1
  2
  3
  4
  5
  6
  7
  8
  9
 10
 11
 12
 13
 14
 15
 16
 17
 18
 19
 20
 21
 22
 23
 24
 25
 26
 27
 28
 29
 30
 31
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
use indexmap::map::IndexMap;

use crate::{base, proto};
use crate::base::{Array, IndexKey, NodeProperties, Value};
use crate::components::{Expandable, Report};
use crate::errors::*;
use crate::utilities::{array::get_ith_column, prepend};
use crate::utilities::json::{AlgorithmInfo, JSONRelease, privacy_usage_to_json, value_to_json};
use crate::utilities::privacy::spread_privacy_usage;

impl Expandable for proto::DpVariance {
    fn expand_component(
        &self,
        privacy_definition: &Option<proto::PrivacyDefinition>,
        component: &proto::Component,
        _public_arguments: &IndexMap<IndexKey, &Value>,
        _properties: &base::NodeProperties,
        component_id: u32,
        mut maximum_id: u32,
    ) -> Result<base::ComponentExpansion> {

        let mut expansion = base::ComponentExpansion::default();


        let argument_ids = component.arguments();

        // variance
        maximum_id += 1;
        let id_variance = maximum_id;
        expansion.computation_graph.insert(id_variance, proto::Component {
            arguments: Some(proto::ArgumentNodeIds::new(indexmap![
                "data".into() => *argument_ids.get(&IndexKey::from("data"))
                    .ok_or_else(|| Error::from("data must be provided as an argument"))?])),
            variant: Some(proto::component::Variant::Variance(proto::Variance {
                finite_sample_correction: self.finite_sample_correction
            })),
            omit: true,
            submission: component.submission,
        });
        expansion.traversal.push(id_variance);

        // noising
        let mechanism = if self.mechanism.to_lowercase().as_str() == "automatic" {
            let privacy_definition = privacy_definition.as_ref()
                .ok_or_else(|| Error::from("privacy_definition must be known"))?;
            if privacy_definition.protect_floating_point
            { "snapping" } else { "laplace" }.to_string()
        } else { self.mechanism.to_lowercase() };

        let mut arguments = indexmap!["data".into() => id_variance];
        let variant = Some(match mechanism.as_str() {
            "laplace" => proto::component::Variant::LaplaceMechanism(proto::LaplaceMechanism {
                privacy_usage: self.privacy_usage.clone()
            }),
            "gaussian" => proto::component::Variant::GaussianMechanism(proto::GaussianMechanism {
                privacy_usage: self.privacy_usage.clone(),
                analytic: false
            }),
            "analyticgaussian" => proto::component::Variant::GaussianMechanism(proto::GaussianMechanism {
                privacy_usage: self.privacy_usage.clone(),
                analytic: true
            }),
            "snapping" => {
                argument_ids.get::<IndexKey>(&"lower".into())
                    .map(|lower| arguments.insert("lower".into(), *lower));
                argument_ids.get::<IndexKey>(&"upper".into())
                    .map(|upper| arguments.insert("upper".into(), *upper));

                proto::component::Variant::SnappingMechanism(proto::SnappingMechanism {
                    privacy_usage: self.privacy_usage.clone()
                })
            },
            _ => bail!("Unexpected invalid token {:?}", self.mechanism.as_str()),
        });

        expansion.computation_graph.insert(component_id, proto::Component {
            arguments: Some(proto::ArgumentNodeIds::new(arguments)),
            variant,
            omit: component.omit,
            submission: component.submission,
        });

        Ok(expansion)
    }
}

impl Report for proto::DpVariance {
    fn summarize(
        &self,
        node_id: u32,
        component: &proto::Component,
        _public_arguments: IndexMap<base::IndexKey, &Value>,
        properties: NodeProperties,
        release: &Value,
        variable_names: Option<&Vec<base::IndexKey>>,
    ) -> Result<Option<Vec<JSONRelease>>> {
        let data_property = properties.get(&IndexKey::from("data"))
            .ok_or("data: missing")?.array()
            .map_err(prepend("data:"))?.clone();

        let mut releases = Vec::new();

        let minimums = data_property.lower_float()?;
        let maximums = data_property.upper_float()?;
        let num_records = data_property.num_records()?;

        let num_columns = data_property.num_columns()?;
        let privacy_usages = spread_privacy_usage(&self.privacy_usage, num_columns as usize)?;

        for column_number in 0..(num_columns as usize) {
            let variable_name = variable_names
                .and_then(|names| names.get(column_number)).cloned()
                .unwrap_or_else(|| "[Unknown]".into());

            releases.push(JSONRelease {
                description: "DP release information".to_string(),
                statistic: "DPVariance".to_string(),
                variables: serde_json::json!(variable_name.to_string()),
                release_info: match release.ref_array()? {
                    Array::Float(v) => value_to_json(&get_ith_column(v, column_number)?.into())?,
                    Array::Int(v) => value_to_json(&get_ith_column(v, column_number)?.into())?,
                    _ => return Err("maximum must be numeric".into())
                },
                privacy_loss: privacy_usage_to_json(&privacy_usages[column_number].clone()),
                accuracy: None,
                submission: component.submission,
                node_id,
                postprocess: false,
                algorithm_info: AlgorithmInfo {
                    name: "".to_string(),
                    cite: "".to_string(),
                    mechanism: self.mechanism.clone(),
                    argument: serde_json::json!({
                            "n": num_records,
                            "constraint": {
                                "lowerbound": minimums[column_number],
                                "upperbound": maximums[column_number]
                            }
                        }),
                },
            });
        }
        Ok(Some(releases))
    }
}