def data(self, newdata):
if newdata == None:
return None
self._data = newdata
# When data changes, update the list of renderers
renderers = suitable_renderers(self.data)
combobox = self.renderer_combobox
previous_selection = combobox.currentIndex(
) # remember previous choice
try: #Attempt to keep the same range
previous_view_rect = self.figure_widget.figureWidget.viewRect()
except AttributeError:
previous_view_rect = None
combobox.clear()
for i, renderer in enumerate(renderers):
combobox.addItem(renderer.__name__, renderer)
# Attempt to keep the same renderer as we had before - or use the
# "best" one. NB setting the current index will trigger the renderer
# to be created in renderer_selected
try:
if previous_selection == 0:
raise ValueError(
) # if we didn't choose the last renderer, just
# pick the best one. Otherwise, try to use the same
# renderer as we used before
else:
index = renderers.index(self.renderer.__class__)
combobox.setCurrentIndex(index)
try:
self.renderer_selected(index)
except Exception as e:
print 'The selected renderer failed becasue', e
except ValueError:
combobox.setCurrentIndex(0)
self.renderer_selected(0)
if previous_view_rect != None:
try:
self.figure_widget.figureWidget.setRange(previous_view_rect,
padding=0)
except AttributeError:
pass
# -*- coding: utf-8 -*-
"""
Created on Tue Oct 27 13:09:09 2015
@author: rwb27
"""
import nplab
import numpy as np
import matplotlib.pyplot as plt
from numpy.random import random
from nplab.ui.data_renderers import suitable_renderers
if __name__ == '__main__':
df = nplab.current_datafile()
group = df.create_group("test_items")
d = group.create_dataset("1d_generic",data=random((100)))
print suitable_renderers(d)
d = group.create_dataset("2d_generic",data=random((100,100)))
print suitable_renderers(d)
d = group.create_dataset("3d_rgb",data=random((100,100,3)))
print suitable_renderers(d)
d = group.create_dataset("3d_generic",data=random((100,100,100)))
print suitable_renderers(d)
df.show_gui(block=True)
df.close()
# -*- coding: utf-8 -*-
"""
Created on Tue Oct 27 13:09:09 2015
@author: rwb27
"""
from __future__ import print_function
import nplab
# import numpy as np
# import matplotlib.pyplot as plt
from numpy.random import random
from nplab.ui.data_renderers import suitable_renderers
if __name__ == '__main__':
df = nplab.current_datafile()
group = df.create_group("test_items")
d = group.create_dataset("1d_generic", data=random((100)))
print(suitable_renderers(d))
d = group.create_dataset("2d_generic", data=random((100, 100)))
print(suitable_renderers(d))
d = group.create_dataset("3d_rgb", data=random((100, 100, 3)))
print(suitable_renderers(d))
d = group.create_dataset("3d_generic", data=random((100, 100, 100)))
print(suitable_renderers(d))
df.show_gui(block=True)
df.close()