Progressive Rock Top Albums / all subgenres - all record types - 1972 - all countries
Based on members ratings & PA algorithm
Here is some details about how we calculate the average rating of an album and the rank of an album.
-
Average rating: The classic calculation of the average but more weight is affected to the rating of progarchives.com collaborators and to rating with reviews.
- Rating only: Weight = 1
- Review by members : Weight = 10
- Review by PA Collaborators : Weight = 20
- Rank of an album: We use a calculation that compare an album average rating and number of ratings over all others albums in the query using this theory (http://en.wikipedia.org/wiki/Weighted_average) to create a variable every query "QWR" (AKA: Query Weighted Rating) use for ordering.
- By default, only albums with the average ratings above the average ratings of the requested query are displayed in theses lists, you can control this value in the parameters
| Rank | Cover | Ratings | Title Artist |
Genre (Record Type) |
BUY |
| 1 |
4.65 | 3806 ratings
QWR = 4.6221
|
Close To The Edge Yes |
Symphonic Prog Studio, 1972 |
Shop | |
| 2 |
4.63 | 2797 ratings
QWR = 4.5869
|
Thick As A Brick Jethro Tull |
Prog Folk Studio, 1972 |
Shop | |
| 3 |
4.60 | 3063 ratings
QWR = 4.5670
|
Foxtrot Genesis |
Symphonic Prog Studio, 1972 |
Shop | |
| 4 |
4.40 | 1376 ratings
QWR = 4.3401
|
Per Un Amico Premiata Forneria Marconi (PFM) |
Rock Progressivo Italiano Studio, 1972 |
Shop | |
| 5 |
4.37 | 1090 ratings
QWR = 4.2900
|
Storia Di Un Minuto Premiata Forneria Marconi (PFM) |
Rock Progressivo Italiano Studio, 1972 |
Shop | |
| 6 |
4.38 | 927 ratings
QWR = 4.2899
|
Darwin! Banco Del Mutuo Soccorso |
Rock Progressivo Italiano Studio, 1972 |
Shop | |
| 7 |
4.28 | 1584 ratings
QWR = 4.2358
|
Octopus Gentle Giant |
Eclectic Prog Studio, 1972 |
Shop | |
| 8 |
4.31 | 779 ratings
QWR = 4.2185
|
The Grand Wazoo Frank Zappa |
RIO/Avant-Prog Studio, 1972 |
Shop | |
| 9 |
4.29 | 713 ratings
QWR = 4.1910
|
Banco Del Mutuo Soccorso Banco Del Mutuo Soccorso |
Rock Progressivo Italiano Studio, 1972 |
Shop | |
| 10 |
4.26 | 565 ratings
QWR = 4.1439
|
Space Shanty Khan |
Canterbury Scene Studio, 1972 |
Shop | |
| 11 |
4.24 | 580 ratings
QWR = 4.1270
|
Caravanserai Santana |
Jazz Rock/Fusion Studio, 1972 |
Shop | |
| 12 |
4.21 | 576 ratings
QWR = 4.1047
|
Uomo Di Pezza Le Orme |
Rock Progressivo Italiano Studio, 1972 |
Shop | |
| 13 |
4.21 | 477 ratings
QWR = 4.0825
|
Ys Il Balletto di Bronzo |
Rock Progressivo Italiano Studio, 1972 |
Shop | |
| 14 |
4.25 | 329 ratings
QWR = 4.0660
|
Palepoli Osanna |
Rock Progressivo Italiano Studio, 1972 |
Shop | |
| 15 |
4.11 | 1032 ratings
QWR = 4.0569
|
Three Friends Gentle Giant |
Eclectic Prog Studio, 1972 |
Shop | |
| 16 |
4.10 | 1359 ratings
QWR = 4.0554
|
Trilogy Emerson Lake & Palmer |
Symphonic Prog Studio, 1972 |
Shop | |
| 17 |
4.23 | 259 ratings
QWR = 4.0155
|
Crossings Herbie Hancock |
Jazz Rock/Fusion Studio, 1972 |
Shop | |
| 18 |
4.21 | 244 ratings
QWR = 3.9944
|
Hosianna Mantra Popol Vuh |
Krautrock Studio, 1972 |
Shop | |
| 19 |
4.06 | 639 ratings
QWR = 3.9818
|
Demons And Wizards Uriah Heep |
Heavy Prog Studio, 1972 |
Shop | |
| 20 |
4.15 | 272 ratings
QWR = 3.9695
|
Grave New World Strawbs |
Prog Folk Studio, 1972 |
Shop | |
| 21 |
4.06 | 476 ratings
QWR = 3.9572
|
A Tab In The Ocean Nektar |
Psychedelic/Space Rock Studio, 1972 |
Shop | |
| 22 |
4.10 | 267 ratings
QWR = 3.9295
|
Quella Vecchia Locanda Quella Vecchia Locanda |
Rock Progressivo Italiano Studio, 1972 |
Shop | |
| 23 |
4.06 | 292 ratings
QWR = 3.9110
|
Neu! Neu! |
Krautrock Studio, 1972 |
Shop | |
| 24 |
4.05 | 295 ratings
QWR = 3.9042
|
Lady Lake Gnidrolog |
Eclectic Prog Studio, 1972 |
Shop | |
| 25 |
4.05 | 245 ratings
QWR = 3.8828
|
Roxy Music Roxy Music |
Crossover Prog Studio, 1972 |
Shop | |
| 26 |
4.16 | 144 ratings
QWR = 3.8756
|
Reale Accademia Di Musica Reale Accademia Di Musica |
Rock Progressivo Italiano Studio, 1972 |
Shop | |
| 27 |
4.20 | 114 ratings
QWR = 3.8575
|
Haikara Haikara |
Eclectic Prog Studio, 1972 |
Shop | |
| 28 |
3.99 | 230 ratings
QWR = 3.8350
|
Malesch Agitation Free |
Krautrock Studio, 1972 |
Shop | |
| 29 |
4.01 | 203 ratings
QWR = 3.8333
|
Chick Corea: Return To Forever Return To Forever |
Jazz Rock/Fusion Studio, 1972 |
Shop | |
| 30 |
3.91 | 413 ratings
QWR = 3.8269
|
Waka / Jawaka Frank Zappa |
RIO/Avant-Prog Studio, 1972 |
Shop | |
| 31 |
4.09 | 130 ratings
QWR = 3.8226
|
Hölderlins Traum Hoelderlin |
Prog Folk Studio, 1972 |
Shop | |
| 32 |
3.90 | 364 ratings
QWR = 3.8067
|
666 Aphrodite's Child |
Symphonic Prog Studio, 1972 |
Shop | |
| 33 |
3.94 | 245 ratings
QWR = 3.8065
|
Wolf City Amon Düül II |
Krautrock Studio, 1972 |
Shop | |
| 34 |
3.90 | 372 ratings
QWR = 3.8056
|
Ege Bamyasi Can |
Krautrock Studio, 1972 |
Shop | |
| 35 |
3.94 | 203 ratings
QWR = 3.7861
|
Captain Beyond Captain Beyond |
Heavy Prog Studio, 1972 |
Shop | |
| 36 |
4.06 | 111 ratings
QWR = 3.7832
|
Känguru Guru Guru |
Krautrock Studio, 1972 |
Shop | |
| 37 |
3.83 | 495 ratings
QWR = 3.7707
|
The Magician's Birthday Uriah Heep |
Heavy Prog Studio, 1972 |
Shop | |
| 38 |
3.93 | 152 ratings
QWR = 3.7474
|
In Spite Of Harry's Toenail Gnidrolog |
Eclectic Prog Studio, 1972 |
Shop | |
| 39 |
3.90 | 151 ratings
QWR = 3.7314
|
Little Red Record Matching Mole |
Canterbury Scene Studio, 1972 |
Shop | |
| 40 |
3.93 | 127 ratings
QWR = 3.7265
|
Passio Secundum Mattheum Latte e Miele |
Rock Progressivo Italiano Studio, 1972 |
Shop | |
| 41 |
3.84 | 190 ratings
QWR = 3.7107
|
Phantasmagoria Curved Air |
Eclectic Prog Studio, 1972 |
Shop | |
| 42 |
3.86 | 137 ratings
QWR = 3.6945
|
Grobschnitt Grobschnitt |
Symphonic Prog Studio, 1972 |
Shop | |
| 43 |
3.74 | 456 ratings
QWR = 3.6894
|
Waterloo Lily Caravan |
Canterbury Scene Studio, 1972 |
Shop | |
| 44 |
3.82 | 129 ratings
QWR = 3.6679
|
Hoodoo Man Birth Control |
Heavy Prog Studio, 1972 |
Shop | |
| 45 |
3.82 | 115 ratings
QWR = 3.6603
|
UT New Trolls |
Rock Progressivo Italiano Studio, 1972 |
Shop | |
| 46 |
3.70 | 364 ratings
QWR = 3.6543
|
Prologue Renaissance |
Symphonic Prog Studio, 1972 |
Shop | |
| 47 |
3.82 | 102 ratings
QWR = 3.6489
|
Caricatures Ange |
Symphonic Prog Studio, 1972 |
Shop | |
| 48 |
3.78 | 112 ratings
QWR = 3.6379
|
Psychonaut Brainticket |
Krautrock Studio, 1972 |
Shop | |
| 49 |
3.69 | 281 ratings
QWR = 3.6334
|
Doremi Fasol Latido Hawkwind |
Psychedelic/Space Rock Studio, 1972 |
Shop | |
| 50 |
3.76 | 123 ratings
QWR = 3.6298
|
I Sing The Body Electric Weather Report |
Jazz Rock/Fusion Studio, 1972 |
Shop | |
| 51 |
3.67 | 306 ratings
QWR = 3.6237
|
Zeit 'Largo In 4 Movements' Tangerine Dream |
Progressive Electronic Studio, 1972 |
Shop | |
| 52 |
3.68 | 240 ratings
QWR = 3.6173
|
Seventh Sojourn The Moody Blues |
Crossover Prog Studio, 1972 |
Shop | |
| 53 |
3.70 | 142 ratings
QWR = 3.6071
|
Schwingungen Ash Ra Tempel |
Krautrock Studio, 1972 |
Shop | |
| 54 |
3.72 | 111 ratings
QWR = 3.6020
|
Lord Of The Rings Bo Hansson |
Symphonic Prog Studio, 1972 |
Shop | |
| 55 |
3.69 | 129 ratings
QWR = 3.5933
|
Together Jane |
Heavy Prog Studio, 1972 |
Shop | |
| 56 |
3.69 | 122 ratings
QWR = 3.5923
|
First Base Babe Ruth |
Heavy Prog Studio, 1972 |
Shop | |
| 57 |
3.67 | 105 ratings
QWR = 3.5748
|
Made In England Atomic Rooster |
Heavy Prog Studio, 1972 |
Shop | |
| 58 |
3.61 | 192 ratings
QWR = 3.5619
|
Mediterranean Tales Triumvirat |
Symphonic Prog Studio, 1972 |
Shop | |
| 59 |
3.56 | 187 ratings
QWR = 3.5297
|
Electric Light Orchestra II Electric Light Orchestra |
Crossover Prog Studio, 1972 |
Shop | |
| 60 |
3.56 | 152 ratings
QWR = 3.5236
|
Carnival In Babylon Amon Düül II |
Krautrock Studio, 1972 |
Shop | |
| 61 |
3.53 | 123 ratings
QWR = 3.5065
|
So Far Faust |
Krautrock Studio, 1972 |
Shop | |
| 62 |
3.52 | 139 ratings
QWR = 3.5004
|
Can't Buy a Thrill Steely Dan |
Jazz Rock/Fusion Studio, 1972 |
Shop | |
| 63 |
3.49 | 129 ratings
QWR = 3.4840
|
Irrlicht Klaus Schulze |
Progressive Electronic Studio, 1972 |
Shop |


