diff --git a/noisyplotype.py b/noisyplotype.py
index 14f6ee26ad2fc6f90f39f9482497a5b093d9fd39..dc7a334fe7d2bfeb066f25654e44fe4a93500496 100644
--- a/noisyplotype.py
+++ b/noisyplotype.py
@@ -9,19 +9,23 @@ def generate_chr_for_one_ind (mean_depth, markers_positions, conversion_factor,
     Generate a chromosome for a given size, density of markers, and depth (follwing a gaussian distrib with a mean_depth and sd_depth).
     
     Args:
-        mean_depth (float): The mean depth of the chromosome.
+        mean_depth (float): The mean sequencing depth of the chromosome
         markers_positions (lst) : liste of marker positions (picked on a grid)
-        err_rate (float): The error rate of the chromosome.
+        conversion_factor (float) : Value of the bp per cM conversion (bp chromosome size / cM chromosome size)
+        errA & errB (float): Respectively the error rate of observing a B whereas the genotype is truely a A and a A whereas the genotype is truely a B
     
     Returns:
-        list: The chromosome with each position having a given genotype.
+        segment: A chromosome with each position having a given genotype with a given site depth and allele depth
+        segment_error : A chromosome with each position having a given genotype with a given site depth and allele depth considering the error rates errA and errB
     '''
-
+    
+    # Create an empty list to store the chromosome
     segment = []
+    # Create an empty list to store the chromosome with error
     segment_error = []
     breakpoints = []
 
-    # Iterate through the list of markers positions
+    # Iterate through the list of markers positions (fixed)
     previousMarkerGenotype = ""
     for i in range(0, len(markers_positions)):
         recomb1 = False
@@ -29,21 +33,23 @@ def generate_chr_for_one_ind (mean_depth, markers_positions, conversion_factor,
         # If the current marker is not the first one
         if i > 0:
             # Calculate the interval between the current marker and the previous one
-            #TODO 
-            #Kosambi inverse function
+            #using the Kosambi inverse function to estimate the chance of recombination
             IntervalWithPreviousMarker = markers_positions[i] - markers_positions[i-1]
-            tempcM = 2 * (IntervalWithPreviousMarker / 100) / conversion_factor 
+            tempcM = 2 * (IntervalWithPreviousMarker / 100) / conversion_factor         ## Conversion factor is used to have the bp per cM 
             IntervalWithPreviousMarkerInRF = 0.5 * ((math.exp(tempcM) - math.exp(-tempcM)) / (math.exp(tempcM) + math.exp(-tempcM)))
             rnd = random.random()
-            # If the random number is greater than the probability of a recombination
-            #print("before",genotype1, genotype2)
-            if rnd > 1 - IntervalWithPreviousMarkerInRF: # a recombination occurs
+
+            # If the random number is greater than the probability of a recombination a recombination occurs
+            # Done for genotype 1
+            if rnd > 1 - IntervalWithPreviousMarkerInRF: 
                 recomb1 = True
                 # If the previous marker is A, change the genotype to B
                 if genotype1 == "A":
                     genotype1 = "B";
                 else :
                     genotype1 = "A";
+                    
+            # Done for genotype 2
             rnd = random.random()
             if rnd > 1 - IntervalWithPreviousMarkerInRF:
                 recomb2 = True
@@ -52,8 +58,8 @@ def generate_chr_for_one_ind (mean_depth, markers_positions, conversion_factor,
                     genotype2 = "B"
                 else :
                     genotype2 = "A"
-            #print("after",genotype1, genotype2)
-        # If the current marker is the first one, fix the two first genotypes.
+                    
+        # If the current marker is the first one, Set the two first genotypes (random).
         else:
             rnd = random.random()
             # If the random number is greater than 0.5
@@ -92,33 +98,35 @@ def generate_chr_for_one_ind (mean_depth, markers_positions, conversion_factor,
         
             breakpoints.append([i,transition]) 
 
