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carwatch-0.1.1
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مشاهده بیشترتوضیحات
A Python package for the CARWatch framework to improve cortisol awakening response sampling.
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | carwatch-0.1.1 |
| نام | carwatch |
| نسخه کتابخانه | 0.1.1 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Annika Muecke |
| ایمیل نویسنده | annika.muecke@fau.de |
| آدرس صفحه اصلی | https://github.com/mad-lab-fau/carwatch |
| آدرس اینترنتی | https://pypi.org/project/carwatch/ |
| مجوز | MIT |
# CARWatch
[](https://pypi.org/project/carwatch/)
[](https://github.com/mad-lab-fau/carwatch/actions/workflows/test-and-lint.yml)
[](https://github.com/psf/black)
**Get the Android app on the Play Store:**
[](https://play.google.com/store/apps/details?id=de.fau.cs.mad.carwatch)
CARWatch is an open-source framework to support **objective** and **low-cost** assessment of cortisol samples.
Its primary focus especially, but not limited to, during the **cortisol awakening response (CAR)** in real-world, unsupervised environments.
It consists of an [Android application](https://github.com/mad-lab-fau/carwatch-app) that schedules sampling times and tracks
them by scanning a barcode on the respective sampling tube as well as a Python package that provides tools to
**configure studies** and **prepare the study materials** and to **process the log data** recorded by the app.
## Features
In order to use CARWatch, you need to prepare the study materials and configure the app.
All these features are provided by `carwatch` which offers a user-friendly command-line interface
for the following tasks:
1. **Setting up a CAR study.**
This includes:
* Customizing study properties to your needs
* Setting up your desired sampling schedule
* Generating a QR-Code for the [CARWatch app](https://github.com/mad-lab-fau/carwatch-app) to automatically set up
the study in the app
2. **Creating printable labels with barcodes for objective sampling time assessment.**
This includes:
* Customizing the numer of saliva samples per day, the number of days, and the number of study participants
* Adding an optional evening saliva sample
* Customize barcodes to fit your printable label templates
3. **Analyzing the CARWatch log data.**
This includes:
* Extracting the sampling timestamps from the log data
* Extracting the self-reported awakening times (if available)
* Merging the time information with the cortisol measures
## Installation
`carwatch` requires Python >=3.8. First, install a compatible version of Python
(e.g. using [miniconda](https://docs.conda.io/en/latest/miniconda.html)). Then, open a terminal (or Anaconda prompt)
and install the `carwatch` package via pip:
```bash
pip install carwatch
```
Alternatively, you can download the package directly from the source repository on GitHub:
```bash
git clone https://github.com/mad-lab-fau/carwatch.git
cd carwatch
pip install .
```
### For Developer
If you are a developer and want to contribute to `carwatch` you can install an editable version of the package from
a local copy of the repository.
`carwatch` uses [poetry](https://python-poetry.org) to manage dependencies and packaging. Once you installed poetry,
run the following commands to clone the repository, initialize a virtual environment and install all development
dependencies:
```bash
git clone https://github.com/mad-lab-fau/carwatch.git
cd carwatch
poetry install
```
## Usage
`carwatch` can be used both **programmatically** and with the provided **command line interface (CLI)**.
The core functionalities of the `carwatch` package are
* creating a QR-Code for configuring the [CARWatch App](https://github.com/mad-lab-fau/carwatch-app) (Preparation),
* creating a PDF with printable barcode labels for the saliva sampling tubes (Preparation),
* and extracting the sampling times for the CARWatch app log recordings (Postprocessing).
### Programmatic Usage
For the preparation steps, the study details can be specified using the `Study` class. Participant IDs can also be
parsed from a *.csv file, when the path to it is specified as `subject_path`, and the corresponding column as
`subject_column`.
Some basic examples are given below. For more information about the available parameters, please refer to the
documentation of the mentioned classes.
