R/forecastqueryservice_interfaces.R

Defines functions query_what_if_forecast_output query_what_if_forecast_input query_forecast_output query_forecast_input

# This file is generated by make.paws. Please do not edit here.
#' @importFrom paws.common populate
#' @include forecastqueryservice_service.R
NULL

.forecastqueryservice$query_forecast_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(ForecastArn = structure(logical(0), tags = list(type = "string")), StartDate = structure(logical(0), tags = list(type = "string")), EndDate = structure(logical(0), tags = list(type = "string")), Filters = structure(list(structure(logical(0), tags = list(type = "string"))), tags = list(type = "map")), NextToken = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.forecastqueryservice$query_forecast_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(Forecast = structure(list(Predictions = structure(list(structure(list(structure(list(Timestamp = structure(logical(0), tags = list(type = "string")), Value = structure(logical(0), tags = list(type = "double"))), tags = list(type = "structure"))), tags = list(type = "list"))), tags = list(type = "map"))), tags = list(type = "structure"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.forecastqueryservice$query_what_if_forecast_input <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(WhatIfForecastArn = structure(logical(0), tags = list(type = "string")), StartDate = structure(logical(0), tags = list(type = "string")), EndDate = structure(logical(0), tags = list(type = "string")), Filters = structure(list(structure(logical(0), tags = list(type = "string"))), tags = list(type = "map")), NextToken = structure(logical(0), tags = list(type = "string"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

.forecastqueryservice$query_what_if_forecast_output <- function(...) {
  args <- c(as.list(environment()), list(...))
  shape <- structure(list(Forecast = structure(list(Predictions = structure(list(structure(list(structure(list(Timestamp = structure(logical(0), tags = list(type = "string")), Value = structure(logical(0), tags = list(type = "double"))), tags = list(type = "structure"))), tags = list(type = "list"))), tags = list(type = "map"))), tags = list(type = "structure"))), tags = list(type = "structure"))
  return(populate(args, shape))
}

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paws.machine.learning documentation built on Sept. 12, 2023, 1:14 a.m.