Desert v. Vinegar Flies: Eye Allometry

Instructions needed to generate the statistics and figures used in Eye Allometry results:<br><br>Make sure Python 3.6+ and the following Python packages are installed (try pip):<br> -matplotlib<br> -numpy<br> -pandas<br> -pickle<br> -scikit-image<br> -scipy<br> -seaborn<br> -statsmodels-eye_tools (from https://github.com/jpcurrea/eye_tools.git)<br><br>A. Plot figures and calculate important statistics:<br>In the terminal, cd to the downloaded folder and run the following:<br> ~! python3 plot.py<br>Running this script produces the following image files:<br> -eye_composition.png<br> -eye_composition.svg<br> -eye_shape.png<br> -eye_shape.svg<br> -fields_of_view.png<br> -fields_of_view.svg<br> -optical_performance.png<br> -optical_performance.svg<br><br>We've also already saved the following files:<br> -stats.txt: allometric statistics collated by measurement<br> -stats.csv: allometric statistics used for table<br><br>B. To generate the allometric data from scratch:<br>1. unzip image_stacks.zip, creating a folder of the same name<br>2. run the following:<br> ~! python3 analysis.py<br>Running this script produces the following:<br> -allometry_data.csv: readable measurements dataframe<br> -allometry_data.pkl: pickled measurements dataframe<br>3. to plot the data, running process A. above.<br>C. To generate Supplemental Figure 2, cd to the downloaded folder and run the following:<br> ~! python3 plot_demo.py<br><br>

用于生成眼部异速生长（Eye Allometry）结果所需的统计数据与图表的操作指南：

请确保已安装Python 3.6及以上版本，以及以下Python依赖包（可通过pip命令安装）：
- matplotlib
- numpy
- pandas
- pickle
- scikit-image
- scipy
- seaborn
- statsmodels-eye_tools（获取地址：https://github.com/jpcurrea/eye_tools.git）

A. 绘制图表并计算核心统计量
在终端中切换至已下载的文件夹，执行以下命令：
~! python3 plot.py
运行该脚本将生成以下图像文件：
- eye_composition.png
- eye_composition.svg
- eye_shape.png
- eye_shape.svg
- fields_of_view.png
- fields_of_view.svg
- optical_performance.png
- optical_performance.svg

同时已预先保存以下文件：
- stats.txt：按测量项整理的异速生长统计数据
- stats.csv：用于制表的异速生长统计数据

B. 从头生成异速生长数据集
1. 解压image_stacks.zip，得到同名文件夹
2. 执行以下命令：
~! python3 analysis.py
运行该脚本将生成以下文件：
- allometry_data.csv：可读格式的测量数据帧
- allometry_data.pkl：经pickle序列化的测量数据帧
3. 如需绘制数据图表，请执行上述流程A。

C. 如需生成补充图2，请切换至已下载的文件夹并执行以下命令：
~! python3 plot_demo.py