Repository: incubator-madlib Updated Branches: refs/heads/master e9e365a68 -> 4fcb60ed8
http://git-wip-us.apache.org/repos/asf/incubator-madlib/blob/4fcb60ed/src/ports/postgres/modules/convex/test/mlp.sql_in ---------------------------------------------------------------------- diff --git a/src/ports/postgres/modules/convex/test/mlp.sql_in b/src/ports/postgres/modules/convex/test/mlp.sql_in new file mode 100644 index 0000000..97541a9 --- /dev/null +++ b/src/ports/postgres/modules/convex/test/mlp.sql_in @@ -0,0 +1,845 @@ +/* ----------------------------------------------------------------------- *//** + * + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + * + *//* ----------------------------------------------------------------------- */ + + + + +-- The data were collected by Anderson, Edgar (1935). +-- The irises of the Gaspe Peninsula, Bulletin of the American Iris Society, 59, 2â5. + +-- Classification + + +SELECT setseed(0.5); +DROP TABLE IF EXISTS iris_data, iris_test, mlp_class, mlp_class_summary CASCADE; +CREATE TABLE iris_data( + id integer, + attributes numeric[], + class_text varchar, + class integer +); + +INSERT INTO iris_data VALUES +(1,ARRAY[5.1,3.5,1.4,0.2],'Iris-setosa',1), +(2,ARRAY[4.9,3.0,1.4,0.2],'Iris-setosa',1), +(3,ARRAY[4.7,3.2,1.3,0.2],'Iris-setosa',1), +(4,ARRAY[4.6,3.1,1.5,0.2],'Iris-setosa',1), +(5,ARRAY[5.0,3.6,1.4,0.2],'Iris-setosa',1), +(6,ARRAY[5.4,3.9,1.7,0.4],'Iris-setosa',1), +(7,ARRAY[4.6,3.4,1.4,0.3],'Iris-setosa',1), +(8,ARRAY[5.0,3.4,1.5,0.2],'Iris-setosa',1), +(9,ARRAY[4.4,2.9,1.4,0.2],'Iris-setosa',1), +(10,ARRAY[4.9,3.1,1.5,0.1],'Iris-setosa',1), +(11,ARRAY[5.4,3.7,1.5,0.2],'Iris-setosa',1), +(12,ARRAY[4.8,3.4,1.6,0.2],'Iris-setosa',1), +(13,ARRAY[4.8,3.0,1.4,0.1],'Iris-setosa',1), +(14,ARRAY[4.3,3.0,1.1,0.1],'Iris-setosa',1), +(15,ARRAY[5.8,4.0,1.2,0.2],'Iris-setosa',1), +(16,ARRAY[5.7,4.4,1.5,0.4],'Iris-setosa',1), +(17,ARRAY[5.4,3.9,1.3,0.4],'Iris-setosa',1), +(18,ARRAY[5.1,3.5,1.4,0.3],'Iris-setosa',1), +(19,ARRAY[5.7,3.8,1.7,0.3],'Iris-setosa',1), +(20,ARRAY[5.1,3.8,1.5,0.3],'Iris-setosa',1), +(21,ARRAY[5.4,3.4,1.7,0.2],'Iris-setosa',1), +(22,ARRAY[5.1,3.7,1.5,0.4],'Iris-setosa',1), +(23,ARRAY[4.6,3.6,1.0,0.2],'Iris-setosa',1), +(24,ARRAY[5.1,3.3,1.7,0.5],'Iris-setosa',1), +(25,ARRAY[4.8,3.4,1.9,0.2],'Iris-setosa',1), +(26,ARRAY[5.0,3.0,1.6,0.2],'Iris-setosa',1), +(27,ARRAY[5.0,3.4,1.6,0.4],'Iris-setosa',1), +(28,ARRAY[5.2,3.5,1.5,0.2],'Iris-setosa',1), +(29,ARRAY[5.2,3.4,1.4,0.2],'Iris-setosa',1), +(30,ARRAY[4.7,3.2,1.6,0.2],'Iris-setosa',1), +(31,ARRAY[4.8,3.1,1.6,0.2],'Iris-setosa',1), +(32,ARRAY[5.4,3.4,1.5,0.4],'Iris-setosa',1), +(33,ARRAY[5.2,4.1,1.5,0.1],'Iris-setosa',1), +(34,ARRAY[5.5,4.2,1.4,0.2],'Iris-setosa',1), +(35,ARRAY[4.9,3.1,1.5,0.1],'Iris-setosa',1), +(36,ARRAY[5.0,3.2,1.2,0.2],'Iris-setosa',1), +(37,ARRAY[5.5,3.5,1.3,0.2],'Iris-setosa',1), +(38,ARRAY[4.9,3.1,1.5,0.1],'Iris-setosa',1), +(39,ARRAY[4.4,3.0,1.3,0.2],'Iris-setosa',1), +(40,ARRAY[5.1,3.4,1.5,0.2],'Iris-setosa',1), +(41,ARRAY[5.0,3.5,1.3,0.3],'Iris-setosa',1), +(42,ARRAY[4.5,2.3,1.3,0.3],'Iris-setosa',1), +(43,ARRAY[4.4,3.2,1.3,0.2],'Iris-setosa',1), +(44,ARRAY[5.0,3.5,1.6,0.6],'Iris-setosa',1), +(45,ARRAY[5.1,3.8,1.9,0.4],'Iris-setosa',1), +(46,ARRAY[4.8,3.0,1.4,0.3],'Iris-setosa',1), +(47,ARRAY[5.1,3.8,1.6,0.2],'Iris-setosa',1), +(48,ARRAY[4.6,3.2,1.4,0.2],'Iris-setosa',1), +(49,ARRAY[5.3,3.7,1.5,0.2],'Iris-setosa',1), +(50,ARRAY[5.0,3.3,1.4,0.2],'Iris-setosa',1), +(51,ARRAY[7.0,3.2,4.7,1.4],'Iris-versicolor',2), +(52,ARRAY[6.4,3.2,4.5,1.5],'Iris-versicolor',2), +(53,ARRAY[6.9,3.1,4.9,1.5],'Iris-versicolor',2), +(54,ARRAY[5.5,2.3,4.0,1.3],'Iris-versicolor',2), +(55,ARRAY[6.5,2.8,4.6,1.5],'Iris-versicolor',2), +(56,ARRAY[5.7,2.8,4.5,1.3],'Iris-versicolor',2), +(57,ARRAY[6.3,3.3,4.7,1.6],'Iris-versicolor',2), +(58,ARRAY[4.9,2.4,3.3,1.0],'Iris-versicolor',2), +(59,ARRAY[6.6,2.9,4.6,1.3],'Iris-versicolor',2), +(60,ARRAY[5.2,2.7,3.9,1.4],'Iris-versicolor',2), +(61,ARRAY[5.0,2.0,3.5,1.0],'Iris-versicolor',2), +(62,ARRAY[5.9,3.0,4.2,1.5],'Iris-versicolor',2), +(63,ARRAY[6.0,2.2,4.0,1.0],'Iris-versicolor',2), +(64,ARRAY[6.1,2.9,4.7,1.4],'Iris-versicolor',2), +(65,ARRAY[5.6,2.9,3.6,1.3],'Iris-versicolor',2), +(66,ARRAY[6.7,3.1,4.4,1.4],'Iris-versicolor',2), +(67,ARRAY[5.6,3.0,4.5,1.5],'Iris-versicolor',2), +(68,ARRAY[5.8,2.7,4.1,1.0],'Iris-versicolor',2), +(69,ARRAY[6.2,2.2,4.5,1.5],'Iris-versicolor',2), +(70,ARRAY[5.6,2.5,3.9,1.1],'Iris-versicolor',2), +(71,ARRAY[5.9,3.2,4.8,1.8],'Iris-versicolor',2), +(72,ARRAY[6.1,2.8,4.0,1.3],'Iris-versicolor',2), +(73,ARRAY[6.3,2.5,4.9,1.5],'Iris-versicolor',2), +(74,ARRAY[6.1,2.8,4.7,1.2],'Iris-versicolor',2), +(75,ARRAY[6.4,2.9,4.3,1.3],'Iris-versicolor',2), +(76,ARRAY[6.6,3.0,4.4,1.4],'Iris-versicolor',2), +(77,ARRAY[6.8,2.8,4.8,1.4],'Iris-versicolor',2), +(78,ARRAY[6.7,3.0,5.0,1.7],'Iris-versicolor',2), +(79,ARRAY[6.0,2.9,4.5,1.5],'Iris-versicolor',2), +(80,ARRAY[5.7,2.6,3.5,1.0],'Iris-versicolor',2), +(81,ARRAY[5.5,2.4,3.8,1.1],'Iris-versicolor',2), +(82,ARRAY[5.5,2.4,3.7,1.0],'Iris-versicolor',2), +(83,ARRAY[5.8,2.7,3.9,1.2],'Iris-versicolor',2), +(84,ARRAY[6.0,2.7,5.1,1.6],'Iris-versicolor',2), +(85,ARRAY[5.4,3.0,4.5,1.5],'Iris-versicolor',2), +(86,ARRAY[6.0,3.4,4.5,1.6],'Iris-versicolor',2), +(87,ARRAY[6.7,3.1,4.7,1.5],'Iris-versicolor',2), +(88,ARRAY[6.3,2.3,4.4,1.3],'Iris-versicolor',2), +(89,ARRAY[5.6,3.0,4.1,1.3],'Iris-versicolor',2), +(90,ARRAY[5.5,2.5,4.0,1.3],'Iris-versicolor',2), +(91,ARRAY[5.5,2.6,4.4,1.2],'Iris-versicolor',2), +(92,ARRAY[6.1,3.0,4.6,1.4],'Iris-versicolor',2), +(93,ARRAY[5.8,2.6,4.0,1.2],'Iris-versicolor',2), +(94,ARRAY[5.0,2.3,3.3,1.0],'Iris-versicolor',2), +(95,ARRAY[5.6,2.7,4.2,1.3],'Iris-versicolor',2), +(96,ARRAY[5.7,3.0,4.2,1.2],'Iris-versicolor',2), +(97,ARRAY[5.7,2.9