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**Structure tensor tutorials** for the implementation in https://github.com/Skielex/structure-tensor. This implementation is compatible with the python package `cupy`. Therefore, if you have large volumes to process and a graphical processing unit (GPU), you can speed up your computations simply by having a working installation of [cupy](https://docs.cupy.dev/en/stable/install.html).
## Orientation Analysis via the Structure Tensor
## Table of Content
1. [Description of Repository Content](#1)
2. [Set-up to run tutorials](#2)
1. [Description of repository content](#1)
2. [Local set-up to run the tutorials and the tool](#2)
3. [Resources and inspiration](#3)
4. [Contributions](#4)
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### 1. Description of Repository Content
The tutorials demonstrate the use of the structure tensor tool for the analysis of 2D and 3D data. The tutorials come with a set of utils (helper functions), named _utilsST_2D.py_- and _utilsST_3D.py_, to inspect the structure tensor output in various ways. The 2D and 3D example tutorials (_ST2D_examples_ and _ST3D_examples_) come as python scripts (.py) and Jupyter Notebooks (.ipynb). While the 2D script covers many examples, the 3D script dives into one example and thus comes with more details. You can also find a set of guided exercises with solution, names _ST2D_exercise_withSolutions.ipynb_. With these tutorials we would like you to 1) learn how to choose the parameters to obtain desirable results, 2) see different options for visualising the output of the structure tensor, and 3) get inspiration for scientific questions that you could answer with the structure tensor tool.
### 1. Description of repository content
The tutorials demonstrate the use of the structure tensor tool for the analysis of orienations in 2D and 3D data. With these tutorials we would like you to 1) learn how to choose the parameters to obtain desirable results, 2) see different options for visualising the output of the structure tensor, and 3) get inspiration for scientific questions that you could answer with the structure tensor tool. The 2D and 3D example tutorials (_ST2D_examples_ and _ST3D_examples_) come as python scripts (.py) and Jupyter Notebooks (.ipynb). While the 2D script covers many examples, the 3D script dives into one example and thus comes with more details. You can also find a set of guided exercises with solutions, names _ST2D_exercise_withSolutions.ipynb_. The tutorials come with a set of utils (helper functions), named _utilsST_2D.py_- and _utilsST_3D.py_, to inspect the output of the structure tensor in various ways.
These tutorials have been developed for the implementation in https://github.com/Skielex/structure-tensor. This implementation is compatible with the python package `cupy`. Therefore, if you have large volumes to process and a graphical processing unit (GPU), you can speed up your computations simply by having a working installation of [cupy](https://docs.cupy.dev/en/stable/install.html).
To find out more, click on the binder icon to run the tutorials online [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/git/https%3A%2F%2Flab.compute.dtu.dk%2FQIM%2Ftutorials%2Fstructuretensor/HEAD)
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### 2. Set-up to run tutorials
Run the tutorials online on [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/git/https%3A%2F%2Flab.compute.dtu.dk%2FQIM%2Ftutorials%2Fstructuretensor/HEAD) by pressing on the binder icon. If you want to run the tutorials locally, check our instructions for [installing Jupyter Notebooks](https://lab.compute.dtu.dk/QIM/tutorials/getting-started) and then follow the instructions below to install the tool.
### 2. Local set-up to run the tutorials and the tool
If you want to run the tutorials locally, check our instructions for [installing Jupyter Notebooks](https://lab.compute.dtu.dk/QIM/tutorials/getting-started) and then follow the instructions below to install the tool.
**Option 1: pip install**
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