intro_tutorial: Add back fix from #1665 comments

docs/tutorials/intro_tutorial.ipynb

@@ -66,7 +66,6 @@
  "\n",
  "```bash\n",
  "pip install matplotlib\n",
- "pip install seaborn\n",
  "```\n"
  ]
  },
@@ -131,11 +130,15 @@
  "source": [
  "import mesa\n",
  "\n",
- "# Visualization tools needed to explore the model.\n",
+ "# Data visualization tool.\n",
  "import matplotlib.pyplot as plt\n",
+ "\n",
+ "# Has multi-dimensional arrays and matrices. Has a large collection of\n",
+ "# mathematical functions to operate on these arrays.\n",
  "import numpy as np\n",
- "import pandas as pd\n",
- "import seaborn as sns"
+ "\n",
+ "# Data manipulation and analysis.\n",
+ "import pandas as pd"
  ]
  },
  {
@@ -146,11 +149,11 @@
  "\n",
  "First create the agent. As the tutorial progresses, more functionality will be added to the agent.\n",
  "\n",
- "**Background:** Agents are the individual entities that act in the model.IT is a good modeling practice to make certain each Agent can be uniquely identified.\n",
+ "**Background:** Agents are the individual entities that act in the model. It is a good modeling practice to make certain each Agent can be uniquely identified.\n",
  "\n",
- "**Model Specific Information:** Agents are the individuals that exchange money, in this case the amount of money an individual agent has is represented as wealth. Additionally, agents each have a unique identifier.\n",
+ "**Model-specific information:** Agents are the individuals that exchange money, in this case the amount of money an individual agent has is represented as wealth. Additionally, agents each have a unique identifier.\n",
  "\n",
- "**Technical Details:** This is done by creating a new class (or object) that extends `mesa.Agent` creating a subclass of the `Agent` class from mesa. The new class is named `MoneyAgent`. The technical details about the agent object can be found in the [mesa repo](https://github.com/projectmesa/mesa/blob/main/mesa/agent.py).\n",
+ "**Code implementation:** This is done by creating a new class (or object) that extends `mesa.Agent` creating a subclass of the `Agent` class from mesa. The new class is named `MoneyAgent`. The technical details about the agent object can be found in the [mesa repo](https://github.com/projectmesa/mesa/blob/main/mesa/agent.py).\n",
  "\n",
  "\n",
  "The `MoneyAgent` class is created with the following code:\n"
@@ -188,13 +191,13 @@
  "source": [
  "### Create Model\n",
  "\n",
- "Next create the model. Again as the tutorial progresses, more functionality will be added to the model.\n",
+ "Next, create the model. Again, as the tutorial progresses, more functionality will be added to the model.\n",
  "\n",
- "**Background:** The model can be visualized as a grid containing all the agents. The model creates, holds and manages all the agents on the grid. Running the model will work through all the time cycles.\n",
+ "**Background:** The model can be visualized as a grid containing all the agents. The model creates, holds and manages all the agents on the grid. The model evolves in discrete time steps.\n",
  "\n",
- "**Model Specific Information:** When a model is created the number of agents within the model is specified. The model then creates the agents and places them on the grid. The model also contains a scheduler which controls the order in which agents are activated. The scheduler is also responsible for advancing the model by one step. The model also contains a data collector which collects data from the model. These topics will be covered in more detail later in the tutorial.\n",
+ "**Model-specific information:** When a model is created the number of agents within the model is specified. The model then creates the agents and places them on the grid. The model also contains a scheduler which controls the order in which agents are activated. The scheduler is also responsible for advancing the model by one step. The model also contains a data collector which collects data from the model. These topics will be covered in more detail later in the tutorial.\n",
  "\n",
- "**Technical Details:** This is done by creating a new class (or object) that extends `mesa.Model` creating a subclass of the `Model` class from mesa. The new class is named `MoneyModel`. The technical details about the agent object can be found in the [mesa repo](https://github.com/projectmesa/mesa/blob/main/mesa/model.py).\n",
+ "**Code implementation:** This is done by creating a new class (or object) that extends `mesa.Model` creating a subclass of the `Model` class from mesa. The new class is named `MoneyModel`. The technical details about the agent object can be found in the [mesa repo](https://github.com/projectmesa/mesa/blob/main/mesa/model.py).\n",
  "\n",
  "The `MoneyModel` class is created with the following code:"
  ]
@@ -225,15 +228,15 @@
  "metadata": {},
  "source": [
  "### Adding the Scheduler\n",
- "Now the model will me modified to add a scheduler.\n",
+ "Now the model will be modified to add a scheduler.\n",
  "\n",
  "**Background:** The scheduler controls the order in which agents are activated, causing the agent to take their defined action. The scheduler is also responsible for advancing the model by one step. A step is the smallest unit of time in the model, and is often referred to as a tick. The scheduler can be configured to activate agents in different orders. This can be important as the order in which agents are activated can impact the results of the model [Comer2014]. At each step of the model, one or more of the agents -- usually all of them -- are activated and take their own step, changing internally and/or interacting with one another or the environment.\n",
  "\n",