,4.2,1.3],'Iris-versicolor',2), +(98,ARRAY[6.2,2.9,4.3,1.3],'Iris-versicolor',2), +(99,ARRAY[5.1,2.5,3.0,1.1],'Iris-versicolor',2), +(100,ARRAY[5.7,2.8,4.1,1.3],'Iris-versicolor',2), +(101,ARRAY[6.3,3.3,6.0,2.5],'Iris-virginica',3), +(102,ARRAY[5.8,2.7,5.1,1.9],'Iris-virginica',3), +(103,ARRAY[7.1,3.0,5.9,2.1],'Iris-virginica',3), +(104,ARRAY[6.3,2.9,5.6,1.8],'Iris-virginica',3), +(105,ARRAY[6.5,3.0,5.8,2.2],'Iris-virginica',3), +(106,ARRAY[7.6,3.0,6.6,2.1],'Iris-virginica',3), +(107,ARRAY[4.9,2.5,4.5,1.7],'Iris-virginica',3), +(108,ARRAY[7.3,2.9,6.3,1.8],'Iris-virginica',3), +(109,ARRAY[6.7,2.5,5.8,1.8],'Iris-virginica',3), +(110,ARRAY[7.2,3.6,6.1,2.5],'Iris-virginica',3), +(111,ARRAY[6.5,3.2,5.1,2.0],'Iris-virginica',3), +(112,ARRAY[6.4,2.7,5.3,1.9],'Iris-virginica',3), +(113,ARRAY[6.8,3.0,5.5,2.1],'Iris-virginica',3), +(114,ARRAY[5.7,2.5,5.0,2.0],'Iris-virginica',3), +(115,ARRAY[5.8,2.8,5.1,2.4],'Iris-virginica',3), +(116,ARRAY[6.4,3.2,5.3,2.3],'Iris-virginica',3), +(117,ARRAY[6.5,3.0,5.5,1.8],'Iris-virginica',3), +(118,ARRAY[7.7,3.8,6.7,2.2],'Iris-virginica',3), +(119,ARRAY[7.7,2.6,6.9,2.3],'Iris-virginica',3), +(120,ARRAY[6.0,2.2,5.0,1.5],'Iris-virginica',3), +(121,ARRAY[6.9,3.2,5.7,2.3],'Iris-virginica',3), +(122,ARRAY[5.6,2.8,4.9,2.0],'Iris-virginica',3), +(123,ARRAY[7.7,2.8,6.7,2.0],'Iris-virginica',3), +(124,ARRAY[6.3,2.7,4.9,1.8],'Iris-virginica',3), +(125,ARRAY[6.7,3.3,5.7,2.1],'Iris-virginica',3), +(126,ARRAY[7.2,3.2,6.0,1.8],'Iris-virginica',3), +(127,ARRAY[6.2,2.8,4.8,1.8],'Iris-virginica',3), +(128,ARRAY[6.1,3.0,4.9,1.8],'Iris-virginica',3), +(129,ARRAY[6.4,2.8,5.6,2.1],'Iris-virginica',3), +(130,ARRAY[7.2,3.0,5.8,1.6],'Iris-virginica',3), +(131,ARRAY[7.4,2.8,6.1,1.9],'Iris-virginica',3), +(132,ARRAY[7.9,3.8,6.4,2.0],'Iris-virginica',3), +(133,ARRAY[6.4,2.8,5.6,2.2],'Iris-virginica',3), +(134,ARRAY[6.3,2.8,5.1,1.5],'Iris-virginica',3), +(135,ARRAY[6.1,2.6,5.6,1.4],'Iris-virginica',3), +(136,ARRAY[7.7,3.0,6.1,2.3],'Iris-virginica',3), +(137,ARRAY[6.3,3.4,5.6,2.4],'Iris-virginica',3), +(138,ARRAY[6.4,3.1,5.5,1.8],'Iris-virginica',3), +(139,ARRAY[6.0,3.0,4.8,1.8],'Iris-virginica',3), +(140,ARRAY[6.9,3.1,5.4,2.1],'Iris-virginica',3), +(141,ARRAY[6.7,3.1,5.6,2.4],'Iris-virginica',3), +(142,ARRAY[6.9,3.1,5.1,2.3],'Iris-virginica',3), +(143,ARRAY[5.8,2.7,5.1,1.9],'Iris-virginica',3), +(144,ARRAY[6.8,3.2,5.9,2.3],'Iris-virginica',3), +(145,ARRAY[6.7,3.3,5.7,2.5],'Iris-virginica',3), +(146,ARRAY[6.7,3.0,5.2,2.3],'Iris-virginica',3), +(147,ARRAY[6.3,2.5,5.0,1.9],'Iris-virginica',3), +(148,ARRAY[6.5,3.0,5.2,2.0],'Iris-virginica',3), +(149,ARRAY[6.2,3.4,5.4,2.3],'Iris-virginica',3), +(150,ARRAY[5.9,3.0,5.1,1.8],'Iris-virginica',3); + + +SELECT mlp_classification( + 'iris_data', -- Source table + 'mlp_class', -- Desination table + 'attributes', -- Input features + 'class', -- Label + ARRAY[5], -- Number of units per layer + 'step_size=0.001, + n_iterations=1000, + tolerance=0', + 'tanh'); + + +SELECT assert( + -- Loss will improve much more if more iterations are run + loss < 30, + 'MLP: Loss is too high (> 30). Wrong result.' +) FROM mlp_class; + +DROP TABLE IF EXISTS mlp_prediction; +DROP TABLE IF EXISTS mlp_prediction_output; +-- See prediction accuracy for training data +SELECT mlp_predict( + 'mlp_class', + 'iris_data', + 'id', + 'mlp_prediction_output', + 'output'); + +-- Sum over the probabilities where the prediction is correct +-- If the predictions were perfect, the score would be 150 +SELECT assert( + score > 140, + 'MLP: Score is too low (< 140). Wrong result.' +) FROM( +SELECT SUM( +mlp_prediction_output.estimated_prob_1*(iris_data.class=1)::INT+ +mlp_prediction_output.estimated_prob_2*(iris_data.class=2)::INT+ +mlp_prediction_output.estimated_prob_3*(iris_data.class=3)::INT +) AS score +FROM mlp_prediction_output INNER JOIN iris_data ON iris_data.id=mlp_prediction_output.id)q; + + +SELECT mlp_predict( + 'mlp_class', + 'iris_data', + 'id', + 'mlp_prediction', + 'response'); + +select * from mlp_prediction; +SELECT assert( + -- Accuracy greater than 90% + COUNT(*)/150.0 > 0.95, + 'MLP: Accuracy is too low (< 95%). Wrong result.' +) FROM + (SELECT iris_data.class AS actual, mlp_prediction.estimated_class as estimated + FROM mlp_prediction INNER JOIN iris_data ON + iris_data.id=mlp_prediction.id) q +WHERE q.actual=q.estimated; + +DROP TABLE IF EXISTS mlp_prediction; +DROP TABLE IF EXISTS mlp_prediction_output; +-- Regression + + +DROP TABLE IF EXISTS lin_housing_wi, mlp_regress CASCADE; +CREATE TABLE lin_housing_wi (id serial, x float8[], grp_by_col int, y float8); +COPY lin_housing_wi (x, grp_by_col, y) FROM STDIN NULL '?' DELIMITER '|'; +{1,0.00632,18.00,2.310,0,0.5380,6.5750,65.20,4.0900,1,296.0,15.30,396.90,4.98} | 1 | 24.00 +{1,0.02731,0.00,7.070,0,0.4690,6.4210,78.90,4.9671,2,242.0,17.80,396.90,9.14} | 1 | 21.60 +{1,0.02729,0.00,7.070,0,0.4690,7.1850,61.10,4.9671,2,242.0,17.80,392.83,4.03} | 1 | 34.70 +{1,0.03237,0.00,2.180,0,0.4580,6.9980,45.80,6.0622,3,222.0,18.70,394.63,2.94} | 1 | 33.40 +{1,0.06905,0.00,2.180,0,0.4580,7.1470,54.20,6.0622,3,222.0,18.70,396.90,5.33} | 1 | 36.20 +{1,0.02985,0.00,2.180,0,0.4580,6.4300,58.70,6.0622,3,222.0,18.70,394.12,5.21} | 1 | 28.70 +{1,0.08829,12.50,7.870,0,0.5240,6.0120,66.60,5.5605,5,311.0,15.20,395.60,12.43} | 1 | 22.90 +{1,0.14455,12.50,7.870,0,0.5240,6.1720,96.10,5.9505,5,311.0,15.20,396.90,19.15} | 1 | 27.10 +{1,0.21124,12.50,7.870,0,0.5240,5.6310,100.00,6.0821,5,311.0,15.20,386.63,29.93} | 1 | 16.50 +{1,0.17004,12.50,7.870,0,0.5240,6.0040,85.90,6.5921,5,311.0,15.20,386.71,17.10} | 1 | 18.90 +{1,0.22489,12.50,7.870,0,0.5240,6.3770,94.30,6.3467,5,311.0,15.20,392.52,20.45} | 1 | 15.00 +{1,0.11747,12.50,7.870,0,0.5240,6.0090,82.90,6.2267,5,311.0,15.20,396.90,13.27} | 1 | 18.90 +{1,0.09378,12.50,7.870,0,0.5240,5.8890,39.00,5.4509,5,311.0,15.20,390.50,15.71} | 1 | 21.70 +{1,0.62976,0.00,8.140,0,0.5380,5.9490,61.80,4.7075,4,307.0,21.00,396.90,8.26} | 1 | 20.40 +{1,0.63796,0.00,8.140,0,0.5380,6.0960,84.50,4.4619,4,307.0,21.00,380.02,10.26} | 1 | 18.20 +{1,0.62739,0.00,8.140,0,0.5380,5.8340,56.50,4.4986,4,307.0,21.00,395.62,8.47} | 1 | 19.90 +{1,1.05393,0.00,8.140,0,0.5380,5.9350,29.30,4.4986,4,307.0,21.00,386.85,6.58} | 1 | 23.10 +{1,0.78420,0.00,8.140,0,0.5380,5.9900,81.70,4.2579,4,307.0,21.00,386.75,14.67} | 1 | 17.50 +{1,0.80271,0.00,8.140,0,0.5380,5.4560,36.60,3.7965,4,307.0,21.00,288.99,11.69} | 1 | 20.20 +{1,0.72580,0.00,8.140,0,0.5380,5.7270,69.50,3.7965,4,307.0,21.00,390.95,11.28} | 1 | 18.20 +{1,1.25179,0.00,8.140,0,0.5380,5.5700,98.10,3.7979,4,307.0,21.00,376.57,21.02} | 1 | 13.60 +{1,0.85204,0.00,8.140,0,0.5380,5.9650,89.20,4.0123,4,307.0,21.00,392.53,13.83} | 1 | 19.60 +{1,1.23247,0.00,8.140,0,0.5380,6.1420,91.70,3.9769,4,307.0,21.00,396.90,18.72} | 1 | 15.20 +{1,0.98843,0.00,8.140,0,0.5380,5.8130,100.00,4.0952,4,307.0,21.00,394.54,19.88} | 1 | 14.50 +{1,0.75026,0.00,8.140,0,0.5380,5.9240,94.10,4.3996,4,307.0,21.00,394.33,16.30} | 1 | 15.60 +{1,0.84054,0.00,8.140,0,0.5380,5.5990,85.70,4.4546,4,307.0,21.00,303.42,16.51} | 1 | 13.90 +{1,0.67191,0.00,8.140,0,0.5380,5.8130,90.30,4.6820,4,307.0,21.00,376.88,14.81} | 1 | 16.60 +{1,0.95577,0.00,8.140,0,0.5380,6.0470,88.80,4.4534,4,307.0,21.00,306.38,17.28} | 1 | 14.80 +{1,0.77299,0.00,8.140,0,0.5380,6.4950,94.40,4.4547,4,307.0,21.00,387.94,12.80} | 1 | 18.40 +{1,1.00245,0.00,8.140,0,0.5380,6.6740,87.30,4.2390,4,307.0,21.00,380.23,11.98} | 1 | 21.00 +{1,1.13081,0.00,8.140,0,0.5380,5.7130,94.10,4.2330,4,307.0,21.00,360.17,22.60} | 1 | 12.70 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25.00 +{1,0.04294,28.00,15.040,0,0.4640,6.2490,77.30,3.6150,4,270.0,18.20,396.90,10.59} | 1 | 20.60 +{1,0.12204,0.00,2.890,0,0.4450,6.6250,57.80,3.4952,2,276.0,18.00,357.98,6.65} | 1 | 28.40 +{1,0.11504,0.00,2.890,0,0.4450,6.1630,69.60,3.4952,2,276.0,18.00,391.83,11.34} | 1 | 21.40 +{1,0.12083,0.00,2.890,0,0.4450,8.0690,76.00,3.4952,2,276.0,18.00,396.90,4.21} | 1 | 38.70 +{1,0.08187,0.00,2.890,0,0.4450,7.8200,36.90,3.4952,2,276.0,18.00,393.53,3.57} | 1 | 43.80 +{1,0.06860,0.00,2.890,0,0.4450,7.4160,62.50,3.4952,2,276.0,18.00,396.90,6.19} | 1 | 33.20 +{1,0.14866,0.00,8.560,0,0.5200,6.7270,79.90,2.7778,5,384.0,20.90,394.76,9.42} | 1 | 27.50 +{1,0.11432,0.00,8.560,0,0.5200,6.7810,71.30,2.8561,5,384.0,20.90,395.58,7.67} | 1 | 26.50 +{1,0.22876,0.00,8.560,0,0.5200,6.4050,85.40,2.7147,5,384.0,20.90,70.80,10.63} | 1 | 18.60 +{1,0.21161,0.00,8.560,0,0.5200,6.1370,87.40,2.7147,5,384.0,20.90,394.47,13.44} | 1 | 19.30 +{1,0.13960,0.00,8.560,0,0.5200,6.1670,90.00,2.4210,5,384.0,20.90,392.69,12.33} 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| 37.60 +{1,0.41238,0.00,6.200,0,0.5040,7.1630,79.90,3.2157,8,307.0,17.40,372.08,6.36} | 1 | 31.60 +{1,0.29819,0.00,6.200,0,0.5040,7.6860,17.00,3.3751,8,307.0,17.40,377.51,3.92} | 1 | 46.70 +{1,0.44178,0.00,6.200,0,0.5040,6.5520,21.40,3.3751,8,307.0,17.40,380.34,3.76} | 1 | 31.50 +{1,0.53700,0.00,6.200,0,0.5040,5.9810,68.10,3.6715,8,307.0,17.40,378.35,11.65} | 1 | 24.30 +{1,0.46296,0.00,6.200,0,0.5040,7.4120,76.90,3.6715,8,307.0,17.40,376.14,5.25} | 1 | 31.70 +{1,0.57529,0.00,6.200,0,0.5070,8.3370,73.30,3.8384,8,307.0,17.40,385.91,2.47} | 1 | 41.70 +{1,0.33147,0.00,6.200,0,0.5070,8.2470,70.40,3.6519,8,307.0,17.40,378.95,3.95} | 1 | 48.30 +{1,0.44791,0.00,6.200,1,0.5070,6.7260,66.50,3.6519,8,307.0,17.40,360.20,8.05} | 1 | 29.00 +{1,0.33045,0.00,6.200,0,0.5070,6.0860,61.50,3.6519,8,307.0,17.40,376.75,10.88} | 1 | 24.00 +{1,0.52058,0.00,6.200,1,0.5070,6.6310,76.50,4.1480,8,307.0,17.40,388.45,9.54} | 1 | 25.10 +{1,0.51183,0.00,6.200,0,0.5070,7.3580,71.60,4.1480,8,307.0,17.40,390.07,4.73} | 1 | 31.50 +{1,0.08244,30.00,4.930,0,0.4280,6.4810,18.50,6.1899,6,300.0,16.60,379.41,6.36} | 1 | 23.70 +{1,0.09252,30.00,4.930,0,0.4280,6.6060,42.20,6.1899,6,300.0,16.60,383.78,7.37} | 1 | 23.30 +{1,0.11329,30.00,4.930,0,0.4280,6.8970,54.30,6.3361,6,300.0,16.60,391.25,11.38} | 1 | 22.00 +{1,0.10612,30.00,4.930,0,0.4280,6.0950,65.10,6.3361,6,300.0,16.60,394.62,12.40} | 1 | 20.10 +{1,0.10290,30.00,4.930,0,0.4280,6.3580,52.90,7.0355,6,300.0,16.60,372.75,11.22} | 1 | 22.20 +{1,0.12757,30.00,4.930,0,0.4280,6.3930,7.80,7.0355,6,300.0,16.60,374.71,5.19} | 1 | 23.70 +{1,0.20608,22.00,5.860,0,0.4310,5.5930,76.50,7.9549,7,330.0,19.10,372.49,12.50} | 1 | 17.60 +{1,0.19133,22.00,5.860,0,0.4310,5.6050,70.20,7.9549,7,330.0,19.10,389.13,18.46} | 2 | 18.50 +{1,0.33983,22.00,5.860,0,0.4310,6.1080,34.90,8.0555,7,330.0,19.10,390.18,9.16} | 2 | 24.30 +{1,0.19657,22.00,5.860,0,0.4310,6.2260,79.20,8.0555,7,330.0,19.10,376.14,10.15} | 2 | 20.50 +{1,0.16439,22.00,5.860,0,0.4310,6.4330,49.10,7.8265,7,330.0,19.10,374.71,9.52} | 2 | 24.50 +{1,0.19073,22.00,5.860,0,0.4310,6.7180,17.50,7.8265,7,330.0,19.10,393.74,6.56} | 2 | 26.20 +{1,0.14030,22.00,5.860,0,0.4310,6.4870,13.00,7.3967,7,330.0,19.10,396.28,5.90} | 2 | 24.40 +{1,0.21409,22.00,5.860,0,0.4310,6.4380,8.90,7.3967,7,330.0,19.10,377.07,3.59} | 2 | 24.80 +{1,0.08221,22.00,5.860,0,0.4310,6.9570,6.80,8.9067,7,330.0,19.10,386.09,3.53} | 2 | 29.60 +{1,0.36894,22.00,5.860,0,0.4310,8.2590,8.40,8.9067,7,330.0,19.10,396.90,3.54} | 2 | 42.80 +{1,0.04819,80.00,3.640,0,0.3920,6.1080,32.00,9.2203,1,315.0,16.40,392.89,6.57} | 2 | 21.90 +{1,0.03548,80.00,3.640,0,0.3920,5.8760,19.10,9.2203,1,315.0,16.40,395.18,9.25} | 2 | 20.90 +{1,0.01538,90.00,3.750,0,0.3940,7.4540,34.20,6.3361,3,244.0,15.90,386.34,3.11} | 2 | 44.00 +{1,0.61154,20.00,3.970,0,0.6470,8.7040,86.90,1.8010,5,264.0,13.00,389.70,5.12} | 2 | 50.00 +{1,0.66351,20.00,3.970,0,0.6470,7.3330,100.00,1.8946,5,264.0,13.00,383.29,7.79} | 2 | 36.00 +{1,0.65665,20.00,3.970,0,0.6470,6.8420,100.00,2.0107,5,264.0,13.00,391.93,6.90} | 2 | 30.10 +{1,0.54011,20.00,3.970,0,0.6470,7.2030,81.80,2.1121,5,264.0,13.00,392.80,9.59} | 2 | 33.80 +{1,0.53412,20.00,3.970,0,0.6470,7.5200,89.40,2.1398,5,264.0,13.00,388.37,7.26} | 2 | 43.10 +{1,0.52014,20.00,3.970,0,0.6470,8.3980,91.50,2.2885,5,264.0,13.00,386.86,5.91} | 2 | 48.80 +{1,0.82526,20.00,3.970,0,0.6470,7.3270,94.50,2.0788,5,264.0,13.00,393.42,11.25} | 2 | 31.00 +{1,0.55007,20.00,3.970,0,0.6470,7.2060,91.60,1.9301,5,264.0,13.00,387.89,8.10} | 2 | 36.50 +{1,0.76162,20.00,3.970,0,0.6470,5.5600,62.80,1.9865,5,264.0,13.00,392.40,10.45} | 2 | 22.80 +{1,0.78570,20.00,3.970,0,0.6470,7.0140,84.60,2.1329,5,264.0,13.00,384.07,14.79} | 2 | 30.70 +{1,0.57834,20.00,3.970,0,0.5750,8.2970,67.00,2.4216,5,264.0,13.00,384.54,7.44} | 2 | 50.00 +{1,0.54050,20.00,3.970,0,0.5750,7.4700,52.60,2.8720,5,264.0,13.00,390.30,3.16} | 2 | 43.50 +{1,0.09065,20.00,6.960,1,0.4640,5.9200,61.50,3.9175,3,223.0,18.60,391.34,13.65} | 2 | 20.70 +{1,0.29916,20.00,6.960,0,0.4640,5.8560,42.10,4.4290,3,223.0,18.60,388.65,13.00} | 2 | 21.10 +{1,0.16211,20.00,6.960,0,0.4640,6.2400,16.30,4.4290,3,223.0,18.60,396.90,6.59} | 2 | 25.20 +{1,0.11460,20.00,6.960,0,0.4640,6.5380,58.70,3.9175,3,223.0,18.60,394.96,7.73} | 2 | 24.40 +{1,0.22188,20.00,6.960,1,0.4640,7.6910,51.80,4.3665,3,223.0,18.60,390.77,6.58} | 2 | 35.20 +{1,0.05644,40.00,6.410,1,0.4470,6.7580,32.90,4.0776,4,254.0,17.60,396.90,3.53} | 2 | 32.40 +{1,0.09604,40.00,6.410,0,0.4470,6.8540,42.80,4.2673,4,254.0,17.60,396.90,2.98} | 2 | 32.00 +{1,0.10469,40.00,6.410,1,0.4470,7.2670,49.00,4.7872,4,254.0,17.60,389.25,6.05} | 2 | 33.20 +{1,0.06127,40.00,6.410,1,0.4470,6.8260,27.60,4.8628,4,254.0,17.60,393.45,4.16} | 2 | 33.10 +{1,0.07978,40.00,6.410,0,0.4470,6.4820,32.10,4.1403,4,254.0,17.60,396.90,7.19} | 2 | 29.10 +{1,0.21038,20.00,3.330,0,0.4429,6.8120,32.20,4.1007,5,216.0,14.90,396.90,4.85} | 2 | 35.10 +{1,0.03578,20.00,3.330,0,0.4429,7.8200,64.50,4.6947,5,216.0,14.90,387.31,3.76} | 2 | 45.40 +{1,0.03705,20.00,3.330,0,0.4429,6.9680,37.20,5.2447,5,216.0,14.90,392.23,4.59} | 2 | 35.40 +{1,0.06129,20.00,3.330,1,0.4429,7.6450,49.70,5.2119,5,216.0,14.90,377.07,3.01} | 2 | 46.00 +{1,0.01501,90.00,1.210,1,0.4010,7.9230,24.80,5.8850,1,198.0,13.60,395.52,3.16} | 2 | 50.00 +{1,0.00906,90.00,2.970,0,0.4000,7.0880,20.80,7.3073,1,285.0,15.30,394.72,7.85} | 2 | 32.20 +{1,0.01096,55.00,2.250,0,0.3890,6.4530,31.90,7.3073,1,300.0,15.30,394.72,8.23} | 2 | 22.00 +{1,0.01965,80.00,1.760,0,0.3850,6.2300,31.50,9.0892,1,241.0,18.20,341.60,12.93} | 2 | 20.10 +{1,0.03871,52.50,5.320,0,0.4050,6.2090,31.30,7.3172,6,293.0,16.60,396.90,7.14} | 2 | 23.20 +{1,0.04590,52.50,5.320,0,0.4050,6.3150,45.60,7.3172,6,293.0,16.60,396.90,7.60} | 2 | 22.30 +{1,0.04297,52.50,5.320,0,0.4050,6.5650,22.90,7.3172,6,293.0,16.60,371.72,9.51} | 2 | 24.80 +{1,0.03502,80.00,4.950,0,0.4110,6.8610,27.90,5.1167,4,245.0,19.20,396.90,3.33} | 2 | 28.50 +{1,0.07886,80.00,4.950,0,0.4110,7.1480,27.70,5.1167,4,245.0,19.20,396.90,3.56} | 2 | 37.30 +{1,0.03615,80.00,4.950,0,0.4110,6.6300,23.40,5.1167,4,245.0,19.20,396.90,4.70} | 2 | 27.90 +{1,0.08265,0.00,13.920,0,0.4370,6.1270,18.40,5.5027,4,289.0,16.00,396.90,8.58} | 2 | 23.90 +{1,0.08199,0.00,13.920,0,0.4370,6.0090,42.30,5.5027,4,289.0,16.00,396.90,10.40} | 2 | 21.70 +{1,0.12932,0.00,13.920,0,0.4370,6.6780,31.10,5.9604,4,289.0,16.00,396.90,6.27} | 2 | 28.60 +{1,0.05372,0.00,13.920,0,0.4370,6.5490,51.00,5.9604,4,289.0,16.00,392.85,7.39} | 2 | 27.10 +{1,0.14103,0.00,13.920,0,0.4370,5.7900,58.00,6.3200,4,289.0,16.00,396.90,15.84} | 2 | 20.30 +{1,0.06466,70.00,2.240,0,0.4000,6.3450,20.10,7.8278,5,358.0,14.80,368.24,4.97} | 2 | 22.50 +{1,0.05561,70.00,2.240,0,0.4000,7.0410,10.00,7.8278,5,358.0,14.80,371.58,4.74} | 2 | 29.00 +{1,0.04417,70.00,2.240,0,0.4000,6.8710,47.40,7.8278,5,358.0,14.80,390.86,6.07} | 2 | 24.80 +{1,0.03537,34.00,6.090,0,0.4330,6.5900,40.40,5.4917,7,329.0,16.10,395.75,9.50} | 2 | 22.00 +{1,0.09266,34.00,6.090,0,0.4330,6.4950,18.40,5.4917,7,329.0,16.10,383.61,8.67} | 2 | 26.40 +{1,0.10000,34.00,6.090,0,0.4330,6.9820,17.70,5.4917,7,329.0,16.10,390.43,4.86} | 2 | 33.10 +{1,0.05515,33.00,2.180,0,0.4720,7.2360,41.10,4.0220,7,222.0,18.40,393.68,6.93} | 2 | 36.10 +{1,0.05479,33.00,2.180,0,0.4720,6.6160,58.10,3.3700,7,222.0,18.40,393.36,8.93} | 2 | 28.40 +{1,0.07503,33.00,2.180,0,0.4720,7.4200,71.90,3.0992,7,222.0,18.40,396.90,6.47} | 2 | 33.40 +{1,0.04932,33.00,2.180,0,0.4720,6.8490,70.30,3.1827,7,222.0,18.40,396.90,7.53} | 2 | 28.20 +{1,0.49298,0.00,9.900,0,0.5440,6.6350,82.50,3.3175,4,304.0,18.40,396.90,4.54} | 2 | 22.80 +{1,0.34940,0.00,9.900,0,0.5440,5.9720,76.70,3.1025,4,304.0,18.40,396.24,9.97} | 2 | 20.30 +{1,2.63548,0.00,9.900,0,0.5440,4.9730,37.80,2.5194,4,304.0,18.40,350.45,12.64} | 2 | 16.10 +{1,0.79041,0.00,9.900,0,0.5440,6.1220,52.80,2.6403,4,304.0,18.40,396.90,5.98} | 2 | 22.10 +{1,0.26169,0.00,9.900,0,0.5440,6.0230,90.40,2.8340,4,304.0,18.40,396.30,11.72} | 2 | 19.40 +{1,0.26938,0.00,9.900,0,0.5440,6.2660,82.80,3.2628,4,304.0,18.40,393.39,7.90} | 2 | 21.60 +{1,0.36920,0.00,9.900,0,0.5440,6.5670,87.30,3.6023,4,304.0,18.40,395.69,9.28} | 2 | 23.80 +{1,0.25356,0.00,9.900,0,0.5440,5.7050,77.70,3.9450,4,304.0,18.40,396.42,11.50} | 2 | 16.20 +{1,0.31827,0.00,9.900,0,0.5440,5.9140,83.20,3.9986,4,304.0,18.40,390.70,18.33} | 2 | 17.80 +{1,0.24522,0.00,9.900,0,0.5440,5.7820,71.70,4.0317,4,304.0,18.40,396.90,15.94} | 2 | 19.80 +{1,0.40202,0.00,9.900,0,0.5440,6.3820,67.20,3.5325,4,304.0,18.40,395.21,10.36} | 2 | 23.10 +{1,0.47547,0.00,9.900,0,0.5440,6.1130,58.80,4.0019,4,304.0,18.40,396.23,12.73} | 2 | 21.00 +{1,0.16760,0.00,7.380,0,0.4930,6.4260,52.30,4.5404,5,287.0,19.60,396.90,7.20} | 2 | 23.80 +{1,0.18159,0.00,7.380,0,0.4930,6.3760,54.30,4.5404,5,287.0,19.60,396.90,6.87} | 2 | 23.10 +{1,0.35114,0.00,7.380,0,0.4930,6.0410,49.90,4.7211,5,287.0,19.60,396.90,7.70} | 2 | 20.40 +{1,0.28392,0.00,7.380,0,0.4930,5.7080,74.30,4.7211,5,287.0,19.60,391.13,11.74} | 2 | 18.50 +{1,0.34109,0.00,7.380,0,0.4930,6.4150,40.10,4.7211,5,287.0,19.60,396.90,6.12} | 2 | 25.00 +{1,0.19186,0.00,7.380,0,0.4930,6.4310,14.70,5.4159,5,287.0,19.60,393.68,5.08} | 2 | 24.60 +{1,0.30347,0.00,7.380,0,0.4930,6.3120,28.90,5.4159,5,287.0,19.60,396.90,6.15} | 2 | 23.00 +{1,0.24103,0.00,7.380,0,0.4930,6.0830,43.70,5.4159,5,287.0,19.60,396.90,12.79} | 2 | 22.20 +{1,0.06617,0.00,3.240,0,0.4600,5.8680,25.80,5.2146,4,430.0,16.90,382.44,9.97} | 2 | 19.30 +{1,0.06724,0.00,3.240,0,0.4600,6.3330,17.20,5.2146,4,430.0,16.90,375.21,7.34} | 2 | 22.60 +{1,0.04544,0.00,3.240,0,0.4600,6.1440,32.20,5.8736,4,430.0,16.90,368.57,9.09} | 2 | 19.80 +{1,0.05023,35.00,6.060,0,0.4379,5.7060,28.40,6.6407,1,304.0,16.90,394.02,12.43} | 2 | 17.10 +{1,0.03466,35.00,6.060,0,0.4379,6.0310,23.30,6.6407,1,304.0,16.90,362.25,7.83} | 2 | 19.40 +{1,0.05083,0.00,5.190,0,0.5150,6.3160,38.10,6.4584,5,224.0,20.20,389.71,5.68} | 2 | 22.20 +{1,0.03738,0.00,5.190,0,0.5150,6.3100,38.50,6.4584,5,224.0,20.20,389.40,6.75} | 2 | 20.70 +{1,0.03961,0.00,5.190,0,0.5150,6.0370,34.50,5.9853,5,224.0,20.20,396.90,8.01} | 2 | 21.10 +{1,0.03427,0.00,5.190,0,0.5150,5.8690,46.30,5.2311,5,224.0,20.20,396.90,9.80} | 2 | 19.50 +{1,0.03041,0.00,5.190,0,0.5150,5.8950,59.60,5.6150,5,224.0,20.20,394.81,10.56} | 2 | 18.50 +{1,0.03306,0.00,5.190,0,0.5150,6.0590,37.30,4.8122,5,224.0,20.20,396.14,8.51} | 2 | 20.60 +{1,0.05497,0.00,5.190,0,0.5150,5.9850,45.40,4.8122,5,224.0,20.20,396.90,9.74} | 2 | 19.00 +{1,0.06151,0.00,5.190,0,0.5150,5.9680,58.50,4.8122,5,224.0,20.20,396.90,9.29} | 2 | 18.70 +{1,0.01301,35.00,1.520,0,0.4420,7.2410,49.30,7.0379,1,284.0,15.50,394.74,5.49} | 2 | 32.70 +{1,0.02498,0.00,1.890,0,0.5180,6.5400,59.70,6.2669,1,422.0,15.90,389.96,8.65} | 2 | 16.50 +{1,0.02543,55.00,3.780,0,0.4840,6.6960,56.40,5.7321,5,370.0,17.60,396.90,7.18} | 2 | 23.90 +{1,0.03049,55.00,3.780,0,0.4840,6.8740,28.10,6.4654,5,370.0,17.60,387.97,4.61} | 2 | 31.20 +{1,0.03113,0.00,4.390,0,0.4420,6.0140,48.50,8.0136,3,352.0,18.80,385.64,10.53} | 2 | 17.50 +{1,0.06162,0.00,4.390,0,0.4420,5.8980,52.30,8.0136,3,352.0,18.80,364.61,12.67} | 2 | 17.20 +{1,0.01870,85.00,4.150,0,0.4290,6.5160,27.70,8.5353,4,351.0,17.90,392.43,6.36} | 2 | 23.10 +{1,0.01501,80.00,2.010,0,0.4350,6.6350,29.70,8.3440,4,280.0,17.00,390.94,5.99} | 2 | 24.50 +{1,0.02899,40.00,1.250,0,0.4290,6.9390,34.50,8.7921,1,335.0,19.70,389.85,5.89} | 2 | 26.60 +{1,0.06211,40.00,1.250,0,0.4290,6.4900,44.40,8.7921,1,335.0,19.70,396.90,5.98} | 2 | 22.90 +{1,0.07950,60.00,1.690,0,0.4110,6.5790,35.90,10.7103,4,411.0,18.30,370.78,5.49} | 2 | 24.10 +{1,0.07244,60.00,1.690,0,0.4110,5.8840,18.50,10.7103,4,411.0,18.30,392.33,7.79} | 2 | 18.60 +{1,0.01709,90.00,2.020,0,0.4100,6.7280,36.10,12.1265,5,187.0,17.00,384.46,4.50} | 2 | 30.10 +{1,0.04301,80.00,1.910,0,0.4130,5.6630,21.90,10.5857,4,334.0,22.00,382.80,8.05} | 2 | 18.20 +{1,0.10659,80.00,1.910,0,0.4130,5.9360,19.50,10.5857,4,334.0,22.00,376.04,5.57} | 2 | 20.60 +{1,8.98296,0.00,18.100,1,0.7700,6.2120,97.40,2.1222,24,666.0,20.20,377.73,17.60} | 2 | 17.80 +{1,3.84970,0.00,18.100,1,0.7700,6.3950,91.00,2.5052,24,666.0,20.20,391.34,13.27} | 2 | 21.70 +{1,5.20177,0.00,18.100,1,0.7700,6.1270,83.40,2.7227,24,666.0,20.20,395.43,11.48} | 2 | 22.70 +{1,4.26131,0.00,18.100,0,0.7700,6.1120,81.30,2.5091,24,666.0,20.20,390.74,12.67} | 2 | 22.60 +{1,4.54192,0.00,18.100,0,0.7700,6.3980,88.00,2.5182,24,666.0,20.20,374.56,7.79} | 2 | 25.00 +{1,3.83684,0.00,18.100,0,0.7700,6.2510,91.10,2.2955,24,666.0,20.20,350.65,14.19} | 2 | 19.90 +{1,3.67822,0.00,18.100,0,0.7700,5.3620,96.20,2.1036,24,666.0,20.20,380.79,10.19} | 2 | 20.80 +{1,4.22239,0.00,18.100,1,0.7700,5.8030,89.00,1.9047,24,666.0,20.20,353.04,14.64} | 2 | 16.80 +{1,3.47428,0.00,18.100,1,0.7180,8.7800,82.90,1.9047,24,666.0,20.20,354.55,5.29} | 2 | 21.90 +{1,4.55587,0.00,18.100,0,0.7180,3.5610,87.90,1.6132,24,666.0,20.20,354.70,7.12} | 2 | 27.50 +{1,3.69695,0.00,18.100,0,0.7180,4.9630,91.40,1.7523,24,666.0,20.20,316.03,14.00} | 2 | 21.90 +{1,13.52220,0.00,18.100,0,0.6310,3.8630,100.00,1.5106,24,666.0,20.20,131.42,13.33} | 2 | 23.10 +{1,4.89822,0.00,18.100,0,0.6310,4.9700,100.00,1.3325,24,666.0,20.20,375.52,3.26} | 2 | 50.00 +{1,5.66998,0.00,18.100,1,0.6310,6.6830,96.80,1.3567,24,666.0,20.20,375.33,3.73} | 2 | 50.00 +{1,6.53876,0.00,18.100,1,0.6310,7.0160,97.50,1.2024,24,666.0,20.20,392.05,2.96} | 2 | 50.00 +{1,9.23230,0.00,18.100,0,0.6310,6.2160,100.00,1.1691,24,666.0,20.20,366.15,9.53} | 2 | 50.00 +{1,8.26725,0.00,18.100,1,0.6680,5.8750,89.60,1.1296,24,666.0,20.20,347.88,8.88} | 2 | 50.00 +{1,11.10810,0.00,18.100,0,0.6680,4.9060,100.00,1.1742,24,666.0,20.20,396.90,34.77} | 2 | 13.80 +{1,18.49820,0.00,18.100,0,0.6680,4.1380,100.00,1.1370,24,666.0,20.20,396.90,37.97} | 2 | 13.80 +{1,19.60910,0.00,18.100,0,0.6710,7.3130,97.90,1.3163,24,666.0,20.20,396.90,13.44} | 2 | 15.00 +{1,15.28800,0.00,18.100,0,0.6710,6.6490,93.30,1.3449,24,666.0,20.20,363.02,23.24} | 2 | 13.90 +{1,9.82349,0.00,18.100,0,0.6710,6.7940,98.80,1.3580,24,666.0,20.20,396.90,21.24} | 2 | 13.30 +{1,23.64820,0.00,18.100,0,0.6710,6.3800,96.20,1.3861,24,666.0,20.20,396.90,23.69} | 2 | 13.10 +{1,17.86670,0.00,18.100,0,0.6710,6.2230,100.00,1.3861,24,666.0,20.20,393.74,21.78} | 2 | 10.20 +{1,88.97620,0.00,18.100,0,0.6710,6.9680,91.90,1.4165,24,666.0,20.20,396.90,17.21} | 2 | 10.40 +{1,15.87440,0.00,18.100,0,0.6710,6.5450,99.10,1.5192,24,666.0,20.20,396.90,21.08} | 2 | 10.90 +{1,9.18702,0.00,18.100,0,0.7000,5.5360,100.00,1.5804,24,666.0,20.20,396.90,23.60} | 2 | 11.30 +{1,7.99248,0.00,18.100,0,0.7000,5.5200,100.00,1.5331,24,666.0,20.20,396.90,24.56} | 2 | 12.30 +{1,20.08490,0.00,18.100,0,0.7000,4.3680,91.20,1.4395,24,666.0,20.20,285.83,30.63} | 2 | 8.80 +{1,16.81180,0.00,18.100,0,0.7000,5.2770,98.10,1.4261,24,666.0,20.20,396.90,30.81} | 2 | 7.20 +{1,24.39380,0.00,18.100,0,0.7000,4.6520,100.00,1.4672,24,666.0,20.20,396.90,28.28} | 2 | 10.50 +{1,22.59710,0.00,18.100,0,0.7000,5.0000,89.50,1.5184,24,666.0,20.20,396.90,31.99} | 2 | 7.40 +{1,14.33370,0.00,18.100,0,0.7000,4.8800,100.00,1.5895,24,666.0,20.20,372.92,30.62} | 2 | 10.20 +{1,8.15174,0.00,18.100,0,0.7000,5.3900,98.90,1.7281,24,666.0,20.20,396.90,20.85} | 2 | 11.50 +{1,6.96215,0.00,18.100,0,0.7000,5.7130,97.00,1.9265,24,666.0,20.20,394.43,17.11} | 2 | 15.10 +{1,5.29305,0.00,18.100,0,0.7000,6.0510,82.50,2.1678,24,666.0,20.20,378.38,18.76} | 2 | 23.20 +{1,11.57790,0.00,18.100,0,0.7000,5.0360,97.00,1.7700,24,666.0,20.20,396.90,25.68} | 2 | 9.70 +{1,8.64476,0.00,18.100,0,0.6930,6.1930,92.60,1.7912,24,666.0,20.20,396.90,15.17} | 2 | 13.80 +{1,13.35980,0.00,18.100,0,0.6930,5.8870,94.70,1.7821,24,666.0,20.20,396.90,16.35} | 2 | 12.70 +{1,8.71675,0.00,18.100,0,0.6930,6.4710,98.80,1.7257,24,666.0,20.20,391.98,17.12} | 2 | 13.10 +{1,5.87205,0.00,18.100,0,0.6930,6.4050,96.00,1.6768,24,666.0,20.20,396.90,19.37} | 2 | 12.50 +{1,7.67202,0.00,18.100,0,0.6930,5.7470,98.90,1.6334,24,666.0,20.20,393.10,19.92} | 2 | 8.50 +{1,38.35180,0.00,18.100,0,0.6930,5.4530,100.00,1.4896,24,666.0,20.20,396.90,30.59} | 2 | 5.00 +{1,9.91655,0.00,18.100,0,0.6930,5.8520,77.80,1.5004,24,666.0,20.20,338.16,29.97} | 2 | 6.30 +{1,25.04610,0.00,18.100,0,0.6930,5.9870,100.00,1.5888,24,666.0,20.20,396.90,26.77} | 2 | 5.60 +{1,14.23620,0.00,18.100,0,0.6930,6.3430,100.00,1.5741,24,666.0,20.20,396.90,20.32} | 2 | 7.20 +{1,9.59571,0.00,18.100,0,0.6930,6.4040,100.00,1.6390,24,666.0,20.20,376.11,20.31} | 2 | 12.10 +{1,24.80170,0.00,18.100,0,0.6930,5.3490,96.00,1.7028,24,666.0,20.20,396.90,19.77} | 2 | 8.30 +{1,41.52920,0.00,18.100,0,0.6930,5.5310,85.40,1.6074,24,666.0,20.20,329.46,27.38} | 2 | 8.50 +{1,67.92080,0.00,18.100,0,0.6930,5.6830,100.00,1.4254,24,666.0,20.20,384.97,22.98} | 2 | 5.00 +{1,20.71620,0.00,18.100,0,0.6590,4.1380,100.00,1.1781,24,666.0,20.20,370.22,23.34} | 2 | 11.90 +{1,11.95110,0.00,18.100,0,0.6590,5.6080,100.00,1.2852,24,666.0,20.20,332.09,12.13} | 2 | 27.90 +{1,7.40389,0.00,18.100,0,0.5970,5.6170,97.90,1.4547,24,666.0,20.20,314.64,26.40} | 2 | 17.20 +{1,14.43830,0.00,18.100,0,0.5970,6.8520,100.00,1.4655,24,666.0,20.20,179.36,19.78} | 2 | 27.50 +{1,51.13580,0.00,18.100,0,0.5970,5.7570,100.00,1.4130,24,666.0,20.20,2.60,10.11} | 2 | 15.00 +{1,14.05070,0.00,18.100,0,0.5970,6.6570,100.00,1.5275,24,666.0,20.20,35.05,21.22} | 2 | 17.20 +{1,18.81100,0.00,18.100,0,0.5970,4.6280,100.00,1.5539,24,666.0,20.20,28.79,34.37} | 2 | 17.90 +{1,28.65580,0.00,18.100,0,0.5970,5.1550,100.00,1.5894,24,666.0,20.20,210.97,20.08} | 2 | 16.30 +{1,45.74610,0.00,18.100,0,0.6930,4.5190,100.00,1.6582,24,666.0,20.20,88.27,36.98} | 2 | 7.00 +{1,18.08460,0.00,18.100,0,0.6790,6.4340,100.00,1.8347,24,666.0,20.20,27.25,29.05} | 2 | 7.20 +{1,10.83420,0.00,18.100,0,0.6790,6.7820,90.80,1.8195,24,666.0,20.20,21.57,25.79} | 2 | 7.50 +{1,25.94060,0.00,18.100,0,0.6790,5.3040,89.10,1.6475,24,666.0,20.20,127.36,26.64} | 2 | 10.40 +{1,73.53410,0.00,18.100,0,0.6790,5.9570,100.00,1.8026,24,666.0,20.20,16.45,20.62} | 2 | 8.80 +{1,11.81230,0.00,18.100,0,0.7180,6.8240,76.50,1.7940,24,666.0,20.20,48.45,22.74} | 2 | 8.40 +{1,11.08740,0.00,18.100,0,0.7180,6.4110,100.00,1.8589,24,666.0,20.20,318.75,15.02} | 2 | 16.70 +{1,7.02259,0.00,18.100,0,0.7180,6.0060,95.30,1.8746,24,666.0,20.20,319.98,15.70} | 2 | 14.20 +{1,12.04820,0.00,18.100,0,0.6140,5.6480,87.60,1.9512,24,666.0,20.20,291.55,14.10} | 2 | 20.80 +{1,7.05042,0.00,18.100,0,0.6140,6.1030,85.10,2.0218,24,666.0,20.20,2.52,23.29} | 2 | 13.40 +{1,8.79212,0.00,18.100,0,0.5840,5.5650,70.60,2.0635,24,666.0,20.20,3.65,17.16} | 2 | 11.70 +{1,15.86030,0.00,18.100,0,0.6790,5.8960,95.40,1.9096,24,666.0,20.20,7.68,24.39} | 2 | 8.30 +{1,12.24720,0.00,18.100,0,0.5840,5.8370,59.70,1.9976,24,666.0,20.20,24.65,15.69} | 2 | 10.20 +{1,37.66190,0.00,18.100,0,0.6790,6.2020,78.70,1.8629,24,666.0,20.20,18.82,14.52} | 2 | 10.90 +{1,7.36711,0.00,18.100,0,0.6790,6.1930,78.10,1.9356,24,666.0,20.20,96.73,21.52} | 2 | 11.00 +{1,9.33889,0.00,18.100,0,0.6790,6.3800,95.60,1.9682,24,666.0,20.20,60.72,24.08} | 2 | 9.50 +{1,8.49213,0.00,18.100,0,0.5840,6.3480,86.10,2.0527,24,666.0,20.20,83.45,17.64} | 2 | 14.50 +{1,10.06230,0.00,18.100,0,0.5840,6.8330,94.30,2.0882,24,666.0,20.20,81.33,19.69} | 2 | 14.10 +{1,6.44405,0.00,18.100,0,0.5840,6.4250,74.80,2.2004,24,666.0,20.20,97.95,12.03} | 2 | 16.10 +{1,5.58107,0.00,18.100,0,0.7130,6.4360,87.90,2.3158,24,666.0,20.20,100.19,16.22} | 2 | 14.30 +{1,13.91340,0.00,18.100,0,0.7130,6.2080,95.00,2.2222,24,666.0,20.20,100.63,15.17} | 2 | 11.70 +{1,11.16040,0.00,18.100,0,0.7400,6.6290,94.60,2.1247,24,666.0,20.20,109.85,23.27} | 2 | 13.40 +{1,14.42080,0.00,18.100,0,0.7400,6.4610,93.30,2.0026,24,666.0,20.20,27.49,18.05} | 2 | 9.60 +{1,15.17720,0.00,18.100,0,0.7400,6.1520,100.00,1.9142,24,666.0,20.20,9.32,26.45} | 2 | 8.70 +{1,13.67810,0.00,18.100,0,0.7400,5.9350,87.90,1.8206,24,666.0,20.20,68.95,34.02} | 2 | 8.40 +{1,9.39063,0.00,18.100,0,0.7400,5.6270,93.90,1.8172,24,666.0,20.20,396.90,22.88} | 2 | 12.80 +{1,22.05110,0.00,18.100,0,0.7400,5.8180,92.40,1.8662,24,666.0,20.20,391.45,22.11} | 2 | 10.50 +{1,9.72418,0.00,18.100,0,0.7400,6.4060,97.20,2.0651,24,666.0,20.20,385.96,19.52} | 2 | 17.10 +{1,5.66637,0.00,18.100,0,0.7400,6.2190,100.00,2.0048,24,666.0,20.20,395.69,16.59} | 2 | 18.40 +{1,9.96654,0.00,18.100,0,0.7400,6.4850,100.00,1.9784,24,666.0,20.20,386.73,18.85} | 2 | 15.40 +{1,12.80230,0.00,18.100,0,0.7400,5.8540,96.60,1.8956,24,666.0,20.20,240.52,23.79} | 2 | 10.80 +{1,10.67180,0.00,18.100,0,0.7400,6.4590,94.80,1.9879,24,666.0,20.20,43.06,23.98} | 2 | 11.80 +{1,6.28807,0.00,18.100,0,0.7400,6.3410,96.40,2.0720,24,666.0,20.20,318.01,17.79} | 2 | 14.90 +{1,9.92485,0.00,18.100,0,0.7400,6.2510,96.60,2.1980,24,666.0,20.20,388.52,16.44} | 2 | 12.60 +{1,9.32909,0.00,18.100,0,0.7130,6.1850,98.70,2.2616,24,666.0,20.20,396.90,18.13} | 2 | 14.10 +{1,7.52601,0.00,18.100,0,0.7130,6.4170,98.30,2.1850,24,666.0,20.20,304.21,19.31} | 2 | 13.00 +{1,6.71772,0.00,18.100,0,0.7130,6.7490,92.60,2.3236,24,666.0,20.20,0.32,17.44} | 2 | 13.40 +{1,5.44114,0.00,18.100,0,0.7130,6.6550,98.20,2.3552,24,666.0,20.20,355.29,17.73} | 2 | 15.20 +{1,5.09017,0.00,18.100,0,0.7130,6.2970,91.80,2.3682,24,666.0,20.20,385.09,17.27} | 2 | 16.10 +{1,8.24809,0.00,18.100,0,0.7130,7.3930,99.30,2.4527,24,666.0,20.20,375.87,16.74} | 2 | 17.80 +{1,9.51363,0.00,18.100,0,0.7130,6.7280,94.10,2.4961,24,666.0,20.20,6.68,18.71} | 2 | 14.90 +{1,4.75237,0.00,18.100,0,0.7130,6.5250,86.50,2.4358,24,666.0,20.20,50.92,18.13} | 2 | 14.10 +{1,4.66883,0.00,18.100,0,0.7130,5.9760,87.90,2.5806,24,666.0,20.20,10.48,19.01} | 2 | 12.70 +{1,8.20058,0.00,18.100,0,0.7130,5.9360,80.30,2.7792,24,666.0,20.20,3.50,16.94} | 2 | 13.50 +{1,7.75223,0.00,18.100,0,0.7130,6.3010,83.70,2.7831,24,666.0,20.20,272.21,16.23} | 2 | 14.90 +{1,6.80117,0.00,18.100,0,0.7130,6.0810,84.40,2.7175,24,666.0,20.20,396.90,14.70} | 2 | 20.00 +{1,4.81213,0.00,18.100,0,0.7130,6.7010,90.00,2.5975,24,666.0,20.20,255.23,16.42} | 2 | 16.40 +{1,3.69311,0.00,18.100,0,0.7130,6.3760,88.40,2.5671,24,666.0,20.20,391.43,14.65} | 2 | 17.70 +{1,6.65492,0.00,18.100,0,0.7130,6.3170,83.00,2.7344,24,666.0,20.20,396.90,13.99} | 2 | 19.50 +{1,5.82115,0.00,18.100,0,0.7130,6.5130,89.90,2.8016,24,666.0,20.20,393.82,10.29} | 2 | 20.20 +{1,7.83932,0.00,18.100,0,0.6550,6.2090,65.40,2.9634,24,666.0,20.20,396.90,13.22} | 2 | 21.40 +{1,3.16360,0.00,18.100,0,0.6550,5.7590,48.20,3.0665,24,666.0,20.20,334.40,14.13} | 2 | 19.90 +{1,3.77498,0.00,18.100,0,0.6550,5.9520,84.70,2.8715,24,666.0,20.20,22.01,17.15} | 2 | 19.00 +{1,4.42228,0.00,18.100,0,0.5840,6.0030,94.50,2.5403,24,666.0,20.20,331.29,21.32} | 2 | 19.10 +{1,15.57570,0.00,18.100,0,0.5800,5.9260,71.00,2.9084,24,666.0,20.20,368.74,18.13} | 2 | 19.10 +{1,13.07510,0.00,18.100,0,0.5800,5.7130,56.70,2.8237,24,666.0,20.20,396.90,14.76} | 2 | 20.10 +{1,4.34879,0.00,18.100,0,0.5800,6.1670,84.00,3.0334,24,666.0,20.20,396.90,16.29} | 2 | 19.90 +{1,4.03841,0.00,18.100,0,0.5320,6.2290,90.70,3.0993,24,666.0,20.20,395.33,12.87} | 2 | 19.60 +{1,3.56868,0.00,18.100,0,0.5800,6.4370,75.00,2.8965,24,666.0,20.20,393.37,14.36} | 2 | 23.20 +{1,4.64689,0.00,18.100,0,0.6140,6.9800,67.60,2.5329,24,666.0,20.20,374.68,11.66} | 2 | 29.80 +{1,8.05579,0.00,18.100,0,0.5840,5.4270,95.40,2.4298,24,666.0,20.20,352.58,18.14} | 2 | 13.80 +{1,6.39312,0.00,18.100,0,0.5840,6.1620,97.40,2.2060,24,666.0,20.20,302.76,24.10} | 2 | 13.30 +{1,4.87141,0.00,18.100,0,0.6140,6.4840,93.60,2.3053,24,666.0,20.20,396.21,18.68} | 2 | 16.70 +{1,15.02340,0.00,18.100,0,0.6140,5.3040,97.30,2.1007,24,666.0,20.20,349.48,24.91} | 2 | 12.00 +{1,10.23300,0.00,18.100,0,0.6140,6.1850,96.70,2.1705,24,666.0,20.20,379.70,18.03} | 2 | 14.60 +{1,14.33370,0.00,18.100,0,0.6140,6.2290,88.00,1.9512,24,666.0,20.20,383.32,13.11} | 2 | 21.40 +{1,5.82401,0.00,18.100,0,0.5320,6.2420,64.70,3.4242,24,666.0,20.20,396.90,10.74} | 2 | 23.00 +{1,5.70818,0.00,18.100,0,0.5320,6.7500,74.90,3.3317,24,666.0,20.20,393.07,7.74} | 2 | 23.70 +{1,5.73116,0.00,18.100,0,0.5320,7.0610,77.00,3.4106,24,666.0,20.20,395.28,7.01} | 2 | 25.00 +{1,2.81838,0.00,18.100,0,0.5320,5.7620,40.30,4.0983,24,666.0,20.20,392.92,10.42} | 2 | 21.80 +{1,2.37857,0.00,18.100,0,0.5830,5.8710,41.90,3.7240,24,666.0,20.20,370.73,13.34} | 2 | 20.60 +{1,3.67367,0.00,18.100,0,0.5830,6.3120,51.90,3.9917,24,666.0,20.20,388.62,10.58} | 2 | 21.20 +{1,5.69175,0.00,18.100,0,0.5830,6.1140,79.80,3.5459,24,666.0,20.20,392.68,14.98} | 2 | 19.10 +{1,4.83567,0.00,18.100,0,0.5830,5.9050,53.20,3.1523,24,666.0,20.20,388.22,11.45} | 2 | 20.60 +{1,0.15086,0.00,27.740,0,0.6090,5.4540,92.70,1.8209,4,711.0,20.10,395.09,18.06} | 2 | 15.20 +{1,0.18337,0.00,27.740,0,0.6090,5.4140,98.30,1.7554,4,711.0,20.10,344.05,23.97} | 2 | 7.00 +{1,0.20746,0.00,27.740,0,0.6090,5.0930,98.00,1.8226,4,711.0,20.10,318.43,29.68} | 2 | 8.10 +{1,0.10574,0.00,27.740,0,0.6090,5.9830,98.80,1.8681,4,711.0,20.10,390.11,18.07} | 2 | 13.60 +{1,0.11132,0.00,27.740,0,0.6090,5.9830,83.50,2.1099,4,711.0,20.10,396.90,13.35} | 2 | 20.10 +{1,0.17331,0.00,9.690,0,0.5850,5.7070,54.00,2.3817,6,391.0,19.20,396.90,12.01} | 2 | 21.80 +{1,0.27957,0.00,9.690,0,0.5850,5.9260,42.60,2.3817,6,391.0,19.20,396.90,13.59} | 2 | 24.50 +{1,0.17899,0.00,9.690,0,0.5850,5.6700,28.80,2.7986,6,391.0,19.20,393.29,17.60} | 2 | 23.10 +{1,0.28960,0.00,9.690,0,0.5850,5.3900,72.90,2.7986,6,391.0,19.20,396.90,21.14} | 2 | 19.70 +{1,0.26838,0.00,9.690,0,0.5850,5.7940,70.60,2.8927,6,391.0,19.20,396.90,14.10} | 2 | 18.30 +{1,0.23912,0.00,9.690,0,0.5850,6.0190,65.30,2.4091,6,391.0,19.20,396.90,12.92} | 2 | 21.20 +{1,0.17783,0.00,9.690,0,0.5850,5.5690,73.50,2.3999,6,391.0,19.20,395.77,15.10} | 2 | 17.50 +{1,0.22438,0.00,9.690,0,0.5850,6.0270,79.70,2.4982,6,391.0,19.20,396.90,14.33} | 2 | 16.80 +{1,0.06263,0.00,11.930,0,0.5730,6.5930,69.10,2.4786,1,273.0,21.00,391.99,9.67} | 2 | 22.40 +{1,0.04527,0.00,11.930,0,0.5730,6.1200,76.70,2.2875,1,273.0,21.00,396.90,9.08} | 2 | 20.60 +{1,0.06076,0.00,11.930,0,0.5730,6.9760,91.00,2.1675,1,273.0,21.00,396.90,5.64} | 2 | 23.90 +{1,0.10959,0.00,11.930,0,0.5730,6.7940,89.30,2.3889,1,273.0,21.00,393.45,6.48} | 2 | 22.00 +{1,0.04741,0.00,11.930,0,0.5730,6.0300,80.80,2.5050,1,273.0,21.00,396.90,7.88} | 2 | 11.90 +\. + +-- Normalize the columns +CREATE TEMPORARY TABLE maxs as( + SELECT + max(x[1]) m1, + max(x[2]) m2, + max(x[3]) m3, + max(x[4]) m4, + max(x[5]) m5, + max(x[6]) m6, + max(x[7]) m7, + max(x[8]) m8, + max(x[9]) m9, + max(x[10]) m10, + max(x[11]) m11, + max(x[12]) m12, + max(x[13]) m13, + max(x[14]) m14 + from lin_housing_wi +); + +CREATE TABLE lin_housing_wi_scaled AS +SELECT ARRAY[ + x[1]/(SELECT m1 from maxs), + x[2]/(SELECT m2 from maxs), + x[3]/(SELECT m3 from maxs), + x[4]/(SELECT m4 from maxs), + x[5]/(SELECT m5 from maxs), + x[6]/(SELECT m6 from maxs), + x[7]/(SELECT m7 from maxs), + x[8]/(SELECT m8 from maxs), + x[9]/(SELECT m9 from maxs), + x[10]/(SELECT m10 from maxs), + x[11]/(SELECT m11 from maxs), + x[12]/(SELECT m12 from maxs), + x[13]/(SELECT m13 from maxs), + x[14]/(SELECT m14 from maxs)] as x, + id,y +FROM lin_housing_wi; + +DROP TABLE IF EXISTS maxs; +DROP TABLE IF EXISTS mlp_regress; +DROP TABLE IF EXISTS mlp_regress_summary; + + +SELECT setseed(0); +SELECT mlp_regression( + 'lin_housing_wi_scaled', -- Source table + 'mlp_regress', -- Desination table + 'x', -- Input features + 'y', -- Dependent variable + ARRAY[5,5], -- Number of units per layer + 'step_size=0.005, + n_iterations=800, + tolerance=0', + 'sigmoid'); + + +SELECT assert( + loss < 10, + 'MLP: Loss is too high (> 10). Wrong result.' +) FROM mlp_regress; + + +DROP TABLE IF EXISTS mlp_prediction_regress; +SELECT mlp_predict( + 'mlp_regress', + 'lin_housing_wi_scaled', + 'id', + 'mlp_prediction_regress', + 'output'); +SELECT assert( + 0.5*SUM(pow(mlp_prediction_regress.estimated_y-lin_housing_wi_scaled.y,2.0))/506 < 10.0, + 'MLP: Predict MSE is too high (> 10). Wrong result' +) +FROM mlp_prediction_regress JOIN lin_housing_wi_scaled +ON mlp_prediction_regress.id = lin_housing_wi_scaled.id; +DROP TABLE IF EXISTS lin_housing_wi_scaled; http://git-wip-us.apache.org/repos/asf/incubator-madlib/blob/4fcb60ed/src/ports/postgres/modules/utilities/validate_args.py_in ---------------------------------------------------------------------- diff --git a/src/ports/postgres/modules/utilities/validate_args.py_in b/src/ports/postgres/modules/utilities/validate_args.py_in index 532326d..ff2c1aa 100644 --- a/src/ports/postgres/modules/utilities/validate_args.py_in +++ b/src/ports/postgres/modules/utilities/validate_args.py_in @@ -110,7 +110,8 @@ def _get_table_schema_names(tbl, only_first_schema=False): if len(names) == 1: if only_first_schema: # restricted to the first schema in search path - all_schemas = [plpy.execute("SELECT current_schema() AS cs")[0]["cs"]] + all_schemas = [plpy.execute( + "SELECT current_schema() AS cs")[0]["cs"]] else: all_schemas = plpy.execute( "SELECT current_schemas(True) ""AS cs")[0]["cs"] @@ -458,6 +459,23 @@ def scalar_col_has_no_null(tbl, col): # ------------------------------------------------------------------------- +def array_col_dimension(tbl, col): + """ + What is the dimension of this array column + """ + if tbl is None: + plpy.error('Input error: Table name (NULL) is invalid') + if col is None: + plpy.error('Input error: Column name is invalid') + + dim = plpy.execute(""" + SELECT max(array_upper({col}, 1)) AS dim + FROM {tbl} + """.format(col=col, tbl=tbl))[0]["dim"] + return dim +# ------------------------------------------------------------------------ + + def array_col_has_same_dimension(tbl, col): """ Do all array elements of an array column have the same length? @@ -545,19 +563,23 @@ def is_var_valid(tbl, var, order_by=None): def input_tbl_valid(tbl, module, check_empty=True): if tbl is None or tbl.strip() == '': - plpy.error("{module} error: NULL/empty input table name!".format(**locals())) + plpy.error( + "{module} error: NULL/empty input table name!".format(**locals())) if not table_exists(tbl): - plpy.error("{module} error: Input table '{tbl}' does not exist".format(**locals())) + plpy.error( + "{module} error: Input table '{tbl}' does not exist".format(**locals())) if check_empty and table_is_empty(tbl): - plpy.error("{module} error: Input table '{tbl}' is empty!".format(**locals())) + plpy.error( + "{module} error: Input table '{tbl}' is empty!".format(**locals())) # ------------------------------------------------------------------------- def output_tbl_valid(tbl, module): - if tbl is None or tbl.strip() == '': - plpy.error("{module} error: NULL/empty output table name!".format(**locals())) + if tbl is None or tbl.strip().lower() in ['', 'null']: + plpy.error( + "{module} error: NULL/empty output table name!".format(**locals())) if table_exists(tbl, only_first_schema=True): plpy.error("""{module} error: Output table '{tbl}' already exists. @@ -568,14 +590,16 @@ def output_tbl_valid(tbl, module): def cols_in_tbl_valid(tbl, cols, module): for c in cols: if c is None or c.strip() == '': - plpy.error("{module} error: NULL/empty column name!".format(**locals())) + plpy.error( + "{module} error: NULL/empty column name!".format(**locals())) missing_cols = columns_missing_from_table(tbl, cols) # FIXME: still printing just 1 column name for backwards compatibility # this should be changed to print all missing columns if missing_cols: c = missing_cols[0] - plpy.error("{module} error: Column '{c}' does not exist in table '{tbl}'!".format(**locals())) + plpy.error( + "{module} error: Column '{c}' does not exist in table '{tbl}'!".format(**locals())) # ------------------------------------------------------------------------- @@ -585,7 +609,8 @@ def regproc_valid(qualified_name, args_str, module): SELECT '{qualified_name}({args_str})'::regprocedure; """.format(**locals())) except: - plpy.error("""{module} error: Required function "{qualified_name}({args_str})" not found!""".format(**locals())) + plpy.error( + """{module} error: Required function "{qualified_name}({args_str})" not found!""".format(**locals())) # -------------------------------------------------------------------------
