diff --git a/TargetQuality/per_shot.py b/TargetQuality/per_shot.py
index 70f6295..0944187 100644
--- a/TargetQuality/per_shot.py
+++ b/TargetQuality/per_shot.py
@@ -5,9 +5,6 @@ from math import log as ln
 
 import subprocess
 from subprocess import STDOUT, PIPE
-from .target_quality import vmaf_probe, transform_vmaf, weighted_search, get_target_q, \
-    adapt_probing_rate, read_weighted_vmaf
-from Projects import Project
 
 import matplotlib
 from matplotlib import pyplot as plt
@@ -15,6 +12,10 @@ from matplotlib import pyplot as plt
 import numpy as np
 from scipy import interpolate
 
+from .target_quality import vmaf_probe, weighted_search, get_target_q, \
+    adapt_probing_rate
+from VMAF import read_weighted_vmaf, transform_vmaf
+from Projects import Project
 from Av1an.bar import process_pipe
 from Chunks.chunk import Chunk
 from Av1an.commandtypes import CommandPair, Command
@@ -198,4 +199,3 @@ def per_shot_target_quality(chunk: Chunk, args: Project):
         plot_probes(args, vmaf_cq, chunk, frames)
 
     return q
-
diff --git a/TargetQuality/target_quality.py b/TargetQuality/target_quality.py
index f6c4b60..16c5575 100644
--- a/TargetQuality/target_quality.py
+++ b/TargetQuality/target_quality.py
@@ -1,59 +1,14 @@
 import subprocess
 from subprocess import STDOUT, PIPE
-from Av1an.commandtypes import CommandPair, Command
-from Projects import Project
-from VMAF import call_vmaf, read_json
-from Chunks.chunk import Chunk
-from math import log as ln
-from math import ceil, floor
-from Av1an.bar import process_pipe
+
 import numpy as np
 from scipy import interpolate
 
-
-def transform_vmaf(vmaf):
-    if vmaf<99.99:
-        return -ln(1-vmaf/100)
-    else:
-        # return -ln(1-99.99/100)
-        return 9.210340371976184
-
-
-def read_weighted_vmaf(file, percentile=0):
-    """Reads vmaf file with vmaf scores in it and return N percentile score from it.
-
-    :return: N percentile score
-    :rtype: float
-    """
-
-    jsn = read_json(file)
-
-    vmafs = sorted([x['metrics']['vmaf'] for x in jsn['frames']])
-
-    percentile = percentile if percentile != 0 else 0.25
-    score = get_percentile(vmafs, percentile)
-
-    return round(score, 2)
-
-
-def get_percentile(scores, percent):
-    """
-    Find the percentile of a list of values.
-    :param scores: - is a list of values. Note N MUST BE already sorted.
-    :param percent: - a float value from 0.0 to 1.0.
-    :return: - the percentile of the values
-    """
-    scores = sorted(scores)
-    key = lambda x: x
-
-    k = (len(scores)-1) * percent
-    f = floor(k)
-    c = ceil(k)
-    if f == c:
-        return key(scores[int(k)])
-    d0 = (scores[int(f)]) * (c-k)
-    d1 = (scores[int(c)]) * (k-f)
-    return d0+d1
+from Av1an.commandtypes import CommandPair, Command
+from Projects import Project
+from VMAF import call_vmaf, read_json, transform_vmaf
+from Chunks.chunk import Chunk
+from Av1an.bar import process_pipe
 
 
 def adapt_probing_rate(rate, frames):
@@ -225,7 +180,3 @@ def get_closest(q_list, q, positive=True):
         q_list = [x for x in q_list if x < q]
 
     return min(q_list, key=lambda x: abs(x - q))
-
-
-
-
diff --git a/VMAF/vmaf.py b/VMAF/vmaf.py
index 1bb53ce..b95d0b3 100755
--- a/VMAF/vmaf.py
+++ b/VMAF/vmaf.py
@@ -4,16 +4,19 @@ import json
 import shlex
 import subprocess
 import sys
+
 from pathlib import Path
 from subprocess import PIPE, STDOUT
 
 import numpy as np
-from math import log10
+from math import log10, ceil, floor
+from math import log as ln
+
+import matplotlib
 from matplotlib import pyplot as plt
 
 from Av1an.bar import process_pipe
 from Chunks.chunk import Chunk
-import matplotlib
 
 matplotlib.use('Agg')
 
@@ -78,6 +81,52 @@ def call_vmaf(chunk: Chunk, encoded: Path, n_threads, model, res,
     return fl_path
 
 
+def get_percentile(scores, percent):
+    """
+    Find the percentile of a list of values.
+    :param scores: - is a list of values. Note N MUST BE already sorted.
+    :param percent: - a float value from 0.0 to 1.0.
+    :return: - the percentile of the values
+    """
+    scores = sorted(scores)
+    key = lambda x: x
+
+    k = (len(scores)-1) * percent
+    f = floor(k)
+    c = ceil(k)
+    if f == c:
+        return key(scores[int(k)])
+
+    d0 = (scores[int(f)]) * (c-k)
+    d1 = (scores[int(c)]) * (k-f)
+    return d0+d1
+
+
+def transform_vmaf(vmaf):
+    if vmaf<99.99:
+        return -ln(1-vmaf/100)
+    else:
+        # return -ln(1-99.99/100)
+        return 9.210340371976184
+
+
+def read_weighted_vmaf(file, percentile=0):
+    """Reads vmaf file with vmaf scores in it and return N percentile score from it.
+
+    :return: N percentile score
+    :rtype: float
+    """
+
+    jsn = read_json(file)
+
+    vmafs = sorted([x['metrics']['vmaf'] for x in jsn['frames']])
+
+    percentile = percentile if percentile != 0 else 0.25
+    score = get_percentile(vmafs, percentile)
+
+    return round(score, 2)
+
+
 def plot_vmaf(source: Path, encoded: Path, args, model, vmaf_res):
     """
     Making VMAF plot after encode is done