Netlogo 中的多尺度景观（小补丁和大补丁组）
Multi-scale landscape in Netlogo (small patches and larger patch groupings)
我试图表示一个多尺度环境，其中我有代表景观中高价值区域的大块和具有本地信息的小块。例如。我想要 1km^2 比例的雪数据，但我也想要更大的补丁 (9km^2) 来总结大规模信息。我的每个大补丁都有一个与其邻居不同的变量值，但变量值可能会在其他补丁的整个景观中重复。我正在为我的海龟寻找最直接的方法来识别大型斑块之间的差异。我曾想过创建补丁集，但我不确定如何解决变量值在不同补丁中重复的问题。非常感谢任何帮助。
编辑：我创建了一个与大比例尺栅格具有相同补丁结构的栅格，并使用它分配 "patch-id's"，这样世界上就不再有变量重复了。我仍在努力让海龟将这些较大的补丁识别为分组实体。
这可能不是最好的方法，但我认为它会奏效。您可以让区域拥有多个变量，例如 "large-region-unique-id" 和 "small-region-unique-id"，并在设置所有这些变量的地方进行一次传递。那么乌龟只需要看一个补丁就可以知道它属于哪个大小区域。
如果您还制作了一种名为 "regions" 的代理（比方说），您可以拥有区域自有变量和唯一区域 ID。 （实际上，代理人的电话号码会起作用
为此）
应该对信息进行编码，以便移动的乌龟可以轻松查找相关信息。
breed [ large-regions large-region ]
large-regions-own [
terrain-type
large-scale-variables
...
(who)
]
breed [ small-regions small-region ]
small-regions-own [
snow-cover
small-scale-variables
...
(who)
]
patches-own [
large-scale-region-who ;; the id (who) of the large-scale-region the patch is in
small-scale-region-who ;; the id (who) of the small-scale-region the patch is in
...
]
然后一只海龟可以向补丁请求相关的 who 信息，并使用它从更大的 "patches".
中查找数据
这可能是这样的
print (word " hilly region count: " count large-regions with [terrain = "hilly"] )
print (word " deep snow count: " count small-regions with [snow-cover > 75])
;; how about highlighting patches that are mountainous with deep snow?
no-display
ask patches [
set terrain-type ""
set my-snow-cover -1
set srw small-scale-region-who
if srw > 0 [set my-snow-cover [snow-cover] of (small-region srw)]
set lrw large-scale-region-who
if lrw > 0
[ set terrain-type [terrain] of large-region lrw]
if-else (terrain-type = "mountain") and (my-snow-cover > 75)
[ set pcolor white ]
[ set pcolor black ]
]
display
print " The mountainous terrain with deep snow-cover is shown in white "
你评论了我的第一个回答
My main issue is that I need to run a "find max-one-of
neigboring-large-patches [large-scale-variable]" so I need my turtles
to understand what the neighboring large-patches are and be able to
read them as units, if that makes sense. I can't quite figure out how
to incorporate that into your answer, any thoughts?
这是如何做到这一点。这段代码又快又草率，但它说明了这一点。
让大区域具有创建期间生成的 x 和 y 值。基本上，这些存储覆盖视口的大区域网格的列号和行号。
breed [ large-regions large-region ]
large-regions-own [
terrain
region-color
population
x
y
]
然后，从概念上讲，一个区域的相邻区域的 x 和 y 值将在该区域的 x 和 y 值的 +/- 1 范围内，因此您可以这样识别它们。
为了以 space 为代价简化编码，当我生成区域时，我还将该区域的唯一标识符 (who) 及其 x 和 y 值存储到该区域的每个补丁中，在变量中lrx 和 lry.