- "**Model Specific Information:** A new class is named `RandomActivationByAgent` is created which extends `mesa.time.RandomActivation` creating a subclass of the `RandomActivation` class from mesa. This class activates all the agents once per step, in random order. Every agent is expected to have a ``step`` method. The step method is the action the agent takes when it is activated by the model schedule. We add an agent to the schedule using the `add` method; when we call the schedule's `step` method, the model shuffles the order of the agents, then activates and executes each agent's ```step``` method. The scheduler is then added to the model.\n",
+ "**Model-specific information:** A new class is named `RandomActivationByAgent` is created which extends `mesa.time.RandomActivation` creating a subclass of the `RandomActivation` class from Mesa. This class activates all the agents once per step, in random order. Every agent is expected to have a ``step`` method. The step method is the action the agent takes when it is activated by the model schedule. We add an agent to the schedule using the `add` method; when we call the schedule's `step` method, the model shuffles the order of the agents, then activates and executes each agent's ```step``` method. The scheduler is then added to the model.\n",
  "\n",
- "**Technical Details:** The technical details about the timer object can be found in the [mesa repo](https://github.com/projectmesa/mesa/blob/main/mesa/time.py). Mesa offers a few different built-in scheduler classes, with a common interface. That makes it easy to change the activation regime a given model uses, and see whether it changes the model behavior. The details pertaining to the scheduler interface can be located the same [mesa repo](https://github.com/projectmesa/mesa/blob/main/mesa/time.py).\n",
+ "**Code implementation:** The technical details about the timer object can be found in the [mesa repo](https://github.com/projectmesa/mesa/blob/main/mesa/time.py). Mesa offers a few different built-in scheduler classes, with a common interface. That makes it easy to change the activation regime a given model uses, and see whether it changes the model behavior. The details pertaining to the scheduler interface can be located the same [mesa repo](https://github.com/projectmesa/mesa/blob/main/mesa/time.py).\n",
  "\n",
- "With that in mind, the MoneyAgent code is modified below to visually show when a new agent is created. The MoneyModel code is modified by adding the RandomActivation method to the model. with the scheduler added looks like this:"
+ "With that in mind, the `MoneyAgent` code is modified below to visually show when a new agent is created. The MoneyModel code is modified by adding the RandomActivation method to the model. with the scheduler added looks like this:"
  ]
  },
  {
@@ -254,7 +257,7 @@
  " # Pass the parameters to the parent class.\n",
  " super().__init__(unique_id, model)\n",
  "\n",
- " # Create the agent's variable and set the initial values.\n",
+ " # Create the agent's attribute and set the initial values.\n",
  " self.wealth = 1\n",
  "\n",
  " def step(self):\n",
@@ -268,7 +271,7 @@
  "\n",
  " def __init__(self, N):\n",
  " self.num_agents = N\n",
- " # Scheduler is created and added to the model\n",
+ " # Create scheduler and assign it to the model\n",
  " self.schedule = mesa.time.RandomActivation(self)\n",
  "\n",
  " # Create agents\n",
@@ -289,7 +292,7 @@
  "metadata": {},
  "source": [
  "### Running the Model\n",
- "A basic model has now been created. The model can be run by creating a model object and calling the step method. The model will run for one step and print the unique_id of each agent. The model can be run for multiple steps by calling the step method multiple times.\n",
+ "A basic model has now been created. The model can be run by creating a model object and calling the step method. The model will run for one step and print the unique_id of each agent. You may run the model for multiple steps by calling the step method multiple times.\n",
  "\n",
  "Note: If you are using `.py` (script) files instead of `.ipynb` (Jupyter), the common convention is\n",
  "to have a `run.py` in the same directory as your model code. You then (1) import the ``MoneyModel`` class,\n",
@@ -408,13 +411,13 @@
  "source": [
  "### Agent Step\n",
  "\n",
- "Looping back to the MoneyAgent the actual step process is now going to be created.\n",
+ "Returning back to the MoneyAgent the actual step process is now going to be created.\n",
  "\n",
  "**Background:** This is where the agent's behavior as it relates to each step or tick of the model is defined.\n",
  "\n",
- "**Model Specific Information:** In this case, the agent will check its wealth, and if it has money, give one unit of it away to another random agent.\n",
+ "**Model-specific information:** In this case, the agent will check its wealth, and if it has money, give one unit of it away to another random agent.\n",
  "\n",
- "**Technical Details:** The agent's step method is called by the scheduler during each step of the model. To allow the agent to choose another agent at random, we use the `model.random` random-number generator. This works just like Python's `random` module, but with a fixed seed set when the model is instantiated, that can be used to replicate a specific model run later."
+ "**Code implementation:** The agent's step method is called by the scheduler during each step of the model. To allow the agent to choose another agent at random, we use the `model.random` random-number generator. This works just like Python's `random` module, but with a fixed seed set when the model is instantiated, that can be used to replicate a specific model run later."
  ]
  },
  {