//
// Copyright 2019 Google LLC
//
// 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.
//

// This file defines the summary data format for the count algorithm.

syntax = "proto2";

package differential_privacy;

import "google/protobuf/any.proto";
import "proto/data.proto";

option java_package = "com.google.differentialprivacy";

// Serialized summary data of a subset of the input data, to be merged at a
// later time.
message Summary {
  // The summary data.
  optional google.protobuf.Any data = 2;
}

message CountSummary {
  // Count of the data subset.
  optional int64 count = 1;

  // TODO: Use below fields in C++ library.
  // Count parameters:
  optional double epsilon = 3;
  optional double delta = 4;
  optional MechanismType mechanism_type = 5;
  optional int32 max_partitions_contributed = 6;
  optional int32 max_contributions_per_partition = 7;
}

message BoundedQuantilesSummary {
  // Distribution of the data subset, stored in the form of a quantile tree
  map<int32, int64> quantile_tree = 1;

  // Quantiles parameters:
  optional double epsilon = 2;
  optional double delta = 3;
  optional MechanismType mechanism_type = 4;
  optional double lower = 5;
  optional double upper = 6;
  optional int32 max_partitions_contributed = 7;
  optional int32 max_contributions_per_partition = 8;
  optional int32 tree_height = 9;
  optional int32 branching_factor = 10;
}

message BoundedSumSummary {
  // Partial sum data for the dataset. For automatically set bounds, partial
  // sum values are stored corresponding to each ApproxBounds bin.
  // For manually set bounds, clamped sum will be stored in pos_sum.
  // Currently, used only by C++ library.
  repeated ValueType pos_sum = 1;
  // neg_sum is used only when bounds are determined automatically.
  repeated ValueType neg_sum = 2;

  // ApproxBounds data if available.
  optional ApproxBoundsSummary bounds_summary = 3;

  // partial_sum is used by the Java library to store partial sum.
  // TODO: Use partial_sum in C++ library
  //  when bounds are set manually.
  optional ValueType partial_sum = 4;

  // TODO: Use below fields in C++ library.
  // partial_sum is used by Java library to store sum
  // Sum parameters:
  optional double epsilon = 5;
  optional double delta = 6;
  optional MechanismType mechanism_type = 7;
  optional double lower = 8;
  optional double upper = 9;
  optional int32 max_partitions_contributed = 10;
  optional int32 max_contributions_per_partition = 11;
}

enum MechanismType {
  EMPTY = 0;
  LAPLACE = 1;
  GAUSSIAN = 2;
}

message BoundedMeanSummary {
  // Count of the data subset.
  optional int64 count = 1;

  // Partial sum data for the dataset.
  repeated ValueType pos_sum = 2;
  repeated ValueType neg_sum = 3;

  // ApproxBounds data if available.
  optional ApproxBoundsSummary bounds_summary = 4;

  // These two fields are only used by the Java library (not C++), similarly to
  // pos_sum and count.
  optional BoundedSumSummary sum_summary = 5;
  optional CountSummary count_summary = 6;
}

// Used for BoundedVariance and BoundedStandardDeviation algorithms.
message BoundedVarianceSummary {
  // Count of the dataset.
  optional int64 count = 1;

  // Partial sum data for the dataset. For manually set bounds, the clamped sum
  // will be stored in pos_sum. For automatically set bounds, partial sum values
  // stored corresponding to each ApproxBounds bin.
  repeated ValueType pos_sum = 2;
  repeated ValueType neg_sum = 3;

  // Partial sum of squares for the dataset. For manually set bounds, clamped
  // sum of squares is stored in pos_sum_of_squares.
  repeated double pos_sum_of_squares = 4;
  repeated double neg_sum_of_squares = 5;

  // ApproxBounds data if available.
  optional ApproxBoundsSummary bounds_summary = 6;
}

message Elements {
  repeated string element = 1;
}

message HistogramSummary {
  repeated int64 bin_count = 1;
}

message BinarySearchSummary {
  reserved 1;

  // Store all inputs.
  repeated ValueType input = 2;
}

message ApproxBoundsSummary {
  repeated int64 pos_bin_count = 1;
  repeated int64 neg_bin_count = 2;
}