Introduction

In data modeling there can be instanes where you will want some sort of hyperbolic transformation of your data. In {healthyR.ai} this is easy with the use of the function hai_hyperbolic_vec() along with it’s corresponding augment and step functions.

Function

The function takes in a numeric vector as it’s argument and will transform the data with one of the following:

sin
cos
tan
sincos This will do: value = sin(x) * cos(x)

The full function call is:

hai_hyperbolic_vec(.x, .scale_type = c("sin", "cos", "tan", "sincos"))

Example

library(dplyr)
library(healthyR.ai)
library(tidyr)
library(ggplot2)

len_out <- 25
by_unit <- "month"
start_date <- as.Date("2021-01-01")

data_tbl <- tibble(
  date_col = seq.Date(
    from = start_date, 
    length.out = len_out, 
    by = by_unit
    ),
  b = runif(len_out),
  fv_sin = hai_hyperbolic_vec(b, .scale_type = "sin"),
  fv_cos = hai_hyperbolic_vec(b, .scale_type = "cos"),
  fv_sc  = hai_hyperbolic_vec(b, .scale_type = "sincos")
)

data_tbl

# A tibble: 25 × 5
   date_col        b fv_sin fv_cos  fv_sc
   <date>      <dbl>  <dbl>  <dbl>  <dbl>
 1 2021-01-01 0.961  0.820   0.573 0.470 
 2 2021-02-01 0.418  0.406   0.914 0.371 
 3 2021-03-01 0.0729 0.0728  0.997 0.0726
 4 2021-04-01 0.426  0.413   0.911 0.376 
 5 2021-05-01 0.851  0.752   0.659 0.496 
 6 2021-06-01 0.824  0.734   0.679 0.499 
 7 2021-07-01 0.659  0.612   0.791 0.484 
 8 2021-08-01 0.683  0.631   0.776 0.490 
 9 2021-09-01 0.173  0.172   0.985 0.169 
10 2021-10-01 0.345  0.338   0.941 0.318 
# … with 15 more rows

Visual

data_tbl %>% 
  pivot_longer(cols = -date_col) %>% 
  ggplot(aes(x = date_col, y = value, color = name)) + 
  geom_line() + 
  facet_wrap(~ name, scales = "free") +
  theme_minimal() +
  labs(color = "")