Conc2DROSignal.py

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Mar 10 15:41:01 2021

@author: eveshalom
"""

import numpy as np
from plots_and_filters import MedianFilter

def createR10_withref(S0ref,S0,Tr,fa,T1ref,datashape):
    R10_ref = 1/T1ref
    ref_frac = (1-np.cos(fa)*np.exp(-Tr*R10_ref))/(1-np.exp(-Tr*R10_ref))
    R10 = (-1/Tr)*np.log((S0-(ref_frac*S0ref))/((S0*np.cos(fa))-(ref_frac*S0ref)))
    R10 = np.tile(R10[:,:,:,np.newaxis],(1,1,1,datashape[-1]))
    return R10

def calcR1_R2(R10,R20st,r1,r2st,Ctiss):
    R1 = R10 + r1*Ctiss
    R2st = R20st + r2st*Ctiss
    return R1,R2st

def Conc2Sig_Linear(Tr,Te,fa,R1,R2st,S,scale,scalevisit1):
    dro_S =  ( (1-np.exp(-Tr*R1)) / (1-(np.cos(fa)*np.exp(-Tr*R1))) )  * (np.sin(fa)*np.exp(-Te*R2st))
    
    if scale == 1:
        ScaleConst = np.percentile(S,98)/np.percentile(dro_S,98)
    elif scale == 2:
        ScaleConst = scalevisit1
    
    dro_S = (dro_S * ScaleConst)
    return dro_S, ScaleConst


def STDmap(S,t0):
    stdev = np.std(S[:,:,:,0:t0],axis=3)
    return stdev

def addnoise(a,std,Sexact,Nt):
    from numpy.random import normal as gaussian
    std = np.tile(std[:,:,:,np.newaxis],(1,1,1,Nt))
    Snoise = abs(Sexact + (a * std * gaussian(0,1,Sexact.shape)))
    return Snoise