//! Cellular automaton - dataset for curriculum learning with increasing complexity.
//! 
//! This dataset is available here:
//! https://huggingface.co/datasets/neoneye/gameoflife-v1
//! 
//! Future experiments:
//! Use different symbols than only . and *.
//! Use different separator characters. Currently no separator is used.
//! Detect of what symbols are being used, so it writes that: dead=., alive=*, separator=none.
//! Do more prediction steps. Currently only 1 or 2 steps are being used.
//! 
//! Game of life: check for oscillators
//! Game of life: recognize shapes.
use super::{CellularAutomaton, cellular_automaton::rule};
use super::{Image, ImageSize, RandomImage, ImageMaskCount, ImageHistogram};
use super::HtmlLog;
use bloomfilter::*;
use rand::rngs::StdRng;
use rand::SeedableRng;
use rand::seq::SliceRandom;
use serde::Serialize;
use std::io::Write;

#[allow(dead_code)]
#[derive(Debug, Clone, Copy, Serialize)]
enum Curriculum {
    // Easy
    StepOneSizeSmall,
    StepOneSizeSmallMedium,
    StepOneSizeSmallMediumBig,

    // Hard
    StepTwoSizeSmall,
    StepOneTwoSizeSmall,
    StepTwoSizeSmallMedium,
    StepOneTwoSizeSmallMedium,
    StepTwoSizeSmallMediumBig,
    StepOneTwoSizeSmallMediumBig,
}

#[allow(dead_code)]
#[derive(Debug, Serialize)]
struct DatasetItem {
    curriculum: Curriculum,
    text: String,
}

#[allow(dead_code)]
#[derive(Debug, Clone, Copy)]
enum Strategy {
    DoNothing,
    ServiettesOneStep,
    ServiettesTwoSteps,
    HighLifeOneStep,
    HighLifeTwoSteps,
}

struct GenerateDataset {
    // bloom is for preventing duplicates
    bloom: Bloom<Image>,
    dataset_items: Vec<DatasetItem>,
}

impl GenerateDataset {
    #[allow(dead_code)]
    fn new() -> Self {
        let bloom_items_count = 100000;
        let false_positive_rate = 0.01;
        Self {
            bloom: Bloom::<Image>::new_for_fp_rate(bloom_items_count, false_positive_rate),
            dataset_items: vec!(),
        }
    }

    #[allow(dead_code)]
    fn populate(&mut self, curriculum: Curriculum, number_of_items: u32, print_to_htmllog: bool) -> anyhow::Result<()> {
        // Prevent too many DatasetItem's with both outputs are all empty
        let max_items_where_both_outputs_all_empty: usize = ((number_of_items as usize) * 5) / 100;

        let step_counts: Vec<u8> = match curriculum {
            Curriculum::StepOneSizeSmall => vec![1],
            Curriculum::StepOneSizeSmallMedium => vec![1],
            Curriculum::StepOneSizeSmallMediumBig => vec![1],
            Curriculum::StepTwoSizeSmall => vec![2],
            Curriculum::StepOneTwoSizeSmall => vec![1, 2],
            Curriculum::StepTwoSizeSmallMedium => vec![2],
            Curriculum::StepOneTwoSizeSmallMedium => vec![1, 2],
            Curriculum::StepTwoSizeSmallMediumBig => vec![2],
            Curriculum::StepOneTwoSizeSmallMediumBig => vec![1, 2],
        };

        let random_seed: u64 = match curriculum {
            Curriculum::StepOneSizeSmall => 0,
            Curriculum::StepOneSizeSmallMedium => 1000000,
            Curriculum::StepOneSizeSmallMediumBig => 2000000,
            Curriculum::StepTwoSizeSmall => 3000000,
            Curriculum::StepOneTwoSizeSmall => 4000000,
            Curriculum::StepTwoSizeSmallMedium => 5000000,
            Curriculum::StepOneTwoSizeSmallMedium => 6000000,
            Curriculum::StepTwoSizeSmallMediumBig => 7000000,
            Curriculum::StepOneTwoSizeSmallMediumBig => 8000000,
        };

