get_id()
Returns the drivers unique id. This can be used to identify the driver, or to select a specific driver instance.
| Static | No |
|---|---|
| Parameters | None |
| Returns | The drivers id string. |
| Example |
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The Auth package provides a standardized interface for authentication in Fuel. This allows our users to write their own drivers and easily integrate a new driver to work with old code by keeping the basic methods consistent.
This driver is the base class for all Auth group drivers. It is defined as an abstract class which contains all methods generic to all group drivers, and abstract method definitions for all methods any group driver MUST implement.
A group driver can load additional drivers that it depends on. Generally, these are ACL drivers. But your implementation could introduce and use custom driver types as well. To do so, add this structure to your driver class:
// autoload the Simpleacl acl driver when loading this group driver
protected $config = array(
'drivers' => array('acl' => array('Simpleacl'))
);
For ease of use, the member() method is exposed through the generic Auth static interface.
Using the static interface, you can do
// returns true if the current user is member of group 16.
$is_member = Auth::member(16);
Generic methods are defined in the group base driver, and are available to all Auth group drivers through extension. These methods provide functions to interact with groups, and to check for access.
The methods defined in the classes but not documented here are used internally, and should not be called directly.
Returns the drivers unique id. This can be used to identify the driver, or to select a specific driver instance.
| Static | No |
|---|---|
| Parameters | None |
| Returns | The drivers id string. |
| Example |
|
Sets a driver configuration value.
| Static | No | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Parameters |
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| Returns | void | |||||||||
| Example |
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Gets a driver configuration value.
| Static | No | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Parameters |
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| Returns | mixed | |||||||||
| Example |
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Every group driver you develop MUST provide all of these methods, and the MUST return the values documented here.
Checks if user is a member of the given group in either all loaded Group drivers or just those specified as the 2nd parameter.
| Static | Yes | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Parameters |
|
|||||||||
| Returns | bool, whether one of the (given) drivers had the current user registered as a member | |||||||||
| Example |
|
Get the display name of the given group name.
| Static | Yes | ||||||
|---|---|---|---|---|---|---|---|
| Parameters |
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| Returns | mixed, the retrieved group display name, or false if the given group does not exist. | ||||||
| Example |
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System: To which city will you be traveling? User: I want to go to Pittsburgh. <?xml version="1.0"?> <result xmlns="urn:ietf:params:xml:ns:mrcpv2" xmlns:ex="http://www.example.com/example" grammar="http://www.example.com/flight"> <interpretation confidence="0.6"> <instance> <ex:airline> <ex:to_city>Pittsburgh</ex:to_city> <ex:airline> <instance> <input mode="speech"> I want to go to Pittsburgh </input> </interpretation> <interpretation confidence="0.4" <instance> <ex:airline> <ex:to_city>Stockholm</ex:to_city> </ex:airline> </instance> <input>I want to go to Stockholm</input> </interpretation> </result>¶
System: What would you like? User: I would like 2 pizzas, one with pepperoni and cheese, one with sausage and a bottle of coke, to go.¶
This example includes an order object which in turn contains objects named "food_item", "drink_item", and "delivery_method". The representation assumes there are no ambiguities in the speech or natural language processing. Note that this representation also assumes some level of intra-sentential anaphora resolution, i.e., to resolve the two "one"s as "pizza".¶
<?xml version="1.0"?> <nl:result xmlns:nl="urn:ietf:params:xml:ns:mrcpv2" xmlns="http://www.example.com/example" grammar="http://www.example.com/foodorder"> <nl:interpretation confidence="1.0" > <nl:instance> <order> <food_item confidence="1.0"> <pizza> <ingredients confidence="1.0"> pepperoni </ingredients> <ingredients confidence="1.0"> cheese </ingredients> </pizza> <pizza> <ingredients>sausage</ingredients> </pizza> </food_item> <drink_item confidence="1.0"> <size>2-liter</size> </drink_item> <delivery_method>to go</delivery_method> </order> </nl:instance> <nl:input mode="speech">I would like 2 pizzas, one with pepperoni and cheese, one with sausage and a bottle of coke, to go. </nl:input> </nl:interpretation> </nl:result>¶
A combination of DTMF input and speech is represented using nested input elements. For example:¶
User: My pin is (dtmf 1 2 3 4)¶
<input> <input mode="speech" confidence ="1.0" timestamp-start="2000-04-03T0:00:00" timestamp-end="2000-04-03T0:00:01.5">My pin is </input> <input mode="dtmf" confidence ="1.0" timestamp-start="2000-04-03T0:00:01.5" timestamp-end="2000-04-03T0:00:02.0">1 2 3 4 </input> </input>¶
Note that grammars that recognize mixtures of speech and DTMF are not currently possible in SRGS; however, this representation might be needed for other applications of NLSML, and this mixture capability might be introduced in future versions of SRGS.¶
Natural language communication makes use of meta-dialog and meta-task utterances. This specification is flexible enough so that meta-utterances can be represented on an application-specific basis without requiring other standard markup.¶
Here are two examples of how meta-task and meta-dialog utterances might be represented.¶
System: What toppings do you want on your pizza?  Anaphoric references, which include pronouns and definite noun phrases that refer to something that was mentioned in the preceding linguistic context, and deictic references, which refer to something that is present in the non-linguistic context, present similar problems in that there may not be sufficient unambiguous linguistic context to determine what their exact role in the interpretation should be. In order to represent unresolved anaphora and deixis using this specification, one strategy would be for the developer to define a more surface-oriented representation that leaves the specific details of the interpretation of the reference open. (This assumes that a later component is responsible for actually resolving the reference).¶
Example: (ignoring the issue of representing the input from the pointing gesture.) System: What do you want to drink?  For example, a pizza order might consist of exactly one pizza, but a pizza might contain zero or more toppings. Since there is no standard way of marking this distinction directly in XML, in the current framework, the developer is free to adopt any conventions that would convey this information in the XML markup. One strategy would be for the developer to wrap the set of items in a grouping element, as in the following example.¶
<order> <pizza> <topping-group> <topping>mushrooms</topping> </topping-group> </pizza> <drink>coke</drink> </order>¶
In this example, the programmer can assume that there is supposed to be exactly one pizza and one drink in the order, but the fact that there is only one topping is an accident of this particular pizza order.¶
Note that the client controls both the grammar and the semantics to be returned upon grammar matches, so the user of MRCPv2 is fully empowered to cause results to be returned in NLSML in such a way that the interpretation is clear to that user.¶
Extensibility in NLSML is provided via result content flexibility, as described in the discussions of meta-utterances and anaphora. NLSML can easily be used in sophisticated systems to convey application-specific information that more basic systems would not make use of, for example, defining speech acts.¶
The following productions make use of the core rules defined in Section B.1 of RFC 5234 [RFC5234].¶
LWS = [*WSP CRLF] 1*WSP ; linear whitespace SWS = [LWS] ; sep whitespace UTF8-NONASCII = %xC0-DF 1UTF8-CONT / %xE0-EF 2UTF8-CONT / %xF0-F7 3UTF8-CONT / %xF8-FB 4UTF8-CONT / %xFC-FD 5UTF8-CONT UTF8-CONT = %x80-BF UTFCHAR = %x21-7E / UTF8-NONASCII param = *pchar quoted-string = SWS DQUOTE *(qdtext / quoted-pair ) DQUOTE qdtext = LWS / %x21 / %x23-5B / %x5D-7E / UTF8-NONASCII quoted-pair = "\" (%x00-09 / %x0B-0C / %x0E-7F) token = 1*(alphanum / "-" / "." / "!" / "%" / "*" / "_" / "+" / "`" / "'" / "~" ) reserved = ";" / "/" / "?" / ":" / "@" / "&" / "=" / "+" / "$" / "," mark = "-" / "_" / "." / "!" / "~" / "*" / "'" / "(" / ")" unreserved = alphanum / mark pchar = unreserved / escaped / ":" / "@" / "&" / "=" / "+" / "$" / "," alphanum = ALPHA / DIGIT BOOLEAN = "true" / "false" FLOAT = *DIGIT ["." *DIGIT] escaped = "%" HEXDIG HEXDIG fragment = *uric uri = [ absoluteURI / relativeURI ] [ "#" fragment ] absoluteURI = scheme ":" ( hier-part / opaque-part ) relativeURI = ( net-path / abs-path / rel-path ) [ "?" query ] hier-part = ( net-path / abs-path ) [ "?" query ] net-path = "//" authority [ abs-path ] abs-path = "/" path-segments rel-path = rel-segment [ abs-path ] rel-segment = 1*( unreserved / escaped / ";" / "@" / "&" / "=" / "+" / "$" / "," ) opaque-part = uric-no-slash *uric uric = reserved / unreserved / escaped uric-no-slash = unreserved / escaped / ";" / "?" / ":" / "@" / "&" / "=" / "+" / "$" / "," path-segments = segment *( "/" segment ) segment = *pchar *( ";" param ) scheme = ALPHA *( ALPHA / DIGIT / "+" / "-" / "." ) authority = srvr / reg-name srvr = [ [ userinfo "@" ] hostport ] reg-name = 1*( unreserved / escaped / "$" / "," / ";" / ":" / "@" / "&" / "=" / "+" ) query = *uric userinfo = ( user ) [ ":" password ] "@" user = 1*( unreserved / escaped / user-unreserved ) user-unreserved = "&" / "=" / "+" / "$" / "," / ";" / "?" / "/" password = *( unreserved / escaped / "&" / "=" / "+" / "$" / "," ) hostport = host [ ":" port ] host = hostname / IPv4address / IPv6reference hostname = *( domainlabel "." ) toplabel [ "." ] domainlabel = alphanum / alphanum *( alphanum / "-" ) alphanum toplabel = ALPHA / ALPHA *( alphanum / "-" ) alphanum IPv4address = 1*3DIGIT "." 1*3DIGIT "." 1*3DIGIT "." 1*3DIGIT IPv6reference = "[" IPv6address "]" IPv6address = hexpart [ ":" IPv4address ] hexpart = hexseq / hexseq "::" [ hexseq ] / "::" [ hexseq ] hexseq = hex4 *( ":" hex4) hex4 = 1*4HEXDIG port = 1*19DIGIT ; generic-message is the top-level rule generic-message = start-line message-header CRLF [ message-body ] message-body = *OCTET start-line = request-line / response-line / event-line request-line = mrcp-version SP message-length SP method-name SP request-id CRLF response-line = mrcp-version SP message-length SP request-id SP status-code SP request-state CRLF event-line = mrcp-version SP message-length SP event-name SP request-id SP request-state CRLF method-name = generic-method / synthesizer-method / recognizer-method / recorder-method / verifier-method generic-method = "SET-PARAMS" / "GET-PARAMS" request-state = "COMPLETE" / "IN-PROGRESS" / "PENDING" event-name = synthesizer-event / recognizer-event / recorder-event / verifier-event message-header = 1*(generic-header / resource-header / generic-field) generic-field = field-name ":" [ field-value ] field-name = token field-value = *LWS field-content *( CRLF 1*LWS field-content) field-content = <the OCTETs making up the field-value and consisting of either *TEXT or combinations of token, separators, and quoted-string> resource-header = synthesizer-header / recognizer-header / recorder-header / verifier-header generic-header = channel-identifier / accept / active-request-id-list / proxy-sync-id / accept-charset / content-type / content-id / content-base / content-encoding / content-location / content-length / fetch-timeout / cache-control / logging-tag / set-cookie / vendor-specific ; -- content-id is as defined in RFC 2392, RFC 2046 and RFC 5322 ; -- accept and accept-charset are as defined in RFC 2616 mrcp-version = "MRCP" "/" 1*2DIGIT "." 1*2DIGIT message-length = 1*19DIGIT request-id = 1*10DIGIT status-code = 3DIGIT channel-identifier = "Channel-Identifier" ":" channel-id CRLF channel-id = 1*alphanum "@" 1*alphanum active-request-id-list = "Active-Request-Id-List" ":" request-id *("," request-id) CRLF proxy-sync-id = "Proxy-Sync-Id" ":" 1*VCHAR CRLF content-base = "Content-Base" ":" absoluteURI CRLF content-length = "Content-Length" ":" 1*19DIGIT CRLF content-type = "Content-Type" ":" media-type-value CRLF media-type-value = type "/" subtype *( ";" parameter ) type = token subtype = token parameter = attribute "=" value attribute = token value = token / quoted-string content-encoding = "Content-Encoding" ":" *WSP content-coding *(*WSP "," *WSP content-coding *WSP ) CRLF content-coding = token content-location = "Content-Location" ":" ( absoluteURI / relativeURI ) CRLF cache-control = "Cache-Control" ":" [*WSP cache-directive *( *WSP "," *WSP cache-directive *WSP )] CRLF fetch-timeout = "Fetch-Timeout" ":" 1*19DIGIT CRLF cache-directive = "max-age" "=" delta-seconds / "max-stale" ["=" delta-seconds ] / "min-fresh" "=" delta-seconds delta-seconds = 1*19DIGIT logging-tag = "Logging-Tag" ":" 1*UTFCHAR CRLF vendor-specific = "Vendor-Specific-Parameters" ":" [vendor-specific-av-pair *(";" vendor-specific-av-pair)] CRLF vendor-specific-av-pair = vendor-av-pair-name "=" value vendor-av-pair-name = 1*UTFCHAR set-cookie = "Set-Cookie:" SP set-cookie-string set-cookie-string = cookie-pair *( ";" SP cookie-av ) cookie-pair = cookie-name "=" cookie-value cookie-name = token cookie-value = *cookie-octet / ( DQUOTE *cookie-octet DQUOTE ) cookie-octet = %x21 / %x23-2B / %x2D-3A / %x3C-5B / %x5D-7E token = <token, defined in [RFC2616], Section 2.2> cookie-av = expires-av / max-age-av / domain-av / path-av / secure-av / httponly-av / extension-av / age-av expires-av = "Expires=" sane-cookie-date sane-cookie-date = <rfc1123-date, from [RFC2616], Section 3.3.1> max-age-av = "Max-Age=" non-zero-digit *DIGIT non-zero-digit = %x31-39 domain-av = "Domain=" domain-value domain-value = <subdomain> path-av = "Path=" path-value path-value = <any CHAR except CTLs or ";"> secure-av = "Secure" httponly-av = "HttpOnly" extension-av = <any CHAR except CTLs or ";"> age-av = "Age=" delta-seconds ; Synthesizer ABNF synthesizer-method = "SPEAK" / "STOP" / "PAUSE" / "RESUME" / "BARGE-IN-OCCURRED" / "CONTROL" / "DEFINE-LEXICON" synthesizer-event = "SPEECH-MARKER" / "SPEAK-COMPLETE" synthesizer-header = jump-size / kill-on-barge-in / speaker-profile / completion-cause / completion-reason / voice-parameter / prosody-parameter / speech-marker / speech-language / fetch-hint / audio-fetch-hint / failed-uri / failed-uri-cause / speak-restart / speak-length / load-lexicon / lexicon-search-order jump-size = "Jump-Size" ":" speech-length-value CRLF speech-length-value = numeric-speech-length / text-speech-length text-speech-length = 1*UTFCHAR SP "Tag" numeric-speech-length = ("+" / "-") positive-speech-length positive-speech-length = 1*19DIGIT SP numeric-speech-unit numeric-speech-unit = "Second" / "Word" / "Sentence" / "Paragraph" kill-on-barge-in = "Kill-On-Barge-In" ":" BOOLEAN CRLF speaker-profile = "Speaker-Profile" ":" uri CRLF completion-cause = "Completion-Cause" ":" cause-code SP cause-name CRLF cause-code = 3DIGIT cause-name = *VCHAR completion-reason = "Completion-Reason" ":" quoted-string CRLF voice-parameter = voice-gender / voice-age / voice-variant / voice-name voice-gender = "Voice-Gender:" voice-gender-value CRLF voice-gender-value = "male" / "female" / "neutral" voice-age = "Voice-Age:" 1*3DIGIT CRLF voice-variant = "Voice-Variant:" 1*19DIGIT CRLF voice-name = "Voice-Name:" 1*UTFCHAR *(1*WSP 1*UTFCHAR) CRLF prosody-parameter = "Prosody-" prosody-param-name ":" prosody-param-value CRLF prosody-param-name = 1*VCHAR prosody-param-value = 1*VCHAR timestamp = "timestamp" "=" time-stamp-value time-stamp-value = 1*20DIGIT speech-marker = "Speech-Marker" ":" timestamp [";" 1*(UTFCHAR / %x20)] CRLF speech-language = "Speech-Language" ":" 1*VCHAR CRLF fetch-hint = "Fetch-Hint" ":" ("prefetch" / "safe") CRLF audio-fetch-hint = "Audio-Fetch-Hint" ":" ("prefetch" / "safe" / "stream") CRLF failed-uri = "Failed-URI" ":" absoluteURI CRLF failed-uri-cause = "Failed-URI-Cause" ":" 1*UTFCHAR CRLF speak-restart = "Speak-Restart" ":" BOOLEAN CRLF speak-length = "Speak-Length" ":" positive-length-value CRLF positive-length-value = positive-speech-length / text-speech-length load-lexicon = "Load-Lexicon" ":" BOOLEAN CRLF lexicon-search-order = "Lexicon-Search-Order" ":" "<" absoluteURI ">" *(" " "<" absoluteURI ">") CRLF ; Recognizer ABNF recognizer-method = recog-only-method / enrollment-method recog-only-method = "DEFINE-GRAMMAR" / "RECOGNIZE" / "INTERPRET" / "GET-RESULT" / "START-INPUT-TIMERS" / "STOP" enrollment-method = "START-PHRASE-ENROLLMENT" / "ENROLLMENT-ROLLBACK" / "END-PHRASE-ENROLLMENT" / "MODIFY-PHRASE" / "DELETE-PHRASE" recognizer-event = "START-OF-INPUT" / "RECOGNITION-COMPLETE" / "INTERPRETATION-COMPLETE" recognizer-header = recog-only-header / enrollment-header recog-only-header = confidence-threshold / sensitivity-level / speed-vs-accuracy / n-best-list-length / input-type / no-input-timeout / recognition-timeout / waveform-uri / input-waveform-uri / completion-cause / completion-reason / recognizer-context-block / start-input-timers / speech-complete-timeout / speech-incomplete-timeout / dtmf-interdigit-timeout / dtmf-term-timeout / dtmf-term-char / failed-uri / failed-uri-cause / save-waveform / media-type / new-audio-channel / speech-language / ver-buffer-utterance / recognition-mode / cancel-if-queue / hotword-max-duration / hotword-min-duration / interpret-text / dtmf-buffer-time / clear-dtmf-buffer / early-no-match enrollment-header = num-min-consistent-pronunciations / consistency-threshold / clash-threshold / personal-grammar-uri / enroll-utterance / phrase-id / phrase-nl / weight / save-best-waveform / new-phrase-id / confusable-phrases-uri / abort-phrase-enrollment confidence-threshold = "Confidence-Threshold" ":" FLOAT CRLF sensitivity-level = "Sensitivity-Level" ":" FLOAT CRLF speed-vs-accuracy = "Speed-Vs-Accuracy" ":" FLOAT CRLF n-best-list-length = "N-Best-List-Length" ":" 1*19DIGIT CRLF input-type = "Input-Type" ":" inputs CRLF inputs = "speech" / "dtmf" no-input-timeout = "No-Input-Timeout" ":" 1*19DIGIT CRLF recognition-timeout = "Recognition-Timeout" ":" 1*19DIGIT CRLF waveform-uri = "Waveform-URI" ":" ["<" uri ">" ";" "size" "=" 1*19DIGIT ";" "duration" "=" 1*19DIGIT] CRLF recognizer-context-block = "Recognizer-Context-Block" ":" [1*VCHAR] CRLF start-input-timers = "Start-Input-Timers" ":" BOOLEAN CRLF speech-complete-timeout = "Speech-Complete-Timeout" ":" 1*19DIGIT CRLF speech-incomplete-timeout = "Speech-Incomplete-Timeout" ":" 1*19DIGIT CRLF dtmf-interdigit-timeout = "DTMF-Interdigit-Timeout" ":" 1*19DIGIT CRLF dtmf-term-timeout = "DTMF-Term-Timeout" ":" 1*19DIGIT CRLF dtmf-term-char = "DTMF-Term-Char" ":" VCHAR CRLF save-waveform = "Save-Waveform" ":" BOOLEAN CRLF new-audio-channel = "New-Audio-Channel" ":" BOOLEAN CRLF recognition-mode = "Recognition-Mode" ":" "normal" / "hotword" CRLF cancel-if-queue = "Cancel-If-Queue" ":" BOOLEAN CRLF hotword-max-duration = "Hotword-Max-Duration" ":" 1*19DIGIT CRLF hotword-min-duration = "Hotword-Min-Duration" ":" 1*19DIGIT CRLF interpret-text = "Interpret-Text" ":" 1*VCHAR CRLF dtmf-buffer-time = "DTMF-Buffer-Time" ":" 1*19DIGIT CRLF clear-dtmf-buffer = "Clear-DTMF-Buffer" ":" BOOLEAN CRLF early-no-match = "Early-No-Match" ":" BOOLEAN CRLF num-min-consistent-pronunciations = "Num-Min-Consistent-Pronunciations" ":" 1*19DIGIT CRLF consistency-threshold = "Consistency-Threshold" ":" FLOAT CRLF clash-threshold = "Clash-Threshold" ":" FLOAT CRLF personal-grammar-uri = "Personal-Grammar-URI" ":" uri CRLF enroll-utterance = "Enroll-Utterance" ":" BOOLEAN CRLF phrase-id = "Phrase-ID" ":" 1*VCHAR CRLF phrase-nl = "Phrase-NL" ":" 1*UTFCHAR CRLF weight = "Weight" ":" FLOAT CRLF save-best-waveform = "Save-Best-Waveform" ":" BOOLEAN CRLF new-phrase-id = "New-Phrase-ID" ":" 1*VCHAR CRLF confusable-phrases-uri = "Confusable-Phrases-URI" ":" uri CRLF abort-phrase-enrollment = "Abort-Phrase-Enrollment" ":" BOOLEAN CRLF ; Recorder ABNF recorder-method = "RECORD" / "STOP" / "START-INPUT-TIMERS" recorder-event = "START-OF-INPUT" / "RECORD-COMPLETE" recorder-header = sensitivity-level / no-input-timeout / completion-cause / completion-reason / failed-uri / failed-uri-cause / record-uri / media-type / max-time / trim-length / final-silence / capture-on-speech / ver-buffer-utterance / start-input-timers / new-audio-channel record-uri = "Record-URI" ":" [ "<" uri ">" ";" "size" "=" 1*19DIGIT ";" "duration" "=" 1*19DIGIT] CRLF media-type = "Media-Type" ":" media-type-value CRLF max-time = "Max-Time" ":" 1*19DIGIT CRLF trim-length = "Trim-Length" ":" 1*19DIGIT CRLF final-silence = "Final-Silence" ":" 1*19DIGIT CRLF capture-on-speech = "Capture-On-Speech " ":" BOOLEAN CRLF ; Verifier ABNF verifier-method = "START-SESSION" / "END-SESSION" / "QUERY-VOICEPRINT" / "DELETE-VOICEPRINT" / "VERIFY" / "VERIFY-FROM-BUFFER" / "VERIFY-ROLLBACK" / "STOP" / "CLEAR-BUFFER" / "START-INPUT-TIMERS" / "GET-INTERMEDIATE-RESULT" verifier-event = "VERIFICATION-COMPLETE" / "START-OF-INPUT" verifier-header = repository-uri / voiceprint-identifier / verification-mode / adapt-model / abort-model / min-verification-score / num-min-verification-phrases / num-max-verification-phrases / no-input-timeout / save-waveform / media-type / waveform-uri / voiceprint-exists / ver-buffer-utterance / input-waveform-uri / completion-cause / completion-reason / speech-complete-timeout / new-audio-channel / abort-verification / start-input-timers / input-type repository-uri = "Repository-URI" ":" uri CRLF voiceprint-identifier = "Voiceprint-Identifier" ":" vid *[";" vid] CRLF vid = 1*VCHAR ["." 1*VCHAR] verification-mode = "Verification-Mode" ":" verification-mode-string verification-mode-string = "train" / "verify" adapt-model = "Adapt-Model" ":" BOOLEAN CRLF abort-model = "Abort-Model" ":" BOOLEAN CRLF min-verification-score = "Min-Verification-Score" ":" [ %x2D ] FLOAT CRLF num-min-verification-phrases = "Num-Min-Verification-Phrases" ":" 1*19DIGIT CRLF num-max-verification-phrases = "Num-Max-Verification-Phrases" ":" 1*19DIGIT CRLF voiceprint-exists = "Voiceprint-Exists" ":" BOOLEAN CRLF ver-buffer-utterance = "Ver-Buffer-Utterance" ":" BOOLEAN CRLF input-waveform-uri = "Input-Waveform-URI" ":" uri CRLF abort-verification = "Abort-Verification " ":" BOOLEAN CRLF¶
The following productions add a new SDP session-level attribute. See Section 13.7.2, Paragraph 7.¶
cmid-attribute = "a=cmid:" identification-tag identification-tag = token¶
<?xml version="1.0" encoding="UTF-8"?> <xs:schema xmlns:xs="http://www.w3.org/2001/XMLSchema" targetNamespace="urn:ietf:params:xml:ns:mrcpv2" xmlns="urn:ietf:params:xml:ns:mrcpv2" elementFormDefault="qualified" attributeFormDefault="unqualified" > <xs:annotation> <xs:documentation> Natural Language Semantic Markup Schema </xs:documentation> </xs:annotation> <xs:include schemaLocation="enrollment-schema.rng"/> <xs:include schemaLocation="verification-schema.rng"/> <xs:element name="result"> <xs:complexType> <xs:sequence> <xs:element name="interpretation" maxOccurs="unbounded"> <xs:complexType> <xs:sequence> <xs:element name="instance"> <xs:complexType mixed="true"> <xs:sequence minOccurs="0"> <xs:any namespace="##other" processContents="lax"/> </xs:sequence> </xs:complexType> </xs:element> <xs:element name="input" minOccurs="0"> <xs:complexType mixed="true"> <xs:choice> <xs:element name="noinput" minOccurs="0"/> <xs:element name="nomatch" minOccurs="0"/> <xs:element name="input" minOccurs="0"/> </xs:choice> <xs:attribute name="mode" type="xs:string" default="speech"/> <xs:attribute name="confidence" type="confidenceinfo" default="1.0"/> <xs:attribute name="timestamp-start" type="xs:string"/> <xs:attribute name="timestamp-end" type="xs:string"/> </xs:complexType> </xs:element> </xs:sequence> <xs:attribute name="confidence" type="confidenceinfo" default="1.0"/> <xs:attribute name="grammar" type="xs:anyURI" use="optional"/> </xs:complexType> </xs:element> <xs:element name="enrollment-result" type="enrollment-contents"/> <xs:element name="verification-result" type="verification-contents"/> </xs:sequence> <xs:attribute name="grammar" type="xs:anyURI" use="optional"/> </xs:complexType> </xs:element> <xs:simpleType name="confidenceinfo"> <xs:restriction base="xs:float"> <xs:minInclusive value="0.0"/> <xs:maxInclusive value="1.0"/> </xs:restriction> </xs:simpleType> </xs:schema>¶
<?xml version="1.0" encoding="UTF-8"?> <!-- MRCP Enrollment Schema (See http://www.oasis-open.org/committees/relax-ng/spec.html) --> <grammar datatypeLibrary="http://www.w3.org/2001/XMLSchema-datatypes" ns="urn:ietf:params:xml:ns:mrcpv2" xmlns="http://relaxng.org/ns/structure/1.0"> <start> <element name="enrollment-result"> <ref name="enrollment-content"/> </element> </start> <define name="enrollment-content"> <interleave> <element name="num-clashes"> <data type="nonNegativeInteger"/> </element> <element name="num-good-repetitions"> <data type="nonNegativeInteger"/> </element> <element name="num-repetitions-still-needed"> <data type="nonNegativeInteger"/> </element> <element name="consistency-status"> <choice> <value>consistent</value> <value>inconsistent</value> <value>undecided</value> </choice> </element> <optional> <element name="clash-phrase-ids"> <oneOrMore> <element name="item"> <data type="token"/> </element> </oneOrMore> </element> </optional> <optional> <element name="transcriptions"> <oneOrMore> <element name="item"> <text/> </element> </oneOrMore> </element> </optional> <optional> <element name="confusable-phrases"> <oneOrMore> <element name="item"> <text/> </element> </oneOrMore> </element> </optional> </interleave> </define> </grammar>¶
<?xml version="1.0" encoding="UTF-8"?> <!-- MRCP Verification Results Schema (See http://www.oasis-open.org/committees/relax-ng/spec.html) --> <grammar datatypeLibrary="http://www.w3.org/2001/XMLSchema-datatypes" ns="urn:ietf:params:xml:ns:mrcpv2" xmlns="http://relaxng.org/ns/structure/1.0"> <start> <element name="verification-result"> <ref name="verification-contents"/> </element> </start> <define name="verification-contents"> <element name="voiceprint"> <ref name="firstVoiceprintContent"/> </element> <zeroOrMore> <element name="voiceprint"> <ref name="restVoiceprintContent"/> </element> </zeroOrMore> </define> <define name="firstVoiceprintContent"> <attribute name="id"> <data type="string"/> </attribute> <interleave> <optional> <element name="adapted"> <data type="boolean"/> </element> </optional> <optional> <element name="needmoredata"> <ref name="needmoredataContent"/> </element> </optional> <optional> <element name="incremental"> <ref name="firstCommonContent"/> </element> </optional> <element name="cumulative"> <ref name="firstCommonContent"/> </element> </interleave> </define> <define name="restVoiceprintContent"> <attribute name="id"> <data type="string"/> </attribute> <element name="cumulative"> <ref name="restCommonContent"/> </element> </define> <define name="firstCommonContent"> <interleave> <element name="decision"> <ref name="decisionContent"/> </element> <optional> <element name="utterance-length"> <ref name="utterance-lengthContent"/> </element> </optional> <optional> <element name="device"> <ref name="deviceContent"/> </element> </optional> <optional> <element name="gender"> <ref name="genderContent"/> </element> </optional> <zeroOrMore> <element name="verification-score"> <ref name="verification-scoreContent"/> </element> </zeroOrMore> </interleave> </define> <define name="restCommonContent"> <interleave> <optional> <element name="decision"> <ref name="decisionContent"/> </element> </optional> <optional> <element name="device"> <ref name="deviceContent"/> </element> </optional> <optional> <element name="gender"> <ref name="genderContent"/> </element> </optional> <zeroOrMore> <element name="verification-score"> <ref name="verification-scoreContent"/> </element> </zeroOrMore> </interleave> </define> <define name="decisionContent"> <choice> <value>accepted</value> <value>rejected</value> <value>undecided</value> </choice> </define> <define name="needmoredataContent"> <data type="boolean"/> </define> <define name="utterance-lengthContent"> <data type="nonNegativeInteger"/> </define> <define name="deviceContent"> <choice> <value>cellular-phone</value> <value>electret-phone</value> <value>carbon-button-phone</value> <value>unknown</value> </choice> </define> <define name="genderContent"> <choice> <value>male</value> <value>female</value> <value>unknown</value> </choice> </define> <define name="verification-scoreContent"> <data type="float"> <param name="minInclusive">-1</param> <param name="maxInclusive">1</param> </data> </define> </grammar>¶
Pierre Forgues Nuance Communications Ltd. 1500 University Street Suite 935 Montreal, Quebec Canada H3A 3S7 EMail<EMAIL_ADDRESS>Charles Galles Intervoice, Inc. 17811 Waterview Parkway Dallas, Texas 75252 USA EMail<EMAIL_ADDRESS>Klaus Reifenrath Scansoft, Inc Guldensporenpark 32 Building D 9820 Merelbeke Belgium EMail<EMAIL_ADDRESS>Andre Gillet (Nuance Communications) Andrew Hunt (ScanSoft) Andrew Wahbe (Genesys) Aaron Kneiss (ScanSoft) Brian Eberman (ScanSoft) Corey Stohs (Cisco Systems, Inc.) Dave Burke (VoxPilot) Jeff Kusnitz (IBM Corp) Ganesh N. Ramaswamy (IBM Corp) Klaus Reifenrath (ScanSoft) Kristian Finlator (ScanSoft) Magnus Westerlund (Ericsson) Martin Dragomirecky (Cisco Systems, Inc.) Paolo Baggia (Loquendo) Peter Monaco (Nuance Communications) Pierre Forgues (Nuance Communications) Ran Zilca (IBM Corp) Suresh Kaliannan (Cisco Systems, Inc.) Skip Cave (Intervoice, Inc.) Thomas Gal (LumenVox)¶
The chairs of the SPEECHSC work group are Eric Burger (Georgetown University) and Dave Oran (Cisco Systems, Inc.).¶
Many thanks go in particular to Robert Sparks, Alex Agranovsky, and Henry Phan, who were there at the end to dot all the i's and cross all the t's.¶


