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Tests pass locally
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Martin Beroiz committed Jun 6, 2016
1 parent 1cf2cc9 commit aec602c
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1 change: 1 addition & 0 deletions .gitignore
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@@ -1 +1,2 @@
*~
*.pyc
2 changes: 1 addition & 1 deletion .travis.yml
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Expand Up @@ -18,7 +18,7 @@ install:

script:
- python setup.py test
- coverage run --source=ois setup.py test
- coverage run --source=ois.py setup.py test

after_success:
- codecov
11 changes: 6 additions & 5 deletions ois.py
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@@ -1,5 +1,4 @@
"""@package ois
"""
Optimal Image Subtraction (OIS) module
--------------------------------------
Expand All @@ -20,13 +19,15 @@
* -h, --help: Prints this help and exits.
* -v, --version: Prints version information and exits.
Martin Beroiz - 2014
(c) Martin Beroiz
email: <martinberoiz@phys.utb.edu>
email: <martinberoiz@gmail.com>
University of Texas at San Antonio
"""

__version__ = '0.1a1'

import numpy as np
from scipy import signal
from scipy import ndimage
Expand Down Expand Up @@ -346,4 +347,4 @@ def subtractongrid(image, refimage, gausslist=None, bkgdegree=3,


if __name__ == '__main__':
pass
print(__doc__)
2 changes: 1 addition & 1 deletion setup.py
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@@ -1,7 +1,7 @@
from setuptools import setup

setup(name='ois',
version='0.1a0',
version='0.1a1',
description='Optimal Image Subtraction',
author='Martin Beroiz',
author_email='[email protected]',
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96 changes: 48 additions & 48 deletions tests/test_subtract.py
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@@ -1,5 +1,5 @@
import unittest
from ois import subtract
import ois
import numpy as np


Expand Down Expand Up @@ -94,15 +94,15 @@ def createkernel(coeffs, gausslist, kernelshape=(10, 10)):

def test_optimalkernelandbkg(self):
# Test Bramich
ruined_image, optKernel, bkg = subtract.optimalkernelandbkg(
ruined_image, optKernel, bkg = ois.optimalkernelandbkg(
self.image, self.ref_img, bkgdegree=self.bkgdeg,
kernelshape=(11, 11))
norm_diff = np.linalg.norm(ruined_image - self.image) \
/ np.linalg.norm(self.image)
self.assertLess(norm_diff, 1E-10)

# Test Alard & Lupton
ruined_image, optKernel, bkg = subtract.optimalkernelandbkg(
ruined_image, optKernel, bkg = ois.optimalkernelandbkg(
self.image, self.ref_img, gausslist=self.mygausslist,
bkgdegree=self.bkgdeg,
kernelshape=(11, 11))
Expand All @@ -114,20 +114,20 @@ def test_subtractongrid(self):

# Test without mask:
# Test Bramich
subt_img = subtract.subtractongrid(self.image, self.ref_img,
gausslist=None,
bkgdegree=self.bkgdeg,
kernelshape=(11, 11),
gridshape=(1, 1))
subt_img = ois.subtractongrid(self.image, self.ref_img,
gausslist=None,
bkgdegree=self.bkgdeg,
kernelshape=(11, 11),
gridshape=(1, 1))
norm_diff = np.linalg.norm(subt_img) / np.linalg.norm(self.image)
self.assertLess(norm_diff, 1E-10)

# Test Alard & Lupton
subt_img = subtract.subtractongrid(self.image, self.ref_img,
gausslist=self.mygausslist,
bkgdegree=self.bkgdeg,
kernelshape=(11, 11),
gridshape=(1, 1))
subt_img = ois.subtractongrid(self.image, self.ref_img,
gausslist=self.mygausslist,
bkgdegree=self.bkgdeg,
kernelshape=(11, 11),
gridshape=(1, 1))
norm_diff = np.linalg.norm(subt_img) / np.linalg.norm(self.image)
self.assertLess(norm_diff, 1E-10)

Expand All @@ -148,67 +148,67 @@ def test_subtractongrid(self):

