From b2d19e206605ed9131b8eb9865fcad1da5b04684 Mon Sep 17 00:00:00 2001
From: Ju Eun Kang <133086206+jueun429@users.noreply.github.com>
Date: Mon, 14 Jul 2025 12:44:00 +0900
Subject: [PATCH] Make follicle start times deterministic

---
 GynCycle_Original code/poissonproc.m | 36 ++++++++++++++++++----------
 README.md                            |  9 ++++++-
 2 files changed, 31 insertions(+), 14 deletions(-)

diff --git a/GynCycle_Original code/poissonproc.m b/GynCycle_Original code/poissonproc.m
index 91003cf..e5c955a 100644
--- a/GynCycle_Original code/poissonproc.m	
+++ b/GynCycle_Original code/poissonproc.m	
@@ -1,13 +1,23 @@
-function S =poissonproc(lambda,tspan)
-
-tb=tspan(1);    %start time
-te=tspan(2);  %end time
-
-%alternative method:
-N=poissrnd(lambda*(te-tb));
-U=rand([N,1]);
-Usort=sort(U);
-S=tb+(te-tb)*Usort;
-%length(S)
-
-end
+function S =poissonproc(lambda,tspan)
+%POISSONPROC Deterministic replacement for follicle start times.
+%   S = POISSONPROC(LAMBDA,TSPAN) returns a vector of equally spaced
+%   start times within the interval defined by TSPAN.  The number of
+%   generated times corresponds to the expected value LAMBDA*(TE-TB).
+
+tb = tspan(1);    % start time
+te = tspan(2);    % end time
+
+% determine the number of events deterministically
+N = max(round(lambda * (te - tb)), 0);
+
+if N <= 0
+    S = [];
+    return
+end
+
+% create uniform time points inside the interval (tb, te)
+step = (te - tb) / (N + 1);
+S = tb + step * (1:N);  % row vector
+S = S(:);               % ensure column vector
+
+end
diff --git a/README.md b/README.md
index 58f1d91..f16a45b 100644
--- a/README.md
+++ b/README.md
@@ -1 +1,8 @@
-# MATLAB
\ No newline at end of file
+# MATLAB
+
+This repository contains a MATLAB implementation of the GynCycle menstrual
+cycle model.  The original code relied on Poisson-distributed start times for
+new follicles.  In this version `poissonproc.m` was changed to remove the
+random Poisson process and instead generate deterministic, evenly spaced
+times.  This allows simulations to be reproducible without setting a random
+seed.