My website
In my website I will talk about myself and things I like.
My favorite animals are albino crocodiles, dogs, cats, red pandas, and ducks
In my blog I will talk about myself and things I like.
My favorite animals are albino crocodiles, dogs, cats, red pandas, and ducks


Level of Detail - show meshes with more or less geometry based on distance
from the camera.
Every level is associated with an object, and rendering can be switched
between them at the distances specified. Typically you would create, say,
three meshes, one for far away (low detail), one for mid range (medium
detail) and one for close up (high detail).
const lod = new THREE.LOD();
//Create spheres with 3 levels of detail and create new LOD levels for them
for( let i = 0; i < 3; i++ ) {
const geometry = new THREE.IcosahedronGeometry( 10, 3 - i )
const mesh = new THREE.Mesh( geometry, material );
lod.addLevel( mesh, i * 75 );
}
scene.add( lod );
[example:webgl_lod webgl / lod ]
Creates a new [name].
See the base [page:Object3D] class for common properties.
Whether the LOD object is updated automatically by the renderer per frame or not. If set to false, you have to call [page:LOD.update]() in the render loop by yourself. Default is true.
Read-only flag to check if a given object is of type [name].
An array of [page:Object level] objects
Each level is an object with the following properties:
[page:Object3D object] - The [page:Object3D] to display at this level.
[page:Float distance] - The distance at which to display this level of
detail.
[page:Float hysteresis] - Threshold used to avoid flickering at LOD
boundaries, as a fraction of distance.
See the base [page:Object3D] class for common methods.
[page:Object3D object] - The [page:Object3D] to display at this level.
[page:Float distance] - The distance at which to display this level of
detail. Default `0.0`.
[page:Float hysteresis] - Threshold used to avoid flickering at LOD
boundaries, as a fraction of distance. Default `0.0`.
Adds a mesh that will display at a certain distance and greater. Typically
the further away the distance, the lower the detail on the mesh.
Returns a clone of this LOD object with its associated levels.
Get the currently active LOD level. As index of the levels array.
Get a reference to the first [page:Object3D] (mesh) that is greater than [page:Float distance].
Get intersections between a casted [page:Ray] and this LOD. [page:Raycaster.intersectObject] will call this method.
Create a JSON structure with details of this LOD object.
Set the visibility of each [page:levels level]'s [page:Object3D object] based on distance from the [page:Camera camera].
[link:https://github.com/mrdoob/three.js/blob/master/src/[path].js src/[path].js]


