Month: June 2017

Whinefulness, Perseveration, and the Infinite Loop

Why do people whine so much? Presumably, people whine about things they cannot control: a phenomenon, an action they must perform, or a situation they must endure, that are of an unpleasant and undesirable nature.

To me, “whining” is slightly different from “complaining,” in that whining contains an added shade of despair and futility. A complaint is actionable; a whine is useless and best ignored. Complaining is more effective, and whining is more impotent.

“Whinefulness” could be classified as an emotion, perhaps not as essential as joy, sadness, or anger, but definitely on par with resentment. In fact, whinefulness is the product of resentment.

I strive to stay away from whinefulness, both of others and of my own. It is functionless: it produces and changes nothing, transcends and transposes nothing, therefore it does not deserve my time. Repeated whining about the same issue or event without due action is an example of perseveration, a pathological behavior.

Perseveration is the repetition of a particular response (such as a word, phrase, or gesture) despite the absence or cessation of a stimulus. It is usually caused by a brain injury or other organic disorder.

This functionless behavior can be loosely described as an infinite loop, in computer science terms. Perseveration is different from Kierkegaard’s concept of repetition, which has a much broader temporal and psychological scope.

I have often found myself creating and entering infinite loops, but I have become increasingly aware of the early signs both in myself and in others. Effort must be made to prevent the creation of a loop, and boundaries must be drawn to avoid being brought into loops created by others. Upon entry, it takes more energy to exit the loop than the energy taken to create it. Since loop creation is already a waste of energy, entering the loop would result in a multiplied waste of energy.

It’s hard to believe human emotions can be reduced as such, but sometimes they can and should be.

Data Visualization Workflow

Extracted from an OpenVis presentation by Mike Bostock.

1. Prototypes should emphasize speed over polish.
Identify the intent of the prototype.
What hypothesis are you testing?
It needn’t look good, or even have labels.
Make just enough to evaluate the idea.
Then decide whether to go straight or turn.

2. Transition from exploring to refining near deadline.
Choose tools that facilitate transition to final product.

3. Clean as you go.
Be ruthless about deleting code.
You are a chef and the git repo is your kitchen.
You try twenty recipes before deciding on one.
Do you really want to clean up all the mess at the end?

4. Make your process reproducible.
Make a build-system that provides machine-readable documentation.
Accelerate the use of parts from previous projects.

5. Try bad ideas deliberately.
You can’t evaluate a visualization absent the data.
Don’t get too attached to your current favorite.
Don’t get stuck at local maximum; go down to go up.

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