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