/*
* Copyright 2007 ZXing authors
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
*      http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
namespace com.google.zxing.oned
{
    using System;
    using com.google.zxing.common;
    
    public abstract class AbstractOneDReader 
    {
          private static  int INTEGER_MATH_SHIFT = 8;
          public static  int PATTERN_MATCH_RESULT_SCALE_FACTOR = 1 << INTEGER_MATH_SHIFT;

          public  Result decode(MonochromeBitmapSource image) {
            return decode(image, null);
          }

          public  Result decode(MonochromeBitmapSource image, System.Collections.Hashtable hints) {
            try {
              return doDecode(image, hints);
            } catch (ReaderException re) {
              bool tryHarder = hints != null && hints.ContainsKey(DecodeHintType.TRY_HARDER);
              if (tryHarder && image.isRotateSupported()) {
                MonochromeBitmapSource rotatedImage = image.rotateCounterClockwise();
                Result result = doDecode(rotatedImage, hints);
                // Record that we found it rotated 90 degrees CCW / 270 degrees CW
                System.Collections.Hashtable metadata = result.getResultMetadata();
                int orientation = 270;
                if (metadata != null && metadata.ContainsKey(ResultMetadataType.ORIENTATION)) {
                  // But if we found it reversed in doDecode(), add in that result here:
                  orientation = (orientation + ((int) metadata[ResultMetadataType.ORIENTATION])) % 360;
                }
                result.putMetadata(ResultMetadataType.ORIENTATION, orientation);
                return result;
              } else {
                throw re;
              }
            }
          }

          /**
           * We're going to examine rows from the middle outward, searching alternately above and below the
           * middle, and farther out each time. rowStep is the number of rows between each successive
           * attempt above and below the middle. So we'd scan row middle, then middle - rowStep, then
           * middle + rowStep, then middle - (2 * rowStep), etc.
           * rowStep is bigger as the image is taller, but is always at least 1. We've somewhat arbitrarily
           * decided that moving up and down by about 1/16 of the image is pretty good; we try more of the
           * image if "trying harder".
           *
           * @param image The image to decode
           * @param hints Any hints that were requested
           * @return The contents of the decoded barcode
           * @throws ReaderException Any spontaneous errors which occur
           */
          private Result doDecode(MonochromeBitmapSource image, System.Collections.Hashtable hints) {
            int width = image.getWidth();
            int height = image.getHeight();
            BitArray row = new BitArray(width);

            int middle = height >> 1;
            bool tryHarder = hints != null && hints.ContainsKey(DecodeHintType.TRY_HARDER);
            int rowStep = Math.Max(1, height >> (tryHarder ? 7 : 4));
            int MaxLines;
            if (tryHarder) {
              MaxLines = height; // Look at the whole image, not just the center
            } else {
              MaxLines = 9; // Nine rows spaced 1/16 apart is roughly the middle half of the image
            }

            for (int x = 0; x < MaxLines; x++) {

              // Scanning from the middle out. Determine which row we're looking at next:
              int rowStepsAboveOrBelow = (x + 1) >> 1;
              bool isAbove = (x & 0x01) == 0; // i.e. is x even?
              int rowNumber = middle + rowStep * (isAbove ? rowStepsAboveOrBelow : -rowStepsAboveOrBelow);
              if (rowNumber < 0 || rowNumber >= height) {
                // Oops, if we run off the top or bottom, stop
                break;
              }

              // Estimate black point for this row and load it:
              try {
                image.estimateBlackPoint(BlackPointEstimationMethod.ROW_SAMPLING, rowNumber);
              } catch (ReaderException re) {
                continue;
              }

              image.getBlackRow(rowNumber, row,0, width);

