fix merge conflict

README.md

@@ -21,8 +21,7 @@ Generators, processors, and backends read their configuration from a shared json
 implementations don't have a common syntax yet.
 
 Here is a diagram of the framework:
-
-(https://github.com/rkube/delta/blob/master/Streaming%20analysis%20architecture.png)
+![Delta Architecture](https://github.com/rkube/delta/blob/master/doc/delta_architecture.png "Delta Architecture")
 
 # Implemented Workflows
 
@@ -195,4 +194,4 @@ for change in cursor():
     print("")
 ```
 
-Visualizers are implemented separately, see f.ex. the web-based 
+Visualizers are implemented separately, see f.ex. the web-based dashboard: [https://github.com/rkube/dashboard_v2](https://github.com/rkube/dashboard_v2)

analysis/lib/kernels.c

@@ -0,0 +1,111 @@
+#include <stdio.h>
+#include <complex.h>
+#include <math.h>
+
+#include "kernels.h"
+
+
+void kernel_coherence(double complex* fft_data,
+                      double* result,
+                      size_t* ch1_idx_arr,
+                      size_t* ch2_idx_arr,
+                      size_t num_idx,
+                      size_t num_fft,
+                      size_t num_bins)
+{ 
+    double complex tmp = 0.0;
+    double complex Pxx = 0.0;
+    double complex Pyy = 0.0;
+    size_t idx3_ch1;
+    size_t idx3_ch2;
+
+    #pragma omp parallel for
+    for(size_t cidx = 0; cidx < num_idx; cidx++)
+    {
+        for(size_t nn = 0; nn < num_fft; nn++)
+        {
+            tmp = 0.0 + 0.0 * I;
+            #pragma omp simd 
+            for(size_t bb = 0; bb < num_bins; bb++)
+            {
+                idx3_ch1 = bb + num_bins * (nn + num_fft * ch1_idx_arr[cidx]);
+                idx3_ch2 = bb + num_bins * (nn + num_fft * ch2_idx_arr[cidx]);
+
+                Pxx = fft_data[idx3_ch1] * conj(fft_data[idx3_ch1]);
+                Pyy = fft_data[idx3_ch2] * conj(fft_data[idx3_ch2]);
+                tmp = tmp + fft_data[idx3_ch1] * conj(fft_data[idx3_ch2]) / csqrt(Pxx * Pyy);
+            }
+            result[nn + num_fft * cidx] = creal(cabs(tmp)) / (double) num_bins;
+        }
+    }
+}
+
+
+void kernel_crossphase(double complex* fft_data,
+                      double* result,
+                      size_t* ch1_idx_arr,
+                      size_t* ch2_idx_arr,
+                      size_t num_idx,
+                      size_t num_fft,
+                      size_t num_bins)
+{ 
+    double complex tmp = 0.0;
+    double complex Pxx = 0.0;
+    double complex Pyy = 0.0;
+    size_t idx3_ch1;
+    size_t idx3_ch2;
+
+    #pragma omp parallel for
+    for(size_t cidx = 0; cidx < num_idx; cidx++)
+    {
+        for(size_t nn = 0; nn < num_fft; nn++)
+        {
+            tmp = 0.0 + 0.0 * I;
+            #pragma omp simd 
+            for(size_t bb = 0; bb < num_bins; bb++)
+            {
+
+                idx3_ch1 = bb + num_bins * (nn + num_fft * ch1_idx_arr[cidx]);
+                idx3_ch2 = bb + num_bins * (nn + num_fft * ch2_idx_arr[cidx]);
+                tmp = tmp + fft_data[idx3_ch1] * conj(fft_data[idx3_ch2]);
+            }
+            tmp = tmp / (double) num_bins;
+            result[nn + num_fft * cidx] = atan2(cimag(tmp), creal(tmp));
+        }
+    }
+}
+
+
+void kernel_crosspower(double complex* fft_data,
+                       double* result,
+                       size_t* ch1_idx_arr,
+                       size_t* ch2_idx_arr,
+                       size_t num_idx,
+                       size_t num_fft,
+                       size_t num_bins)
+{ 
+    double complex tmp = 0.0;
+    double complex Pxx = 0.0;
+    double complex Pyy = 0.0;
+    size_t idx3_ch1;
+    size_t idx3_ch2;
+
+    #pragma omp parallel for
+    for(size_t cidx = 0; cidx < num_idx; cidx++)
+    {
+        for(size_t nn = 0; nn < num_fft; nn++)
+        {
+            tmp = 0.0 + 0.0 * I;
+            #pragma omp simd 
+            for(size_t bb = 0; bb < num_bins; bb++)
+            {
+
+                idx3_ch1 = bb + num_bins * (nn + num_fft * ch1_idx_arr[cidx]);
+                idx3_ch2 = bb + num_bins * (nn + num_fft * ch2_idx_arr[cidx]);
+                tmp = tmp + fft_data[idx3_ch1] * conj(fft_data[idx3_ch2]);
+            }
+
+            result[nn + num_fft * cidx] = cabs(tmp) / (double) num_bins;
+        }
+    }
+}