Esempio n. 1
0
        /// <summary>
        ///     Analyze the data. This counts the records and prepares the data to be
        ///     processed.
        /// </summary>
        /// <param name="theAnalyst">The analyst to use.</param>
        /// <param name="inputFile">The input file.</param>
        /// <param name="headers">True if headers are present.</param>
        /// <param name="format">The format the file is in.</param>
        public void Analyze(EncogAnalyst theAnalyst,
                            FileInfo inputFile, bool headers, CSVFormat format)
        {
            InputFilename      = inputFile;
            ExpectInputHeaders = headers;
            Format             = format;
            _analyst           = theAnalyst;

            Analyzed = true;

            PerformBasicCounts();

            _inputCount  = _analyst.DetermineInputCount();
            _outputCount = _analyst.DetermineOutputCount();
            _idealCount  = InputHeadings.Length - _inputCount;

            if ((InputHeadings.Length != _inputCount) &&
                (InputHeadings.Length != (_inputCount + _outputCount)))
            {
                throw new AnalystError("Invalid number of columns("
                                       + InputHeadings.Length + "), must match input("
                                       + _inputCount + ") count or input+output("
                                       + (_inputCount + _outputCount) + ") count.");
            }
        }
Esempio n. 2
0
        /// <summary>
        ///     Analyze the data. This counts the records and prepares the data to be
        ///     processed.
        /// </summary>
        /// <param name="theAnalyst">The analyst to use.</param>
        /// <param name="inputFile">The input file.</param>
        /// <param name="headers">True if headers are present.</param>
        /// <param name="format">The format the file is in.</param>
        public void Analyze(EncogAnalyst theAnalyst,
                            FileInfo inputFile, bool headers, CSVFormat format)
        {
            InputFilename = inputFile;
            ExpectInputHeaders = headers;
            Format = format;
            _analyst = theAnalyst;

            Analyzed = true;

            PerformBasicCounts();

            _inputCount = _analyst.DetermineInputCount();
            _outputCount = _analyst.DetermineOutputCount();
            _idealCount = InputHeadings.Length - _inputCount;

            if ((InputHeadings.Length != _inputCount)
                && (InputHeadings.Length != (_inputCount + _outputCount)))
            {
                throw new AnalystError("Invalid number of columns("
                                       + InputHeadings.Length + "), must match input("
                                       + _inputCount + ") count or input+output("
                                       + (_inputCount + _outputCount) + ") count.");
            }
        }
        /// <summary>
        ///     Construct the time-series utility.
        /// </summary>
        /// <param name="theAnalyst">The analyst to use.</param>
        /// <param name="includeOutput">Should output fields be included.</param>
        /// <param name="headings">The column headings.</param>
        public TimeSeriesUtil(EncogAnalyst theAnalyst, bool includeOutput,
                              IEnumerable <string> headings)
        {
            _buffer     = new List <double[]>();
            _headingMap = new Dictionary <String, Int32>();
            _analyst    = theAnalyst;
            _lagDepth   = _analyst.LagDepth;
            _leadDepth  = _analyst.LeadDepth;
            _totalDepth = _lagDepth + _leadDepth + 1;
            _inputSize  = includeOutput ? _analyst.DetermineTotalColumns() : _analyst.DetermineTotalInputFieldCount();
            _outputSize = _analyst.DetermineInputCount()
                          + _analyst.DetermineOutputCount();

            int headingIndex = 0;

            foreach (String column  in  headings)
            {
                _headingMap[column.ToUpper()] = headingIndex++;
            }
        }
        /// <summary>
        ///     Construct the time-series utility.
        /// </summary>
        /// <param name="theAnalyst">The analyst to use.</param>
        /// <param name="includeOutput">Should output fields be included.</param>
        /// <param name="headings">The column headings.</param>
        public TimeSeriesUtil(EncogAnalyst theAnalyst, bool includeOutput,
            IEnumerable<string> headings)
        {
            _buffer = new List<double[]>();
            _headingMap = new Dictionary<String, Int32>();
            _analyst = theAnalyst;
            _lagDepth = _analyst.LagDepth;
            _leadDepth = _analyst.LeadDepth;
            _totalDepth = _lagDepth + _leadDepth + 1;
            _inputSize = includeOutput ? _analyst.DetermineTotalColumns() : _analyst.DetermineTotalInputFieldCount();
            _outputSize = _analyst.DetermineInputCount()
                          + _analyst.DetermineOutputCount();

            int headingIndex = 0;

            foreach (String column  in  headings)
            {
                _headingMap[column.ToUpper()] = headingIndex++;
            }
        }