# -*- coding: utf-8 -*-

"""

Created on Thu Nov 24 22:50:27 2016

@author: Shreyas_V

"""

import numpy as np

def accuracy(pred, orig_label, msk):

    '''  calculates complete accuracy

    INPUT: predicted labels, original labels, each 2D numpy arrays

    OUTPUT: float

    '''    

    acc = len(pred[(pred == orig_label) & msk])/float(len(msk[msk]))

    return acc

def DSC_en(pred, orig_label):

    TP = len(pred[(pred == 4) & (pred == orig_label)])

    denom = len(pred[(pred == 4) & msk]) + len (orig_label[(orig_label == 4)])

    if denom == 0:

        return 1.

    return 2.*TP/float(denom)

def DSC(pred, orig_label):

    ''' Calculates Dice Score Coefficient

    INPUT: predicted, original labels

    OUTPUT: float

    '''

    TP = len(pred[(pred != 0) & (orig_label != 0)])

    denom = len(pred[pred!=0]) + len(orig_label[orig_label != 0])

    if denom == 0:

        return 1

    return 2.*TP/float(denom)

def DSC_core_tumor(pred, orig_label):

    ''' Calculates DSC for core tumor (1, 3 and 4)

    INPUT: predicted, original labels

    OUTPUT: float

    '''

    TP = len(pred[((pred!=0) & (pred!=2)) & ((orig_label !=0) & (orig_label !=2))])

    denom = len(pred[pred[((pred!=0) & (pred!=2))]) + len(orig_label[(orig_label !=0) & (orig_label !=2)])

    if denom == 0:

        return 1

    return 2.*TP/float(denom)

def PPV(pred, orig_label):

    TP = len(pred[((pred!=0) & (pred!=2)) & ((orig_label !=0) & (orig_label !=2))])

    FP = len(pred[((pred!=0) & (pred!=2)) & ((orig_label ==0) | (orig_label ==2))])

    if TP == 0:

        return 0.

    return TP/float(TP+FP)