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      DESCRIPTION
  2. 121
      NEWS.md
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4
DESCRIPTION

@ -1,6 +1,6 @@ @@ -1,6 +1,6 @@
Package: AMR
Version: 1.4.0.9042
Date: 2020-12-21
Version: 1.4.0.9043
Date: 2020-12-22
Title: Antimicrobial Resistance Analysis
Authors@R: c(
person(role = c("aut", "cre"),

121
NEWS.md

@ -1,5 +1,5 @@ @@ -1,5 +1,5 @@
# AMR 1.4.0.9042
## <small>Last updated: 21 December 2020</small>
# AMR 1.4.0.9043
## <small>Last updated: 22 December 2020</small>
### New
* Function `is_new_episode()` to determine patient episodes which are not necessarily based on microorganisms. It also supports grouped variables with e.g. `mutate()`, `filter()` and `summarise()` of the `dplyr` package:
@ -15,8 +15,14 @@ @@ -15,8 +15,14 @@
* Functions `random_mic()`, `random_disk()` and `random_rsi()` for random number generation. They take microorganism names and antibiotic names as input to make generation more realistic.
### Changed
* Reference data used for `as.rsi()` can now be set by the user, using the `reference_data` parameter. This allows for using own interpretation guidelines. The user-set data must have the same structure as `rsi_translation`.
* Some functions are now context-aware when used inside `dplyr` verbs, such as `filter()`, `mutate()` and `summarise()`. This means that then the data parameter does not need to be set anymore. This is the case for the new functions `mo_is_gram_negative()`, `mo_is_gram_positive()`, `mo_is_intrinsic_resistant()` and for the existing functions `first_isolate()`, `key_antibiotics()`, `mdro()`, `brmo()`, `mrgn()`, `mdr_tb()`, `mdr_cmi2012()`, `eucast_exceptional_phenotypes()`. This was already the case for antibiotic selection functions (such as using `penicillins()` in `dplyr::select()`).
* Interpretation of antimicrobial resistance - `as.rsi()`:
* Reference data used for `as.rsi()` can now be set by the user, using the `reference_data` argument. This allows for using own interpretation guidelines. The user-set data must have the same structure as `rsi_translation`.
* Better determination of disk zones and MIC values when running `as.rsi()` on a data.frame
* Fix for using `as.rsi()` on a data.frame in older R versions
* `as.rsi()` on a data.frame will not print a message anymore if the values are already clean R/SI values
* If using `as.rsi()` on MICs or disk diffusion while there is intrinsic antimicrobial resistance, a warning will be thrown to remind about this
* Fix for using `as.rsi()` on a `data.frame` that only contains one column for antibiotic interpretations
* Some functions are now context-aware when used inside `dplyr` verbs, such as `filter()`, `mutate()` and `summarise()`. This means that then the data argument does not need to be set anymore. This is the case for the new functions `mo_is_gram_negative()`, `mo_is_gram_positive()`, `mo_is_intrinsic_resistant()` and for the existing functions `first_isolate()`, `key_antibiotics()`, `mdro()`, `brmo()`, `mrgn()`, `mdr_tb()`, `mdr_cmi2012()`, `eucast_exceptional_phenotypes()`. This was already the case for antibiotic selection functions (such as using `penicillins()` in `dplyr::select()`).
```r
# to select first isolates that are Gram-negative
@ -27,23 +33,18 @@ @@ -27,23 +33,18 @@
select(mo, cephalosporins(), aminoglycosides()) %>%
as_tibble()
```
* For all function parameters in the code, it is now defined what the exact type of user input should be (inspired by the [`typed`](https://github.com/moodymudskipper/typed) package). If the user input for a certain function does not meet the requirements for a specific parameter (such as the class or length), an informative error will be thrown. This makes the package more robust and the use of it more reproducible and reliable. In total, more than 400 arguments were defined.
* For all function arguments in the code, it is now defined what the exact type of user input should be (inspired by the [`typed`](https://github.com/moodymudskipper/typed) package). If the user input for a certain function does not meet the requirements for a specific argument (such as the class or length), an informative error will be thrown. This makes the package more robust and the use of it more reproducible and reliable. In total, more than 420 arguments were defined.
* Fix for `set_mo_source()`, that previously would not remember the file location of the original file
* Deprecated function `p_symbol()` that not really fits the scope of this package. It will be removed in a future version. See [here](https://github.com/msberends/AMR/blob/v1.4.0/R/p_symbol.R) for the source code to preserve it.
* Better determination of disk zones and MIC values when running `as.rsi()` on a data.frame
* Updated coagulase-negative staphylococci determination with Becker *et al.* 2020 (PMID 32056452), meaning that the species *S. argensis*, *S. caeli*, *S. debuckii*, *S. edaphicus* and *S. pseudoxylosus* are now all considered CoNS
* Fix for using parameter `reference_df` in `as.mo()` and `mo_*()` functions that contain old microbial codes (from previous package versions)
* Fix for using `as.rsi()` on a data.frame in older R versions
* `as.rsi()` on a data.frame will not print a message anymore if the values are already clean R/SI values
* Fix for using argument `reference_df` in `as.mo()` and `mo_*()` functions that contain old microbial codes (from previous package versions)
* Fixed a bug where `mo_uncertainties()` would not return the results based on the MO matching score
* Fixed a bug where `as.mo()` would not return results for known laboratory codes for microorganisms
* Fixed a bug where `as.ab()` would sometimes fail
* If using `as.rsi()` on MICs or disk diffusion while there is intrinsic antimicrobial resistance, a warning will be thrown to remind about this
* Better tibble printing for MIC values
* Fix for plotting MIC values with `plot()`
* Added `plot()` generic to class `<disk>`
* LA-MRSA and CA-MRSA are now recognised as an abbreviation for *Staphylococcus aureus*, meaning that e.g. `mo_genus("LA-MRSA")` will return `"Staphylococcus"` and `mo_is_gram_positive("LA-MRSA")` will return `TRUE`.
* Fix for using `as.rsi()` on a `data.frame` that only contains one column for antibiotic interpretations
### Other
* All messages and warnings thrown by this package now break sentences on whole words
@ -54,7 +55,7 @@ @@ -54,7 +55,7 @@
# AMR 1.4.0
### New
* Support for 'EUCAST Expert Rules' / 'EUCAST Intrinsic Resistance and Unusual Phenotypes' version 3.2 of May 2020. With this addition to the previously implemented version 3.1 of 2016, the `eucast_rules()` function can now correct for more than 180 different antibiotics and the `mdro()` function can determine multidrug resistance based on more than 150 different antibiotics. All previously implemented versions of the EUCAST rules are now maintained and kept available in this package. The `eucast_rules()` function consequently gained the parameters `version_breakpoints` (at the moment defaults to v10.0, 2020) and `version_expertrules` (at the moment defaults to v3.2, 2020). The `example_isolates` data set now also reflects the change from v3.1 to v3.2. The `mdro()` function now accepts `guideline == "EUCAST3.1"` and `guideline == "EUCAST3.2"`.
* Support for 'EUCAST Expert Rules' / 'EUCAST Intrinsic Resistance and Unusual Phenotypes' version 3.2 of May 2020. With this addition to the previously implemented version 3.1 of 2016, the `eucast_rules()` function can now correct for more than 180 different antibiotics and the `mdro()` function can determine multidrug resistance based on more than 150 different antibiotics. All previously implemented versions of the EUCAST rules are now maintained and kept available in this package. The `eucast_rules()` function consequently gained the arguments `version_breakpoints` (at the moment defaults to v10.0, 2020) and `version_expertrules` (at the moment defaults to v3.2, 2020). The `example_isolates` data set now also reflects the change from v3.1 to v3.2. The `mdro()` function now accepts `guideline == "EUCAST3.1"` and `guideline == "EUCAST3.2"`.
* A new vignette and website page with info about all our public and freely available data sets, that can be downloaded as flat files or in formats for use in R, SPSS, SAS, Stata and Excel: https://msberends.github.io/AMR/articles/datasets.html
* Data set `intrinsic_resistant`. This data set contains all bug-drug combinations where the 'bug' is intrinsic resistant to the 'drug' according to the latest EUCAST insights. It contains just two columns: `microorganism` and `antibiotic`.
@ -86,7 +87,7 @@ @@ -86,7 +87,7 @@
```
* Cleaning columns in a data.frame now allows you to specify those columns with tidy selection, e.g. `as.rsi(df, col1:col9)`
* Big speed improvement for interpreting MIC values and disk zone diameters. When interpreting 5,000 MIC values of two antibiotics (10,000 values in total), our benchmarks showed a total run time going from 80.7-85.1 seconds to 1.8-2.0 seconds.
* Added parameter 'add_intrinsic_resistance' (defaults to `FALSE`), that considers intrinsic resistance according to EUCAST
* Added argument 'add_intrinsic_resistance' (defaults to `FALSE`), that considers intrinsic resistance according to EUCAST
* Fixed a bug where in EUCAST rules the breakpoint for R would be interpreted as ">=" while this should have been "<"
* Added intelligent data cleaning to `as.disk()`, so numbers can also be extracted from text and decimal numbers will always be rounded up:
```r
@ -97,7 +98,7 @@ @@ -97,7 +98,7 @@
* Improvements for `as.mo()`:
* A completely new matching score for ambiguous user input, using `mo_matching_score()`. Any user input value that could mean more than one taxonomic entry is now considered 'uncertain'. Instead of a warning, a message will be thrown and the accompanying `mo_uncertainties()` has been changed completely; it now prints all possible candidates with their matching score.
* Big speed improvement for already valid microorganism ID. This also means an significant speed improvement for using `mo_*` functions like `mo_name()` on microoganism IDs.
* Added parameter `ignore_pattern` to `as.mo()` which can also be given to `mo_*` functions like `mo_name()`, to exclude known non-relevant input from analysing. This can also be set with the option `AMR_ignore_pattern`.
* Added argument `ignore_pattern` to `as.mo()` which can also be given to `mo_*` functions like `mo_name()`, to exclude known non-relevant input from analysing. This can also be set with the option `AMR_ignore_pattern`.
* `get_locale()` now uses at default `Sys.getenv("LANG")` or, if `LANG` is not set, `Sys.getlocale()`. This can be overwritten by setting the option `AMR_locale`.
* Big speed improvement for `eucast_rules()`
* Overall speed improvement by tweaking joining functions
@ -108,7 +109,7 @@ @@ -108,7 +109,7 @@
* Updated the documentation of the `WHONET` data set to clarify that all patient names are fictitious
* Small `as.ab()` algorithm improvements
* Fix for combining MIC values with raw numbers, i.e. `c(as.mic(2), 2)` previously failed but now returns a valid MIC class
* `ggplot_rsi()` and `geom_rsi()` gained parameters `minimum` and `language`, to influence the internal use of `rsi_df()`
* `ggplot_rsi()` and `geom_rsi()` gained arguments `minimum` and `language`, to influence the internal use of `rsi_df()`
* Changes in the `antibiotics` data set:
* Updated oral and parental DDDs from the WHOCC
* Added abbreviation "piptazo" to 'Piperacillin/tazobactam' (TZP)
@ -116,7 +117,7 @@ @@ -116,7 +117,7 @@
* 'Penicillin V' (for oral use, code `PNV`) was removed, since its actual entry 'Phenoxymethylpenicillin' (code `PHN`) already existed
* The group name (`antibiotics$group`) of 'Linezolid' (`LNZ`), 'Cycloserine' (`CYC`), 'Tedizolid' (`TZD`) and 'Thiacetazone' (`THA`) is now "Oxazolidinones" instead of "Other antibacterials"
* Added support for using `unique()` on classes `<rsi>`, `<mic>`, `<disk>`, `<ab>` and `<mo>`
* Added parameter `excess` to the `kurtosis()` function (defaults to `FALSE`), to return the *excess kurtosis*, defined as the kurtosis minus three.
