## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.width = 7,
  fig.height = 5,
  dpi = 96
)
library(prakriti)
library(ggplot2)

theme_prak <- function(base_size = 12) {
  theme_minimal(base_size = base_size) +
    theme(
      plot.title       = element_text(face = "bold", size = rel(1.2)),
      plot.subtitle    = element_text(color = "grey30", margin = margin(b = 8)),
      panel.grid.minor = element_blank(),
      panel.grid.major = element_line(color = "grey92"),
      plot.margin      = margin(12, 12, 12, 12)
    )
}

## ----scatter------------------------------------------------------------------
ggplot(iris, aes(Sepal.Length, Petal.Length,
                 color = Species, shape = Species)) +
  geom_point(size = 3.5, alpha = 0.85) +
  scale_color_prakriti("valley_of_flowers") +
  labs(
    title = "Iris petal vs sepal length",
    subtitle = "valley_of_flowers palette",
    x = "Sepal length (cm)", y = "Petal length (cm)"
  ) +
  theme_prak()

## ----area, fig.height = 4.5---------------------------------------------------
set.seed(42)
months <- rep(month.abb, each = 5)
species <- rep(c("Strobilanthes", "Smithia", "Impatiens",
                 "Senecio", "Eriocaulon"), 12)
area_df <- data.frame(
  month   = factor(months, levels = month.abb),
  species = species,
  cover   = pmax(0, rnorm(60, 40, 20) +
                    rep(c(0, 10, 25, 35, 50, 60, 55, 40, 20, 10, 5, 0),
                        each = 5))
)

ggplot(area_df, aes(month, cover, fill = species, group = species)) +
  geom_area(alpha = 0.88, color = "white", linewidth = 0.3) +
  scale_fill_prakriti("kaas") +
  labs(
    title = "Seasonal wildflower ground cover on Kaas Plateau",
    subtitle = "kaas palette",
    x = NULL, y = "Cover (%)", fill = "Species"
  ) +
  theme_prak()

## ----bar, fig.height = 4.5----------------------------------------------------
set.seed(7)
bio_df <- data.frame(
  region   = rep(c("Nilgiris", "Coorg", "Agumbe", "Wayanad"), each = 5),
  taxon    = rep(c("Birds", "Butterflies", "Reptiles",
                   "Amphibians", "Mammals"), 4),
  richness = sample(30:180, 20, replace = TRUE)
)
bio_df$region <- factor(bio_df$region,
                        levels = c("Nilgiris", "Coorg", "Agumbe", "Wayanad"))

ggplot(bio_df, aes(region, richness, fill = taxon)) +
  geom_col(position = position_dodge(width = 0.8), width = 0.7) +
  scale_fill_prakriti("western_ghats") +
  labs(
    title = "Species richness across Western Ghats sub-regions",
    subtitle = "western_ghats palette",
    x = NULL, y = "Number of species", fill = NULL
  ) +
  theme_prak() +
  theme(legend.position = "top")

## ----donut--------------------------------------------------------------------
pie_df <- data.frame(
  habitat = c("Coral reef", "Mangrove", "Seagrass",
              "Sandy beach", "Rainforest", "Open ocean"),
  pct     = c(28, 18, 12, 10, 22, 10)
)
pie_df$ymax <- cumsum(pie_df$pct)
pie_df$ymin <- c(0, head(pie_df$ymax, -1))
pie_df$mid  <- (pie_df$ymin + pie_df$ymax) / 2
pie_df$label <- paste0(pie_df$habitat, "\n", pie_df$pct, "%")

ggplot(pie_df, aes(ymax = ymax, ymin = ymin, xmax = 4, xmin = 2.2,
                   fill = habitat)) +
  geom_rect(color = "white", linewidth = 0.8) +
  geom_text(aes(x = 3.1, y = mid, label = label),
            size = 3.2, color = "grey15") +
  scale_fill_prakriti("andaman") +
  coord_polar(theta = "y") +
  xlim(c(0.5, 4.5)) +
  labs(
    title = "Andaman Islands habitat composition",
    subtitle = "andaman palette"
  ) +
  theme_void(base_size = 12) +
  theme(
    plot.title    = element_text(face = "bold", hjust = 0.5),
    plot.subtitle = element_text(hjust = 0.5, color = "grey35"),
    legend.position = "none",
    plot.margin = margin(10, 10, 10, 10)
  )

## ----violin, fig.height = 4---------------------------------------------------
set.seed(123)
ridge_df <- do.call(rbind, lapply(1:6, function(m) {
  n <- 400
  base_mu <- c(120, 200, 350, 280, 160, 90)[m]
  data.frame(
    month = factor(month.abb[m], levels = rev(month.abb[1:6])),
    flock = pmax(0, rnorm(n, base_mu, base_mu * 0.3))
  )
}))

cols_chilika <- prakriti_palette("chilika")

ggplot(ridge_df, aes(flock, month, fill = month, color = month)) +
  geom_violin(scale = "width", width = 0.85, alpha = 0.8,
              trim = TRUE, linewidth = 0.3) +
  scale_fill_manual(values = cols_chilika) +
  scale_color_manual(values = cols_chilika) +
  labs(
    title = "Flamingo flock size distribution - Chilika Lake",
    subtitle = "chilika palette",
    x = "Flock size", y = NULL
  ) +
  theme_prak() +
  theme(legend.position = "none",
        panel.grid.major.y = element_blank())

