Sunday, February 28
The closing credits of Hanamaru Kindergarten might win the nod for the best anime of the season.
Posted by: Pixy Misa at
11:53 PM
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Saturday, February 27
Also crazed starving weasels.
Posted by: Pixy Misa at
04:24 PM
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Friday, February 26
Now with added mouseoverness.
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02:00 AM
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Thursday, February 25
The Grand Unified Minx Theory
The mee.nu User Domains
The Minx Components
Posted by: Pixy Misa at
05:40 PM
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Wednesday, February 24
Naturally I had to try this...
100%
50%
Oops!
Now, that's a deliberately constructed corner case, but there is a problem there.
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12:40 PM
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Monday, February 22
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05:44 PM
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Sunday, February 21
I'm in here:
(Click for full screenshot. Thanks go to Steam and GOG's insane holiday sales.)
Actually, I'm not; I'm doing work for my day job, making some progress with Pita, reorganising Meta, and have finally come to a design decision on Miko (all parts of the Minx project for those who haven't been paying attention), redoing the documentation in Sphinx - which will itself be supported in an upcoming version of Meta - and planning for this year's server upgrade.* I did play a bit of Dragon Age over the holidays, but games are taking a back seat for a while.** Despite the fact that I have 224 of them currently installed.
* If things go right we'll be moving from a lowly 8-processor (16-thread) 2.26GHz server with 24GB of RAM to a spiffy new 12-processor (24-thread) 2.66GHz server with 48GB of RAM. That's at least partly to prepare for the move to Pita, which loves to store stuff in memory. Because I can just copy the OpenVZ virtual machines across, the move should be quick and painless.
** Apart from Billy vs. SNAKEMAN!
Posted by: Pixy Misa at
02:16 PM
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Hidamari Sketch continues to exist in its own little universe, and all is right with the world.
Posted by: Pixy Misa at
04:12 AM
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Saturday, February 20
In SQL* you say
select sum(sales) from accounts where state="NY"
. In Pita, the way to do this is:results = accounts.aggregate(state='NY')
**
which will calculate for you the count, length, sum, minimum and maximum, as appropriate, for all the fields in the table at once, so the value you need is results.sales.sum
. Since the table scan is typically slower than any calculations you're likely to be doing, this seems a reasonable approach.In addition, I've added a
results = accounts.stats()
which provides all those, plus mean,*** median, mode, standard deviation, and geometric and harmonic means. Aaaaand standard error, coefficient of variation, sample and population variance, skewness and kurtosis. I even sort of know what kurtosis is.I'm working on two more functions now,
group
and break
, though I may need to come up with another name for the latter because break is a Python keyword. This:for result in accounts.group('state', country='US'): ...
would give you the aggregate sales figures for each state in the US, sensibly enough. And this:for result in accounts.break('state', country='US'):
...
would give you the individual sales figures, and then automatically provide totals after the last sales record for each state.As long as I don't come down with kurtosis...
Update: Kang and jag. Or rather, agg and tab. For aggregate and tabulate.
for line in accounts.aggregate('state', country='US'): ...
will give you one summary line for each state, where for line in accounts.tabulate('state', country='US'):
...
would give you both detail and summary lines. I need to put subtotal and total flags on the records for tabulate. Have to watch the keywords, there. And keep my closet doors closed.* Boo, hiss!
** Or indeed
results =
accounts(state='NY').aggregate()Either way should perform the same and produce the same results. I think...*** Which should come out the same as the average; just one I'm calculating myself and the other I'm pulling out of a stats module.
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03:14 AM
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Tuesday, February 16
Okay, yeah, they needed that sharpening filter. That's Minx's built-in upscaling. Quality is not so hot, as it turns out. I'll check on what filter it's using; normally it's only used for downscaling, which works great:
Posted by: Pixy Misa at
11:35 AM
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