Python csv转化dbc
时间: 2023-11-05 19:00:42 浏览: 55
要将CSV文件转换为DBC文件,您需要使用Python中的一些库和工具。以下是实现此操作的一种方法:
1. 使用pandas库将CSV文件读入DataFrame对象中:
```python
import pandas as pd
csv_file = 'input.csv'
df = pd.read_csv(csv_file)
```
2. 使用canmatrix库创建CAN矩阵对象:
```python
from canmatrix import canmatrix
matrix = canmatrix.CanMatrix()
```
3. 将DataFrame中的数据添加到CAN矩阵对象中:
```python
for _, row in df.iterrows():
message = canmatrix.CanMessage(
frame_id=row['ID'],
name=row['NAME'],
size=row['DLC'],
cycle_time=row['CYCLE_TIME'],
signals=[]
)
for i in range(1, 9):
signal_name = row.get(f'SIGNAL_{i}_NAME')
if signal_name:
start_bit = row[f'SIGNAL_{i}_START_BIT']
length = row[f'SIGNAL_{i}_LENGTH']
is_little_endian = row[f'SIGNAL_{i}_ENDIANNESS'] == 'little'
factor = row[f'SIGNAL_{i}_FACTOR']
offset = row[f'SIGNAL_{i}_OFFSET']
unit = row[f'SIGNAL_{i}_UNIT']
signal = canmatrix.CanSignal(
name=signal_name,
start_bit=start_bit,
size=length,
is_little_endian=is_little_endian,
factor=factor,
offset=offset,
unit=unit
)
message.signals.append(signal)
matrix.add_frame(message)
```
4. 使用cantools库将CAN矩阵对象保存为DBC文件:
```python
import cantools
dbc_file = 'output.dbc'
with open(dbc_file, 'w') as f:
f.write(cantools.database.dump(matrix))
```
这里我们使用了pandas、canmatrix和cantools库来读取CSV文件、创建CAN矩阵对象和将DBC文件保存到磁盘。您需要使用pip安装这些库。