Man pages for spew
SPEW Framework for Generating Synthetic Ecosystems

add_characteristicAdd a characteristic to an existing population
add_char_demoAdd characteristic by matching on demographics
align_pumsMatch the pums variables with marginal totals
allocate_countRe-allocate excess counts to other locations
assign_placeAssign a place to a person
assign_place_coordsAssign a place with long/lat coords to a synthetic population
assign_schoolsAssign schools to a synthetic population.
assign_schools_innerFunction which assigns schools
assign_weightsAssign weights for ipf-based sampling
assign_workplacesAssign an ESRI workplace to synthetic population
assign_workplaces_innerFunction which assigns workplaces
base_map_themeThe base map theme for SPEW
calc_distsCalculate distance b/w cont table row and pums
call_spewWrapper for reading, formatting, and writing SPEW ecosystems
cap_defaultHow to weight the capacities of of school.
ccountAdjust number of households
checkDFCheck if df is in the right format
check_logfileCheck to see if a SPEW log-file is complete
check_pathCheck the path to output to run diags
check_place_idsCheck the Place ID's match
check_pop_tableCheck the pop_table has all the necessary components
check_puma_idsCheck the puma id's match
check_pumsCheck that the pums has all the required components
check_shapefileCheck the shapefile has the necessary components
check_var_namesCheck to see if variable names are in SPEW outputs
clean_namesRemove whitespace, capitals, and non ASCII
combine_countsCombine two rows of a pop_table into one
create_columnParse a SPEW Log-file to into an appropriate column
delawareInput data for Keny County, Delaware
demo_sampleSample extra characteristics from char pums and add them to...
euclidean_distGet the euclidean distance between two points (x1, y1) and...
extract_st_co_trExtract the state, county, and tract ID from a string
extrapolate_probs_to_pumsTake unique probabilites for table and spread them to rest of...
extrapolate_probs_to_pums_jointTake unique probabilites for table and spread them to rest of...
fill_cont_tableFill marginal contingency with ipf
fips_to_nameTranslate FIPS number to place name
format_dataFormat data before entering make
get_base_mapGet the base map for plotting
get_centersGet the center longitude and latitude for each region
get_coords_scaledGetting a plotting data frame
get_data_groupExtract data-group from location name
get_dfsGet the dataframes from SPEW summary output
get_dist_matGet the distance matrix
get_distsGet the distances between the schools and the people.
get_envsGather the unique assignments for the region
get_filenamesGet the filenames of the SPEW output, separated by the level
get_headerExtract the header from a population
get_levelObtain the correct level for ipums data
get_pop_totalsGet the population totals from a summarized SPEW region
get_rowsExtract rows with a certain character
get_shapefile_indicesObtain the shapefile indices corresponding to the pop table
get_targetsObtain the target marginals for IPF
get_total_timeExtract the total run-time from a SPEW log-file
get_weight_distsWeight place assignment probabilities
haversineGet the haversine distance between two points (x1, y1) and...
haversine_distGet the haversine distance between two points (x1, y1) and...
impute_missing_valsImpute Missing Values in a data frame
make_ipf_objSet up for creating a set of marginal information for IPF...
make_mm_objMake moment matching object
merge_reduceWrapper function for merge
organize_summariesOrganize the summaries into a more palatable format
people_to_householdsConvert a population count to household count
plot_agentsPlot the agents of synthetic ecosystem
plot_bdsPlot the boundaries of the synthetic ecosystem
plot_characteristic_proportionsPlot characteristic summary output from...
plot_envPlot the environments of the synthetic ecosystem
plot_interiorPlot the interior of the synthetic ecosystem
plot_labsAdd the labels and the theme to the plot
plot_pop_totalsPlot characteristic summary output from...
plot_regionPlot SPEW region
plot_roadsPlot the roads of the synthetic ecosystem
plot_synecoPlot Synthetic Ecosystem
print_region_listWrite out information on each region
read_dataRead SPEW input data from files
read_marginalsRead in the marginals population characteristic totals
read_momentsRead in the R data object for moment matching
read_pop_tableRead in the population counts
read_roadsRead in road lines shapefiles
read_shapespatial_to_ogrRead in shapefile using readOGR
remove_countRemove a row from the pop_table
remove_excessRemove comma's, accents, etc. from name
remove_holesRemove holes from an object of class Polygon
remove_wordsRemove excess words
replace_wordReplace an existing word
sample_householdsSample appropriate indices from household PUMS
sample_ipfSample households PUMS accoording to IPF
sample_locationsGeneric sampling locations function
sample_locations_roadsSample coordinates from roads
sample_locations_uniformSample from a particular polygon shapefile
sample_mmSample households PUMS according to MM
sample_peopleSample from the individual person PUMS data frame
sample_uniformSample households uniformly
sample_with_contSample from pums
samp_roadsSample the locations from a SpatialLines object
solve_mm_for_jointDo the Moment Matching solving for joint distribution
solve_mm_for_varDo the MM solving for an individual variable
solve_mm_weightsWeight the records of the PUMS so the averages in mm_df will...
spewSPEW algorithm to generate synthetic ecosystems
spewlog_to_dfConvert a SPEW Logfile into a data-frame
spew_mcRun SPEW in Parallel with a Multicore backend
spew_mpiRun SPEW in Parallel with an MPI backend
spew-packagespew: an R package for generating synthetic ecosystems
spew_placeGenerate synthetic ecosystem for single place
spew_seqRun SPEW Sequentially
spew_sockRun SPEW in Parallel with a SOCK backend
standardize_pop_tableMake sure pop_table has the appropriate columns
subset_pumsAlign pums with marginal totals
subset_schoolsSubset the schools to that of the county
subset_shapes_roadsSubset the shapefile and road lines to proper roads within...
summarize_environmentReturn the unique environment assignments in a region
summarize_featuresSummarize individual features of a region
summarize_spewSummarize a SPEW region
summarize_spew_outSummarize spew output
summarize_spew_regionSummarize a singular region from spew output
summarize_synecoSummarize synthetic ecosystem for SPEW console output
summarize_top_regionSummarize the region in a more human-readable format
tartanvilleInput data for Tartanville
update_freqsUpdate frequencies to match # of households
uruguayInput data for Uruguay
usTable of US states and counties
us_pums_sfAn example marginal distribution table
verify_columnVerify the column is the correct size
weight_distsWeight school assignment probabilities
weight_dists2Weight school assignment probabilities
weight_dists_CWeight school assignment probabilities by capacity only
weight_dists_DWeight school assignment probabilities, distance only
write_dataOutput our final synthetic populations as csv's
write_pop_tableWrite out the final, formatted table
write_schoolsWrite school environment
write_workplacesWrite workplaces environment
spew documentation built on Nov. 17, 2017, 7:36 a.m.