I use Matplotlib to generate PNG files of scatterplots. Now, for each scatterplot, in addition to a PNG file, I would *also* like to generate a list of pixel coordinates of the various points in the scatterplot.

The code I use to generate the PNG files for the scatterplots is basically like this:

```
from matplotlib.figure import Figure
from matplotlib.pyplot import setp
from matplotlib.backends.backend_agg import FigureCanvasAgg
...
fig = Figure(figsize=(3, 3), dpi=100)
ax = fig.gca()
for (x, y), m, c in zip(points, markers, colors):
ax.scatter(x, y, marker=m, c=c, s=SIZE, vmin=VMIN, vmax=VMAX)
# several assorted tweaks like ax.spines['top'].set_color('none'), etc.
setp(fig, 'facecolor', 'none')
# FigureCanvasAgg(fig).print_png(FILEPATH)
```

...(where the variables in UPPERCASE stand for settable parameters).

How can I also produce a list of `(px, py)`

pairs of the pixel coordinates in the resulting PNG corresponding to the points in `points`

?

[EDIT: removed some nonsense about `imshow`

.]

[EDIT:

OK, here's what I finally came up with, based on Joe Kington's suggestions.

```
# continued from above...
cnvs = FigureCanvasAgg(fig)
fig.set_canvas(cnvs)
_, ht = cnvs.get_width_height()
pcoords = [(int(round(t[0])), int(round(ht - t[1]))) for t in
ax.transData.transform(points)]
fig.savefig(FILEPATH, dpi=fig.dpi)
```

The resulting pixel coords (in `pcoords`

) are pretty close to the correct values. In fact, the y coords are exactly right. The x coords are 1 or 2 pixels off, which is good enough for my purposes.

]

Doing this is fairly simple, but to understand what's going on, you'll need to read up a bit on matplotlib's transforms. The transformations tutorial is a good place to start.

At any rate, here's an example:

```
import numpy as np
import matplotlib.pyplot as plt
fig, ax = plt.subplots()
points, = ax.plot(range(10), 'ro')
ax.axis([-1, 10, -1, 10])
# Get the x and y data and transform it into pixel coordinates
x, y = points.get_data()
xy_pixels = ax.transData.transform(np.vstack([x,y]).T)
xpix, ypix = xy_pixels.T
# In matplotlib, 0,0 is the lower left corner, whereas it's usually the upper
# right for most image software, so we'll flip the y-coords...
width, height = fig.canvas.get_width_height()
ypix = height - ypix
print 'Coordinates of the points in pixel coordinates...'
for xp, yp in zip(xpix, ypix):
print '{x:0.2f}\t{y:0.2f}'.format(x=xp, y=yp)
# We have to be sure to save the figure with it's current DPI
# (savfig overrides the DPI of the figure, by default)
fig.savefig('test.png', dpi=fig.dpi)
```

This yields:

```
Coordinates of the points in pixel coordinates...
125.09 397.09
170.18 362.18
215.27 327.27
260.36 292.36
305.45 257.45
350.55 222.55
395.64 187.64
440.73 152.73
485.82 117.82
530.91 82.91
```

Try annotation box : http://matplotlib.org/examples/pylab_examples/demo_annotation_box.html

```
import matplotlib.pyplot as plt
from matplotlib.offsetbox import TextArea, DrawingArea, OffsetImage, \
AnnotationBbox
for (x, y), m, c in zip(points, markers, colors):
ax.scatter(x, y, marker=m, c=c, s=SIZE, vmin=VMIN, vmax=VMAX)
for px, py in zip(x,y):
offsetbox = TextArea( " %s, %s" (px, py ) , minimumdescent=False)
ab = AnnotationBbox(offsetbox,(px, py ),
xybox=(-20, 40),
xycoords='data',
boxcoords="offset points",
arrowprops=dict(arrowstyle="->"))
ax.add_artist(ab)
```

I don't have matplotlib installed on my current computer, so my code might not work.

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