API Reference

This section provides links to the complete API documentation for all functions in the movr package.

Function Categories

Visualization Functions

  • plot_traj3d() - 3D trajectory visualization

  • plot_flowmap() - Flow map visualization

  • plot_traj_graph() - Trajectory graph visualization

  • plot_traj3d() - 3D trajectory plots

  • plot.heatmap() - Heatmap visualization

Flow Analysis

  • flowmap() - Create flow maps from mobility data

  • flowmap2() - Alternative flow map creation

  • flow.stat() - Flow statistics

Spatial Analysis

  • radius_of_gyration() - Calculate radius of gyration

  • spatial.corr() - Spatial correlation analysis

  • point.coverage() - Point coverage analysis

  • people.occurrence() - People occurrence analysis

  • voronoi3d() - 3D Voronoi tessellation

  • voronoi2polygons() - 2D Voronoi tessellation

Temporal Analysis

  • hour2tod() - Time-of-day analysis

  • hour2tow() - Time-of-week analysis

  • hour2date() - Hour to date conversion

  • gen_sessions() - Generate mobility sessions

  • entropy.spacetime() - Spatio-temporal entropy

  • entropy.space() - Spatial entropy

  • entropy.rand() - Random entropy

Data Quality

  • dq.traj() - Trajectory data quality assessment

  • dq.traj2() - Alternative trajectory quality check

  • dq.point() - Point-level quality assessment

  • dq.point2() - Alternative point quality check

  • dq.iovan() - Iovan distance quality check

Statistical Analysis

  • fit.power.law() - Fit power law distribution

  • fit.truncated.power.law() - Fit truncated power law

  • fit.polyexp() - Fit polyexponential distribution

  • RMSE() - Root Mean Square Error calculation

Coordinate Transformations

  • cart2geo() - Cartesian to geographic coordinates

  • geo2cart() - Geographic to Cartesian coordinates

  • cart2geo.radian() - Cartesian to geographic (radians)

  • geo2cart.radian() - Geographic to Cartesian (radians)

  • deg2rad() - Degrees to radians

  • rad2deg() - Radians to degrees

  • lonlat2xy() - Longitude/latitude to x/y coordinates

  • stcoords() - Spatio-temporal coordinates

Utility Functions

  • gcd() - Great circle distance

  • euc.dist() - Euclidean distance

  • pairwise.dist() - Pairwise distances

  • midpoint() - Calculate midpoint

  • in.area() - Check if points are in area

  • rot90() - Rotate matrix 90 degrees

  • rep_each() - Repeat each element

  • melt_time() - Melt time data

  • cal_place_dwelling() - Calculate place dwelling

  • traj3d.close() - Close 3D trajectory

  • standardize() - Standardize data

  • standardize_st() - Spatio-temporal standardization

Sequence Analysis

  • seq_approximate() - Approximate sequence

  • seq_collapsed() - Collapse sequence

  • seq_distinct() - Distinct sequence

  • seq_dist() - Sequence distance

Binning Functions

  • vbin() - Vector binning

  • vbin.range() - Vector binning with range

  • vbin.grid() - Grid-based binning

  • heatmap.levels() - Heatmap levels

Plotting Utilities

  • minor.ticks.axis() - Minor tick marks for axes

  • Rcolors() - R color palettes

Getting Help

To get detailed help for any function:

# Get help for a specific function
?plot_traj3d
?flowmap
?radius_of_gyration

# Search for functions
??trajectory
??flow
??spatial

# View all functions in the package
ls("package:movr")

# View package information
packageVersion("movr")
sessionInfo()

Function Arguments

Most functions in movr follow consistent parameter naming:

  • x, y - Spatial coordinates (longitude, latitude)

  • z - Temporal coordinate (timestamp)

  • id - Individual identifier

  • time - Time column name

  • from, to - Origin and destination for flow analysis

  • weight - Weight column for flow analysis

Data Format

The movr package expects mobility data in the following format:

# Example data structure
movement <- data.frame(
  user_id = c("user1", "user1", "user2", "user2"),
  timestamp = c("2023-01-01 10:00:00", "2023-01-01 11:00:00",
                "2023-01-01 10:30:00", "2023-01-01 11:30:00"),
  lon = c(-74.006, -74.007, -73.985, -73.986),
  lat = c(40.712, 40.713, 40.758, 40.759)
)

Required columns: * user_id - Unique identifier for each individual * timestamp - Time of the location record * lon - Longitude coordinate * lat - Latitude coordinate

Optional columns: * origin_cell, destination_cell - For flow analysis * flow_count, population - For weighted analysis * Any additional metadata columns

For more detailed information about each function, use the R help system:

help(package = "movr")