        let sizes: Vec<u8> = match curriculum {
            Curriculum::StepOneSizeSmall => vec![3, 4, 5, 6],
            Curriculum::StepOneSizeSmallMedium => vec![3, 4, 5, 6, 7, 8, 9, 10],
            Curriculum::StepOneSizeSmallMediumBig => vec![3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14],
            Curriculum::StepTwoSizeSmall => vec![3, 4, 5, 6],
            Curriculum::StepOneTwoSizeSmall => vec![3, 4, 5, 6],
            Curriculum::StepTwoSizeSmallMedium => vec![3, 4, 5, 6, 7, 8, 9, 10],
            Curriculum::StepOneTwoSizeSmallMedium => vec![3, 4, 5, 6, 7, 8, 9, 10],
            Curriculum::StepTwoSizeSmallMediumBig => vec![3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14],
            Curriculum::StepOneTwoSizeSmallMediumBig => vec![3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14],
        };

        let temperatures: [u8; 9] = [
            10, 20, 30, 40, 50, 60, 70, 80, 90
        ];
        let strategies: [Strategy; 5] = [
            Strategy::DoNothing,
            Strategy::ServiettesOneStep,
            Strategy::ServiettesTwoSteps,
            Strategy::HighLifeOneStep,
            Strategy::HighLifeTwoSteps,
        ];

        let mut count_input_all_empty: usize = 0;
        let mut count_input_all_alive: usize = 0;
        let mut count_input_one_cell_empty: usize = 0;
        let mut count_input_one_cell_alive: usize = 0;
        let mut count_both_outputs_all_empty: usize = 0;

        let upper_bound: u64 = (number_of_items * 4) as u64;
        let mut number_of_items_created: u32 = 0;
        for i in 0..upper_bound {
            if number_of_items_created >= number_of_items {
                break;
            }
            let mut rng = StdRng::seed_from_u64(random_seed + i);
            let step_count: u8 = *step_counts.choose(&mut rng).unwrap();
            let width: u8 = *sizes.choose(&mut rng).unwrap();
            let height: u8 = *sizes.choose(&mut rng).unwrap();
            let temperature: u8 = *temperatures.choose(&mut rng).unwrap();
            let strategy: Strategy = *strategies.choose(&mut rng).unwrap();

            let size = ImageSize::new(width, height);
            let mut input: Image = RandomImage::two_colors(&mut rng, size, 0, 1, temperature)?;

            // Mutate the input image, to get different distributions
            match strategy {
                Strategy::DoNothing => {},
                Strategy::HighLifeOneStep => {
                    let mut ca: CellularAutomaton<_> = CellularAutomaton::<rule::HighLife>::with_image(&input, None);
                    ca.step(1);
                    input = ca.image().clone();
                },
                Strategy::HighLifeTwoSteps => {
                    let mut ca: CellularAutomaton<_> = CellularAutomaton::<rule::HighLife>::with_image(&input, None);
                    ca.step(2);
                    input = ca.image().clone();
                },
                Strategy::ServiettesOneStep => {
                    let mut ca: CellularAutomaton<_> = CellularAutomaton::<rule::Serviettes>::with_image(&input, None);
                    ca.step(1);
                    input = ca.image().clone();
                },
                Strategy::ServiettesTwoSteps => {
                    let mut ca: CellularAutomaton<_> = CellularAutomaton::<rule::Serviettes>::with_image(&input, None);
                    ca.step(2);
                    input = ca.image().clone();
                },
            }

            let (input_count0, input_count1, _count_other) = input.mask_count();
            let is_input_all_empty: bool = input_count1 == 0;
            let is_input_all_alive: bool = input_count0 == 0;
            let is_input_one_cell_empty: bool = input_count0 == 1;
            let is_input_one_cell_alive: bool = input_count1 == 1;

            if is_input_all_empty {
                count_input_all_empty += 1;
                if count_input_all_empty > 3 {
                    debug!("ignoring input with all empty");
                    continue;
                }
            }
            if is_input_all_alive {
                count_input_all_alive += 1;
                if count_input_all_alive > 3 {
                    debug!("ignoring input with all alive");
                    continue;
                }
            }
            if is_input_one_cell_empty {
                count_input_one_cell_empty += 1;
                if count_input_one_cell_empty > 3 {
                    debug!("ignoring input with one cell empty");
                    continue;
                }
            }
            if is_input_one_cell_alive {
                count_input_one_cell_alive += 1;
                if count_input_one_cell_alive > 3 {
                    debug!("ignoring input with one cell alive");
                    continue;
                }
            }
            
            if self.bloom.check(&input) {
                debug!("skipping duplicate");
                continue;
            }
            self.bloom.set(&input);
            
            let mut ca_nowrap: CellularAutomaton<_> = CellularAutomaton::<rule::GameOfLife>::with_image(&input, Some(0));
            ca_nowrap.step(step_count);
            let output_without_wrap: Image = ca_nowrap.image().clone();

