def select():
spec = Collate(*Collate.from_log(path))
sel = Select(spec, float_keys=['cortex_density', 'retina_density'])
data = np.random.rand(9)
selection = (sel.retina_density > 3.0) & (sel.cortex_density > 5)
assert set(sel[selection].tid) == set([5, 8])
assert repr(sel.select(selection, data)) == repr(data[selection])
list_data = [None, 3, False, object, 3.4, '32', np.int64, unicode, lambda x: x]
list_selection = [True, True, False, True] + [False]*5
assert repr(sel.select(list_selection, list_data)) == repr([None, 3,object])
new_sel = Select(sel.tolist(selection), float_keys=['cortex_density', 'retina_density'])
return new_sel
def pytable_save(collation):
loader = PILImageLoader(['.png'], transform = lambda im: im.rotate(180))
(images, metadata, imlabels) = collation.extract_files(loader, 'ColKey','ColKeyLabels')
sel = Select(collation,
float_keys=['cortex_density', 'retina_density'],
int_keys=['time', 'activity'],
visible_keys = ['cortex_density', 'retina_density', 'activity', 'ColKeyLabels'])
condition = (sel.retina_density > 3.0)
image_sel, iminfo_sel, imlabel_sel = sel.select(condition, images, metadata, imlabels)
with PyTableUtils('utils-test.h5', 'util_test', 'Testing purposes', title='Title') as pytable:
pytable.declare_group('images', 'Storing images')
pytable.declare_group('selector', 'The Select object')
for (ims, iminfos, labels) in zip(image_sel, iminfo_sel, imlabel_sel):
for (im, label, iminfo) in zip(ims, labels, iminfos):
pytable.store_array('images', np.array(im), label, iminfo=iminfo)
pytable.store_selector('selector', sel.subselector(condition), 'subselector')