In this post I’ll present a solution to a puzzle using Python. I think the primary value of this post is that it provides an example of how to translate an objective and a set of constraints into data structures and functions that can be interpreted by a computer. This problem breaks down into two interrelated parts:
- Translate the problem into data structures and functions
- Choose a strategy for finding the solution
If you create a bootable USB flash drive for installing linux on a machines, you may have trouble reformatting it later in Windows. It is possible to create a bootable USB in such a way that the Windows reformatting utility, obtained by right-clicking on the drive and selecting Format…, does not see the partition containing the bootloader. In such a situation, you may have a 8GB drive, but the reformatting utility only sees 6GB, and reformatting will not recover the original 8GB of space.
In this post I’ll consider performing a local hypothesis test for a difference in means with spatial data. I do not know if this is the optimal way to go about this sort of thing, but I have not yet found another solution. I think the best way to describe the problem is to consider the artificial data, and then wade through the code.
I didn’t finish the two posts I was editing this week, but I did draw a shoddy Arduino in GIMP with a Wacom tablet that you can use if you’d like. Below are PNG and XCF files with white and transparent backgrounds.
PNG, white background
PNG, transparent background
XCF, white background
XCF, transparent background