ATTN:(HANDLE THIS INFORMATION SECRETLY) Dear, I hereby contact you personally concerning the situation in my bank. In order to transfer out {us$34,000,000} Thirty four million us dollars, I have the courage to look for a reliable and honest person who will be capable for this important business believing that you will never let me down either now or in future. I am Dr Paul Mbizala K., the Regional computing auditor of (STANDARD BANK OF SOUTH AFRICA) JOHANNESBURG BRANCH (SBSA). There is an account opened in this bank in 1985 and since 1991 nobody has operated on this account again. After going through some old files in the records I discovered that if I do not remit this money out urgently.it will be forfeited for nothing according to South Africa laws and act of 1993,the money will be revert this country government treasury after 15 years if there is no valid claim. I need a foreign partner that will present as a relative to this late man. I concluded to transfer this money overseas for proper investment that will benefit me. The owner of this account is Mr.Bremen K.Schroeder, a foreigner, and a Miner at Kruger Gold Co. a geologist by profession and he died since 1991. No other person knows about this account or any thing concerning it,the account has no other beneficiary and my investigation proved to me as well that this company does not know anything about this account and the amount involved is us$34,000,000 Thirty Four million dollars. I am only contacting you as a foreigner because this money can not be approved to a local bank here, but can only be approved to any foreign account because the money is in US dollars and the former owner of the account is Mr.Bremen K.Schroeder, who is a foreigner too. I know that this message will come to you as a surprise as we dont know ourselves before, we will sign agreement, but be sure that it is real and a fund. I need a truthful person in this business because I don't want to make mistake and I need your strong assurance and trust. At the conclusion of this business, you will be given 50% of the total amount, 50% will be for me and my family. I look forward to your earliest reply through my email address. God Bless You. Yours truly, Dr Mbizala Paul. STANDARD BANK OF SOUTH AFRICA (You can as well contact me through my alternative email address<EMAIL_ADDRESS>---------------------------------------- Upgrade your account today for increased storage; mail forwarding or POP enabled e-mail with automatic virus scanning. Visit our member benefits page at https://members.canada.com/benefits.aspx for more information.


Faro lies in the north west corner of Ria Formosa, which is on Portugal's southern coast. The city has much interesting and ancient architecture. Particularly attractive, is the old part of the city, still surrounded by its Roman walls.
Olhao is in the north east of the Ria. It is a major port and the largest fishing port in the Algarve. It is full of character with Moorish-style architecture.
Position 36°57.8'N, 07°52.2'W (entrance).
When approaching Faro from the West, be aware that there are tuna nets laid to the south of Faro. See report adjacent for further details.
The office of the Capitania (where the Policia Maritima are often found) overlooks the north end of the basin
There is good shelter once inside among the sand dunes, but the entrance is narrow and approaching at night or in strong winds is not advisable.
Faro
The winding channel is 4.5nm long, with a depth of about 4m.
There is a marina here but it is for small local boats only. Off the town, in sheltered water, there are moorings which may be available or anchor near channel buoy 23.
Land either at the Doca de Recreio, passing under the railway bridge (about 1m clearance at high water) or at one of the three jetties outside. It is then just a 15 minute walk into the town.
If landing in the basin note that the pontoons are closed off by individual security gates and that all east side is reserved for fishermen.
The office of the Capitania (where the Policia Maritima are often found) overlooks the north end of the basin, sharing premises with a small maritime museum.
Olhao
The channel leading to the marina here is 5nm long, with a least depth of just over 2m. Approaching on a rising tide is advisable.
The marina is accessed via a narrow channel in the west bank. The entrance to it is at the far western end of the breakwater. It rarely has room for visitors.
Anchorages
Culatra Island - This one is at the entrance to the channel leading to Faro and Olhao and is on the inside of a sandy island with beautiful beaches. The holding is generally good in silt/mud in the area north of the fishing harbour but other areas had thick sea grass or old cables. The small village has a few cottages, a cafe and a small hotel. There is a year-round ferry service to Faro.
Faro
Anchor SW of the Doca de Recreio in 3m. This is under the flight path of the airport, which is one of the busiest during the day (no flights at night).
Olhao - The anchorage is in the channel leading to the commercial port, but may not be permitted due to dredging operations.
See this website for an interesting report on Ria Formosa.
Last updated August 2015.


Welcome
The biggest hope is to help people.
Join our community to get helpful resources regularly.
There are multiple regional resources in here.
Notifications and Updates
Join our Covid Resources Community to help virtually!
We are small but we can help people.
The result of our resources can save a life.
The biggest hope is to help people.
Join our community to get helpful resources regularly.
There are multiple regional resources in here.
Install Covid Resources on your home screen, and access it just like a regular app. It really is that simple!
Install Covid Resources on your home screen, and access it just like a regular app. Open your Chrome menu and tap "Add to Home Screen".
Maybe laterNo internet connection detected
You are back online


You know how it goes: when you discover a cool “something” somewhere, you immediately begin to try to apply it to everything else.
My post on smarter task entry with OmniFocus got me thinking: where else might this logic – wherein I use an application’s localized AppleScript methods if it’s already open, but if not, use another mechanism (like email) – work?
Out of the blue, it hit me: Evernote. I already use Hazel to automatically file documents into Evernote, and although it works, the same problem applies: the methods require the Evernote already be running. Like OmniFocus, I don’t always have it running…and that presents a problem: Evernote is a beast of an application. It isn’t uncommon for it to take anywhere from 15-30 seconds to launch and become usable. Combined with the fact that it likes to become the dominant application when launched, Evernote chokes what should be a fairly painless and automated workflow.
So, I began to form a plan: rework all of my Hazel-based Evernote workflows to use the same logic that I’d come up with for OmniFocus.
Time to get to work.
TL;DR
Use a smart Applescript to send files to Evernote, regardless of whether or not it’s open.
A New Element: Mutt
One fundamental difference exists between my OmniFocus workflow and this new Evernote workflow: the type of content. The OmniFocus workflow uses text and it’s not hard to use mail
to send text. The Evernote workflow, however, deals in rich media types: images, videos, PDFs, etc.
For many reasons, using mail
to send attachments isn’t easy (especially on OS X). Therefore, I’m bringing something else into the picture: Mutt. Mutt is a terminal-based email client that, among other things, allows for easy background sending of email; most important of all, its -a
flag allows for painless sending of attachments.
The easiest way to install Mutt on OS X is via Homebrew; simply run:
$ brew install mutt
Alternatively, you can build mutt yourself from the releases page.
Mavericks Tags
Hazel has one glaringly missing feature (to me): there’s no officially supported way to send dynamic values from Hazel to AppleScript. In practice, this has meant dozens of slightly-different-but-mostly-the-same rules.
OS X 10.9 created a roundabout fix to this when it introduced the long-anticipated concept of tags:
OS X Mavericks includes Tags – a powerful new way to organize your files. Whether your files are on your Mac or in iCloud, you can find them with just one click
Tags aren’t a perfect way for Hazel to pass variable information into an AppleScript, but for our purposes here, they’ll do the trick.
Where does that leave pre-10.9 users? Without tags, you’ll be forced to make several AppleScripts, instead of just using the same one. It’s not the end of the world, but it’s worth knowing.
The Base AppleScript
Each Hazel workflow makes use of the same base AppleScript1:
There’s a lot going on here, but it follows a simple breakdown:
- If Evernote is running, use its AppleScript methods to create notes; otherwise, use Mutt to send an email to an Evernote email address to create the note.
- In either case, use any tags that exist on the file as tags on the Evernote note.
Some Examples
Let’s take a look at some of my earlier Hazel rules and how they change in this new setup.
Save To Evernote
This action – which monitors a single directory and places any file found in it into Evernote – doesn’t change much, but it does make use of the new base AppleScript.
Old:
New:
The primary changes here are twofold:
- I got rid of the action that renamed the file (because, frankly, I didn’t see the point in renaming generic files).
- I use my base
Save File to Evernote.scpt
in place of the embedded script used before.
Comcast Statement
The changes to this action – which monitors my ~/Downloads
folder and archives any Comcast statements in Evernote – showcase the first example of 10.9 tags coming into play
Old:
New:
Here, too, are two changes:
- After the file is renamed, I add two tags to it.
- Then, I use my generic AppleScript.
In either case – whether using Evernote’s AppleScript methods or my Evernote email address – the tags are added to the newly created note.
- Special thanks to Justin Lancy of Veritrope for helping me figure out how to use 10.9 tags in AppleScript. ↩


Error while connecting to your DB
Please create a DB and use the right credentials in your new CuDb() call.
If you are running the _sample - pages:
Just create a db on localhost with
- Username
- culibrary
- Password
- culibrary
- Server
- localhost
- DBName
- culibrary


Chris McDonald and Matthew Heinsen Egan
Communicating using Program Traces
Supported by the growth of embedded devices, the IoT, and modern standardization, C remains an important language for undergraduate students. However, when presented to relatively inexperienced programmers, its very limited runtime support is a source of frustration for both students and educators, alike.
SeeC is a novice-focused tool for the C programming language that displays and records the execution of programs, detects runtime errors, and enables students to review their programs' data and execution history. Students can deterministically replay a program, and reason backwards from a runtime error to determine its true cause. The approach can lead to students' reduced frustration and greater understanding of program behaviour.
This presentation provides a brief overview of SeeC and a discussion on how its program traces provide an opportunity for students to communicate their questions and misunderstandings with educators, and for educators to provide examples and debugging challenges to students.