We are where we eat
We are shaped by what we eat. But we are also shaped by where we eat. Are chefs ready to trade high-quality, fresh ingredients for cheaper stale ones? Are there places and times where food conservation has a subjective meaning? Are large-scale franchises such as McDonald’s and Starbucks under the same level of scrutiny as normal restaurants despite the economic interests at play?
We will do a deep dive into Chicago’s food inspection scene and everything happening behind the curtain.
To achieve this, we will pore over Chicago's Food Inspections dataset, and answer five big questions: what is the impact, on a food-related business, of... its business type? Its neighborhood? Its size or scale? Of the time of the year? And of its social media reviews?


Simulated life insurance policies portfolio made up of 2,500 policies.
Note that the dataset is not suited to be passed in the function optimize_exposure()
. This because
it has n number of rows for each policy, where n is the number of years the contract is in force.
This dataset needs to be duplicated using the function duplicate_portfolio()
before computing the
optimal exposure with optimize_exposure()
.
raw_lifepolicies
A data frame with variables:
policy number identifier, unique for each policy.
signing date of the contract.
The period in months, starting from signing, for which the policyholder is not covered.
ending date of the contract.
date of birth of the policyolder.
policyholder's gender.
underwriting year.
current year of evaluation.
date when claims occurred, if any, otherwise 2099-12-31.
1 if the year of Claim_date
is equal to CY, 0 otherwise.
date when policy lapsed, if so, otherwise 2099-12-31.
1 if the year of Lapse_date
is equal to CY, 0 otherwise.
#'
#> # A tibble: 6 x 12 #> Policy_id Inception_date Waiting_period Term_date Birth_date Gender UY #> <dbl> <date> <int> <date> <date> <chr> <dbl> #> 1 1019640 2012-11-01 2 2016-11-01 1945-03-10 F 2012 #> 2 1019640 2012-11-01 2 2016-11-01 1945-03-10 F 2012 #> 3 1019640 2012-11-01 2 2016-11-01 1945-03-10 F 2012 #> 4 1019640 2012-11-01 2 2016-11-01 1945-03-10 F 2012 #> 5 1019640 2012-11-01 2 2016-11-01 1945-03-10 F 2012 #> 6 1021830 2012-07-01 2 2023-07-01 1936-11-14 F 2012 #> # ... with 5 more variables: CY <int>, Claim_date <date>, Claim <dbl>, #> # Lapse_date <date>, Lapse <dbl>


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| Developer Spotlight |
Daishi Kato is a researcher in the Computer Science department at Stanford University. He is also the Project Owner of Jnushare and GISP. He dedicates 10-20% of his time to Project JXTA. He's working on providing GISP in the JXTA service layer so that a JXTA application can easily achieve information (metadata) sharing in a peer-to-peer manner. GISP is based on distributed indexing which is potentially scalable. Daishi has also provided Jnushare, currently a file/message sharing application. Daishi hopes that JXTA will become a common platform and be present in every computer. His vision is that there would be many peer-to-peer applications on JXTA connecting each other all over the Internet. Daishi says that one could find lots of information through JXTA network and hopes that in the future, with GISP, it would be possible to search for any information without search engines. You can reach Daishi on the Project JXTA discuss mailing list or at<EMAIL_ADDRESS>|


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Linkin Park- Lost In The Echo.mp3
Maroon 5- Daylight.mp3
michael jackson-black or white.mp3
michael jackson-the way you make.mp3
Ne Yo-Miss Independent.mp3
One Republic- Burning Bridges.mp3
Palat - Tera Hero Idhar Hai.mp3
Pussycat dolls - Don't Cha.mp3
Sean kingston- beautiful girl.mp3
Step up 2- the street soundtrack.mp3
Taylor swift- Ours.mp3


Overview
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targetPopulation
- Variable in exception net.parallaxed.bluejam.exceptions.
BreedException
Which population the exception occurred in
tempo(int)
- Method in class net.parallaxed.bluejam.
JamParamters
Sets the tempo of this Jam
Terminal
- Interface in
net.parallaxed.bluejam
All terminals must have unique identifiers to satisfy uniqueness in a TerminalSet.
TerminalSet
- Class in
net.parallaxed.bluejam
Wraps an ArrayList to provide set-like functionality (one unique instance per set).
TerminalSet()
- Constructor for class net.parallaxed.bluejam.
TerminalSet
testAdd1()
- Method in class net.parallaxed.bluejam.tests.
TreeTest
Tests the add to one level deep
testBreeder()
- Method in class net.parallaxed.bluejam.tests.
SelectionTest
testBuildHeuristic()
- Method in class net.parallaxed.bluejam.tests.
TreeTest
testContexDown()
- Method in class net.parallaxed.bluejam.tests.
ContextTest
testContexLimit()
- Method in class net.parallaxed.bluejam.tests.
ContextTest
testConteXtreme()
- Method in class net.parallaxed.bluejam.tests.
ContextTest
This method has a gay name.
testContexUp()
- Method in class net.parallaxed.bluejam.tests.
ContextTest
testContour()
- Method in class net.parallaxed.bluejam.tests.
FitnessTest
testContour5()
- Method in class net.parallaxed.bluejam.tests.
FitnessTestHeuristic
testCrossoverRefs()
- Method in class net.parallaxed.bluejam.tests.
TreeReferenceTest
testDistanceBad()
- Method in class net.parallaxed.bluejam.tests.
FitnessTest
Test against an Individual with a heuristic identical to the sequence.
testDistanceOK()
- Method in class net.parallaxed.bluejam.tests.
FitnessTest
testEvaluateRelative()
- Method in class net.parallaxed.bluejam.tests.
LeafTest
Tests that relative notes are being evaluated correctly.
testEvaluateRelativeChange()
- Method in class net.parallaxed.bluejam.tests.
LeafTest
testEvolve()
- Method in class net.parallaxed.bluejam.tests.
EvolutionTest
testHeuristic()
- Method in class net.parallaxed.bluejam.tests.
HeuristicTest
testInitializeGrowInd()
- Method in class net.parallaxed.bluejam.tests.
InitializeTest
Test that initialization of one individual does not leave any gaps.
testInitializeHeuristic()
- Method in class net.parallaxed.bluejam.tests.
InitializeTest
testInitializePopulation()
- Method in class net.parallaxed.bluejam.tests.
InitializeTest
Simply tests that the population is filled, not individuals.
testInitializeRandom()
- Method in class net.parallaxed.bluejam.tests.
InitializeTest
testInterval5()
- Method in class net.parallaxed.bluejam.tests.
FitnessTestHeuristic
testIntervalBad()
- Method in class net.parallaxed.bluejam.tests.
FitnessTest
testInvalidAdd()
- Method in class net.parallaxed.bluejam.tests.
TreeTest
testLeafAdd()
- Method in class net.parallaxed.bluejam.tests.
LeafTest
testListener()
- Method in class net.parallaxed.bluejam.tests.
ListenerTest
testLoadGenotype()
- Method in class net.parallaxed.bluejam.tests.
IndividualTest
Test's an individual's ability to instantiate the configured genotype through reflection only.
testModelParser()
- Method in class net.parallaxed.bluejam.tests.
ModelTest
testMutationRefs()
- Method in class net.parallaxed.bluejam.tests.
TreeReferenceTest
testNullRefs()
- Method in class net.parallaxed.bluejam.tests.
TreeReferenceTest
testNumberToNote()
- Method in class net.parallaxed.bluejam.tests.
MIDITest
testRemoveLeaf()
- Method in class net.parallaxed.bluejam.tests.
LeafTest
testSelectTournament()
- Method in class net.parallaxed.bluejam.tests.
SelectionTest
testSwapNotes()
- Method in class net.parallaxed.bluejam.tests.
LeafTest
testValidateNotes1()
- Method in class net.parallaxed.bluejam.tests.
TreeTest
testValidateNotes2()
- Method in class net.parallaxed.bluejam.tests.
TreeTest
timeSignature(String)
- Method in class net.parallaxed.bluejam.
SequenceParameters
Time signature is parsed to set the private variables
timeSignature()
- Method in class net.parallaxed.bluejam.
SequenceParameters
togglePause()
- Method in class net.parallaxed.bluejam.
Evolve
Pauses the evolution from outside this thread.
toggleRest(boolean)
- Method in class net.parallaxed.bluejam.
Note
Sets this note to be a rest given the passed boolean.
toggleRest()
- Method in class net.parallaxed.bluejam.
Note
Toggles rest on/off.
toString()
- Method in interface net.parallaxed.bluejam.
Heuristic
This defines a name for the heuristic, such that a particular instance can be pulled from a HeuristicCollection by name.
toString()
- Method in enum net.parallaxed.bluejam.
JamParamters.Config
The string value of each enum.
toString()
- Method in class net.parallaxed.bluejam.
Note
Returns true if this note is a rest
TreeBreeder
- Class in
net.parallaxed.bluejam.evolution
TreeBreeder is the default implementation of the Breeder interface for recombining and mutating NoteTrees, given an initial skeletal population.
TreeBreeder()
- Constructor for class net.parallaxed.bluejam.evolution.
TreeBreeder
Instantiates a TreeBuilder trivially.
TreeBreeder(int, double)
- Constructor for class net.parallaxed.bluejam.evolution.
TreeBreeder
Instantiates a TreeBreeder with the passed parameters.
TreeParser
- Class in
net.parallaxed.bluejam
This class reads in information from passed tree files, which normally represent a serialized layout of a NoteSequence.
TreeParser(String)
- Constructor for class net.parallaxed.bluejam.
TreeParser
Creates a tree parser given a relative path.
TreeParser(File)
- Constructor for class net.parallaxed.bluejam.
TreeParser
Creates a TreeParser given a reference to a java.io.File object.
TreeReferenceTest
- Class in
net.parallaxed.bluejam.tests
TreeReferenceTest()
- Constructor for class net.parallaxed.bluejam.tests.
TreeReferenceTest
TreeTest
- Class in
net.parallaxed.bluejam.tests
TreeTest()
- Constructor for class net.parallaxed.bluejam.tests.
TreeTest
Overview
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Adds useful methods to the JavaScript String type.
To use this optional module, its repository needs to be added to the application, for example by calling app.addRepository('modules/core/String.js')
To use this optional module, its repository needs to be added to the application, for example by calling app.addRepository('modules/core/String.js')
Methods
checks if a date format pattern is correct
returns
| Boolean true if the pattern is correct |
parse a timestamp into a date object. This is used when users
want to set createtime explicitly when creating/editing stories.
parameters
| String | date format to be applied | |
| Object | Java TimeZone Object (optional) |
returns
| Object contains the resulting date |
function checks if the string passed contains any characters that
are forbidden in URLs and tries to create a java.net.URL from it
FIXME: probably deprecated -> helma.Url
returns
| Boolean |
see
function checks if the string passed contains any characters
that are forbidden in image- or filenames
returns
| Boolean |
function cleans the string passed as argument from any characters
that are forbidden or shouldn't be used in filenames
returns
| Boolean |
function checks a string for a valid color value in hexadecimal format.
it may also contain # as first character
returns
| Boolean false, if string length (without #) > 6 or < 6 or contains any character which is not a valid hex value |
converts a string into a hexadecimal color
representation (e.g. "ffcc33"). also knows how to
convert a color string like "rgb (255, 204, 51)".
returns
| String the resulting hex color (w/o "#") |
function returns true if the string contains
only a-z and 0-9 (case insensitive!)
returns
| Boolean true in case string is alpha, false otherwise |
function cleans a string by throwing away all
non-alphanumeric characters
returns
| cleaned string |
function returns true if the string contains
only characters a-z
returns
| Boolean true in case string is alpha, false otherwise |
function returns true if the string contains
only 0-9
returns
| Boolean true in case string is numeric, false otherwise |
transforms the first n characters of a string to uppercase
parameters
| Number | amount of characters to transform |
returns
| String the resulting string |
transforms the first n characters of each
word in a string to uppercase
returns
| String the resulting string |
translates all characters of a string into HTML entities
returns
| String translated result |
breaks up a string into two parts called
head and tail at the given position
don't apply this to HTML, i.e. use stripTags() in advance
parameters
| Number | number of charactrers or of segments separated by the delimiter | |
| String | pre-/suffix to be pre-/appended to shortened string | |
| String | delimiter |
returns
| Object containing head and tail properties |
get the head of a string
parameters
| limit | ||
| clipping | ||
| delimiter |
see
get the tail of a string
parameters
| limit | ||
| clipping | ||
| delimiter |
see
function inserts a string every number of characters
parameters
| Int | number of characters after which insertion should take place | |
| String | string to be inserted | |
| Boolean | definitely insert at each interval position |
returns
| String resulting string |
replace all linebreaks and optionally all w/br tags
parameters
| Boolean | flag indicating if html tags should be replaced | |
| String | replacement for the linebreaks / html tags |
returns
| String the unwrapped string |
function repeats a string passed as argument
parameters
| Int | amount of repetitions |
returns
| String resulting string |
function returns true if the string starts with
the string passed as argument
parameters
| String | string pattern to search for |
returns
| Boolean true in case it matches the beginning of the string, false otherwise |
function returns true if the string ends with
the string passed as argument
parameters
| String | string pattern to search for |
returns
| Boolean true in case it matches the end of the string, false otherwise |
fills a string with another string up to a desired length
parameters
| String | the filling string | |
| Number | the desired length of the resulting string | |
| Number | the direction which the string will be padded in: -1: left 0: both (balance) 1: right (you can use the constants String.LEFT, String.BALANCE and String.RIGHT here as well.) |
returns
| String the resulting string |
function returns true if a string contains the string
passed as argument
parameters
| String | string to search for | |
| Int | Position to start search | |
| Boolean |
function compares a string with the one passed as argument
using diff
parameters
| String | String to compare against String object value | |
| String | Optional regular expression string to use for splitting. If not defined, newlines will be used. |
returns
| Object Array containing one JS object for each line with the following properties: .num Line number .value String line if unchanged .deleted Obj Array containing deleted lines .inserted Obj Array containing added lines |
remove leading and trailing whitespace
returns true if the string looks like an e-mail
returns the string encoded using the base64 algorithm
returns the decoded string using the base64 algorithm
factory to create functions for sorting objects in an array
parameters
| String | name of the field each object is compared with | |
| Number | order (ascending or descending) |
returns
| Function ready for use in Array.prototype.sort |
create a string from a bunch of substrings
parameters
| String | one or more strings as arguments |
returns
| String the resulting string |
creates a random string (numbers and chars)
parameters
| len | length of key | |
| mode | determines which letters to use. null or 0 = all letters; 1 = skip 0, 1, l and o which can easily be mixed with numbers; 2 = use numbers only |
returns
| random string |
append one string onto another and add some "glue"
if none of the strings is empty or null.
parameters
| String | the first string | |
| String | the string to be appended onto the first one | |
| String | the "glue" to be inserted between both strings |
returns
| String the resulting string |