## ----proportion, fig.height = 2.5---------------------------------------------
crops <- data.frame(
  crop = c("Coffee", "Pepper", "Cardamom", "Rice", "Oranges", "Timber"),
  area = c(38, 22, 12, 15, 8, 5)
)
crops$xmax <- cumsum(crops$area)
crops$xmin <- c(0, head(crops$xmax, -1))
crops$mid  <- (crops$xmin + crops$xmax) / 2

ggplot(crops, aes(xmin = xmin, xmax = xmax, ymin = 0, ymax = 1,
                  fill = crop)) +
  geom_rect(color = "white", linewidth = 0.6) +
  geom_text(aes(x = mid, y = 0.5,
                label = paste0(crop, "\n", area, "%")),
            color = "white", fontface = "bold", size = 3.5) +
  scale_fill_prakriti("coorg") +
  coord_cartesian(expand = FALSE) +
  labs(
    title = "Coorg district crop composition",
    subtitle = "coorg palette"
  ) +
  theme_void(base_size = 12) +
  theme(
    plot.title    = element_text(face = "bold"),
    plot.subtitle = element_text(color = "grey30"),
    legend.position = "none",
    plot.margin = margin(12, 12, 12, 12)
  )

## ----tile, fig.height = 4-----------------------------------------------------
set.seed(77)
kutch_df <- data.frame(
  x     = rep(1:14, 10),
  y     = rep(1:10, each = 14),
  motif = sample(c("Mirror", "Indigo block", "Turmeric dye",
                    "Madder red", "Teal thread", "Orange applique",
                    "Purple resist"), 140, replace = TRUE)
)

ggplot(kutch_df, aes(x, y, fill = motif)) +
  geom_tile(color = "grey90", linewidth = 0.3) +
  scale_fill_prakriti("kutch_textile") +
  coord_equal(expand = FALSE) +
  labs(
    title = "Kutch textile motif sampler",
    subtitle = "kutch_textile palette",
    fill = "Motif"
  ) +
  theme_void(base_size = 11) +
  theme(
    plot.title    = element_text(face = "bold"),
    plot.subtitle = element_text(color = "grey30"),
    plot.margin   = margin(12, 12, 12, 12)
  )

## ----jitter-------------------------------------------------------------------
ggplot(mpg, aes(displ, hwy, color = class)) +
  geom_jitter(size = 2.8, alpha = 0.8, width = 0.15) +
  scale_color_prakriti("ladakh_monastery") +
  labs(
    title = "Engine displacement vs highway MPG by vehicle class",
    subtitle = "ladakh_monastery palette",
    x = "Displacement (L)", y = "Highway MPG", color = "Class"
  ) +
  theme_prak()

## ----darkmode, fig.height = 5-------------------------------------------------
set.seed(23)
bio_pts <- data.frame(
  x = c(rnorm(300, 3, 1.2), rnorm(200, 7, 0.8)),
  y = c(rnorm(300, 4, 1.5), rnorm(200, 6, 1.0))
)
bio_pts$intensity <- with(bio_pts,
  dnorm(x, 3, 1.2) * dnorm(y, 4, 1.5) +
  dnorm(x, 7, 0.8) * dnorm(y, 6, 1.0)
)

ggplot(bio_pts, aes(x, y, color = intensity)) +
  geom_point(size = 1.8, alpha = 0.85) +
  scale_color_prakriti("nocturn", discrete = FALSE) +
  labs(
    title = "Bioluminescent point field",
    subtitle = "nocturn palette on dark background",
    x = NULL, y = NULL
  ) +
  theme_minimal(base_size = 12) +
  theme(
    plot.background  = element_rect(fill = "#020A18", color = NA),
    panel.background = element_rect(fill = "#020A18", color = NA),
    panel.grid       = element_blank(),
    text             = element_text(color = "grey80"),
    plot.title       = element_text(face = "bold", color = "white"),
    plot.subtitle    = element_text(color = "grey50"),
    axis.text        = element_text(color = "grey50"),
    legend.position  = "none"
  )

## ----bin2d--------------------------------------------------------------------
set.seed(42)
ggplot(diamonds[sample(nrow(diamonds), 5000), ],
       aes(carat, price)) +
  geom_bin2d(bins = 40) +
  scale_fill_prakriti("munnar", discrete = FALSE) +
  labs(
    title = "Diamond carat vs price density",
    subtitle = "munnar palette",
    x = "Carat", y = "Price (USD)", fill = "Count"
  ) +
  theme_prak()

