use crate::image_loader::Image; use crate::palette16::Palette16OptimisationResults; use crate::TileSize; use proc_macro2::TokenStream; use quote::{format_ident, quote}; use std::iter; pub(crate) fn generate_code( output_variable_name: &str, results: &Palette16OptimisationResults, image: &Image, image_filename: &str, tile_size: TileSize, crate_prefix: String, ) -> TokenStream { let crate_prefix = format_ident!("{}", crate_prefix); let output_variable_name = format_ident!("{}", output_variable_name); let palette_data = results.optimised_palettes.iter().map(|palette| { let colours = palette .clone() .into_iter() .map(|colour| colour.to_rgb15()) .chain(iter::repeat(0)) .take(16) .map(|colour| colour as u16); quote! { #crate_prefix::display::palette16::Palette16::new([ #(#colours),* ]) } }); let tile_size = tile_size.to_size(); let tiles_x = image.width / tile_size; let tiles_y = image.height / tile_size; let mut tile_data = vec![]; for y in 0..tiles_y { for x in 0..tiles_x { let palette_index = results.assignments[y * tiles_x + x]; let palette = &results.optimised_palettes[palette_index]; for inner_y in 0..tile_size / 8 { for inner_x in 0..tile_size / 8 { for j in inner_y * 8..inner_y * 8 + 8 { for i in (inner_x * 8..inner_x * 8 + 8).rev() { let colour = image.colour(x * tile_size + i, y * tile_size + j); tile_data.push(palette.colour_index(colour)); } } } } } } let tile_data = tile_data.chunks(8) .map(|chunk| chunk.iter().fold(0u32, |acc, &x| (acc << 4) | (x as u32))); let assignments = results.assignments.iter().map(|&x| x as u8); quote! { #[allow(non_upper_case_globals)] pub const #output_variable_name: #crate_prefix::display::tile_data::TileData = { const _: &[u8] = include_bytes!(#image_filename); const PALETTE_DATA: &[#crate_prefix::display::palette16::Palette16] = &[ #(#palette_data),* ]; const TILE_DATA: &[u32] = &[ #(#tile_data),* ]; const PALETTE_ASSIGNMENT: &[u8] = &[ #(#assignments),* ]; #crate_prefix::display::tile_data::TileData::new(PALETTE_DATA, TILE_DATA, PALETTE_ASSIGNMENT) }; } }