Make mdoc compile

README.md

@@ -17,7 +17,7 @@ Renders to
 
 See the documentation website at [https://pityka.github.io/nspl/](https://pityka.github.io/nspl/) .
 
-This library is built for Scala 2.13 and Scala 3.1.
+This library is built for Scala 2.13 and Scala 3.2.
 
 Maven coordinates: 
 

docs/content/_index.md

@@ -5,7 +5,7 @@ weight: 1
 
 # Scala plotting library
 nspl is a fast and expressive plotting library for the Scala programming language. 
-nspl can create various plots (scatter, line, bar, box etc) and complex figures.
+nspl can create various scientific plots (scatter, line, bar, box etc) and complex figures.
 
 ## Platforms and output formats
 The library supports Scala on the JVM and Scala.js in the browser.

docs/content/docs/datarenderers/index.md

@@ -38,8 +38,9 @@ An example with triples where the third column (the third element in the triple)
 
 
 val plot4 = xyplot(data -> point())(
-            par(xlab="x axis label",
-            ylab="y axis label")
+            par
+            .xlab("x axis label")
+            .ylab("y axis label")
           )
 
 renderToByteArray(plot4.build, width=2000)
@@ -52,9 +53,10 @@ import org.nspl._
 import org.nspl.awtrenderer._ 
 
 val plot5 = xyplot(data -> line())(
-            par(xlab="x axis label",
-            ylab="y axis label")
-          )
+            par
+            .xlab("x axis label")
+            .ylab("y axis label"))
+
 
 renderToByteArray(plot5.build, width=2000)
 ```
@@ -69,8 +71,9 @@ import org.nspl._
 import org.nspl.awtrenderer._ 
 
 val plot6 = xyplot(data -> lineSegment(color = Color.black))(
-            par(xlab="x axis label",
-            ylab="y axis label")
+            par
+            .xlab("x axis label")
+            .ylab("y axis label")
           )
 
 renderToByteArray(plot6.build, width=2000)
@@ -89,10 +92,11 @@ import org.nspl._
 import org.nspl.awtrenderer._ 
 
 val plot7 = xyplot(data.take(2) -> polynom(() => line()))(
-            par(xlab="x axis label",
-            ylab="y axis label",
-            xlim = Some(0d -> 1d),
-            ylim = Some(0d -> 1d))
+            par
+            .xlab("x axis label")
+            .ylab("y axis label")
+            .xlim(Some(0d -> 1d))
+            .ylim(Some(0d -> 1d))
           )
 
 renderToByteArray(plot7.build, width=2000)
@@ -114,10 +118,12 @@ val plot8 = xyplot(
                                  width = 0.5, 
                                  fill = Color.gray2)
             )(
-            par(xlab="x axis label",
-            ylab="y axis label",
-            xlim = Some(0d -> 3d))
-          )
+             par
+            .xlab("x axis label")
+            .ylab("y axis label")
+            .xlim(Some(0d -> 3d))
+            )
+
 
 renderToByteArray(plot8.build, width=2000)
 ```

docs/content/docs/gallery/index.md

@@ -69,15 +69,14 @@ val data2 = data.addCol(spec, "spec", InnerJoin)
       val fig0 = xyplot(
         data2.col("Sepal.Length", "Sepal.Width", "spec")
       )(
-        par(extraLegend = spec2Num.toSeq.map(x =>
+        par.extraLegend(spec2Num.toSeq.map(x =>
           x._1 -> PointLegend(
             shape = Shape.rectangle(0, 0, 1, 1),
             color = DiscreteColors(spec2Num.size)(x._2)
           )
-        ),
-        xlab = "Sepal.Length",
-        ylab = "Sepal.Width",
-        main = "Iris data")
+        )).xlab("Sepal.Length")
+        .ylab("Sepal.Width")
+        .main("Iris data")
       )
 
       val fig1 = xyplot(
@@ -93,27 +92,30 @@ val data2 = data.addCol(spec, "spec", InnerJoin)
             .toSeq
         )
       )(
-       par(extraLegend = spec2Num.toSeq.map(x =>
-          x._1 -> PointLegend(
-            shape = Shape.rectangle(0, 0, 1, 1),
-            color = DiscreteColors(spec2Num.size)(x._2)
+         par
+          .extraLegend(spec2Num.toSeq.map(x =>
+            x._1 -> PointLegend(
+              shape = Shape.rectangle(0, 0, 1, 1),
+              color = DiscreteColors(spec2Num.size)(x._2)
+            )
+            )
           )
-        ),
-        xlab = "PC1",
-        ylab = "PC2",
-        main = "PC1 vs PC2")
+          .xlab("PC1")
+          .ylab("PC2")
+          .main("PC1 vs PC2")
       )
 
