after code review changes

Author: surabhinath

README.md

@@ -41,11 +41,14 @@ source .env/bin/activate
 pip install -r requirements.txt
 ```
 
+## Running the code
+
 To reproduce the plots from the paper, run 
 ```bash
 jupyter-lab
 ```
 and open the file `scripts/DescriptiveAnalysis.ipynb`. 
+On running the file (either in one go or cell by cell), all plots are saved to scripts/plots/ folder and also displayed in the notebook for easier viewing.
 
 To reproduce the model fits from the paper
 - Ensure you have a working R installation
@@ -56,8 +59,12 @@ To reproduce the model fits from the paper
 setwd('/path/to/Relating_ObjectiveComplexity_SubjectiveComplexity_Beauty_BinaryPixelPatterns/scripts')
 source("process.R")
 source("MixedEffectsModelling.R")
+On running the file, all plots are saved to scripts/plots/ folder and tables are saved to model_fits/.
+Lines printed on the terminal can largely be ignored.
 ```
 
+
+
 ## Citation
 
 If you found this work useful, please consider citing us:

measures/Kolmogorov complexity/calculate_Kolmogorov_complexity.py

@@ -1,6 +1,5 @@
 author = 'Surabhi S Nath'
 import numpy as np
-import sys
 from pybdm import BDM
 
 """

measures/entropy/calculate_entropy.py

@@ -25,8 +25,8 @@ def calculate_entropy(gridorflatgrid, grid_size):
     if len(uniq) == 1:
         return 0
 
-    p1 = cnts[0]/(cnts[0] + cnts[1])        # fraction of white pixels
-    p2 = cnts[1]/(cnts[0] + cnts[1])        # fraction of black pixels
+    p1 = cnts[1]/(cnts[0] + cnts[1])        # fraction of black pixels
+    p2 = cnts[0]/(cnts[0] + cnts[1])        # fraction of white pixels
 
     entropy = -1 * (p1 * math.log(p1,2) + p2 * math.log(p2,2))      # entropy equation (Eq. 1)
     return entropy

measures/entropy_of_means/calculate_entropy_of_means.py

@@ -8,6 +8,8 @@
 Copyright 2014 Cosmo Harrigan
 This program is free software, distributed under the terms of the GNU LGPL v3.0
 
+Code copied from - https://github.com/cosmoharrigan/matrix-entropy in December 2021
+
 Refer to Section 2.2 (2iii) and AII for details.
 """
 
@@ -40,6 +42,7 @@ def calculate_entropy_of_means(flatgrid, grid_size):
     prof = profile(matrices)
     return np.mean(prof)
 
+# Part added by Surabhi S Nath for testing
 if __name__ == "__main__":
     grid_size = 15
 

measures/mean_entropy/calculate_mean_entropy.py

@@ -1,6 +1,5 @@
 author = 'Surabhi S Nath'
 import numpy as np
-import math
 import sys
 sys.path.insert(1, '../entropy/')
 from calculate_entropy import *

scripts/DescriptiveAnalysis.ipynb

@@ -0,0 +1,4 @@
+"","x"
+"(Intercept)",-0.0222955001151414
+"LSC",0.376565037489952
+"intricacy_4",0.255585403925477