Fix convert_to_pd_df

Author: szhan

python/tests/test_imputation.py

@@ -97,7 +97,7 @@ def get_toy_ts():
 Note that there are two sets of matrices, one for each haplotype.
 """
 _fwd_matrix_text_1 = """
-m,h,probRec,probNoRec,noErrProb,errProb,refAl,queryAl,shift,scale,sum,fwdVal
+m,h,probRec,probNoRec,noErrProb,errProb,refAl,queryAl,shift,scale,sum,val
 0,0,0.000000,1.000000,0.999900,0.000100,1,0,0.000000,1.000000,0.000100,0.000100
 0,1,0.000000,1.000000,0.999900,0.000100,0,0,0.000000,1.000000,1.000000,0.999900
 0,2,0.000000,1.000000,0.999900,0.000100,1,0,0.000000,1.000000,1.000100,0.000100
@@ -117,7 +117,7 @@ def get_toy_ts():
 """
 
 _bwd_matrix_text_1 = """
-m,h,probRec,probNoRec,noErrProb,errProb,refAl,queryAl,shift,scale,sum,bwdVal
+m,h,probRec,probNoRec,noErrProb,errProb,refAl,queryAl,shift,scale,sum,val
 2,0,1.000000,0.000000,0.999900,0.000100,1,0,0.000000,0.250000,0.250050,0.250000
 2,1,1.000000,0.000000,0.999900,0.000100,0,0,0.000000,0.250000,0.250050,0.250000
 2,2,1.000000,0.000000,0.999900,0.000100,1,0,0.000000,0.250000,0.250050,0.250000
@@ -133,7 +133,7 @@ def get_toy_ts():
 """
 
 _fwd_matrix_text_2 = """
-m,h,probRec,probNoRec,noErrProb,errProb,refAl,queryAl,shift,scale,sum,fwdVal
+m,h,probRec,probNoRec,noErrProb,errProb,refAl,queryAl,shift,scale,sum,val
 0,0,0.000000,1.000000,0.999900,0.000100,1,1,0.000000,1.000000,0.999900,0.999900
 0,1,0.000000,1.000000,0.999900,0.000100,0,1,0.000000,1.000000,1.000000,0.000100
 0,2,0.000000,1.000000,0.999900,0.000100,1,1,0.000000,1.000000,1.999900,0.999900
@@ -153,7 +153,7 @@ def get_toy_ts():
 """
 
 _bwd_matrix_text_2 = """
-m,h,probRec,probNoRec,noErrProb,errProb,refAl,queryAl,shift,scale,sum,bwdVal
+m,h,probRec,probNoRec,noErrProb,errProb,refAl,queryAl,shift,scale,sum,val
 2,0,1.000000,0.000000,0.999900,0.000100,1,1,0.000000,0.250000,0.749950,0.250000
 2,1,1.000000,0.000000,0.999900,0.000100,0,1,0.000000,0.250000,0.749950,0.250000
 2,2,1.000000,0.000000,0.999900,0.000100,1,1,0.000000,0.250000,0.749950,0.250000
@@ -178,7 +178,13 @@ def convert_to_pd_df(matrix_text):
     assert all(df.probRec + df.probNoRec == 1)
     # Check that non-mismatch and mismatch probabilities sum to 1
     assert all(df.noErrProb + df.errProb == 1)
-    return df
+    matrix = df.val.to_numpy().reshape(
+        (
+            4,
+            4,
+        )
+    )  # size (m, h)
+    return matrix
 
 
 def get_forward_backward_matrices():