GaugeRnR 0.1.4

A simple library for calculating Gauge RnR

Gauge RnR

Install

pip install GaugeRnR

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!

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!

• anova-gage-rr-part-1
• anova-gage-rr-part-2
• Introduction to Statistical Quality Control 6th Edition