run_A_1.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from ipywidgets import interact\n",
    "from ipywidgets.widgets import IntSlider, FloatSlider, Dropdown\n",
    "from code_A_1 import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Erdos Renyi network \n",
    "simulation_data['network_n'] = 1000\n",
    "simulation_data['network_p'] = 0.006   \n",
    "\n",
    "# disease \n",
    "simulation_data['D'] = 50   #disease related genes  \n",
    "simulation_data['p'] = 0.5  #clustering probability\n",
    "\n",
    "# cohort\n",
    "simulation_data['P'] = 15 #patiens number\n",
    "simulation_data['A'] = 0.5  #disease expression density scaling\n",
    "\n",
    "##############################################\n",
    "series = simulate_series(simulation_data) \n",
    "##############################################\n",
    "\n",
    "def plot_data(rho_0, f):\n",
    "    #rho = '0.0' + str(rho_0)\n",
    "    plot_network(series[str(rho_0)][str(f)]) \n",
    "    \n",
    "p = interact(plot_data, rho_0=FloatSlider(min=0.01, max=0.2, step=0.01, value=0.01), f=IntSlider(0,0,10))"
   ]
  }
 ],
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   "file_extension": ".py",
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