            let mut ca_wrap: CellularAutomaton<_> = CellularAutomaton::<rule::GameOfLife>::with_image(&input, None);
            ca_wrap.step(step_count);
            let output_with_wrap: Image = ca_wrap.image().clone();

            let same_output_for_wrap_and_nowrap: bool = output_without_wrap == output_with_wrap;

            if same_output_for_wrap_and_nowrap {
                if output_without_wrap.mask_count_nonzero() == 0 {
                    count_both_outputs_all_empty += 1;
                    if count_both_outputs_all_empty > max_items_where_both_outputs_all_empty {
                        debug!("ignoring dataset item where both outputs are all empty");
                        continue;
                    }
                }
            }

            let mut markdown = String::new();
            markdown.push_str("# Conway's Game of Life\n\n");
            if step_count == 1 {
                markdown.push_str("Perform 1 step.\n\n");
            } else {
                markdown.push_str(&format!("Perform {} steps.\n\n", step_count));
            }
            markdown.push_str("## Input\n\n");
            markdown.push_str(&Self::image_to_markdown_fenced_code_block(&input));
            markdown.push_str("\n\n");
            Self::caption_for_input_output_image(&mut markdown, &input);
            markdown.push_str("\n");
            markdown.push_str("## Output without wrap\n\n");
            markdown.push_str(&Self::image_to_markdown_fenced_code_block(&output_without_wrap));
            markdown.push_str("\n\n");
            Self::caption_for_input_output_image(&mut markdown, &output_without_wrap);
            Self::caption_for_output_compared_to_input(&mut markdown, &output_without_wrap, &input, step_count);
            markdown.push_str("\n");
            markdown.push_str("## Output with wrap\n\n");
            markdown.push_str(&Self::image_to_markdown_fenced_code_block(&output_with_wrap));
            markdown.push_str("\n\n");
            Self::caption_for_input_output_image(&mut markdown, &output_with_wrap);
            Self::caption_for_output_compared_to_input(&mut markdown, &output_with_wrap, &input, step_count);
            markdown.push_str("\n");
            markdown.push_str("## Status\n\n");
            if same_output_for_wrap_and_nowrap {
                markdown.push_str("The outputs are identical.");
            } else {
                markdown.push_str("The outputs are different.");
            }

            if print_to_htmllog {
                let compare_images: Vec<Image> = vec![
                    input.clone(),
                    output_without_wrap.clone(),
                    output_with_wrap.clone(),
                ];
                // if same_output_for_wrap_and_nowrap {
                //     HtmlLog::text("wrap is identical to nowrap");
                // } else {
                //     HtmlLog::text("wrap is different than nowrap");
                // }
                HtmlLog::text(markdown.clone());
                HtmlLog::compare_images(compare_images);
            }

            let dataset_item = DatasetItem {
                curriculum,
                text: markdown,
            };
            self.dataset_items.push(dataset_item);
            number_of_items_created += 1;
        }

        debug!("count_both_outputs_all_empty: {}", count_both_outputs_all_empty);

        Ok(())
    }

    fn caption_for_input_output_image(markdown: &mut String, image: &Image) {
        let (count_empty, count_alive, _count_other) = image.mask_count();
        if count_alive == 0 {
            markdown.push_str("All cells are empty.\n");
        }
        if count_empty == 0 {
            markdown.push_str("All cells are alive.\n");
        }
        if count_alive == 1 {
            markdown.push_str("Only one cell is alive.\n");
        }
        if count_empty == 1 {
            markdown.push_str("Only one cell is empty.\n");
        }

        if count_alive > 0 && count_empty > 0 {
            if image.is_repeated_row().unwrap_or(false) {
                markdown.push_str("The rows are identical.\n");
            }
            if image.is_repeated_column().unwrap_or(false) {
                markdown.push_str("The columns are identical.\n");
            }
        }
    }

    fn caption_for_output_compared_to_input(markdown: &mut String, output: &Image, input: &Image, step_count: u8) {
        if output == input {
            markdown.push_str("This output is identical to the input.\n");
            let (count0, count1, _count_other) = input.mask_count();
            if count0 > 0 && count1 > 0 && step_count == 1 {
                markdown.push_str("Still life.\n");
            }
        } else {
            markdown.push_str("This output is different than the input.\n");
        }
    }

