHandlable
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__init__()
(in
Model
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__setstate__()
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Cacher
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_raveled_index()
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Indexable
)
__init__()
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Adam
)
__setstate__()
(in
ParameterIndexOperationsView
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_raveled_index()
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Param
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__init__()
(in
Opt_Adadelta
)
__setstate__()
(in
Indexable
)
_raveled_index_for()
(in
Indexable
)
__init__()
(in
Optimizer
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__setstate__()
(in
ObsAr
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_raveled_index_for()
(in
Param
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__init__()
(in
RProp
)
__setstate__()
(in
Parameterizable
)
_raveled_index_for_transformed()
(in
Indexable
)
__init__()
(in
opt_SCG
)
__setstate__()
(in
Pickleable
)
_REAL
(in
paramz.domains
)
__init__()
(in
opt_bfgs
)
__setstate__()
(in
Parameterized
)
_remove_from_index_operations()
(in
Indexable
)
__init__()
(in
opt_lbfgsb
)
__setstate__()
(in
NormalTheta
)
_remove_parameter_name()
(in
Parameterizable
)
__init__()
(in
opt_simplex
)
__str__()
(in
Cacher
)
_removeTieParam()
(in
Tie
)
__init__()
(in
opt_tnc
)
__str__()
(in
ParameterIndexOperations
)
_repr_html_()
(in
Model
)
__init__()
(in
VerboseOptimization
)
__str__()
(in
ParameterIndexOperationsView
)
_repr_html_()
(in
Param
)
__init__()
(in
Param
)
__str__()
(in
ObserverList
)
_repr_html_()
(in
Parameterized
)
__init__()
(in
ParamConcatenation
)
__str__()
(in
Model
)
_set_fixed()
(in
Constrainable
)
__init__()
(in
Parameterized
)
__str__()
(in
Optimizer
)
_set_unfixed()
(in
Constrainable
)
__init__()
(in
P
)
__str__()
(in
Param
)
_setup_observers()
(in
ObsAr
)
__init__()
(in
Tie
)
__str__()
(in
ParamConcatenation
)
_setup_observers()
(in
Parameterizable
)
__init__()
(in
LogexpClipped
)
__str__()
(in
Parameterized
)
_setup_observers()
(in
Param
)
__init__()
(in
Logistic
)
__str__()
(in
Remapping
)
_short()
(in
Parameterized
)
__init__()
(in
NormalEta
)
__str__()
(in
Exponent
)
_shrink_label_buf()
(in
Tie
)
__init__()
(in
NormalNaturalAntti
)
__str__()
(in
Logexp
)
_size_transformed()
(in
OptimizationHandlable
)
__init__()
(in
NormalNaturalThroughEta
)
__str__()
(in
LogexpClipped
)
_sync_val_group()
(in
Tie
)
__init__()
(in
NormalNaturalThroughTheta
)
__str__()
(in
LogexpNeg
)
_transform_gradients()
(in
OptimizationHandlable
)
__init__()
(in
NormalNaturalWhooot
)
__str__()
(in
Logistic
)
_traverse()
(in
Parameterizable
)
__init__()
(in
NormalTheta
)
__str__()
(in
NegativeExponent
)
_trigger()
(in
Test
)
__ior__()
(in
ObsAr
)
__str__()
(in
NegativeLogexp
)
_trigger_params_changed()
(in
OptimizationHandlable
)
__ior__()
(in
ParamConcatenation
)
__str__()
(in
NormalEta
)
_trigger_priority()
(in
Test
)
__ipow__()
(in
ObsAr
)
__str__()
(in
NormalNaturalAntti
)
_trigger_start
(in
paramz.tests.observable_tests
)
__ipow__()
(in
ParamConcatenation
)
__str__()
(in
NormalNaturalThroughEta
)
_unpickle()
(in
paramz
)
__irshift__()
(in
ObsAr
)
__str__()
(in
NormalNaturalThroughTheta
)
_updateTieFlag()
(in
Tie
)
__irshift__()
(in
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__str__()
(in
NormalNaturalWhooot
)
Home
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Generated by Epydoc 3.0.1 on Tue Jul 4 11:59:27 2017
http://epydoc.sourceforge.net


Built-in middleware
elfi provides some builtin middleware. You’ll find documentation about them in this document.
logger (source
This middleware is used to log each change to whatever logging system you are using (a simple console.log by default)
import {createStore} from "elfi"
import createLoggerMiddleware from "elfi/middleware/logger"
const logger = createLoggerMiddleware()
const store = createStore(1, [logger])
You can define a custom logger by passing a function to
createLoggerMiddleware
. This function accepts a single argument which is
object with the following shape {oldState, newState, change}
.
import {createStore} from "elfi"
import createLoggerMiddleware from "elfi/middleware/logger"
function logOldState({oldState}) {
console.log(oldState)
}
const logger = createLoggerMiddleware(({oldState}) => console.log(oldState))
const store = createStore(1, [logger])
versioning (source
This middleware is used to add a version number to the state without triggering another state change.
import {createStore} from "elfi"
import createVersioningMiddleware from "elfi/middleware/versioning"
const versioning = createVersioningMiddleware()
const store = createStore(1, [versioning])
By default, it acts as if state is a simple object and sets the version
field
of that object. You will probably want to define how to set the version and for
this you can pass a custom setter function to createVersioningMiddleware
.
It will be called with the new state as the sole argument. Here’s an example with Immutable.js:
import Immutable from "immutable"
import {createStore} from "elfi"
import createVersioningMiddleware from "elfi/middleware/versioning"
const versioning = createVersioningMiddleware(state => (
state.set((state.get("version") || 0) + 1)
))
const store = createStore(new Immutable.Map(), [versioning])


