1. .Rd files, example code, and the autotest workflow | 2. Internal structure of the autotest workflow | 3. autotest-ing the stats::cov function | 3.1 Listing tests without conducting them | 3.2 Conducting tests | 3.4 Controlling which tests are conducted | 4. autotest-ing your package | 4.2 Finer control over testing expectations

Integer input | Vector input | List-column conversion | Return results and documentation | Documentation of input parameters | General Procedure

1. .Rd files, example code, and the autotest workflow | 2. Internal structure of the autotest workflow | 3. autotest-ing the stats::cov function | 3.1 Listing tests without conducting them | 3.2 Conducting tests | 3.4 Controlling which tests are conducted | 4. autotest-ing your package | 4.2 Finer control over testing expectations

Integer input | Vector input | List-column conversion | Return results and documentation | Documentation of input parameters | General Procedure

Introduction | Nomenclature | Spatial clustering versus spatially-constrained clustering | Spatial clustering | Spatially-constrained clustering | Algorithms for spatially-constrained clustering | The SKATER algorithm | The REDCAP algorithms | The "full" clustering algorithm | Using the package | Distance-based versus covariance-based clustering | Observation and reference matrices for covariance clustering | Observation and reference matrices for correlation clustering | Clustering Origin-Destination (OD) matrices | Interpretation of OD clusters | Appendix: Why clusters of significant net in- or out-flow can not be identified | A formal argument | References

Introduction | Nomenclature | Spatial clustering versus spatially-constrained clustering | Spatial clustering | Spatially-constrained clustering | Algorithms for spatially-constrained clustering | The SKATER algorithm | The REDCAP algorithms | The "full" clustering algorithm | Using the package | Distance-based versus covariance-based clustering | Observation and reference matrices for covariance clustering | Observation and reference matrices for correlation clustering | Clustering Origin-Destination (OD) matrices | Interpretation of OD clusters | Appendix: Why clusters of significant net in- or out-flow can not be identified | A formal argument | References

Prerequisites | 1. Google Cloud Console | 2. Authorize once, locally | 3. Code | 4. Environment variables | 5. Deploy credentials to the droplet | 6. Verify | 8. Transfer maintenance | Editor search endpoints | GET /send_search | GET /click/ | GET /list_searches | GET /deactivate_search | Notify email cache

Prerequisites | 1. Google Cloud Console | 2. Authorize once, locally | 3. Code | 4. Environment variables | 5. Deploy credentials to the droplet | 6. Verify | 8. Transfer maintenance | Editor search endpoints | GET /send_search | GET /click/ | GET /list_searches | GET /deactivate_search | Notify email cache

How the pieces fit together | Starting from scratch | Prerequisites | Install Git and Docker | Set the Git user | Get the code | Environment variables | AirTable | Data directory | DNS | TLS certificate | Start the service | Cron job | Check that it works | General maintenance | Uptime alert | Weekly redeploy | Viewing, changing and checking the cron job | Restarting the service | Backing up the data and secrets | Downloading a backup | Restoring a backup | Updating the operating system | Recreating the certificate | Troubleshooting | Transferring maintenance | Operations only | Transferring credentials | Other items to update

How the pieces fit together | Starting from scratch | Prerequisites | Install Git and Docker | Set the Git user | Get the code | Environment variables | AirTable | Data directory | DNS | TLS certificate | Start the service | Cron job | Check that it works | General maintenance | Uptime alert | Weekly redeploy | Viewing, changing and checking the cron job | Restarting the service | Backing up the data and secrets | Downloading a backup | Restoring a backup | Updating the operating system | Recreating the certificate | Troubleshooting | Transferring maintenance | Operations only | Transferring credentials | Other items to update

1. Direct calls of the update functions | 2. Update from a local CRAN mirror

1. Direct calls of the update functions | 2. Update from a local CRAN mirror

1. The check function | 2. The output function | 3. Creating new checks | 3.1 New Local Checks (for package users) | 3.2 New pkgcheck Checks (for pkgcheck developers) | 3.2a Check types | 3.2b Testing new checks

