<s> from mpl_toolkits . mplot3d import Axes3D <EOL> import matplotlib . pyplot as plt <EOL> import mpl_toolkits . mplot3d as m3d <EOL> import os <EOL> import numpy as np <EOL> from scipy import ndimage <EOL> from numpy import linalg <EOL> import nibabel <EOL> import splines_approximation_v2 as splinap <EOL> from sklearn . metrics import mean_squared_error <EOL> def returnSquaredErrors ( fname = None , div = None , size = None ) : <EOL> if fname == None : <EOL> fname = '<STR_LIT>' <EOL> file = nibabel . load ( fname ) <EOL> data = file . get_data ( ) <EOL> p1 , p2 , p3 = splinap . getPxDimensions ( fname ) <EOL> nx , ny , nz = splinap . getDim ( fname ) <EOL> print '<STR_LIT>' , nx , ny , nx <EOL> '''<STR_LIT>''' <EOL> X , Y , Z = ( data > <NUM_LIT:0> ) . nonzero ( ) <EOL> zmin = min ( Z ) + <NUM_LIT:10> <EOL> zmax = max ( Z ) - <NUM_LIT:10> <EOL> print "<STR_LIT>" , zmin <EOL> print "<STR_LIT>" , zmax <EOL> nz = zmax - zmin <EOL> x = [ <NUM_LIT:0> for iz in range ( <NUM_LIT:0> , nz , <NUM_LIT:1> ) ] <EOL> y = [ <NUM_LIT:0> for iz in range ( <NUM_LIT:0> , nz , <NUM_LIT:1> ) ] <EOL> z = [ iz for iz in range ( <NUM_LIT:0> , nz , <NUM_LIT:1> ) ] <EOL> for iz in range ( <NUM_LIT:0> , nz , <NUM_LIT:1> ) : <EOL> x [ iz ] , y [ iz ] = ndimage . measurements . center_of_mass ( np . array ( data [ : , : , iz + zmin ] ) ) <EOL> x_fit , y_fit = get_good_centerline ( nx , ny , nz ) <EOL> msx = mean_squared_error ( x , x_fit ) <EOL> msy = mean_squared_error ( y , y_fit ) <EOL> mean_ms = ( msx + msy ) / <NUM_LIT:2> <EOL> fig1 = plt . figure ( ) <EOL> ax = Axes3D ( fig1 ) <EOL> ax . plot ( x , y , z , zdir = '<STR_LIT:z>' ) <EOL> ax . plot ( x_fit , y_fit , z , zdir = '<STR_LIT:z>' ) <EOL> plt . show ( ) <EOL> print msx , msy , mean_ms <EOL> size_crop = splinap . getSize ( x , y , z , p1 , p2 , p3 ) <EOL> txt = open ( '<STR_LIT>' , '<STR_LIT:a>' ) <EOL> txt . write ( str ( div ) + '<STR_LIT:U+0020>' + str ( int ( round ( size ) ) / div ) + '<STR_LIT:U+0020>' + str ( size_crop ) + '<STR_LIT:U+0020>' + str ( size ) + '<STR_LIT:U+0020>' + str ( msx ) + '<STR_LIT:U+0020>' + str ( msy ) + '<STR_LIT:U+0020>' + '<STR_LIT:U+0020>' + str ( mean_ms ) + '<STR_LIT:U+0020>' + fname + '<STR_LIT:\n>' ) <EOL> txt . close ( ) <EOL> def get_good_centerline ( nx , ny , nz ) : <EOL> x = [ nx / <NUM_LIT:2> for iz in range ( <NUM_LIT:0> , nz , <NUM_LIT:1> ) ] <EOL> y = [ ny / <NUM_LIT:2> for iz in range ( <NUM_LIT:0> , nz , <NUM_LIT:1> ) ] <EOL> return x , y <EOL> def fit ( data , nz ) : <EOL> x = [ <NUM_LIT:0> for iz in range ( <NUM_LIT:0> , nz , <NUM_LIT:1> ) ] <EOL> y = [ <NUM_LIT:0> for iz in range ( <NUM_LIT:0> , nz , <NUM_LIT:1> ) ] <EOL> z = [ iz for iz in range ( <NUM_LIT:0> , nz , <NUM_LIT:1> ) ] <EOL> for iz in range ( <NUM_LIT:0> , nz , <NUM_LIT:1> ) : <EOL> x [ iz ] , y [ iz ] = ndimage . measurements . center_of_mass ( np . array ( data [ : , : , iz ] ) ) <EOL> print '<STR_LIT>' <EOL> coeffsx = np . polyfit ( z , x , <NUM_LIT:1> ) <EOL> polyx = np . poly1d ( coeffsx ) <EOL> x_fit = np . polyval ( polyx , z ) <EOL> print '<STR_LIT>' <EOL> print x_fit <EOL> print '<STR_LIT>' <EOL> coeffsy = np . polyfit ( z , y , <NUM_LIT:1> ) <EOL> polyy = np . poly1d ( coeffsy ) <EOL> y_fit = np . polyval ( polyy , z ) <EOL> fig1 = plt . figure ( ) <EOL> ax = Axes3D ( fig1 ) <EOL> ax . plot ( x , y , z , zdir = '<STR_LIT:z>' ) <EOL> ax . plot ( x_fit , y_fit , z , zdir = '<STR_LIT:z>' ) <EOL> plt . show ( ) <EOL> return x , y , x_fit , y_fit <EOL> if __name__ == "<STR_LIT:__main__>" : <EOL> returnSquaredErrors ( ) </s>
