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Big changes!
Output is now .fits formatted. Output contains backprojection, parameters, and i, j, theta arrays. Fast_hough is a faster thanks to einsum. Functions interpret() and viewer() are Non-Functional right now, so avoid -d.
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.gitignore

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## Project Specific
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#################
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lrginput/*
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*.pyc
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*.exe
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#################
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## Eclipse
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#################
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.project
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bin/
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tmp/
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*.bak
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*.swp
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*~.nib
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local.properties
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# External tool builders
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# Locally stored "Eclipse launch configurations"
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# CDT-specific
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#################
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[Tt]est[Rr]esult*/
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[Bb]uild[Ll]og.*
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#############
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## Python
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#############
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#*.py[co]
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*.pyc
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*.pyo
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*.c
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*.cpp
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*.html
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# Packages
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*.egg

README

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==================================
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Requirements (Python 2.7 Only)
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==================================
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from __future__ import division
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from __future__ import division #Must be first line of code in the file
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from astropy.io import fits
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#from scipy.stats import norm
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#from mpl_toolkits.mplot3d import Axes3D
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#from mayavi import mlab
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#from astropy import wcs
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import numpy as np
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import scipy.ndimage
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import math
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import os
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import matplotlib.pyplot as plt
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import sys
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import string
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import tempfile
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import shutil
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import time
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import fnmatch
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import matplotlib.pyplot as plt
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import numpy as np
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==================================
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Instructions For Use (Python)

batch1/smalltest_xyt00.fits

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batch1/smalltest_xyt01.fits

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batch1/test_xyt00.fits

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batch3/building.jpg

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cython_hough.pyx

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import numpy as np
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cimport numpy as np
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DTYPE = np.int
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ctypedef np.int_t DTYPE_t
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def fast_hough(np.ndarray in_arr, np.ndarray xyt):
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return np.einsum('ijk,ij', xyt, in_arr)
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