Create World

Specific Patches

In NetLogo, to set specific patches at given coordinates to a certain color, you’ll want to directly reference those patches by their coordinates rather than using a random selection method like n-of. Here’s a simple procedure to change the patches at (-1, 1) and (-2, 2) to green and set their degree to 2:

to go-green
  ask patch -1 1 [
    set pcolor green
    set degree 2
  ]
  ask patch -2 2 [
    set pcolor green
    set degree 2
  ]
end

You can then call the procedure go-green in the Command Center, or as part of any other procedure, to change the color of the specified patches.

If “degree” is a property that you want to set, make sure that it is already defined as a patch variable. If not, you need to declare it in the patches-own section:

patches-own [degree]

This line should go at the top of your code, usually right below the globals section, if you have such declarations. Make sure to include this if you haven’t already defined degree.

globals [EduInc]
turtles-own [U education income]
patches-own [degree]

to setup
  clear-all
  create-turtles 100 [
    set U random-normal 0 1
    setxy random-normal 0 5 random-normal 0 5
  ]
  universities
  reset-ticks
end

to universities
  ask patch -10 1 [
    set pcolor green
    set degree 2
  ]
  ask patch 10 1 [
    set pcolor green
    set degree 2
  ]
end

Random-normal location

to setup
  clear-all
  create-turtles 100 [
    set U random-normal 0 1
    setxy random-normal 0 1 random-normal 0 1
  ]
  universities
  reset-ticks
end

Sprout

In NetLogo, the sprout command is used to create new turtles on a specific patch. This can be particularly useful when you want to initialize or spawn agents from specific locations in your model. Here’s how you can use the sprout command effectively:

Basic Usage of sprout

The general syntax of the sprout command is as follows:

ask patches [
  sprout number [ commands ]
]

• number: Specifies how many turtles to create on each patch.
• commands: Optional commands that can be executed by the newly created turtles immediately after they are created.

Example

Here is a simple example that demonstrates how to use sprout to create turtles on green patches only:

to setup
  clear-all
  ;; first color some patches green
  ask patches [
    if random 100 < 10 [  ;; randomly choose about 10% of patches
      set pcolor green
    ]
  ]
  ;; now sprout turtles on green patches
  ask patches with [pcolor = green] [
    sprout 3 [  ;; sprout 3 turtles on each green patch
      set color blue  ;; give them a color
      set size 2       ;; adjust their size
    ]
  ]
  reset-ticks
end

Explanation

• Setup Procedure: This procedure sets up the environment initially.

• Coloring Patches: We color about 10% of the patches green randomly.

• ask patches with [pcolor = green]: This ask block targets only the green patches for the sprout operation.

• sprout 3: On each of these green patches, 3 turtles are created.

• [set color blue set size 2]: These turtles immediately run these commands to set their color to blue and increase their size to 2.

Running the Model

1. Setup: Call setup from the Interface tab to initialize the model and create the turtles on the green patches.
2. Go: Typically, you would have a go procedure to continue running your simulation or apply further logic.

This is a foundational example. Depending on your model’s complexity, you can modify and enhance the sprout command usage to meet your specific requirements.

Feel free to ask more questions if you need further assistance!

Grid

To create turtles in specific regions of the grid in NetLogo based on certain conditions, you can use conditions within the ask command to target specific patches. You can then use sprout to create turtles on those targeted patches. Here’s how you can do this for the top left and bottom right regions of the grid:

Example Setup

Let’s assume you want to create turtles in the top left quadrant if a certain condition is met, and in the bottom right quadrant if a different condition is met. Here’s an illustrative example:

to setup
  clear-all

  ;; Define the condition values you want to check
  let some-value 50  ;; This is an arbitrary value for demonstration

  if some-value > 30 [
    ;; Create turtles in the top left quadrant
    ask patches with [pxcor < max-pxcor / 2 and pycor > max-pycor / 2] [
      if random-float 1 < 0.1 [  ;; Randomly select some percentage of these patches
        sprout 1 [  ;; Create 1 turtle on selected patches
          set color blue
          set size 1.5
        ]
      ]
    ]
  ]

  if some-value <= 30 [
    ;; Create turtles in the bottom right quadrant
    ask patches with [pxcor > max-pxcor / 2 and pycor < max-pycor / 2] [
      if random-float 1 < 0.1 [
        sprout 1 [
          set color red
          set size 1.5
        ]
      ]
    ]
  ]

