/*
This tool is part of the WhiteboxTools geospatial analysis library.
Authors: Dr. John Lindsay
Created: September 18, 2017
Last Modified: 13/10/2018
License: MIT
*/

use whitebox_raster::*;
use crate::tools::*;
use num_cpus;
use std::cmp::Ordering::Equal;
use std::env;
use std::f64;
use std::io::{Error, ErrorKind};
use std::path;
use std::sync::mpsc;
use std::sync::Arc;
use std::thread;

/// This tool calculates the root-mean-square-error (RMSE) or root-mean-square-difference (RMSD) from two
/// input rasters. If the two input rasters possess the same number of rows and columns, the RMSE is
/// calucated on a cell-by-cell basis, otherwise bilinear resampling is used. In addition to RMSE,
/// the tool also reports other common accuracy statistics including the mean verical error, the
/// 95% confidence limit (RMSE x 1.96), and the 90% linear error (LE90), which is the 90% percentile of
/// the residuals between two raster surfaces. The LE90 is the most robust of the reported accuracy
/// statistics when the residuals are non-Gaussian. The LE90 requires sorting the residual values, which
/// can be a relatively slow operation for larger rasters.
///
/// # See Also
/// `PairedSampleTTest`, `WilcoxonSignedRankTest`
pub struct RootMeanSquareError {
    name: String,
    description: String,
    toolbox: String,
    parameters: Vec<ToolParameter>,
    example_usage: String,
}

impl RootMeanSquareError {
    pub fn new() -> RootMeanSquareError {
        // public constructor
        let name = "RootMeanSquareError".to_string();
        let toolbox = "Math and Stats Tools".to_string();
        let description = "Calculates the RMSE and other accuracy statistics.".to_string();

        let mut parameters = vec![];
        parameters.push(ToolParameter {
            name: "Input File".to_owned(),
            flags: vec!["-i".to_owned(), "--input".to_owned()],
            description: "Input raster file.".to_owned(),
            parameter_type: ParameterType::ExistingFile(ParameterFileType::Raster),
            default_value: None,
            optional: false,
        });

        parameters.push(ToolParameter {
            name: "Input Base File".to_owned(),
            flags: vec!["--base".to_owned()],
            description: "Input base raster file used for comparison.".to_owned(),
            parameter_type: ParameterType::ExistingFile(ParameterFileType::Raster),
            default_value: None,
            optional: false,
        });

        let sep: String = path::MAIN_SEPARATOR.to_string();
        let p = format!("{}", env::current_dir().unwrap().display());
        let e = format!("{}", env::current_exe().unwrap().display());
        let mut short_exe = e
            .replace(&p, "")
            .replace(".exe", "")
            .replace(".", "")
            .replace(&sep, "");
        if e.contains(".exe") {
            short_exe += ".exe";
        }
        let usage = format!(
            ">>.*{0} -r={1} -v --wd=\"*path*to*data*\" -i=DEM.tif",
            short_exe, name
        )
        .replace("*", &sep);

        RootMeanSquareError {
            name: name,
            description: description,
            toolbox: toolbox,
            parameters: parameters,
            example_usage: usage,
        }
    }
}

impl WhiteboxTool for RootMeanSquareError {
    fn get_source_file(&self) -> String {
        String::from(file!())
    }

    fn get_tool_name(&self) -> String {
        self.name.clone()
    }

    fn get_tool_description(&self) -> String {
        self.description.clone()
    }

    fn get_tool_parameters(&self) -> String {
        let mut s = String::from("{\"parameters\": [");
        for i in 0..self.parameters.len() {
            if i < self.parameters.len() - 1 {
                s.push_str(&(self.parameters[i].to_string()));
                s.push_str(",");
            } else {
                s.push_str(&(self.parameters[i].to_string()));
            }
        }
        s.push_str("]}");
        s
    }

    fn get_example_usage(&self) -> String {
        self.example_usage.clone()
    }

    fn get_toolbox(&self) -> String {
        self.toolbox.clone()
    }

    fn run<'a>(
        &self,
        args: Vec<String>,
        working_directory: &'a str,
        verbose: bool,
    ) -> Result<(), Error> {
        let mut input_file = String::new();
        let mut base_file = String::new();

        if args.len() == 0 {
            return Err(Error::new(
                ErrorKind::InvalidInput,
                "Tool run with no parameters.",
            ));
        }
        for i in 0..args.len() {
            let mut arg = args[i].replace("\"", "");
            arg = arg.replace("\'", "");
            let cmd = arg.split("="); // in case an equals sign was used
            let vec = cmd.collect::<Vec<&str>>();
            let mut keyval = false;
            if vec.len() > 1 {
                keyval = true;
            }
            if vec[0].to_lowercase() == "-i" || vec[0].to_lowercase() == "--input" {
                if keyval {
                    input_file = vec[1].to_string();
                } else {
                    input_file = args[i + 1].to_string();
                }
            } else if vec[0].to_lowercase() == "-base" || vec[0].to_lowercase() == "--base" {
                if keyval {
                    base_file = vec[1].to_string();
                } else {
                    base_file = args[i + 1].to_string();
                }
            }
        }

