https://github.com/justin900429/tea-tok-clock
Project for the Discrete Mathematics course in NYCU 2021 Fall
https://github.com/justin900429/tea-tok-clock
clock python raspberry-pi
Last synced: 2 months ago
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Project for the Discrete Mathematics course in NYCU 2021 Fall
- Host: GitHub
- URL: https://github.com/justin900429/tea-tok-clock
- Owner: Justin900429
- License: mit
- Created: 2021-11-06T11:20:15.000Z (over 4 years ago)
- Default Branch: main
- Last Pushed: 2022-01-16T09:23:30.000Z (over 4 years ago)
- Last Synced: 2025-05-22T08:36:44.794Z (about 1 year ago)
- Topics: clock, python, raspberry-pi
- Language: Python
- Homepage:
- Size: 1.94 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# README
## Introduction
In this project, we're going to measure time using some physics phenomenon. We choose to
use [Newton's law of cooling](https://en.wikipedia.org/wiki/Newton%27s_law_of_cooling) as the basics to figure out the
time.
## Set up the environment
```shell script
$ pip install -r requirements.txt
```
1. Push `tools` and `sensor.py` to RPI
2. The circuit should be set up:
## Experiments
To find k, we test it different ways:
* Finding the mean of k
* Using linear regression in log-scale
## Configuration
```python
K: float = 0.02 # Constant for the Newton Law of cooling
T_s: float = 23.0 # Surrounding temperature
T_initial: float = 100.0 # Initial temperature
HOST: str = "
"
PORT: str = ""
```
## Training
The training file is located in `train` folder. The default value is listed below.
```shell
$ python train/train.py \
--file_name exp/colling.csv \
--weight exp/model.pt
```
> For more training arguments, please see `train/train.py`
The training process will be like:
```
Epoch 1: 100%|██████████████████████████████████████████████| 465/465 [00:00<00:00, 1301.83it/s, Loss: 1.394]
Epoch 2: 100%|██████████████████████████████████████████████| 465/465 [00:00<00:00, 1259.02it/s, Loss: 0.867]
...
```
## Running code
To successfully activate the code, both `clock.py` and `server.py` should be started:
> Note: `sensor.py` or `sensor_sim.py` should be run first
```shell
# For simulation
$ python sensor_sim.py
$ python clock.py
```
```shell
# For cooling
$ python sensor.py
$ python clock.py --mode
```
```shell
# For heating
$ python sensor.py
$ python clock.py --mode model --heating --weight exp/heating.pt
```
The result would be like
