Esempio n. 1
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        public void ExecuteRecipe(Plot plt)
        {
            // create sample data to represent test scores
            Random rand = new Random(0);

            double[] valuesA = DataGen.RandomNormal(rand, 35, 85, 5);
            double[] valuesB = DataGen.RandomNormal(rand, 42, 87, 3);
            double[] valuesC = DataGen.RandomNormal(rand, 23, 92, 3);

            // create population objects for each set of data values
            var popA = new Statistics.Population(valuesA);
            var popB = new Statistics.Population(valuesB);
            var popC = new Statistics.Population(valuesC);

            // combine several populations into an array and plot it
            var poulations = new Statistics.Population[] { popA, popB, popC };

            string[] populationNames = { "Group A", "Group B", "Group C" };

            // customize the data display format
            var popPlot = plt.AddPopulations(poulations);

            popPlot.DistributionCurve = false;
            popPlot.DataFormat        = ScottPlot.Plottable.PopulationPlot.DisplayItems.ScatterOnBox;
            popPlot.DataBoxStyle      = ScottPlot.Plottable.PopulationPlot.BoxStyle.BarMeanStDev;

            // improve the style of the plot
            plt.XAxis.Grid(false);
            plt.XTicks(populationNames);
        }
Esempio n. 2
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            public void Render(Plot plt)
            {
                // create some sample data to represent test scores
                Random rand = new Random(0);

                double[] scoresA = DataGen.RandomNormal(rand, 35, 85, 5);
                double[] scoresB = DataGen.RandomNormal(rand, 42, 87, 3);
                double[] scoresC = DataGen.RandomNormal(rand, 23, 92, 3);

                // collect multiple populations into a PopulationSeries
                var poulations = new Statistics.Population[] {
                    new Statistics.Population(scoresA),
                    new Statistics.Population(scoresB),
                    new Statistics.Population(scoresC)
                };

                // Plot these as a single series (all styled the same, appearing once in legend)
                var popSeries = new Statistics.PopulationSeries(poulations);

                plt.PlotPopulations(popSeries, "scores");

                // improve the style of the plot
                plt.Title($"Test Scores by Class");
                plt.YLabel("Score");
                plt.XTicks(new string[] { "Class A", "Class B", "Class C" });
                plt.Legend();
                plt.Grid(lineStyle: LineStyle.Dot, enableVertical: false);
            }
Esempio n. 3
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        public void ExecuteRecipe(Plot plt)
        {
            // create sample data to represent test scores
            Random rand = new Random(0);

            double[] scoresA = DataGen.RandomNormal(rand, 35, 72, 7);
            double[] scoresB = DataGen.RandomNormal(rand, 42, 57, 10);
            double[] scoresC = DataGen.RandomNormal(rand, 23, 79, 5);

            // To create a population series we need to start with an array of populations.
            // In this example each population series just has one population in it.
            var popsA = new Statistics.Population[] { new Statistics.Population(scoresA) };
            var popsB = new Statistics.Population[] { new Statistics.Population(scoresB) };
            var popsC = new Statistics.Population[] { new Statistics.Population(scoresC) };

            // create a PopulationSeries for each set of scores, naming it in the process
            var seriesA     = new Statistics.PopulationSeries(popsA, "Class A");
            var seriesB     = new Statistics.PopulationSeries(popsB, "Class B");
            var seriesC     = new Statistics.PopulationSeries(popsC, "Class C");
            var seriesArray = new Statistics.PopulationSeries[] { seriesA, seriesB, seriesC };

            // create a MultiSeries object by passing in the array of series objects and plot it
            var multiSeries = new Statistics.PopulationMultiSeries(seriesArray);
            var popPlot     = plt.AddPopulations(multiSeries);

            // now customize its public fields to extensively customize its display options
            popPlot.DistributionCurve          = true;
            popPlot.DistributionCurveLineStyle = LineStyle.Dash;
            popPlot.ScatterOutlineColor        = System.Drawing.Color.Transparent;
            popPlot.DataFormat   = ScottPlot.Plottable.PopulationPlot.DisplayItems.ScatterAndBox;
            popPlot.DataBoxStyle = ScottPlot.Plottable.PopulationPlot.BoxStyle.BarMeanStDev;

