parser = argparse.ArgumentParser()

parser.add_argument("-i", "--input",nargs="*", help="Input FASTA file", required=True)

parser.add_argument("-req", "--reqr", nargs="*", help="Required Motifs/info")

#parser.add_argument("-o", "--output", help="Output path", default="selecttable.csv")

args = parser.parse_args()

equals = []

notEquals = []

betweens = []

#outputfile = output(args)

for req in args.reqr:

if "==" in req:

equals.append(req.split("=="))

posEqual_csv(args, equals)

posEqual_fa(args)

elif "!=" in req:

notEquals.append(req.split("!="))

elif "~" in req:

betweens.append(req.split("~"))

elif "all":

print("All motifs must be present")

allMotifs_fa(args)

allMotifs_csv(args,equals)

else:

for i in range (len(args.input)):

name = (args.input[i])

name = name.split('.')[0]

name = name + '_reduced.csv'

colsToSearch = []

lst = []

take = True

with open(args.input[i], newline='') as f:

reader = csv.reader(f)

header = next(reader)

lst.append(header)

for h in range (len(header)):

for e in equals:

if e[0] == header[h]:

colsToSearch.append(str(h)+','+e[1])

for row in reader:

for c in colsToSearch:

col, pos = c.split(',')

elems = (row[(int(col))]).split(",")

if len(elems) > 1:

for i in range (len(elems)):

elems[i] = int(elems[i])

elif len(elems) == 1 and elems[0] != '':

elems[0] = int(elems[0])

if int(pos) in elems:

take = True

else:

take = False

break

if take:

lst.append(row)

with open(name, 'w', newline='') as f:

c=0

fieldnames = lst[0]

thewriter = csv.DictWriter(f, fieldnames=fieldnames)

thewriter.writeheader()

first = True

for ab in lst:

motif_pos = dict()

count = 0

if first == True:

first = False

else:

for a in ab:

motif_pos[lst[0][count]] = a

count += 1

c+=1

thewriter.writerow(motif_pos)

for i in range (len(args.input)):

name = (args.input[i])

name = name.split('.')[0]

name = name + '_reduced.csv'

colsToSearch = []

lst = []

take = True

with open(args.input[i], newline='') as f:

reader = csv.reader(f)

header = next(reader)

lst.append(header)

for h in range (len(header)):

for e in equals:

if e[0] == header[h]:

colsToSearch.append(str(h)+','+e[1])

for row in reader:

for c in colsToSearch:

col, pos = c.split(',')

elems = (row[(int(col))]).split(",")

if len(elems) > 1:

for i in range (len(elems)):

elems[i] = int(elems[i])

elif len(elems) == 1 and elems[0] != '':

elems[0] = int(elems[0])

if int(pos) in elems:

take = True

else:

take = False

break

if take:

lst.append(row)

with open(name, 'w', newline='') as f:

c = 0

fieldnames = lst[0]

thewriter = csv.DictWriter(f, fieldnames=fieldnames)

thewriter.writeheader()

first = True

for ab in lst:

motif_pos = dict()

count = 0

if first == True:

first = False

else:

empty = False

for a in ab:

motif_pos[lst[0][count]] = a

count += 1

if a == "":

empty = True

if empty == False:

c+=1

thewriter.writerow(motif_pos)

print(str(c) + " sequences kept after applying the requirements for " + name)

#check hoow many cols, check if all of them has a value

#make a FASTA and make a CSV

for i in range (len(args.input)):

c=0

fasta = {}

name = (args.input[i])

name = name.split('.')[0]

name = name + '_reduced.fa'

with open(args.input[i], newline='') as f:

reader = csv.reader(f)

header = next(reader)

for row in reader:

isEmpty = False

for i in range(1, len(header)-1):

if row[i] == "":

isEmpty = True

break

if isEmpty == False:

fasta[row[0]] = row[len(header)-1]

seq_list = [sequence.Sequence(sequence=seq, name=seqname) for seqname, seq in fasta.items()]

sequence.writeFastaFile(name, seq_list)

c+=1

fasta = {}

name = (args.input[0])

name = name.split('.')[0]

csvFile = name + '_reduced.csv'

seqCol = 0

with open(csvFile, newline='') as f:

reader = csv.reader(f)

header = next(reader)

seqCol = len(header)-1

for row in reader:

fasta[row[0]] = row[len(header)-1]

seq_list = [sequence.Sequence(sequence=seq, name=seqname) for seqname, seq in fasta.items()]

sequence.writeFastaFile(name+'.fa', seq_list)

#print(header[len(header)-1])

# for i in range (len(args.input)):

# name = (args.input[i])

# name = name.split('.')[0]

# name = name + '_reduced.fa'

# with open(args.input[i], newline='') as f:

# reader = csv.reader(f)

# header = next(reader)

# for row in reader:

# isEmpty = False

# for i in range(1, len(header)-1):

# if row[i] == "":

# isEmpty = True

# break

# if isEmpty == False:

# print(row[1])

# fasta[row[0]] = row[len(header)-1]

# seq_list = [sequence.Sequence(sequence=seq, name=seqname) for seqname, seq in fasta.items()]