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patcher_continuous_state [2018/07/04 15:32]
britaldo
patcher_continuous_state [2026/07/14 19:25] (current)
chrystian Fix functor documentation.
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 +===== Patcher Continuous State =====
 +
 ===== Description ===== ===== Description =====
  
-This functor treats cell values (landscape map) as stocks ​of a continuous variable by multiplying the cell values per its spatial dimension (ha). It then harvests quantities of these cells based on a total demand quantity (quota) and a probability map for choosing the cells to be harvested (e.g. profitability),​ resulting in a depleted map of stock values. The harvest is split in patches whose dimension distribution and forms are inputs.+Generate new patches ​of a certain class or category.
  
 ===== Inputs ===== ===== Inputs =====
  
 ^ Name ^ Type ^ Description ^ ^ Name ^ Type ^ Description ^
-| Landscape ​ | [[Categorical ​Map Type]] ​ | Map of classes or categories.  |+Continuous ​Landscape | [[Map Type]] ​ | Map of stocks. Each cell represent the amount of stock stored (in units per hectare).  |
 | Probabilities ​ | [[Map Type]] ​ | Map of spatial probabilities. ​ | | Probabilities ​ | [[Map Type]] ​ | Map of spatial probabilities. ​ |
-Changes  ​| [[Change Matrix ​Type]] ​ | Matrix of number of changes.  | +Quota | [[Real Value Type]] ​ | Accumulation quota (in units).  | 
-Transition Parameters  ​| [[Transition Function Parameter Matrix ​Type]] ​ | Matrix of transition function parameters consisting of Mean Patch size, Patch size variance, and isometry. By varying these parameters, various spatial patterns can be reproduced ​(see examples on [[patterns_of_change|Patterns of Change]]). Increase the patch size for a less-fragmented landscape. Increase the patch size variance for a more diverse landscape, and set isometry greater than one for more isometric patches. Tipically, the isometry ​defines the aggregation level of a patch. Assuming that v is the current isometry value, 0<v<1 forces disaggregation,​ v>1 forces aggregation and v=1 is ignored. The mean patch size and the variance define the size of the new patches.  |+Mean | [[Real Value Type]] ​ | Patch mean (in hectares). ​ | 
 +| Variance | [[Real Value Type]]  | Patch variance (in hectares).  | 
 +| Isometry | [[Real Value Type]] ​ | Patch isometry. ​ |
  
 ===== Optional Inputs ===== ===== Optional Inputs =====
  
 ^ Name ^ Type ^ Description ^ Default Value ^ ^ Name ^ Type ^ Description ^ Default Value ^
-| Neighbor Window Lines  | [[Positive Integer Value Type]] ​ | Number of lines and columns ​of the neighbor ​search window. ​Patches can be created in a diffuse way by increasing the neighbor search window to values greater than 3 for lines and columns; a 3x3 window corresponds to the Moore neighborhood.  ​| 3  | +| Neighbor Window Lines  | [[Positive Integer Value Type]] ​ | Number of lines of the neighborhood ​search window. | 3  | 
-| Neighbor Window Columns ​ | [[Positive Integer Value Type]] ​ | :::  | 3  |+| Neighbor Window Columns ​ | [[Positive Integer Value Type]] ​ | Number of lines of the neighborhood search window. ​ | 3  |
 | Prune Factor ​ | [[Real Value Type]] ​ | A multiple of the quantity of cells to be changed. This is used in order to specify the size of the vector where cells are ranked for subsequent draw. Prune factor multiplies the expected number of cells to be changed to set the quantity of possible cells, based on their spatial probability,​ that take part in the selection mechanism of new patch nuclei. Typically, increasing this value also increases the stochasticity of selection of patch pivot cells. ​ | 10  | | Prune Factor ​ | [[Real Value Type]] ​ | A multiple of the quantity of cells to be changed. This is used in order to specify the size of the vector where cells are ranked for subsequent draw. Prune factor multiplies the expected number of cells to be changed to set the quantity of possible cells, based on their spatial probability,​ that take part in the selection mechanism of new patch nuclei. Typically, increasing this value also increases the stochasticity of selection of patch pivot cells. ​ | 10  |
  
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 ^ Name ^ Type ^ Description ^ ^ Name ^ Type ^ Description ^
-Changed ​Landscape ​ | [[ Categorical ​Map Type]] ​ | Map of classes or categories.  | +Modified Continuous ​Landscape | [[ Map Type]] ​ | Map of remaining stocks.  | 
-Corroded ​Probabilities ​ | [[Map Type]] ​ | Map of depleted spatial probabilities. Where a change occurred, the probability value is set to zero.  | +Modified ​Probabilities | [[Map Type]] ​ | Map of depleted spatial probabilities. ​ | 
-| Remaining ​Changes  ​| [[Change Matrix ​Type]] ​ | Matrix of number of remaining number of changes for each type of transition in case the functor does not succeed in making all the specified changes.  ​|+| Remaining ​Quota | [[Real Value Type]] ​ | ::: |
  
 ===== Group ===== ===== Group =====
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 [[Functor List#​Simulation | Simulation]] [[Functor List#​Simulation | Simulation]]
  
-===== Notes =====  
- 
-Dinamica EGO uses as a local [[wp>​Cellular_automaton|CA]] rule in its transition engine composed of two complementary transition functions, the Expander and the Patcher. Dinamica EGO splits the cell selection mechanism into these processes. The first process is dedicated only to the expansion or contraction of previous patches of a certain class, and it is called Expander. The second process is designed to generate or form new patches through a seeding mechanism, and it is called Patcher. The Patch Isometry is a number varying from 0 to 2. The patches assume a more isometric form as this number increases. The size of new patches and expansion fringes are set according to a lognormal probability distribution. Therefore, it is necessary to specify the parameters of this distribution represented by the mean and variance of the patch sizes to be formed. The combination of Dinamica EGO's transition function presents numerous possibilities with respect to the generation and evolvement of spatial patterns of change. ​ 
- 
-The Patcher function searches for cells around a chosen location for a combined transition. This is done firstly by electing the core cell of the new patch and then selecting a specific number of cells around the core cell, according to their P<​sub>​ij</​sub>​ transition probabilities,​ as depicted below: 
- 
-[{{ :​patcher001.gif?​nolink&​ |The Patcher algorithm for choosing neighboring cells.}}] 
- 
-See [[patterns_of_change|Patterns of Change]] for different examples of patches generated using [[Patcher]] and [[Expander]]. 
  
 ===== Internal Name =====  ===== Internal Name ===== 
  
-Patcher Continuous State+PatcherContinuousState