A simple library for calculating Gauge RnR
Project description
Gauge RnR
Documentations
This GaugeRnR package was built and tested using the resources bellow. If you want to learn more about Gauge RnR and ANOVA they are a great place to start!
Example
The package can be used in the following way:
from gaugeRnR import GaugeRnR
import numpy as np
# The input should be structeted in a 3d
# numpy array with shape [operators parts measurements]
# Example:
# m1 m2 m3
data = np.array( #
[[[3.29, 3.41, 3.64], # p1 | o1
[2.44, 2.32, 2.42], # p2
[4.34, 4.17, 4.27], # p3
[3.47, 3.5, 3.64], # p4
[2.2, 2.08, 2.16]], # p5
[[3.08, 3.25, 3.07], # p1 | o2
[2.53, 1.78, 2.32], # p2
[4.19, 3.94, 4.34], # p3
[3.01, 4.03, 3.2], # p4
[2.44, 1.8, 1.72]], # p5
[[3.04, 2.89, 2.85], # p1 | o3
[1.62, 1.87, 2.04], # p2
[3.88, 4.09, 3.67], # p3
[3.14, 3.2, 3.11], # p4
[1.54, 1.93, 1.55]]]) # p5
g = GaugeRnR(data)
g.calculate()
print(g.toTabulare())
This will result in the following table:
Sources of Variance | DF | SS | MS | Var (σ²) | Std (σ) | F-value | P-value |
---|---|---|---|---|---|---|---|
Operator | 2 | 1.63 | 0.815 | 0.054 | 0.232 | 100.322 | 0.000 |
Part | 4 | 28.909 | 7.227 | 0.802 | 0.896 | 889.458 | 0.000 |
Operator by Part | 8 | 0.065 | 0.008 | 0 | 0 | 0.142 | 0.996 |
Measurment | 30 | 1.712 | 0.057 | 0.057 | 0.239 | ||
Total | 44 | 32.317 | 0.734 | 0.913 | 0.956 |
To access the result from the Gauge RnR data directly:
from gaugeRnR import GaugeRnR, Component, Result
.
.
.
g = GaugeRnR(data)
result = g.calculate()
F = result[Result.F]
>>> print(F[Component.OPERATOR])
100.322
For more examples of how to use this library take a look at the unit tests!
Project details
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GaugeRnR-0.1.3.tar.gz
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