<filename>phenom/waveform/waveform.py<gh_stars>1-10
from phenom.utils.utils import M_eta_m1_m2, chipn, Constants
from numpy import cos

class Waveform(object):
    """docstring for Waveform
    p : dict
        dictionary of physical parameters:
        'mass1', 'mass2',
        'spin1x', 'spin1y', 'spin1z',
        'spin2x', 'spin2y', 'spin2z',
        'f_min', ,'f_max' 'delta_f',
        'theta_LN',
        'tc', 'phic', 'ra', 'dec', 'polarization',
        'approximant',
        'detectors'
        """
    # static element
    default_args = {'approximant':'IMRPhenomD',
                    'm1':50.,
                    'm2':50.,
                    'f_min':30.,
                    'chi1x':0.,
                    'chi1y':0.,
                    'chi1z':0.,
                    'chi2x':0.,
                    'chi2y':0.,
                    'chi2z':0.,
                    'inclination':0.,
                    'distance':1e6 * Constants.PC_SI,
                    'f_max':0.,
                    'fRef':0.,
                    'phiRef':0.,
                    'delta_f':1./2.,
                    'delta_t':1./2.}

    available_approximants = ['IMRPhenomD', 'IMRPhenomPv2_LAL']

    def __init__(self,
        approximant=default_args['approximant'],
        m1=default_args['m1'],
        m2=default_args['m2'],
        chi1x=default_args['chi1x'],
        chi1y=default_args['chi1y'],
        chi1z=default_args['chi1z'],
        chi2x=default_args['chi2x'],
        chi2y=default_args['chi2y'],
        chi2z=default_args['chi2z'],
        inclination=default_args['inclination'],
        distance=default_args['distance'],
        f_min=default_args['f_min'],
        f_max=default_args['f_max'],
        fRef=default_args['fRef'],
        phiRef=default_args['phiRef'],
        delta_f=default_args['delta_f'],
        delta_t=default_args['delta_t']):
        """
        input:
        approx (string) : default = 'IMRPhenomD'
        m1 (Msun)
        m2 (Msun)
        chi1z (dimensionless)
        chi2z (dimensionless)
        f_min (Hz)
        f_max (Hz)
        delta_f (sample rate Hz)
        distance (m) : Default 1e6 * Constants.PC_SI = 1 mega parsec
        fRef (reference frequency Hz)
        phiRef (orbital phase at fRef)"""

        # enforce m1 >= m2 and chi1 is on m1
        if m1<m2: # swap spins and masses
            # chi1z, chi2z = chi2z, chi1z
            chi1x, chi1y, chi1z, chi2x, chi2y, chi2z = chi2x, chi2y, chi2z, chi1x, chi1y, chi1z
            m1, m2 = m2, m1

        # put inputs into a dictionary
        #TODO: automate the names of the fields with values
        self.input_params                = {}
        self.input_params['approximant'] = approximant
        self.input_params['m1']          = float(m1)
        self.input_params['m2']          = float(m2)
        self.input_params['chi1x']       = float(chi1x)
        self.input_params['chi1y']       = float(chi1y)
        self.input_params['chi1z']       = float(chi1z)
        self.input_params['chi2x']       = float(chi2x)
        self.input_params['chi2y']       = float(chi2y)
        self.input_params['chi2z']       = float(chi2z)
        self.input_params['inclination'] = float(inclination)
        self.input_params['distance']    = float(distance)
        self.input_params['f_min']       = float(f_min)
        self.input_params['f_max']       = float(f_max)
        self.input_params['fRef']        = float(fRef)
        self.input_params['phiRef']      = float(phiRef)
        self.input_params['delta_f']     = float(delta_f)
        self.input_params['delta_t']     = float(delta_t)
        #TODO: It would be nicer if only variables that are needed
        #are defined. For examples only time domain approximants need
        #a 'delta_t'. It doesn't really mean anything for frequency domain.

