My own fitness tracker

Written on 15 February 2014, 11:05pm

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The awkward Tanita incident in the beginning of February inspired me to build my own fitness data input + visualising tool. After some nights of work, they are done; and I am pretty happy with the result. Screenshots and description below.

1. Background

I spent some time choosing the new repository for my data. After considering multiple options (like MongoDB, Google Fusion Tables, Dropbox xml, AWS), I chose a MySQL database + periodic Dropbox backup.
So, the measurement data was migrated from Tanita XML to MySQL. Funny enough, shortly after I started to work on this tool, my shared hosting provider had a data corruption incident (for the first time in 5 years since I am using them), and the database had to be restored. This is just another reminder to always backup 🙂
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Panini stickers follow up

Written on 30 January 2014, 11:23pm

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The previous post about Panini stickers got into some mathematical formulas. However, the 2 main conclusions were referring to the duplicates probability and distinct probability. That was the mathematical approach to the problem.
Below – the geeky one 🙂

1. Duplicates probability

In a Panini pack of 17 stickers (out of 192 possible stickers), there are 50% chances to have a duplicate.

The geeky way:
– generate a random array of ‘n’ integers in the range [1,192]
– calculate how many duplicates has the array
– repeat this a number of times to get a reliable view.

Results (PHP code at the end of the post):

Number of stickers - Probability of duplicate
10 - 20.47% 
11 - 25.8% 
12 - 31.2% 
13 - 37.13% 
14 - 40.6% 
15 - 45.47% 
16 - 47% 
17 - 53.4%
18 - 58.4% 
19 - 63.27% 
20 - 66.53% 
21 - 69.87% 
22 - 74.53% 
23 - 76.53% 
24 - 80.27% 
25 - 82.33% 
26 - 85.47% 
27 - 86.27% 
28 - 87.87% 
29 - 89.93% 
30 - 91.67% 
31 - 93.73% 
32 - 94.4% 
33 - 94.87% 
34 - 96.07% 
35 - 96.53% 
36 - 97.13% 
37 - 97.47% 
38 - 97.6% 
39 - 98% 
40 - 98.33% 

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