Probe Profile

probe_profile simulates the vertical jump profiling using vj_profile over external_load loads, but estimate which parameter brings biggest change in the profile summary metric returned by profile_func. This is done by keeping all parameters at initial value, while changing only one parameter. This is then repeated for all parameters. This way we can answer by changing what parameter for standardize change (change_ratio) yield biggest change in profile summary metric (e.g. jump height)

probe_profile(
  mass = 75,
  push_off_distance = 0.4,
  max_force = 3000,
  max_velocity = 4,
  time_to_max_activation = 0.3,
  change_ratio = seq(0.9, 1.1, length.out = 3),
  aggregate = "raw",
  external_load = c(-40, -20, 0, 20, 40, 60, 80, 100),
  profile_func = get_all_profiles,
  ...
)

Arguments

mass	Numeric value. Initial parameter value to be changed using change_ratio.
push_off_distance	Numeric value. Initial parameter value to be changed using change_ratio
max_force	Numeric value. Initial parameter value to be changed using change_ratio
max_velocity	Numeric value. Initial parameter value to be changed using change_ratio
time_to_max_activation	Numeric value. Initial parameter value to be changed using change_ratio
change_ratio	Numeric vector indicating probing change ratios
aggregate	How should get_all_profiles output be aggregated? Default is "raw". Other options involve "ratio" and "diff" which use initial output values
external_load	Numeric vector. Default is c(-40, -20, 0, 20, 40, 60, 80). Forwarded to vj_profile
profile_func	Profiling function. Default is get_all_profiles. Also use get_FV_profile, get_power_profile, and get_all_samozino_profiles
...	Extra argument forwarded to vj_profile

Value

Probing data frame

Examples

require(tidyverse)

# You call also use get get_all_samozino_profiles() function in the profile_func parameter
profile_probe_data <- probe_profile(
  mass = 75,
  max_force = 3000,
  max_velocity = 3,
  time_to_max_activation = 0.3,
  time_step = 0.001,
  external_load = c(-40, -20, 0, 20, 40, 60, 80, 100),
  profile_func = get_all_profiles # Can also use get_all_samozino_profiles
)

plot_data <- gather(profile_probe_data, key = "variable", value = "value", -(1:8)) %>%
  filter(variable %in% c(
    "profile_mean_FV.F0",
    "profile_mean_FV.V0",
    "profile_mean_FV.Pmax",
    "profile_mean_FV.Sfv",
    "profile_mean_power.Pmax",
    "profile_mean_power.Pmax_location",
    "profile_mean_power.F0_perc"
  ))

ggplot(plot_data, aes(x = change_ratio, y = value, color = probing)) +
  theme_minimal() +
  geom_line() +
  facet_wrap(~variable, scales = "free_y") +
  xlab("Normalized parameter change") +
  ylab(NULL)

# -----------------------------------
# When probing using get_FV_profile or get_power_profile use the following
power_probe_data <- probe_profile(
  mass = 75,
  max_force = 3000,
  max_velocity = 3,
  time_to_max_activation = 0.3,
  time_step = 0.001,
  external_load = c(-40, -20, 0, 20, 40, 60, 80, 100),
  profile_func = function(...) list(list = get_power_profile(...))
)