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Merge branch 'gwastro:master' into template_fits
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@ArthurTolley
ArthurTolley authored Mar 10, 2024
2 parents c367a6c + f35d04b commit befd1c4
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166 changes: 68 additions & 98 deletions pycbc/psd/analytical_space.py
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Original file line number Diff line number Diff line change
Expand Up @@ -29,7 +29,7 @@
"""

import numpy as np
from astropy import constants
from astropy.constants import c
from pycbc.psd.read import from_numpy_arrays


Expand All @@ -49,11 +49,11 @@ def psd_lisa_acc_noise(f, acc_noise_level=3e-15):
The PSD value or array for acceleration noise.
Notes
-----
Pease see Eq.(11-13) in <LISA-LCST-SGS-TN-001> for more details.
Please see Eq.(11-13) in <LISA-LCST-SGS-TN-001> for more details.
"""
s_acc = acc_noise_level**2 * (1+(4e-4/f)**2)*(1+(f/8e-3)**4)
s_acc_d = s_acc * (2*np.pi*f)**(-4)
s_acc_nu = (2*np.pi*f/constants.c.value)**2 * s_acc_d
s_acc_nu = (2*np.pi*f/c.value)**2 * s_acc_d

return s_acc_nu

Expand All @@ -74,10 +74,10 @@ def psd_lisa_oms_noise(f, oms_noise_level=15e-12):
The PSD value or array for OMS noise.
Notes
-----
Pease see Eq.(9-10) in <LISA-LCST-SGS-TN-001> for more details.
Please see Eq.(9-10) in <LISA-LCST-SGS-TN-001> for more details.
"""
s_oms_d = oms_noise_level**2 * (1+(2e-3/f)**4)
s_oms_nu = s_oms_d * (2*np.pi*f/constants.c.value)**2
s_oms_nu = s_oms_d * (2*np.pi*f/c.value)**2

return s_oms_nu

Expand All @@ -96,13 +96,13 @@ def lisa_psd_components(f, acc_noise_level=3e-15, oms_noise_level=15e-12):
Returns
-------
[low_freq_component, high_freq_component] : list
low_freq_component, high_freq_component :
The PSD value or array for acceleration and OMS noise.
"""
low_freq_component = psd_lisa_acc_noise(f, acc_noise_level)
high_freq_component = psd_lisa_oms_noise(f, oms_noise_level)

return [low_freq_component, high_freq_component]
return low_freq_component, high_freq_component


def omega_length(f, len_arm=2.5e9):
Expand All @@ -120,7 +120,7 @@ def omega_length(f, len_arm=2.5e9):
omega_len : float or numpy.array
The value of 2*pi*f*LISA_arm_length.
"""
omega_len = 2*np.pi*f * len_arm/constants.c.value
omega_len = 2*np.pi*f * len_arm/c.value

return omega_len

Expand Down Expand Up @@ -151,23 +151,18 @@ def analytical_psd_lisa_tdi_1p5_XYZ(length, delta_f, low_freq_cutoff,
The TDI-1.5 PSD (X,Y,Z channel) for LISA.
Notes
-----
Pease see Eq.(19) in <LISA-LCST-SGS-TN-001> for more details.
Please see Eq.(19) in <LISA-LCST-SGS-TN-001> for more details.
"""
len_arm = np.float64(len_arm)
acc_noise_level = np.float64(acc_noise_level)
oms_noise_level = np.float64(oms_noise_level)
psd = []
fr = np.linspace(low_freq_cutoff, (length-1)*2*delta_f, length)
for f in fr:
[s_acc_nu, s_oms_nu] = lisa_psd_components(
f, acc_noise_level, oms_noise_level)
omega_len = omega_length(f, len_arm)
psd.append(16*(np.sin(omega_len))**2 *
(s_oms_nu+s_acc_nu*(3+np.cos(omega_len))))
fseries = from_numpy_arrays(fr, np.array(psd),
length, delta_f, low_freq_cutoff)
s_acc_nu, s_oms_nu = lisa_psd_components(
fr, acc_noise_level, oms_noise_level)
omega_len = omega_length(fr, len_arm)
psd = 16*(np.sin(omega_len))**2 * (s_oms_nu+s_acc_nu*(3+np.cos(omega_len)))