patches-own [
large-region-who
lrx
lry
]
根据您的要求找到人口最大值的相邻大区域的核心如下。我编写此代码是为了提高调试速度，而不是为了优雅，因此可以大大清理它。完整的源代码有许多打印语句，可以有效地注释解决您请求的搜索的每个步骤。
这环顾四周（补丁 0 0），从该补丁中找到有关大区域 x 和 y 的信息，生成具有附近 x 和 y 值的大区域代理集，做最大[人口]搜索该集合以提取人口最多的区域。它还将请求补丁着色为黑色，将局部大区域着色为蓝色，并将最大人口邻居着色为红色。
它大部分都有效——大区域从它们应该在的位置偏移了一个补丁——但这说明了这一点。 运行设置并亲自去看看。
这是可以玩的（难看的）代码。有趣的问题。您也可以轻松地将其扩展到小区域，并同时工作。享受吧！
globals [
large-region-size
]
breed [ large-regions large-region ]
large-regions-own [
terrain
region-color
population
x
y
]
patches-own [
large-region-who
lrx
lry
]
to setup
clear-all
set large-region-size 5
no-display
make-large-regions
ask patches [ set pcolor white ]
display
ask large-regions [ set hidden? true]
print (word " hilly region count: " count large-regions with [terrain = "hilly"] )
;; print (word " deep snow count: " count small-regions with [snow-cover > 75])
reset-ticks
end
to go
ask patches [ set pcolor white]
; ;; lets examine the large-regions
; print " large region xvals "
; let xvals [ ]
; ask large-regions [ set xvals fput x xvals ]
; set xvals remove-duplicates xvals
; show xvals
; print " "
; print " patch lrx values: "
; set xvals [ ]
; ask patches [ set xvals fput lrx xvals ]
; set xvals remove-duplicates xvals
; show xvals
; print "========================================="
print " let's examine large-regions around the patch at 0 0 "
let x-spot 0
let y-spot 0
print ( word " looking for large-regions with max population bordering the following patch " x-spot " " y-spot)
; ask n-of 1 patches [ set x-spot pxcor set y-spot pycor print (word "selected patch " x-spot ", " y-spot )]
let home-who [ large-region-who] of patch x-spot y-spot
print (word "home-region-who is " home-who)
print " "
;; thinking ahead, we have coded the x and y values of the large region around us directly into the patch variables
let home-x [ lrx ] of patch x-spot y-spot
let home-y [ lry ] of patch x-spot y-spot
print (word "this blue home region has x=" home-x " and y=" home-y )
ask patches with [lrx = home-x and lry = home-y] [ set pcolor blue ]
ask patch x-spot y-spot [ set pcolor black ]
let home-neighbor-set large-regions with [
( x >= ( home-x - 1 )) and ( x <= ( home-x + 1) ) and (y >= ( home-y - 1 ) ) and ( y <= ( home-y + 1 ) ) ]
print "count of home-neighbor-set is "
print count large-regions with [
( x >= ( home-x - 1 )) and ( x <= ( home-x + 1) ) and (y >= ( home-y - 1 ) ) and ( y <= ( home-y + 1) ) ]
print " "
print "here is that set "
show home-neighbor-set
print " "
ask home-neighbor-set [ print (word "Large region with who = " who " has population " population )]
let big-boy max-one-of home-neighbor-set [ population]
show big-boy
print ( word " Neighboring red large-region with largest population is " big-boy " with population " [population] of big-boy )
let bbx 0
let bby 0
let bwho 0
ask big-boy [ set bbx x set bby y set bwho who]
ask patches with [lrx = bbx and lry = bby] [ set pcolor red ]
tick
end
to make-large-regions ;; for testing
let px min-pxcor
let py min-pycor
let region-id -1 ;; missing
let mysize large-region-size
let stopper 0