        # print "calling _generate_fd_waveform"
        self._generate_fd_waveform(self.input_params)

    def _generate_fd_waveform(self, input_params):
        """
        here is where the main driver waveform functions are called
        from the 'Waveform' class.
        When a new approximant is added, add a conditional here.
        Also add it to the 'available_approximants' list at the top.

        input:
            input_params : dict
        """

        """
        From LALSimInspiral.c
        The non-precessing waveforms return h(f) for optimal orientation
        (i=0, Fp=1, Fc=0; Lhat pointed toward the observer)
        To get generic polarizations we multiply by inclination dependence
        and note hc(f) \propto -I * hp(f)
        Non-precessing waveforms multiply hp by pfac, hc by -I*cfac
        """
        cfac = cos(input_params['inclination']);
        pfac = 0.5 * (1. + cfac*cfac);

        if input_params['approximant'] == 'IMRPhenomD':
            #TODO: Add checks to say: if chi1x != 0 then abort and say 'error, this is a non-precessing approximant!'
            from phenom.waveform import PhenomD
            #NOTE: Here we do NOT use self.ph!! This means that if you want access to the
            #isntance attributes and variables from the PhenomD class, or indeed *any*
            #approximant class then you will need to generate an instance of the PhenomD
            #class. This can be changed if we want by replacing 'ph' with 'self.ph'
            #in the lines below.
            #I chose not to use 'self.ph' because I was afraid that the memory useage
            #might be double if I didn't.
            ph = PhenomD(m1=input_params['m1'], m2=input_params['m2'],
                        chi1z=input_params['chi1z'], chi2z=input_params['chi2z'],
                        f_min=input_params['f_min'], f_max=input_params['f_max'],
                        delta_f=input_params['delta_f'],
                        distance=input_params['distance'],
                        fRef=input_params['fRef'], phiRef=input_params['phiRef'],
                        finspin_func="FinalSpin0815")
            ph.IMRPhenomDGenerateFD()
            self.flist_Hz = ph.flist_Hz
            self.htilde   = ph.htilde
            #TODO: Check this by comparing with LAL!
            hptilde = self.htilde
            self.hctilde = -1.j * cfac * hptilde
            self.hptilde = pfac * hptilde

        elif input_params['approximant'] == 'IMRPhenomPv2_LAL':
            from phenom.waveform import PhenomP
            ph = PhenomP(m1=input_params['m1'], m2=input_params['m2'],
                        chi1x=input_params['chi1x'], chi1y=input_params['chi1y'], chi1z=input_params['chi1z'],
                        chi2x=input_params['chi2x'], chi2y=input_params['chi2y'], chi2z=input_params['chi2z'],
                        f_min=input_params['f_min'], f_max=input_params['f_max'],
                        delta_f=input_params['delta_f'],
                        distance=input_params['distance'],
                        fRef=input_params['fRef'], phiRef=input_params['phiRef'],
                        inclination=input_params['inclination'])
            self.flist_Hz = ph.flist_Hz
            self.hptilde = ph.hp
            self.hctilde = ph.hc

        else:
            raise NotImplementedError("approximant = {0} is not implemented. Available approximants = {1}".format(input_params['approximant'], self.available_approximants))

        # TODO: Need to add a master function to return hp and hx with appropriate
        # inclination angle and sin, cosine etc.

<filename>phenom/waveform/waveform.py<gh_stars>1-10
from phenom.utils.utils import M_eta_m1_m2, chipn, Constants
from numpy import cos

class Waveform(object):
    """docstring for Waveform
    p : dict
        dictionary of physical parameters:
        'mass1', 'mass2',
        'spin1x', 'spin1y', 'spin1z',
        'spin2x', 'spin2y', 'spin2z',
        'f_min', ,'f_max' 'delta_f',
        'theta_LN',
        'tc', 'phic', 'ra', 'dec', 'polarization',
        'approximant',
        'detectors'
        """
    # static element
    default_args = {'approximant':'IMRPhenomD',
                    'm1':50.,
                    'm2':50.,
                    'f_min':30.,
                    'chi1x':0.,
                    'chi1y':0.,
                    'chi1z':0.,
                    'chi2x':0.,
                    'chi2y':0.,
                    'chi2z':0.,
                    'inclination':0.,
                    'distance':1e6 * Constants.PC_SI,
                    'f_max':0.,
                    'fRef':0.,
                    'phiRef':0.,
                    'delta_f':1./2.,
                    'delta_t':1./2.}

