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()