diff --git a/cython/gtsam/tests/experiments.py b/cython/gtsam/tests/experiments.py
deleted file mode 100644
index db3127a83..000000000
--- a/cython/gtsam/tests/experiments.py
+++ /dev/null
@@ -1,113 +0,0 @@
-"""
-This file is not a real python unittest. It contains small experiments
-to test the wrapper with gtsam_test, a short version of gtsam.h.
-Its name convention is different from other tests so it won't be discovered.
-"""
-from __future__ import print_function
-import gtsam
-import numpy as np
-
-r = gtsam.Rot3()
-print(r)
-print(r.pitch())
-r2 = gtsam.Rot3()
-r3 = r.compose(r2)
-print("r3 pitch:", r3.pitch())
-
-v = np.array([1, 1, 1]) 
-print("v = ", v)
-r4 = r3.retract(v)
-print("r4 pitch:", r4.pitch())
-r4.print_(b'r4: ')
-r3.print_(b"r3: ")
-
-v = r3.localCoordinates(r4)
-print("localCoordinates:", v)
-
-Rmat = np.array([
-    [0.990074, -0.0942928, 0.104218], 
-    [0.104218,  0.990074, -0.0942928], 
-    [-0.0942928, 0.104218, 0.990074]
-    ])
-r5 = gtsam.Rot3(Rmat)
-r5.print_(b"r5: ")
-
-l = gtsam.Rot3.Logmap(r5)
-print("l = ", l)
-
-
-noise = gtsam.noiseModel_Gaussian.Covariance(Rmat)
-noise.print_(b"noise:")
-
-D = np.array([1.,2.,3.])
-diag = gtsam.noiseModel_Diagonal.Variances(D)
-print("diag:", diag)
-diag.print_(b"diag:")
-print("diag R:", diag.R())
-
-p = gtsam.Point3()
-p.print_("p:")
-factor = gtsam.BetweenFactorPoint3(1,2,p, noise)
-factor.print_(b"factor:")
-
-vv = gtsam.VectorValues()
-vv.print_(b"vv:")
-vv.insert(1, np.array([1.,2.,3.]))
-vv.insert(2, np.array([3.,4.]))
-vv.insert(3, np.array([5.,6.,7.,8.]))
-vv.print_(b"vv:")
-
-vv2 = gtsam.VectorValues(vv)
-vv2.insert(4, np.array([4.,2.,1]))
-vv2.print_(b"vv2:")
-vv.print_(b"vv:")
-
-vv.insert(4, np.array([1.,2.,4.]))
-vv.print_(b"vv:")
-vv3 = vv.add(vv2)
-
-vv3.print_(b"vv3:")
-
-values = gtsam.Values()
-values.insert(1, gtsam.Point3())
-values.insert(2, gtsam.Rot3())
-values.print_(b"values:")
-
-factor = gtsam.PriorFactorVector(1, np.array([1.,2.,3.]), diag)
-print("Prior factor vector: ", factor)
-
-
-
-keys = gtsam.KeyVector()
-
-keys.push_back(1)
-keys.push_back(2)
-print('size: ', keys.size())
-print(keys.at(0))
-print(keys.at(1))
-
-noise = gtsam.noiseModel_Isotropic.Precision(2, 3.0)
-noise.print_('noise:')
-print('noise print:', noise)
-f = gtsam.JacobianFactor(7, np.ones([2,2]), model=noise,  b=np.ones(2))
-print('JacobianFactor(7):\n', f)
-print("A = ", f.getA())
-print("b = ", f.getb())
-
-f = gtsam.JacobianFactor(np.ones(2))
-f.print_('jacoboian b_in:')
-
-
-print("JacobianFactor initalized with b_in:", f)
-
-diag = gtsam.noiseModel_Diagonal.Sigmas(np.array([1.,2.,3.]))
-fv = gtsam.PriorFactorVector(1, np.array([4.,5.,6.]), diag)
-print("priorfactorvector: ", fv)
-
-print("base noise: ", fv.get_noiseModel())
-print("casted to gaussian2: ", gtsam.dynamic_cast_noiseModel_Diagonal_noiseModel_Base(fv.get_noiseModel()))
-
-X = gtsam.symbol(65, 19)
-print(X)
-print(gtsam.symbolChr(X))
-print(gtsam.symbolIndex(X))