def newFn(self, data, *args, **kargs):
if HAVE_METAARRAY and (hasattr(data, 'implements') and data.implements('MetaArray')):
d1 = fn(self, data.view(np.ndarray), *args, **kargs)
info = data.infoCopy()
if d1.shape != data.shape:
for i in range(data.ndim):
if 'values' in info[i]:
info[i]['values'] = info[i]['values'][:d1.shape[i]]
return metaarray.MetaArray(d1, info=info)
else:
return fn(self, data, *args, **kargs)
def newFn(self, data, *args, **kargs):
if HAVE_METAARRAY and isinstance(data, metaarray.MetaArray):
d1 = fn(self, data.view(np.ndarray), *args, **kargs)
info = data.infoCopy()
if d1.shape != data.shape:
for i in range(data.ndim):
if 'values' in info[i]:
info[i]['values'] = info[i]['values'][:d1.shape[i]]
return metaarray.MetaArray(d1, info=info)
else:
return fn(self, data, *args, **kargs)
win.resize(800, 600)
win.show()
ll = [[1, 2, 3, 4, 5]] * 20
ld = [{'x': 1, 'y': 2, 'z': 3}] * 20
dl = {'x': list(range(20)), 'y': list(range(20)), 'z': list(range(20))}
a = np.ones((20, 5))
ra = np.ones((20, ), dtype=[('x', int), ('y', int), ('z', int)])
t.setData(ll)
if HAVE_METAARRAY:
ma = metaarray.MetaArray(np.ones((20, 3)),
info=[{
'values': np.linspace(1, 5, 20)
}, {
'cols': [
{
'name': 'x'
},
{
'name': 'y'
},
{
'name': 'z'
},
]
}])
t.setData(ma)