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Make enum lowercase keys uppercase
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packages/@aws-cdk/aws-cloudwatch/lib/metric-types.ts

Lines changed: 7 additions & 7 deletions
Original file line numberDiff line numberDiff line change
@@ -222,55 +222,55 @@ export enum Statistic {
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*
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* wm10 calculates the average while treating the 90% of the highest values to be equal to the value at the 10th percentile.
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*/
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wm10 = 'wm10',
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WM10 = 'wm10',
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/**
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* Winsorized mean (WM) is similar to trimmed mean. However, with winsorized mean, the values that are outside the boundary are not ignored,
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* but instead are considered to be equal to the value at the edge of the appropriate boundary.
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* After this normalization, the average is calculated. You define the boundaries as one or two numbers between 0 and 100, up to 10 decimal places.
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*
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* wm50 calculates the average while treating the 50% of the highest values to be equal to the value at the 50th percentile.
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*/
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wm50 = 'wm50',
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WM50 = 'wm50',
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/**
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* Winsorized mean (WM) is similar to trimmed mean. However, with winsorized mean, the values that are outside the boundary are not ignored,
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* but instead are considered to be equal to the value at the edge of the appropriate boundary.
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* After this normalization, the average is calculated. You define the boundaries as one or two numbers between 0 and 100, up to 10 decimal places.
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*
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* wm90 calculates the average while treating the 10% of the highest values to be equal to the value at the 90th percentile.
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*/
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wm90 = 'wm90',
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WM90 = 'wm90',
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/**
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* Winsorized mean (WM) is similar to trimmed mean. However, with winsorized mean, the values that are outside the boundary are not ignored,
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* but instead are considered to be equal to the value at the edge of the appropriate boundary.
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* After this normalization, the average is calculated. You define the boundaries as one or two numbers between 0 and 100, up to 10 decimal places.
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*
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* wm95 calculates the average while treating the 5% of the highest values to be equal to the value at the 95th percentile.
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*/
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wm95 = 'wm95',
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WM95 = 'wm95',
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/**
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* Winsorized mean (WM) is similar to trimmed mean. However, with winsorized mean, the values that are outside the boundary are not ignored,
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* but instead are considered to be equal to the value at the edge of the appropriate boundary.
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* After this normalization, the average is calculated. You define the boundaries as one or two numbers between 0 and 100, up to 10 decimal places.
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*
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* wm99 calculates the average while treating the 1% of the highest values to be equal to the value at the 99th percentile.
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*/
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wm99 = 'wm99',
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WM99 = 'wm99',
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/**
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* Winsorized mean (WM) is similar to trimmed mean. However, with winsorized mean, the values that are outside the boundary are not ignored,
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* but instead are considered to be equal to the value at the edge of the appropriate boundary.
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* After this normalization, the average is calculated. You define the boundaries as one or two numbers between 0 and 100, up to 10 decimal places.
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*
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* wm99.9 calculates the average while treating the 0.1% of the highest values to be equal to the value at the 99.9th percentile.
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*/
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wm99_9 = 'wm99.9',
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WM99_9 = 'wm99.9',
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/**
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* Winsorized mean (WM) is similar to trimmed mean. However, with winsorized mean, the values that are outside the boundary are not ignored,
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* but instead are considered to be equal to the value at the edge of the appropriate boundary.
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* After this normalization, the average is calculated. You define the boundaries as one or two numbers between 0 and 100, up to 10 decimal places.
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*
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* wm99.99 calculates the average while treating the 0.01% of the highest values to be equal to the value at the 99.99th percentile.
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*/
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wm99_99 = 'wm99.99',
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WM99_99 = 'wm99.99',
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/**
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* Winsorized mean (WM) is similar to trimmed mean. However, with winsorized mean, the values that are outside the boundary are not ignored,

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