{% extends 'layout-bsa.html' %} {% block pageTitle %} What was the decision of your asylum application? - LIS training - NHSBSA {% endblock %} {% block outerContent %} {% endblock %} {% block content %}


MART
HOME
ABOUT US
PAGE
SHOP
BLOG
CONTACT US
AFFORDABLE PARIS TOURS
CITY TOURS / TOUR TICKETS / TOUR GUIDES
NEW COLLECTION
BLUE TSHIRT
$26
ADD TO CARD
WOMEN SHIRT
$31
ADD TO CARD
YELLOW TSHIRT
$21
ADD TO CARD
COOL LINGERIE
$56
ADD TO CARD


Play MIDI!
Play Audio!
A demo webpage based on machine learning algorithm to automatically transcript music pieces. The player can upload and test on their music.
Webpage Made By : ITung Chiang
Choose a file!


FLETCH LIVES A film review by Randy Parker Copyright 1996 Randy Parker
(Review written in 1989)
In FLETCH LIVES, everybody's favorite investigative reporter is back in action, but unfortunately he's neither better than ever nor new and improved. FLETCH LIVES is a disappointing sequel to the 1985 hit comedy FLETCH, which was a surprisingly engaging Chevy Chase vehicle. With Chase returning in the role of Fletch and with Michael Ritchie serving once again as director, I had hoped that FLETCH LIVES would be better than the average sequel. I should have known better. FLETCH LIVES pales in comparison to the original; someone should have put this sequel out of its misery.
After his dismal outing in so-called FUNNY FARM, you'd think that for the sake of his career, Chase would have learned to avoid the country-side. But no, in FLETCH LIVES he inherits a mansion in Louisiana, which gives him an excuse to quit his crummy job at the paper, pack his chest, and move to the mid-west. In Louisiana, Fletch immediately becomes embroiled in an elaborate and tiresome plot involving the usual mayhem: a murder, a televangelist, a beautiful blonde, a big brute, and a dastardly villain.
Although FLETCH LIVES is genuinely funny at times, more often it flounders and flails. None of the blame, however, falls on Chase, who does his best to evoke laughs in the face of a flat screenplay. Chase gives his character that biting sarcasm and quick wit that made the first film so much fun. And, as in the original, Chase's disguises are simply amazing and his impersonations brilliant. When Chase passes himself off as a faith healer, for example, he's completely unrecognizable, and the scene proves to be one of the few in the movie to offer some inspired humor.
Unfortunately, Chase's efforts are sabotaged by the film's incredibly uneven script and unnecessarily complicated story line. While some of the jokes and gags are effective, most of them fizzle and cater to the lowest common denominator. In fact, FLETCH LIVES hits rock bottom when it commits the unforgivable sin of resorting to nose-picking jokes. FLETCH LIVES also suffers from excess plot; the uncompelling story line should have been merely an excuse for Fletch's irreverent impersonations and wisecracks. But the film devotes so much time and energy to its uncompelling plot that the comic moments often get lost in the shuffle.
Ultimately, there's very little to recommend in FLETCH LIVES as the movie fails to give us either sympathetic characters or sufficient laughs.
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


 Please take a moment to digest the info below.
I don't know if this can be called a skill or not, but I really enjoy experiencing all of the flavors of beer which exist in the world. Yeah, I think that can be a skill: I'm skilled in the art of enjoyment!
Not to be mixed with previous skill, cars are an absolute favorite thing of mine. Too bad they're soooo expensive, otherwise, I'd own a fleet of them.
Are you skilled in the art of enjoyment, or do you have a passion for cars? Let me know!
CONTACT ME© 2021 Anthony Holloway


Class: compound
http://purl.org/biotop/btl2.owl#Compound
Annotations (2)
definition
"A compound is a material entity that consists of well-defined component parts"
()
label
"compound"
()
Superclasses (1)
'material object'
Usage (2)
Class
:
compound
'compound of collective material entities'
≡
compound
and
'has component part'
only
'collective material entity'


Add quick, dynamic tab functionality to transition through panes of local content.
Easily make tabs or pills equal widths of their parent.
A dynamic tab functionality with menu on the left using .nav-stacked class.
A dynamic tab functionality with menu on the right using .nav-stacked class.
A colored tabs using class names of .nav-primary
A colored tabs using class name of .nav-success
A colored tabs using class names of .nav-warning
A colored tabs using class name of .nav-danger
A colored tabs using class names of .nav-info
A colored tabs using class name of .nav-inverse
A dynamic tab functionality using a line as an active indicator by adding class of .nav-line
A justified line tab by adding class of .nav-line
Get base styles and flexible support for collapsible components like accordions and navigation.
The payments can be done in 15 different currencies (see [info] on the ShareIt transaction page). However, if you prefer to pay in US Dollars, British Pounds or any currency other than Euro, please consider that various exchange fees will be applied. For currencies other than USD or GBP, for example, the charge applied by ShareIt can be as much as 9 %.
A standard styles for collapsible components with an arrow indicator.
The payments can be done in 15 different currencies. However, if you prefer to pay in US Dollars, British Pounds or any currency other than Euro, please consider that various exchange fees will be applied. For currencies other than USD or GBP, for example, the charge applied by ShareIt can be as much as 9 %.
A colored styles for collapsible components.


Angular 7 - JWT Authentication Example & Tutorial
Angular API Calls with Django: Authentication with JWT


{% extends "base.html" %} {% load static %} {% block links %} {% endblock links %} {% block content %} Visit the store ! No. 579, Alagirisamy Salai, KK Nagar, Chennai 600078 Number :<PHONE_NUMBER><EMAIL_ADDRESS>Sample Headline blah blah blah Other queries or order specifications? Please feel free to whatsapp or call the store at working hours Whatsapp us Working Hours No. 579, Alagirisamy Salai, KK Nagar Monday - Saturday : 8 AM - 9 PM Sunday : 9AM to 9PM Contact no.<PHONE_NUMBER> {% endblock content %}
No. 579, Alagirisamy Salai, KK Nagar, Chennai 600078
Number :<PHONE_NUMBER>
<EMAIL_ADDRESS>Please feel free to whatsapp or call the store at working hours
No. 579, Alagirisamy Salai, KK Nagar
Monday - Saturday : 8 AM - 9 PM
Sunday : 9AM to 9PM
Contact no.<PHONE_NUMBER>


Working on more examples for the notebook. Currently exploring a collection of simulated examples. In particular, would be useful to have simulated examples that look as realistic in data-density as possible (i.e. fewer sample points, also shorter sampling interval relative to timescale, so doesn’t look like a fuzzy caterpillar. Second, would be good to include examples on data simulated from non-linearized systems made to represent some richer bifurcation examples. Finally it would be good to include as many real-data examples as reasonable.
Running at m = 0.03, N=500
very clear in likelihood and rather clear in summary statistics as well, though summary statistics null remains highly variable. 1600 replicates
Rerunning at m=-0.02 still with N = 500 nice 19
rerunning at m=-0.03 with N = 50 nice 1
pretty hopeless:
rerunning at m=-0.05 with N = 50 nice 0
(hits collapse at end of time), can clearly tell apart, Though with notable uncertainty in indicator statistics, though variance performs substantially better than autocorrelation.
Better tracking of computational objects
Problem: Saving .Rdat files to match the script-name and tracking those files in git does not provide a good map between code and results. Running the same script simultaneously with different parameters would mean that the datafile was overwritten by the first and could have hashtags on figures not correspond to the current version of the data commit.
This also means tracking binary .Rdat files in git, which both takes up extra space and isn’t readable by diff/display tools.
Solution: Rather than only running differently-named scripts simultaneously (or avoiding runs on the the same repository code) it makes more sense to track the data to the computational object directly.
The .Rdat files should be saved using a unique hash name corresponding to the result.
They shouldn’t be revision managed.
This should be handled automatically within social_plot in the socialR package.
This identifier needs to be by flickr id, as git hashtag isn’t unique to the result; the graph is the computational object.
Now implemented in package. Can store all datafiles in a local repository, no need to keep them on the cloud server as they can always be reproduced by rerunning the code – storing the .Rdat output is really about efficiency and convenience.
For completeness this might store the git hash too. Could play with ls environment. Getting ls environment right to save the appropriate data requires manipulating R environments, as ls() inside a function returns only what that function sees.
if(save){
save(list=ls(globalenv()), file=paste(flickr_id, ".Rdat", sep=""))
}
Computational Notebook to-do
Considering a git guide for notebook: setting up, jumping back to a hashtag version, running the code to make any figure, etc
flickr guide?
AWS/EC3 guide


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Magnetic
Magnetic is a customizable bubble picker like the Apple Music genre selection.
$ pod try Magnetic
Features
- [x] Adding/Removing Nodes
- [x] Selection/Deselection/Removed Animations
- [x] Multiple Selection
- [x] Images
- [x] Multiline Label
- [x] Documentation
Requirements
- iOS 9.0+
- Xcode 9.0+
- Swift 5 (Magnetic 3.x), Swift 4 (Magnetic 2.x), Swift 3 (Magnetic 1.x)
Usage
A Magnetic
object is an SKScene.
To display, you present it from an SKView object.
import Magnetic
class ViewController: UIViewController {
var magnetic: Magnetic?
override func loadView() {
super.loadView()
let magneticView = MagneticView(frame: self.view.bounds)
magnetic = magneticView.magnetic
self.view.addSubview(magneticView)
}
}
Properties
var magneticDelegate: MagneticDelegate? // magnetic delegate
var allowsMultipleSelection: Bool // controls whether you can select multiple nodes. defaults to true
var selectedChildren: [Node] // returns selected chidren
Nodes
A Node
object is a SKShapeNode subclass.
Interaction
// add circular node
let node = Node(text: "Italy", image: UIImage(named: "italy"), color: .red, radius: 30)
magnetic.addChild(node)
// add custom node
let node = Node(text: "France", image: UIImage(named: "france"), color: .blue, path: path, marginScale: 1.1)
magnetic.addChild(node)
// remove node
node.removeFromParent()
Properties
var text: String? // node text
var image: UIImage? // node image
var color: UIColor // node color. defaults to white
Animations
override func selectedAnimation() {
// override selected animation
}
override func deselectedAnimation() {
// override deselected animation
}
override func removedAnimation(completion: @escaping () -> Void) {
// override removed animation
}
Delegation
The MagneticDelegate
protocol provides a number of functions for observing the current state of nodes.
func magnetic(_ magnetic: Magnetic, didSelect node: Node) {
// handle node selection
}
func magnetic(_ magnetic: Magnetic, didDeselect node: Node) {
// handle node deselection
}
Customization
Subclass the Node for customization.
For example, a node with an image by default:
class ImageNode: Node {
override var image: UIImage? {
didSet {
sprite.texture = image.map { SKTexture(image: $0) }
}
}
override func selectedAnimation() {}
override func deselectedAnimation() {}
}
Installation
CocoaPods
To install with CocoaPods, simply add this in your Podfile
:
use_frameworks!
pod "Magnetic"
Carthage
To install with Carthage, simply add this in your Cartfile
:
github "efremidze/Magnetic"
Mentions
Communication
- If you found a bug, open an issue.
- If you have a feature request, open an issue.
- If you want to contribute, submit a pull request.
Credits
https://github.com/igalata/Bubble-Picker
License
Magnetic is available under the MIT license. See the LICENSE file for more info.


