Start on calc_Bprime_per_chunk wrapper function

Author: jacobimarsh

Bvalcalc/core/chromBcalc.py

@@ -141,8 +141,11 @@ def chromBcalc(args, blockstart, blockend, chromosome, unlinked_B, prior_pos = N
     chrom_col = np.full(binned_positions.shape, chromosome, dtype="<U20")
 
     output_data = np.core.records.fromarrays(
-    [chrom_col,binned_positions.astype(int),binned_b_values.astype(float)],
-    names='Chromosome,Position,B',formats='U20,i8,f8')
+        [chrom_col,binned_positions.astype(int),binned_b_values.astype(float)],
+        names='Chromosome,Position,B',formats='U20,i8,f8')
+
+    from Bvalcalc.core.helpers import calc_Bprime_per_chunk
+    calc_Bprime_per_chunk()
 
     if args.out is not None: # Write to CSV
         print(f"Writing B output to file...")

Bvalcalc/core/helpers/calc_Bprime_per_chunk.py

@@ -0,0 +1,11 @@
+from Bvalcalc.core.calculateB import calculateB_linear, calculateB_hri
+import numpy as np
+
+def calc_Bprime_per_chunk():
+
+    print("gotcha")
+
+
+    return
+        #chunk_idx, chunk_size, chr_start, chr_size, num_chunks, 
+         #           precise_chunks, lperchunk, rec_rate_per_chunk, gc_rate_per_chunk):

Bvalcalc/core/siteBcalc.py

@@ -16,11 +16,20 @@ def siteBcalc(args):
 
     ## r = 1e-8
     ## chunk_size = 20000
-    ## First we need to identify our linkage block of interest, which will be the area within a cM recombint length region, with a minimum U
 
     ##      0. Make a normal B-map.
 
     ##      1. Find consecutive chunks with local rec_rate below 0.1 * r with int_L > 0 to have interference calculation applied within them.
+    import numpy as np
+    r = 1e-8
+    r_hri_threshold = 0.1 # only run HRI B when chunk r is less than: r * r_hri_threshold
+
+    chunk_rec_rate = np.array([0.001 * r, 0.5 * r])
+    print(chunk_rec_rate[chunk_rec_rate > r_hri_threshold * r], 'Hi')
+
+    import sys
+    sys.exit()
+
     ## 
     ##      2. Re-calculate B from everything EXCEPT within the region (distant B)
     ##