Hi Robert,
On Fri, Jul 15, 2011 at 9:49 AM, robert <rob...@redcor.ch> wrote:
> Hi there,
> I am all new to mathlib world..
>
> What I try to do is plotting some charts over an image.
> I would be very grateful, if somebody could provide me with an example.
> thanks
> robert
>
>
I just did this myself with this code:
def make_cutouts(h5file, band=1, vmin=None, vmax=None, dir='.'):
"""Browse pixel data by pixel selection
A shift-left-click on a pixel in ``image`` creates a plot of
the response data for that pixel. A shift--click on the
resulting plot will save it to two files in ``dir`` whose names
are of the form cutout-xcen-ycen.{dat,png}, where xcen and ycen
are replaced with the location of image center. The png file is
an rgb img, the dat file is raw uint16 data.
Parameters
----------
h5file : string
Path to h5 file containing image data.
band : int
Band to use. Must be 0 or 1.
vmax, vmin : float, optional
Maximum and minimum values to which the image will be scaled.
dir : string, optional
Path to directory in which plots will be saved.
"""
import matplotlib.pyplot as plt
import h5py
from widgets import Button
# get image data here so that it gets compiled into onclick
fin = h5py.File(h5file, 'r')
img = fin['band%d' % band][...]
src = fin['/'].attrs['input_filename']
fin.close()
m, n = img.shape
# make points for drawing square cutout
xcor = np.array([-128, 128, 128, -128, -128], dtype=float)/10
ycor = np.array([-128, -128, 128, 128, -128], dtype=float)/10
def save(fig, mouse, data):
def onclick(event):
if event.button == 1:
xcen = mouse.xdata
ycen = mouse.ydata
i = int(xcen + .5)*10
j = int(ycen + .5)*10
# write data to file
path = os.path.join(dir, 'cutout-%05d-%05d' % (i,j))
fout = h5py.File(path + '.h5', 'w')
fout.create_dataset('image', data.shape, data.dtype)
fout['/'].attrs['input_filename'] = src
fout['/'].attrs['x_center_pixel'] = i
fout['/'].attrs['y_center_pixel'] = j
fout['image'][...] = data
fout.close()
fig.savefig(path + ".png")
# draw square around cutout
mouse.inaxes.plot(xcen + xcor, ycen + ycor, 'r', lw=2)
mouse.canvas.draw()
return onclick
def onclick(event):
mouse = event.mouseevent
if mouse.button == 1 and mouse.key == "shift":
i = int(mouse.xdata + .5)*10
j = int(mouse.ydata + .5)*10
src_axs = mouse.inaxes
ul_x = max(0, i - 128)
ul_y = max(0, j - 128)
lr_x = min(n, i + 128)
lr_y = min(m, j + 128)
data = img[ul_y:lr_y, ul_x:lr_x]
#
newfig = plt.figure()
newfig.subplots_adjust(top=.90)
# add save button
butax = newfig.add_axes([0.45, .92, .1, 0.04])
button = Button(butax, 'Save', color='red', hovercolor='gold')
button.on_clicked(save(fig, mouse, data))
# display image of cutout
axs = newfig.add_subplot(111)
tmp = axs.imshow(data)
newfig.colorbar(tmp)
newfig.show()
fig = plt.figure()
axs = fig.add_subplot(111)
tmp = axs.imshow(img[::10, ::10], vmin=vmin, vmax=vmax, origin='lower',
picker=True)
xmin, xmax, ymin, ymax = np.array(tmp.get_extent()) + .5
axs.set_xticks([t for t in axs.get_xticks() if t >= 0 and t <= xmax])
axs.set_yticks([t for t in axs.get_yticks() if t >= 0 and t <= ymax])
fig.canvas.mpl_connect("pick_event", onclick)
fig.show()
Which is probably more complex than what you need. What it does is display a
thumbnail of a very large image on which you can shift-click to blowup a
256x256 portion in a separate figure. If you then click the (custom) save
button on the blowup it saves the data together with a thumbnail and plots a
square around the cutout pixels in the original image. The tricky part is
that the image axis generally starts at -.5 and this will cause problems as
the plot will want to put up it's own ticks that excede the image bounds and
you will get big white borders where you don't want them. Hence I call
axs.set_xticks etc. to remove the offending ticks. To bad the image itself
doesn't make its own ticks available.
I had to rewrite the button code to make this work as the first click
handler takes the button with it when it exits as the figure doesn't keep a
reference to it, but that is another problem ;)
Chuck
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