User guide

ps_eor covers several related but independently useful areas of 21-cm analysis. The pages below are organized by topic: use only the part relevant to your work. Exact signatures and complete member lists are kept in the API reference.

Data and preparation

Create, inspect, combine, flag, and filter visibility data. These topics are useful whether or not the data will later be passed to the package’s power-spectrum or signal-separation tools.

• Data handling
  • Cartesian visibility cubes
  • Selecting frequencies and UV range
  • Creating a cube from FITS images
  • Creating a cube from an in-memory Kelvin image cube
  • Transforming, changing the field of view, and windowing
  • Stored metadata
  • Plotting and cube arithmetic
  • Weights and noise
  • Combining observations
• Flagging and spectral filtering
  • Flagger pipelines
  • High-pass filtering

Power spectra

Estimate spatial, cylindrical, spherical, auto, cross, and noise-debiased power spectra from compatible Cartesian or spherical cubes.

• Power-spectrum estimation
  • Building an estimator
  • Available products
  • A four-panel simulated example
  • Auto, cross, and noise-debiased spectra
  • Weighting and excluded regions

Signal separation

Use deterministic foreground models or ML-GPR posterior inference. ML-GPR has its own set of focused pages because it includes covariance construction, multiple inference methods, and posterior products.

• Foreground separation
  • Deterministic fitters
  • ML-GPR
• ML-GPR user guide
  • Migrating ML-GPR from 0.x to 1.0
  • Running an ML-GPR fit
  • Building the covariance model
  • Choosing an inference method
  • Posterior components and power spectra
  • Multi-epoch and Cross-GPR models
  • Tutorial notebooks

Instrument and observation simulation

Model telescope sensitivity, projected UV coverage, thermal-noise power, and power-spectrum sensitivity.

• Observation simulation and thermal noise
  • Instrument models
  • UV coverage
  • Noise power and sensitivity
  • Command-line simulation

Spherical and wide-field data

Represent wide-field observations with HEALPix maps and spherical-harmonic coefficients, combine them, and estimate their power spectra.

• Spherical and wide-field analysis
  • When to use spherical cubes
  • Converting Cartesian data
  • Combining and estimating power