gaps_online.reconstruction#

GAPS first guess & prototype event reconstructions

Functions

line3d(z, x_a, y_a, z_a, dx, dy, dz)

describe line depending on z since that is our best constrained value

line3d_2pts(z, tu_x, tu_y, tu_z, tl_x, tl_y, ...)

describe line depending on z since that is our best constrained value.

line_fit(xs, ys, zs[, errs_x, errs_y])

Classes

FitStatus(*values)

LeastSquares(model, x, y, z, x_err, y_err)

Generic least-squares cost function with error.

Reconstruction()

class gaps_online.reconstruction.FitStatus(*values)#
Unknown = 0#
DidNotConverge = 10#
Success = 42#
gaps_online.reconstruction.line3d(z, x_a, y_a, z_a, dx, dy, dz)#

describe line depending on z since that is our best constrained value

This model has 6 free parameters, 3 for the anchor point and 3 for the direction

gaps_online.reconstruction.line3d_2pts(z, tu_x, tu_y, tu_z, tl_x, tl_y, tl_z)#

describe line depending on z since that is our best constrained value. Version with 2 points instead of direction vector, so we can constrain the point on the tof better

class gaps_online.reconstruction.LeastSquares(model, x, y, z, x_err, y_err)#

Generic least-squares cost function with error.

__init__(model, x, y, z, x_err, y_err)#
gaps_online.reconstruction.line_fit(xs, ys, zs, errs_x=None, errs_y=None)#
class gaps_online.reconstruction.Reconstruction#
__init__()#
reco(ev)#