https://github.com/c0sogi/python-dcm
A high-performance Python package for handling ETAS DCM(Data Conversion Format) files used in engine calibration tools like INCA, MDA, EHANDBOOK, and CANape.
https://github.com/c0sogi/python-dcm
automotive dcm ecu-calibration etas inca numpy pandas python
Last synced: 3 months ago
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A high-performance Python package for handling ETAS DCM(Data Conversion Format) files used in engine calibration tools like INCA, MDA, EHANDBOOK, and CANape.
- Host: GitHub
- URL: https://github.com/c0sogi/python-dcm
- Owner: c0sogi
- Created: 2024-11-27T13:47:11.000Z (5 months ago)
- Default Branch: main
- Last Pushed: 2024-12-20T15:18:51.000Z (4 months ago)
- Last Synced: 2024-12-29T08:23:55.343Z (4 months ago)
- Topics: automotive, dcm, ecu-calibration, etas, inca, numpy, pandas, python
- Language: Python
- Homepage:
- Size: 80.1 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# python-dcm
A high-performance Python package for handling ETAS DCM(Data Conversion Format) files used in engine calibration tools like INCA, MDA, EHANDBOOK, and CANape.
## Quick Start
```python
from dcm import DCM
# Read a DCM file
dcm = DCM.from_file('calibration.dcm')
# Access calibration data
parameter_value = dcm.parameters['ENGINE_SPEED'].value
map_data = dcm.maps['FUEL_MAP'].dataframe
curve_data = dcm.curves['BOOST_CURVE'].series
# Interpolate values
x_points = [1000, 1500, 2000] # RPM
y_points = [50, 75, 100] # Load %
interpolated = dcm.maps['FUEL_MAP'].as_function(x_points, y_points)
# Visualize data
dcm.maps['FUEL_MAP'].to_figure()
```
## Key Features
- **Easy Data Access**: Directly access parameters, curves, and maps with Pandas integration
- **Interpolation**: Built-in 1D/2D linear interpolation for real-time value calculation
- **Visualization**: One-line plotting of characteristic curves and maps
- **Excel Integration**: Import/export calibration data from Excel spreadsheets
- **Set Operations**: Compare and merge DCM files with `|`, `-`, `&`, and `%` operators
- **Type Support**: Handle all DCM data types including fixed/group characteristics
## Installation
Requires Python ≥ 3.10
```bash
pip install python-dcm
```
## Common Use Cases
### Data Access & Manipulation
```python
# Get parameter value
rpm_limit = dcm.parameters['MAX_RPM'].value
# Access map as DataFrame
fuel_map = dcm.maps['FUEL_MAP'].dataframe
fuel_map.iloc[0, 0] = 14.7 # Modify value
# Get curve data
boost_curve = dcm.curves['BOOST_CURVE'].series
max_boost = boost_curve.max()
```
### Excel Integration
```python
# Load calibration data from Excel
dcm.load_from_excel(
maps_path='maps.xlsx',
curves_path='curves.xlsx',
parameters_path='params.xlsx'
)
# Each sheet name becomes the calibration object name
```
### Visualization
```python
import matplotlib.pyplot as plt
# Plot a map with custom settings
fig, ax = dcm.maps['FUEL_MAP'].to_figure(
cmap='viridis',
fontsize=12
)
plt.show()
# Plot multiple curves
fig, ax = plt.subplots()
dcm.curves['BOOST_LOW'].to_figure(ax=ax, label='Low')
dcm.curves['BOOST_HIGH'].to_figure(ax=ax, label='High')
plt.legend()
```
### Advanced Features
#### Parameter Type Conversion
```python
param = dcm.parameters['CONTROL_BITS']
binary = param.as_bin() # [1, 3, 5] (bits set to 1)
hex_val = param.as_hex() # [A, F, 1] (hexadecimal digits)
```
#### DCM File Comparison
```python
# Find differences between calibrations
modified = old_dcm % new_dcm
print(modified.parameters.keys()) # Changed parameters
# Merge calibrations
combined = dcm1 | dcm2
```
## Supported Data Types
- Parameters (FESTWERT)
- Parameter Blocks (FESTWERTEBLOCK)
- Characteristic Lines (KENNLINIE/FESTKENNLINIE/GRUPPENKENNLINIE)
- Characteristic Maps (KENNFELD/FESTKENNFELD/GRUPPENKENNFELD)
- Distributions (STUETZSTELLENVERTEILUNG)
- Text Strings (TEXTSTRING)
## Dependencies
- NumPy ≥ 1.20.0
- Pandas ≥ 1.5.0
- Matplotlib ≥ 3.0.0
- OpenPyXL ≥ 3.1.0
## License
MIT License
## Contributing
Contributions welcome! Please format code with [ruff](https://docs.astral.sh/ruff/) before submitting PRs.
## Contact
- Author: c0sogi
- Email: [email protected] or [email protected]
Feel free to reach out for questions or suggestions.
---
For detailed documentation and examples, visit our [GitHub repository](https://github.com/c0sogi/python-dcm).