        if verbose {
            println!("***************{}", "*".repeat(self.get_tool_name().len()));
            println!("* Welcome to {} *", self.get_tool_name());
            println!("***************{}", "*".repeat(self.get_tool_name().len()));
        }

        let sep: String = path::MAIN_SEPARATOR.to_string();

        let mut progress: usize;
        let mut old_progress: usize = 1;

        if !input_file.contains(&sep) && !input_file.contains("/") {
            input_file = format!("{}{}", working_directory, input_file);
        }
        if !base_file.contains(&sep) && !base_file.contains("/") {
            base_file = format!("{}{}", working_directory, base_file);
        }

        if verbose {
            println!("Reading data...")
        };

        let input = Arc::new(Raster::new(&input_file, "r")?);
        let base_raster = Arc::new(Raster::new(&base_file, "r")?);

        let start = Instant::now();
        let rows = input.configs.rows as isize;
        let columns = input.configs.columns as isize;
        let nodata = input.configs.nodata;
        let nodata_base = base_raster.configs.nodata;

        // let num_valid_cells = input.num_valid_cells();
        // the 90th percentile lies at the bottom of the top 10% highest absolute residual values.
        // let target_num_cells = (0.1 * num_valid_cells as f64) as usize;

        if base_raster.configs.rows as isize == rows
            && base_raster.configs.columns as isize == columns
        {
            // The two grids are the same resolution. This simplifies the calculation greatly.
            let mut num_procs = num_cpus::get() as isize;
            let configs = whitebox_common::configs::get_configs()?;
            let max_procs = configs.max_procs;
            if max_procs > 0 && max_procs < num_procs {
                num_procs = max_procs;
            }
            let (tx, rx) = mpsc::channel();
            for tid in 0..num_procs {
                let input = input.clone();
                let base_raster = base_raster.clone();
                let tx = tx.clone();
                thread::spawn(move || {
                    let mut z1: f64;
                    let mut z2: f64;
                    let mut z_diff: f64;
                    for row in (0..rows).filter(|r| r % num_procs == tid) {
                        let mut n = 0i32;
                        let mut s = 0.0f64;
                        let mut sq = 0.0f64;
                        let mut data: Vec<f32> = Vec::with_capacity(columns as usize);
                        for col in 0..columns {
                            z1 = input[(row, col)];
                            z2 = base_raster[(row, col)];
                            if z1 != nodata && z2 != nodata_base {
                                z_diff = z2 - z1;
                                n += 1;
                                s += z_diff;
                                sq += z_diff * z_diff;
                                data.push(z_diff.abs() as f32);
                            }
                        }
                        tx.send((n, s, sq, data)).unwrap();
                    }
                });
            }

            let mut num_cells = 0i32;
            let mut sum = 0.0;
            let mut sq_sum = 0.0;
            let mut abs_residuals: Vec<f32> = Vec::with_capacity((rows * columns) as usize);
            for row in 0..rows {
                let (a, b, c, d) = rx.recv().expect("Error receiving data from thread.");
                num_cells += a;
                sum += b;
                sq_sum += c;

                for i in 0..d.len() {
                    abs_residuals.push(d[i]);
                }

                if verbose {
                    progress = (100.0_f64 * row as f64 / (rows - 1) as f64) as usize;
                    if progress != old_progress {
                        println!("Progress: {}%", progress);
                        old_progress = progress;
                    }
                }
            }

            let rmse = (sq_sum / num_cells as f64).sqrt();
            let mean_vertical_error = sum / num_cells as f64;
            let ninety_percent_cell = (0.9 * num_cells as f64) as usize;
            if verbose {
                println!("Sorting the residuals...");
            }
            abs_residuals.sort_by(|a, b| a.partial_cmp(b).unwrap_or(Equal));
            let le90 = abs_residuals[ninety_percent_cell];

            println!("\nVertical Accuracy Analysis:\n");
            println!("Comparison File: {}", input_file);
            println!("Base File: {}", base_file);
            println!("Mean vertical error: {:.5}", mean_vertical_error);
            println!("RMSE: {:.5}", rmse);
            println!(
                "Accuracy at 95-percent confidence limit: {:.5}",
                rmse * 1.96f64
            );
            println!("LE90: {:.5}", le90);
        } else {
            /* The two grids are not of the same resolution. Bilinear resampling will have to be
            carried out to estimate z-values. Base image = source; input image = destination */
            let mut num_procs = num_cpus::get() as isize;
            let configs = whitebox_common::configs::get_configs()?;
            let max_procs = configs.max_procs;
            if max_procs > 0 && max_procs < num_procs {
                num_procs = max_procs;
            }
            let (tx, rx) = mpsc::channel();
            for tid in 0..num_procs {
                let input = input.clone();
                let base_raster = base_raster.clone();
                let tx = tx.clone();
                thread::spawn(move || {
                    let mut y: f64;
                    let mut x: f64;
                    let mut z1: f64;
                    let mut z2: f64;
                    let mut z_diff: f64;
                    let mut src_row: f64;
                    let mut src_col: f64;
                    let mut origin_row: isize;
                    let mut origin_col: isize;
                    let mut dx: f64;
                    let mut dy: f64;
                    let src_north = base_raster.configs.north;
                    let src_west = base_raster.configs.west;
                    let src_resolution_x = base_raster.configs.resolution_x;
                    let src_resolution_y = base_raster.configs.resolution_y;
                    let mut n0: f64;
                    let mut n1: f64;
                    let mut n2: f64;
                    let mut n3: f64;