return fseries
return from_numpy_arrays(fr, psd, length, delta_f, low_freq_cutoff)


def analytical_psd_lisa_tdi_2p0_XYZ(length, delta_f, low_freq_cutoff,
Expand Down Expand Up @@ -196,23 +191,19 @@ def analytical_psd_lisa_tdi_2p0_XYZ(length, delta_f, low_freq_cutoff,
The TDI-2.0 PSD (X,Y,Z channel) for LISA.
Notes
-----
Pease see Eq.(20) in <LISA-LCST-SGS-TN-001> for more details.
Please see Eq.(20) in <LISA-LCST-SGS-TN-001> for more details.
"""
len_arm = np.float64(len_arm)
acc_noise_level = np.float64(acc_noise_level)
oms_noise_level = np.float64(oms_noise_level)
psd = []
fr = np.linspace(low_freq_cutoff, (length-1)*2*delta_f, length)
for f in fr:
[s_acc_nu, s_oms_nu] = lisa_psd_components(
f, acc_noise_level, oms_noise_level)
omega_len = omega_length(f, len_arm)
psd.append(64*(np.sin(omega_len))**2 * (np.sin(2*omega_len))**2 *
(s_oms_nu+s_acc_nu*(3+np.cos(2*omega_len))))
fseries = from_numpy_arrays(fr, np.array(psd),
length, delta_f, low_freq_cutoff)
s_acc_nu, s_oms_nu = lisa_psd_components(
fr, acc_noise_level, oms_noise_level)
omega_len = omega_length(fr, len_arm)
psd = (64*(np.sin(omega_len))**2 * (np.sin(2*omega_len))**2 *
(s_oms_nu+s_acc_nu*(3+np.cos(2*omega_len))))

return fseries
return from_numpy_arrays(fr, psd, length, delta_f, low_freq_cutoff)


def analytical_csd_lisa_tdi_1p5_XY(length, delta_f, low_freq_cutoff,
Expand Down Expand Up @@ -241,22 +232,19 @@ def analytical_csd_lisa_tdi_1p5_XY(length, delta_f, low_freq_cutoff,
The CSD between LISA's TDI-1.5 channel X and Y.
Notes
-----
Pease see Eq.(56) in <LISA-LCST-SGS-MAN-001(Radler)> for more details.
Please see Eq.(56) in <LISA-LCST-SGS-MAN-001(Radler)> for more details.
"""
len_arm = np.float64(len_arm)
acc_noise_level = np.float64(acc_noise_level)
oms_noise_level = np.float64(oms_noise_level)
csd = []
fr = np.linspace(low_freq_cutoff, (length-1)*2*delta_f, length)
for f in fr:
omega_len = omega_length(f, len_arm)
[s_acc_nu, s_oms_nu] = lisa_psd_components(
f, acc_noise_level, oms_noise_level)
csd.append(-8*np.sin(omega_len)**2 * np.cos(omega_len) *
(s_oms_nu+4*s_acc_nu))
fseries = from_numpy_arrays(fr, np.array(csd),
length, delta_f, low_freq_cutoff)
return fseries
s_acc_nu, s_oms_nu = lisa_psd_components(
fr, acc_noise_level, oms_noise_level)
omega_len = omega_length(fr, len_arm)
csd = (-8*np.sin(omega_len)**2 * np.cos(omega_len) *
(s_oms_nu+4*s_acc_nu))

return from_numpy_arrays(fr, csd, length, delta_f, low_freq_cutoff)


