deleting old file

src/PrimingProb_Final.py

-"""Imports."""
-import numpy as np
-import scipy.constants
-import argparse
-from pathlib import Path
-
-
-class Probability:
-    """Calculates the probability of priming and write the gff file."""
-
-    #  adding parser
-    parser = argparse.ArgumentParser(
-        description="Fasta-file input",
-        add_help=False,
-        formatter_class=argparse.ArgumentDefaultsHelpFormatter,
-    )
-    # add arguments
-    parser.add_argument(
-        'input_file',
-        type=lambda p: Path(p).absolute(),
-        metavar="PATH",
-        help="path to fasta-file",
-    )
-
-    args = parser.parse_args()
-
-    def InterPara(path):
-        """Open the RIblast output file and read only the parameter lines.
-
-        Args:
-            Path to Fasta-file
-
-        Returns:
-            my_list (list): Contains all the paramter lines from RIblast
-        """
-        # myfile = open(sys.argv[1], "r")  # ouput of RIblast
-        myfile = open(path, "r")
-
-        mylist = []  # all lines of Energies starting with an ID-number
-
-        for myline in myfile:  # Read lines containing needed data
-            if myline[0].isdigit():
-                mylist.append(myline)
-            else:
-                continue
-
-        myfile.close()
-
-        return(mylist)
-
-    data = InterPara(args.input_file)
-
-    def InterProb(data_list):
-        """Calculate the prob. and make the gff file.
-
-        Args:
-            data_list (list): Contains all parameters of RIblast
-
-        Returns:
-            gff (file): Gff file contains all the output information
-        """
-        # count interactions per script through fasta ID (first line of fasta)
-        mycounter = open("../inputs/transcript.fasta", "r")
-
-        mycounter_list = []
-
-        for mylinecounter in mycounter:
-            if mylinecounter.startswith(">"):
-                a = mylinecounter
-                a = mylinecounter.replace(">", "")
-                b = a.replace("\n", "")
-                mycounter_list.append(b)
-            else:
-                continue
-
-        counter = 0
-        counter_list = []
-
-        for cc in range(0, len(mycounter_list)):
-            for dd in range(0, len(data_list)):
-                if mycounter_list[cc] in data_list[dd]:
-                    counter = counter + 1
-                else:
-                    continue
-            counter_list.append(counter)
-            counter = 0
-
-        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 2-D 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 d in range(0, len(para_list)):  # Optimize location output
-            a = para_list[d][2].split(":")
-            a[1] = a[1].replace(") ", "")
-            a[1] = a[1].replace("\n", "")
-            a[1] = a[1].replace("-", " ")
-            a[1] = a[1].split(" ")
-            para_list[d][2] = a[1]
-
-        for k in range(0, len(para_list)):  # type-conversion of ID and E
-            for w in range(0, 2):
-                para_list[k][w] = float(para_list[k][w])
-
-        for z in range(0, len(para_list)):  # from kcal/mol to Joule/mol
-            para_list[z][1] = para_list[z][1] * 4184
-
-        kT = scipy.constants.R * 300.15  # calculating gas constant R * T
-
-        for u in range(0, len(para_list)):  # calculating -E / RT
-            para_list[u][1] = (-(para_list[u][1])/kT)
-
-        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][1])
-            prob_list.append(probab)
-            para_list[h][1] = probab
-
-        count_sum = 0
-        sum_list = []
-
-        prob_list2 = prob_list.copy()
-
-        for jj in range(0, len(counter_list)):
-            for ii in range(0, counter_list[jj]):
-                count_sum = count_sum + prob_list[ii]
-            sum_list.append(count_sum)
-            count_sum = 0
-            del prob_list[0:counter_list[jj]]
-
-        real_prob = []
-
-        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
-
-        # real_prob contains all the linearized probabilities
-
-        for vv in range(0, len(para_list)):
-            para_list[vv][1] = real_prob[vv]
-
-        final_list = []
-
-        for bb in range(0, len(sum_list)):  # Insert ID in paralist
-            for ss in range(0, counter_list[bb]):
-                para_list[ss][0] = mycounter_list[bb]
-                final_list.append(para_list[ss])
-            del para_list[0:counter_list[bb]]
-
-        gff = open("../inputs/Potential_Priming_sites.txt", "w+")  # gff file
-
-        for ll in range(0, len(final_list)):
-            gff.write(str(final_list[ll][0]) +
-                      "\tRIblast\ttranscript\t" +
-                      str(final_list[ll][2][1])+"\t" +
-                      str(final_list[ll][2][0])+"\t" +
-                      str(final_list[ll][1])+"\t.\t.\t.\n")
-
-        gff.close
-
-        return gff
-
-    InterProb(data)