Document Generation
Pre-cursor Word:
Number of Token to be generate:
Random next word based on Probability Distribution
LDA Document Generation
Perplexity:
TNG Document Generation
Perplexity:


1 cup mild bone broth (here) (see Note)
1 cup full-fat coconut milk
1 cup water
¼ cup cocoa powder
¼ cup steamed and then frozen cauliflower florets (about 3 florets) (see Note, here)
¼ cup granulated erythritol, or 20 drops liquid stevia
3 tablespoons chia seeds
Pinch of fine Himalayan salt
Fresh blackberries, for garnish (optional)
This chocolaty pudding might look like dessert, but it’s packing serious nutrition. I know bone broth and cauliflower seem like unlikely ingredients for a sweet recipe, but once you let go of conventional ideas about how certain foods should be used, it really opens the door for some creative and delicious options. Case in point: jars of creamy, sweet chocolate pudding made with bone broth and cauliflower! With a great balance of protein and carbs and a little less fat, this pudding is a great option for post-workout nutrition. It’s also toddler approved—I love to pack a jar in Jack’s lunch box! To get a smooth, creamy texture, you’ll need a high-powered blender, but this recipe works equally well as a tapioca-style pudding, made with a regular blender (see Variation below).
Place all of the ingredients in a high-powered blender. Blend on high until the chia seeds are pulverized and the mix is completely smooth and thick.
Pour the mixture into four 6-ounce jars with lids, cover, and refrigerate for at least 4 hours to thicken. Garnish with blackberries before serving, if desired. Store in the refrigerator for up to 1 week.
CHEF’S NOTE: I like to use beef bone broth, whether homemade from the recipe on here or store-bought. However, any kind of broth will work.
VARIATION: This recipe works best with a high-powered blender, which will completely pulverize the chia seeds. You can still make this recipe with a regular blender, but you’ll end up with a pudding that’s more like tapioca. To make, blend all of the ingredients except the chia seeds in the blender until smooth. Then pulse in ¼ cup of chia seeds.
SUBSTITUTIONS: If you can’t do coconut, replace the coconut milk with 2 tablespoons butter or ghee and ½ cup warm water.


@remarks An object that has no correlation between its state and its hash code value should typically not be used as the key. For example, String values are better than StringBuilder objects for use as keys.
You can also use the Item property to add new elements by setting the value of a key that does not exist in the Hashtable; for example, myCollection("myNonexistentKey") = myValue
. However, if the specified key already exists in the Hashtable, setting the Item property overwrites the old value. In contrast, the Add method does not modify existing elements.
If Count is less than the capacity of the Hashtable, this method is an O(1) operation. If the capacity needs to be increased to accommodate the new element, this method becomes an O(n) operation, where n is Count.
@exceptions| Exception | Condition |
|---|---|
| ArgumentException | An element with the same key already exists in the Hashtable. |
Public Sub Main() ' Creates and initializes a new Hashtable. Dim MyHT As New Hashtable MyHT.Add "one", "The" MyHT.Add "two", "quick" MyHT.Add "three", "brown" MyHT.Add "four", "fox" ' Displays the Hashtable. Debug.Print "The Hashtable contains the following:" PrintKeysAndValues MyHT End Sub Public Sub PrintKeysAndValues(ByVal MyHT As Hashtable) Dim de As DictionaryEntry Debug.Print t("\t-KEY-\t-VALUE-") For Each de In MyHT Debug.Print CorString.Format(t("\t{0}:\t{1}"), de.Key, de.Value) Next de Debug.Print End Sub ' This example code produces the following output. ' ' The Hashtable contains the following: ' -KEY- -VALUE- ' one: The ' two: quick ' four: fox ' three: brown


Fun Fact 1: I love running and traveling and 90% of the time I'm traveling I'm going to my destination to run a race. I run to get a workout in, explore my location and make it look like I'm not a tourist, even though I'm sure all the times I look at my phone to see how lost I am betray me.
Fun Fact 2: I was grew up in a village in Michigan that had precisely two stopilghts. Now I live in New York City and the block I live on has more than two stoplights. I've always been a big city girl, but sometimes I miss riding my bike down the center of the road and listening to the rain in the summer.
Fun Fact 3: I love street art and look for it everywhere I go. So far Los Angeles has been one of my favorite places to see it on display. I find the creativity and spontaneity of it inspiring and I think its impermanence makes it even more special. Our world is an art museum.


An anonymous reader has sent what is claimed to be a photograph of Dobson. I suspect this to be an April Fool's Day prank, but have sent the snap to Mr Poxhaven, soliciting his expert opinion. The envelope—with a smudged postmark—contained nothing else to indicate its provenance. Scribbled on the back of the photograph are just three words: “This is Dobson”, which is less than helpful as it is unclear whether it refers to the child clutching an ice lolly or to the gaunt, bespectacled adult behind him.