              // While we have the image data in a BitArray, it's fairly cheap to reverse it in place to
              // handle decoding upside down barcodes.
              for (int attempt = 0; attempt < 2; attempt++) {
                if (attempt == 1) { // trying again?
                  row.reverse(); // reverse the row and continue
                }
                try {
                  // Look for a barcode
                  Result result = decodeRow(rowNumber, row, hints);
                  // We found our barcode
                  if (attempt == 1) {
                    // But it was upside down, so note that
                    result.putMetadata(ResultMetadataType.ORIENTATION, 180);
                    // And remember to flip the result points horizontally.
                    ResultPoint[] points = result.getResultPoints();
                    points[0] = (ResultPoint) new GenericResultPoint(width - points[0].getX() - 1, points[0].getY());
                    points[1] = (ResultPoint)new GenericResultPoint(width - points[1].getX() - 1, points[1].getY());
                  }
                  return result;
                } catch (ReaderException re) {
                  // continue -- just couldn't decode this row
                }
              }
            }

            throw new ReaderException();
          }

          /**
           * Records the size of successive runs of white and black pixels in a row, starting at a given point.
           * The values are recorded in the given array, and the number of runs recorded is equal to the size
           * of the array. If the row starts on a white pixel at the given start point, then the first count
           * recorded is the run of white pixels starting from that point; likewise it is the count of a run
           * of black pixels if the row begin on a black pixels at that point.
           *
           * @param row row to count from
           * @param start offset into row to start at
           * @param counters array into which to record counts
           * @throws ReaderException if counters cannot be filled entirely from row before running out of pixels
           */
          public static void recordPattern(BitArray row, int start, int[] counters) {
            int numCounters = counters.Length;
            for (int i = 0; i < numCounters; i++) {
              counters[i] = 0;
            }
            int end = row.getSize();
            if (start >= end) {
              throw new ReaderException();
            }
            bool isWhite = !row.get(start);
            int counterPosition = 0;

            int k = start;
            while (k < end) {
              bool pixel = row.get(k);
              if ((!pixel && isWhite) || (pixel && !isWhite)) {
                counters[counterPosition]++;
              } else {
                counterPosition++;
                if (counterPosition == numCounters) {
                  break;
                } else {
                  counters[counterPosition] = 1;
                  isWhite = !isWhite;
                }
              }
              k++;
            }
            // If we read fully the last section of pixels and filled up our counters -- or filled
            // the last counter but ran off the side of the image, OK. Otherwise, a problem.
            if (!(counterPosition == numCounters || (counterPosition == numCounters - 1 && k == end))) {
              throw new ReaderException();
            }
          }

          /**
           * Determines how closely a set of observed counts of runs of black/white values matches a given
           * target pattern. This is reported as the ratio of the total variance from the expected pattern
           * proportions across all pattern elements, to the length of the pattern.
           *
           * @param counters observed counters
           * @param pattern expected pattern
           * @param MaxIndividualVariance The most any counter can differ before we give up
           * @return ratio of total variance between counters and pattern compared to total pattern size,
           *  where the ratio has been multiplied by 256. So, 0 means no variance (perfect match); 256 means
           *  the total variance between counters and patterns equals the pattern length, higher values mean
           *  even more variance
           */
          public static int patternMatchVariance(int[] counters, int[] pattern, int MaxIndividualVariance) {
            int numCounters = counters.Length;
            int total = 0;
            int patternLength = 0;
            for (int i = 0; i < numCounters; i++) {
              total += counters[i];
              patternLength += pattern[i];
            }
            if (total < patternLength) {
              // If we don't even have one pixel per unit of bar width, assume this is too small
              // to reliably match, so fail:
              return int.MaxValue;
            }
            // We're going to fake floating-point math in integers. We just need to use more bits.
            // Scale up patternLength so that intermediate values below like scaledCounter will have
            // more "significant digits"
            int unitBarWidth = (total << INTEGER_MATH_SHIFT) / patternLength;
            MaxIndividualVariance = (MaxIndividualVariance * unitBarWidth) >> INTEGER_MATH_SHIFT;

            int totalVariance = 0;
            for (int x = 0; x < numCounters; x++) {
              int counter = counters[x] << INTEGER_MATH_SHIFT;
              int scaledPattern = pattern[x] * unitBarWidth;
              int variance = counter > scaledPattern ? counter - scaledPattern : scaledPattern - counter;
              if (variance > MaxIndividualVariance) {
                return int.MaxValue;
              }
              totalVariance += variance; 
            }
            return totalVariance / total;
          }

          // This declaration should not be necessary, since this class is
          // abstract and so does not have to provide an implementation for every
          // method of an interface it implements, but it is causing NoSuchMethodError
          // issues on some Nokia JVMs. So we add this superfluous declaration:

          public abstract Result decodeRow(int rowNumber, BitArray row, System.Collections.Hashtable hints);
  
    
    }
}