1. The check function | 2. The output function | 3. Creating new checks | 3.1 New Local Checks (for package users) | 3.2 New pkgcheck Checks (for pkgcheck developers) | 3.2a Check types | 3.2b Testing new checks

autotest | Changes in response to autotest | goodpractice | Changes in response to goodpractice | pkgcheck | Changes in response to pkgcheck

autotest | Changes in response to autotest | goodpractice | Changes in response to goodpractice | pkgcheck | Changes in response to pkgcheck

1 Flow Aggregation | 2 Flow Dispersal | 3 Merging directed flows | 4. Flows from spatial interaction models | 5 Flows under optimal allocation | Optimization algorithms

1 Flow Aggregation | 2 Flow Dispersal | 3 Merging directed flows | 4. Flows from spatial interaction models | 5 Flows under optimal allocation | Optimization algorithms

1 Background: Directed Graphs | 1.1 Dual-Weighted Directed Graphs | 2 Introduction to dodgr | 3 Graphs and Street Networks | 3.1 Graph Components | 3.2 Weighting Profiles | 3.3 Random Sub-Graphs | 4 Distance Matrices: dodgr_dists() | 4.1 Aligning Routing Points to Graphs | 4.2 Shortest Path Calculations: Priority Queues | 5 Graph Contraction | 5.1 Routing on Contracted Graphs | 6 Shortest Paths | Bibliography

1 Street Networks and Time-Based Routing | 2. Silicate data and the dodgr_streetnet_sc() function | 3. The weight_streetnet() function | 3.1 Weighting profiles and the write_dodgr_wt_profile function | 4. Time-based routing and the dodgr_times() function | 4.1 Time-based paths and flow aggregation

1 Full Distance Information for Edge Categories | 2. Proportional Distances along each Edge Category | 3. Proportional Distances within a Threshold Distance

1 Background: Directed Graphs | 1.1 Dual-Weighted Directed Graphs | 2 Introduction to dodgr | 3 Graphs and Street Networks | 3.1 Graph Components | 3.2 Weighting Profiles | 3.3 Random Sub-Graphs | 4 Distance Matrices: dodgr_dists() | 4.1 Aligning Routing Points to Graphs | 4.2 Shortest Path Calculations: Priority Queues | 5 Graph Contraction | 5.1 Routing on Contracted Graphs | 6 Shortest Paths | Bibliography

1 Street Networks and Time-Based Routing | 2. Silicate data and the dodgr_streetnet_sc() function | 3. The weight_streetnet() function | 3.1 Weighting profiles and the write_dodgr_wt_profile function | 4. Time-based routing and the dodgr_times() function | 4.1 Time-based paths and flow aggregation

1 Full Distance Information for Edge Categories | 2. Proportional Distances along each Edge Category | 3. Proportional Distances within a Threshold Distance

The pkgcheck Docker container | How to get your package to pass rOpenSci's 'pkgcheck' system

The pkgcheck Docker container | How to get your package to pass rOpenSci's 'pkgcheck' system

The 'Makefile' | Adding new checks

The 'Makefile' | Adding new checks

1. Introduction | 2. Elevation Data | Example usage of elevation data

1. Introduction | 1.1 Bounding boxes: the getbb() function | 2. The overpass API | 2.1. osmdata queries | 2.2 Extracting OSM data from a query | 2.3. Query example | 3. The osmdata object | 3.1. The osmdata_xml() function | 3.2. The osmdata_sf() function | 3.3. The osmdata_sp() function | 4. Recursive searching | 4.1. Example | 4.2 Relation example | 5. Additional Functionality | 6. Related Packages | 7. References

1. Categorical data: add_osm_groups | 1.1 Hulls around groups | 1.2 Inclusive, exclusive, and bisected polygons | 1.3 Adjusting colours with adjust_colours | 1.4 Dark-on-Light Highlights | 1.5 Visualising clustering data | 1.6 The Colour Matrix: Colouring Several Regions | 1.7 Bounding areas within named highways | 2. Continuous data: add_osm_surface | 2.1 Colourbar legends for data surfaces | 2.1 Surfaces and data perimeters | 2.3 Further control of surface appearance

1. Categorical data: add_osm_groups | 1.1 Hulls around groups | 1.2 Inclusive, exclusive, and bisected polygons | 1.3 Adjusting colours with adjust_colours | 1.4 Dark-on-Light Highlights | 1.5 Visualising clustering data | 1.6 The Colour Matrix: Colouring Several Regions | 1.7 Bounding areas within named highways | 2. Continuous data: add_osm_surface | 2.1 Colourbar legends for data surfaces | 2.1 Surfaces and data perimeters | 2.3 Further control of surface appearance

