Logic Pro Search Plugins
Grethe Presnar
I'm asking if there is a search feature in Logic similar to Ableton, where you can just hit command-F (in Ableton) and type in, for example, "soundtoys" and it will pull up my soundtoys plugins for me to drag and drop onto the intended track?
Good, I do not know if they have already found something but I can indicate some plugins, for the topic of member filters it has this plugin, but I think it does not perform conditional logic but uses all the fields you want for filters
Just tried to install Query monitor on a site together with this plugin -loops-and-logic/ , but for some reason i get a fatal error as soon as both of the plugins are activated. Despite the fatal error, both plugins remain activated, but cause the same fatal error again as soon as one of the plugins gets deactivates. This is the error message:
Thanks for the report! The cause here is the Tangible Loops and Logic plugin is triggering an action with an invalid hook name. The hook name appears to be boolean false, which internally gets converted to integer zero by the WordPress hook system, and this is what gets passed onto QM and causes the fatal error. A hook name must be a string, and anything such as boolean false is not going to work and needs to be fixed.
PlugSearch 3 categorizes plugins using its extensive and ever-growing database. Thousands of plugins have been manually assigned to up to three categories, and users can search by category name or dive right into the list of categories.
Tokenization splits a run of text into individual tokens, such as words, whitespace, and punctuation. The rules used to split text into tokens is language-specific. For example, in a language like English, word tokens are usually separated by whitespace and punctuation tokens. Thus, a string such as ran, slept tokenizes to the following in English:
An unstemmed search matches only the word form you're searching for. For example, searching for ran will not match a document containing runs. When stemmed search is enabled, the search matches the exact term, plus words with the same stem. Thus, a search for ran will also match documents containing runs or running because they all share the stem run in English.
MarkLogic Server supports stemming in English and other languages. For a list of languages in which stemming is supported, see Supported Languages. You can also create a user-defined stemmer to add support for other languages; for details, see Using a User-Defined Stemmer Plugin.
The stem of a word is not based on spelling. For example, card and cardiac have different stems even though the spelling of cardiac begins with card. On the other hand, running and ran have the same stem (run) even though their spellings are quite different. If you want to search for a word based on partial pattern matching (like the card and cardiac example above), use wildcard searches as described in Understanding and Using Wildcard Searches.
The stemming supported in MarkLogic Server does not cross different parts of speech. For example, conserve (verb) and conservation (noun) are not considered to have the same stem because they have different parts of speech. Consequently, if you search for conserve with stemmed searches enabled, the results will include documents containing conserve and conserves, but not documents with conservation (unless conserve or conserves also appears).
Stemming is language-specific. Each word evaluated in the context of a specific language. A term in one language will not match a stemmed search for the same term in another language. The language can be specified with an xml:lang attribute or by several other methods. For details on how languages affect queries, see Querying Documents By Languages.
To use stemming in your searches, stemming must be enabled in your database configuration. All new databases created in MarkLogic Server have stemmed searches disabled by default. You can enable stemmed searches after initial creation of your database.
Stemmed searches are supported by special indexes. If you enable stemmed searches in an existing database, you must either reload or reindex the database to ensure that you get stemmed results from searches. You should plan on allocating additional disk space of about twice the size of the source content if you enable stemmed searches.
There are three types of stemming available in MarkLogic Server: basic, advanced, and decompounding. The following table describes the stemming options available on the database configuration page of the Admin Interface.
When stemmed searches are enabled for a database, you can enable and disable the use of stemming on a per query basis through options. Query constructors such as cts:word-query, cts:element-word-query, and cts:element-value-query support stemmed and unstemmed options. For more details on these functions, see the MarkLogic XQuery and XSLT Function Reference.
Query terms that contain a wildcard will not be stemmed. If you leave the stemming option unspecified, the database configuration determines whether or not stemming is applied to words that do not contain a wildcard.
