com.optimaize.langdetect.profiles.LanguageProfile Maven / Gradle / Ivy
package com.optimaize.langdetect.profiles;
import com.optimaize.langdetect.i18n.LdLocale;
import org.jetbrains.annotations.NotNull;
import java.util.List;
import java.util.Map;
/**
* A language profile knows the locale (language), and contains the n-grams and some statistics.
*
* It is built from a training text that should be fairly large and clean.
*
* It contains the n-grams from the training text in the desired gram sizes (eg 2 and 3-grams),
* with possible text filters applied for cleaning. Also, rarely occurring n-grams may have been cut to
* reduce the noise and index size. Use a {@link LanguageProfileBuilder}.
*
* The profile may be created at runtime on-the-fly, or it may be loaded from a previously generated
* text file (see OldLangProfileConverter).
*
* @author Fabian Kessler
*/
public interface LanguageProfile {
@NotNull
LdLocale getLocale();
/**
* Tells what the n in n-grams are used here.
* Example: [1,2,3]
* @return Sorted from smaller to larger.
*/
@NotNull
List getGramLengths();
/**
* @param gram for example "a" or "foo".
* @return 0-n, also zero if this profile does not use n-grams of that length (for example if no 4-grams are made).
*/
int getFrequency(String gram);
/**
* Tells how many different n-grams there are for a certain n-gram size.
* For example the English language has about 57 different 1-grams, whereas Chinese in Hani has thousands.
* @param gramLength 1-n
* @return 0-n, returns zero if no such n-grams were made (for example if no 4-grams were made),
* or if all the training text did not contain such long words.
*/
int getNumGrams(int gramLength);
/**
* Tells how many n-grams there are for all n-gram sizes combined.
* @return 0-n (0 only on an empty profile...)
*/
int getNumGrams();
/**
* Tells how often all n-grams of a certain length occurred, combined.
* This returns a much larger number than {@link #getNumGrams}.
* @param gramLength 1-n
* @return 0-n, returns zero if no such n-grams were made (for example if no 4-grams were made),
* or if all the training text did not contain such long words.
*/
long getNumGramOccurrences(int gramLength);
/**
* Tells how often the n-gram with the lowest amount of occurrences used in this profile occurred.
*
* Most likely there were n-grams with less (unless the returned number is 1), but they were eliminated
* in order to keep the profile reasonably small.
*
* This is the opposite of getMaxGramCount().
*
* @param gramLength 1-n
* @return 0-n, returns zero if no such n-grams were made or existed.
*/
long getMinGramCount(int gramLength);
/**
* Tells how often the n-gram with the highest amount of occurrences used in this profile occurred.
*
* This is the opposite of getMinGramCount().
*
* @param gramLength 1-n
* @return 0-n, returns zero if no such n-grams were made or existed.
*/
long getMaxGramCount(int gramLength);
/**
* Iterates all ngram strings with frequency.
*/
@NotNull
Iterable> iterateGrams();
/**
* Iterates all gramLength-gram strings with frequency.
*/
@NotNull
Iterable> iterateGrams(int gramLength);
}