rwn1v
Reputation: 787
MATLAB plotting function similar to xyplot() from Lattice package
I would like to know if there is any similar function to the xyplot() function from the lattice package in R. I would like to plot groups of observations classified by subgroups in different charts.
For example, if I have the following dataframe:
d <- data.frame(ID=paste0("id",1:40),
Group=paste0("group",rep(1:4,10)),
Subgroup=paste0("subgroup",c(rep(c("A","B","B"),13),"A")),
ValueX=rnorm(40),
ValueY=rnorm(40))
I am looking for the following output:
library(lattice)
xyplot(d$ValueY ~ d$ValueX | d$Group, group=as.factor(d$Subgroup),
auto.key=list(space="right", points=T), pch=20)
In MATLAB, I defined d as a dataset and plotted the following using sbiotrellis function:
sbiotrellis(d,'Group','ValueX','ValueY')
However, the subgroups are not being considered. Any ideas?
Upvotes: 2
Views: 819
Answers (1)
Sathish
Reputation: 12723
R:
write.table(d, file = "myfile.csv", sep = ",", row.names = FALSE)
Matlab:
Operating System
lsb_release -i -r
Distributor ID: RedHatEnterpriseServer
Release: 6.5
Matlab Version and Release
version -date
% ans =
%
% September 15, 2014
version -release
% ans =
%
% 2014b
version -java
%ans =
%
%Java 1.7.0_11-b21 with Oracle Corporation Java HotSpot(TM) 64-Bit Server VM mixed mode
Data
ds = dataset('File', 'myfile.csv','Delimiter',',', 'HeaderLines', 1, 'ReadVarNames', false, 'ReadObsNames', true);
vn = {'ID', 'Group', 'Subgroup', 'ValueX', 'ValueY'};
ds = set(ds, 'VarNames', vn);
ds
% ds =
%
% ID Group Subgroup ValueX ValueY
% "1" '"id1"' '"group1"' '"subgroupA"' 0.5524 -0.21252
% "2" '"id2"' '"group2"' '"subgroupB"' -0.30546 -0.12646
% "3" '"id3"' '"group3"' '"subgroupB"' -0.96933 -1.0407
% "4" '"id4"' '"group4"' '"subgroupA"' 0.024616 -1.1806
% "5" '"id5"' '"group1"' '"subgroupB"' 0.3268 -0.97485
% "6" '"id6"' '"group2"' '"subgroupB"' 0.55165 -0.70415
% "7" '"id7"' '"group3"' '"subgroupA"' 0.36608 -0.97104
% "8" '"id8"' '"group4"' '"subgroupB"' 0.028234 0.26336
% "9" '"id9"' '"group1"' '"subgroupB"' 0.71088 0.97357
% "10" '"id10"' '"group2"' '"subgroupA"' -0.14237 -0.0085301
% "11" '"id11"' '"group3"' '"subgroupB"' 1.1259 -0.85614
% "12" '"id12"' '"group4"' '"subgroupB"' 0.73305 0.33118
% "13" '"id13"' '"group1"' '"subgroupA"' 0.41297 -0.28922
% "14" '"id14"' '"group2"' '"subgroupB"' -0.41621 0.35157
% "15" '"id15"' '"group3"' '"subgroupB"' -0.48856 0.85537
% "16" '"id16"' '"group4"' '"subgroupA"' -1.8682 0.6652
% "17" '"id17"' '"group1"' '"subgroupB"' -0.098612 1.563
% "18" '"id18"' '"group2"' '"subgroupB"' -0.53824 0.57049
% "19" '"id19"' '"group3"' '"subgroupA"' 0.24112 0.168
% "20" '"id20"' '"group4"' '"subgroupB"' -0.35454 -1.23
% "21" '"id21"' '"group1"' '"subgroupB"' -0.45688 1.2703
% "22" '"id22"' '"group2"' '"subgroupA"' 0.68444 -1.3548
% "23" '"id23"' '"group3"' '"subgroupB"' -1.1469 2.1724
% "24" '"id24"' '"group4"' '"subgroupB"' -0.035062 -0.41989
% "25" '"id25"' '"group1"' '"subgroupA"' -1.2422 1.2415
% "26" '"id26"' '"group2"' '"subgroupB"' 2.1308 -0.76941
% "27" '"id27"' '"group3"' '"subgroupB"' -0.87732 -0.9218
% "28" '"id28"' '"group4"' '"subgroupA"' 2.14 0.12569
% "29" '"id29"' '"group1"' '"subgroupB"' 0.13455 -0.22301
% "30" '"id30"' '"group2"' '"subgroupB"' -1.0742 -0.35052
% "31" '"id31"' '"group3"' '"subgroupA"' -1.121 0.55119
