The design sensitivity noise curve for the advanced LIGO detector is available in the ifo.AdvancedLIGO class, and it can be used in a program by assigning the class to a variable:
aligo = ifo.AdvancedLIGO()
gravpy.interferometers.
AdvancedLIGO
(frequencies=None, configuration=None, obs_time=None)[source]¶The advanced LIGO Interferometer.
Supported configurations are
Configuration 
Description 

O1 
First observing run sensitivity 
A+ 
The advancedplus design sensitivity 
See also
InitialLIGO
The initial LIGO interferometer
Examples
Specific configurations can be loaded by passing the configuration keyword argument.
>>> aligo = ifo.AdvancedLIGO(configuration="O1")
It’s straightforward to plot the sensitivity curve for the detector at design sensitivity.
>>> import matplotlib.pyplot as plt
>>> import gravpy.interferometers as ifo
>>> aligo = ifo.AdvancedLIGO()
>>> f, ax = plt.subplots(1)
>>> aligo.plot(ax)
Which should produce an output along the lines of
(Source code, png)
A specific configuration for a given interferometer. This allows for the sensitivity from a given run to be used, or from a specific tuning.
Methods

Produce the antenna pattern for a detector, given its detector tensor, and a set of angles. 

Produce the sensitivity curve of the detector in terms of the energy density. 

The noise amplitude for a detector is defined as \(h^2_n(f) = f S_n(f)\) and is designed to incorporate the effect of integrating an inspiralling signal. 

Plot the noise curve for this detector. 

Calculate the onesided power spectral desnity for a detector. 

Produce a skymap of the antenna repsonse of the interferometer. 

The squareroot of the PSD. 
noise_spectrum 
The design sensitivity of advanced Virgo is available in gravpy using the AdvancedVirgo class.
gravpy.interferometers.
LISA
(frequencies=None, configuration=None, obs_time=None)[source]¶The LISA Interferometer in its missionaccepted state, as of 2018
Methods

Produce the antenna pattern for a detector, given its detector tensor, and a set of angles. 

The noise created by unresolvable galactic binaries at low frequencies. 

Produce the sensitivity curve of the detector in terms of the energy density. 

Calculate the noise due to the singlelink optical metrology, from arxiv:1803.01944. 

The noise amplitude for a detector is defined as \(h^2_n(f) = f S_n(f)\) and is designed to incorporate the effect of integrating an inspiralling signal. 

Plot the noise curve for this detector. 

The power spectral density. 

The acceleration noise for a single test mass. 

Produce a skymap of the antenna repsonse of the interferometer. 

The squareroot of the PSD. 
gravpy.interferometers.
Decigo
(frequencies=None, configuration=None, obs_time=None)[source]¶The full, original Decigo noise curve, from arxiv:1101.3940.
Examples
(Source code, png)
Methods

Produce the antenna pattern for a detector, given its detector tensor, and a set of angles. 

Produce the sensitivity curve of the detector in terms of the energy density. 

The noise amplitude for a detector is defined as \(h^2_n(f) = f S_n(f)\) and is designed to incorporate the effect of integrating an inspiralling signal. 

Plot the noise curve for this detector. 

The power spectrum density of the detector, taken from equation 5 of arxiv:1101.3940. 

Produce a skymap of the antenna repsonse of the interferometer. 

The squareroot of the PSD. 
gravpy.interferometers.
BDecigo
(frequencies=None, configuration=None, obs_time=None)[source]¶The BDecigo noise curve [arxivcurve].
References
arxiv:1802.06977
Examples
(Source code, png)
Methods

Produce the antenna pattern for a detector, given its detector tensor, and a set of angles. 

Produce the sensitivity curve of the detector in terms of the energy density. 

The noise amplitude for a detector is defined as \(h^2_n(f) = f S_n(f)\) and is designed to incorporate the effect of integrating an inspiralling signal. 

Plot the noise curve for this detector. 

Calculate the onesided power spectral desnity for a detector. 

Produce a skymap of the antenna repsonse of the interferometer. 

The squareroot of the PSD. 