Thank you very much.
I know very little about numpy in fact.
If I don't find a pure matplotlib method, I will use your suggestion with
wx.
I think however matplotlib may be used only (and it will be even better as I
plan to make a Qt version in the future)
So, in :
from matplotlib.transforms import Value
from matplotlib.backends.backend_agg import RendererAgg
r = RendererAgg(50, 50, Value(72))
r.draw_image(0, 0, im)
What is the correct format for im ?
Thanks,
Nicolas
On 7/2/07, Christopher Barker <[EMAIL PROTECTED]> wrote:
I don't know how to do it with the MPL agg back-end, but I think you
mentioned wx, and you can do it there instead. a wxImage can be
constructed from a buffer object, then saved as a PNG. You may need to
set the rgb and alpha portions separately. See the wxPython wiki and
search for "Image".
Also:
> matrix = []
> buffer = self.get_renderer().tostring_argb()
> l, h = self.GetSize()
> for ligne in xrange(h):
> matrix.append([])
> for colonne in xrange(l):
> i = 4*(ligne*h + colonne)
> pixel = buffer[i:i+4]
> matrix[-1].append(pixel)
This is a very slow way to create the numpy array!
Option a: first create an empty array:
matrix = numpy.empty((l,h,4), numpy.byte)
then fill that in. but even better:
you can build the array directly from the buffer string:
matrix = numpy.fromstring(buffer, dtype=numpy.byte)
lotlib-users
--
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