From 8b1ec3dba83b3949d8d7c0b20764347c70905ab5 Mon Sep 17 00:00:00 2001 From: Anton Laukemper Date: Wed, 20 Jan 2021 14:48:28 +0100 Subject: [PATCH 1/4] remove dead link --- README.md | 2 -- 1 file changed, 2 deletions(-) diff --git a/README.md b/README.md index 4c1aabe..a1afe67 100644 --- a/README.md +++ b/README.md @@ -6,8 +6,6 @@ Example scripts for defSim || Discrete Event Framework for Social Influence Mode - [defSim git repository](https://github.com/marijnkeijzer/defSim) - [documentation for defSim](https://marijnkeijzer.github.io/defSim) -New to defSim? [Learn how to use defSim in this quick introduction](https://marijnkeijzer.github.io/defSim/Introduction_to_defSim.html) - For a description of all of defSim's functions, see the [documentation](https://marijnkeijzer.github.io/defSim) Included examples From 375e1b668137855dc571929181dd58a9049f6d96 Mon Sep 17 00:00:00 2001 From: Anton Laukemper Date: Wed, 20 Jan 2021 14:53:20 +0100 Subject: [PATCH 2/4] replace dead links --- README.md | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index a1afe67..dabd175 100644 --- a/README.md +++ b/README.md @@ -3,10 +3,11 @@ defSim, examples Example scripts for defSim || Discrete Event Framework for Social Influence Models -- [defSim git repository](https://github.com/marijnkeijzer/defSim) -- [documentation for defSim](https://marijnkeijzer.github.io/defSim) +- [defSim git repository](https://github.com/defSim/defSim) -For a description of all of defSim's functions, see the [documentation](https://marijnkeijzer.github.io/defSim) +New to defSim? [Learn how to use defSim in this quick introduction](https://defsim.github.io/defSim/Introduction_to_defSim.html) + +For a description of all of defSim's functions, see the [documentation](https://defsim.github.io/defSim/) Included examples ----------------- From 88a90fa7ddf59eec55614ca620642bc2924fff0d Mon Sep 17 00:00:00 2001 From: Anton Laukemper Date: Wed, 20 Jan 2021 16:33:34 +0100 Subject: [PATCH 3/4] add text from paper to each notebook and adapt readme --- ExperimentClass.ipynb | 25 +++++++++++------- ModularNetworkModification.ipynb | 10 +++++-- NewAttributeInitializer.ipynb | 29 ++++++++++---------- README.md | 12 +++++---- SimilarityAdoption.ipynb | 45 +++++++++++++++++++------------- 5 files changed, 72 insertions(+), 49 deletions(-) diff --git a/ExperimentClass.ipynb b/ExperimentClass.ipynb index f871557..a28c158 100644 --- a/ExperimentClass.ipynb +++ b/ExperimentClass.ipynb @@ -4,7 +4,14 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "This example shows how you can use the Experiment class to execute a set of simulations. " + "## Low-modularity example: out-of-the-box use\n", + "\n", + "A low degree of modularity means using the package as it comes, ’out of the box’, using a combination of the modules as they come with the user’s installation of defSim. The example code given in this notebook runs a small experiment with a bounded confidence model on a wrapped lattice network, varying the communication regime. It combines the conception of opinions as one-dimensional continuous objects (Deffuant et al. 2002) with the idea that in some contexts (e.g. on social networking platforms) individuals communicate to all their contacts at once rather than on a purely dyadic basis (Keijzer et al. 2018). \n", + "\n", + "Both models run for 10,000 iterations and are repeated 20 times. The code returns a pandas data frame,\n", + "here called ’my_results’ that contains the basic model settings and a set of standard output measures that summarize the model after convergence.\n", + "\n", + "A summary of two of those output measures is given in the figure below where homogeneity (i.e. the size of the biggest cluster of similar agents over the total number of agents) and the average distance between agents are plotted for the different communication regimes. We see that when agents influence all their neighbors at once the largest opinion cluster at the end of the run is much larger than when agents communicate at a one-to-one basis. All the while, the average opinion distance between agents remains at asimilar level between the two experimental conditions, indicating that the level of disagreement on the graph remains roughly the same." ] }, { @@ -54,9 +61,7 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -129,23 +134,23 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 2", + "display_name": "Python 3", "language": "python", - "name": "python2" + "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", - "version": 2 + "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.6" + "pygments_lexer": "ipython3", + "version": "3.6.5" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git a/ModularNetworkModification.ipynb b/ModularNetworkModification.ipynb index 4ff6da5..506aee5 100755 --- a/ModularNetworkModification.ipynb +++ b/ModularNetworkModification.ipynb @@ -4,7 +4,13 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "This example showcases highly modular use of defSim." + "## High-level modularity: Implementing a custom simulation order \n", + "\n", + "All the functions included in defSim can of course be used on their own, completely separate from the simulation framework posed here. Using lower-level defSim functions outside of