Add tutorial notebook for RISE on FRB timeseries data

.gitignore

@@ -17,6 +17,9 @@ coverage.xml
 .tox
 *word_vectors.txt.pt
 
+# tutorial model that is downloaded automatically
+tutorials/models/apertif_frb_dynamic_spectrum_model.onnx
+
 docs/_build
 
 # ide
@@ -36,4 +39,4 @@ venv3
 .python-version
 
 cache/
-dashboard/cache/
+dashboard/cache/

tutorials/README.md

@@ -1,7 +1,7 @@
 <img width="150" alt="Logo_ER10" src="https://user-images.githubusercontent.com/3244249/151994514-b584b984-a148-4ade-80ee-0f88b0aefa45.png">
 
 ## Tutorials
-This folder contains DIANNA tutorial notebooks. 
+This folder contains DIANNA tutorial notebooks.
 
 To install the dependencies for the tutorials, run
 ```
@@ -12,17 +12,17 @@ For general demonstration of DIANNA click on the logo [<img width="75" alt="Logo
 
 Click on the XAI method (explainer) names to watch explanatory videos for the respective method.
 
-Click on the logos below for direct access to a tutorial notebook for an explainability method and data modality/dataset. 
+Click on the logos below for direct access to a tutorial notebook for an explainability method and data modality/dataset.
 
-Run the tutorials directly in Google Colab by clicking on the Colab buttons below: 
+Run the tutorials directly in Google Colab by clicking on the Colab buttons below:
 
 |*Modality*\ Method|RISE|[LIME](https://youtu.be/d6j6bofhj2M)|Kernel[SHAP](https://youtu.be/9haIOplEIGM)|
 |:-----|:---|:---|:---|
 |*Images*|[<img width="25" alt="mnist_zero_and_one_half_size" src="https://user-images.githubusercontent.com/3244249/152540187-b7a8239f-6742-437f-8f9b-35b950ce5ddb.png">](rise_mnist.ipynb) or [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dianna-ai/dianna/blob/main/tutorials/rise_mnist.ipynb) | [<img width="20" alt="LeafSnap30 Logo" src="https://user-images.githubusercontent.com/3244249/151539100-dbdfe0f8-485f-45d4-a249-a1f79e970066.png">](lime_images.ipynb) or [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dianna-ai/dianna/blob/main/tutorials/lime_images.ipynb) | [<img width="25" alt="mnist_zero_and_one_half_size" src="https://user-images.githubusercontent.com/3244249/152540187-b7a8239f-6742-437f-8f9b-35b950ce5ddb.png">](kernelshap_mnist.ipynb) or [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dianna-ai/dianna/blob/main/tutorials/kernelshap_mnist.ipynb) |
 | | [<img width="94" alt="ImageNet_autocrop" src="https://user-images.githubusercontent.com/3244249/152542090-fd78fde1-6dec-43b6-a7ae-eea964b8ae28.png">](rise_imagenet.ipynb) or [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dianna-ai/dianna/blob/main/tutorials/rise_imagenet.ipynb) | | [<img width="20" alt="SimpleGeometric Logo" src="https://user-images.githubusercontent.com/3244249/151539027-f2fc3fc0-282a-4993-9680-74ee28bcd360.png">](kernelshap_geometric_shapes.ipynb) or [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dianna-ai/dianna/blob/main/tutorials/kernelshap_geometric_shapes.ipynb)|
 |*Text* |[<img width="25" alt="nlp-logo_half_size" src="https://user-images.githubusercontent.com/3244249/152540890-c8e1e37d-f0cc-4f84-80a4-2c59176cbf4c.png">](rise_text.ipynb) or [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dianna-ai/dianna/blob/main/tutorials/rise_text.ipynb) |[<img width="25" alt="nlp-logo_half_size" src="https://user-images.githubusercontent.com/3244249/152540890-c8e1e37d-f0cc-4f84-80a4-2c59176cbf4c.png">](lime_text.ipynb) or [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dianna-ai/dianna/blob/main/tutorials/lime_text.ipynb)  |[]()|
