def __getitem__(self, key): return Expression(self, OP.HKEY, Param(key))
def slice(self, *args): return fn.slice(self, Param(list(args)))
def contains(self, value): if isinstance(value, dict): return Expression(self, OP.HCONTAINS_DICT, Param(value)) elif isinstance(value, (list, tuple)): return Expression(self, OP.HCONTAINS_KEYS, Param(value)) return Expression(self, OP.HCONTAINS_KEY, value)
def contains_any(self, *keys): return Expression(self, OP.HCONTAINS_ANY_KEY, Param(list(keys)))
#nn = mega_nn.nn root_name = '/megarun1/nndb_nn/' query = (Network.select(Network.target_names).distinct().tuples()) for query_res in query: target_names, = query_res if len(target_names) == 1: target_name = target_names[0] else: NotImplementedError('Multiple targets not implemented yet') print(target_name) parent_name = root_name + target_name + '/' subquery = (Network.select( Network.id, NetworkJSON.network_json).where(Network.target_names == Param( target_names)).join(NetworkJSON).tuples()) for subquery_res in subquery: id, json_dict = subquery_res nn = QuaLiKizNDNN(json_dict) network_name = parent_name + str(id) if len(nn.feature_names) != features: print('Skipping', id, ': has', len(nn.feature_names), 'features instead of', features) continue if network_name in store: pass else:
def delete(self, *keys): return fn.delete(self, Param(list(keys)))
def test_blob_field_mysql(self): data = bytes(bytearray(range(256))) blob = BlobModel.create(data=Param(data)) res = BlobModel.get(BlobModel.id == blob.id) self.assertEqual(blob.data, data)
def contains_any(self, *keys): return Expr(self, OP_HCONTAINS_ANY_KEY, Param(value))
'efeETG_GB': 'Electron ETG Heat Flux', 'efeITG_GB': 'Electron ITG Heat Flux', 'efeTEM_GB': 'Electron TEM Heat Flux', 'efiITG_GB': 'Ion ITG Heat Flux', 'efiTEM_GB': 'Ion TEM Heat Flux' } feature_names = ['An', 'Ate', 'Ati', 'Ti_Te', 'qx', 'smag', 'x'] feature_names2 = ['Ati', 'Ate', 'An', 'qx', 'smag', 'x', 'Ti_Te'] query = (Network.select(Network.target_names).distinct().tuples()) #df = pd.DataFrame(columns=['target_names', 'id','rms']) results = pd.DataFrame() for ii, query_res in enumerate(query): target_names = query_res[0] subquery = (Network.select( Network.id, NetworkMetadata.rms_validation).where( Network.target_names == Param(target_names)).where( (Network.feature_names == Param(feature_names)) | (Network.feature_names == Param(feature_names2))).join( NetworkMetadata).order_by( NetworkMetadata.rms_validation).tuples()) df = pd.DataFrame(list(subquery), columns=['id', 'rms']) index = pd.MultiIndex.from_product([[tuple(target_names)], df.index]) df.index = index #df.loc[ii] = list(chain([target_names], subquery.get())) results = pd.concat([results, df]) results['id'] = results['id'].astype('int64') #for row in results.iterrows(): # results.set_value(row[0], 'target_names', target_to_fancy[row[1]['target_names']]) #results = results[['target_names', 'l2_norm', 'rms', 'rms_rel']] #results.columns = ['Training Target', 'L_2 norm', 'RMS error [GB]', 'RMS error [%]']
def contains_any(self, *items): return Expression(self, OP.ACONTAINS_ANY, Param(items))
def contains(self, *items): return Expression(self, OP.ACONTAINS, Param(items))