This function plots K functions from different outcomes for comparison. Group means are included as bold lines. Additionally a reference line for a spatially random process can be included.
Arguments
- data
Data.frame with named columns r, K, unit, and outcome. The column r indicates the radius of checked K function, K indicates the K function value, unit specifies the unique K function, and outcome indicates the unit outcome.
- inc.legend
(Optional) Boolean indicating if the legend should be given. This will also include numbers to indicate if any K functions are missing. The default is TRUE.
- inc.noise
(Optional) Boolean indicating if a gray, dashed line should be included to show what spatially random noise would be like. The default is FALSE.
Examples
# Example 1
tmp <- getKFunction(TNBC_pheno[TNBC_pheno$Class == 0, -1],
agents = c("Tumor", "Tumor"),
unit = "Person",
rCheckVals = seq(0, 50, 1)
)
tmp1 <- getKFunction(TNBC_pheno[TNBC_pheno$Class == 1, -1],
agents = c("Tumor", "Tumor"),
unit = "Person",
rCheckVals = seq(0, 50, 1)
)
tmp_1 <- tidyr::pivot_longer(data = tmp, cols = K1:K18)
tmp1_1 <- tidyr::pivot_longer(data = tmp1, cols = K1:K15)
data_plot <- rbind(
data.frame(
"r" = tmp_1$r,
"K" = tmp_1$value,
"unit" = tmp_1$name,
"outcome" = "0"
),
data.frame(
"r" = tmp1_1$r,
"K" = tmp1_1$value,
"unit" = paste0(tmp1_1$name, "_1"),
"outcome" = "1"
)
)
pk1 <- plot_K_functions(data_plot)
# Example 2
tmp <- getKFunction(TNBC_pheno[TNBC_pheno$Class == 0, -1],
agents = c("Tumor", "B"), unit = "Person",
rCheckVals = seq(0, 50, 1)
)
tmp1 <- getKFunction(TNBC_pheno[TNBC_pheno$Class == 1, -1],
agents = c("Tumor", "B"), unit = "Person",
rCheckVals = seq(0, 50, 1)
)
tmp_1 <- tidyr::pivot_longer(data = tmp, cols = K1:K18)
tmp1_1 <- tidyr::pivot_longer(data = tmp1, cols = K1:K15)
data_plot <- rbind(
data.frame(
"r" = tmp_1$r,
"K" = tmp_1$value,
"unit" = tmp_1$name,
"outcome" = "0"
),
data.frame(
"r" = tmp1_1$r,
"K" = tmp1_1$value,
"unit" = paste0(tmp1_1$name, "_1"),
"outcome" = "1"
)
)
pk2 <- plot_K_functions(data_plot)