Data from: A comparison of image statistics of peacock jumping spider colour patterns and natural scenes
Data files
May 06, 2025 version files 2.43 GB
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imageSets.mat
2.13 GB
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Maratus.zip
191.42 MB
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Natural_Scenes.zip
106.24 MB
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README.md
10.02 KB
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salticidVirtualFilters_530nm_5realFilters.mat
221 B
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salticidVirtualFilters_530nm_6realFilters.mat
228 B
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spectralSlopesMaratus.txt
10.25 KB
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spectralSlopesNaturalScenes.txt
4.80 KB
Abstract
The form of arbitrary sexual signals may be driven by the need to be detectable against the background or, alternatively, by selection for efficient processing by the nervous system. This latter alternative is a prediction of the sensory drive hypothesis extended to include efficient coding as a driver of the form of sexual signals. This hypothesis posits that animal visual systems are adapted to process the visual statistics of natural scenes, and that easily-processed stimuli induce a sensation of pleasure in the viewer. In support of this, natural scene statistics have been found to be preferred not only by humans, but by the peacock spider Maratus spicatus. Here we test if male peacock spiders of the highly sexually dimorphic Maratus genus generally (a) evolve colour patterns with image statistics that contrast with the natural background or (b) exploit a potential processing bias by evolving colour patterns with visual statistics similar to those of natural scenes. We analyse and compare multispectral images of male and female spiders of 21 Maratus species and of natural scenes similar to the spiders’ habitat. We find that the image statistics of male patterns diverge from those of natural scenes, whereas the statistics of female patterns do not. Our results support the idea that colour patterns evolve contrasting image statistics to increase conspicuousness and matching image statistics to be camouflaged. Any processing bias for natural scene image statistics in Maratus thus appears to play little role in the evolution of their sexual signals.
- Author: Marie-Christin Hardenbicker
- Other contributors: Joseph Schubert, Cynthia Tedore
- Date created: 2025-02-19
Data and File Overview
Table of Contents
File format: .txt
- spectralSlopesMaratus.txt
- spectralSlopesNaturalScenes.txt
- In Maratus.zip:
- Data for Further Analysis contains 403 .txt files
- In Natural Scenes.zip:
- Data for Further Analysis contains 123 .txt files
File format: .mat (Matlab structure/table)
- imageSets.mat
- salticidVirtualFilters_530nm_5realFilters.mat
- salticidVirtualFilters_530nm_6realFilters.mat
File format: .m (Matlab script)
In Functions.zip:
- circularWindow.m
- prepMatFileNoMask.m
- remGam.m
- rotateAndCenter.m
- round2even.m
- squareCrop.m
- developImgsAndFourierTransform.m
File format: .png
In Maratus.zip:
- Images for Viewing on Digital Display contains 145 .png files
- Images Edited for Fourier Transform contains 145 .png files
- Fourier Plots 145 .png files
In Natural Scenes.zip:
- Images for Viewing on Digital Display contains 41 .png files
- Images Edited for Fourier Transform contains 41 .png files
- Fourier Plots 41 .png files
File format: .Rmd (R notebook)
- statisticalAnalysis.Rmd
Relationships between files/folders/code:
File sets provided before running code
- imageSets.mat
- salticidVirtualFilters_530nm_5realFilters.mat
- salticidVirtualFilters_530nm_6realFilters.mat
- Functions.zip
Code
- developImgsAndFourierTransform.m
- statisticalAnalysis.Rmd
Files/Folders created by developImgsAndFourierTransform.m
- spectralSlopesMaratus.txt
- spectralSlopesNaturalScenes.txt
- Maratus
- Natural Scenes
- Recommended software/tools: Matlab R2024a; R version 4.4.1
File/Folder/Code Details
Details for: spectralSlopesMaratus.txt
- Description: Includes the calculated spectral slopes for Maratus.
- Format(s): .txt, decimal separator = '.'