the standard simulation loop may be considered defSim use with a high degree of modularity. This may be useful for those who wish to, for example, mix elements from the initialization and simulation stage, or implement exogenous shocks or idiosyncrasies into their model. In the example given in this notebook, we demonstrate one way in which lower level defSim functions can be used on their own. The simulation is initialized with a caveman graph network where *k* agents per cave create links to all other agents within one of *l* ’caves’ (Watts 1999). In this case, a network with *l*= 2 and *k* = 10 is created, as specified in the parameter dictionary (line 10 through 13 in code cell 3). \n", + "\n", + "The two caves are internally fully connected, and there are no ties connecting the two caves. The simulation runs for 40 steps (max_iterations on line 9 in code cell 3) under a bounded confidence influence function (specified on line 4). Next, the network isrestructured to create connections between the two caves using Maslov-Sneppen rewiring (Maslov & Sneppen2002). To apply the Maslov-Sneppen rewiring procedure, we can use a network modifier available in defSim which is part of the network_evolution_sim module (on line 20). The module is used by first creating an instance of the MaslovSneppenModifier with the proportion of rewired links as an initialization parameter, and then calling its rewire_network function on the simulation network. Of all ties in the simulation network, approximately 10% (rewiring_prop = 0.1) are rewired. We directly access the network on which the simulation takes place (my_simulation.network). After applying Maslov-Sneppen rewiring, new ties have been created. The in-fluence function used in this example requires knowledge of the opinion distance between connected agents.\n", + "\n", + "This opinion distance is stored as an attribute of each network tie. The new ties we created currently lack this attribute (they are created without any attribute values). Fortunately, the dissimilarity calculator used to calculate opinion distances in this simulation can also be accessed directly (on line 22). We call its calculate_dissimilarity_networkwide function to recalculate opinion distances between all connected agents. Finally, the simulation runs for another 40 iterations. Since the simulation is not reinitialized, agents retain their attribute values and network position. Now that network ties exist between the two caves, agents from both caves can (directly or indirectly) influence one another. Figure 5 shows that agents in each cave quickly converge to local consensus, while average opinions differ between the two caves. When the two caves are connected this leads to global consensus, which notably does not need to be located at the average of the local opinions of the two caves before rewiring." ] }, { @@ -669,7 +675,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.9" + "version": "3.6.5" } }, "nbformat": 4, diff --git a/NewAttributeInitializer.ipynb b/NewAttributeInitializer.ipynb index aaca605..c6b8e5f 100644 --- a/NewAttributeInitializer.ipynb +++ b/NewAttributeInitializer.ipynb @@ -4,7 +4,15 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "This example implements a new attribtue initializer. For more information on writing a new module implementation, see the [GitHub wiki](https://github.com/marijnkeijzer/defSim/wiki). " + "## Mid-level modularity: Implementing your own module\n", + "\n", + "The library of influence functions, attribute initializers, or agent selectors is not exhaustive. defSim aims to enable users to build upon and extend the body of knowledge in the social influence modeling literature. Variations of models with a mid-level degree of modularity do exactly this. By writing one’s own implementationof a module in the defSim framework, the user can go beyond the default, while keeping models aligned with the literature and preserving the efficiency and scalability benefits of using the framework. In the example given in this notebook, we demonstrate how to replace the default attribute initializer and use it in an Experiment. For example, you might be interested in looking at the dynamics of opinion formation given different opinion distributions at the outset. The example experiment given here shows the effect of starting from a bimodal distribution versus a mixed distribution by implementing an attribute initializer and using it in an experiment. \n", + "\n", + "First, we import defSim, the AttributesInitializer class to create our own instance of this Abstract Base Class (ABC), and the method to set a categorical attribute. We also import NumPy, which we use to draw random values from a beta distribution. Second, we write the attribute intializer to match the structure dictated by the AttributesInitializer ABC. It is important to make sure that the class contains the same methods as the ABC, and that these methods contain the same arguments. All arguments that are unique to this method can be passed to the initializer through the key-worded arguments dictionary (kwargs). In this case, we give all the nodes an attribute ’sex’ and asssign one of ’female’ or ’male’ as its value. Based on this categorical attribute, we then draw an opinion from a beta distribution for every opinion feature. The beta distributions for the two types of agents have a different peak, resulting in a bimodal opinion distribution overall. Finally, we initialize and run an experiment, passing our new initializer to the ’attribute_initializer’ keyword. Note that we exclude the variable ’sex’ from the set of variables used for calculating dissimilarity (the ’exclude’ argument to the instance of the attribute initializer on line 22) and from the set of variables that can be influenced (on line 27).