Debugging Procedure | Check that the API is online | Check log of recent requests | Check installation of system dependencies | Check system output and error logs | Manually running checks

Debugging Procedure | Check that the API is online | Check log of recent requests | Check installation of system dependencies | Check system output and error logs | Manually running checks

Why goodpractice? | Quick start | What gp() actually does | Choosing what to run | Check groups | Excluding check groups | Excluding files | Parallel preparation | Tidyverse style checks | Working with results | Custom checks

Why goodpractice? | Quick start | What gp() actually does | Choosing what to run | Check groups | Excluding check groups | Excluding files | Parallel preparation | Tidyverse style checks | Working with results | Custom checks

Local caching and updating for users | Data updating for developers

Local caching and updating for users | Data updating for developers

Detailed Usage | Benchmarks of geodesic accuracy | Performance comparison

Detailed Usage | Benchmarks of geodesic accuracy | Performance comparison

Text searches for R packages | Using search engines | Using language models | Using 'pkgmatch' | Searches based on entire packages

Text searches for R packages | Using search engines | Using language models | Using 'pkgmatch' | Searches based on entire packages

1. editorcheck | 2. editorcheck_contents | 3. pkgmatch | 4. mean | 5. stats_badge | 6. log | 7. clear_cache | 8. stdlogs

1. editorcheck | 2. editorcheck_contents | 3. pkgmatch | 4. mean | 5. stats_badge | 6. log | 7. clear_cache | 8. stdlogs

What does the package do? | Using an R package as input

What does the package do? | Using an R package as input

What's happening inside of gp()? | Writing custom checks | Checks without corresponding preparation steps | Including a preparation step

What's happening inside of gp()? | Writing custom checks | Checks without corresponding preparation steps | Including a preparation step

Installation on Linux systems | Installation on macOS systems

Installation on Linux systems | Installation on macOS systems

1. The package skeleton | 2. Enabling srr roclets for a package | 3. roxygen2 tags | 3.1 Format of srr documentation | 3.2 Locations of srrstats documentation | 3.3 Documenting standards for documentation | 3.4 @srrstatsNA tags for non-applicable standards | 4. The srr workflow

The models used here | Combining metrics within models

The models used here | Combining metrics within models

1. OpenStreetMap Data Structure | 2. Simple Features Data Structure | 3. How osmdata translates OSM into Simple Features | 3.1. OSM Nodes | 3.2. OSM Ways | 3.3 OSM Relations | 3.3(a) Multipolygon Relations | 3.3(b) Multilinestring Relations | 4. GDAL Translation of OSM into Simple Features | 4.1. OSM Nodes | 4.2. OSM Ways | 4.3 OSM Relations | 4.3(a) Multipolygon Relations | 4.3(b) Multilinestring Relations | 5 Examples | 5.1 Routing | 5.1(a) Routing with sf/GDAL | 5.1(b) Routing with osmdata

Default Grid Format | Code | Issue Authors | Issue Contributors | Section Organisation | List Format | Text Format

Default Grid Format | Code | Issue Authors | Issue Contributors | Section Organisation | List Format | Text Format

What does this package do for me? | How do I use it? | Practical tips | Mapbox API tokens | Map generation | Map rectification | Types of map markings and types of spatial objects | Bonus Feature: Polygon Aggregation | How it works

What does this package do for me? | How do I use it? | Practical tips | Mapbox API tokens | Map generation | Map rectification | Types of map markings and types of spatial objects | Bonus Feature: Polygon Aggregation | How it works

1 Background: GTFS and other R packages | 2. Routing | 2.1 GTFS Timetables | 2.2. Routing by mode of transport | 2.3. Routing for earliest arrivals or earliest departures | 3. Convenience Functions: go_home() and go_to_work()

Basic Usage | Extending transfer tables | Modifying transfer tables | Transfer distances | Transfer distances and travel times | A more realistic example

Maximum Traveltimes | Fastest Routes versus Minimal-Transfer Routes | The Traveltimes Algorithm