The stemmed search indexes and word search (unstemmed) indexes have overlapping functionality, and there is a good chance you can get the results you want with only the stemmed search indexes enabled (that is, leaving the word search indexes turned off).
Stemmed searches return relevance-ranked results for the words you search for as well as for words with the same stem as the words you search for. Therefore, you will get the same results as with a word search plus the results for items containing words with the same stem. In most search applications, this is the desirable behavior.
The only time you need to also have word search indexes enabled is when your application requires an exact word search to only return the exact match results (that is, to not return results based on stemming).
Additionally, the stemmed search indexes take up less disk space than the word search (unstemmed) indexes. You can therefore save some disk space and decrease load time when you use the settings of stemmed search enabled and word search turned off in the database configuration. Every index has a cost in terms of disk space used and increased load times. You have to decide based on your application requirements if the cost of creating extra indexes is worthwhile for your application, and whether you can fulfill the same requirements without some of the indexes.
If you do need to perform word (unstemmed) searches when you only have stemmed search indexes enabled (that is, when word searches are turned off in the database configuration), you must do so by first doing a stemmed search and then filtering the results with an unstemmed cts:query, as described in Unstemmed Searches.
Because stemming enables query matches for terms that do not have the same spelling, it can sometimes be difficult to find the words that actually caused the query to match. You can use cts:highlight to test and/or highlight the words that actually matched the query. For details on cts:highlight, see the MarkLogic XQuery and XSLT Function Reference and Highlighting Search Term Matches.
You can use cts:contains to test if a word matches a query. The cts:contains function returns true if there is a match, false if there is no match. For example, you can use the following function to test if a word has the same stem as another word.
You can use a user-defined stemmer plugin to affect how MarkLogic matches a word to its stems during search term resolution. You create a user-defined stemmer in C++ by implementing a subclass of the marklogic::StemmerUDF base class and deploying it to MarkLogic as a native plugin. The StemmerUDF class is a UDF (User Defined Function) interface.
MarkLogic provides several built-in stemmers that you can configure for a language if you are not satisfied with the default stemmer. The following are some use cases in which you might consider implementing a your own stemmer:
In some cases, you might also need a custom lexer or custom dictionary. For example, if you're working with a language not supported by MarkLogic, you probably also need a custom lexer. For details, see Custom Tokenization and Custom Dictionaries for Tokenizing and Stemming.
You implement a user-defined stemmer as a subclass of the MarkLogic::StemmerUDF base class. StemmerUDF is defined in MARKLOGIC_INSTALL_DIR/include/MarkLogic.h. You can find detailed documentation about the class in the User-Defined Function API reference and in MarkLogic.h. You can find an example implementation in MARKLOGIC_INSTALL_DIR/Samples/NativePlugins.
When stemmed searches are enabled, MarkLogic can use either the default stemming plugin for a language, a user-defined stemming plugin, or both (via delegation). This section describes how MarkLogic interacts with a user-defined stemmer. See the following topics:
Stemmers tend to be heavy-weight objects, so MarkLogic maintains a (per-language) pool of stemmer objects for re-use. When MarkLogic needs one of your StemmerUDF objects, it first checks to see if one is available from the pool. If not, MarkLogic creates one using the object factory obtained during plugin registration. MarkLogic then calls the object's initialize method.
When a stemming task completes, the stemmer is returned to the pool unless it is marked as stale. MarkLogic can choose to mark a stemmer stale, or a stemmer can flag itself as stale by returning true from its StemmerUDF::isStale method.
The following diagram is a high level illustration of how MarkLogic interacts with a StemmerUDF object while finding stems. The actual stemming process is more complex and has parts not represented here.
The native plugin interface includes support for bundling dependent libraries in the native plugin zip file. However, many 3rd party natural language processing tools are large, complex, and have strict installation directory requirements. If you are using such a packge, you should install the 3rd party package package independently on each host in the cluster, rather than trying to include it inside your native plugin package.
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