gondola.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, ...])

# Arguments:

Classes

FitStatus(*values)

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

Generic least-squares cost function with error.

Reconstruction([nbins, active])

class gondola.reconstruction.FitStatus(*values)#
Unknown = 0#
DidNotConverge = 10#
Success = 42#
gondola.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

gondola.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

class gondola.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)#
gondola.reconstruction.line_fit(xs, ys, zs, errs_x=None, errs_y=None, errs_z=None, search_anchor=False)#

# Arguments:

  • search anchorperform the fit multiple times, once per point. Select a different

    anchor point for the line each time (one of the hits) until all hits have been used. Return the line with the best chi2.

class gondola.reconstruction.Reconstruction(nbins=100, active=False)#
__init__(nbins=100, active=False)#
fill_histograms()#
finish()#
reco(ev)#