Skip to contents

Changelog

Source: NEWS.md

mcmodule (development version)

New features

  • agg_variates() now accepts custom aggregation functions through agg_func. It also warns when automatic probability aggregation is applied to values greater than one (#98).

  • eval_module() now accepts a list of previous mcmodule objects, allowing an expression to use nodes from multiple modules. Conflicting node names must be resolved beforehand, for example with add_prefix().

  • create_mcnodes() now supports namespace-qualified distribution functions and functions with required arguments. Bare rpert now resolves explicitly to mc2d::rpert(), with a warning when it is masked by the freedom package (#45).

  • mc_network(), visNetwork_nodes(), and get_node_table() gain a percentages argument. Count and time nodes, and stochastic nodes with values exceeding one, are displayed numerically, percentage formatting can also be disabled entirely (#41).

  • Added data-raw/water_example.R, which generates the water-supply quantitative microbial risk assessment example data, node specifications, data keys, and pathway expressions.

  • mctable_bounds() gains drop_constant, which drops inputs whose bounds do not vary (binf == bsup), including inputs made constant by a transformation. It defaults to TRUE. Dropped inputs are returned in the new dropped element, added to fixed when if_not_sampled != "exclude", and created as fixed nodes by eval_module() and trial_totals() (#106).

  • mctable_sobol_matrices() gains transformation and drop_constant arguments. Mapped values are now transformed with mctable$transformation by default, matching mctable_bounds(), which also enables categorical sample_space definitions. Constant inputs are dropped by default before the matrices are built and their names are stored in attr(X, "dropped").

  • trial_totals() now creates trials_n, subsets_n and subsets_p nodes that are defined in mctable but missing from both sample_design and module data as fixed nodes, flagged with from_sample_design_fixed (#106). The new if_not_sampled argument controls the fixed value, as in `eval_module().

Bug fixes and improvements

  • at_least_one() now combines nodes directly when every input comes from sample_design, avoiding unnecessary key matching (#96).

  • create_mcnodes() now constructs mcdata and mcstoc nodes directly instead of generating and parsing R code. Configured transformation expressions continue to be evaluated as R code.

  • eval_module() now reports clearer errors for unnamed or duplicated expression blocks and unsupported expression statements.

  • eval_module() no longer creates duplicate node entries across expressions. Repeated inputs and references reuse existing entries, and reassigned outputs retain their final definition and value.

  • Input nodes that match columns in multiple datasets now produce an informative error instead of being assigned to a dataset implicitly.

  • mc_filter() and mc_compare() now use name exactly as supplied. suffix is appended only when a name is generated automatically from mc_name (#93).

  • mc_network() now provides clearer legend labels and node tooltips and omits duplicated parameter and dependency information (#41).

  • mc_summary() now applies digits and sep_keys consistently when returning stored summaries.

  • mc_summary() now returns summaries with sequential row names (#94).

  • mcmodule_tornado() now shows more tics on the x scale for better interpretation (#101).

  • trial_totals() now creates non-sampled input nodes from mctable or module data when sample_design is supplied (#95).

  • trial_totals() now preserves aggregation metadata on all derived trial totals, and includes some more complex cases tests (#109).

  • mc_keys() now validates that it returns one key row per node variate, and throws more clear warnings and error messages (#109).

  • Added data-raw/imports_example.R to document and standardise generation of the existing imports example datasets and related package objects.

  • mctable_bounds() now probes transformations with a deterministic grid mapped through the distribution in mc_func, instead of random draws. Bounds are reproducible, include the exact endpoints of bounded distributions, and no longer consume the random number stream. Previously, rnorm inputs defined by mean and sd were probed as if mean and sd were the only possible values.

  • mctable_bounds() no longer rounds transformed bounds to six significant digits, which could make distinct bounds appear equal.

  • eval_module() now applies mctable$transformation to fixed values of non-sampled inputs, so they are on the same scale as the sampled values.

  • mctable_bounds(), mctable_sobol_matrices(), eval_module() and trial_totals() now skip a transformation that returns only NA for the sample_space values, with a message, assuming sample_space is already on the model scale (as for test_origin in imports_mctable).

  • mctable_sobol_matrices() now accepts namespace-qualified distribution functions (e.g. mc2d::rpert), as create_mcnodes() does.