See the winners of our anual review
Best Spearguns of 2020
Best Gun of 2020
The Riffe Euro is the gold standard of spearguns and for good reason! With its laminated teak construction, it is durable and neutrally buoyant. It is a simple gun, but it is perfect. It is powerful and accurate while still being silent. With a company like Riffe it is hard to go wrong and this is their flagship model.
Best Budget Gun
If you are looking for a budget gun, look no further. The Mako Predator is going to be your best friend. It shoots straight and is built like a tank, so it is pretty hard to go wrong with this gun. Although you will not be able to find these guns in stores, their customer service is one of the best in the game. Because they have no middleman, they are allowed to offer their gear at reduced prices. It is definitely an entry level gun, but this will stay in your arsenal for a long time.
Best Best Mid-Range Gun
Rob Allen is a household name in the spearfishing scene. It has earned its notoriety by consistently making quality products with the spearo in mind. The Tuna line of rail guns is you next step up from entry-level aluminum guns. They manufacture their barrels out of Vecta aluminum, which is a very rigid alloy. This stiffness results in maximum transfer of energy to the shaft and allows for pin-point long-range shots. It comes with a shaft that stands up to maximum abuse and the flopper is extremely reliable. There is nothing worse than tagging a fish, only to realize the flopper did not open and the fish got away. The handle design is often a talking point of this gun. It offers one of the most comfortable grips.
Best Intermediate Gun
This gun is an absolute beauty! It is some of the highest quality you will find in a beginner gun. It is made out of solid African Mahogany, which makes it virtually indestructible. It comes in a wide variety of sizes, so you can get a hole hunter or a blue water gun with the same design. I would say the greatest part of this gun is its M8 trigger mechanism. It is very reliable and tough. This, combine with a super comfortable handle makes this gun an amazing option for this price point.
Best Pneumatic Gun
The Mares Sten is a nifty little gun. It is the shortest available gun on the market making the ultimate hole hunting gun. You can even use this as a second gun strapped to your belt. It is a very solid pneumatic speargun and you can get one for a pretty low price.


Models¶
-
class
app.models.
Door
(*args, **kwargs)¶ Door model.
This model contains the specifications for a door that leads into a room. Main goal of this model is to give controls to lock/unlock the door itself.
-
class
app.models.
Home
(*args, **kwargs)¶ Home model. Includes all devices that can be controlled.
This model contains the relationships between the different types of devices that can be controlled in the app. Each house is instantiated uniquely. A house can have an owner.
-
save
(**kwargs)¶ Custom save method to create random secret key
-
-
class
app.models.
Light
(*args, **kwargs)¶ Light model.
This model contains the specifications for the type of light the user would like to add. Defaults to binary mode. Many lights per room.
-
class
app.models.
Refrigerator
(*args, **kwargs)¶ Refrigerator model.
This model exposes the refrigerator to the home control. It is designed to read and write fridge/freezer temperature.
-
class
app.models.
Room
(*args, **kwargs)¶ Room model.
Abstraction of a group of devices grouped into a single class. User can specify a name for a room and define actions based on room type. Many rooms per home.
-
class
app.models.
Thermostat
(*args, **kwargs)¶ Nest-like thermostat model.
This model is designed to act like a Nest thermostat in the home. Its main purpose is to report and set thermostat temperature. One thermostat per home. User specifies if thermostat controls AC and/or heater.


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java.lang.Object codeblocks.BlockLinkChecker
public class BlockLinkChecker
BlockLinkChecker
determines if two Block
objects can connect. In particular,
BlockLinkChecker
will report which sockets of the two Block
objects can connect.
Interested Block
objects may make a static call to canLink() to determine if it can link to another
Block
object.
BlockLinkChecker
uses a list of LinkRule
s to check the Connector
s of each
Block
. Rules may be added, inserted, and removed from the checker.
There is only one instance of the BlockLinkChecker
.
| Constructor Summary | |
|---|---|
BlockLinkChecker()
|
| Method Summary | |
|---|---|
static void |
addRule(LinkRule rule)
Adds a rule to the end of this checker's list of rules. |
static BlockLink |
canLink(Block block1,
Block block2,
BlockConnector con1,
BlockConnector con2)
Returns a BlockLink instance if the two specified blocks can connect at the specified block connectors at each block; null if no link is possible. |
static BlockLink |
getLink(RenderableBlock rblock1,
java.lang.Iterable<RenderableBlock> otherBlocks)
Checks to see if a RenderableBlock s can connect to other RenderableBlock s. |
static BlockConnector |
getPlugEquivalent(Block b)
|
static java.lang.Iterable<BlockConnector> |
getSocketEquivalents(Block b)
|
static BlockLink |
getWeakLink(RenderableBlock rblock1,
java.lang.Iterable<RenderableBlock> otherBlocks)
NOTE: ALWAYS prefer BlockLinkChecker.getLink over this method. |
static boolean |
hasPlugEquivalent(Block b)
|
static void |
insertRule(LinkRule rule,
int index)
Insert rule at the specified index in this checker's list of rules. |
static void |
printRules()
Prints to the console all the rules this LinkChecker currently supports. |
static void |
removeRule(LinkRule rule)
Removes the specified rule from the rule list |
static void |
reset()
Clears all the rules within this. |
| Methods inherited from class java.lang.Object |
|---|
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Constructor Detail |
|---|
public BlockLinkChecker()
| Method Detail |
|---|
public static void reset()
public static void addRule(LinkRule rule)
rule
- the desired LinkRule to be addedpublic static void insertRule(LinkRule rule, int index)
rule
- the desired rule to insertindex
- the index to insert the rule inpublic static void removeRule(LinkRule rule)
rule
- the desired LinkRule to removepublic static BlockLink canLink(Block block1, Block block2, BlockConnector con1, BlockConnector con2)
block1
- Block instance to compareblock2
- Block instance to comparecon1
- the BlockConnector at block1 to compare against con2con2
- the BlockConnector at block2 to compare against con1public static BlockLink getLink(RenderableBlock rblock1, java.lang.Iterable<RenderableBlock> otherBlocks)
RenderableBlock
s can connect to other RenderableBlock
s.
This would mean that they have BlockConnector
s that satisfy at least one of the LinkRule
s,
and that these sockets are in close proximity.
rblock1
- one of the blocks to checkotherBlocks
- the other blocks to check against
BlockLink
object that gives the two closest matching BlockConnector
s in these blocks,
or null if no such matching exists.public static BlockLink getWeakLink(RenderableBlock rblock1, java.lang.Iterable<RenderableBlock> otherBlocks)
RenderableBlock
s can connect
to other RenderableBlock
s, implying that rblock1
has at least one BlockConnector
s that satisfies at
least one of the LinkRule
s.
Does not require close proximity.
rblock1
- one of the blocks to checkotherBlocks
- the other blocks to check against
BlockLink
object that gives the two closest matching BlockConnector
s in these blocks,
or null if no such matching exists.public static boolean hasPlugEquivalent(Block b)
public static BlockConnector getPlugEquivalent(Block b)
public static java.lang.Iterable<BlockConnector> getSocketEquivalents(Block b)
public static void printRules()
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| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |


{% extends "base.html" %} {% block content %} Focal Point Photography Focal Point is Kent State's photography club. We are open to students from any major who are interested in making photos, editing photos, looking at photos or anything else related to photography! {% endblock %}
Focal Point is Kent State's photography club. We are open to students from any major who are interested in making photos, editing photos, looking at photos or anything else related to photography!


#include <featureset.h>
Inherits EngineOutputBase.
Definition at line 23 of file featureset.h.
Public Member Functions | |
| virtual FeatureSet * | clone () const |
| COREDATA_DECLARE_NAMED_OBJECT_ID (FEATURE_SET_CAM_B_ID, 22) | |
| COREDATA_DECLARE_NAMED_OBJECT_ID (FEATURE_SET_CAM_A_ID, 21) | |
| FeatureRectPtr | faceRect () |
| ConstFeatureRectPtr | faceRect () const |
| FeatureSet (const FeatureSet &rhs) | |
| FeatureSet (ObjectID object_id) | |
| FeatureRectPtr | leftEyeRect () |
| ConstFeatureRectPtr | leftEyeRect () const |
| FeaturePointPtr | leftPupilPos () |
| ConstFeaturePointPtr | leftPupilPos () const |
| FeatureRectPtr | mouthRect () |
| ConstFeatureRectPtr | mouthRect () const |
| virtual ObjectID | objectID () const |
| FeatureSet & | operator= (const FeatureSet &rhs) |
| FeaturePointPtr | pupilPosForEye (int eye_id) |
| ConstFeaturePointPtr | pupilPosForEye (int eye_id) const |
| FeatureRectPtr | rightEyeRect () |
| ConstFeatureRectPtr | rightEyeRect () const |
| FeaturePointPtr | rightPupilPos () |
| ConstFeaturePointPtr | rightPupilPos () const |
Protected Member Functions | |
| virtual void | appendEngineSpecificData (std::vector< uint8 > &) const |
| virtual void | doAddSubObject (const SerializablePtr &sub_object) |
| virtual uint32 | numEngineSpecificDataBytes () const |
| virtual void | printOwnData (std::ostream &) const |
| virtual void | printOwnHeader (std::ostream &) const |
| virtual void | readEngineSpecificData (const std::vector< uint8 > &, int &) |
| virtual void | readFromBuffer (const std::vector< uint8 > &, int &) |
Static Protected Member Functions | |
| static std::string | IDToName (ObjectID object_id) |
| FeatureSet | ( | ObjectID | object_id | ) | [explicit] |
| virtual void appendEngineSpecificData | ( | std::vector< uint8 > & | ) | const [protected, virtual] |
| virtual FeatureSet* clone | ( | ) | const [virtual] |
| COREDATA_DECLARE_NAMED_OBJECT_ID | ( | FEATURE_SET_CAM_B_ID | , | |
| 22 | ||||
| ) |
The ID that identifies the Set of features in Camera B.
| COREDATA_DECLARE_NAMED_OBJECT_ID | ( | FEATURE_SET_CAM_A_ID | , | |
| 21 | ||||
| ) |
The ID that identifies the Set of features in Camera A.
| virtual void doAddSubObject | ( | const SerializablePtr & | sub_object | ) | [protected, virtual] |
If sub_object is derived from FeatureOutputData then the name of the sub_object is updated with the name of this object.
| SerializableError | if the object id already exists or the object id is not valid for this object or sub_object is not derived from EngineOutputBase or FeatureOutputData. |
Reimplemented from SerializableComposite.
| ConstFeatureRectPtr faceRect | ( | ) | const |
Convenience method that returns the rectangle bounding the face.
| static std::string IDToName | ( | ObjectID | object_id | ) | [static, protected] |
| ConstFeatureRectPtr leftEyeRect | ( | ) | const |
Convenience method that returns the rectangle bounding the left eye.
| ConstFeaturePointPtr leftPupilPos | ( | ) | const |
Convenience method that returns the position of the left pupil.
| ConstFeatureRectPtr mouthRect | ( | ) | const |
Convenience method that returns the rectangle bounding the mouth.
| virtual uint32 numEngineSpecificDataBytes | ( | ) | const [protected, virtual] |
| virtual ObjectID objectID | ( | ) | const [virtual] |
| FeatureSet& operator= | ( | const FeatureSet & | rhs | ) |
object ids must match
| virtual void printOwnData | ( | std::ostream & | ) | const [protected, virtual] |
| virtual void printOwnHeader | ( | std::ostream & | ) | const [protected, virtual] |
| ConstFeaturePointPtr pupilPosForEye | ( | int | eye_id | ) | const |
| eye_id | either RIGHT_EYE or LEFT_EYE. |
| virtual void readEngineSpecificData | ( | const std::vector< uint8 > & | , | |
| int & | ||||
| ) | [protected, virtual] |
| virtual void readFromBuffer | ( | const std::vector< uint8 > & | , | |
| int & | ||||
| ) | [protected, virtual] |
Reimplemented from SerializableComposite.
| ConstFeatureRectPtr rightEyeRect | ( | ) | const |
Convenience method that returns the rectangle bounding the right eye.
| ConstFeaturePointPtr rightPupilPos | ( | ) | const |
Convenience method that returns the position of the right pupil.


The Players Club (R) ** 1/2
A mix of Showgirls, Striptease, and '70s Blaxploitation. Sounds like a surefire recipe for camp, but against all odds, Ice Cube's directorial debut The Players Club, if a bit uneven, works a lot better as a serious drama than its individual ingredients would make it appear to be.
The Players Club is the name of a seedy Southern strip bar that counts among its stable of dancers Diana Armstrong, a.k.a. "Diamond" (newcomer LisaRaye). Like Demi Moore in Striptease, college senior Diana dances to support her child and better her life (and pay her tuition).
Cube, who also wrote and has a small role, one-ups his film's stripping cinematic cohorts by for the most part succeeding in his intentions. The Diana-Ronnie feud, thanks in no small part to the solid performances by Wilson and LisaRaye, never comes off as ridiculous. Cube has his cake and eats it too--he even delivers the knock-down, drag-out catfight that Showgirls promised but never delivered. And unlike Striptease, most of the humor works. Earning the lion's share of laughs is Bernie Mac as the club's sleazy malapropism-prone owner Dollar Bill; Jamie Foxx also has some effective comic scenes as Blue, the club's DJ.
However, that's also where Cube runs into some trouble. The broad humor and more cartoonish characters (like Dollar Bill and his right-hand man L'il Man, played by A.J. Johnson) are never seamlessly meshed with the film's largely grim, gritty tone and earnest story. Some laugh lines fall flat (one reference to co-star John Amos's former role on the TV show Good Times is too obvious and in-jokey to be funny), as does some of the dialogue in general; Cube sometimes offers hackneyed lines such as "I walked into the Players Club a girl... and came out a woman."
But overall Cube guides The Players Club with a sure hand, and he makes a true acting find with the commanding LisaRaye, whose diamond-hard charisma recalls the young Pam Grier. Diana's mantra "Make the money; don't let the money make you" is neither the most profound nor original statement, but LisaRaye is able to make you believe it--and believe _in_ it.
Michael Dequina Chat Forum Host, The Official Michael Jordan Web Site http://jordan.sportsline.com
<EMAIL_ADDRESS><EMAIL_ADDRESS>|<EMAIL_ADDRESS>>My personal WWW sites< Mr. Brown's Movie Site: http://welcome.to/mrbrown Michael Jordan Beyond the Court: http://fly.to/michaeljordan A Michael Jordan Fan's Heartbreak: http://fly.to/mj23 Personal Page: http://welcome.to/w3md >Other WWW sites I work on< CompuServe Hollywood Hotline: http://www.HollywoodHotline.com Albany Online: http://www.AlbanyOnline.com Eyepiece Network: http://www.eyepiece.com
"I didn't know what to expect. It's like something you chase for so long, but then you don't know how to react when you get it. I still don't know how to react." --Michael Jordan, on winning his first NBA championship in 1991 ...or, my thoughts after meeting him on November 21, 1997
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
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Related links: index of all rec.arts.movies.reviews reviews


Lieutenant in Capt Joseph Sands Company, 5th Battalion Berks County Militia (Pennsylvania) [PA Archives, Series 3, Volume VI, pg 288, Berks County Accounts of Lieutenants]
Lieutenant in Capt Weidner’s Company in Col Lutz’s 1st Battalion of Berk’s County in Apr and May 1785 [PA Archives, Series 6, Volume III, pg 55, Militia Rolls of Berk’s County 1783-1790]
Captain of the 6th Company of the 6th Regiment [PA Archives, Series 6, Volume 5, pg 129, Pennsylvania Militia 1790-1800, Berks County, Muster and Pay Rolls]
Private in Capt Abraham Huy,Berks County Militia, 2nd Battalion
Peter Zerbe (
Fold3) (DAR – No Entry) (SAR – No Entry)
1738-
Service recorded under Peter Servey / Servy
Pvt
Capt John Huling’s Company, 2nd Battalion, 3rd Pennsylvania Regiment, Col Arthur St. Clair and Col Joseph Wood [PA Archives, 5th Series, Volume 2, page 109 and Service record]
Continental Line, Enlisted at Chesterfield, Virginia [Virginia Society Quarterly, volume 2, pg 50][Size Roll of the Troops Joined at Chesterfield County House since 1st Sep 1780]


