Package: metaweave 0.4.0

Gabriel Munoz

metaweave: Spatial Ecological Network Inference

A model-agnostic framework for reconstructing and analysing spatially explicit ecological networks from species distributions and ecological inference models. Supports arbitrary ecological groups and includes stochastic block and maximum-entropy inference backends, simulation helpers, network summaries, and spatial mapping utilities.

Authors:Gabriel Munoz [aut, cre]

metaweave_0.4.0.tar.gz
metaweave_0.4.0.zip(r-4.7-any)metaweave_0.4.0.zip(r-4.6-any)metaweave_0.4.0.zip(r-4.5-any)
metaweave_0.4.0.tgz(r-4.6-any)metaweave_0.4.0.tgz(r-4.5-any)
metaweave_0.4.0.tar.gz(r-4.7-any)metaweave_0.4.0.tar.gz(r-4.6-any)
metaweave_0.4.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
metaweave/json (API)

# Install 'metaweave' in R:
install.packages('metaweave', repos = c('https://fgabriel1891.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/fgabriel1891/metaweave/issues

On CRAN:

Conda:

4.70 score 41 exports 2 dependencies

Last updated from:694b83eba9. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK132
source / vignettesOK180
linux-releaseOK122
macos-releaseOK176
macos-oldrelOK156
windows-develOK92
windows-releaseOK83
windows-oldrelOK96
wasm-releaseOK119

Exports:add_network_metricsassemble_communitiesblock_modelbuild_range_stackcreate_standard_gridcrop_filter_stackdownscale_networksinfer_networkinfer_networksinteraction_table_to_matrixlist_shapefileslocal_block_networklocal_probability_networkmake_bboxmap_metricsmaxent_modelnetwork_metrics_rasternew_assemblagenew_distribution_collectionnew_ecological_networknew_inference_modelnew_network_collectionnew_spatial_resultprepare_range_stacksprint.assemblageprint.distribution_collectionprint.ecological_networkprint.inference_modelprint.network_collectionprobability_matrix_modelrarefied_network_metricrasterize_range_filerasterize_range_rowsreconstruct_networksrun_network_downscalingrun_spatial_inferencesbm_modelsimulate_interaction_countssimulate_networksummarize_networksummarize_networks

Dependencies:Rcppterra

Maximum-entropy network inference
Directed food web | Fixed degree sequences | Reproducibility | Reference
Rendered frommaxent-backend.Rmdusingknitr::rmarkdown

Last update: 2026-09-14
Started: 2026-09-14

MetaWeave: rationale, methods, and simulation
Rationale | Core workflow | Inference methods | Block model | Species probability matrix | Simulated example | Create a landscape and distributions | Define a block-level interaction model | Reconstruct local networks | Simulating interaction observations | Standardizing a network metric | Using a species-level probability matrix | Interpretation and limits
Rendered frommethods-and-simulation.Rmdusingknitr::rmarkdown

Last update: 2026-09-14
Started: 2026-09-14

Reconstructing palm-mammal networks with MetaWeave
1. Load packages and data | 2. Clean species ranges | 3. Match ranges and interactions | 4. Build an observed-metaweb baseline | 5. Fit a stochastic block model | 6. Reconstruct and map local SBM networks | 7. Species-pair representation of the retained fit
Rendered frompalm-frugivore-interactions.Rmdusingknitr::rmarkdown

Last update: 2026-09-14
Started: 2026-08-01

Reconstructing palm-mammal networks with MetaWeave
1. Load packages and data | 2. Clean species ranges | 3. Match ranges and interactions | 4. Build an observed-metaweb baseline | 5. Fit a stochastic block model | 6. Reconstruct and map local SBM networks | 7. Species-pair representation of the retained fit
Rendered frompalm-mammal-workflow.Rmdusingknitr::rmarkdown

Last update: 2026-09-14
Started: 2026-09-14

MetaWeave architecture
Vision | Object pipeline | Pluggable inference | Design boundaries
Rendered fromarchitecture.Rmdusingknitr::rmarkdown

Last update: 2026-08-01
Started: 2026-08-01

Readme and manuals

Help Manual

Help pageTopics
Add standard metrics to network collectionadd_network_metrics
Assemble local communities from aligned distribution rastersassemble_communities
Construct a generic stochastic block model backendblock_model
Build a species range stackbuild_range_stack
Create a standard raster gridcreate_standard_grid
Crop a stack and remove species absent from the regioncrop_filter_stack
Compatibility wrapper for spatial network downscalingdownscale_networks
Infer a network for one assemblageinfer_network
Infer networks for many assemblagesinfer_networks
Convert an interaction table to a matrixinteraction_table_to_matrix
List ESRI shapefileslist_shapefiles
Build one local generic block-model network directlylocal_block_network
Build one local palm-mammal probability network directlylocal_probability_network
Create a bounding-box polygonmake_bbox
Map cell metrics back to rastersmap_metrics
Maximum-entropy ecological network modelmaxent_model
Compatibility alias returning metric rastersnetwork_metrics_raster
Construct a local assemblagenew_assemblage
Construct a distribution collectionnew_distribution_collection
Construct an ecological networknew_ecological_network
Construct a pluggable inference modelnew_inference_model
Construct a collection of spatial ecological networksnew_network_collection
Construct a spatial resultnew_spatial_result
Prepare palm and mammal range stacksprepare_range_stacks
Print a MetaWeave objectprint.assemblage print.distribution_collection print.ecological_network print.inference_model print.network_collection
Construct a species-level probability-matrix modelprobability_matrix_model
Placeholder adapter for rarefaction packagesrarefied_network_metric
Rasterize one range filerasterize_range_file
Rasterize rows grouped by speciesrasterize_range_rows
Reconstruct spatial networks from arbitrary distribution groupsreconstruct_networks
Complete compatibility workflowrun_network_downscaling
Run generic spatial ecological-network inferencerun_spatial_inference
Construct the original palm-mammal SBM backendsbm_model
Simulate an interaction-count matrixsimulate_interaction_counts
Simulate a networksimulate_network
Summarize one ecological networksummarize_network
Summarize a collection of networkssummarize_networks