data package

Submodules

data.tdi module

class data.tdi.TDIWaveformGen(T=1, sample_rate=0.1, tdi_gen=2, det='Taiji', t0=10000, use_gpu=True, orbit_file='../orbit/taiji-orbit.hdf5')

Bases: object

property Nf

The number of samples in the frequency domain.

property Nt

The number of samples in the time domain.

static PSD_Noise_X15(fr, sqSnoise, L_arm)

Calculates the X channel PSD of TDI1.0/1.5.

Parameters:
  • fr (float) – Frequency value.

  • sqSnoise (float) – Square root of the noise component.

  • L_arm (float) – Length of the arm.

Returns:

The calculated PSD value.

Return type:

float

static PSD_Noise_X20(fr, sqSnoise, L_arm)

Calculates the X channel PSD of TDI2.0.

Parameters:
  • fr (float) – Frequency value.

  • sqSnoise (float) – Square root of the noise component.

  • L_arm (float) – Length of the arm.

Returns:

The calculated PSD value.

Return type:

float

static PSD_Noise_XY15(fr, sqSnoise, L_arm)

Calculates the XY coorelation term of TDI1.0/1.5.

Parameters:
  • fr (float) – Frequency value.

  • sqSnoise (float) – Square root of the noise component.

  • L_arm (float) – Length of the arm.

Returns:

The calculated PSD value.

Return type:

float

static PSD_Noise_components(fr, sqSnoise)

Calculates the power spectral density (PSD) of acceleration noise and optical metrology system (OMS) noise.

Parameters:
  • fr (float) – The frequency at which the PSD is calculated.

  • sqSnoise (list) – A list containing the amplitude levels of acceleration noise and OMS noise.

Returns:

A list containing the PSD of acceleration noise and OMS noise.

Return type:

list

TDI(wave_gen, index_lambda, index_beta, remove_sky_coords=False, is_ecliptic_latitude=False, orbit_file='.', tdi_gen='2nd generation', t0=10000, tdi_chan='XYZ')

# 1st or 2nd or custom (see docs for custom) # tdi_gen = “2nd generation” # for GBWave # index_lambda = 6 # index_beta = 7

property delta_f

The frequency interval between samples.

property delta_t

The time interval between samples.

property f_max

Set the maximum frequency to half the sampling rate.

gen_noise()

Generates noise from a psd

get_psd()

Generates the PSD of the noise.

init_EMRI()

Initialize the EMRI waveform generator.

init_GB(VGB=True)

Initialize the GB waveform generator.

init_MBHB()

Initialize the MBHB waveform generator.

property sample_frequencies

Array of frequencies at which waveforms are sampled.

property sample_times

Array of times at which waveforms are sampled.

data.utils module

class data.utils.Constant

Bases: object

AU_SI = 149597870700.0
C_SI = 299792458.0
EPS = 1e-08
F0 = 3.168753578687779e-08
GAMMA = 0.5772156649015329
GMSUN = 1.3271244210789466e+20
G_SI = 6.67408e-11
H0 = 67.1
H0_SI = 2.1745629032171688e-18
INVSQRT2 = 0.7071067811865476
INVSQRT3 = 0.5773502691896257
INVSQRT6 = 0.408248290463863
INVSQRTPI = 0.5641895835477563
INVSQRTTWOPI = 0.3989422804014327
MRSUN_SI = 1476.6250615036158
MSUN_SI = 1.98848e+30
MTSUN_SI = 4.925491025873693e-06
Omega0 = 1.9909865927683788e-07
Omegalam = 0.6825
Omegam = 0.3175
PC_SI = 3.085677581491367e+16
PI = 3.141592653589793
PI_2 = 1.5707963267948966
PI_3 = 1.0471975511965979
PI_4 = 0.7853981633974483
SQRT2 = 1.4142135623730951
SQRT3 = 1.7320508075688772
SQRT6 = 2.449489742783178
SQRTPI = 1.772453850905516
SQRTTWOPI = 2.5066282746310007
YRSID_SI = 31558149.763545603

data.waveform module

class data.waveform.AAK(use_gpu=True, n_signal=1)

Bases: object

class data.waveform.GB(use_gpu=False, VGB=True)

Bases: object

read_catalog(cat_path)
class data.waveform.MBHB(f_min, T_buffer, buffer_ind, apx='SEOBNRv4_opt')

Bases: object

static m1_m2_from_M_Chirp_q(M_Chirp, q)
static m1_m2_from_M_q(M, q)

Compute individual masses from total mass and mass ratio.

Choose m1 >= m2.

Parameters:
  • mass (M {float} -- total)

  • ratio (q {mass ratio} -- mass)

  • 1.0 (0.0< q <=)

Returns:

(float, float) – (mass_1, mass_2)

Module contents