A python & numpy data type for floating point numbers with quantified uncertainity.
Project description
This package provides a python and numpy data type (uncertain) which implements a floating point value with quantified uncertainity, allowing for forward uncertainity propagation of uncorrelated values.
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pip install numcertain |
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A brief example of library usage is shown below:
from numpy import array
from numcertain.uncertain import uncertain
scalar = uncertain(42.0, 0.84)
array_a = array([uncertain(1.0, 0.1), uncertain(2.0, 0.2)])
array_b = array([3, 4]).astype(uncertain)
print(f"scalar: {scalar}")
print(f"array_a: {array_a}")
print(f"array_b: {array_b}")
print(f"array_a + array_b: {array_b + array_a}")
print(f"array_b - array_a: {array_a - array_b}")
print(f"array_a * array_b: {array_b * array_a}")
print(f"array_a / array_b: {array_b / array_a}")
scalar: 42.0±0.84
array_a: [uncertain(1.0, 0.1) uncertain(2.0, 0.2)]
array_b: [uncertain(3.0, 0.0) uncertain(4.0, 0.0)]
array_a + array_b: [uncertain(4.0, 0.1) uncertain(6.0, 0.2)]
array_b - array_a: [uncertain(-2.0, 3.1622776601683795) uncertain(-2.0, 4.47213595499958)]
array_a * array_b: [uncertain(3.0, 0.30000000000000004) uncertain(8.0, 0.8)]
array_a / array_b: [uncertain(3.0, 0.30000000000000004) uncertain(2.0, 0.2)]
See https://garryod.github.io/numcertain for more detailed documentation.
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