                    for row in (0..rows).filter(|r| r % num_procs == tid) {
                        y = input.get_y_from_row(row);
                        let mut n = 0i32;
                        let mut s = 0.0f64;
                        let mut sq = 0.0f64;
                        let mut data: Vec<f32> = Vec::with_capacity(columns as usize);
                        for col in 0..columns {
                            z1 = input[(row, col)];
                            if z1 != nodata {
                                x = input.get_x_from_column(col);
                                src_row = (src_north - y) / src_resolution_y;
                                src_col = (x - src_west) / src_resolution_x;
                                origin_row = src_row.floor() as isize;
                                origin_col = src_col.floor() as isize;
                                dx = src_col - src_col.floor();
                                dy = src_row - src_row.floor();

                                n0 = base_raster[(origin_row, origin_col)];
                                n1 = base_raster[(origin_row, origin_col + 1)];
                                n2 = base_raster[(origin_row + 1, origin_col)];
                                n3 = base_raster[(origin_row + 1, origin_col + 1)];

                                if n0 != nodata_base
                                    && n1 != nodata_base
                                    && n2 != nodata_base
                                    && n3 != nodata_base
                                {
                                    // This is the bilinear interpolation equation.
                                    z2 = n0 * (1f64 - dx) * (1f64 - dy)
                                        + n1 * dx * (1f64 - dy)
                                        + n2 * (1f64 - dx) * dy
                                        + n3 * dx * dy;
                                } else {
                                    // some of the neighbours are nodata and an inverse-distance scheme is used instead
                                    let w0 = if n0 != nodata_base {
                                        1f64 / (dx * dx + dy * dy)
                                    } else {
                                        0f64
                                    };
                                    let w1 = if n1 != nodata_base {
                                        1f64 / ((1f64 - dx) * (1f64 - dx) + dy * dy)
                                    } else {
                                        0f64
                                    };
                                    let w2 = if n2 != nodata_base {
                                        1f64 / (dx * dx + (1f64 - dy) * (1f64 - dy))
                                    } else {
                                        0f64
                                    };
                                    let w3 = if n3 != nodata_base {
                                        1f64 / ((1f64 - dx) * (1f64 - dx)
                                            + (1f64 - dy) * (1f64 - dy))
                                    } else {
                                        0f64
                                    };
                                    let sum = w0 + w1 + w2 + w3;
                                    if sum > 0f64 {
                                        z2 = (n0 * w0 + n1 * w1 + n2 * w2 + n3 * w3) / sum;
                                    } else {
                                        z2 = nodata_base;
                                    }
                                }

                                if z2 != nodata_base && !z2.is_nan() {
                                    z_diff = z2 - z1;
                                    n += 1;
                                    s += z_diff;
                                    sq += z_diff * z_diff;
                                    data.push(z_diff.abs() as f32);
                                }
                            }
                        }
                        tx.send((n, s, sq, data)).unwrap();
                    }
                });
            }

            let mut num_cells = 0i32;
            let mut sum = 0.0;
            let mut sq_sum = 0.0;
            let mut abs_residuals: Vec<f32> = Vec::with_capacity((rows * columns) as usize);
            for row in 0..rows {
                let (a, b, c, d) = rx.recv().expect("Error receiving data from thread.");
                num_cells += a;
                sum += b;
                sq_sum += c;

                for i in 0..d.len() {
                    abs_residuals.push(d[i]);
                }

                if verbose {
                    progress = (100.0_f64 * row as f64 / (rows - 1) as f64) as usize;
                    if progress != old_progress {
                        println!("Progress: {}%", progress);
                        old_progress = progress;
                    }
                }
            }

            let rmse = (sq_sum / num_cells as f64).sqrt();
            let mean_vertical_error = sum / num_cells as f64;
            let ninety_percent_cell = (0.9 * num_cells as f64) as usize;
            if verbose {
                println!("Sorting the residuals...");
            }
            abs_residuals.sort_by(|a, b| a.partial_cmp(b).unwrap_or(Equal));
            let le90 = abs_residuals[ninety_percent_cell];

            println!("\nVertical Accuracy Analysis:\n");
            println!("Comparison File: {}", input_file);
            println!("Base File: {}", base_file);
            println!("Mean vertical error: {:.5}", mean_vertical_error);
            println!("RMSE: {:.5}", rmse);
            println!(
                "Accuracy at 95-percent confidence limit: {:.5}",
                rmse * 1.96f64
            );
            println!("LE90: {:.5}", le90);
        }

        let elapsed_time = get_formatted_elapsed_time(start);
        if verbose {
            println!(
                "\n{}",
                &format!("Elapsed Time (excluding I/O): {}", elapsed_time)
            );
        }

        Ok(())
    }
}
