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## ---- include=FALSE, echo=FALSE------------------------------------------
knitr::opts_chunk$set(fig.width = 7, fig.height = 5)
options(digits = 2)
## ---- echo=FALSE---------------------------------------------------------
library(cycleRtools)
## ---- fig.height = 10----------------------------------------------------
plot(x = intervaldata, # "x" is the data, for consistency with other methods.
y = 1:3, # Which plots should be created? see below.
xvar = "timer.min", # What should be plotted on the x axis?
xlab = "Time (min)", # x axis label.
laps = TRUE, # Should different laps be coloured?
breaks = TRUE) # Should stoppages in the ride be shown?
## ------------------------------------------------------------------------
## Zoom to 0-50 minutes.
plot(intervaldata, y = 3, xvar = "timer.min", xlim = c(0, 50))
## ------------------------------------------------------------------------
zone_time(data = intervaldata,
column = power.W, # What are we interested in?
zbounds = c(100, 200, 300), # Zone boundaries.
pct = FALSE) / 60 # Output in minutes.
## How about time above and below CP, as a percentage?
## NB: column = power.W is the default.
zone_time(intervaldata, zbounds = 310, pct = TRUE)
## ------------------------------------------------------------------------
zdist_plot(data = intervaldata,
binwidth = 10, # 10 Watt bins.
zbounds = c(100, 200, 300), # Zone boundaries.
xlim = c(50, 400)) # Zoom to 50-400 Watts.
## ------------------------------------------------------------------------
summary(intervaldata)
## ------------------------------------------------------------------------
times_sec <- 2:20 * 60 # 2-20 minutes.
prof <- mmv(data = intervaldata,
column = power.W, # Could also use speed.kmh.
windows = times_sec)
print(prof)
## ------------------------------------------------------------------------
hypm <- lm(prof[1, ] ~ {1 / times_sec}) # Hyperbolic model.
## Critical Power (Watts) and W' (Joules) estimates
hypm <- setNames(coef(hypm), c("CP", "W'"))
print(hypm)
## Plot with the inverse model overlaid.
plot(times_sec, prof[1, ], ylim = c(hypm["CP"], max(prof[1, ])),
xlab = "Time (sec)", ylab = "Power (Watts)")
curve((hypm["W'"] / x) + hypm["CP"], add = TRUE, col = "red")
abline(h = hypm["CP"], lty = 2)
legend("topright", legend = c("Model", "CP"), bty = "n",
lty = c(1, 2), col = c("red", "black"))
## ------------------------------------------------------------------------
ms <- Pt_model(prof[1, ], times_sec)
print(ms)
plot(times_sec, prof[1, ], ylim = c(hypm["CP"], max(prof[1, ])),
xlab = "Time (sec)", ylab = "Power (Watts)")
## Showing an exponential model, as it best fits these data.
curve(ms$Pfn$exp(x), add = TRUE, col = "red")
## ---- fig.height=3-------------------------------------------------------
library(leaflet)
leaflet(intervaldata) %>% addTiles() %>% addPolylines(~lon, ~lat)
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