The climb is a long, consistently steep ascent, and riders require a steady pacing over 40-45 minutes of output. Brief flatter sections offer some relief, as does each bend’s more gradual outer line if a dense swathe of fans doesn’t cover it. But the steepest parts present the greatest opportunity for riders to eke out gains and join the famous names to have won a Tour stage on Alpe d’Huez.


--- layout: example-full.html title: Ol-Cesium with layers example shortdesc: Ol-Cesium with layers example. docs: > This page's Openlayers Ol-Cesium with layers example. Ol-Cesium can not use custom vector layers. tags: "ol-cesium, openlayers, cesium" resources: - https://cdn.rawgit.com/openlayers/openlayers.github.io/master/en/v5.2.0/css/ol.css - https://cdn.rawgit.com/openlayers/openlayers.github.io/master/en/v5.2.0/build/ol.js -<EMAIL_ADDRESS>- https://openlayers.org/ol-cesium/olcesium.js ---


| Language Available | Monitoring Link | Monitoring Method | Topic/Subtopic Identification |
| English | - | New Releases - amendments or updates are issued. May or may not be consolidated. | Content Comprehension - need to check and understand content first to identify topic/subtopic. |
| Native Language | - | Compare - not issued or published as an update or amendment but may already be consolidated in the main regulation. | As shown/classified - topic/subtopic is already classified. |


Monte4Edu
Bottom-Up Change for Quality Education
Vote Giulia Montefiore for Academic Affairs Officer!
What students really need to drive a cultural change towards quality education at Durham is a passionate representative willing to stand up for students’ ideas, ready to develop implementable changes and be in constant dialogue with her peers.
I am a final year student from Italy and I undertook a Year Abroad studying in France last year. Being part of international projects in Turkey, Poland and Norway enlarged my understanding of different higher education systems and of what quality education means cross-country.
I am Course Rep, Department Rep and Faculty Rep for Social Sciences and Health, and part of the Education Committee at the Students’ Union; as a Combined Honours student in Politics and Economics I am always exposed to different departments. I was Environment Officer in Hild Bede College Exec during my second year, and part of the Union Governance Committee in my first.
If we, the students, get lecturers and researchers to buy into our ideas, we can start implementing change NOW, thereby gaining all the means to bring our vision all the way up to the highest University levels. I have ideas and ways to realise them. If you believe in Bottom-Up Change for Quality Education, vote Monte!
Follow me on Facebook and Twitter!
Voting open from 16th until 19th February at 17.00! Vote at durhamsu.com.
10 Policies for Bottom-Up Change for Quality Education
-
Multiple and Continuous Assessment Methods: we need less pressure on a few hours of exams, and more value to the work we do during the year and the skills we develop through it.
-
Erasmus+ and Exchanges Programmes Accessible for All: everybody should have the choice of keeping their degree to 3 years instead of pushing it to 4.
-
Feedback for All: meaningful feedback is key for improvement, yet too many students are deprived of it for their formatives, summatives and exams.
-
Improve Learning and Teaching methods: let’s study what UK and international institutions with outstanding teaching do, develop change proposals and enter a dialogue with departments to implement world leading teaching. All student-led, all bottom-up.
- Cut extra-course costs:
- Cheaper printing
- Purely online submission for essays and projects
- More online material.
-
Student Discussion Groups in each department: they enable better analysis of problems than questionnaires and are a successful reality in other UK universities.
-
A real place to eat your own food: the Science Site marquee should be put up, equipped with microwaves, until a real solution for students to eat healthily every day has been found. A homemade cold lunch on the floor vs a paid-for hot meal at YUM is not an acceptable dilemma.
-
Zero Errors in Exam Papers: every year errors heavily disrupt exams. We must lobby the University for more rigorous exam-scripts checking.
-
Better Timetabling: the most popular combinations of modules should be accounted for. Stop missing part of the next class because you need to be on the opposite side of town in 10 minutes, but can’t fly.
- More Versatile and user-friendly DUO in a Library open until 2 a.m. when not on 24/7 period.


We are a company of long time developers and engineers, so we understand how this system works and persue our journey and aim to make the cloud storage system as seemless as posible without compromising on security and speed.
Hundreds of websites get hosted almost every week, a thousands are already served in our platfrom. We ensure speed and secuirty with no down time.
We have the best architecture in place for cloud storage with server all over the world, served and saved in mutiple servers. All our premium customers get 10gb of data for upload and download.
Expand and reduce your database needs in no time, we provide solution that are scalable, that meets your and your customer needs. 10 users or 100 thousands, we got you covered.
No stricture in creating any number of user for the access of our servers.
SQL or noSQL, we got you cover, our platform support almost all the technolgy and we upgrading to stay upto date with the market .
Your dashboard provide the overview of your services and user Analysis, queries and reports are high customizable.
Along with gitlab and bitbucket, we have github intregration for hosting and deployment needs.
Along with our 3 most popular plan, we are flexibe with our services, have specific needs, no problem give us call, we'll work out something awesome for you.
Our hi-tech storage architecture ensure we provide services at all, need specific location needs, you can pick and choose from your provided option, its that easy.


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cacheName(String)
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Local storage name to save image to, the url would be used as filename if this is not set
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chainWith(Transformation)
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Url
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BufferedReader
Close the stream.
cloudinary
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Api
Cloudinary
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Cloudinary(Map)
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Cloudinary
Cloudinary(String)
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Cloudinary
Cloudinary()
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Cloudinary
cloudinary()
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AbstractUploaderStrategy
cloudinary()
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Uploader
CLOUDINARY_API_ERROR_CLASSES
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Api
cloudinaryApiUrl(String, Map)
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Cloudinary
cloudName
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Configuration
cloudName(String)
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Url
CN1String
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CN1String(String)
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CN1String
CN1String.Builder
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com.cloudinary.codename1.util
cname
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Configuration
cname(String)
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Url
color(String)
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Transformation
colorSpace(String)
- Method in class com.cloudinary.
Transformation
com.cloudinary
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com.cloudinary.api
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com.cloudinary.api.exceptions
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com.cloudinary.utils
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com.codename1.hello
- package com.codename1.hello
compile(String)
- Static method in class com.cloudinary.
Pattern
config
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Cloudinary
Configuration
- Class in
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Configuration object for a
Cloudinary
instance
Configuration()
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Configuration
Configuration(Map)
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Configuration
Configuration(Configuration)
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Configuration
Configuration.Builder
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com.cloudinary
Build a new
Configuration
contains(String)
- Method in class com.cloudinary.codename1.util.
CN1String
Coordinates
- Class in
com.cloudinary
Coordinates()
- Constructor for class com.cloudinary.
Coordinates
Coordinates(Collection<Rectangle>)
- Constructor for class com.cloudinary.
Coordinates
Coordinates(int[])
- Constructor for class com.cloudinary.
Coordinates
Coordinates(Rectangle)
- Constructor for class com.cloudinary.
Coordinates
Coordinates(String)
- Constructor for class com.cloudinary.
Coordinates
createTransformation(String, String, Map)
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Api
createUploadMapping(String, Map)
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createUploadPreset(Map)
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crop(String)
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Machine Learning: Entropy and Classification
A Simple Classification Example
Let’s say we have a dataset with categorical features , , , and a binary target variable :
| id | Feature | Feature | Feature | Target Variable |
|---|---|---|---|---|
| 1 | a | c | e | |
| 2 | b | d | e | |
| 3 | b | d | f | |
| 4 | a | d | e | |
| 5 | a | c | f | |
| 6 | b | d | f | |
The goal is to find the feature that best predicts the value of .
After a bit of close inspection, we see that Feature will have the highest “predictive power” in determining :
- All instances with Feature equal to
e
(ids 1, 2, 4, 6) belong to class . - All instances with Feature equal to
f
(ids 3, 5) belong to class .
The other features and are not as accurate as in predicting the target. We call Feature as the most informative attribute.
Entropy
It might seem an easy task to determine the most informative attribute in the dataset above by hand. But for larger, more complex datasets, it’s impractical to count and match all the features with target classes for all samples. We need a way to measure the informativeness of a feature, that is, how it effectively classifies the dataset. Fortunately, we have entropy to help us do that.
Entropy is a term used in statistical physics as a measure of how disordered a system is. Machine learning’s use of entropy isn’t far from this concept of disorderedness. In ML, a set of instances is said to be disordered when there’s a considerable mix of target classes that the instances belong to. This means that the more mixed the segment is with respect to the classifications (i.e., target variables), the higher the entropy.
The entropy of a set with a binary target with values and is defined as
where is the proportion of the ith target variable in the set. Entropy always ranges between 0 (minimum disorder) and 1 (maximum disorder).
As an exercise, let’s calculate for the whole dataset:
This tells us that a set whose samples are equally divided among the target’s values is maximally disordered.
If we have two or more target classes, the equation above generalizes as follows:
where is the set of unique values of the target variable.
It’s easy to see that the number of elements in is equal to the number of terms in the summation.
Classifying datasets with categorical attributes is all about segmenting data in a way that the resulting subsets have lower entropy than the whole dataset, all without penalizing the model’s performance when it’s time to classify unknown data (i.e., prevent the model from overfitting).
Information Gain
The informativeness of a feature can be measured using the concept of information gain, which can be defined using entropy. Consider a dataset which we call the parent, and we’d like to know how well a certain feature classifies the elements contained in the parent.
We define the information gain of a feature on some parent dataset as
where is the set of unique values of feature , is the entropy of the parent set, is the proportion of instances belonging to the th value of the considered feature, and is the entropy of the set whose elements have the th value of the feature.
Now let’s apply the definition of information gain for every feature in our dataset above.
Information Gain
The information gain for Feature , whose values are the set , is
and in the summation are the proportion of instances where Feature has values and , respectively.
Now and are the entropies of the subsets whose instances have Feature equal to and , respectively.
Thus, the information gain for Feature is
Information Gain
Given the following values,
we see that the value of is zero.
This means that there is no information gained when using Feature to classify the dataset.
Information Gain
Given the following values,
we see that the value of is 1, the highest information gain among all the features.
Using the definitions and tools outlined above, we can now formally state why Feature is the most informative attribute. It’s because it has the highest information gain among all the features in the dataset.
What about numeric features?
We may begin to wonder about regression problems, where the target variable is a numeric one instead of a categorical one. How do we calculate for the most informative attribute in this case?
Information gain still makes sense here. But it must represent a numerical feature’s “closeness” to the target variable. Instead of using entropy as a measure of disorder (or order) with regards to the categorical target values, we use variance as a measure of closeness to the target value.
A feature will have a high variance if its values do not behave as the target values behave. Low variance occurs when the feature increases (decreases) in value, the target also increases (decrease) in value. In other words, the counterpart of information gain in regression problems is correlation.
Here’s a table outlining which quantities are analogous to each other between classification and regression problems.
| Measure of Orderness | Measure of Informativeness | |
|---|---|---|
| Classification | Entropy | Information Gain |
| Regression | Variance | Correlation |
Hope this was insightful!