while [px < max-pxcor] [
while [py < max-pycor] [
if stopper > 300 [ stop ] ;; stops making large regions
set stopper stopper + 1
let xcode round ( ( px + 1) / 5)
let ycode round ( ( py + 1) / 5)
;; make a new region
let decolor one-of [ red blue yellow green ]
create-large-regions 1 [
set terrain one-of ["hilly" "flat" "mountain" "water" "swamp"]
set region-id who
set population random 1000
set x xcode
set y ycode
set region-color decolor
]
;; large region is defined, update the patches in that region
ask patches with [ (abs (pxcor - px) < (mysize / 2) )
and (abs (pycor - py) < (mysize / 2) )] [
set pcolor decolor
set large-region-who region-id
set lrx xcode
set lry ycode
]
set py py + mysize
]
if py > max-pycor [
set py min-pycor
set px px + mysize]
]
end
我试图表示一个多尺度环境，其中我有代表景观中高价值区域的大块和具有本地信息的小块。例如。我想要 1km^2 比例的雪数据，但我也想要更大的补丁 (9km^2) 来总结大规模信息。我的每个大补丁都有一个与其邻居不同的变量值，但变量值可能会在其他补丁的整个景观中重复。我正在为我的海龟寻找最直接的方法来识别大型斑块之间的差异。我曾想过创建补丁集，但我不确定如何解决变量值在不同补丁中重复的问题。非常感谢任何帮助。
编辑：我创建了一个与大比例尺栅格具有相同补丁结构的栅格，并使用它分配 "patch-id's"，这样世界上就不再有变量重复了。我仍在努力让海龟将这些较大的补丁识别为分组实体。
这可能不是最好的方法，但我认为它会奏效。您可以让区域拥有多个变量，例如 "large-region-unique-id" 和 "small-region-unique-id"，并在设置所有这些变量的地方进行一次传递。那么乌龟只需要看一个补丁就可以知道它属于哪个大小区域。
如果您还制作了一种名为 "regions" 的代理（比方说），您可以拥有区域自有变量和唯一区域 ID。 （实际上，代理人的电话号码会起作用 为此）
应该对信息进行编码，以便移动的乌龟可以轻松查找相关信息。
breed [ large-regions large-region ]
large-regions-own [
terrain-type
large-scale-variables
...
(who)
]
breed [ small-regions small-region ]
small-regions-own [
snow-cover
small-scale-variables
...
(who)
]
patches-own [
large-scale-region-who ;; the id (who) of the large-scale-region the patch is in
small-scale-region-who ;; the id (who) of the small-scale-region the patch is in
...
]
然后一只海龟可以向补丁请求相关的 who 信息，并使用它从更大的 "patches".
中查找数据这可能是这样的
print (word " hilly region count: " count large-regions with [terrain = "hilly"] )
print (word " deep snow count: " count small-regions with [snow-cover > 75])
;; how about highlighting patches that are mountainous with deep snow?
no-display
ask patches [
set terrain-type ""
set my-snow-cover -1
set srw small-scale-region-who
if srw > 0 [set my-snow-cover [snow-cover] of (small-region srw)]
set lrw large-scale-region-who
if lrw > 0
[ set terrain-type [terrain] of large-region lrw]
if-else (terrain-type = "mountain") and (my-snow-cover > 75)
[ set pcolor white ]
[ set pcolor black ]
]
display
print " The mountainous terrain with deep snow-cover is shown in white "
你评论了我的第一个回答
My main issue is that I need to run a "find max-one-of neigboring-large-patches [large-scale-variable]" so I need my turtles to understand what the neighboring large-patches are and be able to read them as units, if that makes sense. I can't quite figure out how to incorporate that into your answer, any thoughts?
这是如何做到这一点。这段代码又快又草率，但它说明了这一点。
让大区域具有创建期间生成的 x 和 y 值。基本上，这些存储覆盖视口的大区域网格的列号和行号。
breed [ large-regions large-region ]
large-regions-own [
terrain
region-color
population
x
y
]
然后，从概念上讲，一个区域的相邻区域的 x 和 y 值将在该区域的 x 和 y 值的 +/- 1 范围内，因此您可以这样识别它们。
为了以 space 为代价简化编码，当我生成区域时，我还将该区域的唯一标识符 (who) 及其 x 和 y 值存储到该区域的每个补丁中，在变量中lrx 和 lry.
