chimeric-tools 0.0.1

ComputationalUncertaintyLab/chimeric-tools

chimeric-tools

Data folder

functions

Preprocess folder

• Function name: formatIndividualPredictions

  • input: a single csv file of individual predictions from metaculus
  • output: a pandas daat frame that is long format
  • info: Wenxuan, this is your code that transforms the csv file to long.

• Function name: write_individual_formatted

  • input: a pandas data frame in lojng format
  • output: nothing
  • info: Wenxuan, this will output the formatted pandas data frame to a file with the name "WW-YYYY-MM-DD_metaculus_individual_predictions.csv.gz" where WW is the epidemic week, YYYY is the year, mm is month, and dd is day.

• Function name: (for prof m to add) metaculus_client

  • input: string that links to user credentials
  • output: object to interact with API
  • info: prof m will write this and Wenuxan and Xinze will test how well it does (or does not) work

spatial folder

• Function Name: fromState2FIPS
  • input: String abbrevation of a state. For example "PA"
  • output: The FIPS value that corresponds to the state (For example the FIPS for PA is 42)
  • info: I think this URL will be useful https://www.nrcs.usda.gov/wps/portal/nrcs/detail/national/home/?cid=nrcs143_013697

Time Folder

functions

• Function name: fromDate2Epiweek

  • input: a string in the format YYYY-mm-dd
  • output: The Epidemic week that corresponds to YYYY-mm-dd
  • info: We can use the epiweeks package to do this.

• Function name: fromDates2Epiweeks

  • input: a list of strings in the format YYYY-mm-dd
  • output: The Epidemic weeks that corresponds to YYYY-mm-dd
  • info: We can use the epiweeks package to do this.

• Function name: today

  • input: nothing
  • output: todays date in YYYY-mm-dd format
  • info: We can use the datetime package to do this.

• Function name: todayEpiWeek

  • input: nothing
  • output: the epidemic weeks that corresponds to todays date in YYYY-mm-dd format
  • info: We can use the datetime package and epiweeks package to do this.

Aggregation