meter_proving 1.0.0

library to calculate random uncertanity of a measurment sequence

Meter proving

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

pip install meter-proving

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.

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%

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

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

poetry run pre-commit run --all-files