Overview
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G
Game
- Class in
mb.tictactoe.data
Contains all data about one game.
Game(String, Board)
- Constructor for class mb.tictactoe.data.
Game
Game(XmlTree)
- Constructor for class mb.tictactoe.data.
Game
game
- Variable in class mb.web.
WebThreadServer
gameEnds()
- Method in class mb.web.
WebThreadServer
Checks winning/loosing conditions and in case if any is fulfilled, sends appropiate messages.
gameOver(Board)
- Static method in class mb.tictactoe.
Ttt
GameParticipants
- Class in
mb.tictactoe
Simple pane used to do some per-participant operations, or just for displaying the list of them.
GameParticipants(ArrayList<Participant>, ActionListener, String)
- Constructor for class mb.tictactoe.
GameParticipants
gamesPlayed
- Variable in class mb.tictactoe.data.
ServerData.UserData
gamesWon
- Variable in class mb.tictactoe.data.
ServerData.UserData
gb
- Variable in class mb.graphics.
GridBagFrame
Short-named variable to use in the code.
gb
- Variable in class mb.graphics.
GridBagPane
Short-named variable to use in the code.
generateEntry(String)
- Method in class mb.tictactoe.
TttLog
Adds time stamp to a given message.
getAsLabel(String)
- Method in class mb.graphics.
GridBagFrame
getAsTextArea(String)
- Method in class mb.graphics.
GridBagFrame
Gets a component that ends with given string, and casts it to JTextField before return.
getAsTextField(String)
- Method in class mb.graphics.
GridBagFrame
Gets a component that ends with given string, and casts it to JTextField before return.
getAsTextField(String)
- Method in class mb.graphics.
GridBagPane
Gets a component that ends with given string, and casts it to JTextField before return.
getAttr(String)
- Method in class mb.web.
XmlTree
getBoard()
- Method in class mb.tictactoe.data.
Game
getBoardHeight()
- Method in class mb.tictactoe.
TttAdminDataPane
getBoardWidth()
- Method in class mb.tictactoe.
TttAdminDataPane
getByName(String)
- Method in class mb.graphics.
GridBagFrame
Finds the first component in this frame whose name ends with the given string.
getByName(String)
- Method in class mb.graphics.
GridBagPane
Finds the first component in this frame whose name ends with the given string.
getCol(int)
- Method in class mb.tictactoe.
TttBoard
getContents()
- Method in class mb.tictactoe.
TttBoard
getCurrPlayer()
- Method in class mb.tictactoe.data.
Board
getCurrPlayer()
- Method in class mb.tictactoe.data.
Game
getDtdURL()
- Method in class mb.web.
XmlTree
getFirstPlayer()
- Method in class mb.web.
WebThreadServer
getHeight()
- Method in class mb.tictactoe.data.
Board
getHeightStr()
- Method in class mb.tictactoe.
TttAdminDataPane
getHostname()
- Method in class mb.tictactoe.
TttServerDataPane
getHostname()
- Method in class mb.web.
WebThread
getId()
- Method in class mb.tictactoe.data.
ChatMsg
getKind()
- Method in class mb.tictactoe.data.
Participant
getKind()
- Method in class mb.tictactoe.
TttClientDataPane
getLastBoard()
- Method in class mb.tictactoe.
TttFrame
getLastByType(String)
- Method in class mb.graphics.
GridBagFrame
Finds the last (chronologically) component of a given type.
getLastByType(String)
- Method in class mb.graphics.
GridBagPane
Finds the last (chronologically) component of a given type.
getLastChat()
- Method in class mb.tictactoe.
TttFrame
getLastLabel()
- Method in class mb.graphics.
GridBagFrame
getLastLabel()
- Method in class mb.graphics.
GridBagPane
getLastLog()
- Method in class mb.tictactoe.
TttFrame
getLastMenu()
- Method in class mb.graphics.
GridBagFrame
Gets the last (chronologically) menu.
getLastServerDataPane()
- Method in class mb.tictactoe.
TttFrame
getLastTextArea()
- Method in class mb.graphics.
GridBagFrame
Gets the last (chronologically) JTextField in this frame.
getLastTextArea()
- Method in class mb.graphics.
GridBagPane
Gets the last (chronologically) JTextField in this frame.
getLastTextField()
- Method in class mb.graphics.
GridBagFrame
Gets the last (chronologically) JTextField in this frame.
getLastTextField()
- Method in class mb.graphics.
GridBagPane
Gets the last (chronologically) JTextField in this frame.
