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| Code Block |
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| theme | Eclipse |
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| language | PQL |
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| title | Probabilistic discrete select |
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| linenumbers | true |
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filteroutput = SELECT({predicate = RelationalPredicate('x > 1.0 AND x < 3.0')}, input) |
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| Code Block |
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| theme | Eclipse |
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| language | javascriptpql |
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| title | Probabilistic continuous select |
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| linenumbers | true |
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filteroutput = SELECT({predicate = RelationalPredicate('x > 1.0 AND x < 4.0')}, input) |
...
| Code Block |
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| theme | Eclipse |
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| language | sqlcql |
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| title | Probabilistic Join |
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| linenumbers | true |
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Select * From input1,input2 WHERE input1.x=input2.y; |
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| Code Block |
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| theme | Eclipse |
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| language | javascriptpql |
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| title | Algebraic operator on probabilistic discrete values |
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| linenumbers | true |
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mapedoutput = MAP({expressions = ['x + 2.0', 'x * 2.0', 'x * toProbabilisticDouble([1.0,0.5;2,0.5])', 'x * toProbabilisticDouble([1.0,0.5])']}, input) |
...
Calculates the Bhattacharyya distance between two distributions.
| Code Block |
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| language | javascriptcql |
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| title | Example |
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SELECT similarity(as2DVector(x1,y1), as2DVector(x2,y2)) FROM stream
|
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Calculates the Mahalanobis distance between the distribution and the value. The value can be a scalar value or a vector.
| Code Block |
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| language | javascriptcql |
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| title | Example |
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SELECT distance(as3DVector(x, y, z), [1.0;2.0;3.0]) FROM stream |
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| Code Block |
|---|
| theme | Eclipse |
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| language | javascriptpql |
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| title | Probabilistic continuous select |
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| linenumbers | true |
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filteroutput = ExistenceToPayload(SELECT({predicate = RelationalPredicate('x > 1.0 AND x < 4.0')}, input)) |