qpym2.hists

Module Contents

Functions

get_h2proj	Return the projection of a 2D histogram along the specified axis
get_sum_hist	Return the sum histogram from the components and their norms
get_hist_settings	Return the nbins and range parameters for histogram according to the model
get_empty_hist	Return an empty histogram according to hm
smooth_nph2
create_hist_m2sum	create a 1D histogram of esum (m2sum)
create_hist_m2diff	create a 1D histogram of ediss (v*sqrt(2))
create_hist_m2e2	create a 1D histogram of e2
create_hist_h2ee	create a 2D histogram of e1 vs e2
create_hist_h2esumediff	create 2D histogram of ediff vs esum (scaled u,v)
create_hist_h2esume2	create 2D histogram of e2 vs esum
create_hist_h2uv	create 2D histogram of u vs v
get_hist_from_rdf	Return a histogram according to hm. Assumes ‘u’ and ‘v’ branches are present in rdf.

Data

HistType

API

qpym2.hists.HistType = None

qpym2.hists.get_h2proj(h2, axis=0)

Return the projection of a 2D histogram along the specified axis

h2numpy.ndarray

The 2D histogram.

axisint

The axis along which to project. Default is 0 (x-axis).

h1numpy.ndarray

The 1D histogram.

qpym2.hists.get_sum_hist(comps, norms)

Return the sum histogram from the components and their norms

compspandas.DataFrame

The components table.

normslist

The list of norms.

sum_histnumpy.ndarray

The sum histogram.

qpym2.hists.get_hist_settings(hm)

Return the nbins and range parameters for histogram according to the model

Args:

hm (hist_model): hist model

Raises:

TypeError: if the hist_type is not supported

Returns:

nbins, range: numbr of bins per axis and range (min, max) per axis

TODO: clean w/ copilot

qpym2.hists.get_empty_hist(hm, return_numpy=True)

Return an empty histogram according to hm

TODO: clean with copilot

qpym2.hists.smooth_nph2(h2, smooth=(1, 'k5b'))

qpym2.hists.create_hist_m2sum(rdf, hm, rtype='numpy')

create a 1D histogram of esum (m2sum)

qpym2.hists.create_hist_m2diff(rdf, hm, rtype='numpy')

create a 1D histogram of ediss (v*sqrt(2))

qpym2.hists.create_hist_m2e2(rdf, hm, rtype='numpy')

create a 1D histogram of e2

qpym2.hists.create_hist_h2ee(rdf, hm, rtype='numpy')

create a 2D histogram of e1 vs e2

qpym2.hists.create_hist_h2esumediff(rdf, hm, rtype='numpy')

create 2D histogram of ediff vs esum (scaled u,v)

qpym2.hists.create_hist_h2esume2(rdf, hm, rtype='numpy')

create 2D histogram of e2 vs esum

qpym2.hists.create_hist_h2uv(rdf, hm, rtype='numpy')

create 2D histogram of u vs v

qpym2.hists.get_hist_from_rdf(rdf, hm, rtype='numpy')

Return a histogram according to hm. Assumes ‘u’ and ‘v’ branches are present in rdf.

Args:

rdf (RDataFrame): RDataFrame object hm (hist_model): hist model rtype (str): return type. ‘numpy’ or ‘root’. Default is ‘numpy’.

Returns:

histogram: (histo, xedges, yedges) if return_numpy is True. otherwise return a THist variant (ROOT)

TODO: there must be a better version than if-else with enum