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age_groups fix

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dr. M.S. (Matthijs) Berends
2019-02-27 11:36:12 +01:00
parent 4ba2ff68e0
commit 54162522bd
41 changed files with 450 additions and 386 deletions
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vignettes/benchmarks.Rmd
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@ -52,7 +52,7 @@ S.aureus <- microbenchmark(as.mo("sau"),
print(S.aureus, unit = "ms", signif = 3)
```
In the table above, all measurements are shown in milliseconds (thousands of seconds). A value of 10 milliseconds means it can determine 100 input values per second. It case of 50 milliseconds, this is only 20 input values per second. The second input is the only one that has to be looked up thoroughly. All the others are known codes (the first is a WHONET code) or common laboratory codes, or common full organism names like the last one.
In the table above, all measurements are shown in milliseconds (thousands of seconds). A value of 5 milliseconds means it can determine 200 input values per second. It case of 100 milliseconds, this is only 10 input values per second. The second input is the only one that has to be looked up thoroughly. All the others are known codes (the first one is a WHONET code) or common laboratory codes, or common full organism names like the last one. Full organism names are always preferred.
To achieve this speed, the `as.mo` function also takes into account the prevalence of human pathogenic microorganisms. The downside is of course that less prevalent microorganisms will be determined less fast. See this example for the ID of *Thermus islandicus* (`B_THERMS_ISL`), a bug probably never found before in humans: