Add mass and findBestNOccurrences to the public API #114
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otorreno
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Jun 4, 2019
| * @brief Calculates the Mueen distance. | ||
| * | ||
| * The result has the following structure: | ||
| * - 1st dimension contains the index of the subsequence in the tieme serie. |
| * | ||
| * The result has the following structure: | ||
| * - 1st dimension correspond the nth best match. | ||
| * - 2nd dimension conrrespond the numbef of queries. |
| * @brief Calculates the N best matches of several queries in several time series. | ||
| * | ||
| * The result has the following structure: | ||
| * - 1st dimension correspond the nth best match. |
| * - 2nd dimension conrrespond the numbef of queries. | ||
| * - 3rd dimension correspond the numbef of time series. | ||
| * | ||
| * For example, the distance in the position (1, 2, 3) correspond to the second best distance of the third query in the |
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corresponds (applies to more lines as well)
| * | ||
| * The result has the following structure: | ||
| * - 1st dimension contains the index of the subsequence in the tieme serie. | ||
| * - 2nd dimension contains the numbef of queries. |
| * The result has the following structure: | ||
| * - 1st dimension contains the index of the subsequence in the tieme serie. | ||
| * - 2nd dimension contains the numbef of queries. | ||
| * - 3rd dimension contains the numbef of time series. |
| * - 3rd dimension contains the numbef of time series. | ||
| * | ||
| * For example, the distance in the position (1, 2, 3) correspond to the distance of the third query to the fourth time | ||
| * serie for the second subsequence in the time serie |
include/khiva/matrix.h
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| * @brief Calculates the moving average and standard deviation of the time series 't'. | ||
| * The result has the following structure: | ||
| * - 1st dimension correspond the nth best match. | ||
| * - 2nd dimension conrrespond the numbef of queries. |
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Apply the same comments, as this is copy pasted from the other, or viceversa
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@@ Coverage Diff @@
## master #114 +/- ##
==========================================
- Coverage 97.75% 97.67% -0.08%
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Files 16 16
Lines 1694 1722 +28
==========================================
+ Hits 1656 1682 +26
- Misses 38 40 +2
Continue to review full report at Codecov.
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otorreno
suggested changes
Jun 4, 2019
include/khiva/matrix.h
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| * @param index Position where the minimum is occurring. | ||
| * @param q Array whose first dimension is the length of the query time series and the second dimension is the number of | ||
| * queries. | ||
| * @param t Array whose first dimension is the lenght of the time series and the second dimension is the number of time |
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length (check other copies of this doc)
| @@ -45,6 +112,40 @@ bool tileIsFarFromDiagonal(long bandSize, long numRows, long row, long numColumn | |||
| */ | |||
| af::array generateMask(long m, long numRows, long row, long numColumns, long column, long nTimeSeries = 1); | |||
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| /** | |||
| * @brief Calculates the Mueen distance. | |||
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Change this to calculate the Mueen similarity search. See #107. When this PR gets merged, please close the mentioned issue.
Some refactor has been performed in order to publish in the API the mass function not requiring some intermediate computation as parameters. The function findBestNOccurrences has been also added to the API. The C and JNI bindings have been also included for these two functions The corresponding unit tests have been created.
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Some refactor has been performed in order to publish in the API the mass
function not requiring some intermediate computation as parameters.
The function findBestNOccurrences has been also added to the API. The C
and JNI bindings have been also included for these two functions
The corresponding unit tests have been created.
Make sure you have checked all steps below.
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