From c4b45750de459e284e84a399232781eebd08de54 Mon Sep 17 00:00:00 2001
From: Vadym Doroshenko <dvadym@google.com>
Date: Sun, 5 Feb 2023 19:56:18 +0100
Subject: [PATCH] Add std

---
 src/bindings/PyDP/mechanisms/mechanism.cpp    | 26 +++++++++++++------
 tests/algorithms/test_numerical_mechanisms.py | 13 ++++++++++
 2 files changed, 31 insertions(+), 8 deletions(-)

diff --git a/src/bindings/PyDP/mechanisms/mechanism.cpp b/src/bindings/PyDP/mechanisms/mechanism.cpp
index 73583d17..6bc14989 100644
--- a/src/bindings/PyDP/mechanisms/mechanism.cpp
+++ b/src/bindings/PyDP/mechanisms/mechanism.cpp
@@ -117,6 +117,13 @@ class GaussianMechanismBinder {
     return downcast_unique_ptr<dp::GaussianMechanism, dp::NumericalMechanism>(
         builder.Build().value());
   };
+  
+  static std::unique_ptr<dp::GaussianMechanism> build_from_std(double std) {
+    dp::GaussianMechanism::Builder builder;
+    builder.SetStandardDeviation(std);
+    return downcast_unique_ptr<dp::GaussianMechanism, dp::NumericalMechanism>(
+        builder.Build().value());
+  };
 
   static void DeclareIn(py::module& m) {
     py::class_<dp::GaussianMechanism, dp::NumericalMechanism> gaus_mech(
@@ -127,17 +134,20 @@ class GaussianMechanismBinder {
                return build(epsilon, delta, l2_sensitivity);
              }),
              py::arg("epsilon"), py::arg("delta"), py::arg("sensitivity") = 1.0)
+        .def_static("create_from_standard_deviation", [](double std) {
+               return build_from_std(std);
+             },
+             py::arg("std"),
+            R"pbdoc(
+              Creates Gaussian mechanism from the given standard deviation.
+            )pbdoc")
         .def_property_readonly("delta", &dp::GaussianMechanism::GetDelta,
                                "The 𝛿 of the Gaussian mechanism.")
-        .def_property_readonly(
-            "std",
-            [](const dp::GaussianMechanism& self) {
-              return dp::GaussianMechanism::CalculateStddev(
-                  self.GetEpsilon(), self.GetDelta(), self.GetL2Sensitivity());
-            },
+         .def_property_readonly(
+            "std", [](dp::GaussianMechanism& mechanism) { return mechanism.CalculateStddev(); },
             R"pbdoc( 
-              The standard deviation parameter of the 
-              Gaussian mechanism underlying distribution. 
+              The standard deviation of the Gaussian mechanism underlying 
+              distribution. 
             )pbdoc")
         .def_property_readonly("l2_sensitivity",
                                &dp::GaussianMechanism::GetL2Sensitivity,
diff --git a/tests/algorithms/test_numerical_mechanisms.py b/tests/algorithms/test_numerical_mechanisms.py
index 137a8aa4..2f6d0103 100644
--- a/tests/algorithms/test_numerical_mechanisms.py
+++ b/tests/algorithms/test_numerical_mechanisms.py
@@ -82,3 +82,16 @@ def test_gaussian_mechanism():
     assert_almost_eq(lower_bound, interval.lower_bound)
     assert_almost_eq(upper_bound, interval.upper_bound)
     assert conf_level == interval.confidence_level
+
+
+def test_gaussian_mechanism_create_from_std():
+    std = 2.0
+    gaussian = num_mech.GaussianMechanism.create_from_standard_deviation(std)
+    assert gaussian.std == 2
+    value = gaussian.add_noise(100)
+    assert 80 <= value <= 120 # in 10*sigma
+    assert type(value) is int
+    value = gaussian.add_noise(200.0)
+    assert type(value) is float
+    assert 180 <= value <= 220 # in 10*sigma
+