            // colors are managed at the population series level:
            foreach (var popSeries in popPlot.MultiSeries.multiSeries)
            {
                popSeries.color = Tools.GetRandomColor(rand);
            }

            // improve the style of the plot
            plt.Legend(location: Alignment.LowerLeft);
            plt.XAxis.Ticks(false);
            plt.XAxis.Grid(false);
            plt.YAxis.MajorGrid(lineStyle: LineStyle.Dot);
            plt.SetAxisLimits(yMin: 0);
        }
Esempio n. 4
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        public void ExecuteRecipe(Plot plt)
        {
            // create sample data to represent test scores
            Random rand = new Random(0);

            double[] scores = DataGen.RandomNormal(rand, 35, 85, 5);

            // First, create a Population object from your test scores
            var pop = new Statistics.Population(scores);

            // You can access population statistics as public fields
            plt.Title($"Mean: {pop.mean} +/- {pop.stdErr}");

            // You can plot a population
            plt.AddPopulation(pop);

            // improve the style of the plot
            plt.XAxis.Ticks(true);
            plt.XAxis.Grid(false);
        }
Esempio n. 5
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        public void ExecuteRecipe(Plot plt)
        {
            // create sample data to represent test scores
            Random rand = new Random(0);

            double[] valuesA = DataGen.RandomNormal(rand, 35, 85, 5);
            double[] valuesB = DataGen.RandomNormal(rand, 42, 87, 3);
            double[] valuesC = DataGen.RandomNormal(rand, 23, 92, 3);

            // create population objects for each set of data values
            var popA = new Statistics.Population(valuesA);
            var popB = new Statistics.Population(valuesB);
            var popC = new Statistics.Population(valuesC);

            // combine several populations into an array and plot it
            var poulations = new Statistics.Population[] { popA, popB, popC };

            string[] populationNames = { "Group A", "Group B", "Group C" };
            plt.AddPopulations(poulations);

            // improve the style of the plot
            plt.XAxis.Grid(false);
            plt.XTicks(populationNames);
        }
Esempio n. 6
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            public void Render(Plot plt)
            {
                // create some sample data to represent test scores.
                Random rand = new Random(0);

                // Each class (A, B, C) is a series.
                // Each semester (fall, spring, summer A, summer B) is a group.

                double[] scoresAfall = DataGen.RandomNormal(rand, 35, 85, 5);
                double[] scoresBfall = DataGen.RandomNormal(rand, 42, 87, 5);
                double[] scoresCfall = DataGen.RandomNormal(rand, 23, 82, 5);

                double[] scoresAspring = DataGen.RandomNormal(rand, 35, 84, 3);
                double[] scoresBspring = DataGen.RandomNormal(rand, 42, 88, 3);
                double[] scoresCspring = DataGen.RandomNormal(rand, 23, 84, 3);

                double[] scoresAsumA = DataGen.RandomNormal(rand, 35, 80, 5);
                double[] scoresBsumA = DataGen.RandomNormal(rand, 42, 90, 5);
                double[] scoresCsumA = DataGen.RandomNormal(rand, 23, 85, 5);

                double[] scoresAsumB = DataGen.RandomNormal(rand, 35, 91, 2);
                double[] scoresBsumB = DataGen.RandomNormal(rand, 42, 93, 2);
                double[] scoresCsumB = DataGen.RandomNormal(rand, 23, 90, 2);

                // Collect multiple populations into a PopulationSeries.
                // All populations in a series will be styled the same and appear once in the legend.

