Astropy Python Full course On Mastering Astronomical Data analysis & Visualization | DESI ASTRO
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Astropy is a powerful and
Astropy is a powerful and widely-used library in Python, tailored specifically for astronomy and astrophysics. It provides a robust framework and tools for handling and analyzing astronomical data, making it an essential resource for astronomers and astrophysicists. Here is a more detailed look at Astropy and its applications:
Chapters Timestamp: All are independents
00:00:00 Introduction to Astropy
00:02:18 Astropy Library Installation
00:04:17 Read & Visualizing JWST FITS Image File
00:35:50 Read & Visualizing FITS Image Colormaps
00:44:14 Read & Visualizing SDSS Telescope FITS BOSS Spectra
01:09:00 Read & Visualizing SDSS Telescope FITS Image
01:32:38 Read & Visualizing SPITZER Telescope Optical FITS Image
01:52:45 Read & Visualizing ASTROSAT Telescope FUV FITS Image
02:24:08 Read & Visualizing HST Telescope FITS Image
02:48:25 Read & Visualizing HST Telescope FITS Spectra
03:07:27 Create RGB Colorful Image with FITS File
03:22:17 Read & Visualize FITS File Data Cube of SDSS-MANGA
03:46:30 Extracting FITS Data Cube Spectra & Import Into Files
04:12:56 2D Cutout of FITS image
04:35:55 Save Cutout Image Into FITS Image File
04:46:55 Constructing White Light Image from Data Cube
04:54:50 Contours Construction on FITS Image
05:04:42 Kernel Convolution With FITS image
05:22:36 Creating FITS 2D image with Header Information
05:36:02 Creating Multi-Extension FITS File with Image. Spectra & Data Cube
06:12:11 Creating FITS Data Table & Saving Into File
06:21:03 Creating FITS Spectra& Data table with Header Information
06:42:21 Astropy 1D Modeling: Linear Modeling
06:56:30 Astropy 1D Modeling: Gaussian Modeling
07:07:29 Zoom Plot of FITS Image File
07:23:13 Convert FITS Image Pixel(x,y) Into RA, DEC & Vice-Versa
07:29:51 Astropy 1D Convolution
07:42:26 Create Sub-Cube Fits Data Cube and Save Into FITS Data Cube
07:52:28 Astropy 1D Sigma Clipping
Key Components of Astropy
Core Package:
Units and Quantities: Handles physical units and quantities, allowing for seamless unit conversions and ensuring consistency in calculations.
Constants: Provides access to fundamental physical constants.
Time: Deals with time and date calculations, and conversions between different time systems (
Coordinates: Facilitates celestial coordinate transformations and representations (e.g., equatorial, galactic coordinates).
Data Handling:
Table: Provides flexible and powerful tools for handling tabular data, similar to pandas DataFrames but with features tailored for astronomy.
FITS (Flexible Image Transport System): Tools for reading, writing, and manipulating FITS files, the standard data format in astronomy.
Modeling: Tools for creating mathematical models and fitting them to data, including non-linear least squares fitting.
Visualization:
Plotting: Integrates with Matplotlib for creating visualizations, including specific tools for plotting astronomical data.
WCS (World Coordinate System):
Handles the conversion between pixel coordinates in images and real-world celestial coordinates.
Applications of Astropy
Data Analysis:
Astronomers use Astropy to analyze observational data, perform statistical analyses, and visualize results.
The Table and FITS modules are handy for manipulating and examining large datasets.
Coordinate Transformations:
Converting between different celestial coordinate systems is a common task in astronomy, and Astropy simplifies this process with its Coordinates module.
Cosmological Calculations:
Researchers use the Cosmology module to study the universe's expansion, calculate distances to celestial objects, and model cosmological phenomena.
Simulation and Modeling:
Astropy's modeling tools allow for creating and fitting complex models to observational data, which is crucial for understanding underlying astrophysical processes.
Time Series Analysis:
The Time module handles and converts between various time formats, essential for time-series analysis of variable stars, exoplanet transits, and other phenomena.
Data Integration and Interoperability:
#Python#PythonProgramming#PythonCourse#LearnPython#PythonTutorial#PythonDeveloper
#Programming #AstroPython #Astronomy #PythonAstronomy #AstroCoding #AstroData #AstroScience #AstroResearch #PythonInAstronomy #Astrophysics #DataScience #SpaceScience #AstroTools #AstroAnalysis #ScienceCoding #AstronomyData #AstroSoftware #AstroDev #PythonForScience #PythonResearch #SpaceTech #PythonForScience #PythonResearch #SpaceTech #FITSFiles #PythonFITS #AstroFITS #AstroDataAnalysis #AstroImaging #AstroDataProcessing
Storing and processing images captured by telescopes, such as sky surveys, galaxy images, and star fields.Spectroscopy:
Handling spectral data from instruments that analyze the light from astronomical objects.
