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Model Localization
Home > Model Development Topics > Model Localization
This topic describes how to provide translations for model-specific run-time messages.
- Multilingual Support forthcoming content
- Quick start
- How model finds translated message
- Model developer: How to mark strings for translation in model code
You can provide translated messages for your model by editing modelName.message.ini
file located in the same directory where modelName.exe
is.
For example:
dir /B openmpp_win_20180205\models\bin
....
modelOne.exe
modelOne.ini
modelOne.message.ini
modelOne.sqlite
modelOne.message.ini
is translated messages for modelOne.exe
Message.ini file must be UTF-8 encoded and it contain model translated messages:
;
; modelOne localized messages
;
[FR]
Run %d = Exécution: %d
[fr-CA]
Run %d = Exécution: %d
;
; Example of multi-line translated message:
;
"Scenario processing" = "\
Traitment \
du scénario\
"
[en]
; Model = Model
If translation the same as original message you can exclude it, e.g.: Model = Model
is not required.
At start model determine list user preferred languages.
For example if current environment is French Canadian and model default language is EN then language list will be: (fr-ca, fr, en)
.
User language preference can be changed in Windows Control Panel or by Linux LANG environment variable. You can override environment language by using model command-line or ini-file argument:
modelOne.exe -OpenM.MessageLanguage es-EC
To find translated message model does lookup in:
path/to/model.exe/modelName.message.ini
path/to/model.exe/common.message.ini
$OM_ROOT/common.message.ini
$OM_ROOT/models/common.message.ini
- database table
model_word
- database table
lang_word
Search done in above order and in the order of user preferred languages, first translation found is used.
For example if there is translation of word Success
exist in modelName.message.ini
, in common.message.ini
and in lang_word
database table then modelName.message.ini
translation is used.
For example, if modelOne.message.ini
is same as above, common.message.ini
is:
[fr]
All: %d = Toute : %d
and database table model_word
contains entry:
fr-CA Done. Fini.
Then model messages in French Canadian environment can be similar to:
2014-03-17 17:14:24.023 Model: modelOne
2014-03-17 17:14:24.070 Exécution 101
2014-03-17 17:14:24.123 Toute : 456
....
2014-03-17 17:14:24.179 Fini.
As you can see for current user language fr-CA
model found 3 messages translated in "generic fr
" French: "Exécution", "Toute" and "Fini",
however "Model" still untranslated. To fix this you can update modelOne.message.ini
by adding:
[fr-CA]
Model = Modèle
Then result would look like:
2014-03-17 17:14:24.023 Modèle: modelOne
2014-03-17 17:14:24.070 Exécution 101
2014-03-17 17:14:24.123 Toute : 456
....
2014-03-17 17:14:24.0179 Fini.
Omc model compiler automatically include first "const char *"
argument of
theLog->logMsg("some message");
theLog->logFormatted("some format %d %g %s",....);
- macro
LT("some message")
WriteLogEntry("some message");
WriteDebugLogEntry("some message");
WarningMsg("some message");
-
ModelExit("some message");
into outputmodel.message.ini
file, which can be used as translation starting point.
If your source code directory already contains translated code/model.message.ini
then such file is merged
with newly added model messages into output bin/model.message.ini
, which you can forward to translation team.
It is possible to use macro LT("something")
in order to build concatenated message,
however LT is "strictly inline" because it returns temporary const char *
pointer. As result following will crash your model:
const char * myBadDay = LT("nice day");
if (myBadDay .... // memory access violation, model crash
How to avoid string concatenation. String concatenation considered as bad practice by any translation guide. For example, if you have something like:
string msg = LT("Table has ") + std::to_string(rowCount) + LT(" rows");
theLog->logMsg(msg.c_str());
then try to replace it with:
theLog->logFormatted("Table has %d rows", rowCount);
Non-translatable strings. Not every output in your model you want to translate For example, you may don't want to translate your model trace output:
WriteDebugLogEntry(NO_LT("------------"));
WriteDebugLogEntry(NO_LT("{1, 2, 3, 4}"));
WriteDebugLogEntry(NO_LT("------------"));
Please use NO_LT
macro to disable unnecessary translation.
