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WfccmDataSet
(28 Apr 2005,
WillGray
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---+ !! <nop>DataSet %TOC% <noautolink> Parent: [[WfccmDataContainer][DataContainer]], Interface: [[WfccmIDataSet][IDataSet]] ---+++ Public Methods * %Y% DataSet(DataSet) - Copy Constructor overload that handles the name list. * %Y% SetDataPoint(int, int, double) - Set the data at that point. * %Y% GetDataPoint(int, int) - Gets the data at that point. * %Y% SetRowName(int, string) - Sets the row name for the row. * %Y% GetRowName(int) - Gets the row name for the row given. * %Y% AddRow(int, string) - Overload to include row name. * %Y% RemoveRows(string, ...) - Removes multiple rows of data by name. * %Y% RemoveRows(ArrayList) - Removes multiple rows of data by id or name. Do not include both. * %Y% Filter(string, ...) - Removes all rows except the ones specified by name. * %Y% Filter(ArrayList) - Removes all rows except the ones specified by id or name. Do not include both. * %Y% Copy() - Returns a new DataSet that is a deep copy of this object. * %Y% Clear() - Overload that also clears the row names. * %Y% Append(DataSet) - Takes another DataSet and adds the rows to this object. There must be the same number of columns and the column names must be identical. The row ids must be exclusive to each data set, e.g. there can't be the same row id in both data sets. If there is a row id conflict, an error will be thrown and no changes are made to the data. * %Y% Merge(DataSet) - Takes another DataSet and adds the columns to this object. Rows that are in one data set and not the other will be added and null values inserted for the rest of the other data set. Column names must be unique to each data set, e.g. there can't be the same column name in both data sets. When there is a column name conflict, an error will be thrown and no changes are made to the data. * %Y% Log(int) - Transforms all values in the data set to the log n value. * %Y% Avgerage(DataGrouping, int) - Combines columns in the DataSet based on groups. * %Y% Load(string) - Loads the object from the file given in the file path. * %Y% Save(string, string) - Write the DataSet to the file given, using the specified delimiter. * %Y% SaveEisen(string, DataGrouping) - Writes the data set with the column headers as the group number concatenated with "---" and the column name. The column names should be padded with "_" at the end to make the column names the same length. * %Y% GeneratePercentage(DataGrouping, int) - Calculate the % of each group that has non-null data or non-zero data. Flag to determine whether to count null or zero. * %Y% GenerateBasicStats() - Calculates the basic statistics (min, first quartile, median, third quartile, max, mean, std dev, number of nulls, number of zeros) for each column and returns an InformationSet. The quartiles are computed by the weighted average at %$x_{(n+1)p}$%. * %Y% MeanStdev() - generates the mean and standard deviation separately for all the positive and negative values and returns them as "out" parameters ---+++ Explicit Interface Public Methods * Filter(ArrayList) * Log(string, int) * Average(string, DataGrouping) * Average(string, DataGrouping, bool) ---+++ Protected Methods * %Y% Copy(DataSet) - Copies a DataSet over the current object. ---+++ Private Members * ArrayList rowNames - The row names. ---+++ Exceptions * Averaging a data set with a gouping that does not reduce the column numbers. * Averaging a data set with the 0 group. * %Y% Logging a data set that has negative values. * %Y% A file is not formatted correctly. * %Y% A file to read does not exist. ---+++ Remarks * When averaging, the default behoviour is to ignore the zeros. Treat them as if they do not exist. Caveat: The only time a null should be returned is if only nulls are in the average set. The function can be flagged to include zeros in the average. The new column name will be the DataGroupings group descriptor. The data sew will be modified from its original state to reflect the changes. The old state will be lost after the change. * Log transformations must be performed on data that is >= 0. If any data point is < 0, the transformation must fail. If any data is < 0, the function should not change any data. For values that are equal to 0, the value will remain zero. When the only function available is log base 10, a value v can be log transformed with a base of b: %$\frac{\log _{10}v}{\log_{10}b}$% * Missing values: stored as =Double.NaN=, written as ".". </noautolink>
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Topic revision: r33 - 28 Apr 2005,
WillGray
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