* Added argument `excess` to the `kurtosis()` function (defaults to `FALSE`), to return the *excess kurtosis*, defined as the kurtosis minus three.
### Other
* Removed functions `portion_R()`, `portion_S()` and `portion_I()` that were deprecated since version 0.9.0 (November 2019) and were replaced with `proportion_R()`, `proportion_S()` and `proportion_I()`
@ -141,7 +142,7 @@ @@ -141,7 +142,7 @@
* Added official antimicrobial names to all `filter_ab_class()` functions, such as `filter_aminoglycosides()`
* Added antibiotics code "FOX1" for cefoxitin screening (abbreviation "cfsc") to the `antibiotics` data set
* Added Monuril as trade name for fosfomycin
* Added parameter `conserve_capped_values` to `as.rsi()` for interpreting MIC values - it makes sure that values starting with "<" (but not "<=") will always return "S" and values starting with ">" (but not ">=") will always return "R". The default behaviour of `as.rsi()` has not changed, so you need to specifically do `as.rsi(..., conserve_capped_values = TRUE)`.
* Added argument `conserve_capped_values` to `as.rsi()` for interpreting MIC values - it makes sure that values starting with "<" (but not "<=") will always return "S" and values starting with ">" (but not ">=") will always return "R". The default behaviour of `as.rsi()` has not changed, so you need to specifically do `as.rsi(..., conserve_capped_values = TRUE)`.
### Changed
* Big speed improvement for using any function on microorganism codes from earlier package versions (prior to `AMR` v1.2.0), such as `as.mo()`, `mo_name()`, `first_isolate()`, `eucast_rules()`, `mdro()`, etc.
@ -249,7 +250,7 @@ @@ -249,7 +250,7 @@
mutate_at(vars(antibiotic1:antibiotic25), as.rsi, mo = .$mybacteria)
```
* Added antibiotic abbreviations for a laboratory manufacturer (GLIMS) for cefuroxime, cefotaxime, ceftazidime, cefepime, cefoxitin and trimethoprim/sulfamethoxazole
* Added `uti` (as abbreviation of urinary tract infections) as parameter to `as.rsi()`, so interpretation of MIC values and disk zones can be made dependent on isolates specifically from UTIs
* Added `uti` (as abbreviation of urinary tract infections) as argument to `as.rsi()`, so interpretation of MIC values and disk zones can be made dependent on isolates specifically from UTIs
* Info printing in functions `eucast_rules()`, `first_isolate()`, `mdro()` and `resistance_predict()` will now at default only print when R is in an interactive mode (i.e. not in RMarkdown)
# AMR 1.0.0
@ -369,7 +370,7 @@ This software is now out of beta and considered stable. Nonetheless, this packag @@ -369,7 +370,7 @@ This software is now out of beta and considered stable. Nonetheless, this packag
# AMR 0.8.0
### Breaking
* Determination of first isolates now **excludes** all 'unknown' microorganisms at default, i.e. microbial code `"UNKNOWN"`. They can be included with the new parameter `include_unknown`:
* Determination of first isolates now **excludes** all 'unknown' microorganisms at default, i.e. microbial code `"UNKNOWN"`. They can be included with the new argument `include_unknown`:
```r
first_isolate(..., include_unknown = TRUE)
```
@ -420,7 +421,7 @@ This software is now out of beta and considered stable. Nonetheless, this packag @@ -420,7 +421,7 @@ This software is now out of beta and considered stable. Nonetheless, this packag
```r
format(x, combine_IR = FALSE)
```
* Additional way to calculate co-resistance, i.e. when using multiple antimicrobials as input for `portion_*` functions or `count_*` functions. This can be used to determine the empiric susceptibility of a combination therapy. A new parameter `only_all_tested` (**which defaults to `FALSE`**) replaces the old `also_single_tested` and can be used to select one of the two methods to count isolates and calculate portions. The difference can be seen in this example table (which is also on the `portion` and `count` help pages), where the %SI is being determined:
* Additional way to calculate co-resistance, i.e. when using multiple antimicrobials as input for `portion_*` functions or `count_*` functions. This can be used to determine the empiric susceptibility of a combination therapy. A new argument `only_all_tested` (**which defaults to `FALSE`**) replaces the old `also_single_tested` and can be used to select one of the two methods to count isolates and calculate portions. The difference can be seen in this example table (which is also on the `portion` and `count` help pages), where the %SI is being determined:
```r
# --------------------------------------------------------------------
@ -476,13 +477,13 @@ This software is now out of beta and considered stable. Nonetheless, this packag @@ -476,13 +477,13 @@ This software is now out of beta and considered stable. Nonetheless, this packag
* Removed deprecated functions `abname()`, `ab_official()`, `atc_name()`, `atc_official()`, `atc_property()`, `atc_tradenames()`, `atc_trivial_nl()`
* Fix and speed improvement for `mo_shortname()`
* Fix for using `mo_*` functions where the coercion uncertainties and failures would not be available through `mo_uncertainties()` and `mo_failures()` anymore
* Deprecated the `country` parameter of `mdro()` in favour of the already existing `guideline` parameter to support multiple guidelines within one country
* Deprecated the `country` argument of `mdro()` in favour of the already existing `guideline` argument to support multiple guidelines within one country
* The `name` of `RIF` is now Rifampicin instead of Rifampin
* The `antibiotics` data set is now sorted by name and all cephalosporins now have their generation between brackets
* Speed improvement for `guess_ab_col()` which is now 30 times faster for antibiotic abbreviations
* Improved `filter_ab_class()` to be more reliable and to support 5th generation cephalosporins
* Function `availability()` now uses `portion_R()` instead of `portion_IR()`, to comply with EUCAST insights
* Functions `age()` and `age_groups()` now have a `na.rm` parameter to remove empty values
* Functions `age()` and `age_groups()` now have a `na.rm` argument to remove empty values
* Renamed function `p.symbol()` to `p_symbol()` (the former is now deprecated and will be removed in a future version)
* Using negative values for `x` in `age_groups()` will now introduce `NA`s and not return an error anymore
* Fix for determining the system's language
@ -577,12 +578,12 @@ This software is now out of beta and considered stable. Nonetheless, this packag @@ -577,12 +578,12 @@ This software is now out of beta and considered stable. Nonetheless, this packag
* All `atc_*` functions are superceded by `ab_*` functions
* All output will be translated by using an included translation file which [can be viewed here](https://github.com/msberends/AMR/blob/master/data-raw/translations.tsv)
* Improvements to plotting AMR results with `ggplot_rsi()`:
* New parameter `colours` to set the bar colours
* New parameters `title`, `subtitle`, `caption`, `x.title` and `y.title` to set titles and axis descriptions
* New argument `colours` to set the bar colours
* New arguments `title`, `subtitle`, `caption`, `x.title` and `y.title` to set titles and axis descriptions
* Improved intelligence of looking up antibiotic columns in a data set using `guess_ab_col()`
* Added ~5,000 more old taxonomic names to the `microorganisms.old` data set, which leads to better results finding when using the `as.mo()` function
* This package now honours the new EUCAST insight (2019) that S and I are but classified as susceptible, where I is defined as 'increased exposure' and not 'intermediate' anymore. For functions like `portion_df()` and `count_df()` this means that their new parameter `combine_SI` is TRUE at default. Our plotting function `ggplot_rsi()` also reflects this change since it uses `count_df()` internally.
* The `age()` function gained a new parameter `exact` to determine ages with decimals
* This package now honours the new EUCAST insight (2019) that S and I are but classified as susceptible, where I is defined as 'increased exposure' and not 'intermediate' anymore. For functions like `portion_df()` and `count_df()` this means that their new argument `combine_SI` is TRUE at default. Our plotting function `ggplot_rsi()` also reflects this change since it uses `count_df()` internally.
* The `age()` function gained a new argument `exact` to determine ages with decimals
* Removed deprecated functions `guess_mo()`, `guess_atc()`, `EUCAST_rules()`, `interpretive_reading()`, `rsi()`
* Frequency tables (`freq()`):
* speed improvement for microbial IDs
@ -626,11 +627,11 @@ This software is now out of beta and considered stable. Nonetheless, this packag @@ -626,11 +627,11 @@ This software is now out of beta and considered stable. Nonetheless, this packag
We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.gitlab.io/AMR/) (built with the great [`pkgdown`](https://pkgdown.r-lib.org/))
* Contains the complete manual of this package and all of its functions with an explanation of their parameters
* Contains the complete manual of this package and all of its functions with an explanation of their arguments
* Contains a comprehensive tutorial about how to conduct antimicrobial resistance analysis, import data from WHONET or SPSS and many more.
#### New
* **BREAKING**: removed deprecated functions, parameters and references to 'bactid'. Use `as.mo()` to identify an MO code.
* **BREAKING**: removed deprecated functions, arguments and references to 'bactid'. Use `as.mo()` to identify an MO code.
* Catalogue of Life as a new taxonomic source for data about microorganisms, which also contains all ITIS data we used previously. The `microorganisms` data set now contains:
* All ~55,000 (sub)species from the kingdoms of Archaea, Bacteria and Protozoa
* All ~3,000 (sub)species from these orders of the kingdom of Fungi: Eurotiales, Onygenales, Pneumocystales, Saccharomycetales and Schizosaccharomycetales (covering at least like all species of *Aspergillus*, *Candida*, *Pneumocystis*, *Saccharomyces* and *Trichophyton*)
@ -643,7 +644,7 @@ We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.git @@ -643,7 +644,7 @@ We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.git
* New function `mo_rank()` for the taxonomic rank (genus, species, infraspecies, etc.)
* New function `mo_url()` to get the direct URL of a species from the Catalogue of Life
* Support for data from [WHONET](https://whonet.org/) and [EARS-Net](https://www.ecdc.europa.eu/en/about-us/partnerships-and-networks/disease-and-laboratory-networks/ears-net) (European Antimicrobial Resistance Surveillance Network):
* Exported files from WHONET can be read and used in this package. For functions like `first_isolate()` and `eucast_rules()`, all parameters will be filled in automatically.
* Exported files from WHONET can be read and used in this package. For functions like `first_isolate()` and `eucast_rules()`, all arguments will be filled in automatically.
* This package now knows all antibiotic abbrevations by EARS-Net (which are also being used by WHONET) - the `antibiotics` data set now contains a column `ears_net`.
* The function `as.mo()` now knows all WHONET species abbreviations too, because almost 2,000 microbial abbreviations were added to the `microorganisms.codes` data set.
