Sorry to repeat myself, but please reduce this to a short, self
contained example, that is absolutely minimal to demonstrate the
problem. http://sscce.org/ should help better explain what I'm after. I
don't want to find the needle in the haystack here -- there is code in
your example that doesn't even run, for example.
That said, are you really after creating a legend entry for each of the
dots? (See below). That just isn't going to work, and I'm not
surprised it eats up excessive amounts of memory. I think you want (and
can) reduce this to a single scatter call.
_series = [_ax1.scatter(_x, _y, color=_c, s=objsize, label=_l,
hatch='.') for _x, _y, _c, _l in izip(mydata_x, mydata_y, colors,
legends)] # returns PathCollection object
Mike
On 10/12/2013 12:57 PM, Martin MOKREJŠ wrote:
Hi,
so here is some quick but working example. I added there are 2-3 functions
(unused)
as a bonus, you can easily call them from the main function using same API
(except the piechart). I hope this shows what I lack in matplotlib - a general
API
so that I could easily switch form scatter plot to piechart or barchart without
altering
much the function arguments. Messing with return objects line2D,
PathCollection, Rectangle
is awkward and I would like to stay away from matplotlib's internals. ;) Some
can be sliced,
so not, you will see in the code.
This eatmem.py will take easily all your memory. Drawing 300000 dots is not
feasible
with 16GB of RAM. While the example is for sure inefficient in many places
generating the data
in python does not eat RAM. That happens afterwards.
I would really like to hear whether matplotlib could be adjusted instead. ;) I
already mentioned
in this thread that it is awkward to pre-create colors before passing all data
to a drawing
function. I think we could all save a lot if matplotlib could dynamically fetch
colors
on the fly from user-created generator, same for legends descriptions. I think
my example
code shows the inefficient approach here. Would I have more time I would
randomize a bit
more the sublist of each series so that the numbers in legends would be more
variable
but that is a cosmetic issue.
Probably due to my ignorance you will see that figures with legends have
different font
sizes, axes are rescaled and the figure. Of course I wanted to have the drawing
same via both
approaches but failed badly. The files/figures with legends should be just
accompanied by the
legend "table" underneath but the drawing itself should be same. Maybe an issue
with DPI settings
but not only.
I placed some comments in the code, please don't take them in person. ;) Of
course
I am glad for the existing work and am happy to contribute my crap. I am fine
if you rewamp
this ugly code into matplotlib testsuite, provide similar function (the API
mentioned above)
so that I could use your code directly. That would be great. I just tried to
show multiple
issues at once, notably that is why I included those unused functions. You will
for sure find
a way to use them.
Regarding the "unnecessary" del() calls etc., I think I have to use keep
some, Ben, because
the function is not always left soon enough. I could drop some, you are right,
but for some
I don't think so. Matplotlib cannot recycle the memory until me (upstream)
deletes the reference
so ... go and test this lousy code. Now you have a testcase. ;) Same with the
gc.collect() calls.
Actually, the main loop with 10 iteration is there just to show why I always
want to clear
a figure when entering a function and while leaving it as well. It happened too
many times that
I drawed over an old figure, and this was posted also few times on this list by
others. That is
a weird behavior in my opinion. We, users, are just forced to use too low-level
functions.
So, have fun eating your memory! :))
Martin
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