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Wednesday, July 26, 2023

Barbie and math

      With the Barbie movie coming out, I think it's time to review Barbie and math.

      If the original Barbie doll were an actual woman, she would be 5'9" tall, have a 39-inch bust, 18-inch waist, 33-inch hips, a size 3 shoe, a weight of 110 pounds, a BMI of 16.24, and perhaps would be anorexic. (Click anorexic for the source of those measurements.) Obviously these measurements are unrealistic and send a harmful message to children. But there's a lot more to Barbie and math.

      In 1992 the infamous talking Barbie included the phrase "Math class is tough!" which was bad enough, but it was ironically misreported by the press as "Math is hard." Neither is the message we want to give to children. This immediately drew protests from the National Council of Teachers of Mathematics, the American Association of University Women, and others. Mattel removed the phrase from future dolls, and the original is now a collector's item.

      Perhaps embarrassed by this experience, subsequently Barbie put her life on the line in a high school project Barbie Bungie to help students learn algebra, physics, and statistics. This is a hands-on experiment attaching Barbie to a thick rubber band, dropping her from a height, measuring the distance of a jump and the time to descend, and then estimating the line of best fit. NCTM has a suggested lesson on this.

      But I want to spend the remainder of this article talking about Barbie and the mathematics of her facial beauty.

      The ancient Greeks discovered a particular number called the Golden Ratio, denoted by Greek letter Φ (phi), that has many interesting mathematical properties, apppears in some patterns of nature, and is considered by many to be asthetically pleasing. The Golden Ratio results from finding the point on a line segment that splits the segement into two smaller segments with lengths a and b, such that (a + b)/a = a/b.


      That ratio a/b is the Golden Ratio, Φ. With a little algebra, Φ = (1 + √5)/2 , which is an irrational number so it has an infinite non-repeating decimal, and rounded to three decimal places is 1.618.

      Renaissance artists, plastic surgeons, and makeup artists are among those who use Golden Ratios in various ways with faces to create ideally proportioned faces. Gary Meisner has wriiren extensively on the Golden Ratio, and he believes there are over 20 different ways that the Golden Ratio shows up in human faces and that “the Golden Ratio is also found very commonly in beautiful models of today across all ethnic groups. Biostatistican professor Dr. Kendra Schmid and her colleagues performed various measures of many faces. They began with 17 potential Golden Ratios, and they decided only six of these ratios were predictors of facial attractiveness. See Schmid.

      This takes us to Barbie. I attempted to measure these six ratios on a picture of Barbie (the doll, not the actress). There are many pictures of Barbie, she does enjoy experimenting with different hairstyles, and I had to find one with a hairstyle that gave me the best chance of measuring her from her hairline and also between her ears. The measurement is not exact for many reasons, and because we are using a two-dimensional photo of a three-dimensional object there is certainly some loss of accuracy. Nevertheless, here are the results:

Face length / Face Width1.07560
Mouth width / Interocular distance1.93750
Mouth width / Nose width1.97872
Lips to chin / Interocular1.54167
Lips to chin / Nose width1.574447
Ear length / Nose width1.57447
Average1.61374
% Deviation from Φ - 0.27%


      I have repeated this measurement process with celebrity faces that I think most people would consider attractive. (This is the sort of thing I would do.) Many celebrities have close phi-ratios such as Scarlett Johansson, Ryan Gosling, Brad Pitt, and Lupita Nyong'o, but none are as close to Φ as Barbie. Some celebrity faces that I think most people would consider attractive did not score well, but possibly this is due to the measurement difficulties I discussed above.

      However, I think the conclusion is clear: Barbie is an ideal beauty, using the Golden Ratio as a standard. But as they say, beauty is in the Phi of the beholder.



R Programming Notes:
      I attempted doing the facial measurements in R. A tip of the hat to @technocrat who helped me with some of the code. With his help, I was able to read the Barbie graphic image into R and add the image onto a ggplot with coordinate axes. I then attempted to find the coordinates of the line segments corresponding to the 6 ratios and to calculate the ratios of the appropriate line segments. See the image below with the line segments. However, drawing these segments and finding the coordinates turned out to be too crude, and the results were unreliable. I include the code below as a reference for superimposing a graphic onto a ggplot. However, I redid the measurements with more precise software using Gary Meisner's software PhiMatrix , and the results in the table above are based on that software. Nevertheless, here is the R code I used:

library(ggplot2)
library(magick)
library(grid)

