Merge pull request #29 from moritz155/24-use-observables

24 use observables

Author: moritz155

.gitignore

@@ -2,6 +2,12 @@
 *.jl.cov
 *.jl.mem
 .idea/
+
+#Test output images
+*.png
+*.svg
+*.mp4
+
 /Manifest.toml
 /docs/Manifest.toml
 #/docs/build/

Project.toml

@@ -1,13 +1,13 @@
 name = "ParallelPlots"
 uuid = "79f8b2c9-78a2-4289-b087-49f7cf65a4c9"
 authors = ["Moritz Schelten <moritz155@win.tu-berlin.de>", "Leon Haufe <leon.haufe@campus.tu-berlin.de>"]
-version = "1.0.0-DEV"
+version = "2.0.0-DEV"
 
 [deps]
 AbstractPlotting = "537997a7-5e4e-5d89-9595-2241ea00577e"
 CairoMakie = "13f3f980-e62b-5c42-98c6-ff1f3baf88f0"
 DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
 
 [compat]
-AbstractPlotting = "0.18.3"
 julia = "1.10"
+#CairoMakie = "0.12.18"

README.md

@@ -33,14 +33,22 @@ You need to use the package (1-3) and install the dependencies (4-5)
 
 ### Usage
 ```@example
-julia> ParallelPlots.create_parallel_coordinates_plot(DataFrame(height=160:180,weight=60:80,age=20:40))
-
+julia> using ParallelPlots
+julia> parallelplot(DataFrame(height=160:180,weight=60:80,age=20:40))
+```
+```
 # If you want to normalize the Data, you can add the value normalized=true, default is false
-julia> ParallelPlots.create_parallel_coordinates_plot(DataFrame(height=160:180,weight=reverse(60:80),age=20:40),normalize=true)
-
+julia> parallelplot(DataFrame(height=160:180,weight=reverse(60:80),age=20:40),normalize=true)
+```
+```
 # If you want to set the size of the plot (default width:800, height:600)
-julia> ParallelPlots.create_parallel_coordinates_plot( DataFrame(height=160:180,weight=60:80,age=20:40), scene_width=200, scene_height=200 )
+julia> parallelplot( DataFrame(height=160:180,weight=60:80,age=20:40), figure = (resolution = (300, 300),) )
+```
+```
+# You can update as well the Graph with Observables
 
+julia> df_observable = Observable(DataFrame(height=160:180,weight=60:80,age=20:40))
+julia> fig, ax, sc = parallelplot(df_observable)
 ```
 
 Please read the [Docs](/docs/build/index.html) for further Information

src/ParallelPlots.jl

@@ -1,7 +1,5 @@
 module ParallelPlots
 
-    export create_parallel_coordinates_plot
-
 using CairoMakie
 using DataFrames
 
@@ -34,15 +32,12 @@ end
 
 
 
-
 """
-    create_parallel_coordinates_plot(data::DataFrame, normalize::Bool)
-
 - Julia version: 1.10.5
 
 # Constructors
 ```julia
-ParallelPlots.create_parallel_coordinates_plot(data::DataFrame; normalize::Bool=false, scene_width::Integer=800, scene_height::Integer=600)
+ParallelPlot(data::DataFrame; normalize::Bool=false)
 ```
 
