import os import pytest import numpy as np from pynpoint.core.pypeline import Pypeline from pynpoint.readwrite.fitsreading import FitsReadingModule from pynpoint.processing.centering import StarAlignmentModule, ShiftImagesModule, \ WaffleCenteringModule, FitCenterModule from pynpoint.processing.extract import StarExtractionModule from pynpoint.processing.resizing import AddLinesModule from pynpoint.util.tests import create_config, create_star_data, create_waffle_data, \ remove_test_data class TestCentering: def setup_class(self) -> None: self.limit = 1e-10 self.test_dir = os.path.dirname(__file__) + '/' create_star_data(self.test_dir+'star') create_waffle_data(self.test_dir+'waffle') create_config(self.test_dir+'PynPoint_config.ini') self.pipeline = Pypeline(self.test_dir, self.test_dir, self.test_dir) def teardown_class(self) -> None: remove_test_data(path=self.test_dir, folders=['star', 'waffle']) def test_read_data(self) -> None: module = FitsReadingModule(name_in='read1', image_tag='star', input_dir=self.test_dir+'star', overwrite=True, check=True) self.pipeline.add_module(module) module = FitsReadingModule(name_in='read2', image_tag='waffle', input_dir=self.test_dir+'waffle', overwrite=True, check=True) self.pipeline.add_module(module) self.pipeline.run_module('read1') self.pipeline.run_module('read2') data = self.pipeline.get_data('star') assert np.sum(data) == pytest.approx(105.54278879805277, rel=self.limit, abs=0.) assert data.shape == (10, 11, 11) data = self.pipeline.get_data('waffle') assert np.sum(data) == pytest.approx(4.000000000000196, rel=self.limit, abs=0.) assert data.shape == (1, 101, 101) def test_star_extract(self) -> None: module = StarExtractionModule(name_in='extract1', image_in_tag='star', image_out_tag='extract1', index_out_tag='index', image_size=0.2, fwhm_star=0.1, position=None) self.pipeline.add_module(module) with pytest.warns(UserWarning) as warning: self.pipeline.run_module('extract1') assert len(warning) == 3 assert warning[0].message.args[0] == 'Can not store the attribute \'INSTRUMENT\' ' \ 'because the dataset \'index\' does not exist.' data = self.pipeline.get_data('extract1') assert np.sum(data) == pytest.approx(104.93318507061295, rel=self.limit, abs=0.) assert data.shape == (10, 9, 9) def test_star_align(self) -> None: module = StarAlignmentModule(name_in='align1', image_in_tag='extract1', ref_image_in_tag=None, image_out_tag='align1', accuracy=10, resize=2., num_references=10, subframe=None) self.pipeline.add_module(module) self.pipeline.run_module('align1') data = self.pipeline.get_data('align1') assert np.sum(data) == pytest.approx(104.7074742320535, rel=self.limit, abs=0.) assert data.shape == (10, 18, 18) def test_star_align_subframe(self) -> None: module = StarAlignmentModule(name_in='align2', image_in_tag='extract1', ref_image_in_tag=None, image_out_tag='align2', accuracy=10, resize=None, num_references=10, subframe=0.1) self.pipeline.add_module(module) self.pipeline.run_module('align2') data = self.pipeline.get_data('align2') assert np.sum(data) == pytest.approx(104.39031104541652, rel=self.limit, abs=0.) assert data.shape == (10, 9, 9) def test_star_align_ref(self) -> None: module = StarAlignmentModule(name_in='align3', image_in_tag='extract1', ref_image_in_tag='align2', image_out_tag='align3', accuracy=10, resize=None, num_references=10, subframe=None) self.pipeline.add_module(module) self.pipeline.run_module('align3') data = self.pipeline.get_data('align3') assert np.sum(data) == pytest.approx(104.46997194330757, rel=self.limit, abs=0.) assert data.shape == (10, 9, 9) def test_star_align_number_ref(self) -> None: module = StarAlignmentModule(name_in='align4', image_in_tag='extract1', ref_image_in_tag='align2', image_out_tag='align4', accuracy=10, resize=None, num_references=20, subframe=None) self.pipeline.add_module(module) with pytest.warns(UserWarning) as warning: self.pipeline.run_module('align4') assert len(warning) == 1 assert warning[0].message.args[0] == 'Number of available images (10) is smaller than ' \ 'num_references (20). Using all available images ' \ 'instead.' data = self.pipeline.get_data('align4') assert np.sum(data) == pytest.approx(104.46997194330757, rel=self.limit, abs=0.) assert data.shape == (10, 9, 9) def test_shift_images_spline(self) -> None: module = ShiftImagesModule(shift_xy=(1., 2.), interpolation='spline', name_in='shift1', image_in_tag='align1', image_out_tag='shift') self.pipeline.add_module(module) self.pipeline.run_module('shift1') data = self.pipeline.get_data('shift') assert np.sum(data) == pytest.approx(104.20425101355244, rel=self.limit, abs=0.) assert data.shape == (10, 18, 18) def test_shift_images_fft(self) -> None: module = ShiftImagesModule(shift_xy=(1., 2.), interpolation='fft', name_in='shift2', image_in_tag='align1', image_out_tag='shift_fft') self.pipeline.add_module(module) self.pipeline.run_module('shift2') data = self.pipeline.get_data('shift_fft') assert np.sum(data) == pytest.approx(104.7074742320535, rel=self.limit, abs=0.) assert data.shape == (10, 18, 18) def test_waffle_center_odd(self) -> None: module = AddLinesModule(name_in='add', image_in_tag='star', image_out_tag='star_add', lines=(45, 45, 45, 45)) self.pipeline.add_module(module) self.pipeline.run_module('add') data = self.pipeline.get_data('star_add') assert np.sum(data) == pytest.approx(105.54278879805278, rel=self.limit, abs=0.) assert data.shape == (10, 101, 101) module = WaffleCenteringModule(size=0.2, center=(50, 50), name_in='waffle', image_in_tag='star_add', center_in_tag='waffle', image_out_tag='center', radius=35., pattern='x', sigma=0.05) self.pipeline.add_module(module) with pytest.warns(DeprecationWarning) as warning: self.pipeline.run_module('waffle') assert len(warning) == 1 assert warning[0].message.args[0] == 'The \'pattern\' parameter will be deprecated in a ' \ 'future release. Please Use the \'angle\' ' \ 'parameter instead and set it to 45.0 degrees.' data = self.pipeline.get_data('center') assert np.sum(data) == pytest.approx(104.93318507061295, rel=self.limit, abs=0.) assert data.shape == (10, 9, 9) attr = self.pipeline.get_attribute('center', 'History: WaffleCenteringModule') assert attr == '[x, y] = [50.0, 50.0]' def test_waffle_center_even(self) -> None: module = AddLinesModule(name_in='add1', image_in_tag='star_add', image_out_tag='star_even', lines=(0, 1, 0, 1)) self.pipeline.add_module(module) self.pipeline.run_module('add1') data = self.pipeline.get_data('star_even') assert np.sum(data) == pytest.approx(105.54278879805275, rel=self.limit, abs=0.) assert data.shape == (10, 102, 102) module = AddLinesModule(name_in='add2', image_in_tag='waffle', image_out_tag='waffle_even', lines=(0, 1, 0, 1)) self.pipeline.add_module(module) self.pipeline.run_module('add2') data = self.pipeline.get_data('waffle_even') assert np.sum(data) == pytest.approx(4.000000000000195, rel=self.limit, abs=0.) assert data.shape == (1, 102, 102) module = ShiftImagesModule(shift_xy=(0.5, 0.5), interpolation='spline', name_in='shift3', image_in_tag='star_even', image_out_tag='star_shift') self.pipeline.add_module(module) self.pipeline.run_module('shift3') data = self.pipeline.get_data('star_shift') assert np.sum(data) == pytest.approx(105.54278879805274, rel=self.limit, abs=0.) assert data.shape == (10, 