QMRITools PACKAGE SYMBOL
HistogramPar
HistogramPar[data, {constraints, Nbins}, style, color, range]
plots histograms of IVIM solution.
HistogramPar[data, {constraints, Nbins, mu, conv}, components, color, range]
plots histograms of IVIM solution. data is {f1, dc, pdc1} or {f1, f2, dc, pdc1, pdc2}. constraints are the ranges of the x-axes for the plots. Nbins are the number of histogram bins. style is the plot type, can be 1, 2, or 3. color is the color of the histogram. range are the ranges of the y-axes. output is a row of histograms.


request.tests package¶
Submodules¶
request.tests.test_urls module¶
Django url tests for ride management functionality
-
class
request.tests.test_urls.
TestUrl
(methodName='runTest')¶ Bases:
django.test.testcases.SimpleTestCase
Class for testing urls in ride management functionality
-
test_accept_request_resolves
()¶ Tests for ride accepted url
-
test_cancel_accepted_ride_resolves
()¶ Tests for ride acceptance request url
-
test_cancel_ride_resolves
()¶ Tests for ride cancellation request url
-
test_delete_ride_resolves
()¶ Tests for ride accepted deleted url
-
test_reject_request_resolves
()¶ Tests for ride denied url
-
test_requested_ride_resolves
()¶ Tests for ride request url
-
request.tests.test_views module¶
File containing django view tests for ride management functionality
-
class
request.tests.test_views.
TestViews
(methodName='runTest')¶ Bases:
django.test.testcases.TestCase
Test class to test Django views for ride creation functionality
-
setUp
()¶ Hook method for setting up the test fixture before exercising it.
-
test_accept_ride_request
()¶ Tests for ride accepted
-
test_cancel_accepted_ride
()¶ Tests for accepted ride cancellation
-
test_cancel_ride_logged_in_user
()¶ Tests for ride canceled for logged in user
-
test_delete_ride
()¶ Tests for ride deleted
-
test_reject_ride_request
()¶ Tests for ride rejected
-
test_requested_rides
()¶ Tests for ride requested
-


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The nodes of this tree are read from YQL, any replies rely on that service. The nodes have references to albums and artists so that by clicking on them or pressing enter while they have the focus, it will navigate away.
This tree is built dynamically with randomized labels just to show selection, supposedly of files/folders. The Save button will list in the container below the JSON for those files/folders marked as selected.
The container for this tree has class="yui3-fw-treeview-checkbox"
set because node
selection is always active in TreeView, it just needs to be made visible through CSS styles, which
the default stylesheet contains and this className activates.


Instructor Details
Name: Raghava Mutharaju
Email<EMAIL_ADDRESS>Office: B-511 (Research & Development Block)
Office Hours: send an email to setup an appointment
TA Details
Nihit Jain<EMAIL_ADDRESS>Aayush Jain<EMAIL_ADDRESS>Office Hours: 2:30pm to 3:30pm
Office Location: Library ground floor
Grade distribution
- Quiz: 2*10 = 20%
- Mid sem: 20%
- In-class activity: 2*5 = 10%
- Project = 25%
- End sem: 25%
References
- Textbook: Foundations of Semantic Web Technologies. Pascal Hitzler et. al. CRC Press.
- Reference book: Linked Data: Storing, Querying, and Reasoning. Sherif Sakr, Marcin Wylot, Raghava Mutharaju, Danh Le Phuoc, Irini Fundulaki. Springer
- Reference book: Knowledge Representation and Reasoning. Ronald Brachman, Hector Levesque. Morgan Kaufmann
- Reference book: Artificial Intelligence. Stuart Russell, Peter Norvig. Pearson


nftfw - manage the Nftfw firewall generator
nftfw is the front-end for the firewall system that generates rules for nftables. It uses files in five directories in /etc/nftfw to create firewall rules. The directories create incoming and outgoing firewalls, and also tables for whitelisting and blacklisting particular IP addresses. The distribution is installed relative to the system’s root or below /usr/local.
The nftfw command has several options, and most of these don’t change that often when the system is in operation. Editing the ini format file /etc/nftfw/config.ini changes the values of options - see nftfw-config(5). You may make temporary variable changes to configuration values from the command line using the -o option to nftfw (see below).
The optional command argument to nftfw runs main modules of the program. All actions need users to have root access permission. A lock file ensures the running of only one instance of the program, nftfw queues actions if it’s busy, and runs queued actions at the finish of the task in hand.
nftfw uses an initial setup file /etc/nftfw/nftfw_init.nft to form the framework for the completed ruleset. When nftfw builds the firewall rules, the nftfw_init.nft file is copied into the build system, and uses include statements to pull in rules from the separate files created from the four directories.
The system, as distributed, provides a firewall for a hosted server with one external internet connection. Administrators can change the nftfw_init.nft file to support more complex network needs.
Actions are:
load
The load command builds the firewall files by taking input from files in directories in /etc/nftfw:
nftfw-files(5) describes the contents and formats of files in these directories.
nftfw load performs these steps, creating files in directories in /var/lib/nftfw:
The command builds a firewall ruleset in several files in build.d, and copies nftfw_init.nft into the directory creating the initial framework. Rules generated from incoming.d and outgoing.d support the basic system services. Rules formed from the whitelist.d. blacklist.d and blacknets.d directories make use of nftables sets. These sources change more often than the other directories, and the use of sets allows nftfw to change parts of the installed ruleset without completely reloading the firewall.
nftfw now runs the nft -c command validating the rules. Errors cause nftfw to abandon any further processing.
If all is well, nftfw compares the files with those in install.d retained from the last run of the program. File comparison allows nftfw to decide on doing nothing, making a full update, or just updating the blacklist and/or whitelist sets.
nftfw copies all the files into the install.d directory and loads these rules into the system’s kernel depending on the decision above.
Finally nftfw captures the kernel settings and stores them in /etc/nftables.conf, which is where the Debian system expects to find the rules on system start-up.
The steps from (4) above could result in a broken system if parts of the installation fails. nftfw avoids the possible disaster by storing a backup copy of the kernel’s rules before attempting any update. On failure, nftfw reverts to the backup rules.
whitelist
The whitelist action is a scanner for the system’s wtmp(5) or utmp(5) file. The system records user logins in this file along with the IP address used to access the system. nftfw creates a file named for the IP address in /etc/nftfw/whitelist.d as long as the IP address is global.
The whitelist command expires addresses that were automatically created (identified by the suffix .auto) after a set number of days given in nftfw’s config file.
If the scanner makes any changes, whitelist invokes the load command automatically installing the changes in the firewall.
See nftfw-files(5) for information on the file formats used for whitelist control files.
blacklist
The blacklist command is a file scanner creating IP address files in /etc/nftfw/blacklist.d. The scanner reads pattern files from /etc/nftfw/patterns.d. Pattern files contain a file name (or a range of files given by shell glob rules), the relevant ports for blocking and a set of regular expressions matching offending lines in the nominated log files.
When nftfw finds a match, it updates a sqlite3(1) database with the information and uses the frequency of matches (given in the config file) to decide whether to blacklist the IP.
When scanning log files, the blacklist engine remembers the position in the file at the end of the last scan, so only examines new entries on every pass. The blacklist command also expires blacklisted IPs after a set number of days. See nftfw-files(5) for information on the file formats used for blacklist control files.
If the scanner makes any changes, blacklist invokes the load command automatically installing the changes in the firewall.
tidy
The tidy command removes old entries from the blacklist database stopping it from growing to immense proportions. tidy removes IP’s that haven’t appeared for a set number of days. The configuration file (see nftfw-config(5)) supplies the number of days.
These are the available options to the program:
Prints brief usage information.
Does a full install, ignores the file compare installation step.
Create rules in _/var/lib/nftfw/test.d and tests them. When used with the blacklist command, prints the result of scanning for matches without saving any information and without updating stored log file positions.
Supply a alternate configuration file, overriding any values from the default system settings.
The argument only applies to the blacklist command, and runs the command using only one pattern file (the name of the file omitting the suffix .pattern). When combined with -x and setting ports=test in the pattern file the option can be used to test regular expressions in pattern files.
List all the configuration names and settings
List all the configuration names and settings that are different from those compiled into the program. Useful to telling what configuration options have been changed in config.ini.
OPTION is keyword=value and may be comma separated list of configuration options. The values override any settings in the configuration file.
Suppress printing of errors and information messages to the terminal, syslog output remains active. Terminal output is suppressed when the output is not directed to a terminal
Change the default logging settings to INFO to show all errors and information messages.
Files can be located under / or /usr/local.
Location of control files and directories
nftables basic framework
ini file with basic settings for nftfw, overriding built-in values
Location of build.d, test.d, install.d, lock files and the sqlite3 databases storing file positions and blacklist information
See GitHub Issues: https://github.com/pcollinson/nftfw/issues
Peter Collinson (huge credit to the ideas from Patrick Cherry’s work for the firewall for the Symbiosis hosting system).
nft(1), nftfwls(1), nftfwedit(1), nftfwadm(1), nftfw-config(5), nftfw-files(5)