-        # Calculate the depth of the current marker        
+        # Calculate the site depth of the current marker    
         g = np.random.poisson(mean_depth)
         # If the depth of the current marker is less than 0 (safeguard)
         if g < 0:
             g = 0
         # Round the depth of the current marker
         site_depth = round(g)
-        # Initialize x and y
+        # Initialize x and y (with and without error)
         x = 0
         y = 0
         x_error = 0
         y_error = 0
+        
         # If the depth of the current marker is 0, genotype is Missing Data
         if site_depth == 0:            
             genotype = "./."
             genotype_error = "./."
         else :
-            # If the current marker is A and the previous marker is A, genotype if homozygote A (ref, 0/0)
+            # If the site is homozygous A (ref, 0/0)
             if genotype1 == "A" and genotype2 == "A":
                 x = site_depth
                 y = 0
                 genotype = "0/0"
                 x_error = 0
                 y_error = 0
+                # Considering the sequencing and mapping error at each site for a given site depth
                 for j in range(0,site_depth):
                     rnd = random.random()
-                    # If the random number is smaller than errA, we switch increase the wrong allele depth
+                    # If the random number is smaller the error rate, we increase the wronge allele depth
                     if rnd < errA:
                         x_error = x_error + 0
                         y_error = y_error + 1
@@ -139,9 +147,10 @@ def generate_chr_for_one_ind (mean_depth, markers_positions, conversion_factor,
                 genotype = "1/1"
                 x_error = 0
                 y_error = 0
+                # Considering the sequencing and mapping error at each site for a given site depth
                 for j in range(0,site_depth):
                     rnd = random.random()
-                    # If the random number is smaller than errB, we switch increase the wronge allele depth
+                    # If the random number is smaller the error rate, we increase the wronge allele depth
                     if rnd < errB:
                         x_error = x_error + 1
                         y_error = y_error + 0
@@ -154,22 +163,24 @@ def generate_chr_for_one_ind (mean_depth, markers_positions, conversion_factor,
                     genotype_error = "0/1"
                 else :
                     genotype_error = "1/1"
+                    
             # If the current marker is neither A nor B, genotype if heterozygous H (0/1)
             else:
                 # Generate a random number between 0 and the depth of the current marker
                 x = random.randint(0,site_depth)
                 y = site_depth - x
+                # Error of A and B compensate themselves in heterozygous site so no need to change the x_error and y_error
                 x_error = x
                 y_error = y
-                # If the depth of x of the current marker is 0, seen as homozygous
+                # If the depth of x of the current marker is 0, it's seen as homozygous site (alt, 1/1)
                 if x == 0:
                     genotype = "1/1"
                     genotype_error = "1/1"
-                # If the depth of y of the current marker is not 0, seen as homozygous
+                # If the depth of x of the current marker is 0, it's seen as homozygous site (ref, 0/0)
                 elif y == 0:
                     genotype = "0/0"
                     genotype_error = "0/0"
-                # If the depth x and y of the current marker is not 0, seen as heterozygous
+                # If the depth x and y of the current marker is not 0, it's seen as heterozygous (0/1)
                 else :
                     genotype = "0/1"
                     genotype_error = "0/1"  
@@ -180,6 +191,7 @@ def generate_chr_for_one_ind (mean_depth, markers_positions, conversion_factor,
         finalGenotype = str(genotype) + ":" + str(site_depth) + ":" + str(x) + "," + str(y) + ":.:.:.:.:."        
         segment.append(finalGenotype)
         
+        # Append the genotype and the depth of the current marker to the segment_error list
         finalGenotype_error = str(genotype_error) + ":" + str(site_depth) + ":" + str(x_error) + "," + str(y_error) + ":.:.:.:.:."
         segment_error.append(finalGenotype_error)
 
@@ -193,6 +205,7 @@ def generate_individuals (nb_individuals, chromosome_size, marker_density, mean_
 
     # Calculate the number of marker requiered
     markers_nb = round(chromosome_size * marker_density)
+    
     # Generate a sorted list of markers positions
     #markers_positions = sorted(random.sample(range(chromosome_size),size))
     markers_positions = np.linspace(1, chromosome_size, markers_nb, dtype="int")
@@ -228,14 +241,13 @@ nb_individuals = 3
 chromosome_size = 44000000
 cMsize = 180    ## Size of genetic map
 conversion_factor = chromosome_size/cMsize   ## Corresponds to a bpPercM conversion ! Needs to be fixed... Does not produce the correct division!
-#print(conversion_factor)
 marker_density = 0.0055
 mean_depth = 3
-max_depth = 6 #TODO
+max_depth = 6 #TODO (better estimate of max?)
 errA = 0.005
 errB = 0.005
 
-# #size = 200000
+## Generate the pop and associate the results to the matrixes with and without errors
 pop = generate_individuals(nb_individuals, chromosome_size, marker_density, mean_depth, conversion_factor, errA, errB)
 matrix = pop[0]
 matrix_error = pop[1]
@@ -264,7 +276,8 @@ header = [
 ]
 
 
-with open('ABtest.vcf', 'w') as file:
+## Write the VCF files (with and without errors)
+with open('test.vcf', 'w') as file:
     # Write the header of the file
     file.writelines(header)
     
@@ -280,7 +293,7 @@ with open('ABtest.vcf', 'w') as file:
         row.append("1/1:"+ str(mean_depth) + ":0," + str(mean_depth) + ":.:.:.:.")
         file.write("\t".join(row) + "\n");
 
-with open('ABtest_error.vcf', 'w') as file:
+with open('test_error.vcf', 'w') as file:
     # Write the header of the file
     file.writelines(header)