@@ -799,7 +799,7 @@ def _compute_haplotype_sharing(
799799 2. Assigning two cohort labels per diploid sample (one for each haplotype).
800800 3. Filtering down to segregating sites to speed up distinction.
801801 4. Grouping all identical haplotypes together using `ht.distinct()`.
802- 5. Counting the number of shared identical groups between every pair of cohorts and returning sharing matrix.
802+ 5. Counting the number of shared identical groups between every pair of cohorts and returning sharing matrix.
803803 """
804804 # Load phased genotypes for the specified region
805805 ds_haps = self .haplotypes (
@@ -933,7 +933,7 @@ def plot_haplotype_sharing_arc(
933933 arc_height = abs (x2 - x1 ) * 0.5
934934 # Scale arc thickness linearly based on sharing count
935935 line_width = 1 + (count / max_sharing ) * 9
936- # Generate points for the arc
936+ # Generate points for the arc
937937 t = np .linspace (0 , np .pi , 50 )
938938 arc_x = x1 + (x2 - x1 ) * (1 - np .cos (t )) / 2
939939 arc_y = arc_height * np .sin (t )
@@ -1069,7 +1069,7 @@ def plot_haplotype_sharing_chord(
10691069 x2 , y2 = cohort_x [c2 ], cohort_y [c2 ]
10701070
10711071 line_width = 1 + (count / max_sharing ) * 9
1072- # Draw a quadratic Bezier curve passing through the center (0,0)
1072+ # Draw a quadratic Bezier curve passing through the center (0,0)
10731073 # t from 0 to 1 traces the curve from cohort 1 to cohort 2
10741074 t = np .linspace (0 , 1 , 50 )
10751075 cx , cy = 0 , 0
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