1 Background: GTFS and other R packages | 2. Routing | 2.1 GTFS Timetables | 2.2. Routing by mode of transport | 2.3. Routing for earliest arrivals or earliest departures | 3. Convenience Functions: go_home() and go_to_work()

Basic Usage | Extending transfer tables | Modifying transfer tables | Transfer distances | Transfer distances and travel times | A more realistic example

Maximum Traveltimes | Fastest Routes versus Minimal-Transfer Routes | The Traveltimes Algorithm

The deposits client | Initialising a deposits client | Metadata | Passing metadata to a deposits client | Creating a new deposit | Retrieving deposits | Uploading files to deposits | Pre-generating frictionless metadata files prior to upload | Editing and updating deposits | Example workflow | Publishing a deposit

Explicit version control | Services without explicit version control

Generating "datapackage.json" files | Generation by uploading files | Local generation | Reading and editing "datapackage.json" files | Updating "datapackage.json" on deposits service

R6 methods | Initialising a deposits client | The R6 client structure

Installation | Setup: API Tokens

Initial Metadata | Preparing data sources | Frictionless metadata | Initiating a remote deposit | Uploading files to a remote deposit | File compression | Editing and updating files | Publishing a deposit

Dublin Core Metadata | Metadata Validation | Metadata to specify connections between deposits | Metadata templates | Valid JSON Files | Metadata and the deposits frictionless workflow

Accuracy of estimated motorcar travel times

1. Introduction | 2. Downloading Data | 2.1 osmdata | 2.2 Negation | 2.3 Additional key-value pairs | 2.4 Downloading with osm_structures and make_osm_map | 2.4.1 The london data of osmplotr | 3. Downloading connected highways | 3.1 connect_highways in detail | 4. Producing maps | 4.1 Saving Maps | 4.2 Plotting different OSM Structures | 4.3 Filling within boundary lines | 4.4 Automating map production | 4.5 Axes

1 Introduction | 2 Data Extraction and Conversion | 3 Plotting | Further Demonstrations

1. Introduction | 2. Downloading Data | 2.1 osmdata | 2.2 Negation | 2.3 Additional key-value pairs | 2.4 Downloading with osm_structures and make_osm_map | 2.4.1 The london data of osmplotr | 3. Downloading connected highways | 3.1 connect_highways in detail | 4. Producing maps | 4.1 Saving Maps | 4.2 Plotting different OSM Structures | 4.3 Filling within boundary lines | 4.4 Automating map production | 4.5 Axes

1 Introduction | 2 Data Extraction and Conversion | 3 Plotting | Further Demonstrations

1. Introduction | 2. Query splitting | 3. Automatic bbox splitting

Overview of Package Statistics | Lines of Code | "desc": The package "DESCRIPTION" file | 1.3 "objects": Objects in all languages | "network": Relationships between objects | "external_calls": All calls made to all R functions

Overview of Package Statistics | Lines of Code | "desc": The package "DESCRIPTION" file | 1.3 "objects": Objects in all languages | "network": Relationships between objects | "external_calls": All calls made to all R functions

1. Introduction | 2. Main Functions | 3. Downloading Data | 3.1 Downloading data for specific date ranges | 3.2 Refreshing data sources | 4. Storing Data | 5. Accessing Aggregate Data | 5.1 Origin-Destination Matrices | 5.1.1. Temporal filtering of trip matrices | 5.1.2. Demographic filtering of trip matrices | 5.1.3. Standardising trip matrices by durations of operation | 5.2. Station Data | 5.3. Summary Statistics | 5.4. Time Series of Daily Trips | 6. Direct database access | 7. Visualisation of bicycle trips | 7.1 Visualisation using R Base functions | 7.2 A More Sophisticated Visualisation

1. Introduction | 2. Main Functions | 3. Downloading Data | 3.1 Downloading data for specific date ranges | 3.2 Refreshing data sources | 4. Storing Data | 5. Accessing Aggregate Data | 5.1 Origin-Destination Matrices | 5.1.1. Temporal filtering of trip matrices | 5.1.2. Demographic filtering of trip matrices | 5.1.3. Standardising trip matrices by durations of operation | 5.2. Station Data | 5.3. Summary Statistics | 5.4. Time Series of Daily Trips | 6. Direct database access | 7. Visualisation of bicycle trips | 7.1 Visualisation using R Base functions | 7.2 A More Sophisticated Visualisation