def guess(xs, ys):
center = np.average(xs, weights=ys / ys.sum())
height_at = np.abs(xs - center).argmin()
apex = ys[height_at]
sigma = np.abs(center - xs[[search.nearest_left(ys, apex / 2, height_at),
search.nearest_right(ys, apex / 2, height_at + 1)]]).sum()
return center, apex, sigma, sigma
def guess(xs, ys):
center = np.average(xs, weights=ys / ys.sum())
height_at = np.abs(xs - center).argmin()
apex = ys[height_at]
sigma = np.abs(center - xs[[
search.nearest_left(ys, apex / 2, height_at),
search.nearest_right(ys, apex / 2, height_at + 1)
]]).sum()
return center, apex, sigma
def guess(xs, ys):
weights = np.clip(ys, 0, np.infty)
center = np.average(xs, weights=weights / weights.sum())
if np.isnan(center):
center = xs.mean()
height_at = np.abs(xs - center).argmin()
apex = ys[height_at]
max_ix = ys.argmax()
if apex < ys[max_ix] * 0.1:
apex = ys[max_ix]
height_at = max_ix
sigma = np.abs(center - xs[[
search.nearest_left(ys, apex / 2, height_at),
search.nearest_right(ys, apex / 2, height_at + 1)
]]).sum()
return center, apex, sigma
