mirror of
https://github.com/gsi-upm/soil
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Notebook v2
This commit is contained in:
jesusmsanchez
parent
39688bc182
commit
cdcb1ec0fd
@ -54,23 +54,11 @@
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},
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{
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"cell_type": "code",
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"execution_count": 25,
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"execution_count": 1,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"ename": "ImportError",
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"evalue": "No module named 'matplotlib'",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mImportError\u001b[0m Traceback (most recent call last)",
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"\u001b[0;32m<ipython-input-25-7de2b31ae930>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mimport\u001b[0m \u001b[0mmatplotlib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpyplot\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mnxsim\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mNetworkSimulation\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mnumpy\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mnetworkx\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mnx\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0msettings\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;31mImportError\u001b[0m: No module named 'matplotlib'"
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]
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}
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],
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"outputs": [],
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"source": [
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"import matplotlib.pyplot as plt\n",
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"from nxsim import NetworkSimulation\n",
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@ -102,7 +90,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 2,
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"metadata": {
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"collapsed": true
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},
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@ -133,11 +121,23 @@
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 3,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Starting simulations...\n",
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"---Trial 0---\n",
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"Setting up agents...\n",
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"Written 50 items to pickled binary file: sim_01/log.0.state.pickled\n",
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"Simulation completed.\n"
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]
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}
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],
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"source": [
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"sim = NetworkSimulation(topology=G, states=init_states, agent_type=ControlModelM2,\n",
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" max_time=settings.max_time, num_trials=settings.num_trials, logging_interval=1.0)\n",
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@ -164,11 +164,19 @@
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 4,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Done!\n"
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]
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}
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],
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"source": [
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"for x in range(0, settings.number_of_nodes):\n",
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" for empresa in models.networkStatus[\"agente_%s\"%x]:\n",
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@ -199,7 +207,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 5,
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"metadata": {
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"collapsed": false
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},
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@ -251,6 +259,13 @@
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"plt.savefig('control_model.png')"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"![alt text](https://raw.githubusercontent.com/gsi-upm/soil/master/control_model.png \"Control model\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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@ -267,7 +282,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 6,
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"metadata": {
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"collapsed": true
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},
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@ -310,7 +325,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 7,
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"metadata": {
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"collapsed": true
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},
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@ -373,7 +388,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 8,
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"metadata": {
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"collapsed": true
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},
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@ -514,87 +529,6 @@
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"source": [
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"This file contains all the variables that can be modified from the simulation. In case of implementing a new spread model, the new variables should be also included in this file."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"# settings.py\n",
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"def init():\n",
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"\n",
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" network_type=1\n",
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" number_of_nodes=1000\n",
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" max_time=50\n",
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" num_trials=1\n",
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" timeout=2\n",
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"\n",
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" #Zombie model\n",
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" bite_prob=0.01 # 0-1\n",
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" heal_prob=0.01 # 0-1\n",
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"\n",
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" #Bass model\n",
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" innovation_prob=0.001\n",
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" imitation_prob=0.005\n",
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"\n",
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" #Sentiment Correlation model\n",
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" outside_effects_prob = 0.2\n",
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" anger_prob = 0.06\n",
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" joy_prob = 0.05\n",
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" sadness_prob = 0.02\n",
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" disgust_prob = 0.02\n",
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"\n",
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" #Big Market model\n",
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" ##Names\n",
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" enterprises = [\"BBVA\",\"Santander\", \"Bankia\"]\n",
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" ##Users\n",
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" tweet_probability_users = 0.44\n",
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" tweet_relevant_probability = 0.25\n",
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" tweet_probability_about = [0.15, 0.15, 0.15]\n",
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" sentiment_about = [0, 0, 0] #Valores por defecto\n",
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" ##Enterprises\n",
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" tweet_probability_enterprises = [0.3, 0.3, 0.3]\n",
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"\n",
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" #SISa\n",
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" neutral_discontent_spon_prob = 0.04\n",
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" neutral_discontent_infected_prob = 0.04\n",
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" neutral_content_spon_prob = 0.18\n",
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" neutral_content_infected_prob = 0.02\n",
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"\n",
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" discontent_neutral = 0.13\n",
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" discontent_content = 0.07\n",
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" variance_d_c = 0.02\n",
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"\n",
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" content_discontent = 0.009\n",
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" variance_c_d = 0.003\n",
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" content_neutral = 0.088\n",
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"\n",
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" standard_variance = 0.055\n",
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"\n",
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" #Spread Model M2 and Control Model M2\n",
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" prob_neutral_making_denier = 0.035\n",
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"\n",
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" prob_infect = 0.075\n",
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"\n",
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" prob_cured_healing_infected = 0.035\n",
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" prob_cured_vaccinate_neutral = 0.035\n",
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"\n",
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" prob_vaccinated_healing_infected = 0.035\n",
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" prob_vaccinated_vaccinate_neutral = 0.035\n",
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" prob_generate_anti_rumor = 0.035\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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