- Windows: Quick Start for Model Users
- Windows: Quick Start for Model Developers
- Linux: Quick Start for Model Users
- Linux: Quick Start for Model Developers
- MacOS: Quick Start for Model Users
- MacOS: Quick Start for Model Developers
- Model Run: How to Run the Model
- MIT License, Copyright and Contribution
- Model Code: Programming a model
- Windows: Create and Debug Models
- Linux: Create and Debug Models
- MacOS: Create and Debug Models
- MacOS: Create and Debug Models using Xcode
- Modgen: Convert case-based model to openM++
- Modgen: Convert time-based model to openM++
- Modgen: Convert Modgen models and usage of C++ in openM++ code
- Model Localization: Translation of model messages
- How To: Set Model Parameters and Get Results
- Model Run: How model finds input parameters
- Model Output Expressions
- Model Run Options and ini-file
- OpenM++ Compiler (omc) Run Options
- OpenM++ ini-file format
- UI: How to start user interface
- UI: openM++ user interface
- UI: Create new or edit scenario
- UI: Upload input scenario or parameters
- UI: Run the Model
- UI: Use ini-files or CSV parameter files
- UI: Compare model run results
- UI: Aggregate and Compare Microdata
- UI: Filter run results by value
- UI: Disk space usage and cleanup
- UI Localization: Translation of openM++
-
Highlight: hook to self-scheduling or trigger attribute
-
Highlight: The End of Start
-
Highlight: Enumeration index validity and the
index_errors
option -
Highlight: Simplified iteration of range, classification, partition
-
Highlight: Parameter, table, and attribute groups can be populated by module declarations
- Oms: openM++ web-service
- Oms: openM++ web-service API
- Oms: How to prepare model input parameters
- Oms: Cloud and model runs queue
- Use R to save output table into CSV file
- Use R to save output table into Excel
- Run model from R: simple loop in cloud
- Run RiskPaths model from R: advanced run in cloud
- Run RiskPaths model in cloud from local PC
- Run model from R and save results in CSV file
- Run model from R: simple loop over model parameter
- Run RiskPaths model from R: advanced parameters scaling
- Run model from Python: simple loop over model parameter
- Run RiskPaths model from Python: advanced parameters scaling
- Windows: Use Docker to get latest version of OpenM++
- Linux: Use Docker to get latest version of OpenM++
- RedHat 8: Use Docker to get latest version of OpenM++
- Quick Start for OpenM++ Developers
- Setup Development Environment
- 2018, June: OpenM++ HPC cluster: Test Lab
- Development Notes: Defines, UTF-8, Databases, etc.
- 2012, December: OpenM++ Design
- 2012, December: OpenM++ Model Architecture, December 2012
- 2012, December: Roadmap, Phase 1
- 2013, May: Prototype version
- 2013, September: Alpha version
- 2014, March: Project Status, Phase 1 completed
- 2016, December: Task List
- 2017, January: Design Notes. Subsample As Parameter problem. Completed
GET Model Metadata
- GET model list
- GET model list including text (description and notes)
- GET model definition metadata
- GET model metadata including text (description and notes)
- GET model metadata including text in all languages
GET Model Extras
GET Model Run results metadata
- GET list of model runs
- GET list of model runs including text (description and notes)
- GET status of model run
- GET status of model run list
- GET status of first model run
- GET status of last model run
- GET status of last completed model run
- GET model run metadata and status
- GET model run including text (description and notes)
- GET model run including text in all languages
GET Model Workset metadata: set of input parameters
- GET list of model worksets
- GET list of model worksets including text (description and notes)
- GET workset status
- GET model default workset status
- GET workset including text (description and notes)
- GET workset including text in all languages
Read Parameters, Output Tables or Microdata values
- Read parameter values from workset
- Read parameter values from workset (enum id's)
- Read parameter values from model run
- Read parameter values from model run (enum id's)
- Read output table values from model run
- Read output table values from model run (enum id's)
- Read output table calculated values from model run
- Read output table calculated values from model run (enum id's)
- Read output table values and compare model runs
- Read output table values and compare model runs (enun id's)
- Read microdata values from model run
- Read microdata values from model run (enum id's)
- Read aggregated microdata from model run
- Read aggregated microdata from model run (enum id's)
- Read microdata run comparison
- Read microdata run comparison (enum id's)