* New filters for antimicrobial classes. Use these functions to filter isolates on results in one of more antibiotics from a specific class:
@ -764,14 +765,14 @@ We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.git @@ -764,14 +765,14 @@ We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.git
* Console will return the percentage of uncoercable input
* Function `first_isolate()`:
* Fixed a bug where distances between dates would not be calculated right - in the `septic_patients` data set this yielded a difference of 0.15% more isolates
* Will now use a column named like "patid" for the patient ID (parameter `col_patientid`), when this parameter was left blank
* Will now use a column named like "key(...)ab" or "key(...)antibiotics" for the key antibiotics (parameter `col_keyantibiotics()`), when this parameter was left blank
* Removed parameter `output_logical`, the function will now always return a logical value
* Renamed parameter `filter_specimen` to `specimen_group`, although using `filter_specimen` will still work
* A note to the manual pages of the `portion` functions, that low counts can influence the outcome and that the `portion` functions may camouflage this, since they only return the portion (albeit being dependent on the `minimum` parameter)
* Will now use a column named like "patid" for the patient ID (argument `col_patientid`), when this argument was left blank
* Will now use a column named like "key(...)ab" or "key(...)antibiotics" for the key antibiotics (argument `col_keyantibiotics()`), when this argument was left blank
* Removed argument `output_logical`, the function will now always return a logical value
* Renamed argument `filter_specimen` to `specimen_group`, although using `filter_specimen` will still work
* A note to the manual pages of the `portion` functions, that low counts can influence the outcome and that the `portion` functions may camouflage this, since they only return the portion (albeit being dependent on the `minimum` argument)
* Merged data sets `microorganisms.certe` and `microorganisms.umcg` into `microorganisms.codes`
* Function `mo_taxonomy()` now contains the kingdom too
* Reduce false positives for `is.rsi.eligible()` using the new `threshold` parameter
* Reduce false positives for `is.rsi.eligible()` using the new `threshold` argument
* New colours for `scale_rsi_colours()`
* Summaries of class `mo` will now return the top 3 and the unique count, e.g. using `summary(mo)`
* Small text updates to summaries of class `rsi` and `mic`
@ -796,16 +797,16 @@ We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.git @@ -796,16 +797,16 @@ We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.git
freq(mo_genus(mo))
```
* Header info is now available as a list, with the `header` function
* The parameter `header` is now set to `TRUE` at default, even for markdown
* The argument `header` is now set to `TRUE` at default, even for markdown
* Added header info for class `mo` to show unique count of families, genera and species
* Now honours the `decimal.mark` setting, which just like `format` defaults to `getOption("OutDec")`
* The new `big.mark` parameter will at default be `","` when `decimal.mark = "."` and `"."` otherwise
* The new `big.mark` argument will at default be `","` when `decimal.mark = "."` and `"."` otherwise
* Fix for header text where all observations are `NA`
* New parameter `droplevels` to exclude empty factor levels when input is a factor
* New argument `droplevels` to exclude empty factor levels when input is a factor
* Factor levels will be in header when present in input data (maximum of 5)
* Fix for using `select()` on frequency tables
* Function `scale_y_percent()` now contains the `limits` parameter
* Automatic parameter filling for `mdro()`, `key_antibiotics()` and `eucast_rules()`
* Function `scale_y_percent()` now contains the `limits` argument
* Automatic argument filling for `mdro()`, `key_antibiotics()` and `eucast_rules()`
* Updated examples for resistance prediction (`resistance_predict()` function)
* Fix for `as.mic()` to support more values ending in (several) zeroes
* if using different lengths of pattern and x in `%like%`, it will now return the call
@ -818,7 +819,7 @@ We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.git @@ -818,7 +819,7 @@ We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.git
#### New
* Repository moved to GitLab
* Function `count_all` to get all available isolates (that like all `portion_*` and `count_*` functions also supports `summarise` and `group_by`), the old `n_rsi` is now an alias of `count_all`
* Function `get_locale` to determine language for language-dependent output for some `mo_*` functions. This is now the default value for their `language` parameter, by which the system language will be used at default.
* Function `get_locale` to determine language for language-dependent output for some `mo_*` functions. This is now the default value for their `language` argument, by which the system language will be used at default.
* Data sets `microorganismsDT`, `microorganisms.prevDT`, `microorganisms.unprevDT` and `microorganisms.oldDT` to improve the speed of `as.mo`. They are for reference only, since they are primarily for internal use of `as.mo`.
* Function `read.4D` to read from the 4D database of the MMB department of the UMCG
* Functions `mo_authors` and `mo_year` to get specific values about the scientific reference of a taxonomic entry
@ -828,12 +829,12 @@ We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.git @@ -828,12 +829,12 @@ We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.git
* `EUCAST_rules` was renamed to `eucast_rules`, the old function still exists as a deprecated function
* Big changes to the `eucast_rules` function:
* Now also applies rules from the EUCAST 'Breakpoint tables for bacteria', version 8.1, 2018, https://www.eucast.org/clinical_breakpoints/ (see Source of the function)
* New parameter `rules` to specify which rules should be applied (expert rules, breakpoints, others or all)
* New parameter `verbose` which can be set to `TRUE` to get very specific messages about which columns and rows were affected
* New argument `rules` to specify which rules should be applied (expert rules, breakpoints, others or all)
* New argument `verbose` which can be set to `TRUE` to get very specific messages about which columns and rows were affected
* Better error handling when rules cannot be applied (i.e. new values could not be inserted)
* The number of affected values will now only be measured once per row/column combination
* Data set `septic_patients` now reflects these changes
* Added parameter `pipe` for piperacillin (J01CA12), also to the `mdro` function
* Added argument `pipe` for piperacillin (J01CA12), also to the `mdro` function
* Small fixes to EUCAST clinical breakpoint rules
* Added column `kingdom` to the microorganisms data set, and function `mo_kingdom` to look up values
* Tremendous speed improvement for `as.mo` (and subsequently all `mo_*` functions), as empty values wil be ignored *a priori*
@ -845,10 +846,10 @@ We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.git @@ -845,10 +846,10 @@ We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.git
as.mo("S. spp") # B_STPHY
mo_fullname("S. species") # "Staphylococcus species"
```
* Added parameter `combine_IR` (TRUE/FALSE) to functions `portion_df` and `count_df`, to indicate that all values of I and R must be merged into one, so the output only consists of S vs. IR (susceptible vs. non-susceptible)
* Added argument `combine_IR` (TRUE/FALSE) to functions `portion_df` and `count_df`, to indicate that all values of I and R must be merged into one, so the output only consists of S vs. IR (susceptible vs. non-susceptible)
* Fix for `portion_*(..., as_percent = TRUE)` when minimal number of isolates would not be met
* Added parameter `also_single_tested` for `portion_*` and `count_*` functions to also include cases where not all antibiotics were tested but at least one of the tested antibiotics includes the target antimicribial interpretation, see `?portion`
* Using `portion_*` functions now throws a warning when total available isolate is below parameter `minimum`
* Added argument `also_single_tested` for `portion_*` and `count_*` functions to also include cases where not all antibiotics were tested but at least one of the tested antibiotics includes the target antimicribial interpretation, see `?portion`
* Using `portion_*` functions now throws a warning when total available isolate is below argument `minimum`
* Functions `as.mo`, `as.rsi`, `as.mic`, `as.atc` and `freq` will not set package name as attribute anymore
* Frequency tables - `freq()`:
* Support for grouping variables, test with:
@ -867,17 +868,17 @@ We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.git @@ -867,17 +868,17 @@ We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.git
* Now prints in markdown at default in non-interactive sessions
* No longer adds the factor level column and sorts factors on count again
* Support for class `difftime`
* New parameter `na`, to choose which character to print for empty values
* New parameter `header` to turn the header info off (default when `markdown = TRUE`)
* New parameter `title` to manually setbthe title of the frequency table
* `first_isolate` now tries to find columns to use as input when parameters are left blank
* New argument `na`, to choose which character to print for empty values
* New argument `header` to turn the header info off (default when `markdown = TRUE`)
* New argument `title` to manually setbthe title of the frequency table
* `first_isolate` now tries to find columns to use as input when arguments are left blank
* Improvements for MDRO algorithm (function `mdro`)
* Data set `septic_patients` is now a `data.frame`, not a tibble anymore
* Removed diacritics from all authors (columns `microorganisms$ref` and `microorganisms.old$ref`) to comply with CRAN policy to only allow ASCII characters
* Fix for `mo_property` not working properly
* Fix for `eucast_rules` where some Streptococci would become ceftazidime R in EUCAST rule 4.5
* Support for named vectors of class `mo`, useful for `top_freq()`
* `ggplot_rsi` and `scale_y_percent` have `breaks` parameter
* `ggplot_rsi` and `scale_y_percent` have `breaks` argument
* AI improvements for `as.mo`:
* `"CRS"` -> *Stenotrophomonas maltophilia*
* `"CRSM"` -> *Stenotrophomonas maltophilia*
@ -944,7 +945,7 @@ We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.git @@ -944,7 +945,7 @@ We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.git
# min median max neval
# 0.01817717 0.01843957 0.03878077 100
```
* Added parameter `reference_df` for `as.mo`, so users can supply their own microbial IDs, name or codes as a reference table
* Added argument `reference_df` for `as.mo`, so users can supply their own microbial IDs, name or codes as a reference table
* Renamed all previous references to `bactid` to `mo`, like:
* Column names inputs of `EUCAST_rules`, `first_isolate` and `key_antibiotics`
* Column names of datasets `microorganisms` and `septic_patients`
@ -973,7 +974,7 @@ We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.git @@ -973,7 +974,7 @@ We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.git
* Fix for `as.mic` for values ending in zeroes after a real number
* Small fix where *B. fragilis* would not be found in the `microorganisms.umcg` data set
* Added `prevalence` column to the `microorganisms` data set
* Added parameters `minimum` and `as_percent` to `portion_df`
* Added arguments `minimum` and `as_percent` to `portion_df`
* Support for quasiquotation in the functions series `count_*` and `portions_*`, and `n_rsi`. This allows to check for more than 2 vectors or columns.
```r
septic_patients %>% select(amox, cipr) %>% count_IR()
@ -984,12 +985,12 @@ We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.git @@ -984,12 +985,12 @@ We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.git
septic_patients %>% portion_S(amcl, gent)
septic_patients %>% portion_S(amcl, gent, pita)
```
* Edited `ggplot_rsi` and `geom_rsi` so they can cope with `count_df`. The new `fun` parameter has value `portion_df` at default, but can be set to `count_df`.
* Edited `ggplot_rsi` and `geom_rsi` so they can cope with `count_df`. The new `fun` argument has value `portion_df` at default, but can be set to `count_df`.
