From 52572d38934e2de079da8171c33738f78971055c Mon Sep 17 00:00:00 2001
From: Haibao Tang <tanghaibao@gmail.com>
Date: Fri, 12 Apr 2024 10:26:56 -0700
Subject: [PATCH] Move iteration out

---
 jcvi/apps/pedigree.py | 89 +++++++++++++++++++++++--------------------
 1 file changed, 48 insertions(+), 41 deletions(-)

diff --git a/jcvi/apps/pedigree.py b/jcvi/apps/pedigree.py
index 16667db8..d91f9f85 100644
--- a/jcvi/apps/pedigree.py
+++ b/jcvi/apps/pedigree.py
@@ -6,8 +6,8 @@
 
 from collections import Counter
 from dataclasses import dataclass
-from random import choice, sample
-from typing import Optional, Tuple
+from random import sample
+from typing import Optional
 
 import numpy as np
 
@@ -60,44 +60,53 @@ class GenotypeCollection(dict):
     Store genotypes for each sample.
     """
 
-    def add(self, s: str, ploidy: int, N: int):
+    def add(self, s: str, ploidy: int):
         """
         Add genotypes for a fixed sample (usually terminal).
         """
-        self[s] = [[f"{s}{i:02d}" for i in range(ploidy)] for _ in range(N)]
+        self[s] = [f"{s}{i:02d}" for i in range(ploidy)]
 
-    def cross(self, s: str, dad: str, mom: str, ploidy: int, N: int):
+    def cross(self, s: str, dad: str, mom: str, ploidy: int):
         """
         Cross two samples to generate genotypes for a new sample.
         """
-        dad_genotypes = self[dad]
-        mom_genotypes = self[mom]
+        dad_genotype = self[dad]
+        mom_genotype = self[mom]
         gamete_ploidy = ploidy // 2
-        sample_genotypes = []
-        for _ in range(N):
-            dad_genotype = choice(dad_genotypes)
-            mom_genotype = choice(mom_genotypes)
-            dad_gamete = sample(dad_genotype, gamete_ploidy)
-            mom_gamete = sample(mom_genotype, gamete_ploidy)
-            sample_genotypes.append(sorted(dad_gamete + mom_gamete))
-        self[s] = sample_genotypes
-
-    def inbreeding_coef(self, s: str) -> Tuple[float, float]:
+        dad_gamete = sample(dad_genotype, gamete_ploidy)
+        mom_gamete = sample(mom_genotype, gamete_ploidy)
+        sample_genotype = sorted(dad_gamete + mom_gamete)
+        self[s] = sample_genotype
+
+    def inbreeding_coef(self, s: str) -> float:
         """
         Calculate inbreeding coefficient for a sample.
         """
-        genotypes = self[s]
-        results = []
-        for genotype in genotypes:
-            ploidy = len(genotype)
-            pairs = ploidy * (ploidy - 1) // 2
-            counter = Counter(genotype)
-            collisions = 0
-            for count in counter.values():
-                collisions += count * (count - 1) // 2
-            results.append(collisions / pairs)
-        results = np.array(results)
-        return results.mean(), results.std()
+        genotype = self[s]
+        ploidy = len(genotype)
+        pairs = ploidy * (ploidy - 1) // 2
+        counter = Counter(genotype)
+        collisions = 0
+        for count in counter.values():
+            collisions += count * (count - 1) // 2
+        return collisions / pairs
+
+
+def simulate_one_iteration(ped: Pedigree, ploidy: int) -> GenotypeCollection:
+    """
+    Simulate one iteration of genotypes.
+    """
+    genotypes = GenotypeCollection()
+    while len(genotypes) < len(ped):
+        for s in ped:
+            if ped[s].is_terminal:
+                genotypes.add(s, ploidy=ploidy)
+            else:
+                dad, mom = ped[s].dad, ped[s].mom
+                if dad not in genotypes or mom not in genotypes:
+                    continue
+                genotypes.cross(s, dad, mom, ploidy=ploidy)
+    return genotypes
 
 
 def inbreeding(args):
@@ -118,19 +127,17 @@ def inbreeding(args):
     ploidy = opts.ploidy
     N = opts.N
     ped = Pedigree(pedfile)
-    genotypes = GenotypeCollection()
-    while len(genotypes) < len(ped):
-        for s in ped:
-            if ped[s].is_terminal:
-                genotypes.add(s, ploidy=ploidy, N=N)
-            else:
-                dad, mom = ped[s].dad, ped[s].mom
-                if dad not in genotypes or mom not in genotypes:
-                    continue
-                genotypes.cross(s, dad, mom, ploidy=ploidy, N=N)
+    all_collections = []
+    for _ in range(N):
+        genotypes = simulate_one_iteration(ped, ploidy)
+        all_collections.append(genotypes)
     for s in ped:
-        mean, std = genotypes.inbreeding_coef(s)
-        print(s, mean, std)
+        inbreeding_coefs = [
+            genotypes.inbreeding_coef(s) for genotypes in all_collections
+        ]
+        mean_inbreeding = np.mean(inbreeding_coefs)
+        std_inbreeding = np.std(inbreeding_coefs)
+        print(f"{s}\t{mean_inbreeding:.4f}\t{std_inbreeding:.4f}")
 
 
 def main():