    available_approximants = ['IMRPhenomD', 'IMRPhenomPv2_LAL']

    def __init__(self,
        approximant=default_args['approximant'],
        m1=default_args['m1'],
        m2=default_args['m2'],
        chi1x=default_args['chi1x'],
        chi1y=default_args['chi1y'],
        chi1z=default_args['chi1z'],
        chi2x=default_args['chi2x'],
        chi2y=default_args['chi2y'],
        chi2z=default_args['chi2z'],
        inclination=default_args['inclination'],
        distance=default_args['distance'],
        f_min=default_args['f_min'],
        f_max=default_args['f_max'],
        fRef=default_args['fRef'],
        phiRef=default_args['phiRef'],
        delta_f=default_args['delta_f'],
        delta_t=default_args['delta_t']):
        """
        input:
        approx (string) : default = 'IMRPhenomD'
        m1 (Msun)
        m2 (Msun)
        chi1z (dimensionless)
        chi2z (dimensionless)
        f_min (Hz)
        f_max (Hz)
        delta_f (sample rate Hz)
        distance (m) : Default 1e6 * Constants.PC_SI = 1 mega parsec
        fRef (reference frequency Hz)
        phiRef (orbital phase at fRef)"""

        # enforce m1 >= m2 and chi1 is on m1
        if m1<m2: # swap spins and masses
            # chi1z, chi2z = chi2z, chi1z
            chi1x, chi1y, chi1z, chi2x, chi2y, chi2z = chi2x, chi2y, chi2z, chi1x, chi1y, chi1z
            m1, m2 = m2, m1

        # put inputs into a dictionary
        #TODO: automate the names of the fields with values
        self.input_params                = {}
        self.input_params['approximant'] = approximant
        self.input_params['m1']          = float(m1)
        self.input_params['m2']          = float(m2)
        self.input_params['chi1x']       = float(chi1x)
        self.input_params['chi1y']       = float(chi1y)
        self.input_params['chi1z']       = float(chi1z)
        self.input_params['chi2x']       = float(chi2x)
        self.input_params['chi2y']       = float(chi2y)
        self.input_params['chi2z']       = float(chi2z)
        self.input_params['inclination'] = float(inclination)
        self.input_params['distance']    = float(distance)
        self.input_params['f_min']       = float(f_min)
        self.input_params['f_max']       = float(f_max)
        self.input_params['fRef']        = float(fRef)
        self.input_params['phiRef']      = float(phiRef)
        self.input_params['delta_f']     = float(delta_f)
        self.input_params['delta_t']     = float(delta_t)
        #TODO: It would be nicer if only variables that are needed
        #are defined. For examples only time domain approximants need
        #a 'delta_t'. It doesn't really mean anything for frequency domain.

        # print "calling _generate_fd_waveform"
        self._generate_fd_waveform(self.input_params)

    def _generate_fd_waveform(self, input_params):
        """
        here is where the main driver waveform functions are called
        from the 'Waveform' class.
        When a new approximant is added, add a conditional here.
        Also add it to the 'available_approximants' list at the top.

        input:
            input_params : dict
        """

        """
        From LALSimInspiral.c
        The non-precessing waveforms return h(f) for optimal orientation
        (i=0, Fp=1, Fc=0; Lhat pointed toward the observer)
        To get generic polarizations we multiply by inclination dependence
        and note hc(f) \propto -I * hp(f)
        Non-precessing waveforms multiply hp by pfac, hc by -I*cfac
        """
        cfac = cos(input_params['inclination']);
        pfac = 0.5 * (1. + cfac*cfac);