* Fix for `ggplot_rsi` when the `ggplot2` package was not loaded
* Added datalabels function `labels_rsi_count` to `ggplot_rsi`
* Added possibility to set any parameter to `geom_rsi` (and `ggplot_rsi`) so you can set your own preferences
* Added possibility to set any argument to `geom_rsi` (and `ggplot_rsi`) so you can set your own preferences
* Fix for joins, where predefined suffices would not be honoured
* Added parameter `quote` to the `freq` function
* Added argument `quote` to the `freq` function
* Added generic function `diff` for frequency tables
* Added longest en shortest character length in the frequency table (`freq`) header of class `character`
* Support for types (classes) list and matrix for `freq`
@ -1046,7 +1047,7 @@ We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.git @@ -1046,7 +1047,7 @@ We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.git
#### Changed
* Improvements for forecasting with `resistance_predict` and added more examples
* More antibiotics added as parameters for EUCAST rules
* More antibiotics added as arguments for EUCAST rules
* Updated version of the `septic_patients` data set to better reflect the reality
* Pretty printing for tibbles removed as it is not really the scope of this package
* Printing of `mic` and `rsi` classes now returns all values - use `freq` to check distributions
@ -1054,7 +1055,7 @@ We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.git @@ -1054,7 +1055,7 @@ We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.git
* Column names for the `key_antibiotics` function are now generic: 6 for broadspectrum ABs, 6 for Gram-positive specific and 6 for Gram-negative specific ABs
* Speed improvement for the `abname` function
* `%like%` now supports multiple patterns
* Frequency tables are now actual `data.frame`s with altered console printing to make it look like a frequency table. Because of this, the parameter `toConsole` is not longer needed.
* Frequency tables are now actual `data.frame`s with altered console printing to make it look like a frequency table. Because of this, the argument `toConsole` is not longer needed.
* Fix for `freq` where the class of an item would be lost
* Small translational improvements to the `septic_patients` dataset and the column `bactid` now has the new class `"bactid"`
* Small improvements to the `microorganisms` dataset (especially for *Salmonella*) and the column `bactid` now has the new class `"bactid"`
@ -1102,7 +1103,7 @@ We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.git @@ -1102,7 +1103,7 @@ We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.git
* Added support for character vector in `join` functions
* Added warnings when a join results in more rows after than before the join
* Altered `%like%` to make it case insensitive
* For parameters of functions `first_isolate` and `EUCAST_rules` column names are now case-insensitive
* For arguments of functions `first_isolate` and `EUCAST_rules` column names are now case-insensitive
* Functions `as.rsi` and `as.mic` now add the package name and version as attributes
#### Other

22
R/aa_helper_functions.R

@ -250,13 +250,22 @@ word_wrap <- function(..., @@ -250,13 +250,22 @@ word_wrap <- function(...,
width = 0.95 * getOption("width"),
extra_indent = 0) {
msg <- paste0(c(...), collapse = "")
# replace new lines to add them again later
msg <- gsub("\n", "*|*", msg, fixed = TRUE)
if (isTRUE(as_note)) {
msg <- paste0("NOTE: ", gsub("^note:? ?", "", msg, ignore.case = TRUE))
}
if (msg %like% "\n") {
# run word_wraps() over every line here, bind them and return again
return(paste0(sapply(trimws(unlist(strsplit(msg, "\n")), which = "right"),
word_wrap,
add_fn = add_fn,
as_note = FALSE,
width = width,
extra_indent = extra_indent),
collapse = "\n"))
}
# we need to correct for already applied style, that adds text like "\033[31m\"
msg_stripped <- font_stripstyle(msg)
# where are the spaces now?
@ -284,7 +293,7 @@ word_wrap <- function(..., @@ -284,7 +293,7 @@ word_wrap <- function(...,
indentation <- 0 + extra_indent
}
msg <- gsub("\n", paste0("\n", strrep(" ", indentation)), msg, fixed = TRUE)
msg <- gsub("*|*", paste0("*|*", strrep(" ", indentation)), msg, fixed = TRUE)
# msg <- gsub("*|*", paste0("*|*", strrep(" ", indentation)), msg, fixed = TRUE)
# remove trailing empty characters
msg <- gsub("(\n| )+$", "", msg)
@ -297,9 +306,6 @@ word_wrap <- function(..., @@ -297,9 +306,6 @@ word_wrap <- function(...,
}
}
# place back spaces
msg <- gsub("*|*", "\n", msg, fixed = TRUE)
# format backticks
msg <- gsub("(`.+?`)", font_grey_bg("\\1"), msg)
@ -629,7 +635,7 @@ font_grey <- function(..., collapse = " ") { @@ -629,7 +635,7 @@ font_grey <- function(..., collapse = " ") {
try_colour(..., before = "\033[38;5;249m", after = "\033[39m", collapse = collapse)
}
font_grey_bg <- function(..., collapse = " ") {
try_colour(..., before = "\033[48;5;255m", after = "\033[49m", collapse = collapse)
try_colour(..., before = "\033[48;5;254m", after = "\033[49m", collapse = collapse)
}
font_green_bg <- function(..., collapse = " ") {
try_colour(..., before = "\033[42m", after = "\033[49m", collapse = collapse)
@ -875,6 +881,6 @@ str2lang <- function(s) { @@ -875,6 +881,6 @@ str2lang <- function(s) {
isNamespaceLoaded <- function(pkg) {
pkg %in% loadedNamespaces()
}
lengths = function(x, use.names = TRUE) {
lengths <- function(x, use.names = TRUE) {
vapply(x, length, FUN.VALUE = NA_integer_, USE.NAMES = use.names)
}

8
R/ab_from_text.R

@ -32,21 +32,21 @@ @@ -32,21 +32,21 @@
#' @param collapse character to pass on to `paste(..., collapse = ...)` to only return one character per element of `text`, see *Examples*
#' @param translate_ab if `type = "drug"`: a column name of the [antibiotics] data set to translate the antibiotic abbreviations to, using [ab_property()]. Defaults to `FALSE`. Using `TRUE` is equal to using "name".
#' @param thorough_search logical to indicate whether the input must be extensively searched for misspelling and other faulty input values. Setting this to `TRUE` will take considerably more time than when using `FALSE`. At default, it will turn `TRUE` when all input elements contain a maximum of three words.
#' @param ... parameters passed on to [as.ab()]
#' @param ... arguments passed on to [as.ab()]
#' @details This function is also internally used by [as.ab()], although it then only searches for the first drug name and will throw a note if more drug names could have been returned.
#'
#' ## Parameter `type`
#' ## Argument `type`
#' At default, the function will search for antimicrobial drug names. All text elements will be searched for official names, ATC codes and brand names. As it uses [as.ab()] internally, it will correct for misspelling.
#'
#' With `type = "dose"` (or similar, like "dosing", "doses"), all text elements will be searched for numeric values that are higher than 100 and do not resemble years. The output will be numeric. It supports any unit (g, mg, IE, etc.) and multiple values in one clinical text, see *Examples*.
#'
#' With `type = "administration"` (or abbreviations, like "admin", "adm"), all text elements will be searched for a form of drug administration. It supports the following forms (including common abbreviations): buccal, implant, inhalation, instillation, intravenous, nasal, oral, parenteral, rectal, sublingual, transdermal and vaginal. Abbreviations for oral (such as 'po', 'per os') will become "oral", all values for intravenous (such as 'iv', 'intraven') will become "iv". It supports multiple values in one clinical text, see *Examples*.
#'
#' ## Parameter `collapse`
#' ## Argument `collapse`
#' Without using `collapse`, this function will return a [list]. This can be convenient to use e.g. inside a `mutate()`):\cr
#' `df %>% mutate(abx = ab_from_text(clinical_text))`
#'
#' The returned AB codes can be transformed to official names, groups, etc. with all [`ab_*`][ab_property()] functions such as [ab_name()] and [ab_group()], or by using the `translate_ab` parameter.
#' The returned AB codes can be transformed to official names, groups, etc. with all [`ab_*`][ab_property()] functions such as [ab_name()] and [ab_group()], or by using the `translate_ab` argument.
#'
#' With using `collapse`, this function will return a [character]:\cr
#' `df %>% mutate(abx = ab_from_text(clinical_text, collapse = "|"))`

4
R/ab_property.R

@ -34,7 +34,7 @@ @@ -34,7 +34,7 @@
#' @param administration way of administration, either `"oral"` or `"iv"`
#' @param units a logical to indicate whether the units instead of the DDDs itself must be returned, see Examples
#' @param open browse the URL using [utils::browseURL()]
#' @param ... other parameters passed on to [as.ab()]
#' @param ... other arguments passed on to [as.ab()]
#' @details All output will be [translate]d where possible.
#'
#' The function [ab_url()] will return the direct URL to the official WHO website. A warning will be returned if the required ATC code is not available.
@ -252,7 +252,7 @@ ab_validate <- function(x, property, ...) { @@ -252,7 +252,7 @@ ab_validate <- function(x, property, ...) {
check_dataset_integrity()
# try to catch an error when inputting an invalid parameter
# try to catch an error when inputting an invalid argument
# so the 'call.' can be set to FALSE
tryCatch(x[1L] %in% antibiotics[1, property],
error = function(e) stop(e$message, call. = FALSE))

6
R/age.R

@ -31,7 +31,7 @@ @@ -31,7 +31,7 @@
#' @param reference reference date(s) (defaults to today), will be coerced with [as.POSIXlt()]
#' @param exact a logical to indicate whether age calculation should be exact, i.e. with decimals. It divides the number of days of [year-to-date](https://en.wikipedia.org/wiki/Year-to-date) (YTD) of `x` by the number of days in the year of `reference` (either 365 or 366).
#' @param na.rm a logical to indicate whether missing values should be removed
#' @param ... parameters passed on to [as.POSIXlt()], such as `origin`
#' @param ... arguments passed on to [as.POSIXlt()], such as `origin`
#' @details Ages below 0 will be returned as `NA` with a warning. Ages above 120 will only give a warning.
#' @return An [integer] (no decimals) if `exact = FALSE`, a [double] (with decimals) otherwise
#' @seealso To split ages into groups, use the [age_groups()] function.
@ -98,12 +98,12 @@ age <- function(x, reference = Sys.Date(), exact = FALSE, na.rm = FALSE, ...) { @@ -98,12 +98,12 @@ age <- function(x, reference = Sys.Date(), exact = FALSE, na.rm = FALSE, ...) {
#' Split ages into age groups
#'
#' Split ages into age groups defined by the `split` parameter. This allows for easier demographic (antimicrobial resistance) analysis.
#' Split ages into age groups defined by the `split` argument. This allows for easier demographic (antimicrobial resistance) analysis.
#' @inheritSection lifecycle Stable lifecycle
#' @param x age, e.g. calculated with [age()]
#' @param split_at values to split `x` at, defaults to age groups 0-11, 12-24, 25-54, 55-74 and 75+. See Details.
#' @param na.rm a [logical] to indicate whether missing values should be removed
#' @details To split ages, the input for the `split_at` parameter can be:
#' @details To split ages, the input for the `split_at` argument can be:
#'
#' * A numeric vector. A value of e.g. `c(10, 20)` will split `x` on 0-9, 10-19 and 20+. A value of only `50` will split `x` on 0-49 and 50+.
#' The default is to split on young children (0-11), youth (12-24), young adults (25-54), middle-aged adults (55-74) and elderly (75+).

2
R/amr.R

@ -79,7 +79,7 @@ NULL @@ -79,7 +79,7 @@ NULL
#' Functions to print classes of the `AMR` package.
#' @inheritSection lifecycle Stable lifecycle
#' @inheritSection AMR Read more on our website!
#' @param ... Parameters passed on to functions
#' @param ... Arguments passed on to functions
#' @inheritParams base::plot
#' @inheritParams graphics::barplot
#' @name plot

4
R/atc_online.R

@ -32,9 +32,9 @@ @@ -32,9 +32,9 @@
#' @param administration type of administration when using `property = "Adm.R"`, see Details
#' @param url url of website of the WHOCC. The sign `%s` can be used as a placeholder for ATC codes.
