Commit 9c0ccc64 authored by Daniel Williams's avatar Daniel Williams
Browse files

Corrected a problem with the inlcination of Dimmelmeier waveforms.

parent c1a3fbc8

minke/sources.py

+20 −23
Original line number Diff line number Diff line
@@ -86,10 +86,10 @@ class Waveform(object): 
        """

        hp, hx, _, _ = self._generate(half=True)

        f, ax = plt.subplots(1,2)

        times = np.arange(0, self.hp.deltaT*len(self.hp.data.data), self.hp.deltaT)

        ax[0].plot(times, self.hp.data.data, label="+ polarisation")

        ax[0].plot(times, self.hx.data.data, label="x polarisation")

        ax[1].plot(self.hp.data.data, self.hx.data.data)

        times = np.arange(0, hp.deltaT*len(hp.data.data), hp.deltaT)

        ax[0].plot(times, hp.data.data, label="+ polarisation")

        ax[0].plot(times, hx.data.data, label="x polarisation")

        ax[1].plot(hp.data.data, hx.data.data)



    def _generate(self, rate=16384.0, half=False):

        """
@@ -117,29 +117,27 @@ class Waveform(object): 
            A copy of the strain in the x polarisation

        """

        row = self._row()

        print "_generate"

        print "Make row"

        self.swig_row = lalburst.CreateSimBurst()

        swig_row = lalburst.CreateSimBurst()

        for a in lsctables.SimBurstTable.validcolumns.keys():

            try:

                setattr(self.swig_row, a, getattr( row, a ))

                setattr(swig_row, a, getattr( row, a ))

            except AttributeError: continue

            except TypeError: 

                continue

        try:

            self.swig_row.numrel_data = row.numrel_data

            swig_row.numrel_data = row.numrel_data

        except:

            pass

        

        hp, hx = lalburst.GenerateSimBurst(self.swig_row, 1.0/rate)

        hp, hx = lalburst.GenerateSimBurst(swig_row, 1.0/rate)

        # FIXME: Totally inefficent --- but can we deep copy a SWIG SimBurst?

        # DW: I tried that, and it doesn't seem to work :/

        if not half :

            hp0, hx0 = lalburst.GenerateSimBurst(self.swig_row, 1.0/rate)

            hp0, hx0 = lalburst.GenerateSimBurst(swig_row, 1.0/rate)

        else:

            hp0, hx0 = hp, hx

        return hp, hx, hp0, hx0

        del(self.swig_row)

        del(swig_row)





    def _row(self, sim=None, slide_id=1):
@@ -445,7 +443,7 @@ class Supernova(Waveform): 
        Ixx, Ixy, Ixz, Iyy, Iyz, Izz = data[5:]



        # Make the new time vector for the requried sample rate

        target_times = np.arange(0, times[-1], 1.0/sample_rate)

        target_times = np.arange(times[0], times[-1], 1.0/sample_rate)



        # Prepare the output matrix

        output = np.zeros((len(target_times), 11))
@@ -515,7 +513,7 @@ class Scheidegger2010(Supernova): 
        if not os.path.isfile(decomposed_path) :

            decomposed = self.decompose(filepath, sample_rate = 16384.0, step_back = 0.01, distance = 10e-3)

            

            np.savetxt(decomposed_path, decomposed, header="# time (2,-2) (2,-1) (2,0) (2,1) (2,2)", fmt='%.8e')

            np.savetxt(decomposed_path, decomposed, header="time (2,-2) (2,-1) (2,0) (2,1) (2,2)", fmt='%.8e')

        

        self.params['numrel_data'] = decomposed_path
@@ -556,9 +554,9 @@ class Dimmelmeier08(Supernova): 
        if not decomposed_path : decomposed_path = filepath+".dec"

        if not os.path.isfile(decomposed_path) :

            decomposed = self.decompose(filepath, sample_rate = 16384.0, step_back = 0.01, distance = 10e-3)

            

            np.savetxt(decomposed_path, decomposed, header="# time (2,-2) (2,-1) (2,0) (2,1) (2,2)", fmt='%.8e')

        

            np.savetxt(decomposed_path, decomposed, header="time (2,-2) (2,-1) (2,0) (2,1) (2,2)", fmt='%.8e')

        self.params['phi']=0

        self.params['incl']=90

        self.params['numrel_data'] = decomposed_path

        

    def decompose(self, numrel_file, sample_rate = 16384.0, step_back = 0.01, distance = 10e-3):
@@ -578,7 +576,7 @@ class Dimmelmeier08(Supernova): 
           The amount of time, in seconds, of the data which should be included

           before the peak amplitude. Defaults to 0.01 sec.



        distance : float

        distance : fllal.MTSUN_SIoat

           The distance, in megaparsecs, from the observer at which the NR waveforms were

           simulated. Defaults to 10 kpc (i.e. 10e-3 Mpc).
@@ -591,20 +589,19 @@ class Dimmelmeier08(Supernova): 
        # Load the times from the file

        data = np.loadtxt(numrel_file)

        data = data.T

        times = data[0]

        times = data[0]*1e-3

        times -= times[0]

        

        # Load the hp components   

        strain = data[1]



        # Make the new time vector for the requried sample rate

        target_times = np.arange(0, times[-1], 1.0/sample_rate)

        target_times = np.arange(times[0], times[-1], 1.0/sample_rate)



        # Prepare the output matrix

        output = np.zeros((len(target_times), 11))



        # Add the times in to the first column of said matrix

        output[:, 0] = target_times

        output[:, 0] = target_times #/ lal.MTSUN_SI

        #

        # Resample to uniform spacing at 16384 kHz

        #
@@ -612,6 +609,6 @@ class Dimmelmeier08(Supernova): 
        #

        # Make the output, and rescale it into dimensionless strain values

        #

        output[:,5] = strain_new # * np.sqrt(lal.G_SI / lal.C_SI**4) #/lal.MRSUN_SI / ( distance * lal.PC_SI * 1e6)

        output[:,5] = strain_new #/  lal.MRSUN_SI #/ ( extract_dist * lal.PC_SI * 1.0e6) )



        return output

notebooks/Supernovae.ipynb

+45 −16

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