getLine()
- Method in class mb.web.
StreamReceiver
getMsg()
- Method in class mb.tictactoe.data.
ChatMsg
getMsg()
- Method in class mb.tictactoe.data.
SystemMsg
getMsg()
- Method in class mb.tictactoe.
TttChat
getName()
- Method in class mb.tictactoe.data.
Participant
getName()
- Method in class mb.web.
XmlTree
getNewName(JComponent)
- Method in class mb.graphics.
GridBagFrame
Constructs a name for new component that is just to be added to the frame.
getNewName(JComponent)
- Method in class mb.graphics.
GridBagPane
Constructs a name for new component that is just to be added to the frame.
getNextClientId()
- Method in class mb.web.
WebThreadServer
Returns unique id number, needed by clients.
getNickname()
- Method in class mb.tictactoe.data.
ChatMsg
getNickname()
- Method in class mb.tictactoe.
TttClientDataPane
getParticipantName()
- Method in class mb.web.
WebThreadServerClient
Returns login used by the user that caused this thread to start.
getParticipants()
- Method in class mb.tictactoe.data.
Game
getPassword()
- Method in class mb.tictactoe.data.
Participant
getPassword()
- Method in class mb.tictactoe.
TttClientDataPane
getPlayCount(Participant)
- Method in class mb.tictactoe.data.
ServerData
getPlayer(int)
- Method in class mb.tictactoe.data.
Game
getPort()
- Method in class mb.tictactoe.
TttServerDataPane
getPort()
- Method in class mb.web.
WebThread
getReceiver()
- Method in class mb.web.
StreamSide
getRow(int)
- Method in class mb.tictactoe.
TttBoard
getSecondPlayer()
- Method in class mb.web.
WebThreadServer
getSelectedParticipants()
- Method in class mb.tictactoe.
GameParticipants
getSender()
- Method in class mb.web.
StreamSide
getSide()
- Method in class mb.tictactoe.data.
Participant
getState()
- Method in class mb.tictactoe.data.
EmptyOrCrossOrNought
Returns state of the object.
getStreamSide(char)
- Method in class mb.web.
StreamPipe
getStreamSideA()
- Method in class mb.web.
StreamPipe
getStreamSideB()
- Method in class mb.web.
StreamPipe
getSubNode(String, int)
- Method in class mb.web.
XmlTree
Gets a sub node with a given subscript.
getSymbol()
- Method in class mb.tictactoe.data.
EmptyOrCrossOrNought
Gets the symbol that represents the state of this object.
getSymbol()
- Method in class mb.tictactoe.data.
Participant
getTempId()
- Method in class mb.tictactoe.data.
Participant
getTimeout()
- Method in class mb.tictactoe.
TttServerDataPane
getTimeout()
- Method in class mb.web.
WebThread
getType()
- Method in class mb.tictactoe.data.
ChatMsg
getValue()
- Method in class mb.web.
XmlTree
getWebId()
- Method in class mb.web.
WebThread
getWebIdFor(Participant)
- Method in class mb.web.
WebThreadServer
getWidth()
- Method in class mb.tictactoe.data.
Board
getWidthStr()
- Method in class mb.tictactoe.
TttAdminDataPane
getWinCount(Participant)
- Method in class mb.tictactoe.data.
ServerData
getWinLen()
- Method in class mb.tictactoe.data.
Board
getWinLen()
- Method in class mb.tictactoe.
TttAdminDataPane
getWinLenStr()
- Method in class mb.tictactoe.
TttAdminDataPane
getX()
- Method in class mb.tictactoe.data.
CellData
getY()
- Method in class mb.tictactoe.data.
CellData
GridBagFrame
- Class in
mb.graphics
GridBagFrame is an extension of JFrame that uses GridBagLayout to place components.
GridBagFrame(String, int, int, int, int)
- Constructor for class mb.graphics.
GridBagFrame
Constructs a GridBagFrame.
GridBagPane
- Class in
mb.graphics
Superclass for any pane used in TicTacToe.
GridBagPane(String)
- Constructor for class mb.graphics.
GridBagPane
Constructs a GridBagPane.
GridBagPane(String, ActionListener)
- Constructor for class mb.graphics.
GridBagPane
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APs
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Scan for WiFi access points
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Contact Me
I'm always looking for collabarators and people to talk to!
Email me at<EMAIL_ADDRESS>--- layout: default title: Contact Sarah Pullman permalink: contact/ ---
I'm always looking for collabarators and people to talk to!
Email me at sspullman@gmail.com.


