A GUI to automatically create a TOPAS-readable MLC simulation file

Overview

topas-create-custom-mlc

A GUI to automatically create a TOPAS-readable MLC simulation file

Modern MLCs can have very compley leaf designs. Since not all geometries can be build using TOPAS, this script creates a custom MLC architecture from a CAD file describing a single leaf (.stl). Using a GUI, the positions of up to 64 leaf pairs can be individually customized - simply limited by the screen height. However, an arbitary amount of leaf pairs can be positioned using rectangular fields, or using presets.

Usage

Before starting the script, a couple of options need to be set to match the program to your .stl file.

Change the values in the ###Setup### portion of the script to match your requirements:

  • leaf_stl_path : Let TOPAS know where to find the .stl file describing the leaf
  • number_of_leaf_pairs : Number of leaf pairs in the MLC
  • MLC-TransZ : Distance from the Source to the top of the MLC, in cm
  • SSD : Source-Surface-Distance, in cm
  • dist_from_xy_plane_to_top_edge : Z-Coordinate of the .stl environment (ideally this would be 0), in mm
  • dist_from_z_axis_to_inner_edge : X-/Y-Coordinate of the .stl environment (deviation from centre axis), in mm

Preview

Preview

Extended Functionality

This program is capable of reflecting leaf bank rotation. The user can change TransY and RotX in the CreateTopasMLCFile() function (custom_mlc_creator_functions.py) to supply a list describing the rotation of each leaf as well as the vertical position. Also, this program assumes the .stl file is set up in so that the field defining face is already facing the Z-axis. In case it is not, the values in RotX should be changed to 0 instead of 180 (degrees).

Dependencies

Requires python3, numpy, and tkinter.
The tkSliderWidget.py is adapted from https://github.com/MenxLi/tkSliderWidget.

You might also like...
A custom-designed Spider Robot trained to walk using Deep RL in a PyBullet Simulation
A custom-designed Spider Robot trained to walk using Deep RL in a PyBullet Simulation

SpiderBot_DeepRL Title: Implementation of Single and Multi-Agent Deep Reinforcement Learning Algorithms for a Walking Spider Robot Authors(s): Arijit

 Notspot robot simulation - Python version
Notspot robot simulation - Python version

Notspot robot simulation - Python version This repository contains all the files and code needed to simulate the notspot quadrupedal robot using Gazeb

Megaverse is a new 3D simulation platform for reinforcement learning and embodied AI research

Megaverse Megaverse is a new 3D simulation platform for reinforcement learning and embodied AI research. The efficient design of the engine enables ph

NeuralWOZ: Learning to Collect Task-Oriented Dialogue via Model-based Simulation (ACL-IJCNLP 2021)
NeuralWOZ: Learning to Collect Task-Oriented Dialogue via Model-based Simulation (ACL-IJCNLP 2021)

NeuralWOZ This code is official implementation of "NeuralWOZ: Learning to Collect Task-Oriented Dialogue via Model-based Simulation". Sungdong Kim, Mi

 Fog Simulation on Real LiDAR Point Clouds for 3D Object Detection in Adverse Weather
Fog Simulation on Real LiDAR Point Clouds for 3D Object Detection in Adverse Weather

LiDAR fog simulation Created by Martin Hahner at the Computer Vision Lab of ETH Zurich. This is the official code release of the paper Fog Simulation

Simulation of the solar system using various nummerical methods

solar-system Simulation of the solar system using various nummerical methods Download the repo Make shure matplotlib, scipy etc. are installed execute

Doosan robotic arm, simulation, control, visualization in Gazebo and ROS2 for Reinforcement Learning.
Doosan robotic arm, simulation, control, visualization in Gazebo and ROS2 for Reinforcement Learning.

Robotic Arm Simulation in ROS2 and Gazebo General Overview This repository includes: First, how to simulate a 6DoF Robotic Arm from scratch using GAZE

Autonomous Ground Vehicle Navigation and Control Simulation Examples in Python

Autonomous Ground Vehicle Navigation and Control Simulation Examples in Python THIS PROJECT IS CURRENTLY A WORK IN PROGRESS AND THUS THIS REPOSITORY I

Simulation code and tutorial for BBHnet training data

Simulation Dataset for BBHnet NOTE: OLD README, UPDATE IN PROGRESS We generate simulation dataset to train BBHnet, our deep learning framework for det

Releases(v1.0.0)
Owner
Sebastian Schäfer
Masters student of medical physics and Python enthusiast.
Sebastian Schäfer
天勤量化开发包, 期货量化, 实时行情/历史数据/实盘交易

TqSdk 天勤量化交易策略程序开发包 TqSdk 是一个由信易科技发起并贡献主要代码的开源 python 库. 依托快期多年积累成熟的交易及行情服务器体系, TqSdk 支持用户使用极少的代码量构建各种类型的量化交易策略程序, 并提供包含期货、期权、股票的 历史数据-实时数据-开发调试-策略回测-

信易科技 2.8k Dec 30, 2022
a curated list of docker-compose files prepared for testing data engineering tools, databases and open source libraries.

data-services A repository for storing various Data Engineering docker-compose files in one place. How to use it ? Set the required settings in .env f

BigData.IR 525 Dec 03, 2022
Understanding the Generalization Benefit of Model Invariance from a Data Perspective

Understanding the Generalization Benefit of Model Invariance from a Data Perspective This is the code for our NeurIPS2021 paper "Understanding the Gen

1 Jan 15, 2022
Code to run experiments in SLOE: A Faster Method for Statistical Inference in High-Dimensional Logistic Regression.

