## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.width  = 5,
  fig.height = 5
)

## ----setup--------------------------------------------------------------------
library(gghinton)
library(ggplot2)

## ----quick-start--------------------------------------------------------------
# A 10x10 signed matrix
set.seed(99)
m <- matrix(rnorm(100), nrow = 10)
rownames(m) <- paste0("r", 1:10)
colnames(m) <- paste0("c", 1:10)

df <- matrix_to_hinton(m)

ggplot(df, aes(x = col, y = row, weight = weight)) +
  geom_hinton() +
  scale_fill_hinton() +
  coord_fixed() +
  theme_hinton() +
  labs(title = "A signed Hinton diagram")

## ----unsigned-----------------------------------------------------------------
m_pos <- abs(m)
df_pos <- matrix_to_hinton(m_pos)

ggplot(df_pos, aes(x = col, y = row, weight = weight)) +
  geom_hinton() +
  scale_fill_hinton() +
  coord_fixed() +
  theme_hinton() +
  labs(title = "An unsigned Hinton diagram")

## ----as-hinton-df-------------------------------------------------------------
# matrix
as_hinton_df(matrix(c(1, -2, 3, -4), 2, 2))

# base R table
t2 <- table(
  group   = c("A", "A", "B", "B"),
  outcome = c("yes", "no", "yes", "no")
)
as_hinton_df(t2)

## ----as-hinton-df-df----------------------------------------------------------
tidy <- data.frame(row = c(1, 1, 2, 2), col = c(1, 2, 1, 2),
                   weight = c(0.5, -0.3, 0.8, -0.1))
as_hinton_df(tidy)

## ----scale-by, fig.width = 8, fig.height = 4----------------------------------
set.seed(1)
df_a <- cbind(matrix_to_hinton(matrix(runif(9, -1,  1), 3, 3)),
              panel = "A (range +/-1)")
df_b <- cbind(matrix_to_hinton(matrix(runif(9, -5,  5), 3, 3)),
              panel = "B (range +/-5)")
df_ab <- rbind(df_a, df_b)

# Per-panel scaling: each panel's largest value fills its cell
ggplot(df_ab, aes(x = col, y = row, weight = weight)) +
  geom_hinton(scale_by = "panel") +
  scale_fill_hinton() +
  coord_fixed() +
  theme_hinton() +
  facet_wrap(~panel) +
  labs(title = 'scale_by = "panel" (default)')

# Global scaling: panel A appears much smaller
ggplot(df_ab, aes(x = col, y = row, weight = weight)) +
  geom_hinton(scale_by = "global") +
  scale_fill_hinton() +
  coord_fixed() +
  theme_hinton() +
  facet_wrap(~panel) +
  labs(title = 'scale_by = "global"')

## ----custom-colours-----------------------------------------------------------
df <- matrix_to_hinton(m)

ggplot(df, aes(x = col, y = row, weight = weight)) +
  geom_hinton(background = FALSE) +
  scale_fill_hinton(values = c(positive = "darkblue", negative = "darkred")) +
  coord_fixed() +
  theme_hinton() +
  labs(title = "Custom colours")

## ----axis-labels--------------------------------------------------------------
# m has rownames/colnames set above
df_named <- matrix_to_hinton(m)

ggplot(df_named, aes(x = col, y = row, weight = weight)) +
  geom_hinton() +
  scale_fill_hinton() +
  scale_x_continuous(
    breaks = seq_len(ncol(m)),
    labels = colnames(m)
  ) +
  scale_y_continuous(
    breaks = seq_len(nrow(m)),
    labels = rev(rownames(m))  # reversed because row 1 is at the top
  ) +
  coord_fixed() +
  theme_hinton() +
  labs(title = "Named axes")

## ----no-bg--------------------------------------------------------------------
ggplot(df, aes(x = col, y = row, weight = weight)) +
  geom_hinton(background = FALSE) +
  scale_fill_hinton(values = c(positive = "grey70")) +
  coord_fixed() +
  theme_hinton() +
  labs(title = "Signed data without background")

## ----mtcars-cor, fig.width = 6, fig.height = 6--------------------------------
df_cor <- as_hinton_df(cor(mtcars))
vars <- colnames(mtcars)

ggplot(df_cor, aes(x = col, y = row, weight = weight)) +
  geom_hinton() +
  scale_fill_hinton() +
  scale_x_continuous(breaks = seq_along(vars), labels = vars) +
  scale_y_continuous(breaks = seq_along(vars), labels = rev(vars)) +
  coord_fixed() +
  theme_hinton() +
  theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
  labs(title = "cor(mtcars)",
       subtitle = "White = positive, black = negative correlation")

