def test_get_config_attribute(self) -> None:
create_config(self.test_dir + 'PynPoint_config.ini')
Pypeline(self.test_dir, self.test_dir, self.test_dir)
storage = DataStorage(self.test_dir + 'PynPoint_database.hdf5')
port = ConfigPort('config', None)
with pytest.warns(UserWarning) as warning:
attribute = port.get_attribute('CPU')
assert len(warning) == 1
assert warning[0].message.args[0] == 'ConfigPort can not load data unless a database is ' \
'connected.'
assert attribute is None
port = ConfigPort('config', storage)
attribute = port.get_attribute('CPU')
assert attribute == 1
attribute = port.get_attribute('NFRAMES')
assert attribute == 'NAXIS3'
attribute = port.get_attribute('PIXSCALE')
assert np.allclose(attribute, 0.027, rtol=limit, atol=0.)
with pytest.warns(UserWarning) as warning:
attribute = port.get_attribute('test')
assert len(warning) == 1
assert warning[0].message.args[
0] == 'The attribute \'test\' was not found.'
assert attribute is None
def setup_class(self):
self.test_dir = os.path.dirname(__file__) + '/'
create_star_data(path=self.test_dir + 'star',
npix_x=51,
npix_y=51,
x0=[10., 10., 10., 10.],
y0=[10., 10., 10., 10.])
create_fake(path=self.test_dir + 'binary',
ndit=[20, 20, 20, 20],
nframes=[20, 20, 20, 20],
exp_no=[1, 2, 3, 4],
npix=(101, 101),
fwhm=3.,
x0=[50, 50, 50, 50],
y0=[50, 50, 50, 50],
angles=[[0., 25.], [25., 50.], [50., 75.], [75., 100.]],
sep=20.,
contrast=1.)
create_config(self.test_dir + 'PynPoint_config.ini')
self.pipeline = Pypeline(self.test_dir, self.test_dir, self.test_dir)
def setup_class(self) -> None:
self.test_dir = os.path.dirname(__file__) + '/'
create_fake(path=self.test_dir + 'science',
ndit=[20, 20, 20, 20],
nframes=[20, 20, 20, 20],
exp_no=[1, 2, 3, 4],
npix=(100, 100),
fwhm=3.,
x0=[50, 50, 50, 50],
y0=[50, 50, 50, 50],
angles=[[0., 25.], [25., 50.], [50., 75.], [75., 100.]],
sep=10.,
contrast=3e-3)
create_fake(path=self.test_dir + 'reference',
ndit=[10, 10, 10, 10],
nframes=[10, 10, 10, 10],
exp_no=[1, 2, 3, 4],
npix=(100, 100),
fwhm=3.,
x0=[50, 50, 50, 50],
y0=[50, 50, 50, 50],
angles=[[0., 25.], [25., 50.], [50., 75.], [75., 100.]],
sep=None,
contrast=None)
create_config(self.test_dir + 'PynPoint_config.ini')
self.pipeline = Pypeline(self.test_dir, self.test_dir, self.test_dir)
def setup_class(self) -> None:
self.limit = 1e-10
self.test_dir = os.path.dirname(__file__) + '/'
np.random.seed(1)
images = np.random.normal(loc=0, scale=2e-4, size=(5, 11, 11))
dark = np.random.normal(loc=0, scale=2e-4, size=(5, 11, 11))
flat = np.random.normal(loc=0, scale=2e-4, size=(5, 11, 11))
images[0, 5, 5] = 1.
dark[:, 5, 5] = 1.
flat[:, 8, 8] = -1.
flat[:, 9, 9] = -1.
flat[:, 10, 10] = -1.