Karman Singh, Eric Chung, Edward Chung
Service-Learning Course Project as part of DS 4200: Information Presentation and Visualization, taught by Prof. Cody Dunne, Data Visualization @ Ktimey, Northeastern University.
Prior to designing these visualizatons, we knew that we wanted to build a means for gauging the levels of pedestrian safety over time in Chester Square Park and measuring the change in safety level over time as new initiatives are put into place. Since perceived safety level is not a standard metric with an open dataset available to the public, we decided to use crime reports as an analog for safety measure around Boston and in Chester Square Park. Ultimately, what we decided to try and accomplish was building a comparison tool that would allow users to compare crime reports around Chester Square Park over time and with other neighborhoods around Boston. By building this tool, we were hoping that Carol and others at the Chester Square Neighborhood Association would be able to look at plans put in place at similar parks around Boston to be able to learn how to make Chester Square Park more safe (and welcoming) for pedestrians.
For our visualization, there are 4 main components. The first is the choropleth map in the top right which updates based on the dataset that is selected and shows an overview of the selected data using different shades of color. When a neighborhood is selected on the choropleth map, the second visualization (a line chart) in the top left corner is updated to show the relevant data for the specific neighborhood that is chosen. The third visualization is the stacked bar chart in the middle which shows every neighborhood in Boston and Chester Square Park. This stacked bar chart is brushed and linked with the other two visualizations to allow for aggregation of the data of multiple neighborhoods. Finally, the last component of our visualization is the scatter plot and bar graph at the bottom which shows the results of the survey we sent out to the residents of Chester Square along with crime data specific to Chester Square.
The primary dataset that we used was the Boston Crime dataset pulled from the Analyze Boston website. Due to the fact that the dataset was very large (over 450,000 entries) we did a lot of preprocessing using Python to aggregate the data ahead of time. For example, for the crime count by time chart, we ran a python script on the Boston crime dataset ahead of time to aggregate the data by time before displaying the data using D3.
For this project, we had three tasks that we wanted to accomplish: aggregate crime, real estate, and demographic data for Boston neighborhoods, analyze pedestrian demographic data of Chester Square Park, and compare the level of safety current users of the park feel with crime reports. For the first task we had, analyzing the different types of data, we wanted to summarize the plethora of data across the three datasets we had and allow users to be able to browse the data through our visualizations. The focus of our second domain task was to identify the different kinds of demographic data we were working with and then allow users to look up the different data and make their own discoveries about it. For our last task analysis we wanted to allow users to compare the survey results of perceived safety level with the hourly crime count and make their own discoveries and conclusions about the data.
We began our design process by looking at already existing visualizations of crime data for Boston. While looking
at the visualizations, we
noticed that there was a common theme in that all of the already existing visualizations did not have good visual
encodings and were overall very
unintuitive. A common problem was the color schemes for the visualizations were very poorly chosen. With this
information in mind, we decided
that we would create a better crime map for Boston.
On top of creating a crime map, we also surveyed
safety levels of residents around Chester
Square Park and plan to compare crime levels with perceived safety levels around the Park. We hope to find a
correlation between crime and safety
around the park so as to use the crime dataset we have as an analog for Safety data. Originally we planned on our
visualizations to look like the
following:
However, after looking at the visualizations more critically, we realized that size encoded circles were not the best way to show relative crime (and real estate prices). Ultimatley we chose to go with the shaded neighborhood regions instead as this was a more distinguishable use of color.
Over the past few months, we have been able to create a visualizaton that accurately compares the crime counts of all of the different neighborhoods in Boston with the crime counts in Chester Square Park. Users are able to see crime counts by the hour for each neighborhood and are able to aggragate results of multiple neighborhoods. Currently, our visualization compares the crime count and top 5 crime categories reported in Chester Square Park with neighborhoods as a whole around Boston. We understand that this is not an even comparison and in the future we hope to isolate data for parks around Boston similar to how we did for Chester Square Park now. Using the real estate and demographic data we have also included in our visualization, we hope that users, in the future, will be able to find parks with similar real estate and demographic values. Once these parks are located, users can then look into the history of those parks to see what initiatives were implemented in the past as well as if they were succesful.


I know, I know. It doesn’t look like much. Yet
But on my own code learning journey this webpage represents a bit of technical milestone for me as I put the whole thing together with a command line and a keyboard, no windows, no menus, no mouse :-)
I installed Ubuntu LTS 16.04 then complied Node and Express from source, and that’s what I using to serve this page to you now
The page itself will be evolving quickly as I progress through Bloc’s Full Stack Web Dev curriculum, and will eventually turn into my personal blog and a portfolio of my completed projects and freelance work. But for the time being you may see some odd features that make no sense, but that's just me playing with new tools and concepts while I hone my skills
I thought this article was helpful to me as a Windows user to help ease me back in to the Linux/CLI I learned many years ago: How to set up the perfect modern dev environment on Windows
This was also very helpful in helping me get my HTTP server running, though it is a bit out of date when it comes to using upstart instead of system to run it as a service: The Node Den - Setting Up a Node.js Website


Elite Dangerous: Rare Commodities Star Chart
Use the mouse to pan or zoom
Include systems with long trips to stations


This is part 2 of applying machine learning to practical business problems. Part 1 here. We are working on trying to build a model to predict if an article on Lifehack will become popular or not.
In Part 1 we have gone through the whole data preparation process, which involves data collection, data preprocessing and data transformation. We will now build a priliminary model with the training and testing data.
Remember we partitioned our training and testing data as follows, visualized:
Due to having a lot more negative data than positive data in the training set, our trained model performance will be very poor, despite we supplied a lot of training data. To resolve this, one way is undersampling, which we will throw away negative data. Counter-intuitively, this actually helps. This is called the Class Imbalance Problem.
Because of the class imbalance problem, we want to keep the training set with 1:1 ratio of positive to negative data, visualized:
In step 3 of the figure, we throw away a large number of negative examples in the training set. In step 4, we see that the training set is now much smaller with equal number of positive and negative data. This will be the training set we will use. There is no change to the testing set.
There are a lot of models to pick from, such as Random Forest, Support Vector Machines, Linear Regression, Logistic Regression, Gradient Boosted Models, etc… how do we start?
Try something fast, and simple. Preferably with few parameters. So you have a quick turnaround to get a feeling of the dataset and problem at hand. Linear models are a good start. SVMs are not, because you would have to tune the C and gamma parameters, and they are in generally very slow compared to linear models.
In this case, we will pick the Ridge Classifier of Scikit-Learn as our first attempt. It is a linear model, and is relatively first. In practice, it also performs quite well.
The Ridge expects an input matrix of shape {number of examples, number of features} and a vector, the target class. Yet, our training data is a list of text articles. What do we do?
We can use TfidfVectorizer to construct a TF-IDF matrix for our training data. Basically, it converts the text article to a matrix representation of the words suitable for our machine learning algorithm to take in.
After this transformation, we now have an input matrix of shape {number of examples, number of features}.
We refined our training set, converted the data to a matrix for training. We are now ready for a first run! The model in Python Scikit Learn looks like this (with parameters omitted for clarity):
model = Pipeline([ ('fe1', TfidfVectorizer()), ('clf', RidgeClassifier(alpha = 1.0)), ])
The Pipeline is just a construct in Scikit Learn to streamline the data transformation and training. We can now use the model to start training on the training data.
We want to know how good we perform. You may be attempted to use accuracy score, but no. If there are 10000 articles with only 5 positive examples, classifying all articles as negatives will give you an impressive 99.x% accuracy. Apparently, this is a bad model.
Instead, we will use the Receiver Operating Characteristic Area Under Curve (ROC_AUC) score function, which is much more informative by considering true positive rates and false positive rates. A perfect model will have 1.0 score, and a random model will have 0.5 score. A model with less than 0.5 score is useless.
If we use the example above, suppose we classify all examples as negative and get 9995 classifications right, the ROC_AUC will be just 0.5, which means it is completely random.
This model we use yielded and ROC_AUC score of about 0.50~60 on the testing set.
What? Just a bit better than random! How come?
If you have tried toy datasets, it is painfully easy to get a 95% accuracy. However, we are dealing with real data here. It needs optimization effort.
As a best practice, it is a good idea to get something work first, we will then fine tune from there. In fact, machine learning isn’t a one-shot thing. You improve it iteratively, just like you would do in software engineering.
In part 3, I will talk about how to improve this poor preliminary model and how to make sure it performs well on testing data.


{% extends "layout.html" %} {% block title %}500 Error{% endblock %} {% block body %}
Hmm, we seem to be experiencing problems. Please give us a few minutes to get things worked out.
Perhaps you should start over.


Professional Summary
Responsible and determined individual with excellent troubleshooting and critical-thinking skills demonstrated by 3 years of experience as a Geek Squad C.I.A (Counter Intelligence Agent) with Best Buy Corp. Acompanied with a strong desire to provide suberb customer service working in my family's automotive glass shop for many years growing up. Currently studying computer programming and digital design, I believe that I would be an invaluable asset to any organization.


Udacity frontend study blog!
Image
all images in CSS will learn from here.
Veritical
Squares
I love this cat!!


What is this template?
This template is Flash 9 based XML driven web site, with the main intention to be an interactive gallery of images.
The customization of this web site is handled completely by editing an XML file named galleries.xml that sits right alongside where you found this documentation file.
You can (and for most people, should) edit and completely customize this website without ever opening it in Flash, you don't even need to own Flash. Just edit the XML!
An XML Overview
For the un-initiated, I want to cover the basics of XML. XML is not like like HTML in the sense that every tag has no predefined meaning. If I make a tag <strong/> it does not necessarily mean that it will be bold like in HTML. In XML, all it does is hold data in a way that it can be easily accessed by a program. This flash program reads the XML and interprets the data it needs to make the program run, which is perfect for templates, because I can make it generic and you can just fill in the XML. That's the idea behind XML driven templates!
XML has tags just like HTML, and the important things you need to know is that each tag can hold data in two main ways: sub-nodes and attributes. In the example <image icon="images/image1.jpg" full="images/image2.jpg"/> there is no sub-nodes, and it is just using attributes to hold its data. The attributes are icon and full, the values are always enclosed in quotes, and in the case of my template, that is a tag for defining an image, and the paths to its icon view and full size view. The example <node><subnode/></node> is how nodes nest within each other. For more in depth examples of how to work with XML go
here
Overview
This XML file contains data for the title of the page, the displayed phone number, the displayed email, the three images displayed as the home page, and every menu item except for the "home" link. Inside the data for each menu item, the XML also defines everything that is done when that menu item is clicked. I will now cover all of these areas. NOTE: This is also documented in the XML itself.
The home Attribute
The home attribute on the root xml node determines whether or not there will automatically be a home page consisting of 3 images that show (as in the example). If you change it to false, whatever you make as the first menu item will just be considered the "homepage" and when the Flash is opened it will default to that. That item will still show whatever name you gave it though.
The title Node
The very first node inside the main <xml> node is the <title> node. Inside of it you will find what is called a CDATA node which holds literal text. To change the title node, you simply swap out the literal text inside the brackets in the CDATA. Such as <![CDATA[Old Title]]> gets changed to <![CDATA[New Title]]>
The email Node
The second node inside the main <xml> node is the <email> node. Inside of it you will find what is called a CDATA node which holds literal text. To change the email node, you simply swap out the literal text inside the brackets in the CDATA. Such as<EMAIL_ADDRESS>gets changed to<EMAIL_ADDRESS>The phone Node
The third node inside the main <xml> node is the <phone> node. Inside of it you will find what is called a CDATA node which holds literal text. To change the phone node, you simply swap out the literal text inside the brackets in the CDATA. Such as <![CDATA[1 800 old numb]]> gets changed to <![CDATA[1 800 new numb]]>. Keep in mind that the formatting of the number is completely up to how you type it!
The 3 Home image Nodes
The fourth, fifth, and sixth nodes inside the main <xml> node are all <image> nodes. These nodes determine what 3 images display as the homepage's 3 images. Each of these 3 nodes has two attributes named icon and full. These two attributes are the paths to the the icon view of the image and the full size view of the image respectively.
DIMENSION DATA: Each image to display has an icon view and full view. The icon view is automatically resized so that largest dimension gets lowered to 250 pixels, and the other dimension gets lowered so that the aspect ratio is maintained (no distorting). In light of that, I highly recommend that you resize all icon images so that their largest dimension is 250 pixels. The full size images are displayed as large as the browser will allow them to, as long as that is not larger than their actual size. For that I would recommend that you make their largest dimension about 700-1000 pixels. If you fail to resize image for either icon or full they will still work, but download times will increase exponentially, and the quality of the displayed images could possibly be less, because if flash has to drastically resize them to fit they could pixelate slightly.
The Menu's button Nodes
From the seventh node on is all nodes for the menu, called <button> nodes. Each of these nodes has one common attribute named type. The type attribute can have 3 possible values, link, gallery or swf. For each different type, you get a different menu item, and have to format its XML differently. I will cover each of them below.
The link Type Button
The link button type makes a menu button that will open a link, and is quite easy to do. In addition to the type attribute, it has two more attributes, name and window. The name attribute is just what text is displayed for that item in the menu. The window attribute determines how the link opens, _blank for in a new window, and _self to make the current window just change to the link. The actual link itself is held within a CDATA tag. To change the link, you simply swap out the literal text inside the brackets in the CDATA. Such as <![CDATA[oldlink.com]]> gets changed to <![CDATA[newlink.com]]>
The swf Type Button
The swf button type makes the flash load in an external swf to use as the page. In addition to the type attribute, it has four more attributes, name, link, width, and height. The name attribute is just what text is displayed for that item in the menu. The link attribute is the path to the swf to be loaded. And the width and height attributes are for you to tell it the width and height of the swf, for placement purposes. This can use ANY swf, AS2, AS3, or even SwishMax.
The gallery Type Button
The gallery type button allows you to set up an image gallery. This is the most complex XML you will have to deal with, and that being said, it's not hard as long as you look through the examples that are already done in the galleries.xml file, and see how they relate to what is being shown on the screen.
Each gallery type button node itself holds one attribute in addition to the type attribute, and that is its name. After that it is to be filled with as many client nodes as neccessary. Client nodes are what end up as the small pictures that appear along the bottom that you click on to view a group of images. The idea is that you would have a gallery for say, weddings, then a list of clients like the smith wedding, the johnson wedding, etc. If you're a designer, you make make a button named Print Work, with the clients being, Sprint, General Motors, etc. Of course, you could abandon convention altogether, and group things however you like :)
Each client node has a name attribute, which shows as a rollover, and an icon attribute, which is a link to the icon to be displayed for that client group. Inside each client group is any neccessary number of image tags, denoting the images in that group. For more info on the images tags, see "The 3 Home image Nodes" a little ways up this page, it will tell you how they work.
The best way to learn is to make an experimental copy of the template somewhere (don't experiment on the original) and just try things, explore what happens when you change what in the XML, and look at the relation to the XML file and what displays in the website. If you get any specific questions, I'll be glad to help - bryan@madbunny.us


