library to calculate random uncertanity of a measurment sequence
Project description
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
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