Compare sorting algorithms' performance: Difference between revisions
Content added Content deleted
m (→{{header|J}}) |
m (→{{header|J}}) |
||
| Line 817: | Line 817: | ||
The first version of the code set only a time limit. The builtin sort violated this only when the data overflowed RAM into virtual space, causing a large jump in time affecting also the next data set as the OS restored itself. The timing might be interesting for some other exercise. Here, a maximum data size test was inserted. Arbitrary time is the reasonable choice without details of the J interpreter nor of specific hardware. The radix sort involves putting data directly into the right spot. It is quick! |
The first version of the code set only a time limit. The builtin sort violated this only when the data overflowed RAM into virtual space, causing a large jump in time affecting also the next data set as the OS restored itself. The timing might be interesting for some other exercise. Here, a maximum data size test was inserted. Arbitrary time is the reasonable choice without details of the J interpreter nor of specific hardware. The radix sort involves putting data directly into the right spot. It is quick! |
||
The data fit curves of the character cell graph were combined with GCD function. This explains "1"s or other strange values where these curves intersect. Finally the scatter plots were multiplied by infinity and added to the best fit curves. The points didn't show up well using the same values as the curves. |
The data fit curves of the character cell graph were combined with GCD +. function. This explains "1"s or other strange values where these curves intersect. Finally the scatter plots were multiplied by infinity and added to the best fit curves. The points didn't show up well using the same values as the curves. |
||
=={{header|Python}}== |
=={{header|Python}}== |
||