//This region contains the handlers for all of the statistical functions presented to the user
/// <summary>
/// Performs a single-variable reductive statistical function on a user-selected variable from the data set.<para/>
/// This operation takes one variable from each row and turns it into one number.
/// </summary>
/// <param name="name">The name of the statistical function as presented to the user.</param>
/// <param name="reductionFunction">
/// The reduction function to use.<para/>
/// This turns a list of numbers into one number through some transformation.
/// </param>
private void StatFunction(string name, Func <IEnumerable <double>, double> reductionFunction)
{
char[] variables = SelectVariableDialog.SelectVariables(name, DataSet.Variables, name + " of:");
if (variables != null && SaveChanges())
{
var data = DataSet.RowSelect(variables[0]);
double value = reductionFunction(data);
MessageBox.Show(name + ": " + value.ToString("0.#####"), "Statistics", MessageBoxButtons.OK, MessageBoxIcon.Information);
}
}
/// <summary>
/// Prompts the user to select a number of variables from a predefined selection of choices.
/// </summary>
/// <param name="title">The title of the selection dialog.</param>
/// <param name="possibleValues">An array of possible character values that each choice can take.</param>
/// <param name="labels">
/// The labels for each different required variable choice.<para/>
/// The size of this parameter array determines the size of the array returned by the method.
/// </param>
/// <returns>Returns an array of user-selected variables from the <c>possibleValues</c> parameter.<para/>
/// If the user cancels the dialog interaction then this method returns null.</returns>
public static char[] SelectVariables(string title, char[] possibleValues, params string[] labels)
{
SelectVariableDialog dialog = new SelectVariableDialog(title, possibleValues, labels);
if (dialog.ShowDialog() == DialogResult.OK)
{
return(dialog.Value);
}
else
{
return(null);
}
}
private void pMCCToolStripMenuItem_Click(object sender, EventArgs e)
{
char[] variables = SelectVariableDialog.SelectVariables("Product-moment correlation coefficient", DataSet.Variables, "PMCC of:", "with:");
if (variables != null && variables[0] != variables[1])
{
if (variables != null && SaveChanges())
{
double value = DataSet.Pmcc(variables[0], variables[1]);
MessageBox.Show("Product-moment correlation coefficient: " + value.ToString("0.#####"), "Statistics", MessageBoxButtons.OK, MessageBoxIcon.Information);
}
}
else
{
MessageBox.Show("The chosen variables must not be the same.", "Statistics", MessageBoxButtons.OK, MessageBoxIcon.Error);
}
}
/// <summary>
/// Performs a double-variable reductive statistical function on a user-selected variable from the data set.<para/>
/// This operation takes two variables from each row and turns it into one number.
/// </summary>
/// <param name="name">The name of the statistical function as presented to the user.</param>
/// <param name="reductionFunction">
/// The reduction function to use.<para/>
/// This turns a list of pairs of numbers into one number through some transformation.
/// </param>
/// <param name="uniqueVariables">True if chosen variables must be unique; false otherwise.</param>
private void StatFunction(string name, Func <IEnumerable <Tuple <double, double> >, double> reductionFunction, bool uniqueVariables = false)
{
char[] variables = SelectVariableDialog.SelectVariables(name, DataSet.Variables, name + " of:", "and:");
if (variables != null && variables[0] != variables[1])
{
if (variables != null && SaveChanges())
{
var data = DataSet.RowSelect(variables[0], variables[1]);
double value = reductionFunction(data);
MessageBox.Show(name + ": " + value.ToString("0.#####"), "Statistics", MessageBoxButtons.OK, MessageBoxIcon.Information);
}
}
else
{
MessageBox.Show("The chosen variables must not be the same.", "Statistics", MessageBoxButtons.OK, MessageBoxIcon.Error);
}
}
private void createRegressionLineToolStripMenuItem_Click(object sender, EventArgs e)
{
char[] variables = SelectVariableDialog.SelectVariables("Regression line", DataSet.Variables, "Independent variable:", "Dependent variable:");
if (variables != null && variables[0] != variables[1])
{
if (variables != null && SaveChanges())
{
LinearCurve line = DataSet.FitLinear(variables[0], variables[1]);
Document.Add(line.ToEquation());
MessageBox.Show(
"The regression line has been added to the Document.\r\n" + line.ToString(),
"Statistics", MessageBoxButtons.OK, MessageBoxIcon.Information);
}
}
else
{
MessageBox.Show("The chosen variables must not be the same.", "Statistics", MessageBoxButtons.OK, MessageBoxIcon.Error);
}
}
