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48 lines
980 B
Python
48 lines
980 B
Python
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import numpy as np
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def linear_data_sample(N=40, rseed=0, m=3, b=-2):
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rng = np.random.RandomState(rseed)
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x = 10 * rng.rand(N)
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dy = m / 2 * (1 + rng.rand(N))
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y = m * x + b + dy * rng.randn(N)
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return (x, y, dy)
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def linear_data_sample_big_errs(N=40, rseed=0, m=3, b=-2):
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rng = np.random.RandomState(rseed)
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x = 10 * rng.rand(N)
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dy = m / 2 * (1 + rng.rand(N))
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dy[20:25] *= 10
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y = m * x + b + dy * rng.randn(N)
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return (x, y, dy)
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def sample_light_curve(phased=True):
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from astroML.datasets import fetch_LINEAR_sample
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data = fetch_LINEAR_sample()
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t, y, dy = data[18525697].T
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if phased:
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P_best = 0.580313015651
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t /= P_best
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return (t, y, dy)
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def sample_light_curve_2(phased=True):
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from astroML.datasets import fetch_LINEAR_sample
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data = fetch_LINEAR_sample()
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t, y, dy = data[10022663].T
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if phased:
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P_best = 0.61596079804
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t /= P_best
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return (t, y, dy)
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