with h5py.File(self.test_dir + 'PynPoint_database.hdf5',
'w') as hdf_file:
hdf_file.create_dataset('images', data=images)
hdf_file.create_dataset('dark', data=dark)
hdf_file.create_dataset('flat', data=flat)
create_config(self.test_dir + 'PynPoint_config.ini')
self.pipeline = Pypeline(self.test_dir, self.test_dir, self.test_dir)
def setup_class(self):
self.test_dir = os.path.dirname(__file__) + '/'
create_star_data(path=self.test_dir+'data1',
npix_x=100,
npix_y=100,
x0=[50, 50, 50, 50],
y0=[50, 50, 50, 50],
parang_start=[0., 25., 50., 75.],
parang_end=[25., 50., 75., 100.],
exp_no=[1, 2, 3, 4])
create_star_data(path=self.test_dir+'data2',
npix_x=100,
npix_y=100,
x0=[50, 50, 50, 50],
y0=[50, 50, 50, 50],
parang_start=[0., 25., 50., 75.],
parang_end=[25., 50., 75., 100.],
exp_no=[1, 2, 3, 4])
create_star_data(path=self.test_dir+'data3',
npix_x=100,
npix_y=100,
x0=[50, 50, 50, 50],
y0=[50, 50, 50, 50],
parang_start=[0., 25., 50., 75.],
parang_end=[25., 50., 75., 100.],
exp_no=[1, 2, 3, 4])
create_config(self.test_dir+'PynPoint_config.ini')
self.pipeline = Pypeline(self.test_dir, self.test_dir, self.test_dir)
def setup_class(self):
self.test_dir = os.path.dirname(__file__) + '/'
np.random.seed(1)
images = np.random.normal(loc=0, scale=2e-4, size=(40, 100, 100))
dark = np.random.normal(loc=0, scale=2e-4, size=(40, 100, 100))
flat = np.random.normal(loc=0, scale=2e-4, size=(40, 100, 100))
images[0, 10, 10] = 1.
images[0, 12, 12] = 1.
images[0, 14, 14] = 1.
images[0, 20, 20] = 1.
images[0, 22, 22] = 1.
images[0, 24, 24] = 1.
dark[:, 10, 10] = 1.
dark[:, 12, 12] = 1.
dark[:, 14, 14] = 1.
flat[:, 20, 20] = -1.
flat[:, 22, 22] = -1.
flat[:, 24, 24] = -1.
with h5py.File(self.test_dir + 'PynPoint_database.hdf5',
'w') as hdf_file:
hdf_file.create_dataset('images', data=images)
hdf_file.create_dataset('dark', data=dark)
hdf_file.create_dataset('flat', data=flat)
hdf_file.create_dataset('header_images/STAR_POSITION',
data=np.full((40, 2), 50.))
create_config(self.test_dir + 'PynPoint_config.ini')
self.pipeline = Pypeline(self.test_dir, self.test_dir, self.test_dir)
def setup_class(self) -> None:
self.limit = 1e-10
self.test_dir = os.path.dirname(__file__) + '/'
create_random(self.test_dir)
create_config(self.test_dir+'PynPoint_config.ini')
def setup_class(self):
self.test_dir = os.path.dirname(__file__) + '/'
create_star_data(path=self.test_dir + 'flux', npix_x=101, npix_y=101)
create_star_data(path=self.test_dir + 'psf',
npix_x=15,
npix_y=15,
x0=[7., 7., 7., 7.],
y0=[7., 7., 7., 7.],
ndit=1,
nframes=1,
noise=False)
create_fake(path=self.test_dir + 'adi',
ndit=[5, 5, 5, 5],
nframes=[5, 5, 5, 5],
exp_no=[1, 2, 3, 4],
npix=(15, 15),
fwhm=3.,
x0=[7., 7., 7., 7.],
y0=[7., 7., 7., 7.],
angles=[[0., 50.], [50., 100.], [100., 150.], [150.,
200.]],
sep=5.5,
contrast=1.)
create_config(self.test_dir + 'PynPoint_config.ini')
self.pipeline = Pypeline(self.test_dir, self.test_dir, self.test_dir)
def test_get_config_attribute(self):
create_config(self.test_dir + "PynPoint_config.ini")
Pypeline(self.test_dir, self.test_dir, self.test_dir)
storage = DataStorage(self.test_dir + "PynPoint_database.hdf5")
port = ConfigPort("config", None)
with pytest.warns(UserWarning) as warning:
attribute = port.get_attribute("CPU")
assert len(warning) == 1
assert warning[0].message.args[0] == "ConfigPort can not load data unless a database is " \
"connected."
assert attribute is None
port = ConfigPort("config", storage)
attribute = port.get_attribute("CPU")
assert attribute == 1
attribute = port.get_attribute("NFRAMES")
assert attribute == "NAXIS3"
attribute = port.get_attribute("PIXSCALE")
assert np.allclose(attribute, 0.027, rtol=limit, atol=0.)
