Astronomical observation logging software
Project description
pydeepskylog
Table of Contents
Description
A Python package with utilities for deep-sky observations. This version of pydeepskylog provides the following functionality:
- Calculating of contrast reserve and optimal detection magnification for deep-sky objects.
- Conversion of magnitudes to SQM value and bortle scale and vice versa.
In the future, it will also include utilities for fetching and adding observation logs from/to the DeepSkyLog website.
Installation
pip install pydeepskylog
Usage
import pydeepskylog as pds
# Calculate contrast reserve
contrast_reserve = pds.contrast_reserve(sqm=22, telescope_diameter=457, magnification=118, magnitude=11, object_diameter1=600, object_diameter2=600)
print(contrast_reserve)
# Define a list of possible magnifications
possible_magnifications = [50, 100, 150, 200, 250]
# Calculate optimal detection magnification
optimal_detection_magnification = pds.optimal_detection_magnification(sqm=22, telescope_diameter=457, magnitude=11, object_diameter1=600, object_diameter2=600, magnifications=possible_magnifications)
print(optimal_detection_magnification)
# Convert naked eye limiting magnitude to SQM value
sqm = pds.nelm_to_sqm(5.8)
# Convert SQM value to naked eye limiting magnitude
nelm = pds.sqm_to_nelm(21.4)
# Convert Bortle scale to SQM value
print(pds.bortle_to_sqm(4))
# Convert SQM value to Bortle scale
print(pds.sqm_to_bortle(21.4))
# Convert naked eye limiting magnitude to bortle scale
print(pds.nelm_to_bortle(5.8))
# Convert bortle scale to naked eye limiting magnitude
print(pds.bortle_to_nelm(4))
Astronomical background
Contrast Reserve
The contrast reserve is a measure of the difference in brightness between the object and the sky background. It is calculated as the difference between the object's surface brightness and the sky background brightness. The contrast reserve is a useful metric for determining the visibility of deep sky objects through a telescope.
The higher the contrast reserve, the easier it is to see the object. The following table can be used to interpret the contrast reserve:
Contrast Reserve | Visibility | Typical color |
---|---|---|
< -0.2 | Not visible | dark grey |
-0.2 < CR < 0.1 | Questionable | light grey |
0.1 < CR < 0.35 | Difficult | dark red |
0.35 < CR < 0.5 | Quite difficult to see | light red |
0.5 < CR < 1.0 | Easy to see | dark green |
1.0 < CR | Very easy to see | light green |
The contrast reserved is calculated for the object as a whole. Smaller details in the object might be visible even if the contrast reserve of the object as a whole is below -0.2. This is certainly the case for galaxies, where the core might be much brighter than the outer regions.
It is important to note that the contrast reserve is a theoretical value and that the actual visibility of an object will depend on a number of other factors, including the observer's experience, the transparency of the sky, and the seeing conditions. The contrast reserve is just a guideline.
The calculation of the contrast reserve depends heavily on the quality of the object database. A small error in the object's magnitude or size can lead to a large error in the contrast reserve.
Only if the observer tries to observe the object, he/she will know if the object is visible or not.
Optimal Detection Magnification
The optimal detection magnification is the magnification at which the object is most easily visible. Take into account that the optimal detection magnification is not the same as the best magnification for observing details in an object, but for the object as a whole.
Magnitudes
Conversion methods are provided to convert magnitudes to SQM value and bortle scale and vice versa.
Different formulae are available to convert magnitudes to SQM value. The formula used here converts a sqm value of 22.0 to a naked eye limiting magnitude of 6.6. The faintest star offset can be given to the formula. If taking a value of -1.4 for the faintest star offset, the formula converts a sqm value of 22.0 to a naked eye limiting magnitude of 8.0.
Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
Please make sure to update tests as appropriate.
License
Acknowledgements
This package is inspired by the DeepskyLog website and the code is based on the formulas used in DeepskyLog. We would like to thank the DeepskyLog developers team.
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