Path-based goodness: Difference between revisions

Line 1:

Path-based goodness is a metric for judging the accuracy and simplicity of temperaments. To compute path-based goodness, we can apply the following steps:

# Choose values for the parameters <code>error_power</code>, <code>complexity_fondness</code>, <code>inaccuracy_fondness</code>, and target_score. The canonical values are:

# Choose values for the parameters <code>error_power</code>, <code>complexity_fondness</code>, <code>inaccuracy_fondness</code>, and <code>target_score</code>. The canonical values are:

~~:::~~ <code>error_power</code> = 1.5,

#* <code>error_power</code> = 1.5,

~~:::~~ <code>complexity_fondness</code> = 0.9,

#* <code>complexity_fondness</code> = 0.9,

~~:::~~ <code>inaccuracy_fondness</code> = 0.98,

#* <code>inaccuracy_fondness</code> = 0.98,

~~:::~~ <code>target_score</code> = 0.02.

#* <code>target_score</code> = 0.02.

# Let ''g'' be a variable. Assign to every JI interval (except 1/1) n/d with error e (in cents) a score equal to <code>inaccuracy_fondness</code>^(e^<code>error_power</code></code>) * <code>complexity_fondness</code>^(n+d) / ''g''.

@@ Line 1: / Line 1: @@
 Path-based goodness is a metric for judging the accuracy and simplicity of temperaments. To compute path-based goodness, we can apply the following steps:
-# Choose values for the parameters <code>error_power</code>, <code>complexity_fondness</code>, <code>inaccuracy_fondness</code>, and target_score. The canonical values are:
+# Choose values for the parameters <code>error_power</code>, <code>complexity_fondness</code>, <code>inaccuracy_fondness</code>, and <code>target_score</code>. The canonical values are:
-::: <code>error_power</code> = 1.5,
+#* <code>error_power</code> = 1.5,
-::: <code>complexity_fondness</code> = 0.9,
+#* <code>complexity_fondness</code> = 0.9,
-::: <code>inaccuracy_fondness</code> = 0.98,
+#* <code>inaccuracy_fondness</code> = 0.98,
-::: <code>target_score</code> = 0.02.
+#* <code>target_score</code> = 0.02.
 # Let ''g'' be a variable. Assign to every JI interval (except 1/1) n/d with error e (in cents) a score equal to <code>inaccuracy_fondness</code>^(e^<code>error_power</code></code>) * <code>complexity_fondness</code>^(n+d) / ''g''.