with pytest.warns(UserWarning) as warning:
attribute = port.get_attribute("test")
assert len(warning) == 1
assert warning[0].message.args[
0] == "No attribute found - requested: test."
assert attribute is None
def setup_class(self) -> None:
self.test_dir = os.path.dirname(__file__) + '/'
self.fitsfile = self.test_dir + 'near/images_1.fits'
create_near_data(path=self.test_dir + 'near')
create_config(self.test_dir + 'PynPoint_config.ini')
self.pipeline = Pypeline(self.test_dir, self.test_dir, self.test_dir)
self.pipeline.set_attribute('config',
'NFRAMES',
'ESO DET CHOP NCYCLES',
static=True)
self.pipeline.set_attribute('config',
'EXP_NO',
'ESO TPL EXPNO',
static=True)
self.pipeline.set_attribute('config', 'NDIT', 'None', static=True)
self.pipeline.set_attribute('config',
'PARANG_START',
'None',
static=True)
self.pipeline.set_attribute('config',
'PARANG_END',
'None',
static=True)
self.pipeline.set_attribute('config', 'DITHER_X', 'None', static=True)
self.pipeline.set_attribute('config', 'DITHER_Y', 'None', static=True)
self.pipeline.set_attribute('config', 'PIXSCALE', 0.045, static=True)
self.pipeline.set_attribute('config', 'MEMORY', 100, static=True)
self.positions = ('chopa', 'chopb')
def setup_class(self):
self.test_dir = os.path.dirname(__file__) + "/"
np.random.seed(1)
images = np.random.normal(loc=0, scale=2e-4, size=(40, 100, 100))
dark = np.random.normal(loc=0, scale=2e-4, size=(40, 100, 100))
flat = np.random.normal(loc=0, scale=2e-4, size=(40, 100, 100))
images[0, 10, 10] = 1.
images[0, 12, 12] = 1.
images[0, 14, 14] = 1.
images[0, 20, 20] = 1.
images[0, 22, 22] = 1.
images[0, 24, 24] = 1.
dark[:, 10, 10] = 1.
dark[:, 12, 12] = 1.
dark[:, 14, 14] = 1.
flat[:, 20, 20] = -1.
flat[:, 22, 22] = -1.
flat[:, 24, 24] = -1.
h5f = h5py.File(self.test_dir + "PynPoint_database.hdf5", "w")
h5f.create_dataset("images", data=images)
h5f.create_dataset("dark", data=dark)
h5f.create_dataset("flat", data=flat)
h5f.create_dataset("header_images/STAR_POSITION",
data=np.full((40, 2), 50.))
h5f.close()
create_config(self.test_dir + "PynPoint_config.ini")
self.pipeline = Pypeline(self.test_dir, self.test_dir, self.test_dir)
def setup_class(self):
self.test_dir = os.path.dirname(__file__) + '/'
create_star_data(path=self.test_dir + 'images', ndit=10, nframes=11)
create_config(self.test_dir + 'PynPoint_config.ini')
self.pipeline = Pypeline(self.test_dir, self.test_dir, self.test_dir)
def setup_class(self) -> None:
self.test_dir = os.path.dirname(__file__) + '/'
create_random(self.test_dir + 'data')
create_config(self.test_dir + 'PynPoint_config.ini')
self.pipeline = Pypeline(self.test_dir, self.test_dir, self.test_dir)
def setup_class(self):
self.test_dir = os.path.dirname(__file__) + "/"
create_random(self.test_dir)
create_config(self.test_dir+"PynPoint_config.ini")
self.pipeline = Pypeline(self.test_dir, self.test_dir, self.test_dir)
def setup_class(self):