- No Outside Help. Using any resource that can be found on the web is fair play, but you may not ask anyone outside of your team for assistance. This includes, but is not limited to the sharing of flags, hints, methodology, or other problem aids. Minor offenders will get a warning, and major offenders will be disqualified.
- Only attack platforms that are designated as targets. Any attack, including DoS, on scoring or other infrastructure will not be tolerated. All attackable services will be clearly marked. We are not responsible for unauthorized attacks, and breaking this rule is grounds for disqualification and possible prosecution by outside organizations.
- Competing teams may consist of up to 5 players, each an American citizen or resident, who is either attending high school in the US or 18 years of age or younger. Verification will be needed for winning teams. All teams must provide an adult contact at their school to vouch for their eligibility. Teams not in compliance with this will still be able to solve problems, but will not be able to win prizes or appear on scoreboards.
- Harassing other players through IRC or on social media will not be tolerated. Players being rude, inflammatory, or vulgar may be quieted or banned at the discretion of the moderators. Giving hints will result in a ban. This is a fun competition, but it is still educational, so appropriate behavior is expected.
- Enforcement and interpretation of rules will be at the sole discretion of the TJCTF organizers. Please see the official agreement for more information, or ask an organizer in IRC for clarification on the rules.


KnowRe web development curriculum for noobs
WebDevCurriculum / +
| This branch is 5 commits ahead of master. Pull request Compare | ||
|---|---|---|
| ... | ||
| FolderNames | Commit comment | last modified |
| README.md |
|---|
| KnowRe web development curriculum 2016 |


public class HirTable
extends java.lang.Object
The user needs to enter n, a, b and gdiff.
n : The Hirzebruch surface is F_n.
(a,b): the curve class is ah + bf with h^2 = n, f = fiber class.
gdiff: max difference between the arithmetic genus and geometric genus of
the curve the program will compute.
The program will compute the number of genus g curves in the linear system
|ih + jf| on F_n which satisfy tangency conditions (alpha, beta) with the
divisor E = h - nf.
1) ih + jf = ah + bf - kE for k = 0,...,a
(due to the recursive nature of Vakil's formula),
2) all valid tangency conditions alpha and beta (valid = satisfy
I(alpha) + I(beta) = j),
3) all g between arithmetic genus of ih +jf and (arithmetic genus of ih +jf) -gdiff.
alpha : tangency condition at assigned points.
beta : tangency condition at unassigned points. beta = (beta_1, beta_2,....)
The output numbers will be located at output/Hir
Note on algorithm:
alpha and beta are stored by ArrayList of Integers. The length of them
(and all alphaP, betaP etc...) are of fixed length which equals
maxlength = b + a * n+ gdiff + 1. This is because max number of fiber
class is in (ah+bf)-aE = bf+a*nf = (b+a*n)f and
g' = g - |gamma| + 1, => |gamma| = g - g' +1 = gdiff +1
maxlength = |beta'| = |beta+gamma|<= |beta| + |gamma| <= b+a * n+ gdiff +1.
Operations of integer sequences are handled by the binom class, which can take arrayList of any length, as long as they satisfy required assumptions (c>=d) for substract(c,d) and binom(c,d).
For possble future modification: If alpha and beta (and their variations) can take different length, ex: (1,2) = (1,2,0,0,..). Then they have to be trimmed while making key (the key class needs to be modified).
| Constructor and Description |
|---|
HirTable(int n,
int a,
int b,
int gdiff)
The constructor of the class.
|
| Modifier and Type | Method and Description |
|---|---|
static void |
main(java.lang.String[] args)
The main method of the class.
|
public HirTable(int n, int a, int b, int gdiff)
n
- The Hirzebruch surface is F_n, n >= 0.a
- The number of ample class h in the curve class ah + bf.b
- The number of fiber class h in the curve class ah + bf.gdiff
- The max difference between arithmetic genus and geometric
genus of the curve we'll compute.


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--- layout: null section-type: about title: About --- ## About
China · Henu · Sophomore · Software Engineering name : jiangcp(coding peasant)
always on the way


We provide
A 'Chance'.
To Try Your Luck.
Sometimes even beat it.
Here is the complete list of all 30 players. Select 11 players from all these and make your team. The amount you win (depending on your team performance) will be distributed once the game is over.


|
AssetTrackerRK
|
Class to hold things used during download. More...
#include <UbloxGPS.h>
Public Member Functions | |
| AssistNowDownload () | |
| Constructor. | |
| virtual | ~AssistNowDownload () |
| Destructor. | |
| bool | alloc (size_t bufferSize) |
| Allocate the buffer to hold temporary data. Required! More... | |
Protected Attributes | |
| size_t | bufferSize = 0 |
| Size of buffer in bytes as determined from alloc() | |
| GoogleMapsDeviceLocator | locator |
| Used to find location data from cellular or Wi-Fi. | |
| float | lat = 0.0 |
| Latitude in degrees from geolocation. | |
| float | lng = 0.0 |
| Longitude in degrees from geolocation. | |
| float | accuracy = 0.0 |
| Accuracy radius in meters from geolocation. | |
| float | elev = 0.0 |
| Elevation in meters from mean sea level from elevation API. | |
| TCPClient | client |
| TCPClient used to contact the u-blox aiding service. | |
| uint8_t * | buffer |
| Buffer to store data, allocated during alloc() | |
| size_t | bufferOffset = 0 |
| Offset currently being written to in buffer. | |
| bool | inHeader = true |
| Set to true if we are processing the HTTP header or false if not. | |
| size_t | contentLength = 0 |
| Content length of the GPS data. | |
Friends | |
| class | UbloxAssistNow |
Class to hold things used during download.
Since download happens infrequently (only at startup if the GPS needs it, this object is allocated on the heap by UbloxAssistNow when needed and deleted when not.
| bool AssistNowDownload::alloc | ( | size_t | bufferSize | ) |
Allocate the buffer to hold temporary data. Required!
| bufferSize | The size of the buffer in bytes. This must be large enough to hold the entire download of aiding data! |
The buffer size varies depending on the number of services, which aiding data is requested, and whether a location is provided.


