def test_image_cleaner(method):
""" Test that we can construct and use a component-based ImageCleaner"""
config = Config({
"TailcutsImageCleaner": {
"boundary_threshold_pe": 5.0,
"picture_threshold_pe": 10.0,
},
"MARSImageCleaner": {
"boundary_threshold_pe": 5.0,
"picture_threshold_pe": 10.0,
},
"FACTImageCleaner": {
"boundary_threshold_pe": 5.0,
"picture_threshold_pe": 10.0,
"time_limit_ns": 6.0,
},
})
tel = TelescopeDescription.from_name("MST", "NectarCam")
subarray = SubarrayDescription(name="test",
tel_positions={1: None},
tel_descriptions={1: tel})
clean = ImageCleaner.from_name(method, config=config, subarray=subarray)
image = np.zeros_like(tel.camera.geometry.pix_x.value, dtype=np.float)
image[10:30] = 20.0
image[31:40] = 8.0
times = np.linspace(-5, 10, image.shape[0])
mask = clean(tel_id=1, image=image, arrival_times=times)
# we're not testing the algorithm here, just that it does something (for the
# algorithm tests, see test_cleaning.py
assert np.count_nonzero(mask) > 0
def test_image_cleaner_no_subarray(method):
with pytest.raises(TypeError):
ImageCleaner.from_name(method)
import numpy as np
import pytest
from traitlets.config import Config
from ctapipe.image import ImageCleaner
from ctapipe.instrument import TelescopeDescription, SubarrayDescription
@pytest.mark.parametrize("method",
ImageCleaner.non_abstract_subclasses().keys())
def test_image_cleaner(method):
""" Test that we can construct and use a component-based ImageCleaner"""
config = Config({
"TailcutsImageCleaner": {
"boundary_threshold_pe": 5.0,
"picture_threshold_pe": 10.0,
},
"MARSImageCleaner": {
"boundary_threshold_pe": 5.0,
"picture_threshold_pe": 10.0,
},
"FACTImageCleaner": {
"boundary_threshold_pe": 5.0,
"picture_threshold_pe": 10.0,
"time_limit_ns": 6.0,
},
})
tel = TelescopeDescription.from_name("MST", "NectarCam")
subarray = SubarrayDescription(name="test",