https://github.com/esheldon/meds

Python and C libraries to work with Multi Epoch Data Structures
https://github.com/esheldon/meds

astronomy python

Last synced: 11 days ago
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Python and C libraries to work with Multi Epoch Data Structures

• Host: GitHub
• URL: https://github.com/esheldon/meds
• Owner: esheldon
• License: gpl-3.0
• Created: 2013-04-02T18:36:20.000Z (over 11 years ago)
• Default Branch: master
• Last Pushed: 2023-10-20T16:56:25.000Z (about 1 year ago)
• Last Synced: 2024-10-19T20:47:06.692Z (19 days ago)
• Topics: astronomy, python
• Language: Python
• Size: 365 KB
• Stars: 8
• Watchers: 6
• Forks: 10
• Open Issues: 13
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
meds

====

A Python library to create and read Multi Epoch Data Structures. A minimal C

library is also provided for reading MEDS files

## Documentation

Full instructions for installing and using the python and C libraries are

here:

https://github.com/esheldon/meds/wiki

### A few examples for reading files

```python

import meds

# create a MEDS object for the given MEDS file

m = meds.MEDS(filename)

# read a cutout for object 35, cutout index 5

object_index = 35

cutout_index = 5

image = m.get_cutout(object_index, cutout_index)

# read the second cutout for this object

cutout_index = 1

im = m.get_cutout(object_index, cutout_index)

# get other image types

seg = m.get_cutout(object_index, cutout_index, type=’seg’)

wt = m.get_cutout(object_index, cutout_index, type=’weight’)

mask = m.get_cutout(object_index, cutout_index, type=’bmask’)

# get a python list of all cutouts for this object

imlist = m.get_cutout_list(object_index)

seglist = m.get_cutout_list(object_index, type=’seg’)

# The contents of the object data table is loaded when the MEDS object is

# created, and are accessible by name.

# number of cutouts

ncutout = m[’ncutout’][object_index]

for i in range(ncutout):

    cutout = m.get_cutout(object_index, i)

    # process the image

# get the jacobian of the WCS transformation

# as a dict

j = m.get_jacobian(object_index, cutout_index)

# as a numpy matrix

j = m.get_jacobian_matrix(object_index, cutout_index)

# list for all cutouts

jlist = m.get_jacobian_list(object_index)

# get the "ubserseg" weight map

wt = m.get_cweight_cutout_nearest(object_index, cutout_index)

```