{ "arguments": { "data": { "type_value": "Array" }, "candidates": { "type_value": "Jagged", "default_python": "None", "default_rust": "None", "description": "Set from which the Exponential mechanism will return an element." } }, "id": "DPQuantile", "name": "dp_quantile", "options": { "alpha": { "type_proto": "double", "type_rust": "f64", "description": "Desired quantiles, defined on `[0,1]`." }, "mechanism": { "type_proto": "string", "type_rust": "String", "default_python": "'Laplace'", "default_rust": "String::from(\"Laplace\")", "description": "Privatizing mechanism to use." }, "privacy_usage": { "type_proto": "repeated PrivacyUsage", "type_rust": "Vec", "default_python": "None", "description": "Object describing the type and amount of privacy to be used for the mechanism release." }, "interpolation": { "type_proto": "string", "type_rust": "String", "default_python": "\"midpoint\"", "default_rust": "String::from(\"midpoint\")", "description": "Interpolation strategy. One of [`lower`, `upper`, `midpoint`, `nearest`, `linear`]" } }, "return": { "type_value": "Array", "description": "Differentially private estimates of the median of each column of the data." }, "description": "Returns differentially private estimates of the median of each column of the data.", "proto_id": 16 }