\n", + "\n", + "We run the model twice, once with a bimodal opinion distribution and once with a mixed distribution, and plot the opinion distribution on the outset and the opinion trajectories of those two runs. Unsurprisingly, the opinion distribution on the outset (top row of panels in Figure 4) affects whether the population splits up into two groups, or whether they find consensus on the single opinion dimension (as shown in the lower two panels of Figure 4.\n", + "\n", + "For more information on writing a new module implementation, see the [GitHub wiki](https://github.com/defSim/defSim/wiki). " ] }, { @@ -131,7 +139,6 @@ "plt.ylabel('frequency')\n", "plt.ylim(0, 25)\n", "\n", - "#plt.savefig('/Users/marijnkeijzer/Desktop/newatt_dist_bimodal.png', dpi=144)\n", "\n", "plt.show()" ] @@ -169,8 +176,6 @@ "plt.xlabel('time')\n", "plt.ylim(0, 1)\n", "\n", - "#plt.savefig('/Users/marijnkeijzer/Desktop/newatt_traj_bimodal.png', dpi=144)\n", - "\n", "plt.show()" ] }, @@ -247,8 +252,6 @@ "plt.ylabel('frequency')\n", "plt.ylim(0, 25)\n", "\n", - "#plt.savefig('/Users/marijnkeijzer/Desktop/newatt_dist_mixed.png', dpi=144)\n", - "\n", "plt.show()" ] }, @@ -285,31 +288,29 @@ "plt.xlabel('time')\n", "plt.ylim(0, 1)\n", "\n", - "#plt.savefig('/Users/marijnkeijzer/Desktop/newatt_traj_mixed.png', dpi=144)\n", - "\n", "plt.show()" ] } ], "metadata": { "kernelspec": { - "display_name": "Python 2", + "display_name": "Python 3", "language": "python", - "name": "python2" + "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", - "version": 2 + "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.6" + "pygments_lexer": "ipython3", + "version": "3.6.5" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git a/README.md b/README.md index dabd175..432c0e5 100644 --- a/README.md +++ b/README.md @@ -9,10 +9,12 @@ New to defSim? [Learn how to use defSim in this quick introduction](https://defs For a description of all of defSim's functions, see the [documentation](https://defsim.github.io/defSim/) -Included examples +As defSim is a framework for social influence models, there are many different ways in which the package or it’s single components can be used. A way to think about the different uses of defSim is by organizing them by their degree of modularity. That is, the degree to which the users separates, reorganizes, or creates elements for their own simulation run. Low degree variations are typically well suited for teaching, illustrating, or replicating. Variations of implementations in the mid and high range of modularity may be more suited to researchers implementing novel ideas. + +This repository introduces examples for each level of modularity: ----------------- -- `ExperimentClass.ipynb` example of the use of the main 'Experiment' function, used to run many replications of simulation runs. -- `SimilarityAdoption.ipynb` includes an implementation of the *SimilarityAdoption* influence function included in Axelrod's seminal 1997 JCR paper. -- `NewAttributeInitializer.ipynb` illustrates how you could program your own attribute initializer, following the defSim framework. -- `ModularNetworkModification.ipynb` showcases a highly modular use of defSim splitting initialization and simulation to allow for network manipulation. +- `ExperimentClass.ipynb` shows an 'out-of-the-box' use of defSim. This example introduces the use of the main 'Experiment' function, used to run many replications of simulation runs. +- `SimilarityAdoption.ipynb` is another low modularity example which showcases the *SimilarityAdoption* influence function included in Axelrod's seminal 1997 JCR paper. +- `NewAttributeInitializer.ipynb` illustrates how you could program your own attribute initializer, following the defSim framework. This a more modular use-case of defSim. +- `ModularNetworkModification.ipynb` showcases a highly modular use of defSim by splitting initialization and simulation to allow for network manipulation. diff --git a/SimilarityAdoption.ipynb b/SimilarityAdoption.ipynb index 420e262..7c9172f 100644 --- a/SimilarityAdoption.ipynb +++ b/SimilarityAdoption.ipynb @@ -6,16 +6,29 @@ "collapsed": true }, "source": [ - "This example showcases the Influence function 'SimilarityAdoption'" + "## Low-modularity example 2: Recreating the Classics\n", + "\n", + "In this example the model by Axelrod (1997) is recreated using the modules that come with the defSim framework. Since no modules need to be adapted or added for this experiment it is another low modularity example. \n", + "The influence function defined by Axelrod is named \"similarity_adoption\" in the defSim framework." ] }, { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": false - }, - "outputs": [], + "metadata": {}, + "outputs": [ + { + "ename": "ModuleNotFoundError", + "evalue": "No module named 'defSim'", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[1;32mimport\u001b[0m \u001b[0mdefSim\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mds\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 2\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mmatplotlib\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpyplot\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 3\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mseaborn\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0msns\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 4\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mnumpy\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 5\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0mmatplotlib\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlines\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mLine2D\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;31mModuleNotFoundError\u001b[0m: No module named 'defSim'" + ] + } + ], "source": [ "import defSim as ds\n", "import matplotlib.pyplot as plt\n", @@ -28,7 +41,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# The classic Axelrod (1997) model with homophily\n", + "### The classic Axelrod (1997) model with homophily\n", "\n", "Below we implement a simulation model exactly as in [1].\n", "\n", @@ -101,9 +114,7 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -161,9 +172,7 @@ { "cell_type": "code", "execution_count": 9, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -269,23 +278,23 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 2", + "display_name": "Python 3", "language": "python", - "name": "python2" + "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", - "version": 2 + "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.6" + "pygments_lexer": "ipython3", + "version": "3.6.5" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } From d0819ded7a3d9c4fe7547244cd1363acc1c66d58 Mon Sep 17 00:00:00 2001 From: Anton Laukemper Date: Thu, 21 Jan 2021 21:28:57 +0100 Subject: [PATCH 4/4] run notebooks and add figure titles --- ExperimentClass.ipynb | 17 +++++++++----- NewAttributeInitializer.ipynb | 41 +++++++++++++++++---------------- SimilarityAdoption.ipynb | 43 +++++++++-------------------------- 3 files changed, 44 insertions(+), 57 deletions(-) diff --git a/ExperimentClass.ipynb b/ExperimentClass.ipynb index a28c158..dfcd551 100644 --- a/ExperimentClass.ipynb +++ b/ExperimentClass.ipynb @@ -16,10 +16,8 @@ }, { "cell_type": "code", - "execution_count": 26, - "metadata": { - "collapsed": true - }, + "execution_count": 1, + "metadata": {}, "outputs": [], "source": [ "import defSim as ds\n", @@ -77,12 +75,12 @@ }, { "cell_type": "code", - "execution_count": 91, + "execution_count": 4, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -130,6 +128,13 @@ "\n", "plt.show()\n" ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { diff --git a/NewAttributeInitializer.ipynb b/NewAttributeInitializer.ipynb index c6b8e5f..f7e1c3d 100644 --- a/NewAttributeInitializer.ipynb +++ b/NewAttributeInitializer.ipynb @@ -2,7 +2,11 @@ "cells": [ { "cell_type": "markdown", - "metadata": {}, + "metadata": { + "slideshow": { + "slide_type": "fragment" + } + }, "source": [ "## Mid-level modularity: Implementing your own module\n", "\n", @@ -10,7 +14,7 @@ "\n", "First, we import defSim, the AttributesInitializer class to create our own instance of this Abstract Base Class (ABC), and the method to set a categorical attribute. We also import NumPy, which we use to draw random values from a beta distribution. Second, we write the attribute intializer to match the structure dictated by the AttributesInitializer ABC. It is important to make sure that the class contains the same methods as the ABC, and that these methods contain the same arguments. All arguments that are unique to this method can be passed to the initializer through the key-worded arguments dictionary (kwargs). In this case, we give all the nodes an attribute ’sex’ and asssign one of ’female’ or ’male’ as its value. Based on this categorical attribute, we then draw an opinion from a beta distribution for every opinion feature. The beta distributions for the two types of agents have a different peak, resulting in a bimodal opinion distribution overall. Finally, we initialize and run an experiment, passing our new initializer to the ’attribute_initializer’ keyword. Note that we exclude the variable ’sex’ from the set of variables used for calculating dissimilarity (the ’exclude’ argument to the instance of the attribute initializer on line 22) and from the set of variables that can be influenced (on line 27).\n", "\n", - "We run the model twice, once with a bimodal opinion distribution and once with a mixed distribution, and plot the opinion distribution on the outset and the opinion trajectories of those two runs. Unsurprisingly, the opinion distribution on the outset (top row of panels in Figure 4) affects whether the population splits up into two groups, or whether they find consensus on the single opinion dimension (as shown in the lower two panels of Figure 4.