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CS/INFO 3300; INFO 5100
Homework 8
Due 11:59pm Wednesday, November 3
Goals: Practice using d3 to work with raster drawing functions
Your work should be in the form of an HTML file called index.html or index.htm with one

element
per problem. For this homework we will be using d3.js. In the section of your file, please
import d3 using this tag:
Create a zip file containing your HTML file and associated data files (i.e. movie_barcodes.json) and
upload it to CMS before the deadline. Submissions that do not include data files may be penalized.
Your submission will be graded using a Python web server run in a parent directory containing your
zip file contents along with many other students’ submissions.
1. In this assignment, you will create a series of movie barcodes using elements. A barcode
uses vertical lines to show the average color of individual frames of a film, helping to reveal how color
is used by cinematographers to give flavor to a film. This has been a popular subject of online
visualization blogs, to the extent that some have even made publicly available tools for generating
them. For this assignment you'll be taking a simpler approach compared to these tools. Your end
barcodes will look exactly like this:

(next page)


We have generated a movie barcode dataset for an eclectic set of 29 films, movie_barcodes.json.
The dataset contains a list of Objects, one for each movie barcode. The relevant properties in each
of the barcode Objects are:
{
title: a _string_ identifying the title of the movie
bars: a _list_ of individual color bars, used to fill the barcode’s canvas
[ {
color: a hexadecimal color _string_ for that specific color bar
x: the x integer position of this specific color bar
} …
]
}
You will find 800 individual bars inside of each movie’s bars list. Your eventual elements
will be 800 pixels in width. This means that you will have a single 1px wide vertical bar for each item
in the bars array. You’ll have 29 individual elements, one for each movie Object.
There are any number of ways to solve this assignment. For class purposes, we will pick the
simplest path that does not involve data joins and instead just uses simple loops. You are welcome
to use joins if you are confident that you can solve the problem. You will have a choice between
two different methods for modifying your canvas. While we suggest that you use the array method,
the line method will deliver identical results.




(next page)








( TECHNICAL DATASET DETAILS (feel free to ignore): The dataset was generated by sampling 400
frame images from each movie file. They were sampled evenly over the duration of the film (i.e.
total_frames / 400 ). For each of those individual frame images, there are any number of strategies
for finding the dominant or average color. Though we tried RGB, LAB, and even K-means
clustering, averaging XYZ colors gave the nicest looking results. Within each image, we converted
each RGB pixel into the XYZ color coordinate space. We then computed the average XYZ value for
all the pixels. That was then converted back into a hexadecimal RGB color for use in the dataset. To
obtain 800 individual bars, each of the 400 frames was duplicated, making thicker barcode lines. )

Procedure:
A. Begin by creating an asynchronous function and importing the dataset, movie_barcodes.json,
using d3.json and await. Make sure that you call your async function.
B. In your HTML, create a

element that will contain all of your barcodes
(e.g.
)
C. Now iterate through each of the movie Objects in movie_barcodes using a forEach loop.
-- D. For each of the movies, create a new
element to hold that movie’s title and canvas.
Add an
element inside of the new
containing the movie’s title (hint: use .text() )
Add a new element inside of the new
. Set its width to 800 and height to 100.
-- E. Obtain a drawing context for the new .
You now have two choices for how to draw the barcode onto the movie canvas:
-- -- Option A. Draw vertical lines for each of the bars
Using a nested forEach loop, begin iterating through the bars array
For each of the bars, set the strokeStyle of the drawing context to the bar’s color
For each of the bars, use the context to draw a vertical line from top to bottom.
To determine the x-position of the bar, refer to the bar’s x property and add 0.5 to it.
( We add 0.5 so that the 1px wide line properly fills that column of pixels. )
( If the bars appear to be very light in color, you forgot to add 0.5 )
-- -- Option B. Manually manipulate the pixel array
Use the getImageData function on the drawing context to get an array of canvas pixels
Using a nested forEach loop, iterate through the bars array within the movie Object.
For each bar, get a hexadecimal color string from its color property. Use the following code
to compute r, g, and b values from the hex color string:
let num = parseInt(color.replace('#',''), 16);
let r = (num >> 16) & 255;
let g = (num >> 8) & 255;
let b = num & 255;
Get the x-position for this bar using the bar’s x property
Using a nested for loop, iterate from 0 to 100. This will become your y value.
Within that loop, use array operations to set the pixel array’s r, g, and b values for each
(x, y) position. This will fill in each bar pixel-by-pixel
( hint: this approach has three nested loops: one looping through movies, another
through bars, and a final one looping through pixels from 0 to 100 )
Finally, use putImageData to paste your pixel array onto each canvas


REFERENCE:

index.html should look something like this before your code runs:




#1



( This is where content will be added )









index.html should look something like this after your code runs:




#1




Aladdin





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