plot_exposure: Plot Training Load Exposure (ATL vs CTL)

In Athlytics: Advanced Sports Performance Analysis for 'Strava' Data

Plot Training Load Exposure (ATL vs CTL)

Description

Visualizes the relationship between Acute and Chronic Training Load.

Usage

plot_exposure(
  stoken,
  activity_type = c("Run", "Ride", "VirtualRide", "VirtualRun"),
  load_metric = "duration_mins",
  acute_period = 7,
  chronic_period = 42,
  user_ftp = NULL,
  user_max_hr = NULL,
  user_resting_hr = NULL,
  end_date = NULL,
  risk_zones = TRUE,
  exposure_df = NULL
)

Arguments

stoken	A valid Strava token from 'rStrava::strava_oauth()'. Required unless 'exposure_df' is provided.
activity_type	Type(s) of activities to include (e.g., "Run", "Ride"). Default uses common types.
load_metric	Method for calculating daily load (e.g., "duration_mins", "tss", "hrss"). Default "duration_mins". See 'calculate_exposure' for details on approximate TSS/HRSS calculations.
acute_period	Days for acute load window (e.g., 7).
chronic_period	Days for chronic load window (e.g., 42). Must be > 'acute_period'.
user_ftp	Required if 'load_metric = "tss"'. Your FTP.
user_max_hr	Required if 'load_metric = "hrss"'. Your max HR.
user_resting_hr	Required if 'load_metric = "hrss"'. Your resting HR.
end_date	Optional. Analysis end date (YYYY-MM-DD string or Date). Defaults to today.
risk_zones	Add background shading for typical ACWR risk zones? Default 'TRUE'.
exposure_df	Optional. A pre-calculated data frame from 'calculate_exposure'. If provided, 'stoken' and other calculation parameters are ignored. Must contain 'date', 'atl', 'ctl' (and 'acwr' if 'risk_zones = TRUE').

Details

Plots ATL vs CTL, optionally showing risk zones based on ACWR. Uses pre-calculated data or calls 'calculate_exposure'.

Visualizes training state by plotting ATL vs CTL (related to PMC charts). Points are colored by date, latest point is highlighted (red triangle). Optional risk zones (based on ACWR thresholds ~0.8, 1.3, 1.5) can be shaded. If 'exposure_df' is not provided, it calls 'calculate_exposure' first.

Value

A ggplot object showing ATL vs CTL.

Examples

# Example using simulated data
data(Athlytics_sample_data)
# Ensure exposure_df is named and other necessary parameters like activity_type are provided
p <- plot_exposure(exposure_df = athlytics_sample_exposure, activity_type = "Run")
print(p)

## Not run: 
# Example using real data (requires authentication)
# stoken <- rStrava::strava_oauth("YOUR_APP_NAME",
#                                "YOUR_APP_CLIENT_ID",
#                                "YOUR_APP_SECRET",
#                                cache = TRUE)

# Plot Exposure trend for Runs (last 6 months)
# plot_exposure(stoken = stoken, # Replace stoken with a valid token object
#               activity_type = "Run",
#               end_date = Sys.Date(), # For internal calculate_exposure: fetches prior data.
#               # Note: start_date applies to the internal calculate_exposure call.
#               user_ftp = 280) # Example, if load_metric = "tss"

# Plot Exposure trend for Rides
# plot_exposure(stoken = stoken, # Replace stoken with a valid token object
#               activity_type = "Ride",
#               user_ftp = 280) # Example, provide if load_metric = "tss"

# Plot Exposure trend for multiple Run types (risk_zones = FALSE for this example)
# plot_exposure(stoken = stoken, # Replace stoken with a valid token object
#               activity_type = c("Run", "VirtualRun"),
#               risk_zones = FALSE,
#               user_ftp = 280) # Example, provide if load_metric = "tss"

## End(Not run)

Athlytics documentation built on June 8, 2025, 1:11 p.m.