LocSim¶
Detector module¶
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class
Detector.Detector(name='det', azimuth_angle='0:0:0', zenith_angle='0:0:0', noise=True, background_rate=10.0, window=2.0, lat='37:56:24.7', lon='75:27:59', elev=550000.0)[source]¶ -
altitude¶
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exposure(ra, dec, FoV=False, alt=-10.0, index=0.77, horizon=90.0)[source]¶ This function takes an ra and a dec and reports the exposure at that point. If you declare FoV to be true, it’ll assume the exposure is uniform across the field of view. Otherwise, it will return an effective areas scaled by a cosine dependance up to the horizon.
Parameters: - ra (the right ascension of the test point) –
- dec (the declination of the test point) –
- FoV (If True, assumes a flat exposure. If false, assumes a cosine dependance.) –
- alt (The location of the Earth's limb. No exposure below this point (degrees)) –
- index (the scaling of the cosine dependance.) –
- horizon (A cut on the field of view of a detector. No exposure below this point (degrees)) –
Returns: float
Return type: the exposure at the test point
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sign_time¶
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sign_times¶
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trigger_time¶
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triggered_counts¶
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triggered_counts_error¶
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GRB module¶
Spacecraft module¶
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class
Spacecraft.Spacecraft(pointings={'01': ('0:0:0', '5:0:0'), '02': ('30:0:0', '20:0:0'), '03': ('60:0:0', '35:0:0'), '04': ('90:0:0', '10:0:0'), '05': ('120:0:0', '25:0:0'), '06': ('150:0:0', '40:0:0'), '07': ('180:0:0', '15:0:0'), '08': ('210:0:0', '30:0:0'), '09': ('240:0:0', '45:0:0'), '10': ('270:0:0', '20:0:0'), '11': ('300:0:0', '35:0:0'), '12': ('330:0:0', '50:0:0')}, lat='37:56:24.7', lon='75:27:59', elev=550000.0, window=4.0, background_rate=10.0, noise=True)[source]¶ The pointings are just key,item pairs of the pointing directions of the detectors on the spacecraft (respect to 0,0 at zenith). The default are 12 detectors pointing every 30 degrees in azimuth and 15 degrees in zenith (offset a bit).
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detnum¶
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Stats module¶
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Stats.addErrors(real_counts, training_counts)[source]¶ Adds all of the errors together in quadrature
Parameters: - real_counts (the array of real grb counts in each detector) –
- training_counts (the arrary of traning counts in each detector) –
Returns: null – numpy array of the errors
Return type: array
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Stats.calcNorms(real_counts, training_counts)[source]¶ Calculates the norm between the vectors in two numpy arrays.
Parameters: - real_counts (the array of real grb counts in each detector) –
- training_counts (the arrary of traning counts in each detector) –
Returns: null – numpy array of the norm between all of the vectors
Return type: array
Utils module¶
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Utils.deg2DMS(DEC)[source]¶ Borrowed from Sylvain Baumont http://supernovae.in2p3.fr/~baumont/
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Utils.deg2HMS(RA)[source]¶ Borrowed from Sylvain Baumont http://supernovae.in2p3.fr/~baumont/