self.test_dir = os.path.dirname(__file__) + "/"
create_star_data(path=self.test_dir + "limits")
create_config(self.test_dir + "PynPoint_config.ini")
self.pipeline = Pypeline(self.test_dir, self.test_dir, self.test_dir)
def setup_class(self):
self.test_dir = os.path.dirname(__file__) + '/'
create_star_data(path=self.test_dir + 'fits')
create_config(self.test_dir + 'PynPoint_config.ini')
self.pipeline = Pypeline(self.test_dir, self.test_dir, self.test_dir)
def setup_class(self) -> None:
self.limit = 1e-5
self.test_dir = os.path.dirname(__file__) + '/'
create_ifs_data(self.test_dir+'science')
create_config(self.test_dir+'PynPoint_config.ini')
self.pipeline = Pypeline(self.test_dir, self.test_dir, self.test_dir)
def setup_class(self) -> None:
self.limit = 1e-10
self.test_dir = os.path.dirname(__file__) + '/'
create_star_data(self.test_dir + 'images')
create_config(self.test_dir + 'PynPoint_config.ini')
self.pipeline = Pypeline(self.test_dir, self.test_dir, self.test_dir)
def setup_class(self):
self.test_dir = os.path.dirname(__file__) + '/'
create_fake(path=self.test_dir + 'dither',
ndit=[20, 20, 20, 20],
nframes=[20, 20, 20, 20],
exp_no=[1, 2, 3, 4],
npix=(100, 100),
fwhm=3.,
x0=[25, 75, 75, 25],
y0=[75, 75, 25, 25],
angles=[[0., 25.], [25., 50.], [50., 75.], [75., 100.]],
sep=None,
contrast=None)
create_fake(path=self.test_dir + 'star',
ndit=[10, 10, 10, 10],
nframes=[10, 10, 10, 10],
exp_no=[1, 3, 5, 7],
npix=(100, 100),
fwhm=3.,
x0=[50, 50, 50, 50],
y0=[50, 50, 50, 50],
angles=[[0., 25.], [25., 50.], [50., 75.], [75., 100.]],
sep=None,
contrast=None)
create_fake(path=self.test_dir + 'sky',
ndit=[5, 5, 5, 5],
nframes=[5, 5, 5, 5],
exp_no=[2, 4, 6, 8],
npix=(100, 100),
fwhm=None,
x0=[50, 50, 50, 50],
y0=[50, 50, 50, 50],
angles=[[0., 25.], [25., 50.], [50., 75.], [75., 100.]],
sep=None,
contrast=None)
create_fake(path=self.test_dir + 'line',
ndit=[4, 4, 4, 4],
nframes=[4, 4, 4, 4],
exp_no=[1, 3, 5, 7],
npix=(20, 20),
fwhm=3.,
x0=[10, 10, 10, 10],
y0=[10, 10, 10, 10],
angles=[[0., 25.], [25., 50.], [50., 75.], [75., 100.]],
sep=None,
contrast=None)
create_config(self.test_dir + 'PynPoint_config.ini')
self.pipeline = Pypeline(self.test_dir, self.test_dir, self.test_dir)
def setup_class(self) -> None:
self.limit = 1e-10
self.test_dir = os.path.dirname(__file__) + '/'
create_fake_data(self.test_dir + 'adi')
create_star_data(self.test_dir + 'psf', npix=21, pos_star=10.)
create_star_data(self.test_dir + 'ref', npix=21, pos_star=10.)
create_config(self.test_dir + 'PynPoint_config.ini')
self.pipeline = Pypeline(self.test_dir, self.test_dir, self.test_dir)
def setup_class(self):
self.test_dir = os.path.dirname(__file__) + '/'
create_random(self.test_dir, ndit=10, parang=None)
create_config(self.test_dir+'PynPoint_config.ini')
np.savetxt(self.test_dir+'parang.dat', np.arange(1., 11., 1.))
np.savetxt(self.test_dir+'new.dat', np.arange(10., 21., 1.))