Update: 2011/08/04 – with the release of rails 3.1.0.rc5 the deployment story solidified, and heroku guys published a blog post how to deploy 3.1 asset pipeline..
config.assets.enabled=false
and jammit will be happy.In my previous post I described the steps necessary to upgrade an existing application to Rails 3.1, but the post did not go into details about how to migrate an existing collection of assets (in my case packaged using Jammit/Jammit-S3 gems) to Sprockets based asset pipeline. Here we dive into the nitty gritty of the migration.
Rails exposes app.config.assets hash during Rails initialization process.
You can modify the values of the config hash inside your config/application.rb or config/environments/xxx.rb.
Here is the definition of the assets config hash with the defaults
rake assets:precompile
. If you have more then one package of js or css (e.g. application.css and mobile.css), you should config.assets.precompile += %w( mobile.css )
in your config/application.rbrm -rf public/assets
. If there are pre-generated files in /assets rails will serve those without processing your app/assets folder.package_path: jammit
to config/assets.ymlconfig.assets.enabled = true
inside config/application.rb= stylesheet_link_tag 'application'
and = javascript_include_tag 'application'
, before corresponding Jammit calls to = include_stylesheets :application
and = include_javascripts :application
Here we make asset pipeline serve jquery, jquery_ujs and jquery-ui javascript files that are bundled in jquery-rails gem.
//= require jquery
//= require jquery_ujs
//= require jquery-ui
You need to use compass gem from github for now
gem 'compass', :git => 'https://github.com/chriseppstein/compass.git', :branch => 'rails31'
gem 'sass', '3.1.5' # I had to fix this version due to a weird interaction b/w compass's blueprint and sass
Inside config/application.rb:
config.sass.load_paths << "#{Gem.loaded_specs['compass'].full_gem_path}/frameworks/compass/stylesheets"
config.sass.load_paths << "#{Gem.loaded_specs['compass'].full_gem_path}/frameworks/blueprint/stylesheets"
I also deleted config/compass.rb, as it does not appear to be doing anything (was only used for compass cli?)
To test, add @import "blueprint/reset";
into app/assets/stylesheets/application.css.scss, restart the server and inspect the content of /assets/application.css
sass-rails gem defines new helpers to use inside scss templates:
body {
some-path: asset-path("rails.png", image);
some-url: asset-url("rails.png", image);
}
By default Sprockets will concatenate all your javascripts into one /assets/application.js event in development environment. This may not be ideal if you have lots of files and need debugging. Adding :debug => true to the calls to include_javascript solves the issue:
= javascript_include_tag 'application', :debug => Rails.env.development?
If you are using Sass’s @import "somepartial";
in your application.css.scss, the partial file should be named _somepartial.css.scss
(.css.scss ending is important), otherwise variables defined in that partial will not be visible outside of that partial, and you will get Sass::SyntaxError: Undefined variable: "$xxx"
.
jQuery UI images are referenced from jQuery UI stylesheet as a relative url(‘images/image-xxx.png’), and this link gets broken because the final stylesheet that gets served to the browser is /assets/application.css. Instead of modifying jquery ui css, I moved the images under app/assets/images/images (should be vendor/assets/images/images??). This allows for a drop-in jquery-ui styles replacement without modifying all internal references to images.
If you are using Mongoid, you may notice that rendering a page takes forever, every image request takes a while. Apparently this is due to Mongoid preloading all models (and hittng mongod) for every request, even for an image. Adding
config.mongoid.preload_models = false
in your config/environments/development.rb makes your migration much much faster. (Beware if you are using single collection inheritance)
Running Rails asset pipeline in development mode will recompile css/js/images on each request, so for deployment to production you will want to precompile your assets. If a file exists under public/assets it will be served by rails without invoking the asset pipeline and recompiling the file.
Generally, to compile the assets, rails comes with assets:precompile rake task.
bundle exec rake assets:precompile RAILS_ENV=production
Setting production environment is important here, and therefore the guideline is to run it on the production server. The result of precompilation is the public/assets folder populated with all your compiled .js and .css fiels with MD5 hash included to the name. If you use sass-rails asset helpers, the paths inside css will also be rewritten to point to the fingerprinted assets.
Heroku now supports 3.1 asset compilation on their cedar stack
Once the app is deployed, heroku will compile requested assets on their cache miss, and store it in the app’s tmp directory automatically, solving the long stanging issue of hacking its read-only filesystem.
Oddly, it looks like precompiling assets has no effect on heroku (e.g. with heroku run rake -t assets:precompile
), it sill recompiles them on the first request.
Once you app can compile and serve the assets, you can setup an Amazon CloudFront CDN distribution with your server as the origin server. Then include the distribution’s domain name into
config.action_controller.asset_host = "xxxxxxxxxxxxx.cloudfront.net"
With Jammit you had to jump through the hoops, rewrite asset paths to bust CDN caches, upload to S3. With the fingerprinted assets, you just push your app to production and CloudFront will cache the assets on its servers. This is a big win for me as it removes a somewhat lengthy process of uploading all assets to S3.
The final cleanup consists of removing jammit and/or jammit-s3 gems from Gemfile, bundle install
it, removing config/assets.yml, calls to include jammit packages from the layout markup.