def analytical_psd_lisa_tdi_1p5_AE(length, delta_f, low_freq_cutoff,
Expand Down Expand Up @@ -285,24 +273,20 @@ def analytical_psd_lisa_tdi_1p5_AE(length, delta_f, low_freq_cutoff,
The PSD of LISA's TDI-1.5 channel A and E.
Notes
-----
Pease see Eq.(58) in <LISA-LCST-SGS-MAN-001(Radler)> for more details.
Please see Eq.(58) in <LISA-LCST-SGS-MAN-001(Radler)> for more details.
"""
len_arm = np.float64(len_arm)
acc_noise_level = np.float64(acc_noise_level)
oms_noise_level = np.float64(oms_noise_level)
psd = []
fr = np.linspace(low_freq_cutoff, (length-1)*2*delta_f, length)
for f in fr:
[s_acc_nu, s_oms_nu] = lisa_psd_components(
f, acc_noise_level, oms_noise_level)
omega_len = omega_length(f, len_arm)
psd.append(8*(np.sin(omega_len))**2 *
(4*(1+np.cos(omega_len)+np.cos(omega_len)**2)*s_acc_nu +
(2+np.cos(omega_len))*s_oms_nu))
fseries = from_numpy_arrays(fr, np.array(psd),
length, delta_f, low_freq_cutoff)
s_acc_nu, s_oms_nu = lisa_psd_components(
fr, acc_noise_level, oms_noise_level)
omega_len = omega_length(fr, len_arm)
psd = (8*(np.sin(omega_len))**2 *
(4*(1+np.cos(omega_len)+np.cos(omega_len)**2)*s_acc_nu +
(2+np.cos(omega_len))*s_oms_nu))

return fseries
return from_numpy_arrays(fr, psd, length, delta_f, low_freq_cutoff)


def analytical_psd_lisa_tdi_1p5_T(length, delta_f, low_freq_cutoff,
Expand Down Expand Up @@ -331,23 +315,19 @@ def analytical_psd_lisa_tdi_1p5_T(length, delta_f, low_freq_cutoff,
The PSD of LISA's TDI-1.5 channel T.
Notes
-----
Pease see Eq.(59) in <LISA-LCST-SGS-MAN-001(Radler)> for more details.
Please see Eq.(59) in <LISA-LCST-SGS-MAN-001(Radler)> for more details.
"""
len_arm = np.float64(len_arm)
acc_noise_level = np.float64(acc_noise_level)
oms_noise_level = np.float64(oms_noise_level)
psd = []
fr = np.linspace(low_freq_cutoff, (length-1)*2*delta_f, length)
for f in fr:
[s_acc_nu, s_oms_nu] = lisa_psd_components(
f, acc_noise_level, oms_noise_level)
omega_len = omega_length(f, len_arm)
psd.append(32*np.sin(omega_len)**2 * np.sin(omega_len/2)**2 *
(4*s_acc_nu*np.sin(omega_len/2)**2 + s_oms_nu))
fseries = from_numpy_arrays(fr, np.array(psd),
length, delta_f, low_freq_cutoff)
s_acc_nu, s_oms_nu = lisa_psd_components(
fr, acc_noise_level, oms_noise_level)
omega_len = omega_length(fr, len_arm)
psd = (32*np.sin(omega_len)**2 * np.sin(omega_len/2)**2 *
(4*s_acc_nu*np.sin(omega_len/2)**2 + s_oms_nu))

return fseries
return from_numpy_arrays(fr, psd, length, delta_f, low_freq_cutoff)


