Glueviz Image Manipulation

glued_figure_manipulation.py

import glue

clients_classes = (glue.clients.HistogramClient,glue.clients.ImageClient,glue.clients.ScatterClient)

clients = []

for i in range(size(hub._subscriptions.keys())):
      tmp = hub._subscriptions.keys()[i]
      if isinstance(tmp, glue.clients.HistogramClient):
         is_class = 'histogram'
      elif  isinstance(tmp, glue.clients.ImageClient):
         is_class = 'image'
      elif  isinstance(tmp, glue.clients.ScatterClient):
         is_class = 'scatter'
      else :
         is_class = 'noclient'
      if is_class != 'noclient' :
         print '%s client instance at position %d: %40s' % (is_class,i,tmp)
         print 'X_label : %s' % (tmp.axes.get_xlabel())
         print 'Y_label : %s' % (tmp.axes.get_ylabel())
         print '-'*10
      clients.append(is_class)

# image client instance at position 6: <glue.clients.image_client.ImageClient object at 0x11ec89ed0>
# X_label : World 1
# Y_label : World 0
# ----------
# scatter client instance at position 7: <glue.clients.scatter_client.ScatterClient object at 0x1216ff7d0>
# X_label : K-Means_StandardScaler_3_classes
# Y_label : RandomPCA comp 1
# ----------
# scatter client instance at position 10: <glue.clients.scatter_client.ScatterClient object at 0x1253edc10>
# X_label : K-Means_StandardScaler_2_classes
# Y_label : RandomPCA comp 1
# ----------
# 
# elmaps scatterplot
# 
# scatter client instance at position 4: <glue.clients.scatter_client.ScatterClient object at 0x11f857a10>
# X_label : Al/Si
# Y_label : Mg/Si
# ----------
# 
# other scatterplot 
# 
# scatter client instance at position 12: <glue.clients.scatter_client.ScatterClient object at 0x121698f90>
# X_label : grid_center_lon
# Y_label : elmap_mgsires
# ----------
# 
# histogram client instance at position 9: <glue.clients.histogram_client.HistogramClient object at 0x11f851510>
# X_label : crater_density
# Y_label : N
# ----------

i = 2
plo = hub._subscriptions.keys()[i]
# x_label = 'Maximum Surface Temperature (K)'
y_label = 'Latitude'
x_label = 'XRS resolution'
plo.axes.set_xlabel(x_label)
plo.axes.set_ylabel(y_label)
# update plot
plo.axes.figure.canvas.draw()


path = '/Users/damo_ma/Documents/Dropbox/work/python/LPCSC2014/'
if clients[i] == 'histogram':
   name = ('%s_%s.') % (clients[i],plo.axes.get_xlabel())
elif  clients[i] == 'image':
   name = ('%s_%s.') % (clients[i],plo.axes.get_xlabel())
elif  clients[i] == 'scatter':
# FIXME extract image title or variable visualized! 
   name = ('%s_%s_vs_%s.') % (clients[i],plo.axes.get_xlabel(),plo.axes.get_ylabel())
name = name.replace(" ", "_").replace("/", "")


# for format in ('png','pdf','eps'):
format = 'jpg'
plo.axes.figure.savefig(path+name+format, bbox_inches='tight',dpi=300)