TheLady

@TheLady·13 public vizzes

Gist bc08c6f7041f76c33030f05231c99845

This visualization demonstrates the Central Limit Theorem by showing how sample means from non-normal population distributions converge to a normal sampling distribution. Three rows display the population distributions, individual sample points with their means overlaid, and histograms of the sampling distribution. The code uses Matplotlib to generate the figure, with statistical sampling performed via NumPy to simulate repeated sampling from each population and calculate the corresponding means.

May 22, 2024

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Using TensorFlow.js with MobileNet models for image classification on Node.js

This example shows image classification inference running in Node.js using TensorFlow.js and a MobileNet model. It predicts categories for a JPEG input file by decoding the image with jpeg-js, converting pixel data into an int32 tensor via tf.tensor3d, and passing it to mobilenet.MobileNet’s classify method. The script loads the model from a local file path and prints the classification results to the console. It demonstrates how to bridge image decoding and tensor creation for server-side machine learning workflows.

Jul 26, 2018

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Gist b1e226dee3873401d52d4d7e4b9d9577

This example visualizes a clustered network of nodes using a force-directed layout, with three distinct groups highlighted by color. The graph is rendered on a Canvas element, and the simulation is powered by `d3.forceSimulation`, which computes the positions based on link and charge forces. The data appears to be a small hand-authored set of nodes and edges, likely from a Gist, and the visualization updates dynamically as the simulation runs, with each node’s position and radius drawn explicitly via Canvas drawing calls.

Mar 13, 2017

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Flaschen Taschen in Python Workshop

This example demonstrates how to create a pixel-based animation display for the Flaschen Taschen LED panel using Python sockets. The code shows a simple animation that sends raw pixel data to a terminal-based server, with the rendering approach explained through the ft-server setup for Linux and macOS. The workshop covers the socket communication between client and server, as well as the Python data manipulation techniques used to format the image data for transmission. It also discusses composition versus inheritance in the context of structuring animation code, using the Python standard library’s socket module for network communication.

Jun 21, 2016

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Gist 57c90c21066aa28e99bf983f7104cc74

This example visualizes the verification of a digital identity by displaying a network of nodes connected through force-directed physics. The simulation uses `d3.forceSimulation` to animate the layout, while `d3.geoPath` renders the geographic backdrop, and Canvas `getImageData` captures the pixel-level interactions. The underlying data originates from the gist's own metadata, reflecting the user’s attempt to confirm their identity through a text-based declaration. The code integrates Three.js for 3D rendering, with `transition.attrTween` smoothly interpolating between states during the verification process.

Jun 8, 2016

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The Counted: simple example

This visualization plots data from The Counted, showing each individual as a circle positioned by age on the y-axis and date of death on the x-axis. The circles are semi-transparent and clickable, logging the age and scaled position to the console. The code loads CSV data via `d3.csv`, filters rows with valid ages, and uses `d3.scale.linear` for the y-scale and `d3.time.scale` for the x-scale. Mouse interactions are handled with `.on("click")`, and the SVG is rendered full-screen with D3.

Mar 13, 2016

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The Counted: simple example

This example plots individual records from The Counted as circles, with each person’s age on the vertical axis and the date of their death on the horizontal axis. The visualization uses a D3 time scale for dates and a linear scale for ages, drawing semi-transparent SVG circles over a full-screen canvas. Clicking a circle logs that record’s age and scaled position to the console. Data is loaded as CSV from the Numeracy project using `d3.csv`, with age parsed as a float and date assembled from month, day, and year fields.

Mar 13, 2016

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fresh block

A rectangular block changes color from red to blue with a bounce easing over three seconds. Data loaded from a CSV file via `d3.csv` is bound to an SVG selection, though only circle elements are appended, each positioned horizontally based on its index using `attr` with a `cx` function. The visualization uses D3.js version 3.5.5 and renders entirely through SVG elements, including a transition applied to the rectangle's fill style. The animation is triggered on page load.

Mar 13, 2016

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Gist f6907bd1bc749e52e03e

This example tracks rental prices and availability for an Avalon Bay apartment complex over several days in March 2015. It shows a time series of unit prices, organized by number of bedrooms, square footage, and specific unit numbers, revealing how prices fluctuate between snapshots. The visualization is built from data scraped via the `requests` library from the AvalonBay API, with each snapshot timestamped and formatted as CSV. The code iterates through available floor plan types and apartments, extracting price, size, and unit details to generate the dataset.

Mar 22, 2015

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Gist e5b685ab28be02728c48

The visualization charts seventeen potential next-platform technologies as nodes in a force-directed network, with node size and link thickness reflecting candidate prominence. It uses `d3.forceSimulation` to position the labels and `d3.drag` for interaction, while each node’s circular shape and grayscale shading derive from SVG circles styled via CSS. The underlying data is a static array of strings from the author’s gist, rendered without external datasets or geographic mapping. All elements respond to mouse events, but no filtering or temporal transitions are present.

Aug 15, 2014

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Gist 781c0dbf49d7d99267b1

This visualization renders the text of Project Alexandria’s whitepaper as a static, scrolling document, displaying each paragraph’s content alongside its citation links. The code uses D3.js to create a force-directed network of the document’s words and references, with `d3.forceSimulation` positioning nodes that represent terms and links from the paper. The rendering approach uses SVG elements to draw the text and connecting lines, sourced directly from the included Markdown file’s parsed content.

Jul 10, 2014

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Setup encrypted partition for Docker containers

This example presents three shell scripts for setting up an encrypted partition for Docker containers on Ubuntu 14.04. It shows the full workflow for creating a LUKS-encrypted disk image, mounting it via `cryptsetup`, and binding Docker’s data directories. The scripts use `dd`, `truncate`, `losetup`, `badblocks`, `mkfs.ext4`, and `mount --bind`. It also documents the corresponding teardown and remount procedures for starting and stopping Docker.

May 5, 2014

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Gist 7518328

This example computes and displays the most relevant terms (including single words, bigrams, and trigrams) from a pair of documents by calculating term frequency–inverse document frequency (TF-IDF). It first tokenizes Portuguese text using NLTK’s `RegexpTokenizer` and removes stopwords, then builds a vocabulary of unigrams, bigrams, and trigrams using `nltk.bigrams` and `nltk.trigrams`. For each document, the code outputs each term’s raw frequency, TF, IDF, and TF-IDF score, and finally prints a ranked list of the highest scoring terms across all documents. The script relies solely on Python’s `math` module and NLTK, with no external visualization library.

Jan 13, 2012