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test_badpixel.py
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test_badpixel.py
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import os
import math
import h5py
import pytest
import numpy as np
from pynpoint.core.pypeline import Pypeline
from pynpoint.processing.badpixel import BadPixelSigmaFilterModule, BadPixelMapModule, \
BadPixelInterpolationModule, BadPixelTimeFilterModule, \
ReplaceBadPixelsModule
from pynpoint.util.tests import create_config, remove_test_data
class TestBadPixel:
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 teardown_class(self) -> None:
remove_test_data(self.test_dir)
def test_bad_pixel_sigma_filter(self) -> None:
module = BadPixelSigmaFilterModule(name_in='sigma1',
image_in_tag='images',
image_out_tag='sigma1',
map_out_tag='None',
box=9,
sigma=3.,
iterate=5)
self.pipeline.add_module(module)
self.pipeline.run_module('sigma1')
data = self.pipeline.get_data('sigma1')
assert np.sum(data) == pytest.approx(0.006513475520308432, rel=self.limit, abs=0.)
assert data.shape == (5, 11, 11)
def test_bad_pixel_map_out(self) -> None:
module = BadPixelSigmaFilterModule(name_in='sigma2',
image_in_tag='images',
image_out_tag='sigma2',
map_out_tag='bpmap',
box=9,
sigma=2.,
iterate=3)
self.pipeline.add_module(module)
self.pipeline.run_module('sigma2')
data = self.pipeline.get_data('sigma2')
assert data[0, 0, 0] == pytest.approx(-2.4570591355257687e-05, rel=self.limit, abs=0.)
assert data[0, 5, 5] == pytest.approx(9.903775276151606e-06, rel=self.limit, abs=0.)
assert np.sum(data) == pytest.approx(0.011777887008566097, rel=self.limit, abs=0.)
assert data.shape == (5, 11, 11)
data = self.pipeline.get_data('bpmap')
assert data[0, 1, 1] == pytest.approx(1., rel=self.limit, abs=0.)
assert data[0, 5, 5] == pytest.approx(0., rel=self.limit, abs=0.)
assert np.sum(data) == pytest.approx(519.0, rel=self.limit, abs=0.)
assert data.shape == (5, 11, 11)
def test_bad_pixel_map(self) -> None:
module = BadPixelMapModule(name_in='bp_map1',
dark_in_tag='dark',
flat_in_tag='flat',
bp_map_out_tag='bp_map1',
dark_threshold=0.99,
flat_threshold=-0.99)
self.pipeline.add_module(module)
self.pipeline.run_module('bp_map1')
data = self.pipeline.get_data('bp_map1')
assert data[0, 0, 0] == pytest.approx(1., rel=self.limit, abs=0.)
assert data[0, 5, 5] == pytest.approx(0., rel=self.limit, abs=0.)
assert np.sum(data) == pytest.approx(117., rel=self.limit, abs=0.)
assert data.shape == (1, 11, 11)
def test_map_no_dark(self) -> None:
module = BadPixelMapModule(name_in='bp_map2',
dark_in_tag=None,
flat_in_tag='flat',
bp_map_out_tag='bp_map2',
dark_threshold=0.99,
flat_threshold=-0.99)
self.pipeline.add_module(module)
self.pipeline.run_module('bp_map2')
data = self.pipeline.get_data('bp_map2')
assert np.sum(data) == pytest.approx(118., rel=self.limit, abs=0.)
assert data.shape == (1, 11, 11)
def test_map_no_flat(self) -> None:
module = BadPixelMapModule(name_in='bp_map3',
dark_in_tag='dark',
flat_in_tag=None,
bp_map_out_tag='bp_map3',
dark_threshold=0.99,
flat_threshold=-0.99)
self.pipeline.add_module(module)
self.pipeline.run_module('bp_map3')
data = self.pipeline.get_data('bp_map3')
assert np.sum(data) == pytest.approx(120., rel=self.limit, abs=0.)
assert data.shape == (1, 11, 11)
def test_bad_pixel_interpolation(self) -> None:
module = BadPixelInterpolationModule(name_in='interpolation',
image_in_tag='images',
bad_pixel_map_tag='bp_map1',
image_out_tag='interpolation',
iterations=10)
self.pipeline.add_module(module)
self.pipeline.run_module('interpolation')
data = self.pipeline.get_data('interpolation')
assert data[0, 0, 0] == pytest.approx(0.00032486907273264834, rel=1e-6, abs=0.)
assert data[0, 5, 5] == pytest.approx(-1.4292408645473845e-05, rel=1e-6, abs=0.)
assert np.sum(data) == pytest.approx(0.008683344127872174, rel=1e-6, abs=0.)
assert data.shape == (5, 11, 11)
def test_bad_pixel_time(self) -> None:
module = BadPixelTimeFilterModule(name_in='time',
image_in_tag='images',
image_out_tag='time',
sigma=(2., 2.))
self.pipeline.add_module(module)
self.pipeline.run_module('time')
data = self.pipeline.get_data('time')
assert data[0, 0, 0] == pytest.approx(0.00032486907273264834, rel=self.limit, abs=0.)
assert data[0, 5, 5] == pytest.approx(-0.00017468532119886812, rel=self.limit, abs=0.)
assert np.sum(data) == pytest.approx(0.004175672043832705, rel=self.limit, abs=0.)
assert data.shape == (5, 11, 11)
def test_replace_bad_pixels(self) -> None:
module = ReplaceBadPixelsModule(name_in='replace1',
image_in_tag='images',
map_in_tag='bp_map1',
image_out_tag='replace',
size=2,
replace='mean')
self.pipeline.add_module(module)
self.pipeline.run_module('replace1')
data = self.pipeline.get_data('replace')
assert data[0, 0, 0] == pytest.approx(0.00032486907273264834, rel=self.limit, abs=0.)
assert data[0, 5, 5] == pytest.approx(4.260114004413933e-05, rel=self.limit, abs=0.)
assert np.sum(data) == pytest.approx(0.00883357395370896, rel=self.limit, abs=0.)
assert data.shape == (5, 11, 11)
module = ReplaceBadPixelsModule(name_in='replace2',
image_in_tag='images',
map_in_tag='bp_map1',
image_out_tag='replace',
size=2,
replace='median')
self.pipeline.add_module(module)
self.pipeline.run_module('replace2')
data = self.pipeline.get_data('replace')
assert data[0, 0, 0] == pytest.approx(0.00032486907273264834, rel=self.limit, abs=0.)
assert data[0, 5, 5] == pytest.approx(4.327154179438619e-05, rel=self.limit, abs=0.)
assert np.sum(data) == pytest.approx(0.008489525337709688, rel=self.limit, abs=0.)
assert data.shape == (5, 11, 11)
module = ReplaceBadPixelsModule(name_in='replace3',
image_in_tag='images',
map_in_tag='bp_map1',
image_out_tag='replace',
size=2,
replace='nan')
self.pipeline.add_module(module)
self.pipeline.run_module('replace3')
data = self.pipeline.get_data('replace')
assert data[0, 0, 0] == pytest.approx(0.00032486907273264834, rel=self.limit, abs=0.)
assert math.isnan(data[0, 5, 5])
assert np.nansum(data) == pytest.approx(0.009049653234723834, rel=self.limit, abs=0.)
assert data.shape == (5, 11, 11)