# jogcaetano13/heel_rise_jupyter_notebook architecture

> Architecture diagram of the GitHub repository jogcaetano13/heel_rise_jupyter_notebook, generated by GitDiagram from its file tree, README and a sample of source files (last updated 2026-09-25). It is an AI-made overview: check details against the source.

- Interactive diagram: https://gitdiagram.com/jogcaetano13/heel_rise_jupyter_notebook
- Repository: https://github.com/jogcaetano13/heel_rise_jupyter_notebook

## Overview

This is a heel-rise accelerometer analysis repository. Its documented workflow is to explore participant recordings, process signals and repetition metrics, and produce aggregated CSV results; a separate classifier investigates samples already logged as errors. The sampled Python code confirms raw-file conversion and signal-processing helpers, while the notebook internals were not sampled, so their documented roles are shown without inferring detailed calls between notebook stages.

Main entry points: [`generate_csv.ipynb`](https://github.com/jogcaetano13/heel_rise_jupyter_notebook/blob/main/generate_csv.ipynb) (CSV processing), [`classify_errors.py`](https://github.com/jogcaetano13/heel_rise_jupyter_notebook/blob/main/classify_errors.py) (Error classifier), [`data`](https://github.com/jogcaetano13/heel_rise_jupyter_notebook/tree/main/data) (Participant dataset), [`script.py`](https://github.com/jogcaetano13/heel_rise_jupyter_notebook/blob/main/script.py) (Recording converter)

## Diagram (Mermaid)

```mermaid
flowchart TD

subgraph group_ingest["Data ingestion"]
  node_converter["Recording converter<br/>[script.py]"]
  node_dataset["Participant dataset"]
end

subgraph group_analysis["Signal analysis"]
  node_csvnotebook["CSV processing<br/>[generate_csv.ipynb]"]
  node_helpers["Signal utilities<br/>[helpers.py]"]
  node_classifier["Error classifier<br/>[classify_errors.py]"]
end

subgraph group_outputs["Analysis outputs"]
  node_results["Processed results<br/>[results.csv]"]
  node_errors["Error log<br/>[errors.csv]"]
  node_classified["Classified errors"]
end

subgraph group_explore["Exploration"]
  node_overview["Dataset overview"]
end

node_analyst(("Analyst"))
node_rawfiles["Source recordings"]

node_rawfiles -->|"reads"| node_converter
node_converter -->|"writes"| node_dataset
node_analyst -->|"explores"| node_overview
node_overview -->|"examines"| node_dataset
node_analyst -->|"runs"| node_csvnotebook
node_csvnotebook -->|"processes"| node_dataset
node_csvnotebook -->|"writes"| node_results
node_csvnotebook -->|"writes"| node_errors
node_csvnotebook -->|"uses"| node_helpers
node_analyst -->|"runs"| node_classifier
node_classifier -->|"reads"| node_errors
node_classifier -->|"reads"| node_dataset
node_classifier -->|"uses"| node_helpers
node_classifier -->|"writes"| node_classified

click node_converter "https://github.com/jogcaetano13/heel_rise_jupyter_notebook/blob/main/script.py"
click node_dataset "https://github.com/jogcaetano13/heel_rise_jupyter_notebook/tree/main/data"
click node_overview "https://github.com/jogcaetano13/heel_rise_jupyter_notebook/blob/main/data_set_overview.ipynb"
click node_csvnotebook "https://github.com/jogcaetano13/heel_rise_jupyter_notebook/blob/main/generate_csv.ipynb"
click node_helpers "https://github.com/jogcaetano13/heel_rise_jupyter_notebook/blob/main/helpers.py"
click node_results "https://github.com/jogcaetano13/heel_rise_jupyter_notebook/blob/main/results.csv"
click node_errors "https://github.com/jogcaetano13/heel_rise_jupyter_notebook/blob/main/errors.csv"
click node_classifier "https://github.com/jogcaetano13/heel_rise_jupyter_notebook/blob/main/classify_errors.py"
click node_classified "https://github.com/jogcaetano13/heel_rise_jupyter_notebook/blob/main/errors_classified.csv"

classDef toneNeutral fill:#f8fafc,stroke:#334155,stroke-width:1.5px,color:#0f172a
classDef toneBlue fill:#dbeafe,stroke:#2563eb,stroke-width:1.5px,color:#172554
classDef toneAmber fill:#fef3c7,stroke:#d97706,stroke-width:1.5px,color:#78350f
classDef toneMint fill:#dcfce7,stroke:#16a34a,stroke-width:1.5px,color:#14532d
classDef toneRose fill:#ffe4e6,stroke:#e11d48,stroke-width:1.5px,color:#881337
classDef toneIndigo fill:#e0e7ff,stroke:#4f46e5,stroke-width:1.5px,color:#312e81
classDef toneTeal fill:#ccfbf1,stroke:#0f766e,stroke-width:1.5px,color:#134e4a
class node_converter,node_dataset toneBlue
class node_csvnotebook,node_helpers,node_classifier toneAmber
class node_results,node_errors,node_classified toneMint
class node_overview toneRose
class node_analyst,node_rawfiles toneIndigo
```

## Components

### Data ingestion

- [Recording converter](https://github.com/jogcaetano13/heel_rise_jupyter_notebook/blob/main/script.py): `script.py`
- [Participant dataset](https://github.com/jogcaetano13/heel_rise_jupyter_notebook/tree/main/data): `data`

### Signal analysis

- [CSV processing](https://github.com/jogcaetano13/heel_rise_jupyter_notebook/blob/main/generate_csv.ipynb): `generate_csv.ipynb`
- [Signal utilities](https://github.com/jogcaetano13/heel_rise_jupyter_notebook/blob/main/helpers.py): `helpers.py`
- [Error classifier](https://github.com/jogcaetano13/heel_rise_jupyter_notebook/blob/main/classify_errors.py): `classify_errors.py`

### Analysis outputs

- [Processed results](https://github.com/jogcaetano13/heel_rise_jupyter_notebook/blob/main/results.csv): `results.csv`
- [Error log](https://github.com/jogcaetano13/heel_rise_jupyter_notebook/blob/main/errors.csv): `errors.csv`
- [Classified errors](https://github.com/jogcaetano13/heel_rise_jupyter_notebook/blob/main/errors_classified.csv): `errors_classified.csv`

### Exploration

- [Dataset overview](https://github.com/jogcaetano13/heel_rise_jupyter_notebook/blob/main/data_set_overview.ipynb): `data_set_overview.ipynb`

### Other components

- **Analyst**
- **Source recordings**

## Connections

- Source recordings → Recording converter: reads
- Recording converter → Participant dataset: writes
- Analyst → Dataset overview: explores
- Dataset overview → Participant dataset: examines
- Analyst → CSV processing: runs
- CSV processing → Participant dataset: processes
- CSV processing → Processed results: writes
- CSV processing → Error log: writes
- CSV processing → Signal utilities: uses
- Analyst → Error classifier: runs
- Error classifier → Error log: reads
- Error classifier → Participant dataset: reads
- Error classifier → Signal utilities: uses
- Error classifier → Classified errors: writes