Write a wrapper function to unpack the arguments before calling the real function. Lambda won't work, for some strange un-Pythonic reason.
import multiprocessing as mp
print a + b
p = mp.Pool(4)
fl = [(a,b) for a in range(3) for b in range(2)]
#mf_wrap = lambda args: myfun(*args) -> this sucker, though more pythonic and compact, won't work
You can flow text into arbitrary shapes in inkscape. (From a hint here).
You simply create a text box, type your text into it, create a frame with some drawing tool, select both the text box and the frame (click and shift) and then go to text->flow into frame.
The omnipresent anonymous asked: Trying to enter sentence so that text forms the number three...any ideas?
The solution: Type '3' using the text toolConvert to path using object->pathSize as necessaryRemove fillUngroupType in actual text in new text boxSelect the text and the '3' pathFlow the text
I would say the most efficient AND readable way of working out confidence intervals from bootstraps is:
Where r is a n x b array where n are different runs (e.g different data sets) and b are the individual bootstraps within a run. This code returns the 95% CIs as three numpy arrays.
Confidence intervals can be computed by bootstrapping the calculation of a descriptive statistic and then finding the appropriate percentiles of the data. I saw that scipy.stats has a built in percentile function and assumed that it would work really fast because (presumably) the code is in C. I was using a simple minded Python/Numpy implementation by first sorting and then picking the appropriate percentile data. I thought this was going to be inefficient timewise and decided that using scipy.stats.scoreatpercentile was going to be blazing fast because
It was native C
It was vectorized - I could compute the CIs for multiple bootstrap runs at the same time