##### Importing module ########################

import numpy as np

import pandas as pd

import matplotlib.pyplot as plt

from tkinter import*

from tkinter import filedialog

##### Importing user data ######################

root = Tk()

Profile = filedialog.askopenfile()

user_cols = [“Distance”, “Dose”]

df1 = pd.read_table(Profile, names=user_cols, header=None)

#####Define 1st and 2nd derivative with central divide difference using superposition principle -function

h = (df1.ix[1,“Distance”] - df1.ix[0,“Distance”])

X = df1[“Distance”]

Y = df1[“Dose”]

def f1():

f1 = (((df1.ix[count + 1, “Dose”]) - (df1.ix[count - 1, “Dose”])) / (2 * h))

return f1

def f2():

f2 = (((df1.ix[count + 2, “Dose”]) - 2*(df1.ix[count, “Dose”]) + (df1.ix[count - 2, “Dose”])) / (4 * h * h))

return f2

##### Calculation first and second derivatives #####

X1 = df1.iloc[1:len(X)-1,0]

X2 = df1.iloc[2:len(X)-2,0]

Y1 = []

Y2 = []

for i in df1[“Dose”]:

count = 1

while count <= (len(Y)-2):

f1_store = Y1.append(f1())

count += 1

count = 2

while count <= (len(Y)-3):

f2_store = Y2.append(f2())

count += 1

break

df2 = pd.DataFrame(list(zip(Y1, Y2)), columns = [“f’(x)”, “f”(x)”])

Data = pd.concat([df1, df2], axis = 1)

###### Finding the Beam Profile parameters ######

## Inflection Points

Rt_maxslope = int(Y1.index(max(Y1)))

Rt_ipvalues = Y2[(Rt_maxslope-6):(Rt_maxslope+4)]

Rt_disvalue = X[(Rt_maxslope-4):(Rt_maxslope+6)]

Rt_dosevalue = list(Y[(Rt_maxslope-4):(Rt_maxslope+6)])

RtSign_Change = int(np.where(np.diff(np.sign(Rt_ipvalues)))[0])

Lt_minslope = int(Y1.index(min(Y1)))

Lt_ipvalues = Y2[(Lt_minslope-5):(Lt_minslope+5)]

Lt_disvalue = X[(Lt_minslope-3):(Lt_minslope+7)]

Lt_dosevalue = list(Y[(Lt_minslope-3):(Lt_minslope+7)])

LtSign_Change = int(np.where(np.diff(np.sign(Lt_ipvalues)))[0])

RtIP_df = pd.DataFrame(list(zip(Rt_disvalue, Rt_dosevalue, Rt_ipvalues)), columns = [“Rt_dis”, “Rt_dose”, “f”(x)”])

LtIP_df = pd.DataFrame(list(zip(Lt_disvalue, Lt_dosevalue, Lt_ipvalues)), columns = [“Lt_dis”, “Lt_dose”, “f”(x)”])

Rt_RDV = (RtIP_df.ix[RtSign_Change, “Rt_dose”] + RtIP_df.ix[RtSign_Change+1, “Rt_dose”])/2

Lt_RDV = (LtIP_df.ix[LtSign_Change, “Lt_dose”] + LtIP_df.ix[LtSign_Change+1, “Lt_dose”])/2

RDV = ((Rt_RDV)+ (Lt_RDV))/2

## Field Size

Rt_Fwidth = (RtIP_df.ix[RtSign_Change, “Rt_dis”] + RtIP_df.ix[RtSign_Change+1, “Rt_dis”])/2

Lt_Fwidth = (LtIP_df.ix[LtSign_Change, “Lt_dis”] + LtIP_df.ix[LtSign_Change+1, “Lt_dis”])/2

Field_Width = (Lt_Fwidth - Rt_Fwidth)

Field_Size = Field_Width/10

## Beam Penumbra

ZeroPoint = int(df1[df1[“Distance”] = = 0].index.values.astype(int))

Rt_X = X[0:ZeroPoint+1]

Rt_Y = Y[0:ZeroPoint+1]

Rt_df = pd.DataFrame(list(zip(Rt_X, Rt_Y)), columns=[“Rt_X”, “Rt_Y”])

Rt_Pa = 1.6*Rt_RDV

Rt_Pb = 0.4*Rt_RDV

Lt_X = X[ZeroPoint:len(X)]

Lt_Y = Y[ZeroPoint:len(X)]

Lt_df = pd.DataFrame(list(zip(Lt_X, Lt_Y)), columns=[“Lt_X”, “Lt_Y”])

Lt_Pa = 1.6*Lt_RDV

Lt_Pb = 0.4*Lt_RDV

pa = []

pb = []

for value in Rt_Y:

if value >= Rt_Pa:

pa = Rt_df[Rt_df[“Rt_Y”] = = value].index.values.astype(int)

break

for value in Rt_Y:

if value >= Rt_Pb:

pb = Rt_df[Rt_df[“Rt_Y”] = = value].index.values.astype(int)

break

pa_Rt = (Rt_df.ix[int(pa), “Rt_X”] + Rt_df.ix[int(pa-1), “Rt_X”])/2

pb_Rt = (Rt_df.ix[int(pb), “Rt_X”] + Rt_df.ix[int(pb-1), “Rt_X”])/2

Rt_penumbra = (pb_Rt - pa_Rt)

for value in Lt_Y:

if value <= Lt_Pa:

pa = Lt_df[Lt_df[“Lt_Y”] = = value].index.values.astype(int)

break

for value in Lt_Y:

if value <= Lt_Pb:

pb = Lt_df[Lt_df[“Lt_Y”] = = value].index.values.astype(int)

break

pa_Lt = (Lt_df.ix[int(pa-1), “Lt_X”] + Lt_df.ix[int(pa), “Lt_X”])/2

pb_Lt = (Lt_df.ix[int(pb-1), “Lt_X”] + Lt_df.ix[int(pb), “Lt_X”])/2

Lt_penumbra = (pb_Lt - pa_Lt)

print(Data)

print(“Right IP=”, Rt_RDV)

print(“Left IP=”, Lt_RDV)

print(“Average RDV=”, RDV)

print(“Field Size=”, Field_Size, “cm”)

print(“Rt Penumbra=”, Rt_penumbra, “mm”)

print(“Lt Penumbra=”, Lt_penumbra, “mm”)

###### Plotting Graph ###########################

fig = plt.figure()

graph = fig.add_subplot(1, 1, 1)

graph.spines[’left’].set_position((’data’, 0.0))

graph.set_xlim(-150, 150)

graph.set_ylim(-5, 100)

major_xticks = np.arange(-150, 150, 10)

major_yticks = np.arange(-5, 105, 5)

minor_xticks = np.arange(-150, 150, 1)

minor_yticks = np.arange(-5, 105, 1)

graph.set_xticks(major_xticks)

graph.set_xticks(minor_xticks, minor=True)

graph.set_yticks(major_yticks)

graph.set_yticks(minor_yticks, minor=True)

plt.grid(b=True, which=’major’, color=’black’, linestyle=’-’)

plt.grid(b=True, which=’minor’, color=’red’, linestyle=’-’)

plt.plot(X, Y, label=“Beam Profile”, color=“blue”, linewidth=0.5, marker=“*”, ms=1)

plt.plot(X2, Y2, label=“Inflection Points”, color=“black”, linewidth=0.5, marker=“*”, ms=1)

plt.xlabel(“Distance from central axis (cm)”)

plt.ylabel(“% Relative Dose”)

plt.title(Profile.name)

plt.legend()

plt.show()

root.mainloop()

####################### End of program code ##########################