# Read the barbie image
barbie <- image_read("barbie.jpg")
barbie <- image_scale(barbie, "300")

# Create a data frame for the line segments
line_data <- data.frame(
x1 = c(100, 150, 140, 138, 210, 138, 150),
y1 = c(290, 355, 302, 260, 280, 260, 275),
x2 = c(210, 150, 167, 170, 210, 138, 155),
y2 = c(290, 235, 302, 260, 310, 235, 275)
)
rownames(line_data) <- c("Face_width","Face_length","Interocular", "Mouth_width", "Lips_2_chin", "Ear_length", "Nose_width" )

# Create a ggplot
p <- ggplot() +
geom_blank() +
theme_minimal() +
theme(
plot.background = element_blank(),
panel.grid = element_blank()
) +
coord_fixed(xlim = c(0, 300), ylim = c(0, 606)) +
xlab("") +
ylab("") +
scale_x_continuous(breaks = seq(0, 300, by = 50)) +
scale_y_continuous(breaks = seq(0, 606, by = 50)) +
geom_hline(yintercept = seq(0, 606, by = 50), linetype = "dotted", color = "gray") +
geom_vline(xintercept = seq(0, 300, by = 50), linetype = "dotted", color = "gray")

# Convert the barbie image to a raster object
barbie_raster <- as.raster(barbie)

# Add the barbie image to the ggplot2 plot
p <- p +
annotation_custom(
grob = rasterGrob(barbie_raster),
xmin = 0, xmax = 300,
ymin = 0, ymax = 606
)

# Add the lines to the plot
p <- p +
geom_segment(
data = line_data,
aes(x = x1, y = y1, xend = x2, yend = y2),
color = c("red", "blue", "black", "red", "navy", "black","navy"),
size = 1.5
)
# Display the plot
print(p)

rownames(line_data) <- c("Face_width","Face_length","Interocular", "Mouth_width", "Lips_2_chin", "Ear_length", "Nose_width" )

d <- vector()
d <- sqrt((line_data$x1 - line_data$x2)^2 + (line_data$y1 - line_data$y2)^2)

Face_width <- d[1]
Face_length <- d[2]
Interocular <- d[3]
Mouth_width <- d[4]
Lips_2_chin <- d[5]
Ear_length <- d[6]
Nose_width <- d[7]
r <- vector()
r[1] <- Face_length / Face_width
r[2] <- Mouth_width / Interocular
r[3] <- Mouth_width / Nose_width
r[4] <- Lips_2_chin / Interocular
r[5] <- Lips_2_chin / Nose_width
r[6] <- Ear_length / Nose_width
m <- mean(r)
phi <- (1 + sqrt(5))/2
percent_deviation <- (m - phi)/phi




Saturday, July 22, 2023

Happy Pi Approximation Day

      Many people know March 14 is celebrated as Pi Day because 3, 1, and 4 are the first three significant digits of π (using the month, day date format). I just learned that July 22 is celebrated as Pi Approximation Day (using the day/month date format) because 22/7 is a common approximation of π .

      π Is defined as the ratio of a circle’s circumference to its diameter. π Is an irrational number (it cannot be expressed as the ratio of two integers), and it has an infinite number of non-repeating digits. Approximations of π date back to ancient civilizations and continue today as people compete to calculate π to billions of decimal places on supercomputers.

      The 22/7 approximation only matches π to the second digit after the decimal place, 3.14, and 22/7 is greater than π, a fact known by Archimedes. The error in the approximation is only about 0.04%, which is close enough for most of us.

      People also compete in the number of decimal places they can recite by memory such as using mnemonic techniques with words, where the length of each word represents a digit of π . There are many creative π mnemonics , but I am content to remember the 15 word "How I need a drink, alcoholic of course, after the heavy lectures involving quantum mechanics."

      A quite impressive feat is Apu from the Simpsons who claimed to be able to recite 40,000 digits of π, and proved it by correctly stating that the 40,000th digit is 1. Apu

      The R computer language carries 15 or 16 digits. That seems like enough. A NASA engineer says he can’t think of a practical application that would require more than 15 digits of π . NASA

      π appears in many areas of math besides geometry and trigonometry. It is hidden away in statistics where the probability density function formula of the normal curve has a √(2π) term in the denominator to get the integral equal to 1, and elsewhere in other branches of math.

      Happy Pi Approximation Day.

      Here is some R code:

library(dplyr)
library(tidytext)

# compare 15 digits of 22/7 to pi
print(22/7, digits=15)
print(pi, digits=15)

# count word length & number of words in this mnemonic
textfile <- c("How I need a drink",
"alcoholic of course",
"after the heavy lectures involving quantum mechanics.")

df<-data.frame(line=1:length(textfile), text=textfile)
df_words <- df %>% unnest_tokens(word, text) %>% mutate(word_length = nchar(word))
df_words
n <- nrow(df_words)
cat("Number of words: ", n)