Construct Consonance Functions from Snowflake Query Results

Source: R/curve_snowflake.R

Connects to a Snowflake database and constructs consonance distributions from query results containing point estimates and confidence intervals.

curve_snowflake(conn, query, estimate_col = "estimate",
  lower_col = "lower", upper_col = "upper", conf.level = 0.95,
  steps = 1000, cores = getOption("mc.cores", 1L), table = TRUE)

Arguments

conn

A DBI connection object to Snowflake database.

query

SQL query string that returns columns for estimate, lower, and upper bounds.

estimate_col

Name of the column containing point estimates. Default is "estimate".

lower_col

Name of the column containing lower bounds. Default is "lower".

upper_col

Name of the column containing upper bounds. Default is "upper".

conf.level

Confidence level of the input intervals. Default is 0.95.

steps

Number of consonance levels to compute. Default is 1000.

cores

Number of cores for parallel computation.

table

Logical. If TRUE (default), includes a summary table.

Value

A list with class "concurve" containing the intervals dataframe, density dataframe, and optionally a summary table.

Details

This function requires the DBI and odbc packages to be installed. It connects to Snowflake, executes the provided query, and constructs consonance functions from the results.

See also

curve_snowflake_batch() for batch processing

curve_rev() for constructing curves from published intervals

export_for_powerbi() for exporting results

Examples

if (FALSE) { # \dontrun{
library(DBI)
library(odbc)

# Connect to Snowflake
conn <- dbConnect(odbc::odbc(),
  Driver = "Snowflake",
  Server = "your_account.snowflakecomputing.com",
  Database = "your_database",
  Schema = "your_schema",
  UID = "your_username",
  PWD = "your_password"
)

# Query with estimate and CI columns
query <- "SELECT estimate, lower_ci, upper_ci FROM results WHERE analysis_id = 1"
result <- curve_snowflake(conn, query,
  estimate_col = "estimate",
  lower_col = "lower_ci",
  upper_col = "upper_ci"
)

ggcurve(result[[1]], type = "c")

dbDisconnect(conn)
} # }