LSSTApplications  15.0+21,16.0+1,16.0+10,16.0+3,16.0+4,16.0-1-g2115a9e+4,16.0-1-g4515a79+8,16.0-1-g7bb14cc,16.0-1-g80120d7+6,16.0-1-g98efed3+6,16.0-1-gb7f560d+3,16.0-18-g7a076d417,16.0-2-g2ed7261+3,16.0-2-g311bfd2,16.0-2-g568a347+5,16.0-2-g7adb079,16.0-2-gd4c87cb+5,16.0-3-g099ede0,16.0-3-g150e024+5,16.0-3-g1f513a6+2,16.0-3-g958ce35,16.0-3-gc6a11d1,16.0-4-g84f75fb+7,16.0-4-gcfd1396+6,16.0-4-gde8cee2,16.0-5-g7bc0afb+5,16.0-5-g81851deb,16.0-5-g82b7855+1,16.0-5-gd32631f,16.0-5-gf14cb0b,16.0-6-g2dd73041+6,16.0-6-gcf12234+1,16.0-7-g95fb7bf+2,16.0-7-gc37dbc2+6,w.2018.28
LSSTDataManagementBasePackage
Namespaces | Functions
testUtils.py File Reference

Go to the source code of this file.

Namespaces

 lsst.afw.image.testUtils
 

Functions

def lsst.afw.image.testUtils.makeGaussianNoiseMaskedImage (dimensions, sigma, variance=1.0)
 
def lsst.afw.image.testUtils.makeRampImage (bbox, start=0, stop=None, imageClass=ImageF)
 Make an image whose values are a linear ramp. More...
 
def lsst.afw.image.testUtils.assertImagesAlmostEqual (testCase, image0, image1, skipMask=None, rtol=1.0e-05, atol=1e-08, msg="Images differ")
 Assert that two images are almost equal, including non-finite values. More...
 
def lsst.afw.image.testUtils.assertImagesEqual (args, kwds)
 Assert that two images are exactly equal, including non-finite values. More...
 
def lsst.afw.image.testUtils.assertMasksEqual (testCase, mask0, mask1, skipMask=None, msg="Masks differ")
 Assert that two masks are equal. More...
 
def lsst.afw.image.testUtils.assertMaskedImagesAlmostEqual (testCase, maskedImage0, maskedImage1, doImage=True, doMask=True, doVariance=True, skipMask=None, rtol=1.0e-05, atol=1e-08, msg="Masked images differ")
 Assert that two masked images are nearly equal, including non-finite values. More...
 
def lsst.afw.image.testUtils.assertMaskedImagesEqual (args, kwds)
 Assert that two masked images are exactly equal, including non-finite values. More...
 
def lsst.afw.image.testUtils.imagesDiffer (image0, image1, skipMask=None, rtol=1.0e-05, atol=1e-08)
 Compare the pixels of two image or mask arrays; return True if close, False otherwise. More...