np.savetxt(self.test_dir+'attribute.dat', np.arange(1, 11, 1), fmt='%i')
data2d = np.random.normal(loc=0, scale=2e-4, size=(10, 10))
np.savetxt(self.test_dir+'data_2d.dat', data2d)
self.pipeline = Pypeline(self.test_dir, self.test_dir, self.test_dir)
def setup_class(self):
self.test_dir = os.path.dirname(__file__) + "/"
create_star_data(path=self.test_dir + "images",
npix_x=20,
npix_y=20,
x0=[10, 10, 10, 10],
y0=[10, 10, 10, 10],
parang_start=[0., 25., 50., 75.],
parang_end=[25., 50., 75., 100.],
exp_no=[1, 2, 3, 4])
create_config(self.test_dir + "PynPoint_config.ini")
self.pipeline = Pypeline(self.test_dir, self.test_dir, self.test_dir)
def setup_class(self):
self.test_dir = os.path.dirname(__file__) + "/"
create_star_data(path=self.test_dir+"dither",
npix_x=100,
npix_y=100,
x0=[25, 75, 75, 25],
y0=[75, 75, 25, 25],
parang_start=[0., 25., 50., 75.],
parang_end=[25., 50., 75., 100.],
exp_no=[1, 2, 3, 4])
create_star_data(path=self.test_dir+"star_odd",
npix_x=101,
npix_y=101,
x0=[50],
y0=[50],
parang_start=[0.],
parang_end=[25.],
exp_no=[1],
noise=False)
create_star_data(path=self.test_dir+"star_even",
npix_x=100,
npix_y=100,
x0=[49.5],
y0=[49.5],
parang_start=[0.],
parang_end=[25.],
exp_no=[1],
noise=False)
create_waffle_data(path=self.test_dir+"waffle_odd",
npix=101,
x_waffle=[20., 20., 80., 80.],
y_waffle=[20., 80., 80., 20.])
create_waffle_data(path=self.test_dir+"waffle_even",
npix=100,
x_waffle=[20., 20., 79., 79.],
y_waffle=[20., 79., 79., 20.])
create_config(self.test_dir+"PynPoint_config.ini")
self.pipeline = Pypeline(self.test_dir, self.test_dir, self.test_dir)
def setup_class(self) -> None:
self.test_dir = os.path.dirname(__file__) + '/'
create_star_data(path=self.test_dir+'dither',
npix_x=100,
npix_y=100,
x0=[25, 75, 75, 25],
y0=[75, 75, 25, 25],
parang_start=[0., 25., 50., 75.],
parang_end=[25., 50., 75., 100.],
exp_no=[1, 2, 3, 4])
create_star_data(path=self.test_dir+'star_odd',
npix_x=101,
npix_y=101,
x0=[50],
y0=[50],
parang_start=[0.],
parang_end=[25.],
exp_no=[1],
noise=False)
create_star_data(path=self.test_dir+'star_even',
npix_x=100,
npix_y=100,
x0=[49.5],
y0=[49.5],
parang_start=[0.],
parang_end=[25.],
exp_no=[1],
noise=False)
create_waffle_data(path=self.test_dir+'waffle_odd',
npix=101,
x_spot=[20., 20., 80., 80.],
y_spot=[20., 80., 80., 20.])
create_waffle_data(path=self.test_dir+'waffle_even',
npix=100,
x_spot=[20., 20., 79., 79.],
y_spot=[20., 79., 79., 20.])
create_config(self.test_dir+'PynPoint_config.ini')
self.pipeline = Pypeline(self.test_dir, self.test_dir, self.test_dir)
def setup_class(self):
self.test_dir = os.path.dirname(__file__) + "/"
# science
create_fake(path=self.test_dir + 'adi',
ndit=[22, 17, 21, 18],
nframes=[23, 18, 22, 19],
exp_no=[1, 2, 3, 4],
npix=(100, 102),
fwhm=3.,
x0=[25, 75, 75, 25],
y0=[75, 75, 25, 25],
angles=[[0., 25.], [25., 50.], [50., 75.], [75., 100.]],
sep=7.,
contrast=1e-2)
# dark
ndit = [3, 3, 5, 5]
np.random.seed(2)
for j, item in enumerate(ndit):
image = np.random.normal(loc=0, scale=2e-4, size=(item, 100, 100))
create_fits(self.test_dir + 'dark',
'dark' + str(j + 1).zfill(2) + '.fits', image, ndit[j])
# flat
ndit = [3, 3, 5, 5]
np.random.seed(3)
for j, item in enumerate(ndit):
image = np.random.normal(loc=1, scale=1e-2, size=(item, 100, 100))
create_fits(self.test_dir + 'flat',
'flat' + str(j + 1).zfill(2) + '.fits', image, ndit[j])
create_config(self.test_dir + "PynPoint_config.ini")
self.pipeline = Pypeline(self.test_dir, self.test_dir, self.test_dir)
def setup_class(self):
self.test_dir = os.path.dirname(__file__) + "/"
np.random.seed(1)
images = np.random.normal(loc=0, scale=2e-4, size=(10, 100, 100))
dark = np.random.normal(loc=0, scale=2e-4, size=(10, 100, 100))
flat = np.random.normal(loc=0, scale=2e-4, size=(10, 100, 100))
h5f = h5py.File(self.test_dir + "PynPoint_database.hdf5", "w")
h5f.create_dataset("images", data=images)
h5f.create_dataset("dark", data=dark)
h5f.create_dataset("flat", data=flat)
h5f.close()
create_config(self.test_dir + "PynPoint_config.ini")
self.pipeline = Pypeline(self.test_dir, self.test_dir, self.test_dir)
def setup_class(self) -> None:
self.limit = 1e-10
self.test_dir = os.path.dirname(__file__) + '/'
create_random(self.test_dir, nimages=10)
create_config(self.test_dir + 'PynPoint_config.ini')
np.savetxt(self.test_dir + 'parang.dat', np.arange(10., 20., 1.))
