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Metadata and mappings from abbreviations to corresponding text in csv

Index

Variables

Object literals

Variables

headers

headers: string[] = ['location','target','type','unit','bin_start_incl','bin_end_notincl','value']

The headers expected in the csv files

regionIds

regionIds: RegionId[] = ['nat','hhs1','hhs2','hhs3','hhs4','hhs5','hhs6','hhs7','hhs8','hhs9','hhs10']

Short ids representing a region in the code.

scoreIds

scoreIds: string[] = ['logScore','logScoreMultiBin','error','absError']

Short ids representing a score in the code.

stateIds

stateIds: string[] = ['AK', 'AL', 'AR', 'AZ', 'CA', // 0-4'CO', 'CT', 'DC', 'DE', 'FL', // 5-9'GA', 'HI', 'IA', 'ID', 'IL', // 10-14'IN', 'KS', 'KY', 'LA', 'MA', // 15-19'MD', 'ME', 'MI', 'MN', 'MO', // 20-24'MS', 'MT', 'NC', 'ND', 'NE', // 25-29'NH', 'NJ', 'NM', 'NV', 'NY', // 30-34'OH', 'OK', 'OR', 'PA', 'RI', // 35-39'SC', 'SD', 'TN', 'TX', 'UT', // 40-44'VA', 'VT', 'WA', 'WI', 'WV', // 45-49'WY']

List of US state abbreviations

targetIds

targetIds: TargetId[] = ['1-ahead','2-ahead','3-ahead','4-ahead','peak','peak-wk','onset-wk']

Short ids representing a target in the code.

Object literals

regionFullName

regionFullName: object

Mapping from region ids to full region name as used in the csvs

hhs1

hhs1: string = "HHS Region 1"

hhs10

hhs10: string = "HHS Region 10"

hhs2

hhs2: string = "HHS Region 2"

hhs3

hhs3: string = "HHS Region 3"

hhs4

hhs4: string = "HHS Region 4"

hhs5

hhs5: string = "HHS Region 5"

hhs6

hhs6: string = "HHS Region 6"

hhs7

hhs7: string = "HHS Region 7"

hhs8

hhs8: string = "HHS Region 8"

hhs9

hhs9: string = "HHS Region 9"

nat

nat: string = "US National"

regionStates

regionStates: object

Mapping from region ids to the states in those regions

hhs1

hhs1: string[] = [6, 19, 21, 30, 39, 46].map(i => stateIds[i])

hhs10

hhs10: string[] = [0, 13, 37, 47].map(i => stateIds[i])

hhs2

hhs2: string[] = [31, 34].map(i => stateIds[i])

hhs3

hhs3: string[] = [8, 20, 38, 45, 49].map(i => stateIds[i])

hhs4

hhs4: string[] = [1, 9, 10, 17, 25, 27, 40, 42].map(i => stateIds[i])

hhs5

hhs5: string[] = [14, 15, 22, 23, 35, 48].map(i => stateIds[i])

hhs6

hhs6: string[] = [2, 18, 32, 36, 43].map(i => stateIds[i])

hhs7

hhs7: string[] = [12, 16, 24, 29].map(i => stateIds[i])

hhs8

hhs8: string[] = [5, 26, 28, 41, 44, 50].map(i => stateIds[i])

hhs9

hhs9: string[] = [3, 4, 11, 33].map(i => stateIds[i])

nat

nat: string[] = stateIds

targetFullName

targetFullName: object

Mapping from target ids to full name as used in the csvs

1-ahead

1-ahead: string = "1 wk ahead"

2-ahead

2-ahead: string = "2 wk ahead"

3-ahead

3-ahead: string = "3 wk ahead"

4-ahead

4-ahead: string = "4 wk ahead"

onset-wk

onset-wk: string = "Season onset"

peak

peak: string = "Season peak percentage"

peak-wk

peak-wk: string = "Season peak week"

targetType

targetType: object

Target type for each target. Note that there can be only two target types, 'percent' and 'week'.

1-ahead

1-ahead: string = "percent"

2-ahead

2-ahead: string = "percent"

3-ahead

3-ahead: string = "percent"

4-ahead

4-ahead: string = "percent"

onset-wk

onset-wk: string = "week"

peak

peak: string = "percent"

peak-wk

peak-wk: string = "week"

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