Time-series Data:
Managing data that varies over time, such as light curves of variable stars.
Simulation Data:
Storing the results of simulations in astrophysics and cosmology.
Chapters Timestamp: All are independents
00:00:00 Introduction to Astropy
00:02:18 Astropy Library Installation
00:04:17 Read & Visualizing JWST FITS Image File
00:35:50 Read & Visualizing FITS Image Colormaps
00:44:14 Read & Visualizing SDSS Telescope FITS BOSS Spectra
01:09:00 Read & Visualizing SDSS Telescope FITS Image
01:32:38 Read & Visualizing SPITZER Telescope Optical FITS Image
01:52:45 Read & Visualizing ASTROSAT Telescope FUV FITS Image
02:24:08 Read & Visualizing HST Telescope FITS Image
02:48:25 Read & Visualizing HST Telescope FITS Spectra
03:07:27 Create RGB Colorful Image with FITS File
03:22:17 Read & Visualize FITS File Data Cube of SDSS-MANGA
03:46:30 Extracting FITS Data Cube Spectra & Import Into Files
04:12:56 2D Cutout of FITS image
04:35:55 Save Cutout Image Into FITS Image File
04:46:55 Constructing White Light Image from Data Cube
04:54:50 Contours Construction on FITS Image
05:04:42 Kernel Convolution With FITS image
05:22:36 Creating FITS 2D image with Header Information
05:36:02 Creating Multi-Extension FITS File with Image. Spectra & Data Cube
06:12:11 Creating FITS Data Table & Saving Into File
06:21:03 Creating FITS Spectra& Data table with Header Information
06:42:21 Astropy 1D Modeling: Linear Modeling
06:56:30 Astropy 1D Modeling: Gaussian Modeling
07:07:29 Zoom Plot of FITS Image File
07:23:13 Convert FITS Image Pixel(x,y) Into RA, DEC & Vice-Versa
07:29:51 Astropy 1D Convolution
07:42:26 Create Sub-Cube Fits Data Cube and Save Into FITS Data Cube
07:52:28 Astropy 1D Sigma Clipping
Key Components of Astropy
Core Package:
Units and Quantities: Handles physical units and quantities, allowing for seamless unit conversions and ensuring consistency in calculations.
Constants: Provides access to fundamental physical constants.
Time: Deals with time and date calculations, and conversions between different time systems (
Coordinates: Facilitates celestial coordinate transformations and representations (e.g., equatorial, galactic coordinates).
Data Handling:
Table: Provides flexible and powerful tools for handling tabular data, similar to pandas DataFrames but with features tailored for astronomy.
FITS (Flexible Image Transport System): Tools for reading, writing, and manipulating FITS files, the standard data format in astronomy.
Modeling: Tools for creating mathematical models and fitting them to data, including non-linear least squares fitting.
Visualization:
Plotting: Integrates with Matplotlib for creating visualizations, including specific tools for plotting astronomical data.
WCS (World Coordinate System):
Handles the conversion between pixel coordinates in images and real-world celestial coordinates.
Applications of Astropy
Data Analysis:
Astronomers use Astropy to analyze observational data, perform statistical analyses, and visualize results.
The Table and FITS modules are handy for manipulating and examining large datasets.
Coordinate Transformations:
Converting between different celestial coordinate systems is a common task in astronomy, and Astropy simplifies this process with its Coordinates module.
Cosmological Calculations:
Researchers use the Cosmology module to study the universe's expansion, calculate distances to celestial objects, and model cosmological phenomena.
Simulation and Modeling:
Astropy's modeling tools allow for creating and fitting complex models to observational data, which is crucial for understanding underlying astrophysical processes.
Time Series Analysis:
The Time module handles and converts between various time formats, essential for time-series analysis of variable stars, exoplanet transits, and other phenomena.
Data Integration and Interoperability:
#Python#PythonProgramming#PythonCourse#LearnPython#PythonTutorial#PythonDeveloper
#Programming #AstroPython #Astronomy #PythonAstronomy #AstroCoding #AstroData #AstroScience #AstroResearch #PythonInAstronomy #Astrophysics #DataScience #SpaceScience #AstroTools #AstroAnalysis #ScienceCoding #AstronomyData #AstroSoftware #AstroDev #PythonForScience #PythonResearch #SpaceTech #PythonForScience #PythonResearch #SpaceTech #FITSFiles #PythonFITS #AstroFITS #AstroDataAnalysis #AstroImaging #AstroDataProcessing
Storing and processing images captured by telescopes, such as sky surveys, galaxy images, and star fields.Spectroscopy:
Handling spectral data from instruments that analyze the light from astronomical objects.
Time-series Data:
Managing data that varies over time, such as light curves of variable stars.
Simulation Data:
Storing the results of simulations in astrophysics and cosmology.
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