fix: remove unnecessary class

src/primingprob/priming_prob.py

-"""Imports."""
+"""Calculates the probability of priming and write the gff file."""
 import numpy as np
 import scipy.constants  # type: ignore
 
 
-class Probability:
-    """Calculates the probability of priming and write the gff file."""
+def inter_para(input_path):
+    """Open the RIblast output file and read only the parameter lines.
 
-    def inter_para(input_path):
-        """Open the RIblast output file and read only the parameter lines.
+    Args:
+    Path to Energies.txt file
 
-        Args:
-            Path to Energies.txt file
+    Returns:
+    my_list (list): Contains the paramter lines from Energies.txt
+    """
+    Energies = open(input_path, "r")  # ouput of RIblast
 
-        Returns:
-            my_list (list): Contains the paramter lines from Energies.txt
-        """
-        Energies = open(input_path, "r")  # ouput of RIblast
+    mylist = []  # all lines of Energies starting with an ID-number
 
-        mylist = []  # all lines of Energies starting with an ID-number
+    for myline in Energies:  # Read lines containing needed data
+        if myline[0].isdigit():
+            mylist.append(myline)
+        elif myline[0].isdigit() is False:
+            continue
 
-        for myline in Energies:  # Read lines containing needed data
-            if myline[0].isdigit():
-                mylist.append(myline)
-            elif myline[0].isdigit() is False:
-                continue
+    Energies.close()
 
-        Energies.close()
+    return(mylist)
 
-        return(mylist)
 
-    def inter_prob(data_list, fasta_path, output_path):
-        """Calculate the prob. and write the gff file.
+def inter_prob(data_list, fasta_path, output_path):
+    """Calculate the prob. and write the gff file.
 
-        Args:
-            data_list (list): Contains all parameters of Energies.txt
-            fasta_path (path): Path to fasta file
-            output_path (path): Path to output file
+     Args:
+        data_list (list): Contains all parameters of Energies.txt
+        fasta_path (path): Path to fasta file
+        output_path (path): Path to output file
 
-        Returns:
-            gff (file): Gff file contains all the output information
-        """
-        # count interactions per script through fasta-ID
-        fastafile = open(fasta_path, "r")
-        id_list = []  # contains list of transcipt IDs
+    Returns:
+        gff (file): Gff file contains all the output information
+    """
+    # count interactions per script through fasta-ID
+    fastafile = open(fasta_path, "r")
+    id_list = []  # contains list of transcipt IDs
 
-        for mylinecounter in fastafile:
-            if mylinecounter.startswith(">"):
-                a = mylinecounter
-                a = mylinecounter.replace(">", "")
-                b = a.split()
-                c = b[0]
-                id_list.append(c)
-            elif mylinecounter.startswith(">") is False:
-                continue
+    for mylinecounter in fastafile:
+        if mylinecounter.startswith(">"):
+            a = mylinecounter
+            a = mylinecounter.replace(">", "")
+            b = a.split()
+            c = b[0]
+            id_list.append(c)
+        elif mylinecounter.startswith(">") is False:
+            continue
 
-        counter = 0
-        counter_list = []  # list of number of interactions per transcript
+    counter = 0
+    counter_list = []  # list of number of interactions per transcript
 
-        for cc in range(0, len(id_list)):
-            for dd in range(0, len(data_list)):
-                if id_list[cc] in data_list[dd]:
-                    counter = counter + 1
+    for cc in range(0, len(id_list)):
+        for dd in range(0, len(data_list)):
+            if id_list[cc] in data_list[dd]:
+                counter = counter + 1
 
-            counter_list.append(counter)
-            counter = 0
+        counter_list.append(counter)
+        counter = 0
 
-        para_list = []
+    para_list = []
 
-        for i in range(0, len(data_list)):
-            x = data_list[i].split(",")
-            para_list.append(x)
-        # splitting each list item by the "," this results in a 2D list
+    for i in range(0, len(data_list)):
+        x = data_list[i].split(",")
+        para_list.append(x)
+    # splitting each list item by the "," this results in a 2D list
 
-        for j in range(0, len(para_list)):
-            del para_list[j][1:-2]
-        # only keeps the ID-numer, the interaction
-        # energy, and interaction site of both sequences. (still a 2D-list)
+    for j in range(0, len(para_list)):
+        del para_list[j][1:-2]
+    # only keeps the ID-numer, the interaction
+    # energy, and interaction site of both sequences. (still a 2D-list)
 
-        start_end_index = 1  # index of start and end in the list
+    start_end_index = 1  # index of start and end in the list
 
-        for d in range(0, len(para_list)):  # Optimize location output
-            a = para_list[d][2].split(":")
-            a[start_end_index] = a[start_end_index].replace(") ", "")
-            a[start_end_index] = a[start_end_index].replace("\n", "")
-            a[start_end_index] = a[start_end_index].replace("-", " ")
-            a[start_end_index] = a[start_end_index].split(" ")
-            para_list[d][2] = a[start_end_index]
+    for d in range(0, len(para_list)):  # Optimize location output
+        a = para_list[d][2].split(":")
+        a[start_end_index] = a[start_end_index].replace(") ", "")
+        a[start_end_index] = a[start_end_index].replace("\n", "")
+        a[start_end_index] = a[start_end_index].replace("-", " ")
+        a[start_end_index] = a[start_end_index].split(" ")
+        para_list[d][2] = a[start_end_index]
 
