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)