% "32" '"id32"' '"group4"' '"subgroupB"' 0.88677 -1.1549
% "33" '"id33"' '"group1"' '"subgroupB"' -0.28575 1.1066
% "34" '"id34"' '"group2"' '"subgroupA"' -0.10857 -2.0048
% "35" '"id35"' '"group3"' '"subgroupB"' -0.78056 0.23084
% "36" '"id36"' '"group4"' '"subgroupB"' -0.16794 -0.48823
% "37" '"id37"' '"group1"' '"subgroupA"' -0.080923 0.309
% "38" '"id38"' '"group2"' '"subgroupB"' 1.7291 -1.0569
% "39" '"id39"' '"group3"' '"subgroupB"' -1.2291 -1.7684
% "40" '"id40"' '"group4"' '"subgroupA"' -1.3804 1.4364
Divide the data into groups based on Subgroup variable
target = 'subgroupA';
vi = find(cellfun('length', regexp(ds.Subgroup, target)) == 1);
data1 = ds(vi, :);
target = 'subgroupB';
vi = find(cellfun('length', regexp(ds.Subgroup, target)) == 1);
data2 = ds(vi, :);
Plot trellis plot. Use hold on to plot multiple layers on to one figure
t1 = sbiotrellis(data1, 'Group', 'ValueX', 'ValueY', 'LineStyle', 'none', 'Marker', 'o', 'MarkerEdgeColor', [1,0,0], 'MarkerSize', 4, 'MarkerFaceColor', [1,0,0]);
hold on
t2 = sbiotrellis(data2, 'Group', 'ValueX', 'ValueY', 'LineStyle', 'none', 'Marker', 'o', 'MarkerEdgeColor', [0,0,1], 'MarkerSize', 4, 'MarkerFaceColor', [0,0,1]);
t2.labelx = 'X';
t2.labely = 'Y';
t2.plottitle = 'My Trellis Plot';
Plot upto this point:
Capture gcf which gives the handle to the parent of the current figure
bx = gcf
% bx =
%
% Figure (SimBiologyTrellisPlot) with properties:
%
% Number: 2
% Name: ''
% Color: [0.9400 0.9400 0.9400]
% Position: [415 124 518 384]
% Units: 'pixels'
%
% Show all properties
Using the parent handle, get the properties of its children
bx1 = bx.Children
% bx1 =
%
% 6x1 graphics array:
%
% Axes (Group "group4")
% Axes (Group "group3")
% Axes (Group "group1")
% Legend (ValueY, ValueY)
% Axes (Group "group2")
% Axes (BackgroundAxes)
Now, you could see that there are 6 children (5 Axes and 1 legend) for bx handle. The properties of children could be manipulated as follows.
To get the list of parameters for each child, do
get(bx1(1))
% ALim: [0 1]
% ALimMode: 'auto'
% ActivePositionProperty: 'position'
% AmbientLightColor: [1 1 1]
% BeingDeleted: 'off'
% Box: 'on'
% BoxStyle: 'back'
% BusyAction: 'queue'
% ButtonDownFcn: {3x1 cell}
% CLim: [0 1]
% CLimMode: 'auto'
% CameraPosition: [0.1359 0.0838 17.3205]
% CameraPositionMode: 'auto'
% CameraTarget: [0.1359 0.0838 0]
% CameraTargetMode: 'auto'
% CameraUpVector: [0 1 0]
% CameraUpVectorMode: 'auto'
% CameraViewAngle: 6.6086
% CameraViewAngleMode: 'auto'
% Children: [2x1 Line]
% Clipping: 'on'
% ClippingStyle: '3dbox'
% Color: [1 1 1]
% ColorOrder: [7x3 double]
% ColorOrderIndex: 3
% CreateFcn: ''
% CurrentPoint: [2x3 double]
% DataAspectRatio: [2.2045 2.2974 1]
% DataAspectRatioMode: 'auto'
% DeleteFcn: ''
% FontAngle: 'normal'
% FontName: 'Helvetica'
% FontSize: 8
% FontSmoothing: 'on'
% FontUnits: 'points'
% FontWeight: 'normal'
% GridAlpha: 0.1500
% GridAlphaMode: 'auto'
% GridColor: [0.1500 0.1500 0.1500]
% GridColorMode: 'auto'
% GridLineStyle: '-'
% HandleVisibility: 'on'
% HitTest: 'on'
% Interruptible: 'on'
% LabelFontSizeMultiplier: 1.1000
% Layer: 'bottom'
% LineStyleOrder: '-'
% LineStyleOrderIndex: 1
% LineWidth: 0.5000
% MinorGridAlpha: 0.2500
% MinorGridAlphaMode: 'auto'
% MinorGridColor: [0.1000 0.1000 0.1000]
% MinorGridLineStyle: ':'
% NextPlot: 'replace'