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Jamie is a psychology PhD student based at the University of Sussex.
The parameters available for a trial depend primarily on what plugin is used for the trial. However, there are several options that do not depend on the particular plugin; they are available for all trials.
The data
parameter enables tagging the trial with additional properties. This can be useful for storing properties of the trial that are not directly apparent from the values that the plugin records. The data
parameter value should be an object that contains key-value pairs.
A simple example is the Flanker Task. In this experiment, participants respond to the direction of an arrow, pressing a key to the left for a left-pointing arrow (<) and a key to the right for a right-pointing arrow (>). The arrow appears in the center of flankers, or arrows that the participant should ignore. Those flankers can be congruent (»»>) or incongruent («>«).
A trial for the Flanker Task written with jsPsych might look like this:
var trial = {
type: 'html-keyboard-response',
stimulus: '<<<<<',
choices: ['f','j'],
data: {
stimulus_type: 'congruent',
target_direction: 'left'
}
}
Note the use of the data parameter to add a property stimulus_type
with the value congruent
and a property target_direction
with the value left
. Having these properties recorded directly in the data simplifies data analysis, making it easy to aggregate data by stimulus_type
and/or target_direction
.
The default inter-trial interval (ITI) in jsPsych is 0 ms. This can be adjusted at the experiment-wide level by changing the default_iti
parameter in jsPsych.init()
.
The ITI can also be controlled at the trial level through the post_trial_gap
parameter. Setting this parameter to a positive integer x will cause a blank screen to display after the trial for x milliseconds.
var trial = {
type: 'html-keyboard-response',
stimulus: 'There will be a 1.5 second blank screen after this trial.',
post_trial_gap: 1500
}
Immediately before a trial runs, there is an opportunity to run an arbitrary function through the on_start
event handler. This event handler is passed a single argument containing an editable copy of the trial parameters. This event handler can therefore be used to alter the trial based on the state of the experiment, among other uses.
var trial = {
type: 'html-keyboard-response',
stimulus: '<<<<<',
choices: ['f','j'],
data: {
stimulus_type: 'congruent',
target_direction: 'left'
},
on_start: function(trial){
trial.stimulus = '<<><<';
trial.data.stimulus_type = 'incongruent';
}
}
After a trial is completed, there is an opportunity to run an arbitrary function through the on_finish
event handler. This event handler is passed a single argument containing an editable copy of the data recorded for that trial. This event handler can therefore be used to update the state of the experiment based on the data collected or modify the data collected.
This can be useful to calculate new data properties that were unknowable at the start of the trial. For example, with the Flanker Task example above, the on_finish
event could add a new property correct
.
var trial = {
type: 'html-keyboard-response',
stimulus: '<<<<<',
choices: ['f','j'],
data: {
stimulus_type: 'congruent',
target_direction: 'left'
},
on_finish: function(data){
if(data.key_press == 70){// 70 is the numeric code for f
data.correct = true; // can add property correct by modify data object directly
} else {
data.correct = false;
}
}
}
The on_load
callback can be added to any trial. The callback will trigger once the trial has completed loading. For most plugins, this will occur once the display has been initially updated but before any user interactions or timed events (e.g., animations) have occurred.
var trial = {
type: 'image-keyboard-response',
stimulus: 'imgA.png',
on_load: function() {
console.log('The trial just finished loading.');
}
};
Most plugins allow parameters to be functions. In a typical declaration of a jsPsych trial, parameters have to be known at the start of the experiment. This makes it impossible to alter the content of the trial based on the outcome of previous trials. When functions are used as parameters for a block of trials, the function is evaluated at the start of each trial, and the return value of the function is used as the parameter. This enables dynamic updating of the parameter based on data that a subject has generated.
Here is a sketch of how this functionality could be used to display feedback to a subject in the Flanker Task.
var timeline = [];
var trial = {
type: 'html-keyboard-response',
stimulus: '<<<<<',
choices: ['f','j'],
data: {
stimulus_type: 'congruent',
target_direction: 'left'
},
on_finish: function(data){
if(data.key_press == 70){// 70 is the numeric code for f
data.correct = true; // can add property correct by modify data object directly
} else {
data.correct = false;
}
}
}
var feedback = {
type: 'html-keyboard-response',
stimulus: function(){
var last_trial_correct = jsPsych.data.get().last(1).values()[0].correct;
if(last_trial_correct){
return "
Correct!
";
} else {
return "
Wrong.
"
}
}
}
timeline.push(trial, feedback);


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Compiling 'pg' on MS Windows¶ ↑
In order to build this extension on MS Windows you will need a couple things.
First, a compiler. For the one click installer this means you should use the DevKit or the compiler that comes with cygwin if you're building on that platform.
If you've built Ruby yourself, you should use the same compiler to build this library that you used to build Ruby.
Second, PostgreSQL. Be sure you installed it with the development header files if you installed it using the standard PostgreSQL installer for Windows. If you didn't, you can run the installer again, select “modify”, and then select the 'development headers' option to install them.
I recommend making sure that 'pg_config.exe' is in your PATH. The PostgreSQL installer for Windows does not necessarily update your PATH when it installs itself, so you may need to do this manually. This isn't strictly necessary, however.
In order to build ruby-pg, just run 'rake'. If the pg_config.exe executable is not in your PATH, you'll need to explicitly point ruby-pg to where your PostgreSQL headers and libraries are with something like this:
rake --with-pg-dir=c:/progra~1/postgr~1/8.3
Adjust your path accordingly. BE SURE TO USE THE SHORT PATH NAMES! If you try to use a path with spaces in it, the nmake.exe program will choke.
Building binary 'pg' gems for MS Windows¶ ↑
Binary gems for windows can be built on Linux, OS-X and even on Windows with the help of docker. This is how regular windows gems are built for rubygems.org .
To do this, install boot2docker [on Windows](github.com/boot2docker/windows-installer/releases) or [on OS X](github.com/boot2docker/osx-installer/releases) and make sure it is started. A native Docker installation is best on Linux.
Then run:
rake gem:windows
This will download a docker image suited for building windows gems, and it will download and build OpenSSL and PostgreSQL. Finally the gem is built containing binaries for all supported ruby versions.
Reporting Problems¶ ↑
If you have any problems you can submit them via [the project's issue-tracker]. And submit questions, problems, or solutions, so that it can be improved.


