Hi,
I'm using matplotlib for my scientific analysis, and charmed by It's function.
Because I often use another tools for data histograming,
I think it's convenient if matplotlib could plot already histogramed data more efficiently.
For exmple, changing from
hist(x, bins=10, noplot=0, normed=0)
to
hist(x, bins=10, noplot=0, normed=0, weights=[], errors=[])
Calling
hist([0.5, 1.5, 1.7, 2.5], [0.0, 1.0, 3.0])
equals to
hist([0.5, 1.6, 2.5], [0.0, 1.0, 3.0], weights=[1.0, 2.0, 0.0])
or
hist([0.5, 1.6, 2.5], [0.0, 1.0, 3.0], weights=[1.0, 2.0, 0.0], errors=[1.0, 1.414, 0.0])
(1) When "weights" argument is provided, "x" is assumed as a list of weighted mean (or center) values of each bin and "weights" is assumed as a list of (already histogramed) weights of each bin.
(2) When "errors" argument is omitted, it's default values are set to the squares of weights.
(3) When "errors" argument is provided, it's values are used as a list of one-sigma errors of each bin.
Thank you for reading.
Koji