 | *Time series*| [<img width="25" alt="Weather Logo" src="https://user-images.githubusercontent.com/3244249/242001499-3ff3d639-ed2f-4a38-b7ac-957c984bce9f.png">](rise_timeseries_weather.ipynb) or [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dianna-ai/dianna/blob/main/tutorials/rise_timeseries_weather.ipynb)| [<img width="25" alt="Weather Logo" src="https://user-images.githubusercontent.com/3244249/242001499-3ff3d639-ed2f-4a38-b7ac-957c984bce9f.png">](lime_timeseries_weather.ipynb) or [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dianna-ai/dianna/blob/main/tutorials/lime_timeseries_weather.ipynb)| |
-| | | [<img width="25" alt="Coffe Logo" src="https://user-images.githubusercontent.com/3244249/241999275-9ab50a0f-5da3-41d2-80e9-70d2c8769162.jpg">](lime_timeseries_coffee.ipynb) or [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dianna-ai/dianna/blob/main/tutorials/lime_timeseries_coffee.ipynb) | |
+| | [<img width="25" alt="FRB logo" src="https://github.com/dianna-ai/dianna/assets/6370787/f53b280d-94b0-40ec-bfe7-ee48777d7964">](rise_timeseries_frb.ipynb) or [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dianna-ai/dianna/blob/main/tutorials/rise_timeseries_frb.ipynb) | [<img width="25" alt="Coffee Logo" src="https://user-images.githubusercontent.com/3244249/241999275-9ab50a0f-5da3-41d2-80e9-70d2c8769162.jpg">](lime_timeseries_coffee.ipynb) or [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dianna-ai/dianna/blob/main/tutorials/lime_timeseries_coffee.ipynb) | |
 | *Tabular* | | [<img width="75" alt="Penguin Logo" src="https://github.com/dianna-ai/dianna/assets/3244249/c7716ad3-f992-4557-80d9-1d8178c7ed57">](lime_tabular_penguin.ipynb) or [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dianna-ai/dianna/blob/main/tutorials/lime_tabular_penguin.ipynb) | |
 | | | [<img width="25" alt="Weather Logo" src="https://user-images.githubusercontent.com/3244249/242001499-3ff3d639-ed2f-4a38-b7ac-957c984bce9f.png">](lime_tabular_weather.ipynb) or [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dianna-ai/dianna/blob/main/tutorials/lime_tabular_weather.ipynb)| |
 
@@ -36,10 +36,8 @@ The datasets used in the tutorials are represented with their respective logos:
 |*Text*| [Stanford sentiment treebank](https://nlp.stanford.edu/sentiment/index.html) | <img width="25" alt="nlp-logo_half_size" src="https://user-images.githubusercontent.com/3244249/152540890-c8e1e37d-f0cc-4f84-80a4-2c59176cbf4c.png">|
 |*Timeseries* | [Coffee dataset](https://timeseriesclassification.com/description.php?Dataset=Coffee)  | <img width="25" alt="Coffe Logo" src="https://github.com/dianna-ai/dianna/assets/3244249/9ab50a0f-5da3-41d2-80e9-70d2c8769162">|
 |           | [Weather dataset](https://zenodo.org/record/7525955) | <img width="25" alt="Weather Logo" src="https://github.com/dianna-ai/dianna/assets/3244249/3ff3d639-ed2f-4a38-b7ac-957c984bce9f">|
+|           | FRB dataset | <img width="25" alt="FRB logo" src="https://github.com/dianna-ai/dianna/assets/6370787/f53b280d-94b0-40ec-bfe7-ee48777d7964">|
 |*Tabular*| [Penguin dataset](https://www.kaggle.com/code/parulpandey/penguin-dataset-the-new-iris)| <img width="75" alt="Penguin Logo" src="https://github.com/dianna-ai/dianna/assets/3244249/c7716ad3-f992-4557-80d9-1d8178c7ed57"> | |
 |           | [Weather dataset](https://zenodo.org/record/7525955) | <img width="25" alt="Weather Logo" src="https://github.com/dianna-ai/dianna/assets/3244249/3ff3d639-ed2f-4a38-b7ac-957c984bce9f">|
 
-The ONNX models used in the tutorials are available at [tutorials/models](https://github.com/dianna-ai/dianna/tree/main/tutorials/models).
-
-
-
+The ONNX models used in the tutorials are available at [tutorials/models](https://github.com/dianna-ai/dianna/tree/main/tutorials/models). The FRB model is available [here](https://zenodo.org/record/10656614)

tutorials/data/apertif_frb_classes.txt

@@ -0,0 +1,2 @@
+Noise
+FRB