# Test Bramich:
# Image masked, ref masked
subt_img = subtract.subtractongrid(image_masked, ref_img_masked,
gausslist=None,
bkgdegree=self.bkgdeg,
kernelshape=(11, 11),
gridshape=(1, 1))
subt_img = ois.subtractongrid(image_masked, ref_img_masked,
gausslist=None,
bkgdegree=self.bkgdeg,
kernelshape=(11, 11),
gridshape=(1, 1))
norm_diff = np.linalg.norm(subt_img.compressed()) \
/ np.linalg.norm(image_masked.compressed())
self.assertLess(norm_diff, 1E-10)
# Image not masked, ref masked
subt_img = subtract.subtractongrid(self.image, ref_img_masked,
gausslist=None,
bkgdegree=self.bkgdeg,
kernelshape=(11, 11),
gridshape=(1, 1))
subt_img = ois.subtractongrid(self.image, ref_img_masked,
gausslist=None,
bkgdegree=self.bkgdeg,
kernelshape=(11, 11),
gridshape=(1, 1))
norm_diff = np.linalg.norm(subt_img.compressed()) \
/ np.linalg.norm(self.image)
self.assertLess(norm_diff, 1E-10)
# Image masked, ref not masked
subt_img = subtract.subtractongrid(image_masked, self.ref_img,
gausslist=None,
bkgdegree=self.bkgdeg,
kernelshape=(11, 11),
gridshape=(1, 1))
subt_img = ois.subtractongrid(image_masked, self.ref_img,
gausslist=None,
bkgdegree=self.bkgdeg,
kernelshape=(11, 11),
gridshape=(1, 1))
norm_diff = np.linalg.norm(subt_img.compressed()) \
/ np.linalg.norm(image_masked.compressed())
self.assertLess(norm_diff, 1E-10)
# Image not masked, ref masked
subt_img = subtract.subtractongrid(self.image, ref_img_masked,
gausslist=None,
bkgdegree=self.bkgdeg,
kernelshape=(11, 11),
gridshape=(1, 1))
subt_img = ois.subtractongrid(self.image, ref_img_masked,
gausslist=None,
bkgdegree=self.bkgdeg,
kernelshape=(11, 11),
gridshape=(1, 1))
norm_diff = np.linalg.norm(subt_img.compressed()) \
/ np.linalg.norm(self.image)
self.assertLess(norm_diff, 1E-10)

# Test Alard & Lupton
# Image masked, ref masked
subt_img = subtract.subtractongrid(image_masked, ref_img_masked,
gausslist=self.mygausslist,
bkgdegree=self.bkgdeg,
kernelshape=(11, 11),
gridshape=(1, 1))
subt_img = ois.subtractongrid(image_masked, ref_img_masked,
gausslist=self.mygausslist,
bkgdegree=self.bkgdeg,
kernelshape=(11, 11),
gridshape=(1, 1))
norm_diff = np.linalg.norm(subt_img.compressed()) \
/ np.linalg.norm(image_masked.compressed())
self.assertLess(norm_diff, 1E-10)
# Image masked, ref not masked
subt_img = subtract.subtractongrid(image_masked, self.ref_img,
gausslist=self.mygausslist,
bkgdegree=self.bkgdeg,
kernelshape=(11, 11),
gridshape=(1, 1))
subt_img = ois.subtractongrid(image_masked, self.ref_img,
gausslist=self.mygausslist,
bkgdegree=self.bkgdeg,
kernelshape=(11, 11),
gridshape=(1, 1))
norm_diff = np.linalg.norm(subt_img.compressed()) \
/ np.linalg.norm(image_masked.compressed())
self.assertLess(norm_diff, 1E-10)
# Image not masked, ref masked
subt_img = subtract.subtractongrid(self.image, ref_img_masked,
gausslist=self.mygausslist,
bkgdegree=self.bkgdeg,
kernelshape=(11, 11),
gridshape=(1, 1))
subt_img = ois.subtractongrid(self.image, ref_img_masked,
gausslist=self.mygausslist,
bkgdegree=self.bkgdeg,
kernelshape=(11, 11),
gridshape=(1, 1))
norm_diff = np.linalg.norm(subt_img.compressed()) \
/ np.linalg.norm(self.image)
self.assertLess(norm_diff, 1E-10)
Expand Down

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