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ReadFileBase

class nndm_library.ReadFileBase(path, recursive=False, ext='.txt', relabel_events=True)

Class to read the labeled data coming in a format like the following:

data1 data2 data3

v11 v12 v13

. . .

. . .

. . .

vn1 vn2 vn3

where data1, data2, … respresent names and vij, a value in the given i row and column dataj.

Parameters

• path (string) – the direction to the file containing all the events information.

• recursive (bool) – read all the .lhe files found in all paths inside a given files_dir

• ext (str) – extension of the files to read

• relabel_events (bool) – there is an id for each possible event. For instance a collision have an id for it and two sub ids for the particle that interact in it. When relabel_events is True, the values of id are associated unequivocally with each event.

Variables

• data – dataframe with the read events

• files_dir – directory with the name of the files read and its id

add_angle(axes=['px', 'py', 'pz'], angle_axis='pz')

Calculate the angle of the particles starting from a list of the form [px, py, pz]. This with respect to the “axis” element.

extract_params_from_path()

Format is as follows: {particle_name}_{param1}_{value1}_{param2}_{value2}_{param3}_{value3}*.lhe An example would be eta_decay_events_mk_0.38_eps2_5.404557191441203e-07.lhe.

Returns

dictionary with all extracted data

ReadLhe

class nndm_library.ReadLhe(path, particle_ids=None, var_of_interest=None, outgoing=False, recursive=False, relabel_events=True, verbose=1)

Class to read the data coming in lhe format. By default it will read all the particles. Filters used apply to the such default data.

Parameters

• path (string) – the direction to the file containing all the events information.

• partcile_ids (list of integers) – ids of the particles to extract from the file according to the pdg, By default: None, which means exctract all the particles.

• var_of_interest (list of strings) – names of the variables to extract from the lhe. eg. [“e”,”angle”], [“e”,”px”,”py”] …. By default: None, which means exctract all the variables.

• outgoing (bool) – filtrate to obtain all the outgoing particles

• files_dir (string) – directory where the files are to be found

• recursive (bool) – read all the .lhe files found in all paths inside a given files_dir

• verbose (bool) – show progress reading all the .lhe files

Variables

• data – dataframe with the read events

• files_dir – directory with the name of the files read and its id

add_angle(axes=['px', 'py', 'pz'], angle_axis='pz')

Calculate the angle of the particles starting from a list of the form [px, py, pz]. This with respect to the “axis” element.

extract_params_from_path()

Format is as follows: {particle_name}_{param1}_{value1}_{param2}_{value2}_{param3}_{value3}*.lhe An example would be eta_decay_events_mk_0.38_eps2_5.404557191441203e-07.lhe.

Returns

dictionary with all extracted data

ReadRoot

class nndm_library.ReadRoot(path: str, output_base_tree='treeout', pattern_output='first', output_base_middle_branch='/e/out', leafs=['out.t', 'out.x', 'out.y', 'out.z', 'out._mass'], recursive=False, files_dir=None, relabel_events=True)

Class to read the labeled data coming in ROOT format. By default it assumes values for output_base_tree, pattern_output, output_base_middle_branch, and leafs. This is for a fast reading.

Parameters

• path (str) – the direction to the root file(s)

• output_base_name (str) – Name bas of the first node of the tree that has the data. For instance, if the base name is treeout, there options could be treeout1, treeout2, …., treeoutN.

• pattern_output (str) – The idea is this parameter define a methodology to choose from the possible first nodes that have a given output_base_name. As an example, first would choose treeoout1 in the example before.

• output_base_middle_branch (str) – middle branch that goes after the selected first node chosen by the output pattern. If this variable is “e/out”, following the example the tree to consult at the moment would be treeout1/e/out/.

• leafs (list of strings) – what are the leafs to exaplore in the actual branch. If out.a is the ouput name for the a momenta, giving a list [out.x, out.y] will give the data to consult. That is, treeout1/e/out/out.x and treeout1/e/out/out.y

• relabel_events (bool) – there is an id for each possible event. For instance a collision have an id for it and two sub ids for the particle that interact in it. When relabel_events is True, the values of id are associated unequivocally with each event.

Variables

• data – dataframe with the read events

• files_dir – directory with the name of the files read and its id

add_angle(axes=['px', 'py', 'pz'], angle_axis='pz')

Calculate the angle of the particles starting from a list of the form [px, py, pz]. This with respect to the “axis” element.

extract_params_from_path()

Format is as follows: {particle_name}_{param1}_{value1}_{param2}_{value2}_{param3}_{value3}*.lhe An example would be eta_decay_events_mk_0.38_eps2_5.404557191441203e-07.lhe.

Returns

dictionary with all extracted data

FilesManipulator

class nndm_library.FilesManipulator(path, particle_ids=None, var_of_interest=None, outgoing=False, verbose=0)

General methods intended for the manipulation of the files and its names in a given directory(ies).

Parameters

• path (string) – the direction to the file containing all the events information.

• partcile_ids – ids of the particles to extract from the file according to the pdg,

By default: None, which means exctract all the particles. :type partcile_ids: list of integers

Parameters

• var_of_interest (list of strings) – names of the variables to extract from the lhe. eg. [“e”,”angle”], [“e”,”px”,”py”] …. By default: None, which means exctract all the variables.

• outgoing (bool) – filtrate to obtain all the outgoing particles

Variables

scan –

it is a dictionary with the values of the benchmark points, each with its respective result sets of vaues of the variable of interest (var_of_interest). Note that the benchmark points are read from the name. Format is as follows: {particle_name}_{param1}_{value1}_{param2}_{value2}_{param3}_{value3}*.lhe An example would be eta_decay_events_mk_0.38_eps2_5.404557191441203e-07.lhe. Here we have pictorical description of the scan:

First, a list of ints is [int, int, …] == [(int)]. So a list of a list of floats is: [[(float)], [(float)], …] == [( [(float)] )] {id: [(int)], typ: [(str)], mk: [(float)], eps2: [(float)], px: [[(float)], [(float)], …], py: [( [(float)] )], pz: [( [(float)] )] } Note that momentum and energy are a list of arrays, where each array correspons to a param point

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