-        for k in range(0, len(para_list)):  # type-conversion of ID and E
-            for w in range(0, 2):  # "2" because first two elements in each sublist are ID and E
-                para_list[k][w] = float(para_list[k][w])
+    for k in range(0, len(para_list)):  # type-conversion of ID and E
+        for w in range(0, 2):  # "2" because first two elements in each sublist are ID and E
+            para_list[k][w] = float(para_list[k][w])
 
-        joule = 4184  # 1kcal = 4184 joule
-        inter_energy = 1  # index of inter. energy in list
+    joule = 4184  # 1kcal = 4184 joule
+    inter_energy = 1  # index of inter. energy in list
 
-        for z in range(0, len(para_list)):  # from kcal/mol to Joule/mol
-            para_list[z][inter_energy] = para_list[z][inter_energy] * joule
+    for z in range(0, len(para_list)):  # from kcal/mol to Joule/mol
+        para_list[z][inter_energy] = para_list[z][inter_energy] * joule
 
-        T = 300.15  # Roomtemperature (27 degree celsius) in Kelvin
-        KT = scipy.constants.R * T  # calculating gas constant R * T
+    T = 300.15  # Roomtemperature (27 degree celsius) in Kelvin
+    KT = scipy.constants.R * T  # calculating gas constant R * T
 
-        for u in range(0, len(para_list)):  # calculating -E / RT
-            para_list[u][inter_energy] = (-(para_list[u][inter_energy])/KT)
+    for u in range(0, len(para_list)):  # calculating -E / RT
+        para_list[u][inter_energy] = (-(para_list[u][inter_energy])/KT)
 
-        prob_list = []  # List containing all the prob.
+    prob_list = []  # List containing all the prob.
 
-        for h in range(0, len(para_list)):  # calculating the e^(-E/kT)
-            probab = np.exp(para_list[h][inter_energy])
-            prob_list.append(probab)
-            para_list[h][inter_energy] = probab
+    for h in range(0, len(para_list)):  # calculating the e^(-E/kT)
+        probab = np.exp(para_list[h][inter_energy])
+        prob_list.append(probab)
+        para_list[h][inter_energy] = probab
 
-        probability_sum = 0  # variable to calculate sum of probabilities per transcipt
-        sum_list = []  # List containing all the sums
+    probability_sum = 0  # variable to calculate sum of probabilities per transcipt
+    sum_list = []  # List containing all the sums
 
-        prob_list2 = prob_list.copy()
+    prob_list2 = prob_list.copy()
 
-        for jj in range(0, len(counter_list)):
-            for ii in range(0, counter_list[jj]):
-                probability_sum = probability_sum + prob_list[ii]
-            sum_list.append(probability_sum)
-            probability_sum = 0  # setting back to 0, for next interactions
-            del prob_list[0:counter_list[jj]]
+    for jj in range(0, len(counter_list)):
+        for ii in range(0, counter_list[jj]):
+            probability_sum = probability_sum + prob_list[ii]
+        sum_list.append(probability_sum)
+        probability_sum = 0  # setting back to 0, for next interactions
+        del prob_list[0:counter_list[jj]]
 
-        real_prob = []  # contains all the normalized probabilities
+    real_prob = []  # contains all the normalized probabilities
 
-        for jj in range(0, len(sum_list)):
-            for ii in range(0, counter_list[jj]):
-                prob_list2[ii] = prob_list2[ii]/sum_list[jj]
-                real_prob.append(prob_list2[ii])
-            del prob_list2[0:counter_list[jj]]  # Normalized probabilities
+    for jj in range(0, len(sum_list)):
+        for ii in range(0, counter_list[jj]):
+            prob_list2[ii] = prob_list2[ii]/sum_list[jj]
+            real_prob.append(prob_list2[ii])
+        del prob_list2[0:counter_list[jj]]  # Normalized probabilities
 
-        for vv in range(0, len(para_list)):  # inserting the normalized values in para_list
-            para_list[vv][1] = real_prob[vv]
+    for vv in range(0, len(para_list)):  # inserting the normalized values in para_list
+        para_list[vv][1] = real_prob[vv]
 
-        final_list = []  # List containing all the final paramters to print
+    final_list = []  # List containing all the final paramters to print
 
-        for bb in range(0, len(sum_list)):  # Insert ID in paralist
-            for ss in range(0, counter_list[bb]):
-                para_list[ss][0] = id_list[bb]
-                final_list.append(para_list[ss])
-            del para_list[0:counter_list[bb]]
+    for bb in range(0, len(sum_list)):  # Insert ID in paralist
+        for ss in range(0, counter_list[bb]):
+            para_list[ss][0] = id_list[bb]
+            final_list.append(para_list[ss])
+        del para_list[0:counter_list[bb]]
 
-        gff = open(output_path, "w+")  # gff file
+    gff = open(output_path, "w+")  # gff file
 
-        for ll in range(0, len(final_list)):  # writing gff file
-            gff.write(str(final_list[ll][0]) +  # transcript ID
-                      "\tRIblast\tPriming Site\t" +
-                      str(final_list[ll][2][1])+"\t" +  # start
-                      str(final_list[ll][2][0])+"\t" +  # end
-                      str(final_list[ll][1])+"\t.\t.\t.\n")  # probability
+    for ll in range(0, len(final_list)):  # writing gff file
+        gff.write(str(final_list[ll][0]) +  # Transcript ID
+                  "\tRIblast\tPriming Site\t" +
+                  str(final_list[ll][2][1])+"\t" +  # Start
+                  str(final_list[ll][2][0])+"\t" +  # End
+                  str(final_list[ll][1])+"\t.\t.\t.\n")  # probability
 
-        gff.close
-        return final_list
+    gff.close
+    return final_list