Merge pull request rmcantin#11 from ericfrederich/python3

work with Python 3
sigopt · Mar 29, 2017 · e4c416e · e4c416e
2 parents 2dadf53 + e82aa17
commit e4c416e
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Showing 9 changed files with 3,555 additions and 2,604 deletions.
diff --git a/CMakeLists.txt b/CMakeLists.txt
@@ -223,7 +223,7 @@ IF(BAYESOPT_PYTHON_INTERFACE)
 
   #Find where to install Python libs
   execute_process ( COMMAND 
-         python -c "from distutils.sysconfig import get_python_lib; print get_python_lib()" 
+         python -c "from distutils.sysconfig import get_python_lib; print(get_python_lib())"
          OUTPUT_VARIABLE PYTHON_SITE_PACKAGES OUTPUT_STRIP_TRAILING_WHITESPACE)
 
   INSTALL(

diff --git a/cmake/PythonMagic.cmake b/cmake/PythonMagic.cmake
@@ -13,16 +13,16 @@ endif()
 if( PYTHON_EXECUTABLE )
   # architecture independent
   execute_process(
-    COMMAND ${PYTHON_EXECUTABLE} -c "from distutils.sysconfig import get_python_lib; print get_python_lib(0)"
+    COMMAND ${PYTHON_EXECUTABLE} -c "from distutils.sysconfig import get_python_lib; print(get_python_lib(0))"
     OUTPUT_VARIABLE _python_sitepackage OUTPUT_STRIP_TRAILING_WHITESPACE
     RESULT_VARIABLE _python_failed0)
   # architexture dependent
   execute_process(
-    COMMAND ${PYTHON_EXECUTABLE} -c "from distutils.sysconfig import get_python_lib; print get_python_lib(1)"
+    COMMAND ${PYTHON_EXECUTABLE} -c "from distutils.sysconfig import get_python_lib; print(get_python_lib(1))"
     OUTPUT_VARIABLE _python_distpackage OUTPUT_STRIP_TRAILING_WHITESPACE
     RESULT_VARIABLE _python_failed1)
 #  execute_process(
-#    COMMAND ${PYTHON_EXECUTABLE} -c "from distutils.sysconfig import get_python_lib; from os.path import relpath; print relpath(get_python_lib(1,prefix='${CMAKE_INSTALL_PREFIX}'),'${CMAKE_INSTALL_PREFIX}')"
+#    COMMAND ${PYTHON_EXECUTABLE} -c "from distutils.sysconfig import get_python_lib; from os.path import relpath; print(relpath(get_python_lib(1,prefix='${CMAKE_INSTALL_PREFIX}'),'${CMAKE_INSTALL_PREFIX}'))"
 #    OUTPUT_VARIABLE OPENRAVE_PYTHON_INSTALL_DIR OUTPUT_STRIP_TRAILING_WHITESPACE
 #    RESULT_VARIABLE _python_failed2)
 

diff --git a/python/bayesopt.cpp b/python/bayesopt.cpp
diff --git a/python/bayesopt.pyx b/python/bayesopt.pyx
@@ -121,6 +121,9 @@ cdef extern from "bayesopt/bayesopt.h":
 ###########################################################################
 cdef bopt_params dict2structparams(dict dparams):
 
+    # be nice and allow Python 3 code to pass strings or bytes
+    dparams = {k: v.encode('latin-1') if isinstance(v, str) else v for k, v in dparams.items()}
+
     params = initialize_parameters_to_default()
 
     params.n_iterations = dparams.get('n_iterations',params.n_iterations)

diff --git a/python/bayesoptmodule.py b/python/bayesoptmodule.py
@@ -177,4 +177,4 @@ def optimize(self):
 if __name__ == "__main__":
     BO = BayesOptContinuous()
     __value__, __x__, __err__ = BO.optimize()
-    print "Result", __x__
+    print("Result", __x__)
diff --git a/python/demo_cam.py b/python/demo_cam.py
@@ -19,11 +19,16 @@
 #    along with BayesOpt.  If not, see <http://www.gnu.org/licenses/>.
 # ------------------------------------------------------------------------
 
+import sys
 from SimpleCV import Camera
 import numpy as np
 import bayesopt
 from time import sleep
 
+# Python3 compat
+if sys.version_info[0] == 3:
+    raw_input = input
+
 # Initialize the camera
 cam = Camera()
 cost = np.zeros(256)
@@ -50,7 +55,7 @@ def costImage(i):
                                                   valid_values, params)
 
 x_out = int(x_out)
-print x_out
+print(x_out)
 img1 = img.binarize(x_out)
 
 img1 = img.sideBySide(img1).sideBySide(img2)

diff --git a/python/demo_dimscaling.py b/python/demo_dimscaling.py
@@ -57,9 +57,9 @@ def func(x):
 
 mvalue, x_out, error = bayesopt.optimize(func, dim, lb, ub, params)
 
-print "Result", mvalue, x_out
+print("Result", mvalue, x_out)
 
-print "Global optimal", 0, np.arange(1,1+dim)
+print("Global optimal", 0, np.arange(1,1+dim))
 
-print "Y Gap", mvalue
-print "X Gap", math.sqrt(mvalue*dim)
+print("Y Gap", mvalue)
+print("X Gap", math.sqrt(mvalue*dim))
diff --git a/python/demo_distance.py b/python/demo_distance.py
@@ -49,7 +49,7 @@ def evaluateSample(self,Xin):
 params['crit_name'] = "cSum(cEI,cDistance)"
 params['crit_params'] = [1, 0.5]
 params['kernel_name'] = "kMaternISO3"
-print "Callback implementation"
+print("Callback implementation")
 
 n = 2                     # n dimensions
 lb = np.zeros((n,))
@@ -59,11 +59,11 @@ def evaluateSample(self,Xin):
 
 mvalue, x_out, error = bayesopt.optimize(testfunc, n, lb, ub, params)
 
-print "Result", x_out
-print "Seconds", clock() - start
+print("Result", x_out)
+print("Seconds", clock() - start)
 
 
-print "OO implementation"
+print("OO implementation")
 bo_test = BayesOptTest(n)
 bo_test.parameters = params
 bo_test.lower_bound = lb
@@ -72,18 +72,18 @@ def evaluateSample(self,Xin):
 start = clock()
 mvalue, x_out, error = bo_test.optimize()
 
-print "Result", x_out
-print "Seconds", clock() - start
+print("Result", x_out)
+print("Seconds", clock() - start)
 
 
-print "Callback discrete implementation"
+print("Callback discrete implementation")
 x_set = np.random.rand(100,n)
 start = clock()
 
 mvalue, x_out, error = bayesopt.optimize_discrete(testfunc, x_set, params)
 
-print "Result", x_out
-print "Seconds", clock() - start
+print("Result", x_out)
+print("Seconds", clock() - start)
 
 value = np.array([testfunc(i) for i in x_set])
-print "Optimun", x_set[value.argmin()]
+print("Optimun", x_set[value.argmin()])
diff --git a/python/demo_quad.py b/python/demo_quad.py
@@ -25,6 +25,10 @@
 
 from time import clock
 
+# Python3 compat
+if sys.version_info[0] == 3:
+    raw_input = input
+
 # Function for testing.
 def testfunc(Xin):
     total = 5.0
@@ -48,7 +52,7 @@ def evaluateSample(self,Xin):
 params['n_iter_relearn'] = 5
 params['n_init_samples'] = 2
 
-print "Callback implementation"
+print("Callback implementation")
 
 n = 5                     # n dimensions
 lb = np.zeros((n,))
@@ -57,11 +61,11 @@ def evaluateSample(self,Xin):
 start = clock()
 mvalue, x_out, error = bayesopt.optimize(testfunc, n, lb, ub, params)
 
-print "Result", mvalue, "at", x_out
-print "Running time:", clock() - start, "seconds"
+print("Result", mvalue, "at", x_out)
+print("Running time:", clock() - start, "seconds")
 raw_input('Press INTRO to continue')
 
-print "OO implementation"
+print("OO implementation")
 bo_test = BayesOptTest(n)
 bo_test.parameters = params
 bo_test.lower_bound = lb
@@ -70,18 +74,18 @@ def evaluateSample(self,Xin):
 start = clock()
 mvalue, x_out, error = bo_test.optimize()
 
-print "Result", mvalue, "at", x_out
-print "Running time:", clock() - start, "seconds"
+print("Result", mvalue, "at", x_out)
+print("Running time:", clock() - start, "seconds")
 raw_input('Press INTRO to continue')
 
-print "Callback discrete implementation"
+print("Callback discrete implementation")
 x_set = np.random.rand(100,n)
 start = clock()
 
 mvalue, x_out, error = bayesopt.optimize_discrete(testfunc, x_set, params)
 
-print "Result", mvalue, "at", x_out
-print "Running time:", clock() - start, "seconds"
+print("Result", mvalue, "at", x_out)
+print("Running time:", clock() - start, "seconds")
 
 value = np.array([testfunc(i) for i in x_set])
-print "Optimum", value.min(), "at", x_set[value.argmin()]
+print("Optimum", value.min(), "at", x_set[value.argmin()])