Code to run experiments in SLOE: A Faster Method for Statistical Inference in High-Dimensional Logistic Regression. Not an official Google product. Me

Google Research 27 Dec 12, 2022
Implementing DeepMind's Fast Reinforcement Learning paper

Fast Reinforcement Learning This is a repo where I implement the algorithms in the paper, Fast reinforcement learning with generalized policy updates.

Marcus Chiam 6 Nov 28, 2022
Non-stationary GP package written from scratch in PyTorch

NSGP-Torch Examples gpytorch model with skgpytorch # Import packages import torch from regdata import NonStat2D from gpytorch.kernels import RBFKernel

Zeel B Patel 1 Mar 06, 2022
Contrastive Learning for Compact Single Image Dehazing, CVPR2021

AECR-Net Contrastive Learning for Compact Single Image Dehazing, CVPR2021. Official Pytorch based implementation. Paper arxiv Pytorch Version TODO: mo

glassy 253 Jan 01, 2023
Code for reproducing experiments in "Improved Training of Wasserstein GANs"

Improved Training of Wasserstein GANs Code for reproducing experiments in "Improved Training of Wasserstein GANs". Prerequisites Python, NumPy, Tensor

Ishaan Gulrajani 2.2k Jan 01, 2023
Official source code to CVPR'20 paper, "When2com: Multi-Agent Perception via Communication Graph Grouping"

When2com: Multi-Agent Perception via Communication Graph Grouping This is the PyTorch implementation of our paper: When2com: Multi-Agent Perception vi

34 Nov 09, 2022
Official implementation for "Symbolic Learning to Optimize: Towards Interpretability and Scalability"

Symbolic Learning to Optimize This is the official implementation for ICLR-2022 paper "Symbolic Learning to Optimize: Towards Interpretability and Sca

VITA 8 Dec 19, 2022
PyTorch implementation of Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy

Anomaly Transformer in PyTorch This is an implementation of Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy. This pape

spencerbraun 160 Dec 19, 2022
Breast Cancer Classification Model is applied on a different dataset

Breast Cancer Classification Model is applied on a different dataset

1 Feb 04, 2022
Code to reproduce the results in "Visually Grounded Reasoning across Languages and Cultures", EMNLP 2021.

marvl-code [WIP] This is the implementation of the approaches described in the paper: Fangyu Liu*, Emanuele Bugliarello*, Edoardo M. Ponti, Siva Reddy

25 Nov 15, 2022
Implementation of fast algorithms for Maximum Spanning Tree (MST) parsing that includes fast ArcMax+Reweighting+Tarjan algorithm for single-root dependency parsing.

Fast MST Algorithm Implementation of fast algorithms for (Maximum Spanning Tree) MST parsing that includes fast ArcMax+Reweighting+Tarjan algorithm fo

Miloš Stanojević 11 Oct 14, 2022
A Simulated Optimal Intrusion Response Game

Optimal Intrusion Response An OpenAI Gym interface to a MDP/Markov Game model for optimal intrusion response of a realistic infrastructure simulated u

Kim Hammar 10 Dec 09, 2022
AdaDM: Enabling Normalization for Image Super-Resolution

AdaDM AdaDM: Enabling Normalization for Image Super-Resolution. You can apply BN, LN or GN in SR networks with our AdaDM. Pretrained models (EDSR*/RDN

58 Jan 08, 2023
Randstad Artificial Intelligence Challenge (powered by VGEN). Soluzione proposta da Stefano Fiorucci (anakin87) - primo classificato

Randstad Artificial Intelligence Challenge (powered by VGEN) Soluzione proposta da Stefano Fiorucci (anakin87) - primo classificato Struttura director

Stefano Fiorucci 1 Nov 13, 2021
sequitur is a library that lets you create and train an autoencoder for sequential data in just two lines of code

sequitur sequitur is a library that lets you create and train an autoencoder for sequential data in just two lines of code. It implements three differ

Jonathan Shobrook 305 Dec 21, 2022
A PyTorch implementation of "Predict then Propagate: Graph Neural Networks meet Personalized PageRank" (ICLR 2019).

APPNP ⠀ A PyTorch implementation of Predict then Propagate: Graph Neural Networks meet Personalized PageRank (ICLR 2019). Abstract Neural message pass

Benedek Rozemberczki 329 Dec 30, 2022