Metadata-Version: 2.1
Name: meter_proving
Version: 1.0.0
Summary: library to calculate random uncertanity of a measurment sequence
Author: StigHaraldGustavsen
Author-email: stighg@gmail.com
Requires-Python: >=3.10,<4.0
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Requires-Dist: numba (>=0.56.4,<0.57.0)
Description-Content-Type: text/markdown

# Meter proving
Simple package for caluclating random uncertanity of a set of repeted measurments.

![Tests](https://github.com/StigHaraldGustavsen/meter_proving/actions/workflows/tests.yml/badge.svg)

```Bash
pip install meter-proving
```


```python
from meter_proving import calculate_uncertanity

res = calculate_uncertanity([1000.00, 1000.00, 1000.00, 1000.25, 999.75])
print(res)
```

By default standard error is gotten from range of values, if this where to come from standard deviation set repetability param to false with a confidence intervall of 95% (coverage factor of almost 2), but theses can be parameterized.

```python
from meter_proving import calculate_uncertanity

res = calculate_uncertanity(
    [1000.00, 1000.00, 1000.00, 1000.25, 999.75],
    repetability = False
    )

print(res)
```

Standard error from standard deviation and has coverage factor of 1, witch gives a confidence interval of approx 68%

```python
from meter_proving import calculate_uncertanity

res = calculate_uncertanity(
    [1000.00, 1000.00, 1000.00, 1000.25, 999.75],
    coverage_factor = 1.0,
    repetability = False
    )

print(res)
```


### Start dev
```bash
poetry install
poetry config virtualenvs.in-project true
poetry run pre-commit run --all-files
```
### Run precommits
run precomits before you push code back to remote
```bash
poetry run pre-commit run --all-files
```