Sample Ques..
First Mention :
Second Mention :
Third Mention :
Fourth Mention :
Fifth Mention :
Sixth Mention :
Seventh Mention :
Eighth Mention :
Ninth Mention :
Tenth Mention :


{{ "Thank you! Before you confirm receipt" | trans }}
{{ "Thank you for your presence, welcome to buy our products again!" | trans }}


'Rush Hour' (1998)
A movie review by Walter Frith
Member of the 'Internet Movie Critics Association' http://www.geocities.com/Hollywood/Studio/5713/index.html
and
Member of the 'Online Film Critics Society' http://ofcs.org/ofcs/
When you ask someone why they liked 'Rush Hour', the standard answer will probably be something like: "Lots of action!" "Lots of comedy!" "Great match-up of stars like Jackie Chan and Chris Tucker!" Unfortunately, the film has everything we've seen before and the picture looks for a new twist and while it comes up somewhat successful, it's predictable formula doesn't quite pull it off. 'Rush Hour' is for the movie goer who sees about five movies a year and a movie critic, whether amateur or professional, always looks for that little extra edge and it isn't found here. The film is entertaining on the surface but eventually you'll be looking at your watch after about the first 45 minutes.
Since Jackie Chan assaulted our senses with his North American breakthrough film 'Rumble in the Bronx' in 1996, he has been on a roll, even though film distributors have released some of his other films since then that have actually been released in his native land years before and the films, when released here in North America, were actually six or seven years old. Nobody does present day martial arts better than Jackie Chan and I have a lot of respect for him and his ability.
Chris Tucker annoyed the heck out of me in 1997's 'The Fifth Element' with that high pitched voice of his used in robotic fashion as a talk show host 250 years in the future. Tucker is very funny and has a lot of potential and I see a great future in the movies for him but a new angle must be found for his success to continue. 'Stakeout', '48 hrs.' etc. etc. Films where the cops get together with their colleagues or other helpful people in order to catch the bad guys. Let's do it again!
 The Chinese consulate to Los Angeles has his little daughter kidnapped and he calls upon a good friend of his, a Hong Kong police office played in classic fashion by Jackie Chan. The FBI want Chan kept out of the picture and use Tucker to keep Chan occupied so he won't get in the way of their domestic law enforcement. That's it. That's all. That's the whole story, folks!
The film moves well without becoming repetitive in its humour but it can't escape its formula origins and because of that it fails. Director Brett Ratner makes the classic formula movie mistake by allowing his actors to improvise too much instead of following a strict pattern style of direction. The screenplay by Jim Jim Kouf and Ross Lamanna has some funny moments but it isn't a hard screenplay to write, let alone execute.
Am I asking you to avoid 'Rush Hour'. No. Many of you will find it entertaining but if your taste is a little high brow for 8 dollars then, yes, avoid it at all costs. It's not a bad secondary feature at the drive-in and will become the perfect Saturday night video movie in a few months. It's just that kind of flick.
OUT OF 5 > * * *
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The size of a Digest Access challenge must be less than 2048 bytes. The following example shows a challenge assigned to the character string szChallenge.
C++
szChallenge = "realm=\"Microsoft_Example_Forest\",";
algorithm = "MD5-sess\", qop=\"auth\", nonce=\"0123456789abcdef\"";
Note The challenge string is enclosed in double quotes and contains embedded double quotes. Embedded double quotes must be preceded (escaped) with a backslash (\).
A Digest challenge can contain the following directives.
Directive Description
realm An implementation-defined hint to the client about which credentials are required. The client should display this information to the user if it is prompting for credentials.
algorithm Microsoft Digest supports MD5 and MD5-Sess. For optimal performance, use MD5-Sess.
qop This directive can be set to auth, auth-int, or auth-conf. For more information, see Quality of Protection and Ciphers.
nonce A unique encoded value generated by the server for each challenge. This value must not be altered by the client.
opaque Contains a reference for the security context that is being established. For more information, see Maintaining the Security Context Between Connections.
cipher(SASL only) The list of ciphers that the server supports. This element can be present in a Digest SASL challenge only if the qop directive specifies auth-conf. For more information, see Quality of Protection and Ciphers.
charset This directive can be set to utf-8 if the server can process UTF-8–encoded user names and realms. If the client understands the charset directive, it can respond by using UTF-8–encoded values.


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