diff --git a/README.md b/README.md
index a668644..a8e3170 100644
--- a/README.md
+++ b/README.md
@@ -9,6 +9,7 @@
 - [Documentation](#documentation)
   * [`simulateRIR`](#simulaterir)
   * [`simulateTrajectory`](#simulatetrajectory)
+  * [`activateMixedPrecision`](#activateMixedPrecision)
   * [`beta_SabineEstimation`](#beta_sabineestimation)
   * [`att2t_SabineEstimator`](#att2t_sabineestimator)
   * [`t2n`](#t2n)
@@ -101,6 +102,15 @@ Filter an audio signal by the RIRs of a motion trajectory recorded with a microp
 *2D ndarray*
 	Matrix with the signals captured by each microphone in each column.
 
+### `activateMixedPrecision`
+
+Activate the mixed precision mode, only for Pascal GPU architecture or superior.
+
+#### Parameters
+
+* **activate** : *bool, optional.*
+        True for activate and Flase for deactivate. True by default.
+        
 ### `beta_SabineEstimation`
 
 Estimation of the reflection coefficients needed to have the desired reverberation time.
diff --git a/examples/example.py b/examples/example.py
index a66232b..8b7a297 100755
--- a/examples/example.py
+++ b/examples/example.py
@@ -9,7 +9,7 @@
 from math import ceil
 
 import gpuRIR
-gpuRIR.activate_mixed_precision(False)
+gpuRIR.activateMixedPrecision(False)
 
 room_sz = [3,3,2.5]  # Size of the room [m]
 nb_src = 2  # Number of sources
@@ -32,3 +32,4 @@
 
 t = np.arange(int(ceil(Tmax * fs))) / fs
 plt.plot(t, RIRs.reshape(nb_src*nb_rcv, -1).transpose())
+plt.show()
\ No newline at end of file
diff --git a/examples/simulate_trajectory.py b/examples/simulate_trajectory.py
index fee8e72..7977d4e 100644
--- a/examples/simulate_trajectory.py
+++ b/examples/simulate_trajectory.py
@@ -9,6 +9,7 @@
 from scipy.io import wavfile
 
 import gpuRIR
+gpuRIR.activateMixedPrecision(False)
 
 fs, source_signal = wavfile.read('source_signal.wav')
 
@@ -33,3 +34,4 @@
 filtered_signal = gpuRIR.simulateTrajectory(source_signal, RIRs)
 wavfile.write('filtered_signal.wav', fs, filtered_signal)
 plt.plot(filtered_signal)
+plt.show()
diff --git a/examples/time_vs_T60.py b/examples/time_vs_T60.py
index f5cb779..5c1eaa7 100644
--- a/examples/time_vs_T60.py
+++ b/examples/time_vs_T60.py
@@ -9,7 +9,7 @@
 import time
 
 import gpuRIR
-gpuRIR.activate_mixed_precision(False)
+gpuRIR.activateMixedPrecision(False)
 
 T60_vec = np.arange(0.1, 2.2, 0.2) # Reverberation times to measure
 nb_test_per_point = 10 # Number of simulations per T60 to average the runtime
@@ -46,4 +46,5 @@
 
 plt.semilogy(T60_vec, times)
 plt.ylabel("time [s]")
-plt.xlabel("T60 [s]")
\ No newline at end of file
+plt.xlabel("T60 [s]")
+plt.show()
\ No newline at end of file
diff --git a/examples/time_vs_nbRIRs.py b/examples/time_vs_nbRIRs.py
index 36ef471..7b950ab 100644
--- a/examples/time_vs_nbRIRs.py
+++ b/examples/time_vs_nbRIRs.py
@@ -9,7 +9,7 @@
 import time
 
 import gpuRIR
-gpuRIR.activate_mixed_precision(False)
+gpuRIR.activateMixedPrecision(False)
 
 nb_src_vec = np.concatenate([2**np.arange(12), [4094]]) # Number of RIRs to measure
 nb_test_per_point = 10 # Number of simulations per T60 to average the runtime
@@ -47,3 +47,4 @@
 plt.loglog(nb_src_vec, times)
 plt.ylabel("time [s]")
 plt.xlabel("number of RIRs")
+plt.show()
diff --git a/gpuRIR/__init__.py b/gpuRIR/__init__.py
index faf538c..cc5a2da 100644
--- a/gpuRIR/__init__.py
+++ b/gpuRIR/__init__.py
@@ -201,7 +201,7 @@ def simulateTrajectory(source_signal, RIRs, timestamps=None, fs=None):
 		
 	return filtered_signal
 
-def activate_mixed_precision(activate=True):
+def activateMixedPrecision(activate=True):
 	''' Activate the mixed precision mode, only for Pascal GPU architecture or superior.
 
 	Parameters
diff --git a/src/gpuRIR_cuda.cu b/src/gpuRIR_cuda.cu
index 7b4fe29..64d30c9 100644
--- a/src/gpuRIR_cuda.cu
+++ b/src/gpuRIR_cuda.cu
@@ -21,9 +21,6 @@ static const int nThreadsISM_x = 4;
 static const int nThreadsISM_y = 4;
 static const int nThreadsISM_z = 4;
 
-// Time vector generation
-static const int nThreadsTime = 128;
-
 // RIR computation
 static const int initialReductionMin = 512;
 static const int nThreadsGen_t = 32;
@@ -46,6 +43,11 @@ static const int nThreadsConv_x = 256;
 static const int nThreadsConv_y = 1;
 static const int nThreadsConv_z = 1;
 
+#if __CUDA_ARCH__ >= 530
+#define h2zeros __float2half2_rn(0.0)
+#define h2ones __float2half2_rn(1.0)
+#define h2pi __float2half2_rn(PI)
+#endif
 
 // To hide the cuRAND generator in the header and don't need to include the cuda headers there
 struct cuRandGeneratorWrapper_t
@@ -58,13 +60,6 @@ cuRandGeneratorWrapper_t gpuRIR_cuda::cuRandGenWrap;
 int cuda_arch;
 
 
-#if __CUDA_ARCH__ >= 530
-#define h2zeros __float2half2_rn(0.0)
-#define h2ones __float2half2_rn(1.0)
-#define h2pi __float2half2_rn(PI)
-#endif
-
-
 /***************************/
 /* Auxiliar host functions */
 /***************************/
@@ -89,7 +84,7 @@ inline void gpuAssert(curandStatus_t code, const char *file, int line, bool abor
 
 #define gpuErrchk(ans) { gpuAssert((ans), __FILE__, __LINE__); }
 inline void gpuAssert(cufftResult_t code, const char *file, int line, bool abort=true) {
-   if (code != CURAND_STATUS_SUCCESS) 
+   if (code != CUFFT_SUCCESS) 
    {
       fprintf(stderr,"GPUassert: %s %s %d\n", code, file, line);
       if (abort) exit(code);
@@ -146,6 +141,7 @@ __device__ __forceinline__ scalar_t mic_directivity(scalar_t doaVec[3], scalar_t
 		case DIR_HYPCARD:	return 0.25f + 0.75f*cosTheta;
 		case DIR_SUBCARD: 	return 0.75f + 0.25f*cosTheta;
 		case DIR_BIDIR: 	return cosTheta;
+		default: printf("Invalid microphone pattern"); return 0.0f;
 	}
 }
 
@@ -175,26 +171,6 @@ __device__ __forceinline__ half2 h2abs(half2 x) {
 	return *reinterpret_cast<half2*>( &i );
 }
 
-__device__ __forceinline__ half2 my_h2sin(half2 x) {
-	return __floats2half2_rn(sinf(__low2float(x)), sinf(__high2float(x)));
-}
-
-__device__ __forceinline__ half2 my_h2cos(half2 x) {
-	return __floats2half2_rn(cosf(__low2float(x)), cosf(__high2float(x)));
-}
-
-__device__ __forceinline__ half2 my_h2cospi(half2 x) {
-	// It is always on [-0.5, 0.5], so we do not need argument reduction
-	
-	// cos(pi*x) polinomial approximation for x in [-0.5,0.5]
-	half2 x2 = __hmul2(x, x);
-	half2 c = __float2half2_rn(-1.229339658587166);
-	c = __hfma2(x2, c, __float2half2_rn(+4.043619929856572f));
-	c = __hfma2(x2, c, __float2half2_rn(-4.934120365987677f));
-	c = __hfma2(x2, c, __float2half2_rn(+0.999995282317910));
-	
-	return c;
-}
 __device__ __forceinline__ half2 my_h2sinpi(half2 x) {
 	// Argument reduction to [-0.5, 0.5]
 	half2 i = h2rint(x);
@@ -216,32 +192,35 @@ __device__ __forceinline__ half2 my_h2sinpi(half2 x) {
 	return s;
 }
 
+__device__ __forceinline__ half2 my_h2cospi(half2 x) {
+	// It is always on [-0.5, 0.5], so we do not need argument reduction
+	
+	// cos(pi*x) polinomial approximation for x in [-0.5,0.5]
+	half2 x2 = __hmul2(x, x);
+	half2 c = __float2half2_rn(-1.229339658587166f);
+	c = __hfma2(x2, c, __float2half2_rn(+4.043619929856572f));
+	c = __hfma2(x2, c, __float2half2_rn(-4.934120365987677f));
+	c = __hfma2(x2, c, __float2half2_rn(+0.999995282317910f));
+	
+	return c;
+}
+
 __device__ __forceinline__ half2 hanning_window_mp(half2 t, half2 Tw_inv) {	
 	half2 c = my_h2cospi(__hmul2(Tw_inv, t));
 	return __hmul2(c, c);
-	// return __hmul2(__hadd2(h2ones, h2cos(__hmul2(PI_Tw_2, t))), __float2half2_rn(0.5f));
 }
 
 __device__ __forceinline__ half2 my_h2sinc(half2 x) {
-	// x = __hmul2(h2pi, x);
 	x = __hfma2(__heq2(x, h2zeros), __float2half2_rn(1e-7f), x);
 	return __h2div(my_h2sinpi(x), __hmul2(h2pi, x));
 	
 }
 
 __device__ __forceinline__ half2 image_sample_mp(half2 amp, scalar_t tau, scalar_t t1, scalar_t t2, half2 Tw_2, half2 Tw_inv) {
-	half2 t_tau = __floats2half2_rn(t1-tau, t2-tau);  // __hsub2(t, tau);
+	half2 t_tau = __floats2half2_rn(t1-tau, t2-tau);
 	if (__hble2(h2abs(t_tau), Tw_2)) {
 		return __hmul2(hanning_window_mp(t_tau, Tw_inv), __hmul2(amp, my_h2sinc( t_tau )));
 	} else return h2zeros;
-	
-	// half2 t_tau = __floats2half2_rn(t1-tau, t2-tau);  // __hsub2(t, tau);
-	// if (__hble2(h2abs(t_tau), __float2half2_rn(8e-3f/2))) {
-		// half2 FsPI = __hmul2( __float2half2_rn(Fs), __float2half2_rn(PI));
-		// return my_h2sinc( __hmul2(t_tau, FsPI) );
-	// } else return h2zeros;
-	
-	// return my_h2sin(amp);
 }
 
 #endif
@@ -357,11 +336,6 @@ __global__ void calcAmpTau_kernel(scalar_t* g_amp /*[M_src]M_rcv][nb_img_x][nb_i
 	}
 }
 
-__global__ void generateTime_kernel(scalar_t* t, scalar_t Fs, int nSamples) {
-	int sample = blockIdx.x * blockDim.x + threadIdx.x;
-	if (sample<nSamples) t[sample] = sample/Fs;
-}
-
 __global__ void generateRIR_kernel(scalar_t* initialRIR, scalar_t* amp, scalar_t* tau, int T, int M, int N, int iniRIR_N, int ini_red, scalar_t Tw) {
 	int t = blockIdx.x * blockDim.x + threadIdx.x;
 	int m = blockIdx.y * blockDim.y + threadIdx.y;
@@ -371,7 +345,7 @@ __global__ void generateRIR_kernel(scalar_t* initialRIR, scalar_t* amp, scalar_t
 	if (m<M && t<T) {
 		scalar_t loc_sum = 0;
 		for (int n=n_ini; n<n_max; n++) {
-			loc_sum += image_sample(amp[m*N+n], tau[m*N+n], /* loc_tim */ t, Tw);
+			loc_sum += image_sample(amp[m*N+n], tau[m*N+n], t, Tw);
 		}
 		initialRIR[m*T*iniRIR_N + t*iniRIR_N + blockIdx.z] = loc_sum;
 	}
@@ -928,12 +902,14 @@ scalar_t* gpuRIR_cuda::cuda_convolutions(scalar_t* source_segments, int M_src, i
 }
 
 gpuRIR_cuda::gpuRIR_cuda(bool mPrecision) {
-	activate_mixed_precision(mPrecision);
-
+	// Get CUDA architecture
 	cudaDeviceProp prop;
     cudaGetDeviceProperties(&prop, 0);
 	cuda_arch = prop.major*100 + prop.minor*10;
 
+	// Activate mixed precision if selected
+	activate_mixed_precision(mPrecision);
+	
 	// Initiate CUDA runtime API
 	scalar_t* memPtr_warmup;
 	gpuErrchk( cudaMalloc(&memPtr_warmup, 1*sizeof(scalar_t)) );