#' @param url_vet url of website of the WHOCC for veterinary medicine. The sign `%s` can be used as a placeholder for ATC_vet codes (that all start with "Q").
#' @param ... parameters to pass on to `atc_property`
#' @param ... arguments to pass on to `atc_property`
#' @details
#' Options for parameter `administration`:
#' Options for argument `administration`:
#'
#' - `"Implant"` = Implant
#' - `"Inhal"` = Inhalation

2
R/eucast_rules.R

@ -81,7 +81,7 @@ format_eucast_version_nr <- function(version, markdown = TRUE) { @@ -81,7 +81,7 @@ format_eucast_version_nr <- function(version, markdown = TRUE) {
#'
#' Important examples include amoxicillin and amoxicillin/clavulanic acid, and trimethoprim and trimethoprim/sulfamethoxazole. Needless to say, for these rules to work, both drugs must be available in the data set.
#'
#' Since these rules are not officially approved by EUCAST, they are not applied at default. To use these rules, include `"other"` to the `rules` parameter, or use `eucast_rules(..., rules = "all")`.
#' Since these rules are not officially approved by EUCAST, they are not applied at default. To use these rules, include `"other"` to the `rules` argument, or use `eucast_rules(..., rules = "all")`.
#' @section Antibiotics:
#' To define antibiotics column names, leave as it is to determine it automatically with [guess_ab_col()] or input a text (case-insensitive), or use `NULL` to skip a column (e.g. `TIC = NULL` to skip ticarcillin). Manually defined but non-existing columns will be skipped with a warning.
#'

16
R/first_isolate.R

@ -37,16 +37,16 @@ @@ -37,16 +37,16 @@
#' @param col_keyantibiotics column name of the key antibiotics to determine first *weighted* isolates, see [key_antibiotics()]. Defaults to the first column that starts with 'key' followed by 'ab' or 'antibiotics' (case insensitive). Use `col_keyantibiotics = FALSE` to prevent this.
#' @param episode_days episode in days after which a genus/species combination will be determined as 'first isolate' again. The default of 365 days is based on the guideline by CLSI, see Source.
#' @param testcodes_exclude character vector with test codes that should be excluded (case-insensitive)
#' @param icu_exclude logical whether ICU isolates should be excluded (rows with value `TRUE` in column `col_icu`)
#' @param specimen_group value in column `col_specimen` to filter on
#' @param icu_exclude logical whether ICU isolates should be excluded (rows with value `TRUE` in the column set with `col_icu`)
#' @param specimen_group value in the column set with `col_specimen` to filter on
#' @param type type to determine weighed isolates; can be `"keyantibiotics"` or `"points"`, see Details
#' @param ignore_I logical to determine whether antibiotic interpretations with `"I"` will be ignored when `type = "keyantibiotics"`, see Details
#' @param points_threshold points until the comparison of key antibiotics will lead to inclusion of an isolate when `type = "points"`, see Details
#' @param info print progress
#' @param include_unknown logical to determine whether 'unknown' microorganisms should be included too, i.e. microbial code `"UNKNOWN"`, which defaults to `FALSE`. For WHONET users, this means that all records with organism code `"con"` (*contamination*) will be excluded at default. Isolates with a microbial ID of `NA` will always be excluded as first isolate.
#' @param ... parameters passed on to [first_isolate()] when using [filter_first_isolate()], or parameters passed on to [key_antibiotics()] when using [filter_first_weighted_isolate()]
#' @param ... arguments passed on to [first_isolate()] when using [filter_first_isolate()], or arguments passed on to [key_antibiotics()] when using [filter_first_weighted_isolate()]
#' @details
#' These functions are context-aware when used inside `dplyr` verbs, such as `filter()`, `mutate()` and `summarise()`. This means that then the `x` parameter can be omitted, please see *Examples*.
#' These functions are context-aware when used inside `dplyr` verbs, such as `filter()`, `mutate()` and `summarise()`. This means that then the `x` argument can be omitted, please see *Examples*.
#'
#' The [first_isolate()] function is a wrapper around the [is_new_episode()] function, but more efficient for data sets containing microorganism codes or names.
#'
@ -80,11 +80,11 @@ @@ -80,11 +80,11 @@
#' @section Key antibiotics:
#' There are two ways to determine whether isolates can be included as first *weighted* isolates which will give generally the same results:
#'
#' 1. Using `type = "keyantibiotics"` and parameter `ignore_I`
#' 1. Using `type = "keyantibiotics"` and argument `ignore_I`
#'
#' Any difference from S to R (or vice versa) will (re)select an isolate as a first weighted isolate. With `ignore_I = FALSE`, also differences from I to S|R (or vice versa) will lead to this. This is a reliable method and 30-35 times faster than method 2. Read more about this in the [key_antibiotics()] function.
#'
#' 2. Using `type = "points"` and parameter `points_threshold`
#' 2. Using `type = "points"` and argument `points_threshold`
#'
#' A difference from I to S|R (or vice versa) means 0.5 points, a difference from S to R (or vice versa) means 1 point. When the sum of points exceeds `points_threshold`, which default to `2`, an isolate will be (re)selected as a first weighted isolate.
#' @rdname first_isolate
@ -184,7 +184,7 @@ first_isolate <- function(x, @@ -184,7 +184,7 @@ first_isolate <- function(x,
dots <- unlist(list(...))
if (length(dots) != 0) {
# backwards compatibility with old parameters
# backwards compatibility with old arguments
dots.names <- dots %pm>% names()
if ("filter_specimen" %in% dots.names) {
specimen_group <- dots[which(dots.names == "filter_specimen")]
@ -238,7 +238,7 @@ first_isolate <- function(x, @@ -238,7 +238,7 @@ first_isolate <- function(x,
check_columns_existance <- function(column, tblname = x) {
if (!is.null(column)) {
stop_ifnot(column %in% colnames(tblname),
"Column `", column, "` not found.", call = FALSE)
"Column '", column, "' not found.", call = FALSE)
}
}

2
R/g.test.R

@ -200,7 +200,7 @@ g.test <- function(x, @@ -200,7 +200,7 @@ g.test <- function(x,
if (any(E < 5) && is.finite(PARAMETER))
warning("G-statistic approximation may be incorrect due to E < 5")
structure(list(statistic = STATISTIC, parameter = PARAMETER,
structure(list(statistic = STATISTIC, argument = PARAMETER,
p.value = PVAL, method = METHOD, data.name = DNAME,
observed = x, expected = E, residuals = (x - E) / sqrt(E),
stdres = (x - E) / sqrt(V)), class = "htest")

4
R/ggplot_pca.R

@ -47,13 +47,13 @@ @@ -47,13 +47,13 @@
#' @param arrows_textangled a logical whether the text at the end of the arrows should be angled
#' @param arrows_alpha the alpha (transparency) of the arrows and their text
#' @param base_textsize the text size for all plot elements except the labels and arrows
#' @param ... Parameters passed on to functions
#' @param ... Arguments passed on to functions
#' @source The [ggplot_pca()] function is based on the `ggbiplot()` function from the `ggbiplot` package by Vince Vu, as found on GitHub: <https://github.com/vqv/ggbiplot> (retrieved: 2 March 2020, their latest commit: [`7325e88`](https://github.com/vqv/ggbiplot/commit/7325e880485bea4c07465a0304c470608fffb5d9); 12 February 2015).
#'
#' As per their GPL-2 licence that demands documentation of code changes, the changes made based on the source code were:
#' 1. Rewritten code to remove the dependency on packages `plyr`, `scales` and `grid`
#' 2. Parametrised more options, like arrow and ellipse settings
#' 3. Hardened all input possibilities by defining the exact type of user input for every parameter
#' 3. Hardened all input possibilities by defining the exact type of user input for every argument
#' 4. Added total amount of explained variance as a caption in the plot
#' 5. Cleaned all syntax based on the `lintr` package, fixed grammatical errors and added integrity checks
#' 6. Updated documentation

6
R/ggplot_rsi.R

@ -45,8 +45,8 @@ @@ -45,8 +45,8 @@
#' @param caption text to show as caption of the plot
#' @param x.title text to show as x axis description
#' @param y.title text to show as y axis description
#' @param ... other parameters passed on to [geom_rsi()]
#' @details At default, the names of antibiotics will be shown on the plots using [ab_name()]. This can be set with the `translate_ab` parameter. See [count_df()].
#' @param ... other arguments passed on to [geom_rsi()]
#' @details At default, the names of antibiotics will be shown on the plots using [ab_name()]. This can be set with the `translate_ab` argument. See [count_df()].
#'
#' ## The functions
#' [geom_rsi()] will take any variable from the data that has an [`rsi`] class (created with [as.rsi()]) using [rsi_df()] and will plot bars with the percentage R, I and S. The default behaviour is to have the bars stacked and to have the different antibiotics on the x axis.
@ -91,7 +91,7 @@ @@ -91,7 +91,7 @@
#' select(AMX, NIT, FOS, TMP, CIP) %>%
#' ggplot_rsi(datalabels = FALSE)
#'
#' # add other ggplot2 parameters as you like:
#' # add other ggplot2 arguments as you like:
#' example_isolates %>%
#' select(AMX, NIT, FOS, TMP, CIP) %>%
#' ggplot_rsi(width = 0.5,

2
R/is_new_episode.R

@ -25,7 +25,7 @@ @@ -25,7 +25,7 @@
#' Determine (new) episodes for patients
#'
#' This function determines which items in a vector can be considered (the start of) a new episode, based on the parameter `episode_days`. This can be used to determine clinical episodes for any epidemiological analysis.
#' This function determines which items in a vector can be considered (the start of) a new episode, based on the argument `episode_days`. This can be used to determine clinical episodes for any epidemiological analysis.
#' @inheritSection lifecycle Stable lifecycle
#' @param x vector of dates (class `Date` or `POSIXt`)
#' @param episode_days length of the required episode in days, defaults to 365. Every element in the input will return `TRUE` after this number of days has passed since the last included date, independent of calendar years. Please see *Details*.

6
R/key_antibiotics.R

@ -34,9 +34,9 @@ @@ -34,9 +34,9 @@
#' @param GramPos_1,GramPos_2,GramPos_3,GramPos_4,GramPos_5,GramPos_6 column names of antibiotics for **Gram-positives**, case-insensitive. See details for which antibiotics will be used at default (which are guessed with [guess_ab_col()]).
#' @param GramNeg_1,GramNeg_2,GramNeg_3,GramNeg_4,GramNeg_5,GramNeg_6 column names of antibiotics for **Gram-negatives**, case-insensitive. See details for which antibiotics will be used at default (which are guessed with [guess_ab_col()]).
#' @param warnings give a warning about missing antibiotic columns (they will be ignored)
#' @param ... other parameters passed on to functions
#' @param ... other arguments passed on to functions
#' @details
#' The [key_antibiotics()] function is context-aware when used inside `dplyr` verbs, such as `filter()`, `mutate()` and `summarise()`. This means that then the `x` parameter can be omitted, please see *Examples*.
#' The [key_antibiotics()] function is context-aware when used inside `dplyr` verbs, such as `filter()`, `mutate()` and `summarise()`. This means that then the `x` argument can be omitted, please see *Examples*.
