Metadata-Version: 2.3
Name: sysloss
Version: 1.10.0
Summary: Power tree analysis of circuits, boards and systems.
License: MIT
Keywords: system,power,tree,loss,efficiency,energy,board,component,battery
Author: Geir Drange
Requires-Python: >=3.10,<4.0
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Electronic Design Automation (EDA)
Requires-Dist: matplotlib (>=3.0,<4.0)
Requires-Dist: packaging (>=21.1)
Requires-Dist: pandas (>=2.0,<3.0)
Requires-Dist: pillow (>=9.3.0)
Requires-Dist: pydot (>=3.0.0)
Requires-Dist: rich (>=12.0)
Requires-Dist: rustworkx (>=0.13)
Requires-Dist: scipy (>=1.9,<2.0)
Requires-Dist: toml (>=0.10.2)
Requires-Dist: tqdm (>=4.63)
Project-URL: Documentation, https://sysloss.readthedocs.io/en/latest/Getting%20started.html#
Project-URL: Homepage, https://github.com/geddy11/sysloss
Project-URL: Repository, https://github.com/geddy11/sysloss
Description-Content-Type: text/markdown


![](https://github.com/geddy11/sysloss/raw/main/docs/sysloss.svg)

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</p>

# sysLoss
sysLoss is a tool for analyzing power trees, system power and losses. From the smallest IoT sensor to large industrial installations. The tool is efficient and easy to use, the analysis result provides a detailed report on voltages, currents, power and efficiency for every component defined in the system. Output format is Pandas DataFrame: Create charts, plots and export to Excel and other formats. 

## Installation
```bash
$ pip install sysloss
```
or
```bash
$ conda install conda-forge::sysloss
```

## Usage
Analyze the power tree of a simple battery-powered bluetooth sensor:
```python
from sysloss.components import *
from sysloss.system import System

bts = System("Bluetooth sensor", Source("CR2032", vo=3.0, rs=10))
bts.add_comp("CR2032", comp=Converter("Buck 1.8V", vo=1.8, eff=0.87))
bts.add_comp("Buck 1.8V", comp=PLoad("MCU", pwr=13e-3))
bts.add_comp("CR2032", comp=Converter("Boost 5V", vo=5.0, eff=0.82))
bts.add_comp("Boost 5V", comp=RLoss("RC filter", rs=6.8))
bts.add_comp("RC filter", comp=ILoad("Sensor", ii=6e-3))
bts.tree()
```
```
Bluetooth sensor
└── CR2032
    ├── Boost 5V
    │   └── RC filter
    │       └── Sensor
    └── Buck 1.8V
        └── MCU
```
```python
df = bts.solve()
print(df)
```
![result](https://github.com/geddy11/sysloss/raw/main/docs/bts.png)

Create graphical power tree diagrams:
```python
import sysloss.diagram as sd

sd.make_diag(bts, fname="bts.png")
```
![tree](https://github.com/geddy11/sysloss/raw/main/docs/bts-tree.png)

And heat diagrams:
```python
sd.make_hdiag(bts, fname="bts-heat.png")
```
![heat](https://github.com/geddy11/sysloss/raw/main/docs/bts-heat-tree.png)

## Documentation
The [documentation](https://sysloss.readthedocs.io/en/latest/Getting%20started.html) includes tutorials in the form of Jupyter notebooks, located in docs/nb.

## Contributing

Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.

## License

`sysloss` was created by Geir Drange. It is licensed under the terms of the MIT license.

