def test_create_convolutionfunction(self):
cf = create_convolutionfunction_from_image(self.image, nz=1)
cf_image = convert_convolutionfunction_to_image(cf)
cf_image.data = numpy.real(cf_image.data)
if self.persist:
export_image_to_fits(
cf_image, "%s/test_convolutionfunction_cf.fits" % self.dir)
def test_readwriteconvolutionfunction(self):
im = create_test_image()
cf = create_convolutionfunction_from_image(im)
export_convolutionfunction_to_hdf5(cf, '%s/test_data_model_helpers_convolutionfunction.hdf' % self.dir)
newcf = import_convolutionfunction_from_hdf5('%s/test_data_model_helpers_convolutionfunction.hdf' % self.dir)
assert newcf.data.shape == cf.data.shape
assert numpy.max(numpy.abs(cf.data - newcf.data)) < 1e-15
def test_readwriteconvolutionfunction(self):
im = create_test_image()
cf = create_convolutionfunction_from_image(im)
config = {
"buffer": {
"directory": self.dir
},
"convolutionfunction": {
"name": "test_bufferconvolutionfunction.hdf",
"data_model": "ConvolutionFunction"
}
}
bdm = BufferConvolutionFunction(config["buffer"],
config["convolutionfunction"], cf)
bdm.sync()
new_bdm = BufferConvolutionFunction(config["buffer"],
config["convolutionfunction"])
new_bdm.sync()
newcf = bdm.memory_data_model
assert newcf.data.shape == cf.data.shape
assert numpy.max(numpy.abs(cf.data - newcf.data)) < 1e-15