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- validationRules. It is possible to define a set of validationRules. With these validation rules it is possible to define a set of criteria which determines the outputflag of the calculated value based on the number of missing values and/or doubtfulls doubtfuls values counted in the input values.
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The validation rules are optional in the configuration and can be used to define the outputflag and the custom flagsource of the output value based on the number of missing values/unreliables values and/or the number of doubtfull doubtful values in the used input values. The available output flags are reliable, doubtful and missing.
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1 if the percentage of missing and/or unreliable values is less than 15% the output should be reliable.
2 if the percentage of missing values is less than 40% the output should be doubtfulldoubtful.
3 in all other cases the output should be a missing value.
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The example shows that in total 3 validation rules were needed. The first rule checks if less than 15% of the input is missing/unreliable. If this is not the case than it will be checked if the second rule can be applied. The second rule states that if less than 40% of the input is missing that in that case the output flag should be set to doubtfulldoubtful. The last rule takes care of all the other situations. Note that it has a percentage configured of 100%. Which means that this rule will be applied. However because 2 rules are defined above this rule FEWS will always try to apply these rules first before applying this rule.
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Finally it is also possible to define validation rules based on the number of doubtful values in the input. It is even possible to define validation rules based on a combination of an allowed percentage of unreliable/missing values and doubtfull doubtful values. The sequence of applying the rules is also in this case the order in which the rules are configured. The first rule which applies to the
current situation is used.
Let's say for example that we also want rules to be defined for the doubtful input values. For example when only a small number of input values are doubtful we still want the output to be reliable. Otherwise we would like to have the output to be doubtfull doubtful but with an custom flag source which give us an indication of how many of the input values were doubtful.
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Time | Input value | input flag | Output value | output flag | custom flagsource |
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1-1-2012 00:15 |
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1-1-2012 00:30 | 1 |
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1-1-2012 00:45 | 1 |
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1-1-2012 01:00 | 1 |
| 3 | doubtful | - |
1-1-2012 01:15 |
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1-1-2012 01:30 | 1 |
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1-1-2012 01:45 |
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1-1-2012 02:00 | 1 |
| NaN | - | - |
1-1-2012 02:15 | 1 |
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1-1-2012 02:30 | 1 | doubtful |
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1-1-2012 02:45 | 1 |
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1-1-2012 03:00 | 1 |
| 4 | doubtful | D1 |
1-1-2012 03:15 | 1 |
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1-1-2012 03:30 | 1 |
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1-1-2012 03:45 | 1 |
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1-1-2012 04:00 | 1 |
| 4 | doubtfull doubtful | - |
The first output value is set to doubtful. Because in this case the total percentage of missing values is 25%. Which means that the following rule is applied.
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