def averaged_lisa_fplus_sq_approx(f, len_arm=2.5e9):
Expand All @@ -367,7 +347,7 @@ def averaged_lisa_fplus_sq_approx(f, len_arm=2.5e9):
The sky and polarization angle averaged squared antenna response.
Notes
-----
Pease see Eq.(36) in <LISA-LCST-SGS-TN-001> for more details.
Please see Eq.(36) in <LISA-LCST-SGS-TN-001> for more details.
"""
from scipy.interpolate import interp1d
from astropy.utils.data import download_file
Expand Down Expand Up @@ -405,7 +385,7 @@ def averaged_response_lisa_tdi_1p5(f, len_arm=2.5e9):
The sky and polarization angle averaged TDI-1.5 response to GW.
Notes
-----
Pease see Eq.(39) in <LISA-LCST-SGS-TN-001> for more details.
Please see Eq.(39) in <LISA-LCST-SGS-TN-001> for more details.
"""
omega_len = omega_length(f, len_arm)
ave_fp2 = averaged_lisa_fplus_sq_approx(f, len_arm)
Expand All @@ -431,7 +411,7 @@ def averaged_response_lisa_tdi_2p0(f, len_arm=2.5e9):
The sky and polarization angle averaged TDI-2.0 response to GW.
Notes
-----
Pease see Eq.(40) in <LISA-LCST-SGS-TN-001> for more details.
Please see Eq.(40) in <LISA-LCST-SGS-TN-001> for more details.
"""
omega_len = omega_length(f, len_arm)
response_tdi_1p5 = averaged_response_lisa_tdi_1p5(f, len_arm)
Expand Down Expand Up @@ -469,21 +449,19 @@ def sensitivity_curve_lisa_semi_analytical(length, delta_f, low_freq_cutoff,
LISA's sensitivity curve (6-links).
Notes
-----
Pease see Eq.(42-43) in <LISA-LCST-SGS-TN-001> for more details.
Please see Eq.(42-43) in <LISA-LCST-SGS-TN-001> for more details.
"""
sense_curve = []
len_arm = np.float64(len_arm)
acc_noise_level = np.float64(acc_noise_level)
oms_noise_level = np.float64(oms_noise_level)
fr = np.linspace(low_freq_cutoff, (length-1)*2*delta_f, length)
fp_sq = averaged_lisa_fplus_sq_approx(fr, len_arm)
for i in range(len(fr)):
[s_acc_nu, s_oms_nu] = lisa_psd_components(
fr[i], acc_noise_level, oms_noise_level)
omega_len = 2*np.pi*fr[i] * len_arm/constants.c.value
sense_curve.append((s_oms_nu + s_acc_nu*(3+np.cos(2*omega_len))) /
(omega_len**2*fp_sq[i]))
fseries = from_numpy_arrays(fr, np.array(sense_curve)/2,
s_acc_nu, s_oms_nu = lisa_psd_components(
fr, acc_noise_level, oms_noise_level)
omega_len = 2*np.pi*fr * len_arm/c.value
sense_curve = ((s_oms_nu + s_acc_nu*(3+np.cos(2*omega_len))) /
(omega_len**2*fp_sq))
fseries = from_numpy_arrays(fr, sense_curve/2,
length, delta_f, low_freq_cutoff)

return fseries
Expand All @@ -509,19 +487,15 @@ def sensitivity_curve_lisa_SciRD(length, delta_f, low_freq_cutoff):
LISA's sensitivity curve in SciRD.
Notes
-----
Pease see Eq.(114) in <LISA-LCST-SGS-TN-001> for more details.
Please see Eq.(114) in <LISA-LCST-SGS-TN-001> for more details.
"""
sense_curve = []
fr = np.linspace(low_freq_cutoff, (length-1)*2*delta_f, length)
for f in fr:
s_I = 5.76e-48 * (1+(4e-4/f)**2)
s_II = 3.6e-41
R = 1 + (f/2.5e-2)**2
sense_curve.append(10/3 * (s_I/(2*np.pi*f)**4+s_II) * R)
fseries = from_numpy_arrays(fr, sense_curve,
length, delta_f, low_freq_cutoff)
s_I = 5.76e-48 * (1+(4e-4/fr)**2)
s_II = 3.6e-41
R = 1 + (fr/2.5e-2)**2
sense_curve = 10/3 * (s_I/(2*np.pi*fr)**4+s_II) * R

return fseries
return from_numpy_arrays(fr, sense_curve, length, delta_f, low_freq_cutoff)