patches-own [
large-region-who
lrx
lry
]
根据您的要求找到人口最大值的相邻大区域的核心如下。我编写此代码是为了提高调试速度，而不是为了优雅，因此可以大大清理它。完整的源代码有许多打印语句，可以有效地注释解决您请求的搜索的每个步骤。
这环顾四周（补丁 0 0），从该补丁中找到有关大区域 x 和 y 的信息，生成具有附近 x 和 y 值的大区域代理集，做最大[人口]搜索该集合以提取人口最多的区域。它还将请求补丁着色为黑色，将局部大区域着色为蓝色，并将最大人口邻居着色为红色。
它大部分都有效——大区域从它们应该在的位置偏移了一个补丁——但这说明了这一点。 运行设置并亲自去看看。
这是可以玩的（难看的）代码。有趣的问题。您也可以轻松地将其扩展到小区域，并同时工作。享受吧！
globals [
large-region-size
]
breed [ large-regions large-region ]
large-regions-own [
terrain
region-color
population
x
y
]
patches-own [
large-region-who
lrx
lry
]
to setup
clear-all
set large-region-size 5
no-display
make-large-regions
ask patches [ set pcolor white ]
display
ask large-regions [ set hidden? true]
print (word " hilly region count: " count large-regions with [terrain = "hilly"] )
;; print (word " deep snow count: " count small-regions with [snow-cover > 75])
reset-ticks
end
to go
ask patches [ set pcolor white]
; ;; lets examine the large-regions
; print " large region xvals "
; let xvals [ ]
; ask large-regions [ set xvals fput x xvals ]
; set xvals remove-duplicates xvals
; show xvals
; print " "
; print " patch lrx values: "
; set xvals [ ]
; ask patches [ set xvals fput lrx xvals ]
; set xvals remove-duplicates xvals
; show xvals
; print "========================================="
print " let's examine large-regions around the patch at 0 0 "
let x-spot 0
let y-spot 0
print ( word " looking for large-regions with max population bordering the following patch " x-spot " " y-spot)
; ask n-of 1 patches [ set x-spot pxcor set y-spot pycor print (word "selected patch " x-spot ", " y-spot )]
let home-who [ large-region-who] of patch x-spot y-spot
print (word "home-region-who is " home-who)
print " "
;; thinking ahead, we have coded the x and y values of the large region around us directly into the patch variables
let home-x [ lrx ] of patch x-spot y-spot
let home-y [ lry ] of patch x-spot y-spot
print (word "this blue home region has x=" home-x " and y=" home-y )
ask patches with [lrx = home-x and lry = home-y] [ set pcolor blue ]
ask patch x-spot y-spot [ set pcolor black ]
let home-neighbor-set large-regions with [
( x >= ( home-x - 1 )) and ( x <= ( home-x + 1) ) and (y >= ( home-y - 1 ) ) and ( y <= ( home-y + 1 ) ) ]
print "count of home-neighbor-set is "
print count large-regions with [
( x >= ( home-x - 1 )) and ( x <= ( home-x + 1) ) and (y >= ( home-y - 1 ) ) and ( y <= ( home-y + 1) ) ]
print " "
print "here is that set "
show home-neighbor-set
print " "
ask home-neighbor-set [ print (word "Large region with who = " who " has population " population )]
let big-boy max-one-of home-neighbor-set [ population]
show big-boy
print ( word " Neighboring red large-region with largest population is " big-boy " with population " [population] of big-boy )
let bbx 0
let bby 0
let bwho 0
ask big-boy [ set bbx x set bby y set bwho who]
ask patches with [lrx = bbx and lry = bby] [ set pcolor red ]
tick
end
to make-large-regions ;; for testing
let px min-pxcor
let py min-pycor
let region-id -1 ;; missing
let mysize large-region-size
let stopper 0
while [px < max-pxcor] [
while [py < max-pycor] [
if stopper > 300 [ stop ] ;; stops making large regions
set stopper stopper + 1
let xcode round ( ( px + 1) / 5)
let ycode round ( ( py + 1) / 5)
;; make a new region
let decolor one-of [ red blue yellow green ]
create-large-regions 1 [
set terrain one-of ["hilly" "flat" "mountain" "water" "swamp"]
set region-id who
set population random 1000
set x xcode
set y ycode
set region-color decolor
]
;; large region is defined, update the patches in that region
ask patches with [ (abs (pxcor - px) < (mysize / 2) )
and (abs (pycor - py) < (mysize / 2) )] [
set pcolor decolor
set large-region-who region-id
set lrx xcode
set lry ycode
]
set py py + mysize
]
if py > max-pycor [
set py min-pycor
set px px + mysize]
]
end