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Getting Started

  • Introduction
  • Setting up Python
    • Getting and installing conda on your machine
    • Setting up a conda environment
  • Setting up astrolab
    • Installation
    • Basic Usage

The Package

  • The astrolab package
    • astrolab.timing module
      • load_signal()
      • chunk_signal()
      • power_spectrum()
    • astrolab.imaging module
      • load_image()
      • display()
      • get_files()
      • stack_files()
      • stack()
      • flip()
      • crop()
      • shift()
      • rotate()
      • find_star()
      • display3D()
      • sort_astrophotos()
    • astrolab.spectroscopy module
      • find_angle()
      • rotate_spectrum()
      • crop_spectrum()
      • get_spectrum()
      • plot_ref()
      • plot_fraunhofer()
      • calibrate()
    • astrolab.photometry module
      • get_star_counts()
      • get_bkg_counts_pp()
      • get_bright_star_catalog()
      • get_star_data()
      • get_color_temperature_fits()
      • get_mags()
      • get_temp()
      • get_distances()
      • reject_outliers()

Tutorials

  • Tutorials
    • An “acoustic” binary
      • Loading the signal
      • Obtaining frequency information from our signal
        • Analysing a single “chunk” of data
        • Automatically chunking the signal
        • Finding the dominant frequency per chunk
      • Getting the distance ratio for our “binary”
      • Identifying the “ideal” chunk-size
      • Discussion
    • Basic image reduction
      • Loading a single light frame
      • Loading calibration frames
      • Stacking the calibration frames
      • Reducing the image
    • Basic image stacking
      • Loading the light frames
      • Naively stacking our lights
      • Stacking images using single-star alignment
        • Step 1: Find the location of a bright star in each image
        • Step 2: Find how much each image needs to be shifted
        • Step 3: Shift and stack the images
      • Cropping and analysing the final image
    • Characterising the solar spectrum
      • Loading the image data
      • Calibrating the spectrum
      • Testing our calibration
    • Stellar spectroscopy
      • Loading an image for spectroscopy
      • A brief overview of slitless spectroscopy
      • Producing an intensity profile
        • Subtracting the background
      • Calibrating your spectrum: going from pixels to Angstroms
        • Two-point calibration
        • One-point calibration
      • Discussion
    • Stellar photometry
      • Loading an image for photometry
      • Getting the relative magnitude of a star in one filter
        • Getting counts from the target star
          • Cropping the image
          • Performing aperture photometry
          • Identifying the background automagically
        • Getting counts of the reference star
        • Get magnitude of target star relative to the reference star
      • Repeating for multiple filters
      • Getting the absolute magnitude of a star
      • Getting the star’s effective temperature using a colour-temperature diagram
      • Discussion
Astrolab Documentation
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Revision 273461b6. Last updated on March 18, 2024.