#'
#' The function [key_antibiotics()] returns a character vector with 12 antibiotic results for every isolate. These isolates can then be compared using [key_antibiotics_equal()], to check if two isolates have generally the same antibiogram. Missing and invalid values are replaced with a dot (`"."`) by [key_antibiotics()] and ignored by [key_antibiotics_equal()].
#'
@ -157,7 +157,7 @@ key_antibiotics <- function(x, @@ -157,7 +157,7 @@ key_antibiotics <- function(x,
dots <- unlist(list(...))
if (length(dots) != 0) {
# backwards compatibility with old parameters
# backwards compatibility with old arguments
dots.names <- dots %pm>% names()
if ("info" %in% dots.names) {
warnings <- dots[which(dots.names == "info")]

2
R/lifecycle.R

@ -44,7 +44,7 @@ @@ -44,7 +44,7 @@
#' \if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:5px} \cr}
#' The [lifecycle][AMR::lifecycle] of this function is **stable**. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
#'
#' If the unlying code needs breaking changes, they will occur gradually. For example, a parameter will be deprecated and first continue to work, but will emit an message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
#' If the unlying code needs breaking changes, they will occur gradually. For example, a argument will be deprecated and first continue to work, but will emit an message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
#' @section Retired lifecycle:
#' \if{html}{\figure{lifecycle_retired.svg}{options: style=margin-bottom:5px} \cr}
#' The [lifecycle][AMR::lifecycle] of this function is **retired**. A retired function is no longer under active development, and (if appropiate) a better alternative is available. No new arguments will be added, and only the most critical bugs will be fixed. In a future version, this function will be removed.

2
R/mdro.R

@ -35,7 +35,7 @@ @@ -35,7 +35,7 @@
#' @param verbose a logical to turn Verbose mode on and off (default is off). In Verbose mode, the function does not return the MDRO results, but instead returns a data set in logbook form with extensive info about which isolates would be MDRO-positive, or why they are not.
#' @inheritSection eucast_rules Antibiotics
#' @details
#' These functions are context-aware when used inside `dplyr` verbs, such as `filter()`, `mutate()` and `summarise()`. This means that then the `x` parameter can be omitted, please see *Examples*.
#' These functions are context-aware when used inside `dplyr` verbs, such as `filter()`, `mutate()` and `summarise()`. This means that then the `x` argument can be omitted, please see *Examples*.
#'
#' For the `pct_required_classes` argument, values above 1 will be divided by 100. This is to support both fractions (`0.75` or `3/4`) and percentages (`75`).
#'

12
R/mo.R

@ -38,7 +38,7 @@ @@ -38,7 +38,7 @@
#' @param reference_df a [data.frame] to be used for extra reference when translating `x` to a valid [`mo`]. See [set_mo_source()] and [get_mo_source()] to automate the usage of your own codes (e.g. used in your analysis or organisation).
#' @param ignore_pattern a regular expression (case-insensitive) of which all matches in `x` must return `NA`. This can be convenient to exclude known non-relevant input and can also be set with the option `AMR_ignore_pattern`, e.g. `options(AMR_ignore_pattern = "(not reported|contaminated flora)")`.
#' @param language language to translate text like "no growth", which defaults to the system language (see [get_locale()])
#' @param ... other parameters passed on to functions
#' @param ... other arguments passed on to functions
#' @rdname as.mo
#' @aliases mo
#' @keywords mo Becker becker Lancefield lancefield guess
@ -200,7 +200,7 @@ as.mo <- function(x, @@ -200,7 +200,7 @@ as.mo <- function(x,
uncertainty_level <- translate_allow_uncertain(allow_uncertain)
if (!is.null(reference_df)
&& mo_source_isvalid(reference_df)
&& check_validity_mo_source(reference_df)
&& isFALSE(Becker)
&& isFALSE(Lancefield)
&& all(x %in% unlist(reference_df), na.rm = TRUE)) {
@ -388,7 +388,7 @@ exec_as.mo <- function(x, @@ -388,7 +388,7 @@ exec_as.mo <- function(x,
# defined df to check for
if (!is.null(reference_df)) {
mo_source_isvalid(reference_df)
check_validity_mo_source(reference_df)
reference_df <- repair_reference_df(reference_df)
}
@ -1408,10 +1408,10 @@ exec_as.mo <- function(x, @@ -1408,10 +1408,10 @@ exec_as.mo <- function(x,
msg <- paste0(msg, ": ", paste('"', unique(failures), '"', sep = "", collapse = ", "))
}
msg <- paste0(msg,
".\nUse mo_failures() to review ", plural[2], ". Edit the `allow_uncertain` parameter if needed (see ?as.mo).\n",
".\nUse mo_failures() to review ", plural[2], ". Edit the `allow_uncertain` argument if needed (see ?as.mo).\n",
"You can also use your own reference data, e.g.:\n",
' as.mo("mycode", reference_df = data.frame(own = "mycode", mo = "B_ESCHR_COLI"))\n',
' mo_name("mycode", reference_df = data.frame(own = "mycode", mo = "B_ESCHR_COLI"))\n')
' as.mo("mycode", reference_df = data.frame(own = "mycode", mo = "', MO_lookup$mo[match("Escherichia coli", MO_lookup$fullname)], '"))\n',
' mo_name("mycode", reference_df = data.frame(own = "mycode", mo = "', MO_lookup$mo[match("Escherichia coli", MO_lookup$fullname)], '"))\n')
warning_(paste0("\n", msg),
add_fn = font_red,
call = FALSE,

6
R/mo_property.R

@ -30,7 +30,7 @@ @@ -30,7 +30,7 @@
#' @param x any character (vector) that can be coerced to a valid microorganism code with [as.mo()]. Can be omitted for auto-guessing in `mo_is_*()` functions when used inside `dplyr` verbs, such as [`filter()`][dplyr::filter()], [`mutate()`][dplyr::mutate()] and [`summarise()`][dplyr::summarise()], please see *Examples*.
#' @param property one of the column names of the [microorganisms] data set: `r paste0('"``', colnames(microorganisms), '\``"', collapse = ", ")`, or must be `"shortname"`
#' @param language language of the returned text, defaults to system language (see [get_locale()]) and can be overwritten by setting the option `AMR_locale`, e.g. `options(AMR_locale = "de")`, see [translate]. Also used to translate text like "no growth". Use `language = NULL` or `language = ""` to prevent translation.
#' @param ... other parameters passed on to [as.mo()], such as 'allow_uncertain' and 'ignore_pattern'
#' @param ... other arguments passed on to [as.mo()], such as 'allow_uncertain' and 'ignore_pattern'
#' @param ab any (vector of) text that can be coerced to a valid antibiotic code with [as.ab()]
#' @param open browse the URL using [utils::browseURL()]
#' @details All functions will return the most recently known taxonomic property according to the Catalogue of Life, except for [mo_ref()], [mo_authors()] and [mo_year()]. Please refer to this example, knowing that *Escherichia blattae* was renamed to *Shimwellia blattae* in 2010:
@ -44,7 +44,7 @@ @@ -44,7 +44,7 @@
#'
#' The Gram stain - [mo_gramstain()] - will be determined based on the taxonomic kingdom and phylum. According to Cavalier-Smith (2002, [PMID 11837318](https://pubmed.ncbi.nlm.nih.gov/11837318)), who defined subkingdoms Negibacteria and Posibacteria, only these phyla are Posibacteria: Actinobacteria, Chloroflexi, Firmicutes and Tenericutes. These bacteria are considered Gram-positive - all other bacteria are considered Gram-negative. Species outside the kingdom of Bacteria will return a value `NA`. Functions [mo_is_gram_negative()] and [mo_is_gram_positive()] always return `TRUE` or `FALSE` (except when the input is `NA` or the MO code is `UNKNOWN`), thus always return `FALSE` for species outside the taxonomic kingdom of Bacteria.
#'
#' Intrinsic resistance - [mo_is_intrinsic_resistant()] - will be determined based on the [intrinsic_resistant] data set, which is based on `r format_eucast_version_nr(3.2)`. The [mo_is_intrinsic_resistant()] can be vectorised over parameters `x` (input for microorganisms) and over `ab` (input for antibiotics).
#' Intrinsic resistance - [mo_is_intrinsic_resistant()] - will be determined based on the [intrinsic_resistant] data set, which is based on `r format_eucast_version_nr(3.2)`. The [mo_is_intrinsic_resistant()] can be vectorised over arguments `x` (input for microorganisms) and over `ab` (input for antibiotics).
#'
#' All output will be [translate]d where possible.
#'
@ -585,7 +585,7 @@ mo_validate <- function(x, property, language, ...) { @@ -585,7 +585,7 @@ mo_validate <- function(x, property, language, ...) {
Lancefield <- FALSE
}
# try to catch an error when inputting an invalid parameter
# try to catch an error when inputting an invalid argument
# so the 'call.' can be set to FALSE
tryCatch(x[1L] %in% MO_lookup[1, property, drop = TRUE],
error = function(e) stop(e$message, call. = FALSE))

17
R/mo_source.R

@ -36,7 +36,7 @@ @@ -36,7 +36,7 @@
#' @aliases set_mo_source get_mo_source
#' @details The reference file can be a text file separated with commas (CSV) or tabs or pipes, an Excel file (either 'xls' or 'xlsx' format) or an \R object file (extension '.rds'). To use an Excel file, you will need to have the `readxl` package installed.
#'
#' [set_mo_source()] will check the file for validity: it must be a [data.frame], must have a column named `"mo"` which contains values from [`microorganisms$mo`][microorganisms] and must have a reference column with your own defined values. If all tests pass, [set_mo_source()] will read the file into \R and will ask to export it to `"~/mo_source.rds"`. The CRAN policy disallows packages to write to the file system, although '*exceptions may be allowed in interactive sessions if the package obtains confirmation from the user*'. For this reason, this function only works in interactive sessions so that the user can **specifically confirm and allow** that this file will be created. The destination of this file can be set with the `destination` parameter and defaults to the user's home directory. It can also be set as an \R option, using `options(AMR_mo_source = "my/location/file.rds")`.
#' [set_mo_source()] will check the file for validity: it must be a [data.frame], must have a column named `"mo"` which contains values from [`microorganisms$mo`][microorganisms] and must have a reference column with your own defined values. If all tests pass, [set_mo_source()] will read the file into \R and will ask to export it to `"~/mo_source.rds"`. The CRAN policy disallows packages to write to the file system, although '*exceptions may be allowed in interactive sessions if the package obtains confirmation from the user*'. For this reason, this function only works in interactive sessions so that the user can **specifically confirm and allow** that this file will be created. The destination of this file can be set with the `destination` argument and defaults to the user's home directory. It can also be set as an \R option, using `options(AMR_mo_source = "my/location/file.rds")`.
#'
#' The created compressed data file `"mo_source.rds"` will be used at default for MO determination (function [as.mo()] and consequently all `mo_*` functions like [mo_genus()] and [mo_gramstain()]). The location and timestamp of the original file will be saved as an attribute to the compressed data file.