  • agg_variates() now keeps from_sample_design_fixed when aggregating sample-design nodes, and trial_totals() sets it to FALSE for inputs taken from sample_design, consistent with eval_module().

  • sample_space now accepts a single numeric value (e.g. "1", "c(1)", "c('1')" or "value = 1") as a constant input, equivalent to "min = 1, max = 1", and check_mctable() accepts bare numeric values.

  • eval_module() no longer fails when a multi-line quoted expression is passed directly to exp. The expression is named "exp" and the existing warning recommends naming it explicitly.

mcmodule 1.3.1

CRAN release: 2026-09-02

Lifecycle

Bug fixes

  • mc_plot() now draws boxplots above scatter points (#86).

  • get_node_list() now uses node_name instead of param_names when filtering in_nodes (#84).

  • optim_ndvar() no longer produces warnings related to empty mctable handling (#87).

  • mcmodule_converg() tests are now reproducible on CRAN. Tests for non-convergence now set a random seed, because false negatives are expected when using a very limited number of simulations (#87).

Documentation

mcmodule 1.3.0

CRAN release: 2026-05-25

New features

Bug fixes

  • Fixed a bug in mc_compare() when comparing a total mcnode with multiple data_names (#71).

  • Fixed an add_prefix() bug where totals node names were not correctly prefixed (#68).

  • Fixed a bug in eval_module() when package::function() nomenclature was used within expressions (#32).

  • Renamed filter_suffix to suffix (#77).

Documentation

  • Expanded the main package vignette, including sensitivity analysis examples (#49, #70).

  • Added sensitivity analysis vignette (#49, #70).

  • Expanded mc_compare() documentation with align_uncertainty explanation (#65).

  • Updated the package citation and README details (#57, #69).

mcmodule 1.2.0

CRAN release: 2026-03-02

Breaking changes

  • create_mcnodes() no longer automatically calculates rpert() mode when not provided. This was not widely used and lacked transparency.

New features

Minor improvements and bug fixes

  • add_prefix() no longer has issues when mcmodule uses pipes (#51).

  • add_prefix() and combine_modules() now handle absent module metadata in nodes.

  • create_mcnodes() now handles argument ordering and issues warnings for multiple column matches (#34).

  • eval_module() improves handling of mcnode creation from data when nodes are not in mctable or prev_mcmodule (#32).

  • get_node_list() now uses custom AST traversal parser and improves mcnode ordering for better network visualization(#39, #40).

  • mc_network() fixes bug related to unprefixed inputs in trial_totals output nodes.

  • trial_totals() now combines keys from all inputs, not just the main mc_name.

  • eval_module()and set_mctable()now can use sensi_baseline and sensi_variation to perfrom One-At-a-Time sensitivity analysis. This will be further developed in future releases (#49).

  • Not exported functions mc_summary_keys() and node_list_summary() have been removed.

  • The distinction between “exp” and “module” terminology has been clarified throughout the package.

  • Function documentation has been extended and harmonised.

  • Documentation updated to clarify use of mcstoc() and mcdata() within expressions in eval_module() (#32, #42).

  • Vignettes updated to document new analysis functions and features (#3, #4, #32, #48, #49, #50).

  • Website links updated to https://nataliaciria.com/mcmodule/.

mcmodule 1.1.1

CRAN release: 2025-11-25

mcmodule 1.1.0

CRAN release: 2025-10-22

  • Re-submission to CRAN. Removed unexported function examples.

  • eval_module() gains match_keys parameter for flexible data-mcnode matching.

  • eval_module() now supports multiple prev_mcmodule data names.

  • eval_module() improves R function handling within mcmodule expressions.

  • trial_totals() now supports agg_suffix skipping.

  • at_least_one() improves agg_keys combination.

  • Fixed missing agg_suffix handling.

  • Fixed dimension matching for aggregated nodes.

  • Fixed prefix issues in combined probability nodes.

  • NA removal added in key columns.

  • Added tests for totals custom names and various dimension matching scenarios.

mcmodule 1.0.1

  • Re-submission to CRAN. Removed unexported function examples, replaced dontrun with donttest, added vignette link to DESCRIPTION, and included citation file.

mcmodule 1.0.0

  • Initial CRAN submission.