Class bluedata

x.__init__(...) initializes x; see help(type(x)) for signature

Parameters:

• data (list(whatever)) - data to sample
• blueness (float) - How much should you avoid choosing the same item in succession? If -0.5 < blueness < 0, then you are more likely to choose the same item several times in a row. If 0 < blueness < 1, you are unlikely to choose the same item twice in succession (though it is possible). If blueness => 1, you will never get the same item twice until you've run through the entire list of data.
• rng - a random number generator, per the random module. You can generate repeated sequences of data by repeatedly passing it a random number generator in the same state.

Overrides: object.__init__

Add another datum to be sampled.

Parameters:

• datum (whatever) - thing to be added. It has a probability of 1/len(self) of being the next sample.

Pick n items from the data set.

Parameters:

• n (int) - how many items to pick.

Pick n items from the data set.

Parameters:

• n (int) - how many items to pick.

Returns: list(whatever), with length==n

Inspect (but do not remove) the next item to be picked.

Returns: whatever (not a list!)

the next item to be picked.

Split the data set into two parts, of size n and len(data)-n. Successive calls to split will avoid having the same items appear in the first part. For instance, given a bluedata of size 100, with ten calls to split(10), each datum will appear in the first part of the return tuple exactly once.

Returns: tuple(list, list)

Forget prior history of usage. Choices after this call are uncorrelated with choices before this call.