- Size(s): 10 KB
- Dimensions: 145 rows x 10 columns
- Variables:
- channel: spectral sensitivity of the channel that has been analysed (in nm)
- species: species of Maratus
- id: ID of the animal
- sex: is the animal male, female or juvenile
- extension_tube: size of the extension tube used in mm
- slope: spectral slope calculated from multispectral image
- hf: highest spatial frequency that was analysed
- lf: lowest spatial frequency analysed
- N: size of the squared image (one dimension) in pixels
- Rsqrds: goodness of fit R^2 of the linear model
Details for: spectralNaturalScenes.txt
- Description: Includes the calculated spectral slopes for the multispectral images of random noise image stimuli.
- Format(s): .txt, decimal separator = '.'
- Size(s): 4 KB
- Dimensions: 41 rows x 6 columns
- Variables:
- channel: spectral sensitivity of the channel that has been analysed (in nm)
- id: ID of the multispectral photo
- region: region the photo was taken at
- location: region the photo was taken at
- habitat: what kind of habitat the photo was taken at
- slope: spectral slope calculated from multispectral image
- Rsqrds: goodness of fit R^2 of the linear model
Details for: Data for Further Analysis (this folder can be found in Maratus.zip and Natural Scenes.zip)
- Description: This folder contains data of rotationally averaged amplitudes (of all, binned and cut frequencies, i.e., from low frequency cut off to high frequency cut off) that can be used for further analysis for example using a different software. It contains two subfolders:
- File naming scheme: data_'range of frequencies''animal ID/photo ID''channel'.txt
- File format(s): .txt, decimal separator = '.'
- Folder size(s):
- in Maratus.zip: 698 MB
- in Natural Scenes.zip: 470 MB
- File dimensions: varying number of rows depending on frequency range x 2 columns
- Variables:
- freqs: spatial frequency
- meanAmpl: rotationally averaged amplitude
Details for: imageSets.mat
- Description: Matlab structure including multispectral imaging data and metadata for male and female Maratus abdomens and natural scenes
- Format(s): .mat
- Size(s): 2,13 GB
- Dimensions: 112 rows x 15 columns
- Variables:
- id: image set ID
- selection_data: not relevant
- rgb_images: not relevant
- project: which object was photographed M. spicatus ('Maratus') or 'Random Image Stimuli'
- illumination_type: how were objects illuminated when photographed
- taxon: species of the object
- x_date_photographed: date and time photos were taken
- gray_standard: logical array defining the gray standard in the image
- transformation_variables: values that the image needs to be rotated and centered by (for images of M. spicatus)
- square_mask: logical values needed to cut the biggest square out of M. spicatus abdomen
- aperture: aperture of the camera
- extension_tube_length: extension tube length used with the camera
- lamp_tilt: vertical tilt of the lamp if used
- animal_id: ID of M. spicatus
- maturity: maturity of M. spicatus
- sex: sex of M. spicatus
- target_amplitude_spectrum: computer generated spectral slope of random image stimuli (before printing)
- images:
- id: image ID
- exposure: exposure of the camera
- filter: filter used (for more information on filters see Tedore and Nilsson (2019) and Glenszczyk et al. (2021).
- quantum_catch_matrix: quantum catch image obtained by the camera
- filter_position: filter position in the camera
Details for: salticidVirtualFilters_530nm_5realFilters.mat
- Description: Matfile containing coefficients to create computational Salticid green channel (530 nm) with 5 existing filters in multispectral camera.
- Format(s): .mat
- Size(s): 221 Byte
Details for: salticidVirtualFilters_530nm_6realFilters.mat
- Description: Matfile containing coefficients to create computational Salticid green channel (530 nm) with 6 existing filters in multispectral camera.
- Format(s): .mat
- Size(s): 228 Byte
Details for: Functions.zip
If you are running Matlab codes make sure to add the path of this folder to your code or have the functions in the same folder as your code and data.
- Description: Folder containing custom written functions needed to run Matlab scripts. Includes:
- circularWindow.m
- prepMatFileNoMask.m
- remGam.m: removes Gamma
- rotateAndCenter.m
- round2even.m
- squareCrop.m
- File format(s): .m
- Folder size(s): 6 KB
Details for: developImgsAndFourierTransform.m
- Description: Matlab code that develops multispectral images and creates virtual filters from existing real filters in the multispectral camera. These virtual filter images are then analyzed for their spectral slope with a Fourier transform. This code can be used either to analyse multispectral images of Maratus (set imageType to ‚Maratus‘) or to analyze multispectral images of natural scenes (set imageType to ‚Natural Scenes‘).
- Format(s): .m
- Size(s): 19 KB
- Instructions: To use this code you have to first download all functions that are stored in the functions folder and the image data set called imageSets.mat as well as the coefficient files salticidVirtualFilters_530nm_5realFilters.mat and salticidVirtualFilters_530nm_6realFilters.mat. All files have to be in the same folder to run the code. Choose if you want to analyse multispectral images of Maratus or of natural scenes by specifying imageType. This code produces one folder named Maratus or Natural Scenes depending on what is specified under image Type. The Folder contains for folders: Images for Viewing on Digital Display, Images Edited for Fourier Transform, Fourier Plots, Data for Further Analysis. The code also produces a text file: either spectralSlopesMaratus.txt or spectralSlopesImageStimuli.txt depending on which image type is specified.
Details for: Images for Viewing on Digital Display (this folder can be found in Maratus.zip and Natural Scenes.zip)
- Description:This folder contains multispectral images with the typical sRGB gamma scaling removed such that brightness scales linearly with intensity when viewed on an sRGB-calibrated screen (not to be used for further analysis).
- File format(s): .png
- Folder size(s):
- in Maratus.zip: 193.3 MB
- in Natural Scenes.zip: 32.8 MB
- File naming scheme:
- in Maratus.zip: 'species_sex''animal ID''channel'.png
- in Natural Scenes.zip: 'photo_ID'_'channel'.png
Details for: Images Edited for Fourier Transform (this folder can be found in Maratus.zip and Natural Scenes.zip)
- Description:This folder contains multispectral images prepped for the Fourier transform (Maratus: cropped to squares, rotated and centered and windowed; Natural Scenes: cropped to squares and windowed).
- File format(s): .png
- Folder size(s):
- in Maratus.zip: 7.7 MB
- in Natural Scenes.zip: 16.3 MB
- File naming scheme:
- in Maratus.zip: 'species_sex''animal ID''channel'.png
- in Natural Scenes.zip: 'photo_ID'_'channel'.png
Details for: Fourier Plots (this folder can be found in Maratus.zip and Natural Scenes.zip)
- Description:This folder contains plots of the results of the Fourier analysis of each of the multispectral images (prepped image, amplitude spectrum and rotationally averaged amplitude plotted against frequency).
- File format(s): .png
- Folder size(s):
- in Maratus.zip: 51.2 MB
- in Natural Scenes.zip: 58.3 MB
- File naming scheme:
- in Maratus.zip: 'species_sex''animal ID''channel'.png
- in Natural Scenes.zip: 'photo_ID'_'channel'.png
Details for: statisticalAnalysis.Rmd
- Description: R Notebook that reads in spectralSlopesMaratus.txt and spectralSlopesNaturalScenes.txt file and models the data as described in the statistical methods part of the manuscript.
- Format(s): .Rmd
- Size(s): 8 KB
- Instructions: To use this code download the files spectralSlopesMaratus.txt and spectralSlopesNaturalScenes.txt and save in the same folder. Run the code.
Multispectral imaging
Multispectral imaging was done using a multispectral camera containing three bird-based optical filters (U, M, and L) previously described in Tedore and Nilsson (2019) and two additional filters previously described in Glenszczyk et al. (2021). By taking a weighted sum of these pre-existing camera filters, we calculated computational filters to generate new spectral sensitivities matching the spectral sensitivity of the salticid green receptor, which typically peaks around 530 nm (De Voe 1975; Yamashita and Tateda 1976; Blest et al. 1981; Zurek et al. 2015; Glenszczyk et al. 2021). The computational filter technique is further described in Tedore and Nilsson (2021) and Glenszczyk et al. (2021).