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import os
import h5py
import pytest
import numpy as np
from pynpoint.core.pypeline import Pypeline
from pynpoint.readwrite.fitsreading import FitsReadingModule
from pynpoint.processing.extract import StarExtractionModule, ExtractBinaryModule
from pynpoint.util.tests import create_config, create_star_data, create_fake_data, remove_test_data
class TestExtract:
def setup_class(self) -> None:
self.limit = 1e-10
self.test_dir = os.path.dirname(__file__) + '/'
create_star_data(self.test_dir+'star')
create_fake_data(self.test_dir+'binary')
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', 'binary'])
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)
self.pipeline.run_module('read1')
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)
module = FitsReadingModule(name_in='read2',
image_tag='binary',
input_dir=self.test_dir+'binary',
overwrite=True,
check=True)
self.pipeline.add_module(module)
self.pipeline.run_module('read2')
data = self.pipeline.get_data('binary')
assert np.sum(data) == pytest.approx(11.012854046962481, rel=self.limit, abs=0.)
assert data.shape == (10, 21, 21)
self.pipeline.set_attribute('binary', 'PARANG', -1.*np.linspace(0., 180., 10), static=False)
def test_extract_position_none(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.'
assert warning[1].message.args[0] == 'Can not store the attribute \'PIXSCALE\' because ' \
'the dataset \'index\' does not exist.'
assert warning[2].message.args[0] == 'Can not store the attribute \'History: ' \
'StarExtractionModule\' 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_extract_center_none(self) -> None:
module = StarExtractionModule(name_in='extract2',
image_in_tag='star',
image_out_tag='extract2',
index_out_tag='index',
image_size=0.2,
fwhm_star=0.1,
position=(None, None, 0.2))
self.pipeline.add_module(module)
with pytest.warns(UserWarning) as warning:
self.pipeline.run_module('extract2')
assert len(warning) == 3
assert warning[0].message.args[0] == 'Can not store the attribute \'INSTRUMENT\' because ' \
'the dataset \'index\' does not exist.'
assert warning[1].message.args[0] == 'Can not store the attribute \'PIXSCALE\' because ' \
'the dataset \'index\' does not exist.'
assert warning[2].message.args[0] == 'Can not store the attribute \'History: ' \
'StarExtractionModule\' because the dataset ' \
'\'index\' does not exist.'
data = self.pipeline.get_data('extract2')
assert np.sum(data) == pytest.approx(104.93318507061295, rel=self.limit, abs=0.)
assert data.shape == (10, 9, 9)
def test_extract_position(self) -> None:
module = StarExtractionModule(name_in='extract7',
image_in_tag='star',
image_out_tag='extract7',
index_out_tag=None,
image_size=0.2,
fwhm_star=0.1,
position=(5, 5, 0.2))
self.pipeline.add_module(module)
self.pipeline.run_module('extract7')
data = self.pipeline.get_data('extract7')
assert np.sum(data) == pytest.approx(104.93318507061295, rel=self.limit, abs=0.)
assert data.shape == (10, 9, 9)
def test_extract_too_large(self) -> None:
module = StarExtractionModule(name_in='extract3',
image_in_tag='star',
image_out_tag='extract3',
index_out_tag=None,
image_size=0.2,
fwhm_star=0.1,
position=(2, 2, 0.05))
self.pipeline.add_module(module)
with pytest.warns(UserWarning) as warning:
self.pipeline.run_module('extract3')
assert len(warning) == 10
assert warning[0].message.args[0] == f'Chosen image size is too large to crop the image ' \
f'around the brightest pixel (image index = 0, ' \
f'pixel [x, y] = [2, 2]). Using the center of ' \
f'the image instead.'
data = self.pipeline.get_data('extract3')
assert np.sum(data) == pytest.approx(104.93318507061295, rel=self.limit, abs=0.)
assert data.shape == (10, 9, 9)
def test_star_extract_cpu(self) -> None:
with h5py.File(self.test_dir+'PynPoint_database.hdf5', 'a') as hdf_file:
hdf_file['config'].attrs['CPU'] = 4
module = StarExtractionModule(name_in='extract4',
image_in_tag='star',
image_out_tag='extract4',
index_out_tag='index',
image_size=0.2,
fwhm_star=0.1,
position=(2, 2, 0.05))
self.pipeline.add_module(module)
with pytest.warns(UserWarning) as warning:
self.pipeline.run_module('extract4')
assert len(warning) == 2
assert warning[0].message.args[0] == 'The \'index_out_port\' can only be used if ' \
'CPU = 1. No data will be stored to this output port.'
assert warning[1].message.args[0] == 'Chosen image size is too large to crop the image ' \
'around the brightest pixel (image index = 0, ' \
'pixel [x, y] = [2, 2]). Using the center of the ' \
'image instead.'
def test_extract_binary(self) -> None:
with h5py.File(self.test_dir+'PynPoint_database.hdf5', 'a') as hdf_file:
hdf_file['config'].attrs['CPU'] = 1
module = ExtractBinaryModule(pos_center=(10., 10.),
pos_binary=(10., 16.),
name_in='extract5',
image_in_tag='binary',
image_out_tag='extract5',
image_size=0.15,
search_size=0.07,
filter_size=None)
self.pipeline.add_module(module)
self.pipeline.run_module('extract5')
data = self.pipeline.get_data('extract5')
assert np.sum(data) == pytest.approx(1.3419098759577548, rel=self.limit, abs=0.)
assert data.shape == (10, 7, 7)
def test_extract_binary_filter(self) -> None:
module = ExtractBinaryModule(pos_center=(10., 10.),
pos_binary=(10., 16.),
name_in='extract6',
image_in_tag='binary',
image_out_tag='extract6',
image_size=0.15,
search_size=0.07,
filter_size=0.05)
self.pipeline.add_module(module)
self.pipeline.run_module('extract6')
data = self.pipeline.get_data('extract6')
assert np.sum(data) == pytest.approx(1.3789593661036972, rel=self.limit, abs=0.)
assert data.shape == (10, 7, 7)
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