 # Arguments
@@ -52,78 +47,128 @@ ParallelPlots.create_parallel_coordinates_plot(data::DataFrame; normalize::Bool=
 
 # Examples
 ```@example
-julia> ParallelPlots.create_parallel_coordinates_plot(DataFrame(height=160:180,weight=60:80,age=20:40))
+julia> using ParallelPlots
+julia> parallelplot(DataFrame(height=160:180,weight=60:80,age=20:40))
 
 # If you want to normalize the Data, you can add the value normalized=true, default is false
-julia> ParallelPlots.create_parallel_coordinates_plot(DataFrame(height=160:180,weight=reverse(60:80),age=20:40),normalize=true)
+julia> parallelplot(DataFrame(height=160:180,weight=reverse(60:80),age=20:40),normalize=true)
 
-# If you want to set the size of the plot (default width:800, height:600)
-julia> ParallelPlots.create_parallel_coordinates_plot( DataFrame(height=160:180,weight=60:80,age=20:40), scene_width=200, scene_height=200 )
+# If you want to set the size of the plot
+julia> parallelplot( DataFrame(height=160:180,weight=60:80,age=20:40), figure = (resolution = (300, 300),) )
 
-```
+# You can update as well the Graph with Observables
 
+julia> df_observable = Observable(DataFrame(height=160:180,weight=60:80,age=20:40))
+julia> fig, ax, sc = parallelplot(df_observable)
+```
 
 """
-function create_parallel_coordinates_plot(data::DataFrame; normalize::Bool=false, scene_width::Integer=800, scene_height::Integer=600)
-    
-    # check the given DataFrame
-    input_check(data)
-
-    # Normalize the data if required
-    if normalize
-        data = normalize_DF(data)
-    end
+@recipe(ParallelPlot, df) do scene
+    Attributes(
+    # size, normalize attributes
+        normalize = false
+    )
+end
+
+
+function Makie.plot!(pp::ParallelPlot{<:Tuple{<:DataFrame}})
+
+    # our first parameter is the DataFrame-Observable
+    df_observable  = pp[1]
 
-    # Parse the DataFrame into a list of arrays
-    parsed_data = [data[!, col] for col in names(data)]
-
-    # Compute limits for each column
-    limits = [(minimum(col), maximum(col)) for col in parsed_data]
-
-    let
-        # creates the Scene for the Plot
-        scene = Scene(resolution = (scene_width, scene_height), camera=campixel!)
-        numberFeatures = length(parsed_data) # Number of features, equivalent to the X Axis
-        sampleSize = size(data, 1)       # Number of samples, equivalent to the Y Axis
-
-        # Plot dimensions
-        width = scene_width * 0.75  # 75% of scene width
-        height = scene_height * 0.75  # 75% of scene width
-        offset = min(scene_width, scene_height) * 0.15  # 15% of scene dimensions
-
-        # Create axes
-        for i in 1:numberFeatures
-            # x will be used to split the Scene for each feature
-            x = (i - 1) / (numberFeatures - 1) * width
-            # LineAxis will create one Axis Vertical, for each Feature one Axis
-            MakieLayout.LineAxis(scene, limits=limits[i],
-                spinecolor=:black, labelfont="Arial",
-                ticklabelfont="Arial", spinevisible=true,
-                minorticks=IntervalsBetween(2),
-                # the lowest and highest point to maximize the Axis from Bottom to Top
-                endpoints=Point2f0[(offset + x, offset), (offset + x, offset + height)],
-                ticklabelalign=(:right, :center), labelvisible=true,
-                # using the names of the dataframe for display the axis
-                label=names(data)[i])
+    # this helper function will update our observables
+    # whenever df_observable change
+    function update_plot(data)
+
+        # check the given DataFrame
+        input_check(data)
+
+        # Normalize the data if required
+        if pp.normalize[] # TODO: what happens when the parameter is an observeable to? will it update?
+            data = normalize_DF(data)
         end
 
-        # Draw lines connecting points for each row
-        for i in 1:sampleSize
-            dataPoints = [
-                # calcuating the point respectivly of the width and height in the Screen
-                Point2f0(
-                    # calculates which feature the Point should be on
-                    offset + (j - 1) / (numberFeatures - 1) * width,
-                    # calculates the Y axis value
-                    (parsed_data[j][i] - limits[j][1]) / (limits[j][2] - limits[j][1]) * height + offset
-                )
-                # iterates through the Features and creates for each feature the samplePoint (above)
-                for j in 1:numberFeatures
-            ]
-            lines!(scene, dataPoints, color=get(Makie.ColorSchemes.inferno, (i - 1) / (sampleSize - 1)),
-                show_axis=false)
+        # Parse the DataFrame into a list of arrays
+        parsed_data = [data[!, col] for col in names(data)]
+
+        # Compute limits for each column
+        limits = [(minimum(col), maximum(col)) for col in parsed_data]
+
+        let
+            # get the scene
+            fig = current_figure()
+            scene = fig.scene
+
+            # reset scene
+            empty!(fig.scene)
+            trim!(fig.layout)
+            empty!(fig.content)
+            fig.current_axis[] = nothing
+
+            # get the widht and height
+            scene_width,scene_height = size(scene)
+
+
+
+            numberFeatures = length(parsed_data) # Number of features, equivalent to the X Axis
+            sampleSize = size(data, 1)       # Number of samples, equivalent to the Y Axis
+
+            # Plot dimensions
+            width = scene_width[] * 0.75  # 75% of scene width
+            height = scene_height[] * 0.75  # 75% of scene width
+            offset = min(scene_width[], scene_height[]) * 0.15  # 15% of scene dimensions
+
+            # Create axes
+            for i in 1:numberFeatures
+                # x will be used to split the Scene for each feature
+                x = (i - 1) / (numberFeatures - 1) * width
+                # LineAxis will create one Axis Vertical, for each Feature one Axis
+                MakieLayout.LineAxis(scene, limits=limits[i],
+                    spinecolor=:black, labelfont="Arial",
+                    ticklabelfont="Arial", spinevisible=true,
+                    minorticks=IntervalsBetween(2),
+                    # the lowest and highest point to maximize the Axis from Bottom to Top
+                    endpoints=Point2f0[(offset + x, offset), (offset + x, offset + height)],
+                    ticklabelalign=(:right, :center), labelvisible=true,
+                    # using the names of the dataframe for display the axis
+                    label=names(data)[i])
+            end
+
+            # Draw lines connecting points for each row
+            for i in 1:sampleSize
+                dataPoints = [
+                    # calcuating the point respectivly of the width and height in the Screen
+                    Point2f0(
+                        # calculates which feature the Point should be on
+                        offset + (j - 1) / (numberFeatures - 1) * width,
+                        # calculates the Y axis value
+                        (parsed_data[j][i] - limits[j][1]) / (limits[j][2] - limits[j][1]) * height + offset
+                    )
+                    # iterates through the Features and creates for each feature the samplePoint (above)
+                    for j in 1:numberFeatures
+                ]
+                lines!(scene, dataPoints, color=get(Makie.ColorSchemes.inferno, (i - 1) / (sampleSize - 1)),
+                    show_axis=false)
+            end
+            return scene
         end
-        return scene
+
     end
+
+    # connect `update_plot` so that it is called whenever the DataFrame changes
+    Makie.Observables.onany(update_plot, df_observable)
+
+    # then call it once manually with the first dataFrame
+    # contents so we prepopulate all observables with correct values
+    update_plot(df_observable[])
+
+    # some Random Plot, else we get an error
+    lines!(pp, 1:9, iseven.(1:9) .- 0; color = :tomato)
+
+    # lastly we return the new ParallelPlot
+    pp
 end
+
+
+
 end