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Pre-release 16 of April 2024

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@amc1999 amc1999 released this 17 Apr 03:12
· 235 commits to master since this release
v1.17.2-pre-2
f773a3b

Preview release 16 of April 2024

v1.17.2-pre-2

This is a preview of the next release, do not use it in production.

Main features of this release:

  • c++ core: new optional lifecycle attributes to probe events
  • c++ core: new "untransformed" tables
  • c++ core: allow explicit declaration of table filter attribute
  • UI: microdata aggregation and run comparison
  • go: initial version of dbget utility to extract and transform model run results
  • go: new fair scheduling of cloud CPU resources

Other changes:

  • c++ core: new example model TableProbe2
  • c++ core: protect model run-time code from Microsoft MPI bug
  • go dbcopy: add output to TSV files
  • change oms UI back-end and MSBuild to correctly handle ini-files in UI
  • Linux and MacOS: fix issues with spaces in file path

New optional lifecycle attributes to probe events

A new option lifecycle_attributes creates 2 attributes and a supporting classification which can be used to probe model events. For more information, please see the wiki topic (containing worked examples with screenshots) at:
Lifecycle Attributes · openmpp/openmpp.github.io Wiki

New "untransformed" tables

In this release, if the " table" keyword is followed by the optional keyword "untransformed", the measures for that table are computed using no weights and no population scaling, and the run-level table is computed by assembling measures over subs (using the new measures_method=assemble), e.g. by summing counts rather than by averaging them over subs.

Allow explicit declaration of table filter attribute

An entity table filter is an expression involving entity attributes.
OpenM++ creates identity attributes as needed to implement the table filters in a model.
They are shown in table and attribute topics in the Developer Edition of the model’s Symbol Reference.

A new syntax in this release allows a model developer to declare the table filter explicitly in the table declaration, e.g.:

table snapshot untransformed Person X01_Events //EN All Events
[ bool filter_X01 = trigger_changes(lifecycle_counter) ]
{
    lifecycle_event //EN Event
  * {
        unit //EN N
    } //EN Statistic
};

This can be a convenient way to explore a table filter directly, e.g. using microdata output.
It is equivalent to declaring the original filter expression as an identity attribute, then using that attribute instead of the expression as the table filter.
Table filters declared explicitly do not participate in de-duplication of table filters (sharing of identical filters) done by OpenM++.

New example model TableProbe2

This release includes a new example model TableProbe2, which is used in the wiki to illustrate entity table concepts and use.

TableProbe2 is not Modgen compatible.

UI: microdata aggregation and run comparison

Microdata UI provides new capabilities to aggregate and compare model runs microdata. For example, if there is a hypothetical tax model then user can compare different taxation policies to find an average percent of income difference by age group, province and gender.

Initial version of dbget utility to extract and transform model run results

New dbget utility allow to extract and transform model run results from the database and save it into CSV files. For example it allows to compare run results microdata to find which age and gender groups are winning or loosing from taxation policy changes:

dbget -db modelOne.sqlite -do microdata-compare
  -m TaxModel
  -dbget.Run Default
  -dbget.WithRuns "Updated Tax Policy"
  -dbget.Entity Person
  -dbget.GroupBy "AgeGroup, Gender"
  -dbget.Calc "OM_COUNT_IF( Income[base] - Income[variant] > param.Threshold[base] )"

This release include an initial version of dbget utility, functionality will be significantly extended in subsequent releases

New fair scheduling of cloud CPU resources

Oms web-service back-end updated to fairly share cloud CPU resources between multiple users under heavy load. With previous version batch users (those who were submitting 100x model runs through R or Pythin scripts) were able to monopolize entire cluster CPU resources for multiple days. New version provides fair share of CPUs to all users even under heavy load.

Download source code and binaries:

IMPORTANT:
Full version of OpenM++ source code always included into "Download" links above.
Please do NOT use "Source code (zip)" or "Source code (tar.gz)" archives from "Assets" links below.
It is auto-generated by GitHub release tools and contains only half of OpenM++ source code.

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