102, 102) module = ShiftImagesModule(shift_xy=(0.5, 0.5), interpolation='spline', name_in='shift4', image_in_tag='waffle_even', image_out_tag='waffle_shift') self.pipeline.add_module(module) self.pipeline.run_module('shift4') data = self.pipeline.get_data('waffle_shift') assert np.sum(data) == pytest.approx(4.000000000000194, rel=self.limit, abs=0.) assert data.shape == (1, 102, 102) module = WaffleCenteringModule(size=0.2, center=(50, 50), name_in='waffle_even', image_in_tag='star_shift', center_in_tag='waffle_shift', image_out_tag='center_even', radius=35., pattern='x', sigma=0.05) self.pipeline.add_module(module) with pytest.warns(DeprecationWarning) as warning: self.pipeline.run_module('waffle_even') assert len(warning) == 1 assert warning[0].message.args[0] == 'The \'pattern\' parameter will be deprecated in a ' \ 'future release. Please Use the \'angle\' ' \ 'parameter instead and set it to 45.0 degrees.' data = self.pipeline.get_data('center_even') assert np.sum(data) == pytest.approx(105.22695036281449, rel=self.limit, abs=0.) assert data.shape == (10, 9, 9) attr = self.pipeline.get_attribute('center_even', 'History: WaffleCenteringModule') assert attr == '[x, y] = [50.5, 50.5]' def test_fit_center_full(self) -> None: module = FitCenterModule(name_in='fit1', image_in_tag='shift', fit_out_tag='fit_full', mask_out_tag='mask', method='full', mask_radii=(None, 0.1), sign='positive', model='gaussian', guess=(1., 2., 3., 3., 0.01, 0., 0.)) self.pipeline.add_module(module) self.pipeline.run_module('fit1') data = self.pipeline.get_data('fit_full') assert np.mean(data[:, 0]) == pytest.approx(0.94, rel=0., abs=0.05) assert np.mean(data[:, 2]) == pytest.approx(2.07, rel=0., abs=0.05) assert np.mean(data[:, 4]) == pytest.approx(0.0676, rel=0., abs=0.05) assert np.mean(data[:, 6]) == pytest.approx(0.0665, rel=0., abs=0.05) assert np.mean(data[:, 8]) == pytest.approx(0.24, rel=0., abs=0.05) assert data.shape == (10, 14) data = self.pipeline.get_data('mask') assert np.sum(data) == pytest.approx(103.45599730750453, rel=self.limit, abs=0.) assert data.shape == (10, 18, 18) def test_fit_center_mean(self) -> None: module = FitCenterModule(name_in='fit2', image_in_tag='shift', fit_out_tag='fit_mean', mask_out_tag=None, method='mean', mask_radii=(None, 0.1), sign='positive', model='moffat', guess=(1., 2., 3., 3., 0.01, 0., 0., 1.)) self.pipeline.add_module(module) self.pipeline.run_module('fit2') data = self.pipeline.get_data('fit_mean') assert np.mean(data[:, 0]) == pytest.approx(0.94, rel=0., abs=0.01) assert np.mean(data[:, 2]) == pytest.approx(2.059, rel=0., abs=0.01) assert np.mean(data[:, 4]) == pytest.approx(0.083, rel=0., abs=0.01) assert np.mean(data[:, 6]) == pytest.approx(0.08, rel=0., abs=0.01) assert np.mean(data[:, 8]) == pytest.approx(0.242, rel=0., abs=0.01) assert data.shape == (10, 16) def test_shift_images_tag(self) -> None: module = ShiftImagesModule(shift_xy='fit_full', interpolation='spline', name_in='shift5', image_in_tag='shift', image_out_tag='shift_tag_1') self.pipeline.add_module(module) self.pipeline.run_module('shift5') data = self.pipeline.get_data('shift_tag_1') assert np.sum(data) == pytest.approx(103.76410960085425, rel=1e-6, abs=0.9) assert data.shape == (10, 18, 18) def test_shift_images_tag_mean(self) -> None: module = ShiftImagesModule(shift_xy='fit_mean', interpolation='spline', name_in='shift6', image_in_tag='shift', image_out_tag='shift_tag_2') self.pipeline.add_module(module) self.pipeline.run_module('shift6') data = self.pipeline.get_data('shift_tag_2') assert np.sum(data) == pytest.approx(103.42285439876926, rel=1e-6, abs=0.) assert data.shape == (10, 18, 18)