#'
@ -125,11 +125,11 @@ @@ -125,11 +125,11 @@
set_mo_source <- function(path, destination = getOption("AMR_mo_source", "~/mo_source.rds")) {
meet_criteria(path, allow_class = "character", has_length = 1, allow_NULL = TRUE)
meet_criteria(destination, allow_class = "character", has_length = 1)
stop_ifnot(destination %like% "[.]rds$", "the `destination` must be a file location with file extension .rds")
stop_ifnot(destination %like% "[.]rds$", "the `destination` must be a file location with file extension .rds.")
mo_source_destination <- path.expand(destination)
stop_ifnot(interactive(), "This function can only be used in interactive mode, since it must ask for the user's permission to write a file to their home folder.")
stop_ifnot(interactive(), "this function can only be used in interactive mode, since it must ask for the user's permission to write a file to their home folder.")
if (is.null(path) || path %in% c(FALSE, "")) {
mo_env$mo_source <- NULL
@ -160,13 +160,13 @@ set_mo_source <- function(path, destination = getOption("AMR_mo_source", "~/mo_s @@ -160,13 +160,13 @@ set_mo_source <- function(path, destination = getOption("AMR_mo_source", "~/mo_s
try(
df <- utils::read.table(header = TRUE, sep = ",", stringsAsFactors = FALSE),
silent = TRUE)
if (!mo_source_isvalid(df, stop_on_error = FALSE)) {
if (!check_validity_mo_source(df, stop_on_error = FALSE)) {
# try tab
try(
df <- utils::read.table(header = TRUE, sep = "\t", stringsAsFactors = FALSE),
silent = TRUE)
}
if (!mo_source_isvalid(df, stop_on_error = FALSE)) {
if (!check_validity_mo_source(df, stop_on_error = FALSE)) {
# try pipe
try(
df <- utils::read.table(header = TRUE, sep = "|", stringsAsFactors = FALSE),
@ -175,7 +175,7 @@ set_mo_source <- function(path, destination = getOption("AMR_mo_source", "~/mo_s @@ -175,7 +175,7 @@ set_mo_source <- function(path, destination = getOption("AMR_mo_source", "~/mo_s
}
# check integrity
mo_source_isvalid(df)
check_validity_mo_source(df)
df <- subset(df, !is.na(mo))
@ -211,6 +211,7 @@ set_mo_source <- function(path, destination = getOption("AMR_mo_source", "~/mo_s @@ -211,6 +211,7 @@ set_mo_source <- function(path, destination = getOption("AMR_mo_source", "~/mo_s
}
}
attr(df, "mo_source_location") <- path
attr(df, "mo_source_destination") <- mo_source_destination
attr(df, "mo_source_timestamp") <- file.mtime(path)
saveRDS(df, mo_source_destination)
mo_env$mo_source <- df
@ -226,7 +227,7 @@ set_mo_source <- function(path, destination = getOption("AMR_mo_source", "~/mo_s @@ -226,7 +227,7 @@ set_mo_source <- function(path, destination = getOption("AMR_mo_source", "~/mo_s
get_mo_source <- function(destination = getOption("AMR_mo_source", "~/mo_source.rds")) {
if (!file.exists(path.expand(destination))) {
if (interactive()) {
# source file might have been deleted, update reference
# source file might have been deleted, so update reference
set_mo_source("")
}
return(NULL)
@ -244,7 +245,7 @@ get_mo_source <- function(destination = getOption("AMR_mo_source", "~/mo_source. @@ -244,7 +245,7 @@ get_mo_source <- function(destination = getOption("AMR_mo_source", "~/mo_source.
mo_env$mo_source
}
mo_source_isvalid <- function(x, refer_to_name = "`reference_df`", stop_on_error = TRUE) {
check_validity_mo_source <- function(x, refer_to_name = "`reference_df`", stop_on_error = TRUE) {
check_dataset_integrity()
if (paste(deparse(substitute(x)), collapse = "") == "get_mo_source()") {

2
R/pca.R

@ -90,7 +90,7 @@ pca <- function(x, @@ -90,7 +90,7 @@ pca <- function(x,
# this is to support quoted variables: df %pm>% pca("mycol1", "mycol2")
new_list[[i]] <- x[, new_list[[i]]]
} else {
# remove item - it's a parameter like `center`
# remove item - it's a argument like `center`
new_list[[i]] <- NULL
}
}

6
R/proportion.R

@ -36,15 +36,15 @@ @@ -36,15 +36,15 @@
#' @param data a [data.frame] containing columns with class [`rsi`] (see [as.rsi()])
#' @param translate_ab a column name of the [antibiotics] data set to translate the antibiotic abbreviations to, using [ab_property()]
#' @inheritParams ab_property
#' @param combine_SI a logical to indicate whether all values of S and I must be merged into one, so the output only consists of S+I vs. R (susceptible vs. resistant). This used to be the parameter `combine_IR`, but this now follows the redefinition by EUCAST about the interpretation of I (increased exposure) in 2019, see section 'Interpretation of S, I and R' below. Default is `TRUE`.
#' @param combine_IR a logical to indicate whether all values of I and R must be merged into one, so the output only consists of S vs. I+R (susceptible vs. non-susceptible). This is outdated, see parameter `combine_SI`.
#' @param combine_SI a logical to indicate whether all values of S and I must be merged into one, so the output only consists of S+I vs. R (susceptible vs. resistant). This used to be the argument `combine_IR`, but this now follows the redefinition by EUCAST about the interpretation of I (increased exposure) in 2019, see section 'Interpretation of S, I and R' below. Default is `TRUE`.
#' @param combine_IR a logical to indicate whether all values of I and R must be merged into one, so the output only consists of S vs. I+R (susceptible vs. non-susceptible). This is outdated, see argument `combine_SI`.
#' @inheritSection as.rsi Interpretation of R and S/I
#' @details
#' The function [resistance()] is equal to the function [proportion_R()]. The function [susceptibility()] is equal to the function [proportion_SI()].
#'
#' **Remember that you should filter your table to let it contain only first isolates!** This is needed to exclude duplicates and to reduce selection bias. Use [first_isolate()] to determine them in your data set.
#'
#' These functions are not meant to count isolates, but to calculate the proportion of resistance/susceptibility. Use the [`count()`][AMR::count()] functions to count isolates. The function [susceptibility()] is essentially equal to `count_susceptible() / count_all()`. *Low counts can influence the outcome - the `proportion` functions may camouflage this, since they only return the proportion (albeit being dependent on the `minimum` parameter).*
#' These functions are not meant to count isolates, but to calculate the proportion of resistance/susceptibility. Use the [`count()`][AMR::count()] functions to count isolates. The function [susceptibility()] is essentially equal to `count_susceptible() / count_all()`. *Low counts can influence the outcome - the `proportion` functions may camouflage this, since they only return the proportion (albeit being dependent on the `minimum` argument).*
#'
#' The function [proportion_df()] takes any variable from `data` that has an [`rsi`] class (created with [as.rsi()]) and calculates the proportions R, I and S. It also supports grouped variables. The function [rsi_df()] works exactly like [proportion_df()], but adds the number of isolates.
#' @section Combination therapy:

6
R/random.R

@ -34,7 +34,7 @@ @@ -34,7 +34,7 @@
#' @param ... extension for future versions, not used at the moment
#' @details The base R function [sample()] is used for generating values.
#'
#' Generated values are based on the latest EUCAST guideline implemented in the [rsi_translation] data set. To create specific generated values per bug or drug, set the `mo` and/or `ab` parameter.
#' Generated values are based on the latest EUCAST guideline implemented in the [rsi_translation] data set. To create specific generated values per bug or drug, set the `mo` and/or `ab` argument.
#' @return class `<mic>` for [random_mic()] (see [as.mic()]) and class `<disk>` for [random_disk()] (see [as.disk()])
#' @name random
#' @rdname random
@ -89,7 +89,7 @@ random_exec <- function(type, size, mo = NULL, ab = NULL) { @@ -89,7 +89,7 @@ random_exec <- function(type, size, mo = NULL, ab = NULL) {
if (nrow(df_new) > 0) {
df <- df_new
} else {
warning_("No rows found that match mo '", mo, "', ignoring parameter `mo`", call = FALSE)
warning_("No rows found that match mo '", mo, "', ignoring argument `mo`", call = FALSE)
}
}
@ -100,7 +100,7 @@ random_exec <- function(type, size, mo = NULL, ab = NULL) { @@ -100,7 +100,7 @@ random_exec <- function(type, size, mo = NULL, ab = NULL) {
if (nrow(df_new) > 0) {
df <- df_new
} else {
warning_("No rows found that match ab '", ab, "', ignoring parameter `ab`", call = FALSE)
warning_("No rows found that match ab '", ab, "', ignoring argument `ab`", call = FALSE)
}
}

10
R/resistance_predict.R

@ -39,11 +39,11 @@ @@ -39,11 +39,11 @@
#' @param info a logical to indicate whether textual analysis should be printed with the name and [summary()] of the statistical model.
#' @param main title of the plot
#' @param ribbon a logical to indicate whether a ribbon should be shown (default) or error bars
#' @param ... parameters passed on to functions
#' @param ... arguments passed on to functions
#' @inheritSection as.rsi Interpretation of R and S/I
#' @inheritParams first_isolate
#' @inheritParams graphics::plot
#' @details Valid options for the statistical model (parameter `model`) are:
#' @details Valid options for the statistical model (argument `model`) are:
#' - `"binomial"` or `"binom"` or `"logit"`: a generalised linear regression model with binomial distribution
#' - `"loglin"` or `"poisson"`: a generalised log-linear regression model with poisson distribution
#' - `"lin"` or `"linear"`: a linear regression model
@ -138,11 +138,11 @@ resistance_predict <- function(x, @@ -138,11 +138,11 @@ resistance_predict <- function(x,
meet_criteria(preserve_measurements, allow_class = "logical", has_length = 1)
meet_criteria(info, allow_class = "logical", has_length = 1)
stop_if(is.null(model), 'choose a regression model with the `model` parameter, e.g. resistance_predict(..., model = "binomial")')
stop_if(is.null(model), 'choose a regression model with the `model` argument, e.g. resistance_predict(..., model = "binomial")')
dots <- unlist(list(...))
if (length(dots) != 0) {
# backwards compatibility with old parameters
# backwards compatibility with old arguments
dots.names <- dots %pm>% names()
if ("tbl" %in% dots.names) {
x <- dots[which(dots.names == "tbl")]
@ -158,7 +158,7 @@ resistance_predict <- function(x, @@ -158,7 +158,7 @@ resistance_predict <- function(x,
stop_if(is.null(col_date), "`col_date` must be set")
}
stop_ifnot(col_date %in% colnames(x),
"column `", col_date, "` not found")
"column '", col_date, "' not found")
# no grouped tibbles
x <- as.data.frame(x, stringsAsFactors = FALSE)

74
R/rsi.R

@ -36,9 +36,9 @@ @@ -36,9 +36,9 @@
#' @param guideline defaults to the latest included EUCAST guideline, see Details for all options
#' @param conserve_capped_values a logical to indicate that MIC values starting with `">"` (but not `">="`) must always return "R" , and that MIC values starting with `"<"` (but not `"<="`) must always return "S"
#' @param add_intrinsic_resistance *(only useful when using a EUCAST guideline)* a logical to indicate whether intrinsic antibiotic resistance must also be considered for applicable bug-drug combinations, meaning that e.g. ampicillin will always return "R" in *Klebsiella* species. Determination is based on the [intrinsic_resistant] data set, that itself is based on `r format_eucast_version_nr(3.2)`.
