context("test zip_choropleth")
test_that("state_zoom returns ggplot", {
data(df_pop_zip, package="choroplethrZip")
expect_is(zip_choropleth(df_pop_zip, state_zoom=c("new york")), "ggplot")
})
test_that("setting title returns ggplot", {
data(df_pop_zip, package="choroplethrZip")
expect_is(zip_choropleth(df_pop_zip, state_zoom=c("new york"), title="test title"), "ggplot")
})
test_that("setting legend returns ggplot", {
data(df_pop_zip, package="choroplethrZip")
expect_is(zip_choropleth(df_pop_zip, state_zoom=c("new york"), legend="test legend"), "ggplot")
})
test_that("continuous scale returns ggplot", {
data(df_pop_zip, package="choroplethrZip")
expect_is(zip_choropleth(df_pop_zip, state_zoom=c("new york"), num_colors=1), "ggplot")
})
test_that("county_zoom returns ggplot", {
data(df_pop_zip, package="choroplethrZip")
nyc_fips = c(36005, 36047, 36061, 36081, 36085)
expect_is(zip_choropleth(df_pop_zip,
county_zoom=nyc_fips,
title="2012 New York City Zip Population Estimates",
legend="Population"), "ggplot")
})
test_that("zip_zoom returns ggplot", {
data(df_pop_zip, package="choroplethrZip")
manhattan_les = c("10002", "10003", "10009")
manhattan_ues = c("10021", "10028", "10044", "10128")
zip_choropleth(df_pop_zip,
zip_zoom=c(manhattan_les, manhattan_ues),
title="2012 Lower and Upper East Side Zip Population Estimates",
legend="Population")
})
test_that("msa_zoom returns ggplot", {
data(df_pop_zip, package="choroplethrZip")
expect_is(zip_choropleth(df_pop_zip,
msa_zoom="New York-Newark-Jersey City, NY-NJ-PA",
title="2012 NY-Newark-Jersey City MSA\nZip Population Estimates",
legend="Population"), "ggplot")
})
# this test is important, but I think that it causes travis to fail because it can take a
# few minutes to run
#test_that("full county zoom returns ggplot", {
# data(df_pop_zip, package="choroplethrZip")
# expect_is(zip_choropleth(df_pop_zip,
# title="2012 USA\nZip Population Estimates",
# legend="Population"), "ggplot")
#})
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