Array model: Difference between revisions

Most APLs, flat or nested, implicitly store simple numeric arrays as one of many [[numeric type]]s. When a numeric array is formed from numbers with different types, all numbers are converted to a common type in order to be represented as a flat array. If the hierarchy of numeric types is not strict, that is, there are some pairs of numeric types for which neither type is a subset of the other, then this coercion may affect the behavior of the numbers in the array. For example, [[J]] on a 64-bit machine uses both 64-bit integers and [[wikipedia:IEEE_754|double-precision floats]]. [[Catenate|Catenating]] the two results in an array of doubles, which will lose precision for integers whose absolute value is larger than 2⁵³. In [[Dyalog APL]] a similar issue occurs with [[decimal float]]s and [[complex number]]s: combining the two results in an array of complex numbers, but this loses precision since Dyalog's complex numbers are stored as pairs of double-precision floats and its 128-bit decimal floats have higher precision that doubles.