                var popsA = new Statistics.Population[] {
                    new Statistics.Population(scoresAfall),
                    new Statistics.Population(scoresAspring),
                    new Statistics.Population(scoresAsumA),
                    new Statistics.Population(scoresAsumB)
                };

                var popsB = new Statistics.Population[] {
                    new Statistics.Population(scoresBfall),
                    new Statistics.Population(scoresBspring),
                    new Statistics.Population(scoresBsumA),
                    new Statistics.Population(scoresBsumB)
                };

                var popsC = new Statistics.Population[] {
                    new Statistics.Population(scoresCfall),
                    new Statistics.Population(scoresCspring),
                    new Statistics.Population(scoresCsumA),
                    new Statistics.Population(scoresCsumB)
                };

                var seriesA   = new Statistics.PopulationSeries(popsA, "Class A");
                var seriesB   = new Statistics.PopulationSeries(popsB, "Class B");
                var seriesC   = new Statistics.PopulationSeries(popsC, "Class C");
                var allSeries = new Statistics.PopulationSeries[] { seriesA, seriesB, seriesC };

                // create a MultiSeries from multiple population series and plot it
                var multiSeries = new Statistics.PopulationMultiSeries(allSeries);

                plt.PlotPopulations(multiSeries);

                // improve the style of the plot
                plt.Title($"Test Scores by Class");
                plt.YLabel("Score");
                plt.XTicks(new string[] { "Fall", "Spring", "Summer A", "Summer B" });
                plt.Legend();
                plt.Grid(lineStyle: LineStyle.Dot, enableVertical: false);
            }
Esempio n. 7
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        public void ExecuteRecipe(Plot plt)
        {
            // Each class (A, B, C) is a series.
            // Each semester (fall, spring, summer A, summer B) is a group.

            // create sample data to represent test scores for each class in each semester
            Random rand = new Random(0);

            double[] scoresAfall   = DataGen.RandomNormal(rand, 35, 85, 5);
            double[] scoresBfall   = DataGen.RandomNormal(rand, 42, 87, 5);
            double[] scoresCfall   = DataGen.RandomNormal(rand, 23, 82, 5);
            double[] scoresAspring = DataGen.RandomNormal(rand, 35, 84, 3);
            double[] scoresBspring = DataGen.RandomNormal(rand, 42, 88, 3);
            double[] scoresCspring = DataGen.RandomNormal(rand, 23, 84, 3);
            double[] scoresAsumA   = DataGen.RandomNormal(rand, 35, 80, 5);
            double[] scoresBsumA   = DataGen.RandomNormal(rand, 42, 90, 5);
            double[] scoresCsumA   = DataGen.RandomNormal(rand, 23, 85, 5);
            double[] scoresAsumB   = DataGen.RandomNormal(rand, 35, 91, 2);
            double[] scoresBsumB   = DataGen.RandomNormal(rand, 42, 93, 2);
            double[] scoresCsumB   = DataGen.RandomNormal(rand, 23, 90, 2);

            // Collect multiple populations into a PopulationSeries.
            // All populations in a series will be styled the same and appear once in the legend.
            var popsA = new Statistics.Population[] {
                new Statistics.Population(scoresAfall),
                new Statistics.Population(scoresAspring),
                new Statistics.Population(scoresAsumA),
                new Statistics.Population(scoresAsumB)
            };

            var popsB = new Statistics.Population[] {
                new Statistics.Population(scoresBfall),
                new Statistics.Population(scoresBspring),
                new Statistics.Population(scoresBsumA),
                new Statistics.Population(scoresBsumB)
            };

            var popsC = new Statistics.Population[] {
                new Statistics.Population(scoresCfall),
                new Statistics.Population(scoresCspring),
                new Statistics.Population(scoresCsumA),
                new Statistics.Population(scoresCsumB)
            };

            // create a population series for each array of populations and give it a label
            var seriesA   = new Statistics.PopulationSeries(popsA, "Class A");
            var seriesB   = new Statistics.PopulationSeries(popsB, "Class B");
            var seriesC   = new Statistics.PopulationSeries(popsC, "Class C");
            var allSeries = new Statistics.PopulationSeries[] { seriesA, seriesB, seriesC };

            // create a MultiSeries from multiple population series and plot it
            var multiSeries = new Statistics.PopulationMultiSeries(allSeries);

            plt.AddPopulations(multiSeries);

            // improve the style of the plot
            string[] groupNames = new string[] { "Fall", "Spring", "Summer A", "Summer B" };
            plt.XTicks(groupNames);
            plt.XAxis.Grid(false);
            plt.Legend();
        }