def callback(br, m):
_ = users, sct # FIXME: ip only seems to take local and global; sct is neither..
newsizes = np.array(map(m.ix[0].similarity, users)) * 30
#s = sct.get_sizes()
#s[:] = newsizes
sct._sizes = newsizes
ip()
def example():
# pl.ioff()
pl.ion()
import pandas
from numpy.random import uniform
n = 25
m = pandas.DataFrame({
'x': uniform(-1, 1, size=n),
'y': uniform(-1, 1, size=n),
'size': uniform(3, 10, size=n) ** 2,
'color': uniform(0, 1, size=n),
})
# test using a custom index
m['silly_index'] = ['%sth' % x for x in range(n)]
m.set_index('silly_index', drop=True, inplace=True, verify_integrity=True)
print m
ax = pl.subplot(111)
plt = ax.scatter(m['x'], m['y'])
b = LassoBrowser(m, ax)
print b.idxs
#from viz.interact.pointbrowser import PointBrowser
#pb = PointBrowser(m, plot=plt)
pl.show()
ip()
def example():
# pl.ioff()
pl.ion()
import pandas
from numpy.random import uniform
n = 25
m = pandas.DataFrame({
'x': uniform(-1, 1, size=n),
'y': uniform(-1, 1, size=n),
'size': uniform(3, 10, size=n)**2,
'color': uniform(0, 1, size=n),
})
# test using a custom index
m['silly_index'] = ['%sth' % x for x in range(n)]
m.set_index('silly_index', drop=True, inplace=True, verify_integrity=True)
print m
ax = pl.subplot(111)
plt = ax.scatter(m['x'], m['y'])
b = LassoBrowser(m, ax)
print b.idxs
#from viz.interact.pointbrowser import PointBrowser
#pb = PointBrowser(m, plot=plt)
pl.show()
ip()
def callback(event):
print 'callback:', event
ax = event.inaxes
pl.ion()
newfig = pl.figure()
ax.set_figure(newfig)
newfig.set_axes([ax])
newfig.canvas.show()
ip()
def icons(users, distance):
"""Visualization using user profile images as the points."""
# It would be pretty cool to put user thumbails where points are.
# but i'm still not sure how to do this yet.
images = []
try:
print 'getting images..'
for p in users:
print p
f = p.image
img = imread('image.tmp')
images.append(img)
except Exception as e:
print 'got an error...'
import traceback
etype, evalue, tb = sys.exc_info()
print yellow % '\n'.join(traceback.format_exception(etype, evalue, tb))
ip()
(W, H, _) = shape(img) # thumbnails should all be the same size
count = len(images)
pl.figure()
P2, _ = mds(distance, 2)
X,Y = P2[:,0], P2[:,1]
## XXX: not a great transformation b/c we might stretch more in one dimension
def N(x):
"force x to fit in interval [0,1]"
x = (x - x.min())
x = x / x.max()
assert all(x >= 0) and all(x <= 1)
return x
X = N(X)*475
Y = N(Y)*425
figimages = [pl.figimage(img, xo=x, yo=y) for img, x, y in zip(images, X, Y)]
