def create_sample_image(psi='-30d'):
seed(10)
# set up the sample image using a HESS camera geometry (since it's easy
# to load)
geom = CameraGeometry.from_name("HESS", 1)
# make a toymodel shower model
model = toymodel.generate_2d_shower_model(centroid=(0.2, 0.3),
width=0.001,
length=0.01,
psi=psi)
# generate toymodel image in camera for this shower model.
image, signal, noise = toymodel.make_toymodel_shower_image(
geom, model.pdf, intensity=50, nsb_level_pe=100)
# denoise the image, so we can calculate hillas params
clean_mask = tailcuts_clean(geom, image, 1, 10,
5) # pedvars = 1 and core and boundary
# threshold in pe
image[~clean_mask] = 0
# Pixel values in the camera
pix_x = geom.pix_x.value
pix_y = geom.pix_y.value
return pix_x, pix_y, image
def create_sample_image():
# set up the sample image using a HESS camera geometry (since it's easy
# to load)
geom = CameraGeometry.from_name("HESS", 1)
# make a toymodel shower model
model = toymodel.generate_2d_shower_model(centroid=(0.2, 0.3),
width=0.001, length=0.01,
psi='30d')
# generate toymodel image in camera for this shower model.
image, signal, noise = toymodel.make_toymodel_shower_image(geom, model.pdf,
intensity=50,
nsb_level_pe=100)
# denoise the image, so we can calculate hillas params
clean_mask = tailcuts_clean(geom, image, 1, 10,
5) # pedvars = 1 and core and boundary
# threshold in pe
image[~clean_mask] = 0
# Pixel values in the camera
pix_x = geom.pix_x.value
pix_y = geom.pix_y.value
return pix_x, pix_y, image
from matplotlib import pyplot as plt
from ctapipe.io import CameraGeometry
from ctapipe.visualization import CameraDisplay
from ctapipe.reco import mock
if __name__ == '__main__':
plt.style.use('ggplot')
fig = plt.figure(figsize=(12, 8))
ax = fig.add_subplot(1, 1, 1)
geom = CameraGeometry.from_name('hess', 1)
disp = CameraDisplay(geom, ax=ax)
disp.add_colorbar()
model = mock.generate_2d_shower_model(centroid=(0.05, 0.0),
width=0.005,
length=0.025,
psi='35d')
image, sig, bg = mock.make_mock_shower_image(geom,
model.pdf,
intensity=50,
nsb_level_pe=20)
disp.image = image
mask = disp.image > 15
Example of drawing a Camera using different norms
"""
from matplotlib.style import use
import matplotlib.pylab as plt
from ctapipe.io import CameraGeometry
from ctapipe.visualization import CameraDisplay
from ctapipe.reco import mock
from matplotlib.colors import PowerNorm
if __name__ == "__main__":
use("ggplot")
# load the camera
fig, axs = plt.subplots(1, 3, figsize=(15, 5))
geom = CameraGeometry.from_name("hess", 1)
titles = "Linear Scale", "Log-Scale", "PowerNorm(gamma=2)"
model = mock.generate_2d_shower_model(centroid=(0.2, 0.0), width=0.01, length=0.1, psi="35d")
image, sig, bg = mock.make_mock_shower_image(geom, model.pdf, intensity=50, nsb_level_pe=1000)
disps = []
for ax, title in zip(axs, titles):
disps.append(CameraDisplay(geom, ax=ax, image=image, title=title))
disps[0].norm = "lin"
disps[1].norm = "log"
disps[2].norm = PowerNorm(2)
Example of drawing a Camera using different norms
"""
import matplotlib.pylab as plt
from ctapipe.image import mock
from ctapipe.io import CameraGeometry
from ctapipe.visualization import CameraDisplay
from matplotlib.colors import PowerNorm
from matplotlib.style import use
if __name__ == '__main__':
use('ggplot')
# load the camera
fig, axs = plt.subplots(1, 3, figsize=(15, 5))
geom = CameraGeometry.from_name("hess", 1)
titles = 'Linear Scale', 'Log-Scale', 'PowerNorm(gamma=2)'
model = mock.generate_2d_shower_model(
centroid=(0.2, 0.0),
width=0.01,
length=0.1,
psi='35d',
)
image, sig, bg = mock.make_mock_shower_image(
geom,
model.pdf,
intensity=50,
nsb_level_pe=1000,
from ctapipe.image import toymodel
from ctapipe.io import CameraGeometry
from ctapipe.visualization import CameraDisplay
from matplotlib import pyplot as plt
if __name__ == '__main__':
plt.style.use('ggplot')
fig = plt.figure(figsize=(12, 8))
ax = fig.add_subplot(1, 1, 1)
geom = CameraGeometry.from_name('hess', 1)
disp = CameraDisplay(geom, ax=ax)
disp.add_colorbar()
model = toymodel.generate_2d_shower_model(
centroid=(0.05, 0.0), width=0.005, length=0.025, psi='35d'
)
image, sig, bg = toymodel.make_toymodel_shower_image(
geom, model.pdf, intensity=50, nsb_level_pe=20
)
disp.image = image
mask = disp.image > 15
disp.highlight_pixels(mask, linewidth=3)
plt.show()
