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import os
import h5py
import pytest
import numpy as np
from pynpoint.core.pypeline import Pypeline
from pynpoint.processing.darkflat import DarkCalibrationModule, FlatCalibrationModule
from pynpoint.util.tests import create_config, remove_test_data
class TestDarkFlat:
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))
crop = np.random.normal(loc=0, scale=2e-4, size=(5, 7, 7))
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 teardown_class(self) -> None:
remove_test_data(self.test_dir)
def test_input_data(self) -> None:
data = self.pipeline.get_data("dark")
assert np.sum(data) == pytest.approx(
-2.0262345764957305e-05, rel=self.limit, abs=0.0
)
assert data.shape == (5, 11, 11)
data = self.pipeline.get_data("flat")
assert np.sum(data) == pytest.approx(
0.0076413379497053, rel=self.limit, abs=0.0
)
assert data.shape == (5, 11, 11)
def test_dark_calibration(self) -> None:
module = DarkCalibrationModule(
name_in="dark",
image_in_tag="images",
dark_in_tag="dark",
image_out_tag="dark_cal",
)
self.pipeline.add_module(module)
self.pipeline.run_module("dark")
data = self.pipeline.get_data("dark_cal")
assert np.sum(data) == pytest.approx(
0.00717386583629883, rel=self.limit, abs=0.0
)
assert data.shape == (5, 11, 11)
def test_flat_calibration(self) -> None:
module = FlatCalibrationModule(
name_in="flat",
image_in_tag="dark_cal",
flat_in_tag="flat",
image_out_tag="flat_cal",
)
self.pipeline.add_module(module)
self.pipeline.run_module("flat")
data = self.pipeline.get_data("flat_cal")
assert np.sum(data) == pytest.approx(
0.00717439711853594, rel=self.limit, abs=0.0
)
assert data.shape == (5, 11, 11)
def test_flat_crop(self) -> None:
module = FlatCalibrationModule(
name_in="flat_crop",
image_in_tag="crop",
flat_in_tag="flat",
image_out_tag="flat_crop",
)
self.pipeline.add_module(module)
with pytest.warns(UserWarning) as warning:
self.pipeline.run_module("flat_crop")
assert len(warning) == 1
assert (
warning[0].message.args[0]
== "The calibration images were cropped around their "
"center to match the shape of the science images."
)
data = self.pipeline.get_data("flat_crop")
assert np.sum(data) == pytest.approx(
-0.003242901413605404, rel=self.limit, abs=0.0
)
assert data.shape == (5, 7, 7)
def test_flat_too_small(self) -> None:
module = FlatCalibrationModule(
name_in="flat_small",
image_in_tag="flat",
flat_in_tag="crop",
image_out_tag="flat_small",
)
self.pipeline.add_module(module)
with pytest.raises(ValueError) as error:
self.pipeline.run_module("flat_small")
assert (
str(error.value) == "Shape of the calibration images is smaller than the "
"science images."
)
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