        if input_params['approximant'] == 'IMRPhenomD':
            #TODO: Add checks to say: if chi1x != 0 then abort and say 'error, this is a non-precessing approximant!'
            from phenom.waveform import PhenomD
            #NOTE: Here we do NOT use self.ph!! This means that if you want access to the
            #isntance attributes and variables from the PhenomD class, or indeed *any*
            #approximant class then you will need to generate an instance of the PhenomD
            #class. This can be changed if we want by replacing 'ph' with 'self.ph'
            #in the lines below.
            #I chose not to use 'self.ph' because I was afraid that the memory useage
            #might be double if I didn't.
            ph = PhenomD(m1=input_params['m1'], m2=input_params['m2'],
                        chi1z=input_params['chi1z'], chi2z=input_params['chi2z'],
                        f_min=input_params['f_min'], f_max=input_params['f_max'],
                        delta_f=input_params['delta_f'],
                        distance=input_params['distance'],
                        fRef=input_params['fRef'], phiRef=input_params['phiRef'],
                        finspin_func="FinalSpin0815")
            ph.IMRPhenomDGenerateFD()
            self.flist_Hz = ph.flist_Hz
            self.htilde   = ph.htilde
            #TODO: Check this by comparing with LAL!
            hptilde = self.htilde
            self.hctilde = -1.j * cfac * hptilde
            self.hptilde = pfac * hptilde

        elif input_params['approximant'] == 'IMRPhenomPv2_LAL':
            from phenom.waveform import PhenomP
            ph = PhenomP(m1=input_params['m1'], m2=input_params['m2'],
                        chi1x=input_params['chi1x'], chi1y=input_params['chi1y'], chi1z=input_params['chi1z'],
                        chi2x=input_params['chi2x'], chi2y=input_params['chi2y'], chi2z=input_params['chi2z'],
                        f_min=input_params['f_min'], f_max=input_params['f_max'],
                        delta_f=input_params['delta_f'],
                        distance=input_params['distance'],
                        fRef=input_params['fRef'], phiRef=input_params['phiRef'],
                        inclination=input_params['inclination'])
            self.flist_Hz = ph.flist_Hz
            self.hptilde = ph.hp
            self.hctilde = ph.hc

        else:
            raise NotImplementedError("approximant = {0} is not implemented. Available approximants = {1}".format(input_params['approximant'], self.available_approximants))

        # TODO: Need to add a master function to return hp and hx with appropriate
        # inclination angle and sin, cosine etc.

docstring for Waveform     p : dict         dictionary of physical parameters:         'mass1', 'mass2',         'spin1x', 'spin1y', 'spin1z',         'spin2x', 'spin2y', 'spin2z',         'f_min', ,'f_max' 'delta_f',         'theta_LN',         'tc', 'phic', 'ra', 'dec', 'polarization',         'approximant',         'detectors' # static element input:         approx (string) : default = 'IMRPhenomD'         m1 (Msun)         m2 (Msun)         chi1z (dimensionless)         chi2z (dimensionless)         f_min (Hz)         f_max (Hz)         delta_f (sample rate Hz)         distance (m) : Default 1e6 * Constants.PC_SI = 1 mega parsec         fRef (reference frequency Hz)         phiRef (orbital phase at fRef) # enforce m1 >= m2 and chi1 is on m1 # swap spins and masses # chi1z, chi2z = chi2z, chi1z # put inputs into a dictionary #TODO: automate the names of the fields with values #TODO: It would be nicer if only variables that are needed #are defined. For examples only time domain approximants need #a 'delta_t'. It doesn't really mean anything for frequency domain. # print "calling _generate_fd_waveform" here is where the main driver waveform functions are called         from the 'Waveform' class.         When a new approximant is added, add a conditional here.         Also add it to the 'available_approximants' list at the top.          input:             input_params : dict From LALSimInspiral.c         The non-precessing waveforms return h(f) for optimal orientation         (i=0, Fp=1, Fc=0; Lhat pointed toward the observer)         To get generic polarizations we multiply by inclination dependence         and note hc(f) \propto -I * hp(f)         Non-precessing waveforms multiply hp by pfac, hc by -I*cfac #TODO: Add checks to say: if chi1x != 0 then abort and say 'error, this is a non-precessing approximant!' #NOTE: Here we do NOT use self.ph!! This means that if you want access to the #isntance attributes and variables from the PhenomD class, or indeed *any* #approximant class then you will need to generate an instance of the PhenomD #class. This can be changed if we want by replacing 'ph' with 'self.ph' #in the lines below. #I chose not to use 'self.ph' because I was afraid that the memory useage #might be double if I didn't. #TODO: Check this by comparing with LAL! # TODO: Need to add a master function to return hp and hx with appropriate # inclination angle and sin, cosine etc.