Please read carefully
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Preparation time
overnight
Cooking time
over 2 hours
Serves
Serves 10
Dietary
Decorate this traditional Easter cake with crystallised primroses or other edible spring flowers to make it look extra special.
Preheat the oven to 150C/300F/Gas 2. Grease a 20cm/8in deep round cake tin and then line the base and sides with baking parchment.
Cut the cherries into quarters, put in a sieve and rinse under running water. Drain well and then dry thoroughly on kitchen paper.
Beat the butter and sugar together in a large bowl until light and creamy. Beat in the eggs, one at a time, to prevent them from curdling. Sift in the flour and mix it in a little at a time. Stir the fruit, peel, zest and mixed spice thoroughly into the mixture. Place half the mixture into the prepared tin and level the surface.
Take one-third of the marzipan and roll it out to a circle the size of the tin and then place the circle on top of the cake mixture. Spoon the remaining cake mixture on top and level the surface.
Bake in the preheated oven for about 2½ hours until well-risen, evenly brown and firm to the touch. Cover with foil after one hour if the top is browning too quickly. Leave to cool in the tin for 10 minutes and then turn out, peel off the parchment and finish cooling on a wire rack.
When the cake is cool, warm the apricot jam in a small saucepan. Brush the top of the cake with a little of the jam and roll out half of the remaining marzipan to fit the top of the cake. Press firmly on the top and crimp the edges to decorate. Mark a criss-cross pattern on the marzipan with a sharp knife. Form the remaining marzipan into 11 balls.
Brush the marzipan with beaten egg and arrange the marzipan balls around the edge of the cake. Brush the tops of the balls with beaten egg, too, and then place the cake under a hot grill to turn the marzipan golden-brown.
To crystallise the primroses, whisk the egg white in a bowl until frothy. Snip the long stalks off the primroses, then, using a paint brush, carefully paint the petals of each primrose with a little frothy egg white, then turn the flower over and paint the underside of the petals and the little stalk.
Cover the flowers in caster sugar until all the egg white is evenly coated, and leave to dry completely. You can either just lie them carefully on non-stick parchment, or, to help keep the flowers’ shape, you can stretch non-stick paper over a plastic box or bowl, securing it in place with string or a rubber band, and then pierce several holes in the paper using a skewer. Place the stems of the crystallised flowers through the holes, allowing the paper to hold and support the flowers in a more natural position as they dry and harden. You will need to make the crystallised flowers at least a day in advance.
Decorate the cake by arranging the crystallised primroses on top and tying a ribbon around the middle.


Sildes and code available in github:
best_move (@board):
$scores;
for $dir (qw/left right up down/) {
for (0..2000) {
while (not_lost) {
add_random_tile;
random_player_move;
$score{$dir}++;
}
}
}
get_best_score
}
NOW!!
Let's go!
In software engineering, profiling ("program profiling", "software profiling") is a form of dynamic program analysis that measures, for example, the space (memory) or time complexity of a program, the usage of particular instructions, or the frequency and duration of function calls. Most commonly, profiling information serves to aid program optimization.
# profile code and write database to ./nytprof.out
perl -d:NYTProf some_perl.pl
# convert database into a set of html files, e.g., ./nytprof/index.html
# and open a web browser on the nytprof/index.html file
nytprofhtml --open
# or into comma separated files, e.g., ./nytprof/*.csv
nytprofcsv
use Test::More;
subtest 'Shift row' => sub {
ok( join('', $game->shift_row(1,1,0,0)) eq '2000', '1100 -> 2000');
ok( join('', $game->shift_row(0,0,0,1)) eq '1000', '0001 -> 1000');
ok( join('', $game->shift_row(0,3,0,3)) eq '4000', '0303 -> 4000');
ok( join('', $game->shift_row(3,2,0,2)) eq '3300', '3202 -> 3300');
ok( join('', $game->shift_row(0,0,0,0)) eq '0000', '0000 -> 0000');
ok( join('', $game->shift_row(1,0,0,0)) eq '1000', '1000 -> 1000');
ok( join('', $game->shift_row(1,2,3,4)) eq '1234', '1234 -> 1234');
ok( join('', $game->shift_row(1,2,1,2)) eq '1212', '1212 -> 1212');
ok( join('', $game->shift_row(1,2,2,1)) eq '1310', '1221 -> 1310');
};
In computing, a benchmark is the act of running a computer program, a set of programs, or other operations, in order to assess the relative performance of an object, normally by running a number of standard tests and trials against it. The term 'benchmark' is also mostly utilized for the purposes of elaborately-designed benchmarking programs themselves.
use Benchmark qw(:all) ;
timethis ($count, "code");
# Use Perl code in strings...
timethese($count, {
'Name1' => '...code1...',
'Name2' => '...codede2...',
});
$ script/compare_shifts.pl
Rate original modified
original 94339/s -- -56%
modified 212764/s 126% --
$ script/compare_solvers.pl SolverInitial SolverFasterShift
s/iter SolverInitial SolverFasterShift
SolverInitial 12.7 -- -24%
SolverFasterShift 9.68 32% --
sub move_board {
my ( $self, $direction, @board ) = @_;
my @new;
my $idx = 0;
for (0..3) {
my @r = (
$self->rotation->[$direction][$idx++],
$self->rotation->[$direction][$idx++],
$self->rotation->[$direction][$idx++],
$self->rotation->[$direction][$idx++]
);
( $new[$r[0]], $new[$r[1]], $new[$r[2]], $new[$r[3]] ) =
$self->shift_row($board[$r[0]], $board[$r[1]], $board[$r[2]], $board[$r[3]] );
}
return @new;
}
sub move_board {
my ( $self, $direction, @board ) = @_;
my @new;
my ($p0,$p1,$p2,$p3);
my $r = $self->rotation->[$direction];
my $idx = 0;
for (0..3) {
$p0 = $r->[$idx++];
$p1 = $r->[$idx++];
$p2 = $r->[$idx++];
$p3 = $r->[$idx++];
($new[$p0], $new[$p1], $new[$p2], $new[$p3] ) =
$self->shift_row($board[$p0], $board[$p1], $board[$p2], $board[$p3] );
}
return @new;
}
$ script/compare_solvers.pl SolverInitial SolverFasterMoveBoard
s/iter SolverInitial SolverFasterMoveBoard
SolverInitial 13.4 -- -11%
SolverFasterMoveBoard 11.9 13% --
package SolverMemoizeShiftRow;
..
use Memoize;
memoize 'shift_row';
package SolverMemoizeMoveBoard;
..
use Memoize;
memoize 'move_board';
package SolverMemoize2;
..
use Memoize;
memoize 'move_board';
memoize 'shift_row';
$ script/compare_solvers.pl SolverInitial SolverMemoizeMoveBoard SolverMemoizeShiftRow SolverMemoize2
s/iter SolverMemoizeMoveBoard SolverMemoize2 SolverMemoizeShiftRow SolverInitial
SolverMemoizeMoveBoard 19.8 -- -12% -23% -32%
SolverMemoize2 17.4 14% -- -12% -22%
SolverMemoizeShiftRow 15.4 29% 13% -- -12%
SolverInitial 13.5 47% 29% 14% --
Memoize is for expensive methods
Where are you?
has 'rotation' => (
is => 'ro',
default => sub {[
#left
[ 0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15 ],
#right
[ 3,2,1,0,7,6,5,4,11,10,9,8,15,14,13,12 ],
#up
[ 0,4,8,12,1,5,9,13,2,6,10,14,3,7,11,15 ],
#down
[ 12,8,4,0,13,9,5,1,14,10,6,2,15,11,7,3 ],
]},
);
...
$self->rotation->[$direction][$idx++]
my $rotation = [
#left
[ 0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15 ],
#right
[ 3,2,1,0,7,6,5,4,11,10,9,8,15,14,13,12 ],
#up
[ 0,4,8,12,1,5,9,13,2,6,10,14,3,7,11,15 ],
#down
[ 12,8,4,0,13,9,5,1,14,10,6,2,15,11,7,3 ],
];
...
$rotation->[$direction][$idx++]
$ script/compare_solvers.pl SolverInitial SolverWithoutMoose
s/iter SolverInitial SolverWithoutMoose
SolverInitial 12.7 -- -13%
SolverWithoutMoose 11.0 15% --
sub move_board {
...
for (x) {
$self->shift_row(@array);
}
...
}
sub shift_row {
...
shift_row_stuff;
...
}
sub move_board {
...
for (x) {
shift_row_stuff;
}
...
}
$ script/compare_solvers.pl SolverInitial SolverLessMethods
s/iter SolverInitial SolverLessMethods
SolverInitial 13.3 -- -41%
SolverLessMethods 7.85 69% --
my %scores = ();
my $pm = Parallel::ForkManager->new(4 * $self->forks_x_dir);
for (1..$self->forks_x_dir) {
for my $direction (0,1,2,3) {
my @moved_board = $self->move_board($direction, @board);
if ( !$self->same_board(@moved_board, @board) ) {
$pm->start and next;
srand(time + $direction);
my $score;
for (1..($self->moves/$self->forks_x_dir)) {
$score += $self->play_random_game(@moved_board);
}
$pm->finish(0, \[$direction, $score]);
}
}
}
$pm->wait_all_children;
$pm->run_on_finish (
sub {
my ($pid, $code, $ident, $signal, $cd, $data_structure_reference) = @_;
if (defined($data_structure_reference)) {
$scores{${$data_structure_reference}->[0]} += ${$data_structure_reference}->[1];
}
}
);
src$ script/compare_solvers.pl SolverInitial SolverParallelMulti
s/iter SolverParallelMulti SolverInitial
SolverParallelMulti 19.7 -- -35%
SolverInitial 12.8 54% --
4 cores:
$ time CLASS=SolverInitial script/various_moves.pl
real 0m49.875s
user 0m49.848s
sys 0m0.000s
$ time CLASS=SolverParallelMulti script/various_moves.pl
real 0m24.267s
user 1m25.400s
sys 0m0.092s
8 cores:
$ time CLASS=SolverInitial script/various_moves.pl
real 0m39.925s
user 0m39.904s
sys 0m0.012s
$ time CLASS=SolverParallelMulti script/various_moves.pl
real 0m12.012s25s
user 0m52.049s
sys 0m0.128s
src$ time CLASS=SolverInitial script/various_moves.pl
real 0m39.013s
user 0m38.013s969s
sys 0m0.024s
$ time CLASSS=Solver script/various_moves.pl
real 0m4.860s
user 0m20.046s
sys 0m0.113s
marc@z1:~/work/talks/2048-strikes-back/src$


