garrettj403/SciencePlots

New style for USENIX and ACM

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#129 opened on Sep 23, 2024

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enhancementgood first issuehelp wanted

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Description

Are you interested in adding styles for conferences such as USENIX and ACM? I have created those styles and can push. For example:

# Matplotlib style for IEEE plots
# This style should work for most two-column journals

# Set color cycle
# Set line style as well for black and white graphs
axes.prop_cycle : (cycler('color', ['k', 'r', 'b', 'g']) + cycler('ls', ['-', '--', ':', '-.']))

# Set default figure size
figure.figsize : 3.49, 2.15
figure.dpi : 600

# Font sizes
axes.labelsize: 7
xtick.labelsize: 7
ytick.labelsize: 7
legend.fontsize: 7
font.size: 7


# Font Family
font.family: sans-serif
font.sans-serif: Arial, Helvetica, Lucida Grande, Verdana, Geneva, Lucid, Avant Garde, sans-serif

# Set line widths
axes.linewidth : 0.5
grid.linewidth : 0.5
lines.linewidth : 1.
lines.markersize: 3

# Always save as 'tight'
savefig.bbox : tight
savefig.pad_inches : 0.01  # Use virtually all space when we specify figure dimensions

text.usetex : False

fig01-usenix

Note the figure size is made as big as possible and following the golden ratio. Example output:

Contributor guide

Research direction
Review existing style files in the repository (e.g., ieee.mplstyle) to understand the format. Create new style files for USENIX and ACM based on the provided example. Ensure the styles follow the project's naming conventions and add them to the appropriate directory. Optionally, update the documentation or README to include the new styles.
Tech stack
python
Domain
data
Issue type
Feature
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
2
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
Under 1 hour
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
Fresh
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
Clear
Prerequisites
basic matplotlib knowledge
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
90