np.savetxt(self.test_dir + 'new.dat', np.arange(20., 30., 1.))
np.savetxt(self.test_dir + 'attribute.dat',
np.arange(0, 10, 1),
fmt='%i')
np.savetxt(self.test_dir + 'wavelength.dat', np.arange(0., 10., 1.))
data2d = np.random.normal(loc=0, scale=2e-4, size=(10, 10))
np.savetxt(self.test_dir + 'data_2d.dat', data2d)
self.pipeline = Pypeline(self.test_dir, self.test_dir, self.test_dir)
def setup_class(self):
self.test_dir = os.path.dirname(__file__) + "/"
np.random.seed(1)
image_3d = np.random.normal(loc=0, scale=2e-4, size=(4, 10, 10))
image_2d = np.random.normal(loc=0, scale=2e-4, size=(10, 10))
science = np.random.normal(loc=0, scale=2e-4, size=(4, 10, 10))
dark = np.random.normal(loc=0, scale=2e-4, size=(4, 10, 10))
h5f = h5py.File(self.test_dir + "PynPoint_database.hdf5", "w")
h5f.create_dataset("image_3d", data=image_3d)
h5f.create_dataset("image_2d", data=image_2d)
h5f.create_dataset("science", data=science)
h5f.create_dataset("dark", data=dark)
h5f.close()
create_star_data(path=self.test_dir + "images")
create_config(self.test_dir + "PynPoint_config.ini")
self.pipeline = Pypeline(self.test_dir, self.test_dir, self.test_dir)
def setup_class(self):
self.test_dir = os.path.dirname(__file__) + '/'
np.random.seed(1)
images = np.random.normal(loc=0, scale=2e-4, size=(10, 100, 100))
dark = np.random.normal(loc=0, scale=2e-4, size=(10, 100, 100))
flat = np.random.normal(loc=0, scale=2e-4, size=(10, 100, 100))
crop = np.random.normal(loc=0, scale=2e-4, size=(10, 60, 60))
with h5py.File(self.test_dir + 'PynPoint_database.hdf5',
'w') as hdf_file:
hdf_file.create_dataset('images', data=images)
hdf_file.create_dataset('dark', data=dark)
hdf_file.create_dataset('flat', data=flat)
hdf_file.create_dataset('crop', data=crop)
create_config(self.test_dir + 'PynPoint_config.ini')
self.pipeline = Pypeline(self.test_dir, self.test_dir, self.test_dir)
def setup_class(self):
self.test_dir = os.path.dirname(__file__) + '/'
np.random.seed(1)
image_3d = np.random.normal(loc=0, scale=2e-4, size=(4, 10, 10))
image_2d = np.random.normal(loc=0, scale=2e-4, size=(1, 10, 10))
science = np.random.normal(loc=0, scale=2e-4, size=(4, 10, 10))
dark = np.random.normal(loc=0, scale=2e-4, size=(4, 10, 10))
with h5py.File(self.test_dir + 'PynPoint_database.hdf5',
'w') as hdf_file:
hdf_file.create_dataset('image_3d', data=image_3d)
hdf_file.create_dataset('image_2d', data=image_2d)
hdf_file.create_dataset('science', data=science)
hdf_file.create_dataset('dark', data=dark)
create_star_data(path=self.test_dir + 'images')
create_config(self.test_dir + 'PynPoint_config.ini')
self.pipeline = Pypeline(self.test_dir, self.test_dir, self.test_dir)
