nes | C# NES emulator | Video Game library

My recollection was that a member of our team figured out we could generate sounds by turning something on and off quickly. This was the early 1980's and unfortunately I don't remember the specifics. But I think a key point is that we were flipping a switch, not computing the data for those waves. The waves that resulted were the results of a "pulsed" action. This may account for some of the early sounds but I think its also speculative. I wasn't the one directly involved, and theoretically, this at best only explains square and pulse waves, not triangle or sawtooth waves. Will be interested in what others come up with.

It looks like you're using this: https://github.com/tpoisot/bipy and that prova.py is your addition (it would be nice if you include this kind of information in your question in future questions!)

The problem is that bipartite_class is not a free-standing module, but is a part of the package bipy. That means you need to import it from outside the package. You need to move prova.py one directory up, to bipy-master, and change its contents to:

First off, it's important to know why you're missing data, and to see if you can possibly impute rather than just drop.

If you still want to drop, you can use df = df.dropna(how='any').

The reason why Excel shows "N/A" as the value for missing data is because that's Excel's way of showing missing data. It doesn't mean that the value of the cell that is missing data is N/A--that would be a string containing an N, a slash, and an A. Instead, you can try df = df[~df['Year'].isnull()] as an alternative method for selecting non-null values.

Where does the initial state that you want to compress come from? I guess there are three likely options.

1. It's random. Most likely that means some code seeded a pseudo random number generator using some value like e.g. the time of the day, then used that to produce the values. In this case, you could get your hands on the seed (which most likely would be a fairly short number) and use that as the identifier from which everything else is computed. Make sure to use a portable random number generator with well-defined deterministic behaviour, e.g. some Mersenne Twister implementation. The JavaScript built in number generator is implementation-defined so it does not fit this bill.

2. It came from some catalog made by the game developer (i.e. you). Then just obfuscating the index into that catalog might be good enough.

3. It came from some user hand-tuning the values. In this case you're out of luck, since as I understand the problem chances are that any possible combination could get entered. You can't compress a large set of values to a smaller set of values without losing information.

There might be middle grounds. You could have a randomised setup that subsequently got hand-tuned, and the description as initial seed plus a few modifications would be shorter than the full set of settings. Or the hand-tuning would only be allowed following specific rules set out by the game developer, which again would make for a limited set of possible values and a potentially shorter encoding. Thinking along these categories might help you analyze your own situation and find a suitable solution.

You can also look at this from an information theory point of view. You can't expect to encode a sequence of fully independent and uniformly distributed digits with less information than those digits, perhaps expressed in some other base or whatever. You can compress data if there are patterns to it that make some combinations more likely than others. The more you tell us about these patterns, the better we might be able to advise. In total you can't get below the entropy of the source (i.e. game state distribution), so estimating that might help you find a lower bound for what to expect.

Figured it out! Bryan Oakley in the comments mentioned that it might be the highlightcolor. I tried changing the color of that, and it didn't change anything. Intellisense, however, saved the day. It suggested using highlightbackground and highlightthickness, either of which I can use to hide the outline.

Keep only numeric columns in your dataframe and use xts :

The margins in your .row class is causing the issue:

MIDI channels and programs are stored on Instrument instances, so use getContextByClass(instrument.Instrument) to find the closest Instrument in the stream, and then access its .midiProgram.

Be careful:

• .midiChannel and .midiProgram are 0-indexed, so MIDI channel 10 will be 9 in music21, etc., (we're discussing changing this behavior in the next release)
• Some information might be missing if you're not running the bleeding edge version (we merged a patch yesterday on this topic), so I advise pulling from git: pip install git+https://github.com/cuthbertLab/music21
• .flat is going to kill you, though, if the file is multitrack. If you follow my advice you'll just get the last instrument on every track. 90% of the time people doing .flat actually want .recurse().

The reason why rasterize does not work in the end is obvious: the crs of the vector and raster do not match. But can you edit your question a bit more to explain what you want to achieve? It is very odd to create a raster and then polygons and then rasterize these again. My impression is that you are making things much more complicated than need be. You also talk about circles. Which circles? I am guessing you may want circles around your points, but that is not what you are doing. It would probably be helpful to figure out things step by step, first figure out how to get the general result you want, then how to get it Pacific centered.

Below is a cleaned up version of the first part of your code. It also makes it reproducible. You need to create example in code, like this: