started addMethods

Author: jpivarski

histogrammar/sparksql.py

@@ -0,0 +1,72 @@
+#!/usr/bin/env python
+
+# Copyright 2016 DIANA-HEP
+# 
+# Licensed 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.
+
+import histogrammar.primitives.average
+import histogrammar.primitives.bag
+import histogrammar.primitives.bin
+import histogrammar.primitives.categorize
+import histogrammar.primitives.centrallybin
+import histogrammar.primitives.collection
+import histogrammar.primitives.count
+import histogrammar.primitives.deviate
+import histogrammar.primitives.fraction
+import histogrammar.primitives.irregularlybin
+import histogrammar.primitives.minmax
+import histogrammar.primitives.select
+import histogrammar.primitives.sparselybin
+import histogrammar.primitives.stack
+import histogrammar.primitives.sum
+
+def addMethods(df):
+    def histogrammar(self, h):
+        converter = self.df._sc._jvm.org.dianahep.histogrammar.sparksql.pyspark.AggregatorConverter()
+        agg = h._sparksql(self.df._sc._jvm, converter)
+        result = converter.histogrammar(self.df._jdf, agg)
+        return Factory.fromJson(jsonlib.loads(result.toJsonString()))
+
+    def Average(self, quantity):
+        return self.histogrammar(histogrammar.primitives.average.Average(quantity))
+
+    def Bag(self, quantity, range):
+        return self.histogrammar(histogrammar.primitives.bag.Bag(quantity, range))
+
+    # def Bin(self, num, low, high, quantity, value=histogrammar.primitives.count.Count(), underflow=histogrammar.primitives.count.Count(), overflow=histogrammar.primitives.count.Count(), nanflow=histogrammar.primitives.count.Count()):
+    #     return self.histogrammar()
+
+
+
+
+    # df.histogrammar    = types.MethodType(histogrammar, df)
+
+    # hg.Average         = types.MethodType(Average        , df)
+    # hg.Bag             = types.MethodType(Bag            , df)
+    # hg.Bin             = types.MethodType(Bin            , df)
+    # hg.Categorize      = types.MethodType(Categorize     , df)
+    # hg.CentrallyBin    = types.MethodType(CentrallyBin   , df)
+    # hg.Label           = types.MethodType(Label          , df)
+    # hg.UntypedLabel    = types.MethodType(UntypedLabel   , df)
+    # hg.Index           = types.MethodType(Index          , df)
+    # hg.Branch          = types.MethodType(Branch         , df)
+    # hg.Count           = types.MethodType(Count          , df)
+    # hg.Deviate         = types.MethodType(Deviate        , df)
+    # hg.Fraction        = types.MethodType(Fraction       , df)
+    # hg.IrregularlyBin  = types.MethodType(IrregularlyBin , df)
+    # hg.Minimize        = types.MethodType(Minimize       , df)
+    # hg.Maximize        = types.MethodType(Maximize       , df)
+    # hg.Select          = types.MethodType(Select         , df)
+    # hg.SparselyBin     = types.MethodType(SparselyBin    , df)
+    # hg.Stack           = types.MethodType(Stack          , df)
+    # hg.Sum             = types.MethodType(Sum            , df)