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manipulating_tables_and_lookup_tables [2026/08/07 03:09] hermann |
manipulating_tables_and_lookup_tables [2026/08/18 03:09] (current) hermann [Printing a table with any number of key columns] |
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| }}; | }}; | ||
| }}; | }}; | ||
| - | |||
| - | // priceTable is usable here, once the Group it was produced inside -- and | ||
| - | // through its sequenceInput, the loop that Group was forced to wait for -- | ||
| - | // has finished. | ||
| </code> | </code> | ||
| + | |||
| + | ''priceTable'' is usable here, once the Group it was produced inside — and through its ''sequenceInput'', the loop that Group was forced to wait for — has finished. | ||
| The loop's own iterations are still eligible to run in parallel with each other: nothing inside it is a Mux, nothing inside it is consumed from outside it, and it feeds no submodel output port -- see [[basic_data_flow|Basic Data Flow]]. Only the loop as a whole is sequenced against the merge, which is why this avoids the cost the Mux-accumulator pattern above pays on every single iteration. | The loop's own iterations are still eligible to run in parallel with each other: nothing inside it is a Mux, nothing inside it is consumed from outside it, and it feeds no submodel output port -- see [[basic_data_flow|Basic Data Flow]]. Only the loop as a whole is sequenced against the merge, which is why this avoids the cost the Mux-accumulator pattern above pays on every single iteration. | ||
| Line 1047: | Line 1045: | ||
| ]; | ]; | ||
| - | result := CalculatePythonExpression (String $"( | + | result := CalculatePythonExpression $"( |
| inputTable = dinamica.inputs['t1'] | inputTable = dinamica.inputs['t1'] | ||
| header = inputTable[0] | header = inputTable[0] | ||
| Line 1060: | Line 1058: | ||
| dinamica.outputs['reshapedTable'] = dinamica.prepareTable(newTable, 1) | dinamica.outputs['reshapedTable'] = dinamica.prepareTable(newTable, 1) | ||
| - | )") {{ | + | )" {{ |
| NumberTable myTable 1; | NumberTable myTable 1; | ||
| }}; | }}; | ||