analysis.profiles.fieldseries.py

#!/usr/bin/env python3
import numpy as np,sys,image,seaborn as sns,plot,argparse,glob,pandas as pd
from os import path
from nki import plots
# from nki import runners

parser = argparse.ArgumentParser(description='specify mulitple mhd images to analyse')
parser.add_argument('--dir',default=r"Z:\brent\fieldseries\F180813B")
parser.add_argument('--noupdate',action='store_true')
opt = parser.parse_args()

# isoc in plan.dump. here multiplied y,z coords with -1.
if 'F180813B' in opt.dir:
    isoc = [0.165627,-16.8293,0.299999]
if 'F180823Q' in opt.dir:
    isoc = [3.71,-16.8293,0.299999]

print("isoc",isoc)

fname = path.join(opt.dir,'profile_plot')
setnames = ["2cm","23cm","3cm","4cm","5cm","6cm","8cm","10cm","15cm","20cm"] #23 is sorted here.

if not opt.noupdate:
    ## lets make csv
    imagefiles = sorted(glob.glob(path.join(opt.dir,"**","*dose.mhd"), recursive=True))
    try:
        assert(len(setnames)*2==len(imagefiles))
    except AssertionError as e:
        print(e)
        print(setnames)
        print(imagefiles)

    print([s+' '+i for s,i in zip(setnames,imagefiles[::2])])

    listoframes=[]
    for i,setname in enumerate(setnames):
        pin_im = image.image( imagefiles[int(2*i)] )
        gpumcd_im = image.image( imagefiles[int(2*i+1)] )
        print ('loading',imagefiles[int(2*i)],setname)

        isoc_index = pin_im.get_pixel_index([i*10 for i in isoc],False) #mm to cm, no halfpixel
        print ("isoc_index",isoc_index)

        py_x,py_y,py_z = pin_im.get_profiles_at_index(isoc_index)
        gy_x,gy_y,gy_z = gpumcd_im.get_profiles_at_index(isoc_index)

        x_x,x_y,x_z = pin_im.get_axes_labels()

        #alter axes labels to distance from isoc
        x_x = [x-isoc[0]*10 for x in x_x]
        x_y = [x-isoc[1]*10 for x in x_y]
        x_z = [x-isoc[2]*10 for x in x_z]

        y_xrel = ( gy_x - py_x ) / py_x
        y_xrat = gy_x / py_x

        columntitles = ["Setname","Generator","Axis",'Distance to isoc [mm]','Dose [cGy]']
        listoframes.append( plots.cols2dataframe(columntitles,x_x,py_x,metadata=[setname,'pinnacle','X']) )
        listoframes.append( plots.cols2dataframe(columntitles,x_y,py_y,metadata=[setname,'pinnacle','Y']) )
        listoframes.append( plots.cols2dataframe(columntitles,x_z,py_z,metadata=[setname,'pinnacle','Z']) )
        listoframes.append( plots.cols2dataframe(columntitles,x_x,gy_x,metadata=[setname,'gpumcd','X']) )
        listoframes.append( plots.cols2dataframe(columntitles,x_y,gy_y,metadata=[setname,'gpumcd','Y']) )
        listoframes.append( plots.cols2dataframe(columntitles,x_z,gy_z,metadata=[setname,'gpumcd','Z']) )
        listoframes.append( plots.cols2dataframe(columntitles,x_x,y_xrel,metadata=[setname,'reldiff','relY']) )
        listoframes.append( plots.cols2dataframe(columntitles,x_x,y_xrat,metadata=[setname,'ratio','ratY']) )

    df = pd.concat(listoframes)
    df.to_csv(fname+".csv")
    # print(df)

## lets plot csv
df = pd.read_csv(fname+".csv",index_col=0)

plots.fieldseries(df,fname)