Moving calc-confidence & erf to protocol.nls.

* They seem to better fit in there.
* removing initialization of current-theory-info from setup b/c it's superfluous

Author: daimpi

SocNetABM.nlogo

@@ -32,7 +32,6 @@ to setup [rs]
     ; alpha + beta): the first (second) entry is the denominator for 
     ; theory 1 (2).
     set b (list (a1 + b1) (a2 + b2))
-    set current-theory-info [0 0]
     ; calculate the prior (i.e. mean of the beta distribution) from the random 
     ; alphas / betas.
     calc-posterior
@@ -335,85 +334,6 @@ to set-researcher-colors
     set color turquoise
   ]
 end
-
-
-
-
-
-; Calculates how confident the researcher is in the fact that her current best 
-; theory is actually the best theory (i.e. how unlikely it is that she will 
-; change her mind). This calculation only makes sense in case researchers have
-; converged.
-to calc-confidence
-  if converged-ticks = 0 [
-    set g-depressed-confidence false
-  ]
-  if g-depressed-confidence [stop]
-  let stop? false
-  ask turtles [
-    if stop? [stop]
-    let belief-to-beat item ((mytheory + 1) mod 2) current-theory-info
-      * strategy-threshold
-    let cur-theory mytheory
-    if converged-ticks = 0 [
-      set avg-neighbor-signal mean [item cur-theory subj-th-i-signal] of 
-        (turtle-set link-neighbors self)
-    ]
-    ; if the scientist would be given sufficient time for her belief to
-    ; converge to the average signal of her and her link-neighbors, would
-    ; this be enough for her to abandon her current theory? If so, she's not
-    ; confident enough.
-    if avg-neighbor-signal <= belief-to-beat [
-      set confidence 0
-      set stop? true
-      set g-depressed-confidence true
-      stop
-    ]
-    ; the following calculations are based on probability maximization of the 
-    ; normal-distribution. This is separately documented at [placeholder].
-    let alpha item mytheory a
-    let varepsilon avg-neighbor-signal - belief-to-beat
-    let delta item mytheory current-theory-info - belief-to-beat
-    if (2 * alpha - 1) * delta <= belief-to-beat [
-      set confidence 0
-      set stop? true
-      stop
-    ]
-    let exit-probability 0.5 + 0.5 * erf (
-      ((0 - 2 * alpha + 1) * delta + belief-to-beat) 
-      / (sqrt((0 - 2 * alpha * delta + delta + belief-to-beat) 
-      * (belief-to-beat + varepsilon) * (0 - 1 + belief-to-beat + varepsilon) 
-      / (varepsilon * (belief-to-beat + delta))) 
-      * (belief-to-beat + delta)))
-    ifelse exit-probability > 0 [
-      set confidence 1 - exit-probability
-    ][
-     set confidence 1
-    ]
-  ]
-  ifelse stop? [
-    set g-confidence 0
-  ][
-    set g-confidence reduce * [confidence] of turtles
-  ]
-end
-
-
-
-
-
-; reports a numerical approximation for the error-function function on its 
-; negative domain, therefore the argument (x) must be smaller than 0. For 
-; sources see infotab.
-to-report erf [x]
-  let t (1 - .5 * x)
-  report exp ( 0 - x ^ 2 - 1.26551223 + 1.00002368 / t 
-    + .37409196 / t ^ 2 + 0.09678418 / t ^ 3 
-    - .18628806 / t ^ 4 + .27886807 / t ^ 5 
-    - 1.13520398 / t ^ 6 + 1.48851587 / t ^ 7 
-    - .82215223 / t ^ 8 + .17087277 / t ^ 9) 
-    / t - 1
-end
 @#$#@#$#@
 GRAPHICS-WINDOW
 210

protocol.nls

@@ -62,6 +62,85 @@ end
 
 
 
+; Calculates how confident the researcher is in the fact that her current best 
+; theory is actually the best theory (i.e. how unlikely it is that she will 
+; change her mind). This calculation only makes sense in case researchers have
+; converged.
+to calc-confidence
+  if converged-ticks = 0 [
+    set g-depressed-confidence false
+  ]
+  if g-depressed-confidence [stop]
+  let stop? false
+  ask turtles [
+    if stop? [stop]
+    let belief-to-beat item ((mytheory + 1) mod 2) current-theory-info
+      * strategy-threshold
+    let cur-theory mytheory
+    if converged-ticks = 0 [
+      set avg-neighbor-signal mean [item cur-theory subj-th-i-signal] of 
+        (turtle-set link-neighbors self)
+    ]
+    ; if the scientist would be given sufficient time for her belief to
+    ; converge to the average signal of her and her link-neighbors, would
+    ; this be enough for her to abandon her current theory? If so, she's not
+    ; confident enough.
+    if avg-neighbor-signal <= belief-to-beat [
+      set confidence 0
+      set stop? true
+      set g-depressed-confidence true
+      stop
+    ]
+    ; the following calculations are based on probability maximization of the 
+    ; normal-distribution. This is separately documented at [placeholder].
+    let alpha item mytheory a
+    let varepsilon avg-neighbor-signal - belief-to-beat
+    let delta item mytheory current-theory-info - belief-to-beat
+    if (2 * alpha - 1) * delta <= belief-to-beat [
+      set confidence 0
+      set stop? true
+      stop
+    ]
+    let exit-probability 0.5 + 0.5 * erf (
+      ((0 - 2 * alpha + 1) * delta + belief-to-beat) 
+      / (sqrt((0 - 2 * alpha * delta + delta + belief-to-beat) 
+      * (belief-to-beat + varepsilon) * (0 - 1 + belief-to-beat + varepsilon) 
+      / (varepsilon * (belief-to-beat + delta))) 
+      * (belief-to-beat + delta)))
+    ifelse exit-probability > 0 [
+      set confidence 1 - exit-probability
+    ][
+     set confidence 1
+    ]
+  ]
+  ifelse stop? [
+    set g-confidence 0
+  ][
+    set g-confidence reduce * [confidence] of turtles
+  ]
+end
+
+
+
+
+
+; reports a numerical approximation for the error-function function on its 
+; negative domain, therefore the argument (x) must be smaller than 0. For 
+; sources see infotab.
+to-report erf [x]
+  let t (1 - .5 * x)
+  report exp ( 0 - x ^ 2 - 1.26551223 + 1.00002368 / t 
+    + .37409196 / t ^ 2 + 0.09678418 / t ^ 3 
+    - .18628806 / t ^ 4 + .27886807 / t ^ 5 
+    - 1.13520398 / t ^ 6 + 1.48851587 / t ^ 7 
+    - .82215223 / t ^ 8 + .17087277 / t ^ 9) 
+    / t - 1
+end
+
+
+
+
+
 ; reports 1 if scientists converged on the best theory (th1) by the end of the 
 ; run, 0 otherwise
 to-report successful-run