Generate floats with Normal/Gaussian distribution #30
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We plan to add some documentation when this is merged! 😉 |
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Very cool! 🎉 |
lib/rantly/generator.rb
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| case distribution | ||
| when :normal | ||
| params[:center] ||= 0 | ||
| params[:scale] || = 1 |
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Syntax error here when I ran it. Remove extra space and align conditional assignment operator.
lib/rantly/generator.rb
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| raise "The distribution scale should be greater than zero" unless params[:scale].positive? | ||
| # Sum of 6 draws from a uniform distribution give as a draw of a normal | ||
| # distribution centered in 3 | ||
| ([rand, rand, rand, rand, rand, rand].sum - 3) * params[:scale] + center |
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Syntax error with center. Probably mean params[:center]?
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A test would be helpful for this, but it can be added later. |
Ana06
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@abargnesi I think you need to enable Travis builds for |
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@abargnesi please rereview it. I tried the code works now and I added a test. In the In the test a random center is generated. An array of 100 floats with a normal distribution centered in this center is also generated. The test checks that the average of the points is close to the center. I do not come up with a simpler way to test this. @vicgalle you may also want to take a look to the test 😉 |
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Good point regarding travis-ci, thanks! I enabled it for rantly-rb/rantly, see here. |
lib/rantly/generator.rb
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| raise "The distribution scale should be greater than zero" unless params[:scale].positive? | ||
| # Sum of 6 draws from a uniform distribution give as a draw of a normal | ||
| # distribution centered in 3 (central limit theorem). | ||
| ([rand, rand, rand, rand, rand, rand].sum - 3) * params[:scale] + params[:center] |
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Enumerable#sum was added in ruby 2.4.0. Since ruby 2.3 is still being maintained (see here) we should widen support by using reduce, e.g.:
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Actually in Travis there are many Ruby versions: https://travis-ci.org/rantly-rb/rantly/builds/320015060
Si I guess we want to support all of them. I'll change this then. 😉
test/rantly_test.rb
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| normal_points = Array.new(100){ float(:normal, { center: center }) } | ||
| [center, normal_points] | ||
| }.check{ |center, normal_points| | ||
| average_center = normal_points.sum / 100 |
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Same argument against using Enumerable#sum.
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Feel free to make additional commits to your branch for this PR. We can always squash all commits before merging to make |
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@abargnesi please re-review it 😉 There are some Travis builds failing: Couldn't find a repository matching this job but it seems unrelated to the changes as the test are passing, when reporting the coverage the job is not found 😕 |
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Test are passing now, I had used the @abargnesi @vicgalle should I merge this then? 😉 |
This allow us to generate points with more probability when we are closer to a limit/key point. The sum of 6 draws from a uniform distribution give as a draw of a normal distribution centered in 3. This is commonly used in programming for simplicity and it is proved by the central limit theorem. Contributes to rantly-rb#29 Co-authored-by: Víctor Gallego Alcalá <vicgalle@ucm.es>
When generating floats using the normal distribution, allow to specify the scale. This allow us to decide how close or far away should be the generated points from the limit/key point. Contributes to rantly-rb#29 Co-authored-by: Víctor Gallego Alcalá <vicgalle@ucm.es>
In the test a random center is generated. An array of 100 floats with a normal distribution centered in this center is also generated. The test checks that the average of the points is close to the center.
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No complains means I can merge it 😝 Merging.... 🚢 |
Add generations of floats using normal distribution, also called Gaussian distribution. This allow us to generate points with more probability when we are closer to a limit/key point. We also allow allow to specify the scale, which allow us to decide how close or far away should the generated points be from the limit/key point. 🤓
The sum of 6 draws from a uniform distribution give as a draw of a normal distribution centered in 3. This is commonly used in programming for simplicity and it is proved by the central limit theorem.
Closes #29.
Not sure if we should add some kind of tests here. 🤔
Pair-programmed by @Ana06 and @vicgalle.