GET Parameters, Output Tables or Microdata values
- GET parameter values from workset
- GET parameter values from model run
- GET output table expression(s) from model run
- GET output table calculated expression(s) from model run
- GET output table values and compare model runs
- GET output table accumulator(s) from model run
- GET output table all accumulators from model run
- GET microdata values from model run
- GET aggregated microdata from model run
- GET microdata run comparison
GET Parameters, Output Tables or Microdata as CSV
- GET csv parameter values from workset
- GET csv parameter values from workset (enum id's)
- GET csv parameter values from model run
- GET csv parameter values from model run (enum id's)
- GET csv output table expressions from model run
- GET csv output table expressions from model run (enum id's)
- GET csv output table accumulators from model run
- GET csv output table accumulators from model run (enum id's)
- GET csv output table all accumulators from model run
- GET csv output table all accumulators from model run (enum id's)
- GET csv calculated table expressions from model run
- GET csv calculated table expressions from model run (enum id's)
- GET csv model runs comparison table expressions
- GET csv model runs comparison table expressions (enum id's)
- GET csv microdata values from model run
- GET csv microdata values from model run (enum id's)
- GET csv aggregated microdata from model run
- GET csv aggregated microdata from model run (enum id's)
- GET csv microdata run comparison
- GET csv microdata run comparison (enum id's)
GET Modeling Task metadata and task run history
- GET list of modeling tasks
- GET list of modeling tasks including text (description and notes)
- GET modeling task input worksets
- GET modeling task run history
- GET status of modeling task run
- GET status of modeling task run list
- GET status of modeling task first run
- GET status of modeling task last run
- GET status of modeling task last completed run
- GET modeling task including text (description and notes)
- GET modeling task text in all languages
Update Model Profile: set of key-value options
- PATCH create or replace profile
- DELETE profile
- POST create or replace profile option
- DELETE profile option
Update Model Workset: set of input parameters
- POST update workset read-only status
- PUT create new workset
- PUT create or replace workset
- PATCH create or merge workset
- DELETE workset
- POST delete multiple worksets
- DELETE parameter from workset
- PATCH update workset parameter values
- PATCH update workset parameter values (enum id's)
- PATCH update workset parameter(s) value notes
- PUT copy parameter from model run into workset
- PATCH merge parameter from model run into workset
- PUT copy parameter from workset to another
- PATCH merge parameter from workset to another
Update Model Runs
- PATCH update model run text (description and notes)
- DELETE model run
- POST delete model runs
- PATCH update run parameter(s) value notes
Update Modeling Tasks
Run Models: run models and monitor progress
Download model, model run results or input parameters
- GET download log file
- GET model download log files
- GET all download log files
- GET download files tree
- POST initiate entire model download
- POST initiate model run download
- POST initiate model workset download
- DELETE download files
- DELETE all download files
Upload model runs or worksets (input scenarios)
- GET upload log file
- GET all upload log files for the model
- GET all upload log files
- GET upload files tree
- POST initiate model run upload
- POST initiate workset upload
- DELETE upload files
- DELETE all upload files
Download and upload user files
- GET user files tree
- POST upload to user files
- PUT create user files folder
- DELETE file or folder from user files
- DELETE all user files
User: manage user settings
Model run jobs and service state
- GET service configuration
- GET job service state
- GET disk usage state
- POST refresh disk space usage info
- GET state of active model run job
- GET state of model run job from queue
- GET state of model run job from history
- PUT model run job into other queue position
- DELETE state of model run job from history
Administrative: manage web-service state
- POST a request to refresh models catalog
- POST a request to close models catalog
- POST a request to close model database
- POST a request to delete the model
- POST a request to open database file
- POST a request to cleanup database file
- GET the list of database cleanup log(s)
- GET database cleanup log file(s)
- POST a request to pause model run queue
- POST a request to pause all model runs queue
- PUT a request to shutdown web-service