The program helps with converting given CSV data in a specific convention from a vehicle to PDF overview raport.
Data refer to flight quality indicators of the quadcopter.
This data is related to actual orientation of vehicle and its desired values defined in RPY angles.
The quality indicators (RMS and SSE) are computed and displayed, aswell as visualised raw data and control errors.
The CSV file must be sent to this endpoint for data handling as file keyword:
| HTTP method | endpoint | description | request type | response type |
|---|---|---|---|---|
| 🟡 POST | /upload-data | get raport about flight data | CSV file | PDF file |
Command for testing:
curl -X POST -H "Content-Type: multipart/form-data" -F "file=@data.csv" --output Data-report.pdf http://localhost:8083/upload-data
Data have to be .csv format and columns stands for:
| rolld | pitchd | yawd | altituded | roll | pitch | yaw | altitude | isClamp |
where "d" suffix stands for "desired".
Example data sample can be found in data.csv file in the project folder.
Example input:
0.000000;0.200000;0.000000;20.000000;0.000000;0.200000;0.000000;20.000000;false
0.300000;0.000000;0.174524;25.000000;0.032357;0.185000;0.050000;20.500000;false
0.300000;0.000000;0.342020;25.000000;0.082606;0.170000;0.174524;21.000000;false
0.300000;0.000000;0.500000;25.000000;0.130000;0.140000;0.342020;22.000000;false
0.300000;0.000000;0.642788;25.000000;0.200000;0.100000;0.500000;23.000000;false
0.300000;0.000000;0.766044;25.000000;0.250000;0.060000;0.642788;24.000000;false
0.300000;0.000000;0.866025;25.000000;0.280000;0.030000;0.766044;24.500000;false
0.300000;0.000000;0.939693;25.000000;0.290000;0.020000;0.866025;24.800000;false
0.300000;0.000000;0.984808;25.000000;0.300000;0.010000;0.939693;25.000000;false
0.300000;0.000000;1.000000;25.000000;0.300000;0.000000;0.984808;25.000000;false
0.300000;0.000000;1.000000;25.000000;0.300000;0.000000;1.000000;25.000000;false
0.300000;0.000000;1.000000;25.000000;0.300000;0.000000;1.000000;25.000000;false
...
The result consists of numerical results and plots.
Golang is known for its goroutines performance.
Here is some collected data that shows the superiority of the parallel approach with a limited file size.
The results show the program execution time (milliseconds) for single-threaded and parallel versions.
(data samples = rows in csv file)
| Data samples | Single-thread | Goroutines |
|---|---|---|
| 1000 | 124 | 58 |
| 2000 | 130 | 62 |
| 4000 | 145 | 70 |
| 8000 | 176 | 88 |
| 16000 | 245 | 117 |
| 32000 | 335 | 182 |
| 64000 | 571 | 306 |
| 128000 | 1025 | 580 |
| 256000 | 1927 | 1116 |
| 512000 | 3970 | 2290 |
| 1024000 | 7584 | 4420 |
| 2048000 | 14998 | 8800 |
| 4096000 | 30009 | 17453 |
| 8192000 | 65727 | 34101 |
| 16384000 | 121729 | OUT OF RAM |
In this case, goroutines work well up to ~1 GB file size and this depends on the size of RAM used.
Until then, goroutines are about 2 times more efficient than the single-thread approach.
Follow these simple commands to deploy application. Building process:
docker build -t dataraport:go .Running in background:
docker run --name dataRaportContainer -d -p 8083:8083 dataraport:goNow the containerized application should run properly.
Flight-quality-overview-microservice is released under the MIT license.
Sebastian Brzustowicz <Se.Brzustowicz@gmail.com>