Package: grim
The GRIM testAn implementation of the GRIM test, in pythonIntroductionThis package is based on the GRIM (Granularity-Related Inconsistency of Means) test first highlighted by Heathers & Brown in their 2016 paper.The test makes use of a simple numerical property to identify if the mean of integer values has been correctly calculated.You don't need the original integer values. You just need themeanand the number (n) of items.What about rounding?Often themeanyou are testing has previously been rounded. You can check if themeanis consistent with a particular rounding type by including that as an argument.This implementation supports all the rounding types found in the Pythondecimalimplementation(at least between versions 3.8 and 3.11).(They are: ROUND_CEILING, ROUND_DOWN, ROUND_FLOOR, ROUND_HALF_DOWN, ROUND_HALF_EVEN, ROUND_HALF_UP, ROUND_UP, ROUND_05UP)If no rounding type is included then the test assumes ROUND_HALF_UP.How do I install it?On the command line:pipinstallgrimIn a google Colab/iPython/Jupyter notebook:!pipinstallgrimExample: Is thismean,nand rounding type consistent?fromgrimimportmean_testerimportdecimal# mean is 11.09 and n is 21print(mean_tester.consistency_check('11.09','21',decimal.ROUND_HALF_UP))This will returnFalseas the mean could not be correct given a list of 21 integers (and using ROUND_HALF_UP rounding.)Example: Is thismean&nconsistent using any rounding type?fromgrimimportmean_testerimportdecimal# mean is 11.09 and n is 21print(mean_tester.summary_consistency_check('11.09','21'))This will return:{'ROUND_CEILING':False,'ROUND_DOWN':True,'ROUND_FLOOR':True,'ROUND_HALF_DOWN':False,'ROUND_HALF_EVEN':False,'ROUND_HALF_UP':False,'ROUND_UP':False,'ROUND_05UP':True}As you can see, a given mean and n might be consistent using one form of rounding but not others.You can pass in the numbers as Strings or Decimals, this avoids floating point accuracy issues that are more likely to occur when using a 'float'.How do I see some logging about how the possible matches the algorithm has considered?Add an extra argument,log_status=True.print(mean_tester.summary_consistency_check('11.09','21',log_status=True))The output would look this:Tue, 18 Apr 2023 18:02:00 +0000 : Target Mean: 11.09, Decimal places: 2, Lower match: 11.00, Middle match: 11.05, Upper match: 11.10, Match status: False, Rounding method: ROUND_CEILING
Tue, 18 Apr 2023 18:02:00 +0000 : Target Mean: 11.09, Decimal places: 2, Lower match: 11.00, Middle match: 11.04, Upper match: 11.09, Match status: True, Rounding method: ROUND_DOWN
Tue, 18 Apr 2023 18:02:00 +0000 : Target Mean: 11.09, Decimal places: 2, Lower match: 11.00, Middle match: 11.04, Upper match: 11.09, Match status: True, Rounding method: ROUND_FLOOR
Tue, 18 Apr 2023 18:02:00 +0000 : Target Mean: 11.09, Decimal places: 2, Lower match: 11.00, Middle match: 11.05, Upper match: 11.10, Match status: False, Rounding method: ROUND_HALF_DOWN
Tue, 18 Apr 2023 18:02:00 +0000 : Target Mean: 11.09, Decimal places: 2, Lower match: 11.00, Middle match: 11.05, Upper match: 11.10, Match status: False, Rounding method: ROUND_HALF_EVEN
Tue, 18 Apr 2023 18:02:00 +0000 : Target Mean: 11.09, Decimal places: 2, Lower match: 11.00, Middle match: 11.05, Upper match: 11.10, Match status: False, Rounding method: ROUND_HALF_UP
Tue, 18 Apr 2023 18:02:00 +0000 : Target Mean: 11.09, Decimal places: 2, Lower match: 11.00, Middle match: 11.05, Upper match: 11.10, Match status: False, Rounding method: ROUND_UP
Tue, 18 Apr 2023 18:02:00 +0000 : Target Mean: 11.09, Decimal places: 2, Lower match: 11.00, Middle match: 11.04, Upper match: 11.09, Match status: True, Rounding method: ROUND_05UP
{'ROUND_CEILING': False, 'ROUND_DOWN': True, 'ROUND_FLOOR': True, 'ROUND_HALF_DOWN': False, 'ROUND_HALF_EVEN': False, 'ROUND_HALF_UP': False, 'ROUND_UP': False, 'ROUND_05UP': True}A warning about floating point numbers & computers:Beware of creating Decimals from floating point numbers as these may have floating point inaccuracies.e.g.:importdecimalprint(decimal.Decimal(1.1))1.100000000000000088817841970012523233890533447265625Notice how the inaccurate representation of 1.1 from the floating point number has been preserved in the Decimal. Its better to create a decimal from a String E.g.:importdecimalprint(decimal.Decimal('1.1'))1.1Many tools can be configured to read in text [that might be a number] as a string with out parsing. Some tools, such as Webdriver, only return a string (Which is useful!)For more information on the origins of these issues in modern computer languagesread this.How can I find out more about the GRIM test?James Heathers has publishedarticlesthat explain how the technique works and how he used it to expose inconsistencies in scientific papers.Citation fileThere is acitation fileincluded in the code repo.