import fs from 'node:fs'
import typed from 'typed-function'
import { create, all } from '../lib/esm/index.js'

const { Spa, DenseMatrix, SparseMatrix, FibonacciHeap } = create(all)

const _importFromStream = function (stream) {
  return new Promise(function (resolve, reject) {
    // header regex
    const headerRegex = /%%MatrixMarket ([a-zA-Z]+) ([a-zA-Z]+) ([a-zA-Z]+) ([a-zA-Z]+)/
    const coordinateHeaderRegex = /(\d+) (\d+) (\d+)/
    const coordinateDataRegex = /(\d+) (\d+) (.*)/
    const coordinatePatternRegex = /(\d+) (\d+)/
    const arrayHeaderRegex = /(\d+) (\d+)/
    const arrayDataRegex = /(\d+)/

    // Matrix Market supported formats
    const typecodes = ['matrix']
    const formats = ['coordinate', 'array']
    const datatypes = ['real', 'pattern']
    const qualifiers = ['general', 'symmetric']

    // matrix data
    let mm = null
    let buffer = ''

    const readHeader = function (line) {
      // check line is a header
      const matches = line.match(headerRegex)
      if (matches !== null) {
        // get matches values
        const typecode = matches[1]
        const format = matches[2]
        const datatype = matches[3]
        const qualifier = matches[4]
        // check typecode
        if (!typecodes.includes(typecode)) {
          // typecode not supported
          reject(new Error('Matrix Market type code is not supported: ' + typecode))
          // close stream
          stream.close()
        }
        // check format
        if (!formats.includes(format)) {
          // typecode not supported
          reject(new Error('Matrix Market format is not supported: ' + format))
          // close stream
          stream.close()
        }
        // check datatype
        if (!datatypes.includes(datatype)) {
          // typecode not supported
          reject(new Error('Matrix Market datatype is not supported: ' + datatype))
          // close stream
          stream.close()
        }
        if (!qualifiers.includes(qualifier)) {
          // typecode not supported
          reject(new Error('Matrix Market qualifier is not supported: ' + qualifier))
          // close stream
          stream.close()
        }

        // initialize matrix market structure
        mm = {
          typecode: typecode,
          format: format,
          datatype: datatype,
          qualifier: qualifier,
          data: null
        }
      } else {
        // invalid header
        reject(new Error('Invalid file header: ' + line))
        // close stream
        stream.close()
      }
    }

    const readStructure = function (line) {
      // vars
      let matches
      // check matrix format
      switch (mm.format) {
        case 'coordinate':
          // rows columns entries
          matches = line.match(coordinateHeaderRegex)
          if (matches !== null) {
            // read structure
            mm.rows = parseInt(matches[1])
            mm.columns = parseInt(matches[2])
            mm.entries = parseInt(matches[3])
            // initialize data
            mm.data = new FibonacciHeap()
          }
          break
        case 'array':
          matches = line.match(arrayHeaderRegex)
          if (matches !== null) {
            // read structure
            mm.rows = parseInt(matches[1])
            mm.columns = parseInt(matches[2])
            // initialize data
            mm.data = []
          }
          break
      }
    }

    const readValue = function (text) {
      // check datatype
      switch (mm.datatype) {
        case 'real':
          return parseFloat(text)
        case 'pattern':
          return 1
      }
    }

    const readData = function (line) {
      // vars
      let matches
      // check matrix format
      switch (mm.format) {
        case 'coordinate':
          {
            // regex to use
            const rx = mm.datatype !== 'pattern' ? coordinateDataRegex : coordinatePatternRegex
            // check data line is correct
            matches = line.match(rx)
            if (matches !== null) {
              // row, columns, value
              const r = parseInt(matches[1]) - 1
              const c = parseInt(matches[2]) - 1
              const v = readValue(matches.length === 4 ? matches[3] : null)
              // insert entry
              mm.data.insert(c, { i: r, j: c, v: v })
              // check matrix is simmetric
              if (mm.qualifier === 'symmetric' && c !== r) {
                // insert entry
                mm.data.insert(r, { i: c, j: r, v: v })
              }
            }
          }
          break
        case 'array':
          // check data line is correct
          matches = line.match(arrayDataRegex)
          if (matches !== null) {
            // get values in row
            const values = []
            for (let j = 1; j < matches.length; j++) { values.push(readValue(matches[j])) }
            // push entry
            mm.data.push(values)
          }
          break
      }
    }

    const processLine = function (line) {
      // check this is the first line
      if (mm !== null) {
        // skip all comments
        if (line.charAt(0) !== '%') {
          // check data is ready to be processed
          if (mm.data !== null) {
            // it is a data row
            readData(line)
          } else {
            // read matrix structure
            readStructure(line)
          }
        }
      } else {
        // read header, initialize data
        readHeader(line)
      }
    }

    stream.on('data', function (chunk) {
      // concatenate chunk
      buffer += chunk
      // eol
      let index = buffer.indexOf('\n')
      // process lines
      while (index !== -1) {
        // extract line
        const line = buffer.substr(0, index)
        // process line
        processLine(line.trim())
        // update buffer
        buffer = buffer.length > index ? buffer.substr(index + 1) : ''
        // next line
        index = buffer.indexOf('\n')
      }
    })

    stream.on('end', function () {
      // check mm
      if (mm !== null) {
        // process matrix format
        switch (mm.format) {
          case 'coordinate':
            {
              // CCS structure
              const values = mm.datatype !== 'pattern' ? [] : undefined
              const index = []
              const ptr = []
              const datatype = mm.datatype === 'real' ? 'number' : undefined
              // mm data & pointer
              const d = mm.data
              let p = -1
              let spa = new Spa(mm.rows)
              // push value
              const pushValue = function (i, v) {
                // push row
                index.push(i)
                // check there is a value (pattern matrix)
                if (values) { values.push(v) }
              }
              // extract node (column sorted)
              let n = d.extractMinimum()
              // loop all nodes
              while (n !== null) {
                // check column changed
                if (p !== n.key) {
                  // process sparse accumulator
                  spa.forEach(0, mm.rows, pushValue)
                  // process columns from p + 1 to n.j
                  for (let j = p + 1; j <= n.key; j++) {
                    // ptr update
                    ptr.push(index.length)
                  }
                  // create sparse accumulator
                  spa = new Spa(mm.rows)
                  // reset p
                  p = n.key
                }
                // store value in spa
                spa.set(n.value.i, n.value.v)
                // extract node
                n = d.extractMinimum()
              }
              // process sparse accumulator
              spa.forEach(0, mm.rows, pushValue)
              // ptr update
              ptr.push(index.length)
              // resolve promise
              resolve(new SparseMatrix({
                values: values,
                index: index,
                ptr: ptr,
                size: [mm.rows, mm.columns],
                datatype: datatype
              }))
            }
            break
          case 'array':
            // resolve promise
            console.log(mm.data)
            resolve(new DenseMatrix({
              data: mm.data,
              size: [mm.rows, mm.columns]
            }))
            break
        }
      }
    })

    stream.on('error', function (e) {
      // reject promise
      reject(new Error(e))
    })
  })
}
/**
 * Imports a Matrix Market matrix from the filesystem. (https://math.nist.gov/MatrixMarket/)
 */
export const marketImport = typed('importMatrix', {
  Array: function (files) {
    return Promise.all(files.map(file => _import(file)))
  },
  string: function (file) {
    const input = fs.createReadStream(file)
    return _importFromStream(input)
  }
})