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(v0.7.1.9035) cephalosporins and unit tests

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dr. M.S. (Matthijs) Berends
2019-08-11 19:07:26 +02:00
parent 3f5828e74a
commit 1d423cca89
38 changed files with 382 additions and 361 deletions
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36
vignettes/benchmarks.Rmd
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@ -110,7 +110,7 @@ Uncommon microorganisms take a lot more time than common microorganisms. To reli
### Repetitive results
Repetitive results are unique values that are present more than once. Unique values will only be calculated once by `as.mo()`. We will use `mo_fullname()` for this test - a helper function that returns the full microbial name (genus, species and possibly subspecies) which uses `as.mo()` internally.
Repetitive results are unique values that are present more than once. Unique values will only be calculated once by `as.mo()`. We will use `mo_name()` for this test - a helper function that returns the full microbial name (genus, species and possibly subspecies) which uses `as.mo()` internally.
```{r, message = FALSE}
library(dplyr)
@ -132,7 +132,7 @@ length(x)
n_distinct(x)
# now let's see:
run_it <- microbenchmark(mo_fullname(x),
run_it <- microbenchmark(mo_name(x),
times = 10)
print(run_it, unit = "ms", signif = 3)
```
@ -141,22 +141,22 @@ So transforming 500,000 values (!!) of `r n_distinct(x)` unique values only take
### Precalculated results
What about precalculated results? If the input is an already precalculated result of a helper function like `mo_fullname()`, it almost doesn't take any time at all (see 'C' below):
What about precalculated results? If the input is an already precalculated result of a helper function like `mo_name()`, it almost doesn't take any time at all (see 'C' below):
```{r}
run_it <- microbenchmark(A = mo_fullname("B_STPHY_AUR"),
B = mo_fullname("S. aureus"),
C = mo_fullname("Staphylococcus aureus"),
run_it <- microbenchmark(A = mo_name("B_STPHY_AUR"),
B = mo_name("S. aureus"),
C = mo_name("Staphylococcus aureus"),
times = 10)
print(run_it, unit = "ms", signif = 3)
```
So going from `mo_fullname("Staphylococcus aureus")` to `"Staphylococcus aureus"` takes `r format(round(run_it %>% filter(expr == "C") %>% pull(time) %>% median() / 1e9, 4), scientific = FALSE)` seconds - it doesn't even start calculating *if the result would be the same as the expected resulting value*. That goes for all helper functions:
So going from `mo_name("Staphylococcus aureus")` to `"Staphylococcus aureus"` takes `r format(round(run_it %>% filter(expr == "C") %>% pull(time) %>% median() / 1e9, 4), scientific = FALSE)` seconds - it doesn't even start calculating *if the result would be the same as the expected resulting value*. That goes for all helper functions:
```{r}
run_it <- microbenchmark(A = mo_species("aureus"),
B = mo_genus("Staphylococcus"),
C = mo_fullname("Staphylococcus aureus"),
C = mo_name("Staphylococcus aureus"),
D = mo_family("Staphylococcaceae"),
E = mo_order("Bacillales"),
F = mo_class("Bacilli"),
@ -173,19 +173,19 @@ Of course, when running `mo_phylum("Firmicutes")` the function has zero knowledg
When the system language is non-English and supported by this `AMR` package, some functions will have a translated result. This almost does't take extra time:
```{r}
mo_fullname("CoNS", language = "en") # or just mo_fullname("CoNS") on an English system
mo_name("CoNS", language = "en") # or just mo_name("CoNS") on an English system
mo_fullname("CoNS", language = "es") # or just mo_fullname("CoNS") on a Spanish system
mo_name("CoNS", language = "es") # or just mo_name("CoNS") on a Spanish system
mo_fullname("CoNS", language = "nl") # or just mo_fullname("CoNS") on a Dutch system
mo_name("CoNS", language = "nl") # or just mo_name("CoNS") on a Dutch system
run_it <- microbenchmark(en = mo_fullname("CoNS", language = "en"),
de = mo_fullname("CoNS", language = "de"),
nl = mo_fullname("CoNS", language = "nl"),
es = mo_fullname("CoNS", language = "es"),
it = mo_fullname("CoNS", language = "it"),
fr = mo_fullname("CoNS", language = "fr"),
pt = mo_fullname("CoNS", language = "pt"),
run_it <- microbenchmark(en = mo_name("CoNS", language = "en"),
de = mo_name("CoNS", language = "de"),
nl = mo_name("CoNS", language = "nl"),
es = mo_name("CoNS", language = "es"),
it = mo_name("CoNS", language = "it"),
fr = mo_name("CoNS", language = "fr"),
pt = mo_name("CoNS", language = "pt"),
times = 10)
print(run_it, unit = "ms", signif = 4)
```