fix zero division

impute_jass/impute_jass/imputation_launcher.py

@@ -16,7 +16,6 @@ class ImputationLauncher(object):
         """
 
         """
-
         ref_panel_file = "/mnt/atlas/PCMA/1._DATA/ImpG_refpanel/{0}.eur.1pct.bim".format(chrom)
         #ref_panel = pd.read_csv(ref_panel_file, sep="\t", names=['chr', "nothing", 'pos', 'Ref_all', 'alt_all'], index_col = 1)
 

impute_jass/impute_jass/stat_models.py

@@ -23,9 +23,6 @@ def impg_model(zt, sig_t, sig_i_t, lamb=0.01, batch=True):
 
     sig_t_inv = np.linalg.pinv(sig_t)
     var = compute_var(sig_i_t, sig_t_inv, lamb, batch)
-    #if var< 0:
-    #    var=0
-
     mu = compute_mu(sig_i_t, sig_t_inv, zt)
-    mu = mu / (((1+lamb)-var)**0.5)
+    #mu = mu / (((1+lamb)-var)**0.5)
     return({"var":var, "mu":mu})

impute_jass/impute_jass/windows.py

@@ -11,7 +11,6 @@ from .ld_matrix import generate_sparse_matrix
 import pandas as pd
 import numpy as np
 
-
 def parse_region_position(ld_file):
     """
     Retrieve the region definition from a ld-file generated by impute_jass
@@ -51,7 +50,6 @@ def prepare_zscore_for_imputation(ref_panel, zscore):
     zscore = zscore.loc[zscore.index.intersection(ref_panel.index)]
     return zscore
 
-
 def in_region(pos_vector, start, end):
     return ((start < pos_vector) & (pos_vector < end))
 
@@ -103,11 +101,16 @@ def impg_like_imputation(ld_file, ref_panel, zscore, window_size, buffer, unknow
     LD_mat = generate_sparse_matrix(ld_file, ref_panel)
     Nwindows = ((int(end_ld_block)) - (int(start_ld_block)))//window_size
     # adapt window size to cover the LD block
-    window_resize = np.ceil((int(end_ld_block) - (int(start_ld_block)))/Nwindows)
+    if Nwindows > 0:
+        window_resize = np.ceil((int(end_ld_block) - (int(start_ld_block)))/Nwindows)
+    else:
+        Nwindows = 1
+        window_resize = np.ceil(int(end_ld_block) - (int(start_ld_block)))
+        
     all_unknowns = ref_panel.loc[ref_panel.index.difference(zscore.index)]
     #zscore = pd.read_csv(Zfile, index_col=0, sep="\t")
     zscore = prepare_zscore_for_imputation(ref_panel, zscore)
-    print("### Imputation of {0} snps ###".format(unknowns.shape[0]))
+    print("### Imputation of {0} snps ###".format(all_unknowns.shape[0]))
 
     for i in range(Nwindows):
         # Boundary of the sliding_window