\n", + "We run the model twice, once with a bimodal opinion distribution and once with a mixed distribution, and plot the opinion distribution on the outset and the opinion trajectories of those two runs. Unsurprisingly, the opinion distribution on the outset (Figure 1 and 3) affects whether the population splits up into two groups, or whether they find consensus on the single opinion dimension (as shown in Figure 2 and 4).\n", "\n", "For more information on writing a new module implementation, see the [GitHub wiki](https://github.com/defSim/defSim/wiki). " ] @@ -18,9 +22,7 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": true - }, + "metadata": {}, "outputs": [], "source": [ "import defSim as ds\n", @@ -40,9 +42,7 @@ { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": true - }, + "metadata": {}, "outputs": [], "source": [ "class MyAttributeInitializer(ds.AttributesInitializer):\n", @@ -79,7 +79,7 @@ }, { "cell_type": "code", - "execution_count": 237, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -102,12 +102,12 @@ }, { "cell_type": "code", - "execution_count": 238, + "execution_count": 6, "metadata": {}, "outputs": [ { "data": { - "image/png": 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ZTI4AAAAASUVORK5CYII=\n", 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"text/plain": [ "
" ] @@ -138,19 +138,19 @@ "plt.xlabel('opinion')\n", "plt.ylabel('frequency')\n", "plt.ylim(0, 25)\n", - "\n", + "plt.title(\"Figure 1\")\n", "\n", "plt.show()" ] }, { "cell_type": "code", - "execution_count": 239, + "execution_count": 7, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
" ] @@ -175,6 +175,7 @@ "plt.ylabel('opinion')\n", "plt.xlabel('time')\n", "plt.ylim(0, 1)\n", + "plt.title(\"Figure 2\")\n", "\n", "plt.show()" ] @@ -190,7 +191,7 @@ }, { "cell_type": "code", - "execution_count": 270, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -217,12 +218,12 @@ }, { "cell_type": "code", - "execution_count": 271, + "execution_count": 10, "metadata": {}, "outputs": [ { "data": { - "image/png": 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AAABJRU5ErkJggg==\n", 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\n", "text/plain": [ "
" ] @@ -251,18 +252,19 @@ "plt.xlabel('opinion')\n", "plt.ylabel('frequency')\n", "plt.ylim(0, 25)\n", + "plt.title(\"Figure 3\")\n", "\n", "plt.show()" ] }, { "cell_type": "code", - "execution_count": 272, + "execution_count": 11, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -287,6 +289,7 @@ "plt.ylabel('opinion')\n", "plt.xlabel('time')\n", "plt.ylim(0, 1)\n", + "plt.title(\"Figure 4\")\n", "\n", "plt.show()" ] diff --git a/SimilarityAdoption.ipynb b/SimilarityAdoption.ipynb index 7c9172f..2896b3e 100644 --- a/SimilarityAdoption.ipynb +++ b/SimilarityAdoption.ipynb @@ -14,21 +14,9 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "metadata": {}, - "outputs": [ - { - "ename": "ModuleNotFoundError", - "evalue": "No module named 'defSim'", - "output_type": "error", - "traceback": [ - "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[1;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)", - "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[1;32mimport\u001b[0m \u001b[0mdefSim\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mds\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 2\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mmatplotlib\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpyplot\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 3\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mseaborn\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0msns\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 4\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mnumpy\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 5\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0mmatplotlib\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlines\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mLine2D\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;31mModuleNotFoundError\u001b[0m: No module named 'defSim'" - ] - } - ], + "outputs": [], "source": [ "import defSim as ds\n", "import matplotlib.pyplot as plt\n", @@ -61,12 +49,12 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -113,7 +101,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "metadata": {}, "outputs": [ { @@ -151,15 +139,6 @@ "First, let's check whether all runs have converged:" ] }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "It looks like they did! \n", - "\n", - "Now, we can plot what the effect of this *homophily* parameter is on the diversity of available feature vectors in the simulations we ran. We will look at **average distance** between all agents, and at the **number of culturally distinct regions**, that is, the number of clusters of connected agents with a perfecly similar feature vector. " - ] - }, { "cell_type": "markdown", "metadata": {}, @@ -171,12 +150,12 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 5, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -202,12 +181,12 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 6, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -233,12 +212,12 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 7, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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