    fn image_to_markdown_fenced_code_block(image: &Image) -> String {
        format!("```\n{}\n```", GenerateDataset::image_to_string(image))
    }

    fn image_to_string(image: &Image) -> String {
        let mut result = String::new();
        for y in 0..image.height() {
            if y > 0 {
                result.push('\n');
            }
            for x in 0..image.width() {
                let value: u8 = image.get(x as i32, y as i32).unwrap_or(0);
                let character: char = match value {
                    0 => '.',
                    1 => '*',
                    _ => '?',
                };
                result.push(character);
            }
        }
        result
    }

    fn dataset_to_jsonl(dataset_items: &Vec<DatasetItem>) -> anyhow::Result<String> {
        let mut jsonl_rows = Vec::<String>::new();
        for dataset_item in dataset_items {
            let jsonl_row: String = serde_json::to_string(dataset_item)?;
            jsonl_rows.push(jsonl_row);
        }
        let jsonl_data: String = jsonl_rows.join("\n");
        Ok(jsonl_data)
    }

    #[allow(dead_code)]
    fn shuffle(&mut self) {
        let mut rng = StdRng::seed_from_u64(0);
        self.dataset_items.shuffle(&mut rng);
    }

    #[allow(dead_code)]
    fn save(&self, path: &std::path::Path) -> anyhow::Result<()> {
        let s: String = Self::dataset_to_jsonl(&self.dataset_items)?;
        println!("dataset number of rows: {}", self.dataset_items.len());
        println!("dataset jsonl bytes: {}", s.len());

        let mut file = std::fs::File::create(path)?;
        file.write_all(s.as_bytes())?;
        Ok(())
    }
}

#[cfg(test)]
mod tests {
    use super::*;
    use crate::arc::ImageTryCreate;
    use std::path::PathBuf;

    #[test]
    fn test_10000_image_to_string() {
        // Arrange
        let pixels: Vec<u8> = vec![
            1, 0, 0,
            0, 1, 1,
            1, 1, 255,
        ];
        let input: Image = Image::try_create(3, 3, pixels).expect("image");

        // Act
        let actual: String = GenerateDataset::image_to_string(&input);
        
        // Assert
        assert_eq!(actual, "*..\n.**\n**?");
    }

    #[allow(dead_code)]
    // #[test]
    fn test_20000_generate_and_save() {
        let path: PathBuf = PathBuf::from("/Users/neoneye/Downloads/gameoflife.jsonl");
        let mut generator = GenerateDataset::new();
        let number_of_items: u32 = 4700;
        generator.populate(Curriculum::StepOneSizeSmall, number_of_items, false).expect("ok");
        generator.populate(Curriculum::StepOneSizeSmallMedium, number_of_items, false).expect("ok");
        generator.populate(Curriculum::StepOneSizeSmallMediumBig, number_of_items, false).expect("ok");
        generator.populate(Curriculum::StepTwoSizeSmall, number_of_items, false).expect("ok");
        generator.populate(Curriculum::StepOneTwoSizeSmall, number_of_items, false).expect("ok");
        generator.populate(Curriculum::StepTwoSizeSmallMedium, number_of_items, false).expect("ok");
        generator.populate(Curriculum::StepOneTwoSizeSmallMedium, number_of_items, false).expect("ok");
        generator.populate(Curriculum::StepTwoSizeSmallMediumBig, number_of_items, false).expect("ok");
        generator.populate(Curriculum::StepOneTwoSizeSmallMediumBig, number_of_items, false).expect("ok");
        generator.shuffle();
        generator.save(&path).expect("ok");
    }

    #[allow(dead_code)]
    // #[test]
    fn test_20001_do_something() {
        for i in 0..20u64 {
            let size = ImageSize::new(10, 8);
            let step0: Image = RandomImage::two_colors(&mut StdRng::seed_from_u64(i), size, 0, 1, 35).expect("ok");
            let step1: Image = RandomImage::draw_dots(&mut StdRng::seed_from_u64(i+5), &step0, 2, 5).expect("ok");
            let step2: Image = RandomImage::draw_dots(&mut StdRng::seed_from_u64(i+8), &step1, 3, 5).expect("ok");
            let mut images = Vec::<Image>::new();
            images.push(step2.clone());
            let mut ca: CellularAutomaton<_> = CellularAutomaton::<rule::GameOfLifeExtra>::with_image(&step0, None);
            for _ in 0..4 {
                ca.step_once();
                images.push(ca.image().clone());
            }
            HtmlLog::compare_images(images);
        }
    }
}