<jupyter_start><jupyter_text>A Tour of HyperScreen<jupyter_code>import os
from hyperscreen import hypercore
data_dir = '../tests/data/'
os.listdir(data_dir)
data_file = data_dir + '/hrcI_evt1_casAtest.fits.gz'
obs = hypercore.HRCevt1(data_file)
obs.image()
obs.image(masked_x = obs.data['x'][obs.gtimask], masked_y = obs.data['y'][obs.gtimask])
mask = obs.data['Hyperbola test failed']
obs.image(masked_x = obs.data['x'][mask], masked_y = obs.data['y'][mask])
mask_steve = obs.data['Hyperbola test failed']
obs.image(masked_x = obs.data['x'][mask], masked_y = obs.data['y'][mask])
tremblay = obs.hyperscreen()
mask_grant = tremblay['All Survivals (boolean mask)']
obs.image(masked_x = obs.data['x'][mask], masked_y = obs.data['y'][mask])<jupyter_output><empty_output>
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{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '79098', 'license': 'MIT', 'n_tokens_mistral': 313, 'n_tokens_neox': 310, 'n_words': 49, 'path': 'notebooks/Untitled.ipynb', 'repo_name': 'granttremblay/hyperscreen', 'size': '767'}