def sensitivity_curve_lisa_confusion(length, delta_f, low_freq_cutoff,
Expand Down Expand Up @@ -557,7 +531,7 @@ def sensitivity_curve_lisa_confusion(length, delta_f, low_freq_cutoff,
LISA's sensitivity curve with Galactic confusion noise.
Notes
-----
Pease see Eq.(85-86) in <LISA-LCST-SGS-TN-001> for more details.
Please see Eq.(85-86) in <LISA-LCST-SGS-TN-001> for more details.
"""
if base_model == "semi":
base_curve = sensitivity_curve_lisa_semi_analytical(
Expand All @@ -571,13 +545,11 @@ def sensitivity_curve_lisa_confusion(length, delta_f, low_freq_cutoff,
if duration < 0 or duration > 10:
raise Exception("Must between 0 and 10.")
fr = np.linspace(low_freq_cutoff, (length-1)*2*delta_f, length)
sh_confusion = []
f1 = 10**(-0.25*np.log10(duration)-2.7)
fk = 10**(-0.27*np.log10(duration)-2.47)
for f in fr:
sh_confusion.append(0.5*1.14e-44*f**(-7/3)*np.exp(-(f/f1)**1.8) *
(1.0+np.tanh((fk-f)/(0.31e-3))))
fseries_confusion = from_numpy_arrays(fr, np.array(sh_confusion),
sh_confusion = (0.5*1.14e-44*fr**(-7/3)*np.exp(-(fr/f1)**1.8) *
(1.0+np.tanh((fk-fr)/0.31e-3)))
fseries_confusion = from_numpy_arrays(fr, sh_confusion,
length, delta_f, low_freq_cutoff)
fseries = from_numpy_arrays(base_curve.sample_frequencies,
base_curve+fseries_confusion,
Expand Down Expand Up @@ -622,7 +594,7 @@ def sh_transformed_psd_lisa_tdi_XYZ(length, delta_f, low_freq_cutoff,
noise, transformed from LISA sensitivity curve.
Notes
-----
Pease see Eq.(7,41-43) in <LISA-LCST-SGS-TN-001> for more details.
Please see Eq.(7,41-43) in <LISA-LCST-SGS-TN-001> for more details.
"""
fr = np.linspace(low_freq_cutoff, (length-1)*2*delta_f, length)
if tdi == "1.5":
Expand Down Expand Up @@ -680,13 +652,11 @@ def semi_analytical_psd_lisa_confusion_noise(length, delta_f, low_freq_cutoff,
raise Exception("The version of TDI, currently only for 1.5 or 2.0.")
fseries_response = from_numpy_arrays(fr, np.array(response),
length, delta_f, low_freq_cutoff)
sh_confusion = []
f1 = 10**(-0.25*np.log10(duration)-2.7)
fk = 10**(-0.27*np.log10(duration)-2.47)
for f in fr:
sh_confusion.append(0.5*1.14e-44*f**(-7/3)*np.exp(-(f/f1)**1.8) *
(1.0+np.tanh((fk-f)/(0.31e-3))))
fseries_confusion = from_numpy_arrays(fr, np.array(sh_confusion),
sh_confusion = (0.5*1.14e-44*fr**(-7/3)*np.exp(-(fr/f1)**1.8) *
(1.0+np.tanh((fk-fr)/0.31e-3)))
fseries_confusion = from_numpy_arrays(fr, sh_confusion,
length, delta_f, low_freq_cutoff)
psd_confusion = 2*fseries_confusion.data * fseries_response.data
fseries = from_numpy_arrays(fseries_confusion.sample_frequencies,
Expand Down
2 changes: 0 additions & 2 deletions pycbc/results/render.py
View file
Original file line number Diff line number Diff line change
@@ -1,5 +1,3 @@
#!/usr/bin/python

# Copyright (C) 2015 Christopher M. Biwer
#
# This program is free software; you can redistribute it and/or modify it
Expand Down
20 changes: 3 additions & 17 deletions pycbc/results/versioning.py
View file
Original file line number Diff line number Diff line change
@@ -1,5 +1,3 @@
#!/usr/bin/python

# Copyright (C) 2015 Ian Harry
#
# This program is free software; you can redistribute it and/or modify it
Expand All @@ -20,8 +18,9 @@
import subprocess
import urllib.parse

import lal, lalframe
import pycbc.version, glue.git_version
import lal
import lalframe
import pycbc.version

def get_library_version_info():
"""This will return a list of dictionaries containing versioning
Expand Down Expand Up @@ -88,19 +87,6 @@ def add_info_new_version(info_dct, curr_module, extra_str):
pass
library_list.append(lalsimulationinfo)

glueinfo = {}
glueinfo['Name'] = 'LSCSoft-Glue'
glueinfo['ID'] = glue.git_version.id
glueinfo['Status'] = glue.git_version.status
glueinfo['Version'] = glue.git_version.version
glueinfo['Tag'] = glue.git_version.tag
glueinfo['Author'] = glue.git_version.author
glueinfo['Builder'] = glue.git_version.builder
glueinfo['Branch'] = glue.git_version.branch
glueinfo['Committer'] = glue.git_version.committer
glueinfo['Date'] = glue.git_version.date
library_list.append(glueinfo)

pycbcinfo = {}
pycbcinfo['Name'] = 'PyCBC'
pycbcinfo['ID'] = pycbc.version.version
Expand Down
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