Check for gaps in date sequence

Description

Check for gaps in date sequence

Usage

check_date_continuity(dates)

Arguments

Value

A data frame with gap information, or NULL if no gaps

Check for extreme values in weather columns

Description

Check for extreme values in weather columns

Usage

check_extreme_values(data, key_cols, temp_range, radn_range, rain_range)

Arguments

Value

A data frame of rows with extreme values, or NULL if none found

Check for missing values in key columns

Description

Check for missing values in key columns

Usage

check_missing_values(data, key_cols)

Arguments

Value

A data frame with missing value counts, or NULL if no missing values

Check weather records for data quality issues

Description

This function validates weather records for:

• Continuous weather data (no gaps in dates)

• No missing values in key columns (mint, maxt, radn, rain)

• No extreme values (e.g., less than -100 or above 100 for temperature, less than 0 for radiation and rain)

• Latitude and longitude columns exist and contain a single non-NA value for all records

Usage

check_weather(
  data,
  key_cols = c("mint", "maxt", "radn", "rain"),
  temp_range = c(-100, 100),
  radn_range = c(0, 50),
  rain_range = c(0, 500),
  stop_on_error = FALSE
)

Arguments

Value

If stop_on_error is FALSE, returns a list with the following components:

If stop_on_error is TRUE and issues are found, the function stops with an error message.

Examples

file <- system.file("extdata/ppd_72150.met", package = "tidyweather")
records <- read_weather(file)
result <- check_weather(records)
if (result$is_valid) {
  print("Weather data passed all quality checks")
} else {
  print(result)
}

The time elapsed in hours between the specified sun angle from 90 degree in am and pm. +ve above the horizon, -ve below the horizon.

Description

The time elapsed in hours between the specified sun angle from 90 degree in am and pm. +ve above the horizon, -ve below the horizon.

Usage

day_length(doy, lat, angle = -6)

Arguments

Value

day length in hours

Interpolate 3-Hourly Temperature Values using sine curve.

Description

Interpolates temperature values at 3-hourly intervals from daily minimum and maximum temperatures using a sine curve.

Usage

interpolate_3hr(mint, maxt)

Arguments

Value

A numeric matrix of interpolated 3-hourly temperature values. Rows correspond to input minimum and maximum temperatures and columns correspond to the eight interpolated 3-hourly intervals.

Examples

mint <- c(0, 10)
maxt <- c(30, 40)
interpolate_3hr(mint = mint, maxt = maxt)

Return a y value from a linear interpolation function

Description

Return a y value from a linear interpolation function

Usage

interpolation_function(x, y, values, split = "\\s+")

Arguments

Value

The interpolated values

Calculate the last frost day

Description

This function calculates the last frost day from a numeric vector of daily minimum temperatures using tidyverse principles.

Usage

last_frost_day(
  .data,
  threshold = weather_options$get("extreme.frost_threshold"),
  hemisphere = "south",
  require_full_year = weather_options$get("require_full_year")
)

Arguments

Value

An data.frame or tibble representing the day of year for the last frost, or NA if no frost occurs

Examples

file <- system.file("extdata/ppd_72150.met", package = "tidyweather")
records <- read_weather(file)
records |>
    dplyr::group_by(year) |>
    last_frost_day(require_full_year = FALSE)

Calculate the number of frost days

Description

This function calculates the number of frost days from a numeric vector of daily minimum temperatures using tidyverse principles.

Usage

number_frost_day(
  .data,
  threshold = weather_options$get("extreme.frost_threshold"),
  require_full_year = weather_options$get("require_full_year")
)

Arguments

Value

An data.frame or tibble representing the number of frost days, or 0 if no frost occurs

Examples

file <- system.file("extdata/ppd_72150.met", package = "tidyweather")
records <- read_weather(file)
records |>
    dplyr::group_by(year) |> 
    number_frost_day(require_full_year = FALSE)

Read weather records from a file list and/or a folder list

Description

Read weather records from a file list and/or a folder list

Usage

read_weather(file, format = "APSIM", ...)

Arguments

Value

A data.frame which contains all weather data.

Examples

file <- system.file("extdata/ppd_72150.met", package = "tidyweather")
records <- read_weather(file)
head(records)

Summarise Weather Extremes and Key Indicators

Description

This function calculates summary metrics for weather data, including the number of frost days and the last frost day, grouped by one or more grouping variables. The function uses package-wide options for thresholds and year completeness.

Usage

summarise_weather(.data)

Arguments

Details

The function retrieves thresholds and settings from the global tidyweather options via weather_options$get(). The default frost threshold is weather_options$get("extreme.frost_threshold") and require_full_year is weather_options$get("require_full_year"). These can be changed using weather_options$set().

This function is designed to work with grouped tibbles (e.g., after dplyr::group_by()), applying the summary per group.

Value

A tibble with one row per group, containing the following columns:

number_frost_days

Number of days where minimum temperature is below the frost threshold.

last_frost_day

The day of year of the last frost (or NA if none).

Examples

library(dplyr)

# Example weather data (daily minimum temperatures)
weather_data <- read_weather(system.file("extdata/ppd_72150.met", package = "tidyweather"))

# Summarise without grouping
weather_options$set("require_full_year" = FALSE)
summarise_weather(weather_data)

# Summarise by group (e.g., year)
weather_data_grouped <- weather_data %>% group_by(year)
summarise_weather(weather_data_grouped)

Calculate thermal time using cardinal temperatures

Description

Calculate thermal time using cardinal temperatures

Usage

thermal_time(mint, maxt, x_temp, y_temp, method = NULL)

Arguments

Value

The thermal time.

Examples

mint <- c(0, 10)
maxt <- c(30, 40)
x_temp <- c(0, 20, 35)
y_temp <- c(0, 20, 0)
thermal_time(mint, maxt, x_temp, y_temp)
thermal_time(mint, maxt, x_temp, y_temp, method = '3hr')

Significantly t-test with auto-correlation for time serial data

Description

Method is presented by Santer et al. 2000

Usage

ttest_ts(y, slope = NULL)

Arguments

Value

p values of t-test

tidyweather options

Description

An options manager for configuring tidyweather parameters. This object provides methods to get and set weather-related parameters.

Usage

weather_options

Format

An object of class list of length 3.

Available Options

extreme.frost_threshold

Frost threshold for extreme weather events. Default: 0

require_full_year

Whether to require a full year of data for certain calculations. Default: TRUE

Methods

get(key)

Retrieve the value of an option by its key (e.g., "extreme.frost_threshold")

set(key, value)

Set the value of an option by its key

reset()

Reset all options to their default values

Examples

# Get default frost threshold
weather_options$get("extreme.frost_threshold")

# Set custom values
weather_options$set("extreme.frost_threshold" = -2)

# Reset to defaults
weather_options$reset()

Write weather data to file

Description

Exports weather records to a file in the specified format. Currently supports APSIM format for agricultural modeling applications.

Usage

write_weather(records, file, format = "APSIM", overwrite = FALSE)

Arguments

Value

Invisibly returns the file path of the written file

Examples

# Read sample weather data from package
file <- system.file("extdata/ppd_72150.met", package = "tidyweather")
records <- read_weather(file)

# Write to temporary file
temp_file <- tempfile(fileext = ".met")

# Write to APSIM format
write_weather(records, temp_file, format = "APSIM")

# Overwrite existing file
write_weather(records, temp_file, format = "APSIM", overwrite = TRUE)