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Nesting Tasks Dataset for 2D-Nesting Efficiency Estimation

Authors: Lallier, Corentin; Vézard, Laurent; Pinaud, Bruno; Blin, Guillaume;

Nesting Tasks Dataset for 2D-Nesting Efficiency Estimation

Abstract

Nesting efficiency dataset This is the raw dataset associated with the paper “Graph Neural Networks Comparison for 2D-Nesting Efficiency Estimation”, by C.Lallier, L. Vézard, B. Pinaud and G. Blin, 2022. Consisting of 100,000 nesting tasks. Usage: The files are: tasks.gz, parts.gz, constraints.gz, and shapes.gz. They are in PICKLE file format version 5 with a gzip compression. Example to load a file : import pandas as pd tasks = pd.read_pickle('tasks.gz') Description: Tasks.gz file contains nestings high-level descriptors. It is composed of the following columns: Column Type Description efficiency float The variable to predict (label). Given in % duration integer input data. The nesting algorithm convergence time. Given in s. sheet_width integer input data. The width of the nesting area. Given in m-4 sheet_length integer input data. Facultative. The height of the nesting area. Given in m-4 sheet_type integer input data. Kind of the nesting. tasks_index integer Generated data. Join key between tables. is_train, is_val, is_test boolean Generated data. Can be used as mask for the train, val and test subsets. Parts.gz contains description of the parts to be nested : Column Type Description tasks_index integer Reference to the join key from the Task table. parts_id integer Generated part id. shape_hash integer Reference to the hash of the part's shape, join key from the Shape table. Shapes.gz is the description of the shapes of the parts to be nested : Column Type Description shape_hash integer Generated data. Join key between tables. raw list of integers List of x, y tuples for each point. Unit is m-4 sizes list of integers List of sub-shapes sizes. Constraints.gz describes constraints and their parameters: Column Type Description type string Generated constraint type. tasks_index integer Reference to the join key from the Task table. parts_1, parts_2 list of integers References to the parts_id from the Parts table. p1_x, p1_y and p2_x, p2_y list of floats Input data. Origin position (x, y) of the constraint on parts. For each part of the constraint. r1_start, r1_end, r1_flip_x list of floats Input data. Rotation (start, end, and flip_x) parameters of the constraint. Multiple ranges accepted. y_min, y_max list of floats Input data. Range from (y_min, y_max). Multiple ranges accepted. x_offset, y_offset, motif_order, x_alignment_type, y_alignment_type, proximity_type, max_distance, groups_relative_orientation, is_frozen float Input data. Other constraint parameters.

Fix an error in 'constraints.gz', swap 'c8' and 'g4' values in column 'type'

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Nesting efficiency prediction

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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