#' @param reference_data a [data.frame] to be used for interpretation, which defaults to the [rsi_translation] data set. Changing this parameter allows for using own interpretation guidelines. This parameter must contain a data set that is equal in structure to the [rsi_translation] data set (same column names and column types). Please note that the `guideline` parameter will be ignored when `reference_data` is manually set.
#' @param reference_data a [data.frame] to be used for interpretation, which defaults to the [rsi_translation] data set. Changing this argument allows for using own interpretation guidelines. This argument must contain a data set that is equal in structure to the [rsi_translation] data set (same column names and column types). Please note that the `guideline` argument will be ignored when `reference_data` is manually set.
#' @param threshold maximum fraction of invalid antimicrobial interpretations of `x`, please see *Examples*
#' @param ... for using on a [data.frame]: names of columns to apply [as.rsi()] on (supports tidy selection like `AMX:VAN`). Otherwise: parameters passed on to methods.
#' @param ... for using on a [data.frame]: names of columns to apply [as.rsi()] on (supports tidy selection like `AMX:VAN`). Otherwise: arguments passed on to methods.
#' @details
#' ## How it works
#'
@ -46,7 +46,7 @@ @@ -46,7 +46,7 @@
#'
#' 1. For **cleaning raw / untransformed data**. The data will be cleaned to only contain values S, I and R and will try its best to determine this with some intelligence. For example, mixed values with R/SI interpretations and MIC values such as `"<0.25; S"` will be coerced to `"S"`. Combined interpretations for multiple test methods (as seen in laboratory records) such as `"S; S"` will be coerced to `"S"`, but a value like `"S; I"` will return `NA` with a warning that the input is unclear.
#'
#' 2. For **interpreting minimum inhibitory concentration (MIC) values** according to EUCAST or CLSI. You must clean your MIC values first using [as.mic()], that also gives your columns the new data class [`mic`]. Also, be sure to have a column with microorganism names or codes. It will be found automatically, but can be set manually using the `mo` parameter.
#' 2. For **interpreting minimum inhibitory concentration (MIC) values** according to EUCAST or CLSI. You must clean your MIC values first using [as.mic()], that also gives your columns the new data class [`mic`]. Also, be sure to have a column with microorganism names or codes. It will be found automatically, but can be set manually using the `mo` argument.
#' * Using `dplyr`, R/SI interpretation can be done very easily with either:
#' ```
#' your_data %>% mutate_if(is.mic, as.rsi) # until dplyr 1.0.0
@ -54,7 +54,7 @@ @@ -54,7 +54,7 @@
#' ```
#' * Operators like "<=" will be stripped before interpretation. When using `conserve_capped_values = TRUE`, an MIC value of e.g. ">2" will always return "R", even if the breakpoint according to the chosen guideline is ">=4". This is to prevent that capped values from raw laboratory data would not be treated conservatively. The default behaviour (`conserve_capped_values = FALSE`) considers ">2" to be lower than ">=4" and might in this case return "S" or "I".
#'
#' 3. For **interpreting disk diffusion diameters** according to EUCAST or CLSI. You must clean your disk zones first using [as.disk()], that also gives your columns the new data class [`disk`]. Also, be sure to have a column with microorganism names or codes. It will be found automatically, but can be set manually using the `mo` parameter.
#' 3. For **interpreting disk diffusion diameters** according to EUCAST or CLSI. You must clean your disk zones first using [as.disk()], that also gives your columns the new data class [`disk`]. Also, be sure to have a column with microorganism names or codes. It will be found automatically, but can be set manually using the `mo` argument.
#' * Using `dplyr`, R/SI interpretation can be done very easily with either:
#' ```
#' your_data %>% mutate_if(is.disk, as.rsi) # until dplyr 1.0.0
@ -65,9 +65,9 @@ @@ -65,9 +65,9 @@
#'
#' ## Supported guidelines
#'
#' For interpreting MIC values as well as disk diffusion diameters, supported guidelines to be used as input for the `guideline` parameter are: `r paste0('"', sort(unique(AMR::rsi_translation$guideline)), '"', collapse = ", ")`.
#' For interpreting MIC values as well as disk diffusion diameters, supported guidelines to be used as input for the `guideline` argument are: `r paste0('"', sort(unique(AMR::rsi_translation$guideline)), '"', collapse = ", ")`.
#'
#' Simply using `"CLSI"` or `"EUCAST"` as input will automatically select the latest version of that guideline. You can set your own data set using the `reference_data` parameter. The `guideline` parameter will then be ignored.
#' Simply using `"CLSI"` or `"EUCAST"` as input will automatically select the latest version of that guideline. You can set your own data set using the `reference_data` argument. The `guideline` argument will then be ignored.
#'
#' ## After interpretation
#'
@ -79,7 +79,7 @@ @@ -79,7 +79,7 @@
#'
#' ## Other
#'
#' The function [is.rsi.eligible()] returns `TRUE` when a columns contains at most 5% invalid antimicrobial interpretations (not S and/or I and/or R), and `FALSE` otherwise. The threshold of 5% can be set with the `threshold` parameter.
#' The function [is.rsi.eligible()] returns `TRUE` when a columns contains at most 5% invalid antimicrobial interpretations (not S and/or I and/or R), and `FALSE` otherwise. The threshold of 5% can be set with the `threshold` argument.
#' @section Interpretation of R and S/I:
#' In 2019, the European Committee on Antimicrobial Susceptibility Testing (EUCAST) has decided to change the definitions of susceptibility testing categories R and S/I as shown below (<https://www.eucast.org/newsiandr/>).
#'
@ -113,7 +113,8 @@ @@ -113,7 +113,8 @@
#' CIP = as.mic(0.256),
#' GEN = as.disk(18),
#' TOB = as.disk(16),
#' NIT = as.mic(32))
#' NIT = as.mic(32),
#' ERY = "R")
#' as.rsi(df)
#'
#' # for single values
@ -323,25 +324,25 @@ as.rsi.mic <- function(x, @@ -323,25 +324,25 @@ as.rsi.mic <- function(x,
mo <- suppressMessages(search_type_in_df(df, "mo"))
}, silent = TRUE)
if (!is.null(df) && !is.null(mo) && is.data.frame(df)) {
mo_var_found <- paste0(" based on column `", font_bold(mo), "`")
mo_var_found <- paste0(" based on column '", font_bold(mo), "'")
mo <- df[, mo, drop = TRUE]
}
}, error = function(e)
stop_('No information was supplied about the microorganisms (missing parameter "mo"). See ?as.rsi.\n\n',
stop_('No information was supplied about the microorganisms (missing argument `mo`). See ?as.rsi.\n\n',
"To transform certain columns with e.g. mutate_at(), use `data %>% mutate_at(vars(...), as.rsi, mo = .$x)`, where x is your column with microorganisms.\n",
"To tranform all disk diffusion zones in a data set, use `data %>% as.rsi()` or data %>% mutate_if(is.disk, as.rsi).", call = FALSE)
)
}
if (length(ab) == 1 && ab %like% "as.mic") {
stop_('No unambiguous name was supplied about the antibiotic (parameter "ab"). See ?as.rsi.', call = FALSE)
stop_('No unambiguous name was supplied about the antibiotic (argument `ab`). See ?as.rsi.', call = FALSE)
}
ab_coerced <- suppressWarnings(as.ab(ab))
mo_coerced <- suppressWarnings(as.mo(mo))
guideline_coerced <- get_guideline(guideline, reference_data)
if (is.na(ab_coerced)) {
message_("Returning NAs for unknown drug: `", font_bold(ab),
"`. Rename this column to a drug name or code, and check the output with as.ab().",
message_("Returning NAs for unknown drug: '", font_bold(ab),
"'. Rename this column to a drug name or code, and check the output with `as.ab()`.",
add_fn = font_red,
as_note = FALSE)
return(as.rsi(rep(NA, length(x))))
@ -353,7 +354,7 @@ as.rsi.mic <- function(x, @@ -353,7 +354,7 @@ as.rsi.mic <- function(x,
uti <- rep(uti, length(x))
}
message_("=> Interpreting MIC values of '", font_bold(ab), "' (",
message_("=> Interpreting MIC values of ", ifelse(isTRUE(list(...)$is_data.frame), "column ", ""), "'", font_bold(ab), "' (",
ifelse(ab_coerced != ab, paste0(ab_coerced, ", "), ""),
ab_name(ab_coerced, tolower = TRUE), ")", mo_var_found,
" according to ", ifelse(identical(reference_data, AMR::rsi_translation),
@ -412,25 +413,25 @@ as.rsi.disk <- function(x, @@ -412,25 +413,25 @@ as.rsi.disk <- function(x,
mo <- suppressMessages(search_type_in_df(df, "mo"))
}, silent = TRUE)
if (!is.null(df) && !is.null(mo) && is.data.frame(df)) {
mo_var_found <- paste0(" based on column `", font_bold(mo), "`")
mo_var_found <- paste0(" based on column '", font_bold(mo), "'")
mo <- df[, mo, drop = TRUE]
}
}, error = function(e)
stop_('No information was supplied about the microorganisms (missing parameter "mo"). See ?as.rsi.\n\n',
stop_('No information was supplied about the microorganisms (missing argument `mo`). See ?as.rsi.\n\n',
"To transform certain columns with e.g. mutate_at(), use `data %>% mutate_at(vars(...), as.rsi, mo = .$x)`, where x is your column with microorganisms.\n",
"To tranform all disk diffusion zones in a data set, use `data %>% as.rsi()` or data %>% mutate_if(is.disk, as.rsi).", call = FALSE)
)
}
if (length(ab) == 1 && ab %like% "as.disk") {
stop_('No unambiguous name was supplied about the antibiotic (parameter "ab"). See ?as.rsi.', call = FALSE)
stop_('No unambiguous name was supplied about the antibiotic (argument `ab`). See ?as.rsi.', call = FALSE)
}
ab_coerced <- suppressWarnings(as.ab(ab))
mo_coerced <- suppressWarnings(as.mo(mo))
guideline_coerced <- get_guideline(guideline, reference_data)
if (is.na(ab_coerced)) {
message_("Returning NAs for unknown drug: `", font_bold(ab),
"`. Rename this column to a drug name or code, and check the output with as.ab().",
message_("Returning NAs for unknown drug: '", font_bold(ab),
"'. Rename this column to a drug name or code, and check the output with `as.ab()`.",
add_fn = font_red,
as_note = FALSE)
return(as.rsi(rep(NA, length(x))))
@ -442,7 +443,7 @@ as.rsi.disk <- function(x, @@ -442,7 +443,7 @@ as.rsi.disk <- function(x,
uti <- rep(uti, length(x))
}
message_("=> Interpreting disk zones of '", font_bold(ab), "' (",
message_("=> Interpreting disk zones of ", ifelse(isTRUE(list(...)$is_data.frame), "column ", ""), "'", font_bold(ab), "' (",
ifelse(ab_coerced != ab, paste0(ab_coerced, ", "), ""),
ab_name(ab_coerced, tolower = TRUE), ")", mo_var_found,
" according to ", ifelse(identical(reference_data, AMR::rsi_translation),