% OuterPosition: [172.4400 6.7600 289.2000 211.0400]
% Parent: [1x1 Figure]
% PickableParts: 'visible'
% PlotBoxAspectRatio: [1 0.8046 0.8046]
% PlotBoxAspectRatioMode: 'auto'
% Position: [239 49 174 140]
% Projection: 'orthographic'
% Selected: 'off'
% SelectionHighlight: 'on'
% SortMethod: 'childorder'
% Tag: ''
% TickDir: 'in'
% TickDirMode: 'auto'
% TickLabelInterpreter: 'tex'
% TickLength: [0.0100 0.0250]
% TightInset: [0 1.4852e-06 0 0]
% Title: [1x1 Text]
% TitleFontSizeMultiplier: 1.1000
% TitleFontWeight: 'bold'
% Type: 'axes'
% UIContextMenu: []
% Units: 'pixels'
% UserData: []
% View: [0 90]
% Visible: 'on'
% XAxisLocation: 'bottom'
% XColor: [0.1500 0.1500 0.1500]
% XColorMode: 'auto'
% XDir: 'normal'
% XGrid: 'off'
% XLabel: [1x1 Text]
% XLim: [-2.0686 2.3405]
% XLimMode: 'manual'
% XMinorGrid: 'off'
% XMinorTick: 'off'
% XScale: 'linear'
% XTick: [-2 -1 0 1 2]
% XTickLabel: ''
% XTickLabelMode: 'manual'
% XTickLabelRotation: 0
% XTickMode: 'auto'
% YAxisLocation: 'left'
% YColor: [0.1500 0.1500 0.1500]
% YColorMode: 'auto'
% YDir: 'normal'
% YGrid: 'off'
% YLabel: [1x1 Text]
% YLim: [-2.2136 2.3813]
% YLimMode: 'manual'
% YMinorGrid: 'off'
% YMinorTick: 'off'
% YScale: 'linear'
% YTick: [-2 -1 0 1 2]
% YTickLabel: ''
% YTickLabelMode: 'manual'
% YTickLabelRotation: 0
% YTickMode: 'auto'
% ZColor: [0.1500 0.1500 0.1500]
% ZColorMode: 'auto'
% ZDir: 'normal'
% ZGrid: 'off'
% ZLabel: [1x1 Text]
% ZLim: [-1 1]
% ZLimMode: 'auto'
% ZMinorGrid: 'off'
% ZMinorTick: 'off'
% ZScale: 'linear'
% ZTick: [-1 0 1]
% ZTickLabel: ''
% ZTickLabelMode: 'auto'
% ZTickLabelRotation: 0
% ZTickMode: 'auto'
To get the value of paramater of a child, do
get(bx1(1), 'ZGrid')
%ans =
%
%off
To customize parameters of each child, do
set(bx1(1), 'ZGrid', 'on')
Customize properties of subplots, legend, and title
%subplot 4
bx1(1).Title.String = 'Group 4';
bx1(1).Title.Position = [0.1359, 2.6, 0];
bx1(1).Title.FontWeight = 'bold';
%subplot 3
bx1(2).Title.String = 'Group 3';
bx1(2).Title.Position = [0.1359, 2.6, 0];
bx1(2).Title.FontWeight = 'bold';
%subplot 1
bx1(3).Title.String = 'Group 1';
bx1(3).Title.Position = [0.1359, 2.6, 0];
bx1(3).Title.FontWeight = 'bold';
%legend text, box, and location
bx1(4).String = {'SubgroupA', 'SubgroupB'};
bx1(4).Position = [397.2451 185 109.7549 29.2715];
h =findobj('type', 'legend');
set(h, 'Box', 'off');
%subplot 2
bx1(5).Title.String = 'Group 2';
bx1(5).Title.Position = [0.1359, 2.6, 0];
bx1(5).Title.FontWeight = 'bold';
% Title location
set(bx1(6), 'Position', [30, 30, 390, 324]);
After evaluating the children handles, we see a final plot shown at the end of this solution.
Other properties of the figure can be also modified and if you look at the source code of sbiotrellis ('edit sbiotrellis') or typing the plot object followed by a letter and tab completion (t2.u ), you could get the list of properties or hidden properties that can be manipulated after rendering the plot.
properties
hFig;
nPlots;
plots;
properties (Hidden)
layoutObj;
labelx = '';
labely = '';
plottitle = '';
legendnames = {};
plotLegend;
rows;
cols;
titleFontSize = 8;
axisLimitSlack = .05
backgroundInsets = [30 30 30 30];
foregroundInsets = [50 50 05 35];
Output:
R - Lattice - xyplot:
Matlab - sbiotrellis:
Upvotes: 2
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