https://github.com/emilydolson/evo_in_space

Figures, scripts and data for paper "Spatial resource heterogeneity creates local hotspots of evolutionary potential"
https://github.com/emilydolson/evo_in_space

avida biodiversity evolution evolutionary-computation spatial-data-analysis

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Figures, scripts and data for paper "Spatial resource heterogeneity creates local hotspots of evolutionary potential"

• Host: GitHub
• URL: https://github.com/emilydolson/evo_in_space
• Owner: emilydolson
• License: mit
• Created: 2016-12-06T19:46:54.000Z (almost 9 years ago)
• Default Branch: master
• Last Pushed: 2018-02-25T06:34:14.000Z (over 7 years ago)
• Last Synced: 2024-01-30T05:33:44.611Z (over 1 year ago)
• Topics: avida, biodiversity, evolution, evolutionary-computation, spatial-data-analysis
• Language: TeX
• Homepage:
• Size: 11.5 MB
• Stars: 1
• Watchers: 3
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.md

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README

          
This repository contains figures, scripts, and data for the paper:

# Spatial resource heterogeneity creates local hotspots of evolutionary potential

By Emily Dolson and Charles Ofria

European Conference on Artificial Life, 2017

![](figs/50065_all_hotspots.png)

[![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](https://opensource.org/licenses/MIT)

[![Paper:10.7551/ecal_a_023](https://img.shields.io/badge/DOI-10.7551%2F978‐0‐262‐33936‐0‐ch071-green.svg)](http://cognet.mit.edu/proceed/10.7551/ecal_a_023)

## Contents:

- *hotspots.tex* -  LaTeX file for main paper

- *alifeconf.sty* - Style file for ECAL

- *Zotero.bib* - bibliography file for paper

- *config* - contains all files used to generate daa

  - *avida* - executable used to generate data

  - *avida-lineage* - executable used to output lineage trajectories

  - *avida.cfg* - config file for Avida (not changed from default)

  - *defaults-heads.org* - starting organism (not changed from default)

  - *env500XX.cfg* - these files indicate how to build the 8 different environments

  - *envcontrol.cfg* - file to specify the homogeneous control environment

  - *events.cfg* - tells Avida what data to output when

  - *corner_events.cfg* - events file that puts starting organism in oppostie corner

  - *instset-heads.cfg* - tells avida what instruction set to use (not changed from default)

  - *lineage_events.cfg* - events file for runs where spatial lineage is being output

  - *write_events_file.py* - python script to make events file that only prints phenotype grid immediately before a new task is going to evolve (assumes that extract_points.py has already been called to determine when each task will evolve)

- *data* - contains summary-level data files extracted from raw data (raw data would be too large too include)

  - *all_task_locs.csv* - the locations where each task first evolved in each run

  - *control_diversity_ranks.csv* - the percentile of the diversity of the cell where each task first evolved in each replicate of the control condition

  - *diversity_ranks.csv* - the percentile of the diversity of the cell where each task first evolved in each replicate of the experimental conditions

  - *qsub_files* - all of the scripts used to submit experiments to MSU's high performance compupting cluster

- *figs* - figures

  - *50060_9_paths.png* - all lineage paths for task 9 in environment 50060 (not very useful - there are too many)

  - *50065_all_hotspots.png* - all hotspots across all environments

  - *9_50013_density.png* - kernel density map for task 9 in environment 50013

  - *9_50013_hotspots.png* - hotspot locations for task 9 in environment 50013

  - *9_50013_k-hat.png* - Ripley's K for task 9 in environment 50013

  - *9_50013_points.png* - point locations for task 9 in environment 50013

  - *control_9_paths.png* - 5 example lineage paths for task 9 for each environment

  - *localdiversity.png* - qqplot comparing diversity ranks to uniform distribution

  - *statsfig.png* - diagram outlining statsitics pipeline

  - *statsfig_horizontal_1col.png* - smaller version of the stats pipeline figure that fits in 1 column

- *scripts* - Python and R scripts for processing and analyzing data

  - *collect_points.py* - grab data from task_locs.csv files for each rep and summarize them into all_task_locs.csv

  - *draw_hotspots.py* - can be used to make various figures showing points, hotspots, and lineage paths over an environment

  - *env500XX.csv* - files generated by extract_env_data.py that indicate distance from each cell in each environment to each resource

  - *envcontrol.csv* - like above, except it's all 0s

  - *extract_diversity.py* - generate diversity_ranks.csv file from raw phenotype grids

  - *extract_env_data.py* - generate csv files indicating the distance from each cell in an environment to each resource

  - *extract_grids.py* - grab phenotype grids from right before each task evolves out of tar archives

  - *extract_paths.csv* - convert sequence of ints output by avida-lineage into actual sequences of coordinates and environments that a lineage passed through

  - *extract_points.csv* - loop through phenotype grids to figure out when each task first appears (generates task_locs.csv)

  - *kriging.R* - R script that handles all of the regression that we used in an attempt to figure out what causes hotspots

  - *make_diversity_maps.csv* - makes heat maps of local diversity for updates immediately before tasks evolved

  - *make_hotspot_figure.py* - variant on draw_hotspots.py, used to make multi-panel hotspot figure in paper

  - *make_path_figure.py* - variant on draw_hotspots.py used to make multipanel path figure in paper