NSW launches economic blueprint to nowhere
by Houses and HolesYou’ve got to love the powers that be. Their arrgoant disregard for standards of living, for the wishes of the people, for simple economic sense, via Domain:
A new blueprint for the NSW economy predicts the state’s annual output will hit $1 trillion by the end of next decade and reach $2 trillion by around 2040 as consumer demand from Asia’s fast-growing middle-classes boosts exports.
Treasurer Dominic Perrottet will on Wednesday launch the NSW 2040 Economic Blueprint, which identifies seven key policy “levers” that can be used to enhance economic performance.
There are 1269 words left in this subscriber-only article.


A general purpose writer of data from avro streams. This writer analyzes the writer schema when constructed so that writes can be more efficient. Once constructed, a writer can be reused or shared among threads to avoid incurring more resolution costs. More...
Classes | |
| interface | ArrayAccess |
| class | DictionaryMapAccess |
| interface | EnumAccess |
| interface | MapAccess |
| class | RecordFieldWriter |
Public Member Functions | |
| void | Write (T datum, Encoder encoder) |
Protected Member Functions | |
| delegate void | WriteItem (Object value, Encoder encoder) |
| PreresolvingDatumWriter (Schema schema, ArrayAccess arrayAccess, MapAccess mapAccess) | |
| void | WriteNull (object value, Encoder encoder) |
| Serializes a "null". | |
| void | Write< S > (object value, Schema.Type tag, Writer< S > writer) |
| A generic method to serialize primitive Avro types. | |
| abstract void | WriteRecordFields (object record, RecordFieldWriter[] writers, Encoder encoder) |
| abstract void | EnsureRecordObject (RecordSchema recordSchema, object value) |
| abstract void | WriteField (object record, string fieldName, int fieldPos, WriteItem writer, Encoder encoder) |
| Extracts the field value from the given object. | |
| abstract WriteItem | ResolveEnum (EnumSchema es) |
| Serializes an enumeration. | |
| WriteItem | ResolveArray (ArraySchema schema) |
| Serialized an array. The default implementation calls EnsureArrayObject() to ascertain that the given value is an array. It then calls GetArrayLength() and GetArrayElement() to access the members of the array and then serialize them. | |
| void | WriteMap (WriteItem itemWriter, object value, Encoder encoder) |
| Serialized a map. The default implementation first ensure that the value is indeed a map and then uses GetMapSize() and GetMapElements() to access the contents of the map. | |
| int | ResolveUnion (UnionSchema us, Schema[] branchSchemas, object obj) |
| Finds the branch within the given UnionSchema that matches the given object. The default implementation calls Matches() method in the order of branches within the UnionSchema. If nothing matches, throws an exception. | |
| abstract void | WriteFixed (FixedSchema es, object value, Encoder encoder) |
| Serialized a fixed object. The default implementation requires that the value is a GenericFixed object with an identical schema as es. | |
| abstract bool | UnionBranchMatches (Schema sc, object obj) |
Static Protected Member Functions | |
| static AvroException | TypeMismatch (object obj, string schemaType, string type) |
Properties | |
| Schema | Schema [get, set] |
A general purpose writer of data from avro streams. This writer analyzes the writer schema when constructed so that writes can be more efficient. Once constructed, a writer can be reused or shared among threads to avoid incurring more resolution costs.
| WriteItem Avro.Generic.PreresolvingDatumWriter< T >.ResolveArray | ( | ArraySchema | schema | ) | [inline, protected] |
Serialized an array. The default implementation calls EnsureArrayObject() to ascertain that the given value is an array. It then calls GetArrayLength() and GetArrayElement() to access the members of the array and then serialize them.
| schema | The ArraySchema for serialization |
| value | The value being serialized |
| encoder | The encoder for serialization |
| abstract WriteItem Avro.Generic.PreresolvingDatumWriter< T >.ResolveEnum | ( | EnumSchema | es | ) | [protected, pure virtual] |
Serializes an enumeration.
| es | The EnumSchema for serialization |
Implemented in Avro.Generic.GenericDatumWriter< T >, and Avro.Specific.SpecificDatumWriter< T >.
| int Avro.Generic.PreresolvingDatumWriter< T >.ResolveUnion | ( | UnionSchema | us, |
| Schema[] | branchSchemas, | ||
| object | obj | ||
| ) | [inline, protected] |
Finds the branch within the given UnionSchema that matches the given object. The default implementation calls Matches() method in the order of branches within the UnionSchema. If nothing matches, throws an exception.
| us | The UnionSchema to resolve against |
| obj | The object that should be used in matching |
| void Avro.Generic.PreresolvingDatumWriter< T >.Write< S > | ( | object | value, |
| Schema.Type | tag, | ||
| Writer< S > | writer | ||
| ) | [inline, protected] |
A generic method to serialize primitive Avro types.
| S | Type of the C# type to be serialized |
| value | The value to be serialized |
| tag | The schema type tag |
| writer | The writer which should be used to write the given type. |
| abstract void Avro.Generic.PreresolvingDatumWriter< T >.WriteField | ( | object | record, |
| string | fieldName, | ||
| int | fieldPos, | ||
| WriteItem | writer, | ||
| Encoder | encoder | ||
| ) | [protected, pure virtual] |
Extracts the field value from the given object.
| value | The record value from which the field needs to be extracted |
| fieldName | The name of the field in the record |
| fieldPos | The position of field in the record |
Implemented in Avro.Generic.GenericDatumWriter< T >, and Avro.Specific.SpecificDatumWriter< T >.
| abstract void Avro.Generic.PreresolvingDatumWriter< T >.WriteFixed | ( | FixedSchema | es, |
| object | value, | ||
| Encoder | encoder | ||
| ) | [protected, pure virtual] |
Serialized a fixed object. The default implementation requires that the value is a GenericFixed object with an identical schema as es.
| es | The schema for serialization |
| value | The value to be serialized |
| encoder | The encoder for serialization |
Implemented in Avro.Specific.SpecificDatumWriter< T >, and Avro.Generic.GenericDatumWriter< T >.
| void Avro.Generic.PreresolvingDatumWriter< T >.WriteMap | ( | WriteItem | itemWriter, |
| object | value, | ||
| Encoder | encoder | ||
| ) | [inline, protected] |
Serialized a map. The default implementation first ensure that the value is indeed a map and then uses GetMapSize() and GetMapElements() to access the contents of the map.
| schema | The MapSchema for serialization |
| value | The value to be serialized |
| encoder | The encoder for serialization |
| void Avro.Generic.PreresolvingDatumWriter< T >.WriteNull | ( | object | value, |
| Encoder | encoder | ||
| ) | [inline, protected] |
Serializes a "null".
| value | The object to be serialized using null schema |
| encoder | The encoder to use while serialization |


