rm(list = ls())
gc()
library(dplyr)
library(data.table)
library(readxl)
library(testthat)
data("seats10")
data(state)
states <- data.table(state_abb = state.abb,
state = state.name)
pop2010 <- fread("data/pop/pop2010.csv")
true_pv <- read_excel("data-raw/PriorityValues2010.xls", skip = 7,
col_names = c("house_seat", "priority", "state", "state_seat"))
setDT(true_pv)
invisible(apportion(pop2010, store_priority = TRUE, total_seats = 440))
prio2 <- melt(priority_scores, id = "state", value = "priority")
prio2[states,
state := i.state_abb,
on = "state"
]
# Retain only the highest priority score in each round
prio3 <- prio2[order(priority)
][ ,
data.table::last(.SD),
by = variable
]
# Census-provided data are rounded
expect_equivalent(prio3[ , .(state, round(priority))],
true_pv[ , .(state, priority)])
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