summarize_spew_out: Summarize spew output
In spew: SPEW Framework for Generating Synthetic Ecosystems

Description Usage Arguments Value Note Examples

Summarize spew output

summarize_spew_out(syneco = NULL, vars_to_sum_h, vars_to_sum_p,
  vars_to_sum_env = NULL, samp_size = 10^4, type = "US",
  summary_level = 2, marginals = NULL, output_dir = NULL,
  top_region_id = NULL, has_marg = FALSE)

`syneco`	output from the 'spew' function
`vars_to_sum_h`	character vector of variables from the household data frame output to summarize
`vars_to_sum_p`	character vector of variables from the person data frame output to summarize
`vars_to_sum_env`	character vector of variables from the person data frame which correspond to environment assignments. Default is NULL.
`samp_size`	number of agents to retain from each lower-level region, for plotting purposes only. Default is 10^4.
`type`	Only used when output_dir is specified."US" for a US population, "IPUMS" for IPUMS population, or "custom" for a custom population. This effects what the summary levels are.
`summary_level`	Only used when output_dir is specified. IFor the US, 1-state, 2-county, 3-tract. For IPUMS, 1 -country, 2-province. For "custom," these are defined by the user's input data.
`marginals`	list containing all of the marginal totals. See ?make_ipf_marg for more details.
`output_dir`	path to top level directory of SPEW folders. Ex. "./10" for Delaware. Default is NULL. In the case it is NULL, we do not need to read in data.
`top_region_id`	name of the region. Default is NULL. It is only used in the case where we directly summarize the syneco object.
`has_marg`	Does the region of marginals to refer to? Logical. Default is FALSE.

list with the household summary list, people summary list, header for households, and header for people, and a data frame of plotting coordinates by summary region

This function is only guaranteed to work when you provide marginals describing how a category is "cut." If a certain category is not represented, then the final totals in each category may be off.

data(tartanville)

tartanville_syneco <- spew(tartanville$pop_table, tartanville$shapefile, 
                           tartanville$pums_h, tartanville$pums_p)
                           
out <-  summarize_spew_out(tartanville_syneco, 
                           vars_to_sum_h = c("puma_id"), 
                           vars_to_sum_p = c("SEX"), 
                           vars_to_sum_env = NULL, 
                           top_region_id = "Tartanville") 
print(out)