LISA Instrument

Python package package simulating instrumental noises, the propagation of laser beams, the measurements and the on-board processing.

The default HDF5 measurement file has the following structure,

  |- ISI beatnote frequency (total, offsets, fluctuations), of shape (N), in Hz
  |  - isi_carrier_offsets
  |  - isi_carrier_fluctuations
  |  - isi_carriers
  |  - isi_usb_offsets
  |  - isi_usb_fluctuations
  |  - isi_usbs
  |
  |- ISI DWS measurements (in yaw and pitch), of shape (N), in rad
  |  - isi_dws_phis
  |  - isi_dws_etas
  |
  |- Measured pseudo-ranges (MPRs), of shape (N), in s
  |  - mprs
  |
  |- TMI beatnote frequency (total, offsets, fluctuations), of shape (N), in Hz
  |  - tmi_carrier_offsets
  |  - tmi_carrier_fluctuations
  |  - tmi_carriers
  |  - tmi_usb_offsets
  |  - tmi_usb_fluctuations
  |  - tmi_usbs
  |
  |- RFI beatnote frequency (total, offsets, fluctuations), of shape (N), in Hz
  |  - rfi_carrier_offsets
  |  - rfi_carrier_fluctuations
  |  - rfi_carriers
  |  - rfi_usb_offsets
  |  - rfi_usb_fluctuations
  |  - rfi_usbs
  |

If the keep_all option is set to True, the HDF5 measurement file also contains intermediary simulated quantities. Refer to Instrument.write() for more information.

Metadata are saved as attributes of the measurement file.

Please read carefully this README for more information. Documentation is available as docstring for instrumental simulation, for noise generation, for DSP tools, and for container classes.

Usage

Run a simulation

Make sure that Python 3.7 or newer is available, and install lisaconstants and lisainstrument using pip,

pip install git+https://gitlab.in2p3.fr/lisa-simulation/constants.git@latest
pip install git+https://gitlab.in2p3.fr/lisa-simulation/instrument.git@latest

You can run a simulation by creating an Instrument object and calling simulate().

from lisainstrument import Instrument
instrument = Instrument()
instrument.simulate()

You can parametrize the simulation by setting the desired arguments when instantiating your instrument, or by using the convenience methods,

instrument = Instrument(aafilter=None, dt=0.25, size=10000)
instrument.disable_all_noises(but='laser')
instrument.disable_dopplers()
instrument.simulate()

Set keep_all to True to keep in memory intermediary simulated quantities,

instrument.simulate(keep_all=True)

Write to a measurement file

You can write the results of a simulation to a measurement file (note that simulate() will be called before writing to disk if the simulation has not run yet),

instrument = Instrument()
instrument.write()

You can specify a path to the measurement file, and set keep_all to True to save intermediary simulated quantities,

instrument.write('my-file.h5', keep_all=True)

Plot measurements

Once the simulation has been run, can use convenience methods to plot all beatnote frequency offsets, beatnote frequency fluctuations, beatnote total frequencies, MPRs, or DWS measurements.

instrument.plot_offsets()
instrument.plot_fluctuations()
instrument.plot_totals()
instrument.plot_mprs()
instrument.plot_dws()

You can skip a number of samples at the beginning, and save the figures to disk,

instrument.plot_fluctuations(output='my-fluctuations.pdf', skip=500)

To plot quantities for all spacecraft or MOSAs, use the plot() method,

instrument.isi_carrier_fluctuations.plot(output='my-figure.png', title='ISI Carrier Fluctuations')

or use the usual Matplotlib functions with a single timeseries,

import matplotlib.pyplot as plt
plt.plot(instrument.t, instrument.isi_carrier_fluctuations['12'])
plt.show()

Contributing

Report an issue

We use the issue-tracking management system associated with the project provided by Gitlab. If you want to report a bug or request a feature, open an issue at https://gitlab.in2p3.fr/lisa-simulation/instrument/-/issues. You may also thumb-up or comment on existing issues.

Development environment

We strongly recommend to use Python virtual environments.

To setup the development environment, use the following commands:

git clone git@gitlab.in2p3.fr:lisa-simulation/instrument.git
cd instrument
python -m venv .
source ./bin/activate
python -m pip install --upgrade pip
python -m pip install -r requirements.txt

Workflow

The project's development workflow is based on the issue-tracking system provided by Gitlab, as well as peer-reviewed merge requests. This ensures high-quality standards.

Issues are solved by creating branches and opening merge requests. Only the assignee of the related issue and merge request can push commits on the branch. Once all the changes have been pushed, the "draft" specifier on the merge request is removed, and the merge request is assigned to a reviewer. He can push new changes to the branch, or request changes to the original author by re-assigning the merge request to them. When the merge request is accepted, the branch is merged onto master, deleted, and the associated issue is closed.

Pylint and unittest

We enforce PEP 8 (Style Guide for Python Code) with Pylint syntax checking, and correction of the code using the unittest testing framework. Both are implemented in the continuous integration system.

You can run them locally

pylint lisainstrument
python -m pytest

Authors

• Jean-Baptiste Bayle (j2b.bayle@gmail.com)
• Olaf Hartwig (olaf.hartwig@obspm.fr)
• Martin Staab (martin.staab@aei.mpg.de)

Acknowledgment

We are thankful to J. Waldmann for sharing his implementation of long power-law noise time series generators, based on Plaszczynski, S. (2005). Generating long streams of 1/f^alpha noise. J. Waldmann's pyplnoise module has been included in this project as a submodule. You can find the original project at https://github.com/janwaldmann/pyplnoise.