  reset-ticks
end

Explanation

• max-pxcor and max-pycor:
  • These are NetLogo built-in variables that represent the maximum x-coordinate and y-coordinate respectively of the grid.
  • By dividing them by two, you can effectively split the grid into quadrants.
• Turtle Creation in Quadrants:
  • Top Left Quadrant: Targeted by patches with pxcor < max-pxcor / 2 and pycor > max-pycor / 2.
  • Bottom Right Quadrant: Targeted by patches with pxcor > max-pxcor / 2 and pycor < max-pycor / 2.
• Conditional Logic:
  • The example above checks a variable some-value. If it is greater than 30, turtles are created in the top left. If less than or equal to 30, turtles are created in the bottom right.
• Randomness:
  • if random-float 1 < 0.1: This adds randomness to the creation of turtles so that not every patch in the specified region will have a turtle. Adjust the 0.1 as needed to control the density of turtle creation.

With these tools and commands, you can integrate more complex conditions and procedures tailored to the needs of your specific model. If you need further modifications or explanations, feel free to ask!

Certain patches

In NetLogo, if you want to create turtles on specific patches defined by their coordinates, you can simply use the patch-at primitive to target those patches and use sprout to create turtles. Here is how you can achieve that:

Step-by-Step Example

Let’s say you want to create turtles at specific patches identified by their coordinates. You can define these coordinates in a list and then iterate over them to create the turtles.

to setup
  clear-all

  ;; Define a list of specific patch coordinates
  ;; Each sublist contains an x, y coordinate pair
  let target-patches [[-5 5] [2 -3] [4 4] [-7 -7]]
  
  ;; Iterate through the list of coordinates
  foreach target-patches [
    coords -> 
    ;; Extract the x and y coordinates
    let x first coords
    let y last coords
    
    ;; Target the patch and create a turtle
    ask patch x y [
      sprout 1 [
        set color green
        set size 1.5
      ]
    ]
  ]

  reset-ticks
end

Explanation

1. Defining Coordinates:
   • target-patches is a list containing sublists of x and y coordinates where you want the turtles to be created.
2. foreach Loop:
   • The foreach primitive is used to iterate over each sublist (each coordinate pair) in target-patches.
3. Extracting Coordinates:
   • Within the loop, let x first coords and let y last coords are used to extract the x and y values from each coordinate sublist.
4. Targeting Specific Patches:
   • ask patch x y: This targets the patch located at the coordinates (x, y).
5. Creating Turtles:
   • sprout 1: This creates one turtle on the specified patch.
   • You can set properties of the turtles, like color and size, within the square brackets following sprout.

This setup allows you to precisely control where turtles are created by specifying exact patch locations. You can extend or modify the list of coordinates as needed for your model. If you have further questions or want to add more features, feel free to ask!

Wait command

The wait command in NetLogo is used to pause the execution of a turtle or observer for a specified amount of time, measured in seconds. This can be helpful if you want to slow down the actions in your simulation to better observe what’s happening, or to simulate delays in processes.

Here’s a detailed explanation of how the wait command works:

Usage

• Syntax:

  wait number

• number: This is the amount of time, in seconds, you want the execution to pause. It can be a whole number or a decimal for fractions of a second.

Examples

1. Wait for 1 second:

   wait 1

2. Wait for half a second:

   wait 0.5

Behavior

• The wait command can be used within any procedure, whether it is meant for the observer, turtles, or patches.

• While one agent or the observer is in a wait period, other agents or the observer are not affected unless you explicitly code otherwise in a synchronous manner. This means you could have different agents waiting for different periods independently.

• Using wait can be helpful when debugging or demonstrating a model, as it allows observers to see each step clearly.

Considerations

• Performance: Excessive use of the wait command can significantly slow down your model if running for a large number of agents.

• Real-time simulations: In simulations that aim to run in real-time or near real-time, careful consideration of how wait affects timing and perceptual flow is necessary.

• Testing and Learning: wait is particularly useful in educational settings to illustrate model dynamics step-by-step.

Common Use Cases

• Animations: Slowing down movement patterns to observe complex interactions.

• Sequential Events: modeling processes where each step should be visible, like decision-making processes in agent-based models.

• Instructional Models: Providing pauses so that learners can follow along with explanations tied to specific model states or actions.

While wait can be visually instructive, keep in mind its impact on the flow and performance of the model to strike a balance between clarity and efficiency.