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public CAGWorkflow() { InitializeComponent(); } } } After switching to the workflow designer view, drag and drop a ConditionedActivityGroup to the workflow. Figure 5-17 shows the workflow with the empty CAG. As you can see in Figure 5-17, the CAG is composed of two distinct sections. The top section is like a filmstrip that contains the list of child activities that have been added. This is where you drag and drop new activities or select an existing activity for modification. The bottom section of the CAG is a preview or edit area for the currently selected activity. By clicking the small button to the left of Previewing, you can switch back and forth between Previewing and Editing. If the child activity that you add is itself a composite activity, you will need to switch to Editing mode in order to add children to it. Once the composite activity is in Editing mode, you drag and drop new child activities onto the bottom section of the CAG to add them to the composite activity.

Essentially, we just need to plug in the single variable we have in our data (hits in a season) and the amount of expected successes into the model. Let s assume our fictitious baseball player has 200 hits during the season. Our goal is to estimate the likelihood the batter will attain a certain amount of hits. Defining the variables in the model nets us the following: The (average mean) is 200 hits/162 games in a season. The batter on average has 1.2345 hits per game. K is the amount of successful hits we expect the hitter to have. Let s use the number 1 to calculate the probability of the hitter having a single hit in the game. K! becomes 1!, which translates to 1.

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Figure 5-17. Workflow with empty CAG Drag and drop four instances of the CodeActivity onto the top filmstrip area of the CAG. Each one of these activities corresponds to a kind of item to process (sandwich, fries, drink, combo). To keep the purpose of each activity clear, change the names of these activities to codeSandwich, codeFries, codeDrink, and codeCombo. Each CodeActivity requires a different WhenCondition. When the condition is true, the activity is executed. All conditions should be set as a Declarative Rule Condition. The ConditionName and Expression properties for each condition are shown in Table 5-5. Double-click each CodeActivity to add a handler for the ExecuteCode event. The complete code for the CAGWorkflow.cs file is shown and discussed in Listing 5-17.

CHAPTER 9 PREDICTIVE ANALYTICS (WHAT-IF MODELING)

Double-clicking one of the child activities switches the CAG designer from Previewing to Editing mode. This allows you to interact with the child activity.

Dim fso,s,re,line,lineNbr Set fso = CreateObject("Scripting.FileSystemObject") Set s = fso.OpenTextFile(WScript.Arguments.Item(0), 1, True) Set re = New RegExp re.Pattern = "^(0 2/(0 [1-9]|[12][0-9])| (0 [469]|11)/(0 [1-9]|[12][0-9]|30)| (0 [13578]|1[02])/(0 [1-9]|[12][0-9]|3[01]))/\d{4}$" lineNbr = 0 Do While Not s.AtEndOfStream line = s.ReadLine() lineNbr = lineNbr + 1 If re.Test(line) Then WScript.Echo "Found match: '" & line & "' at line " & lineNbr End If Loop s.Close

The formula is illustrated in Figure 9-11 after the numbers are entered into the Poisson calculation. The answer to our problem is 35.9 percent. The full answer is that the probability of a batter with 200 hits in a season to have a 1 hit in a game is 35.9 percent.

this.LineItems.Contains("sandwich") this.LineItems.Contains("fries") this.LineItems.Contains("drink") this.LineItems.Contains("combo")

Listing 5-17. Complete CAGWorkflow.cs File using using using using System; System.ComponentModel; System.Collections.Generic; System.Workflow.Activities;

The Poisson distribution formula is cornerstone of the coding scenario. Once you understand this part, you are ready to proceed to implement this model in a Silverlight application.

<html> <head> <title>4-15. Validating Dates in MM/DD/YYYY</title> </head> <body> <form name="form1"> <input type="textbox" name="txtInput" /> <script type="text/javascript"> function validate() { if (! document.form1.txtInput.value.match(/^(0 2/(0 [1-9]|[12][0-9])| (0 [469]|11)/(0 [1-9]|[12][0-9]|30)| (0 [13578]|1[02])/(0 [1-9]|[12][0-9]|3[01]))/\d{4}$/)) { alert("Please enter valid value!") } else { alert("Success!") } } </script> <input type="button" name="btnSubmit" onclick="validate()" value="Go" /> </form> </body> </html>

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