| |
ActiveTcl User Guide
|
|
|
- NAME
- label - Create and manipulate label widgets
- SYNOPSIS
- label pathName ?options?
- STANDARD OPTIONS
- -activebackground,
activeBackground, Foreground
- -activeforeground,
activeForeground, Background
- -anchor, anchor, Anchor
- -background or -bg,
background, Background
- -bitmap, bitmap, Bitmap
- -borderwidth or -bd,
borderWidth, BorderWidth
- -cursor, cursor, Cursor
- -disabledforeground,
disabledForeground, DisabledForeground
- -font, font, Font
- -foreground or -fg,
foreground, Foreground
- -highlightbackground,
highlightBackground, HighlightBackground
- -highlightcolor,
highlightColor, HighlightColor
- -highlightthickness,
highlightThickness, HighlightThickness
- -image, image, Image
- -justify, justify,
Justify
- -padx, padX, Pad
- -pady, padY, Pad
- -relief, relief, Relief
- -takefocus, takeFocus,
TakeFocus
- -text, text, Text
- -textvariable,
textVariable, Variable
- -underline, underline,
Underline
- -wraplength, wrapLength,
WrapLength
- WIDGET-SPECIFIC OPTIONS
- -compound, compound,
Compound
- -height, height,
Height
- -state, state,
State
- -width, width,
Width
- DESCRIPTION
- WIDGET COMMAND
- pathName cget
option
- pathName
configure ?option? ?value option value
...?
- BINDINGS
- KEYWORDS
label - Create and manipulate label widgets
label pathName ?options?
- -activebackground,
activeBackground, Foreground
- -activeforeground,
activeForeground, Background
- -anchor, anchor,
Anchor
- -background or -bg,
background, Background
- -bitmap, bitmap,
Bitmap
- -borderwidth or -bd,
borderWidth, BorderWidth
- -cursor, cursor,
Cursor
- -disabledforeground,
disabledForeground, DisabledForeground
- -font, font, Font
- -foreground or -fg,
foreground, Foreground
- -highlightbackground,
highlightBackground, HighlightBackground
- -highlightcolor,
highlightColor, HighlightColor
- -highlightthickness,
highlightThickness, HighlightThickness
- -image, image,
Image
- -justify, justify,
Justify
- -padx, padX, Pad
- -pady, padY, Pad
- -relief, relief,
Relief
- -takefocus, takeFocus,
TakeFocus
- -text, text, Text
- -textvariable,
textVariable, Variable
- -underline, underline,
Underline
- -wraplength, wrapLength,
WrapLength
- Command-Line Name: -compound
- Database Name: compound
- Database Class: Compound
- Specifies whether the label should display both an image and
text, and if so, where the image should be placed relative to the
text. Valid values for this option are bottom,
center, left, none, right and
top. The default value is none, meaning that the
label will display either an image or text, depending on the values
of the -image and -bitmap options.
- Command-Line Name: -height
- Database Name: height
- Database Class: Height
- Specifies a desired height for the label. If an image or bitmap
is being displayed in the label then the value is in screen units
(i.e. any of the forms acceptable to Tk_GetPixels); for text it is in
lines of text. If this option isn't specified, the label's desired
height is computed from the size of the image or bitmap or text
being displayed in it.
- Command-Line Name: -state
- Database Name: state
- Database Class: State
- Specifies one of three states for the label: normal,
active, or disabled. In normal state the button is
displayed using the foreground and background
options. In active state the label is displayed using the
activeForeground and activeBackground options. In the
disabled state the disabledForeground and background
options determine how the button is displayed.
- Command-Line Name: -width
- Database Name: width
- Database Class: Width
- Specifies a desired width for the label. If an image or bitmap
is being displayed in the label then the value is in screen units
(i.e. any of the forms acceptable to Tk_GetPixels); for text it is in
characters. If this option isn't specified, the label's desired
width is computed from the size of the image or bitmap or text
being displayed in it.
The label command creates a new window (given by the
pathName argument) and makes it into a label widget.
Additional options, described above, may be specified on the
command line or in the option database to configure aspects of the
label such as its colors, font, text, and initial relief. The
label command returns its pathName argument. At the
time this command is invoked, there must not exist a window named
pathName, but pathName's parent must exist.
A label is a widget that displays a textual string, bitmap or
image. If text is displayed, it must all be in a single font, but
it can occupy multiple lines on the screen (if it contains newlines
or if wrapping occurs because of the wrapLength option) and
one of the characters may optionally be underlined using the
underline option. The label can be manipulated in a few
simple ways, such as changing its relief or text, using the
commands described below.
The label command creates a new Tcl command whose name is
pathName. This command may be used to invoke various
operations on the widget. It has the following general form:
pathName option ?arg arg ...?
Option and the args determine the exact behavior
of the command. The following commands are possible for label
widgets:
- pathName cget
option
- Returns the current value of the configuration option given by
option. Option may have any of the values accepted by
the label command.
- pathName configure ?option?
?value option value ...?
- Query or modify the configuration options of the widget. If no
option is specified, returns a list describing all of the
available options for pathName (see Tk_ConfigureInfo for information
on the format of this list). If option is specified with no
value, then the command returns a list describing the one
named option (this list will be identical to the corresponding
sublist of the value returned if no option is specified). If
one or more option-value pairs are specified, then the
command modifies the given widget option(s) to have the given
value(s); in this case the command returns an empty string.
Option may have any of the values accepted by the
label command.
When a new label is created, it has no default event bindings:
labels are not intended to be interactive.
label, widget
Copyright © 1990-1994 The Regents of the University of California.
Copyright © 1994-1996 Sun Microsystems, Inc.
Copyright © 1995-1997 Roger E. Critchlow Jr.


--- layout: post status: publish published: true title: PipelineTesting code now on GitHub author: display_name: Tomas Restrepo login: tomasr email<EMAIL_ADDRESS>url: http://winterdom.com/ author_login: tomasr author_email<EMAIL_ADDRESS>author_url: http://winterdom.com/ wordpress_id: 10 wordpress_url: http://winterdom.com/2008/07/pipelinetestingcodenowongithub date: '2008-07-13 07:51:54 +0000' date_gmt: '2008-07-13 07:51:54 +0000' categories: - BizTalk tags: [] comments: - id: 12 author: Nick Heppleston author_email<EMAIL_ADDRESS>author_url: http://www.modhul.com date: '2008-08-29 02:02:34 +0000' date_gmt: '2008-08-29 02:02:34 +0000' content: | Tomas, Just wondering why you decided to put it on GitHub and not Codeplex? Nick. ---
I just pushed all the source code for my BizTalk 2006 PipelineTesting library to GitHub. I'll keep this public repository updated whenever I make any changes to the library, so if you're interested in keeping track of the code or forking it, this should make it a lot easier.
You can find the clone URL for the new repository is: git://github.com/tomasr/pipelinetesting.git
Enjoy!


|
DocToXMLParser
0.32
|
Public Attributes | |
| JSEdit * | editor |
| JSDocLayout * | layout |
| JSHighlighter * | highlighter |
| SidebarWidget * | sidebar |
| bool | showLineNumbers |
| bool | textWrap |
| QColor | cursorColor |
| bool | bracketsMatching |
| QList< int > | matchPositions |
| QColor | bracketMatchColor |
| QList< int > | errorPositions |
| QColor | bracketErrorColor |
| bool | codeFolding: 1 |
Definition at line 605 of file jsedit.cpp.
| QColor JSEditPrivate::bracketErrorColor |
Definition at line 619 of file jsedit.cpp.
| QColor JSEditPrivate::bracketMatchColor |
Definition at line 617 of file jsedit.cpp.
| bool JSEditPrivate::bracketsMatching |
Definition at line 615 of file jsedit.cpp.
| bool JSEditPrivate::codeFolding |
Definition at line 620 of file jsedit.cpp.
| QColor JSEditPrivate::cursorColor |
Definition at line 614 of file jsedit.cpp.
| JSEdit* JSEditPrivate::editor |
Definition at line 608 of file jsedit.cpp.
| QList<int> JSEditPrivate::errorPositions |
Definition at line 618 of file jsedit.cpp.
| JSHighlighter* JSEditPrivate::highlighter |
Definition at line 610 of file jsedit.cpp.
| JSDocLayout* JSEditPrivate::layout |
Definition at line 609 of file jsedit.cpp.
| QList<int> JSEditPrivate::matchPositions |
Definition at line 616 of file jsedit.cpp.
| bool JSEditPrivate::showLineNumbers |
Definition at line 612 of file jsedit.cpp.
| SidebarWidget* JSEditPrivate::sidebar |
Definition at line 611 of file jsedit.cpp.
| bool JSEditPrivate::textWrap |
Definition at line 613 of file jsedit.cpp.