#### Study Setup Example
```python
from carwatch.utils import Study
study = Study(
study_name="ExampleStudy",
num_days=3,
num_subjects=15,
num_samples=5,
subject_prefix="VP_",
has_evening_sample=True,
start_sample_from_zero=True,
)
```
#### Barcode Generation Example
For generating barcodes, the `LabelGenerator` class can be used, receiving a `Study` instance as a parameter. Your
custom printing label layout can be specified using the `CustomLayout` class. By default, the
[_AveryZweckform J4791_](https://www.avery-zweckform.com/vorlage-j4791) layout is used.
To start the PDF generation, call the `generate` method of the `LabelGenerator` class. The output PDF will be exported
to the directory specified by `output_dir` (per default: the current working directory).
```python
from carwatch.utils import Study
from carwatch.labels import CustomLayout, LabelGenerator
study = Study(
study_name="ExampleStudy",
num_days=3,
num_subjects=15,
num_samples=5,
subject_prefix="VP_",
has_evening_sample=True,
start_sample_from_zero=True,
)
generator = LabelGenerator(study=study, add_name=True, has_barcode=True)
layout = CustomLayout(
num_cols=3,
num_rows=4,
left_margin=3,
right_margin=3,
top_margin=2,
bottom_margin=2,
inter_col=0.2,
inter_row=0.5,
)
generator.generate(output_dir=".", debug=True, layout=layout)
```
#### QR-Code Generation Example
For generating the QR-Code, the `QrCodeGenerator` class can be used, again receiving a `Study` instance as a parameter.
The `saliva_distances` parameter specifies the desired distances between saliva samples in minutes. The resulting
QR-Code for setting up the CARWatch App will be exported to the directory specified by `output_dir` directory
(per default: the current working directory).
```python
from carwatch.qr_codes import QrCodeGenerator
from carwatch.utils import Study
if __name__ == "__main__":
study = Study(
study_name="ExampleStudy",
num_days=3,
num_subjects=15,
num_samples=5,
subject_prefix="VP_",
has_evening_sample=True,
start_sample_from_zero=True,
)
generator = QrCodeGenerator(study=study, saliva_distances=[10, 10, 10], contact_email="dum@my.com")
generator.generate(output_dir=".")
```
#### Postprocessing Example
To be added
### Command Line Interface
For the preparation steps, `carwatch` also provides a CLI for more convenient usage.
To use it, open a terminal session in the `carwatch` directory, and activate the corresponding python environment by
typing:
```
poetry shell
```
Then, start the CLI by typing:
```
python generate_labels.py
```
You will then be prompted to enter all the required information step-by-step. The desired output files will
be automatically generated for you.
For more information about the prompted commands please run:
```
python generate_labels.py --help
```
## License
This project is licensed under the MIT License. See the LICENSE file for details.
## Contributing
We welcome contributions to `carwatch`! For more information, have a look at the [Contributing Guidelines](CONTRIBUTING.md).
## Citing carwatch
If you use `carwatch` in your work, please report the version you used in the text. Additionally, please also cite
[our paper](https://www.sciencedirect.com/science/article/abs/pii/S0306453023000513?via%3Dihub) published in
Psychoneuroendocrinology:
```
Richer, R., Abel, L., Küderle, A., Eskofier, B. M., & Rohleder, N. (2023). CARWatch – A smartphone application for
improving the accuracy of cortisol awakening response sampling. Psychoneuroendocrinology, 151, 106073.
https://doi.org/10.1016/j.psyneuen.2023.106073
```
## Contact
If you have any questions or feedback about CARWatch, please contact
[Robert Richer](mailto:robert.richer@fau.de).
نیازمندی
| مقدار | نام |
|---|---|
| >=3.4.5,<4.0.0 | jupyterlab |
| >=0.14.0,<0.15.0 | python-barcode |
| >=2.5.2,<3.0.0 | CairoSVG |
| >=8.1.3,<9.0.0 | click |
| >=1.5.0,<2.0.0 | pandas |
| >=7.3.1,<8.0.0 | qrcode |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.8,<3.11 | Python |
نحوه نصب
نصب پکیج whl carwatch-0.1.1:
pip install carwatch-0.1.1.whl
نصب پکیج tar.gz carwatch-0.1.1:
pip install carwatch-0.1.1.tar.gz