 
 
       val scree = xyplot(
         indexed(eval.firstCol("x").toVec.toSeq.sorted.reverse) -> line()
       )(
-        par(xAxisMargin = 0,
-        xlab = "Order",
-        ylab = "Eval",
-        main = "Scree"
-      ))
+        par
+         .xAxisMargin(0)
+         .xlab("Order")
+         .ylab("Eval")
+         .main("Scree")
+      )
 
       renderToByteArray(
       group(fig0,fig1,scree,TableLayout(2)).build,
@@ -127,10 +129,11 @@ val data2 = data.addCol(spec, "spec", InnerJoin)
       val hist1 = xyplot(
         HistogramData(rotated.firstCol("PC1").toVec.toSeq, 10) -> bar()
       )(
-        par(xlab = "PC1",
-        ylab = "freq.",
-        main = "Loading distribution",
-        ylim = Some(0d, Double.NaN))
+        par
+          .xlab("PC1")
+          .ylab("freq.")
+          .main("Loading distribution")
+          .ylim(Some(0d -> Double.NaN))
       )
 
       renderToByteArray(hist1.build,width=2000)

docs/content/docs/layouts/index.md

@@ -50,8 +50,6 @@ Or the same with `sequence()`:
 ```scala mdoc:bytes:assets/layout2.png
 import org.nspl._ 
 import org.nspl.awtrenderer._ 
-import org.nspl.data.DataMatrix
-import scala.util.Random.nextDouble
 
 val sequencedPlot = sequence(List(plot1,plot2),TableLayout(2))
 

docs/content/docs/usage/index.md

@@ -47,12 +47,7 @@ The most important method in nspl's API is the `xyplot()()` method, a factory fo
 Its signature is roughly:
 ```scala
 def xyplot[F: FC](data: (DataSource, List[DataRenderer], LegendConfig)*)(
-      xlog: Boolean = false,
-      ylog: Boolean = false,
-      main: String = "",
-      xlab: String = "",
-      ylab: String = "",
-      .. many other global plot parameters ..)
+      parameters: Parameters)
 ```
 
 In the first parameter list of `xyplot` we give one or more data sources each with zero or more `DataRenderer`. 
@@ -62,6 +57,8 @@ For the full list of data renderers see the methods in the [Renderers trait]({{<
 
 The third element of the triple controls whether the data source is included in the legend or not. 
 
+Finally, `Parameters` is an immutable holder of commont plot settings. There is a default instance of it named `par` at `org.nspl.par` . The class defines specialized copy methods following a builder like pattern e.g. one can write `par.withXLab("some label")`.
+
 In the below example we have a single data source, each row is plotted as a series of consecutive line segments and also as a point. Finally, the data source is included in the legend.
 ```scala mdoc:bytes:assets/usage1.png
 import org.nspl._ 
@@ -76,8 +73,9 @@ val someData =
   )
 
 val plot = xyplot((someData , List(point(),line()), InLegend("series 1")))(
-            par(xlab="x axis label",
-            ylab="y axis label")
+             par
+            .withXLab("x axis label")
+            .withYLab("y axis label")
           )
 
 renderToByteArray(plot, width=2000)
@@ -99,10 +97,11 @@ val sparseMatrix =
     (2d, 2d, 1d),
   )
 
-val plot2 = rasterplot(sparseMatrix)(par(
-            xlab="x axis label",
-            ylab="y axis label"
-          ))
+val plot2 = rasterplot(sparseMatrix)(
+            par
+            .withXLab("x axis label")
+            .withYLab("y axis label")
+            )
 
 renderToByteArray(plot2.build, width=2000)
 ```
@@ -132,7 +131,6 @@ There is also a factory method which does all these in one call:
 ```scala mdoc:bytes:assets/usage_box.png
 import org.nspl._ 
 import org.nspl.awtrenderer._ 
-import org.nspl.data.DataMatrix 
 import scala.util.Random.nextDouble
 
 val randomData1 = 0 until 10 map (_ => nextDouble())

docs/content/imports/index.md

@@ -29,7 +29,7 @@ import org.nspl.awtrenderer._
 
 If you don't want to pollute the namespace then you can import only the `FontConfiguration` implicit instance, and prefix every call with its package e.g.
 
-```scala mdoc
+```scala
 import org.nspl
 import org.nspl.awtrenderer.{defaultGlyphMeasurer, defaultAWTFont}
 ```