echolocatoR pipeline on a single locus — finemap_pipeline" />
Unlike finemap_loci
, you don't need to provide a top_SNPs
data.frame.
Instead, just manually provide the coordinates of the locus you want to fine-map.
finemap_pipeline( locus, fullSS_path, results_dir, dataset_name = "dataset_name", dataset_type = "dataset_type", top_SNPs = "auto", force_new_subset = F, force_new_LD = F, force_new_finemap = T, finemap_methods = c("ABF", "FINEMAP", "SUSIE", "POLYFUN_SUSIE"), bp_distance = 5e+05, n_causal = 5, chrom_col = "CHR", position_col = "POS", snp_col = "SNP", pval_col = "P", effect_col = "Effect", stderr_col = "StdErr", tstat_col = "t-stat", locus_col = "Locus", freq_col = "Freq", MAF_col = "MAF", A1_col = "A1", A2_col = "A2", gene_col = "Gene", N_cases_col = "N_cases", N_controls_col = "N_controls", N_cases = NULL, N_controls = NULL, proportion_cases = "calculate", sample_size = NULL, LD_reference = "1KGphase1", superpopulation = "EUR", download_reference = T, download_method = "direct", min_POS = NA, max_POS = NA, min_MAF = NA, trim_gene_limits = F, max_snps = NULL, file_sep = "\t", min_r2 = 0, LD_block = F, LD_block_size = 0.7, min_Dprime = F, query_by = "coordinates", remove_variants = F, remove_correlates = F, probe_path = "./Data/eQTL/gene.ILMN.map", conditioned_snps, plot_LD = F, remove_tmps = T, plot.types = c("simple"), PAINTOR_QTL_datasets = NULL, server = F, PP_threshold = 0.95, consensus_threshold = 2, case_control = T, QTL_prefixes = NULL, plot.window = NULL, plot.Nott_epigenome = plot.Nott_epigenome, plot.Nott_binwidth = 2500, plot.Nott_bigwig_dir = NULL, plot.XGR_libnames = NULL, plot.Roadmap = F, plot.Roadmap_query = NULL, conda_env = "echoR", verbose = T )
| fullSS_path | Path to the full summary statistics file (GWAS or QTL) that you want to fine-map. |
|---|---|
| results_dir | Where to store all results. |
| dataset_name | The name you want to assign to the dataset being fine-mapped, This will be used to name the subdirectory where your results will be stored (e.g. Data/GWAS/<dataset_name>). Don't use special characters (e.g.".", "/"). |
| dataset_type | The kind dataset you're fine-mapping (e.g. GWAS, eQTL, tQTL). This will also be used when creating the subdirectory where your results will be stored (e.g. Data/<dataset_type>/Kunkle_2019). |
| top_SNPs | A data.frame with the genomic coordinates of the lead SNP for each locus.
The lead SNP will be used as the center of the window when extracting subset from the full GWAS/QTL summary statistics file.
Only one SNP per Locus should be included.
At minimum,
|
| force_new_subset | By default, if a subset of the full summary stats file for a given locus is already present,
then echolocatoR will just use the pre-existing file.
Set |
| force_new_LD | By default, if an LD matrix file for a given locus is already present,
then echolocatoR will just use the preexisting file.
Set |
| force_new_finemap | By default, if an fine-mapping results file for a given locus is already present,
then echolocatoR will just use the preexisting file.
Set |
| finemap_methods | Which fine-mapping methods you want to use. |
| bp_distance | The width of the window size you want each locus to be.
For example, if |
| n_causal | The maximum number of potential causal SNPs per locus. This parameter is used somewhat differntly by different fine-mapping tools. See tool-specific functions for details. |
| chrom_col | Name of the chromosome column in the full summary stats file. Can be "chr1" or "1" format. (default: ="CHR") |
| position_col | Name of the genomic position column in the full summary stats file. Must be in units of basepairs. (default: ="POS") |
| snp_col | Name of the SNP RSID column in the full summary stats file. (default: ="SNP") |
| pval_col | Name of the p-value column in the full summary stats file. Raw p-values are preferred, but if not available corrected p-values (e.g. FDR) can be used instead. (default: ="P") |
| effect_col | Name of the effect size column in the full summary stats file. Effect size is preferred, but if not available other metrics like Beta for Odds Ratio can be used instead. (default: ="Effect") |
| stderr_col | Name of the standard error column in the full summary stats file.
You can also set |
| tstat_col | Name of the t-statistic column in the full summary stats file.
This column is not necessary unless |
| locus_col | Name of the locus column in the full summary stats file. (default: ="Locus") |
| freq_col | Name of the allele frequency column in the full summary stats file.
Effect allele frequency is preferred, but the non-effect allele can be provided instead (though this may be less accurate).
This column is not necessary unless |
| MAF_col | Name of the minor allele frequency column in the full summary stats file. Can be inferred from freq_col if missing from the dataset. (default: ="MAF") |
| A1_col | Name of the effect/risk allele column in the full summary stats. IMPORTANT: Make sure this actually the case for your full summary stats file. Unfortunately, different studies report different kinds of allele information in a non-standardized way. Meaning that A1/A2 can refer to any number of things:
This makes comparing summary stats across GWAS/QTL datasets very confusing for several reasons:
This process of reversing per-SNP valences based on aligning the alleles is known as allele flipping. This is important when comparing individual SNPs, but can also have an impact on colocalization results. |
| gene_col | For QTL studies, the name of the [e]gene column in the full summary stats file (default: "gene").
This column will be used for filtering summary stats if supplying a named list of gene:Locus pairs to |
| N_cases_col | Name of the column in the full summary stats that has the number of case subjects in the study.
This can either be per SNP sample sizes, or one number repeated across all rows.
Proxy cases (e.g. relatives of people with the disease being investigated) should be included in this estimate if any were used in the study.
This column is not necesssary if |
| N_controls_col | Name of the column in the full summary stats that has the number of control subjects in the study.
This can either be per SNP sample sizes, or one number repeated across all rows.
This column is not necesssary if |
| N_cases | The number of case subjects in the study. Instead of providing a redundant N_cases_col column, you can simply enter one value here. |
| N_controls | The number of control subjects in the study. Instead of providing a redundant N_controls_col column, you can simply enter one value here. |
| proportion_cases | The proportion of total subjects in the study that were cases.
if |
| sample_size | The overall sample size of the study.
If none is given, and N_cases and N_controls columns are present,
then sample_size is inferred to be: |
| LD_reference | Which linkage disequilibrium reference panel do you want to use. Options include:
|
| superpopulation | Subset your LD reference panel by superopulation.
Setting the superpopulation is not currently possible when
|
| download_reference | When acquiring LD matrixes,
the default is to delete the full vcf or npz files after echolocatoR has extracted the necssary subset.
However, if you wish to keep these full files (which can be quite large) set |
| min_POS | Manually set the minimum genomic position for your locus subset.
|
| max_POS | Manually set the maximum genomic position for your locus subset.
|
| min_MAF | Remove any SNPs with MAF < |
| trim_gene_limits | If a valid gene symbol is provided to |
| max_snps | The maximum number of SNPs to include in the locus.
If the current window size yields > |
| file_sep | The separator in the full summary stats file.
This parameter is only necessary if |
| min_r2 | Remove any SNPs are below the LD r2 threshold with the lead SNP within their respective locus. |
| LD_block | Calculate LD blocks with plink and only include the block to which the lead SNP belongs. |
| LD_block_size | Adjust the granularity of block sizes when |
| min_Dprime | Remove any SNPs are below the LD D' threshold with the lead SNP within their respective locus.
This is paramter currently only works when |
| query_by | Choose which method you want to use to extract locus subsets from the full summary stats file. Methods include:
|
| remove_variants | A list of variants to remove from the locus subset file. |
| remove_correlates | If |
| probe_path | The location of the file containing translations between probe IDs and gene symbols. Only used for certain eQTL datasets. |
| conditioned_snps | Which SNPs to conditions on when fine-mapping with COJO. |
| plot_LD | Whether to plot a subset of the LD matix. |
| remove_tmps | Whether to remove any temporary files (e.g. FINEMAP output files) after the pipeline is done running. |
| plot.types | Which kinds of plots to include. Options:
|
| PAINTOR_QTL_datasets | A list of QTL datasets to be used when conducting joint functional fine-mapping with PAINTOR. |
| server | Whether echolocatoR is being run on a computing cluster/server or on a local machine. |
| PP_threshold | The minimum fine-mapped posterior probability for a SNP to be considered part of a Credible Set.
For example, |
| consensus_threshold | The minimum number of fine-mapping tools that include a SNP in their 95% Credible Sets to consider that it a "Consensus SNP" (default=2). |
| plot.window | Zoom into the center of the locus when plotting (without editing the fine-mapping results file).
You can also pass a list of window sizes (e.g. |
| plot.Nott_binwidth | When including Nott et al. (2019) epigenomic data in the track plots, adjust the bin width of the histograms. |
| plot.Nott_bigwig_dir | Instead of pulling Nott et al. (2019) epigenomic data from the UCSC Genome Browser, use a set of local bigwig files. |
| plot.Roadmap | Find and plot annotations from Roadmap. |
| plot.Roadmap_query | Only plot annotations from Roadmap whose metadata contains a string or any items from a list of strings
(e.g. |
| conda_env | The name of a conda environment to use. |
| verbose | Whether echolocatoR should be verbose or silent. |
| loci | Character list of loci in Locus col of |
The primary functions of echolocatoR that expedite fine-mapping by wrapping many other echolocatoR functions into one. Encompasses steps including:
Extract subsets of the full summmary stats GWAS or QTL file and reformat them to be compatible with echolocatoR's various functions
Download and prepare the necessary LD matrix.
Run various fine-mapping tools and merge the results into a single multi-finemap data.frame.
Summarise the results in a multi-track plot for each locus.
Other MAIN:
finemap_loci()


Introduction
Otto Exensions is a library of helpful classes from Fizz Buzz LLC that extend the Otto event bus library from Square, Inc.
Usage
Including In Your Application
Otto Extensions is packaged as a standalone .jar file which you can place in the libs/
folder
of your application. It is compatible with all versions of Android and has no minimum SDK requirement. You
can download the latest .jar on the GitHub project by clicking the "Download" button.
If you are a Maven user, you can also fetch Otto Extensions from the central repositories by including the following
dependency in your application's pom.xml
:
<dependency> <groupId>com.fizzbuzz</groupId> <artifactId>otto-extensions</artifactId> <version>(insert latest version)</version> </dependency>
Contributing
If you would like to contribute code to Otto Extensions, you can do so through GitHub by forking the repository and sending a pull request.
When submitting code, please make every effort to follow existing conventions and style in order to keep
the code as readable as possible. Please also make sure your code compiles by running mvn clean
verify
. Checkstyle failures during compilation indicate errors in your style and can be viewed in the
checkstyle-result.xml
file.
Before your code can be accepted into the project you must also sign the Individual Contributor License Agreement (CLA).
License
Copyright 2013 Fizz Buzz LLC Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.


Match Play. Red leads 3-0 to 7. Should Red double? If doubled, should White take?
pips Red=130 White=147
(CorrectAnswer= 0/0, ErrorScore= 0)
Red should not double this position but that is because he is too good to double. He is ahead in race, threat and position so White should be dropping very quickly if he is given the chance to do so. A gammon loss with the cube on 2 would spell the end of the match for White.
Red can afford to take a roll here and he can keep the cube in reserve for later if his gammon chances recede. Even at 0-0 he should play on.
Red can afford to take a roll here and he can keep the cube in reserve for later if his gammon chances recede. Even at 0-0 he should play on.
Cube analysis 2-ply cubeless equity +0.942 (Money: +0.807) 0.728 0.413 0.014 - 0.272 0.072 0.003 Cubeful equities: 1. No double +1.013 2. Double, take +1.498 (+0.484) 3. Double, pass +1.000 (-0.013) Proper cube action: Too good to double, pass (2.7%)


(509)***-****
<EMAIL_ADDRESS>have experience working with Linux, Python, CLI, Git, HTML, CSS, PHP, Apache2, and I am certified in Microsoft Office 2016.
I have been a part of Prosser School District's SWAT, or Student with an Aptitude for Technology, for the past 3 years. SWAT is an afterschool class/program where it trains students grades 9-12 to handle basic to midlevel technical service for the Prosser School District.
I have been working with HTML since August 2017, and since then, I have gained a firm understanding of the basics of web development. I have also learned the basics of networking and how networks work.
GPA: 3.35
GPA: 3.56
Apart from school work, I enjoy running, hiking, camping, software/web development, reading, and spending time with my friends and family.
When forced indoors, I follow a number of sci-fi and fantasy genre movies and games. I am attempting to learn how to cook, and I spend a large amount of my free time exploring the latest technology advancements in the front-end web development world including the hardware side.
At the time of writing this, I am currently working on a couple of projects including developing my own website, setting up a web server on a Raspberry Pi, and working on graphics.
Some future projects I intend to work on would most likely involve learning new programming languages and expanding on my skills in programming.


This is a demonstration of using Crossbar.io to enable live synching of UI elements for collaboration.
Works across several tabs or browsers by setting a common controller
channel in all instances.
All interactions on this demo occur in response to messages routed through the instance of Crossbar.io displayed in the status line at the bottom of the demo box.
The demo uses Farbtastic color picker
created by Steven Wittens and licensed under GPL 2. The Farbtastic code was slightly
modified allowing to suppress color change events being generated when color is set externally
instead of by the user from within the control.


{% extends "base.html" %} {% block page_content %}
Using the browser should be simple ... just use the controls in navigation bar at the top.
The Gammapy browser is implemented via a restful API, i.e. all pages are accessed via GET requests with these URLs:
| URL | Content |
| / | About page |
| /obs/obs_id | Basic observation info |
| /events/obs_id | Event info |
| /irfs/obs_id | IRF info |