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- 1 OpasnetUtils features
- 2 List/Glossary of package contents
- 3 Installation
- 4 Manual
Defining and analyzing endpoints of a model can be as easy as Fetching a relevant variable, evaluating it (using EvalOutput) and using some of the available functions (i.e. summary() for ovariables).
List/Glossary of package contents
Find more about each function or method using ?<topic> in the R console or search the #Manual. Topics are in approximate order of prevalency.
- EvalOutput - is the method used to evaluate ovariables.
- ComputeDependencies - is automatically run when evaluating ovariables to fetch and evaluate any dependencies they have.
- CheckMarginals - is automatically run when evaluating ovariables to check the marginal status of output indices.
- CheckInput - is automatically run when evaluating ovariables to incorporate input definitions if available.
- CheckCollapse - is automatically run when evaluating ovariables. Uses CollapseMarginal if orders are present.
- CheckDecisions - is automatically run when evaluating ovariables. Adds scenarios to output if their definitions are present.
- CollapseMarginal - is used to streamline large models by removing indices through summation etc.
- DecisionTableParser - parses scenarios used in decision analysis from data.frames.
- CollapseTableParser - parses collapse orders from data.frames.
- Optimize - finds optimal combination of index values.
- Minimize - finds optimal combination of index values so that the resulting value is minimal.
Custom methods for Opasnet and ovariables
- oprint - prints a data.frame or the output of an ovariable as a html formatted table so it looks nice on the web page.
- oapply - uses tapply on ovariable output. Instead of defining INDEX you can define cols as the column names you want to remove.
- orbind - uses rbind on the output slots two ovariables. Differing columns are allowed (missing ones are added automatically).
- combine - is similar to orbind, but more efficient and combines source columns.
- merge - merges ovariable outputs.
- summary - provides common statistics about the data using tapply. Defaults to describing the distribution about each ovariable index.
- plot - plots ovariable output. Defaults to comparison of data and formula results.
- Ops - methods for mathematical operations between ovariables (i.e. X * Y).
- Math - methods for single variable mathematical operations (i.e. exp(X)).
External (serverside) data and objects
- opbase.data - downloads data from the Opasnet database.
- opbase.upload - uploads data to the Opasnet database.
- opbase.locations - downloads the index information of a particular dataset.
- opbase.obj.exists - checks whether object (as identified by page identifier) exists in the database.
- opbase.series - downloads list of datasets for a particular object.
- opasnet.data - downloads data from any file uploaded to Opasnet as text.
- opasnet.csv - downloads data from any .csv file uploaded to Opasnet.
- objects.get - downloads saved R objects matching a key.
- objects.latest - downloads latest saved R objects matching a code block in Opasnet.
- objects.put - uploads R objects. Returns key.
- objects.store - uploads public R objects in Opasnet code block.
- objects.encode - encrypts R objects.
- objects.decode - decrypts R objects.
- Ovariable - constructs ovariables. More feature than new("ovariable", ...).
- Fetch - downloads saved R objects in batch fashion.
- tidy - makes common adjustments to data.frames used for ovariable data slots.
- interpret - forms a probability distributions based on regular expressions OpasnetUtils/Interpret.
- result - accesses the result column of the output slot of an ovariable. Result(X) <- y -shortcut is possible.
- ddata_apply - updates data slot of an ovariable based on a link in the ddata slot. Does not overwrite unless force_ddata = TRUE.
- convert.units - is a unit conversion engine.
- fillna - looks for empty column values (NA) in specified data.frame columns and replaces them with all other values in the same column.
- dropall - cleans factors of unused levels.
Health impact assessment
- GIS.Exposure - does spatial exposure mapping.
- GIS.Concentration.matrix - does spatial concentration mapping based on point emission.
Installation of RStudio and rgdal in Ubuntu
OpasnetUtils is available from the CRAN repository on any platform capable of running R. Use the drop down menu in the RGui or the R command install.packages("OpasnetUtils") to download the most recent official release.
In Ubuntu machines, you will probably have problems with the rgdal package. Therefore, this is a detailed description how that was successfully done in Ubuntu 16.04 (32-bit version because the computers were old):
1) Install R by adding this instruction to the file /etc/apt/sources.list  (this particular code uses a Danish mirror to download packages. Note that the file is write-protected and you may need command sudo gedit to open the file):
deb https://mirrors.dotsrc.org/cran/bin/linux/ubuntu xenial/
2) Then, in the terminal, run these commands:
sudo apt-get update sudo apt-get install r-base
3) The rgdal package does not install properly from R. Therefore, you should run these commands from the terminal first :
sudo apt-get update && sudo apt-get install libgdal-dev libproj-dev
4) Then, install RStudio by clicking the right version from . Follow instructions to install.
5) Search your computer to find R and RStudio. Drag their icons to the left taskbar to make it easy to launch them.
6) Open RStudio and from Tools / Install packages... install at least packages OpasnetUtils, ggplot2, rgdal, and reshape2 with dependencies.
If you would like to acquire the most recent version, you are welcome to download and compile our source code which is available at https://www.opasnet.org/svn/opasnet_utils/trunk/. For most recent function definitions see the R sub folder. Compilation on Windows machines requires R tools (See the CRAN homepage for more information).