.. only:: html .. note:: :class: sphx-glr-download-link-note Click :ref:`here ` to download the full example code .. rst-class:: sphx-glr-example-title .. _sphx_glr_auto_graphs_plot_graphs_basics.py: A quick start guide to graphs ============================== .. code-block:: default # sphinx_gallery_thumbnail_number = 4 In this example, we show how to create graphs. We show how to create and configure its axes and its colors. We show how to create a plot based on the combination of several plots. The `draw` method the `Graph` class ----------------------------------- The simplest way to create a graphics is to use the `draw` method. The `Normal` distribution for example provides a method to draw the density function of the gaussian distribution. .. code-block:: default import openturns as ot import openturns.viewer as viewer from matplotlib import pylab as plt ot.Log.Show(ot.Log.NONE) .. code-block:: default n = ot.Normal() n .. raw:: html

Normal(mu = 0, sigma = 1)

.. code-block:: default graph = n.drawPDF() view = viewer.View(graph) .. image:: /auto_graphs/images/sphx_glr_plot_graphs_basics_001.png :alt: plot graphs basics :class: sphx-glr-single-img To configure the look of the plot, we can first observe the type of graphics returned by the `drawPDF` method returns: it is a `Graph`. .. code-block:: default graph = n.drawPDF() type(graph) The `Graph` class provides several methods to configure the legends, the title and the colors. Since a graphics can contain several sub-graphics, the `setColors` takes a list of colors as inputs argument: each item of the list corresponds to the sub-graphics. .. code-block:: default graph.setXTitle("N") graph.setYTitle("PDF") graph.setTitle("Probability density function of the standard gaussian distribution") graph.setLegends(["N"]) graph.setColors(["blue"]) view = viewer.View(graph) .. image:: /auto_graphs/images/sphx_glr_plot_graphs_basics_002.png :alt: Probability density function of the standard gaussian distribution :class: sphx-glr-single-img Combine several graphics ------------------------ In order to combine several graphics, we can use the `add` method. Let us create an empirical histogram from a sample. .. code-block:: default sample = n.getSample(100) .. code-block:: default histo = ot.HistogramFactory().build(sample).drawPDF() view = viewer.View(histo) .. image:: /auto_graphs/images/sphx_glr_plot_graphs_basics_003.png :alt: X0 PDF :class: sphx-glr-single-img Then we add the histogram to the `graph` with the `add` method. The `graph` then contains two plots. .. code-block:: default graph.add(histo) view = viewer.View(graph) .. image:: /auto_graphs/images/sphx_glr_plot_graphs_basics_004.png :alt: Probability density function of the standard gaussian distribution :class: sphx-glr-single-img Draw a cloud ------------ The `Cloud` class creates clouds of bidimensional points. To demonstrate it, let us create two gaussian distributions in two dimensions. Create a Funky distribution .. code-block:: default corr = ot.CorrelationMatrix(2) corr[0, 1] = 0.2 copula = ot.NormalCopula(corr) x1 = ot.Normal(-1., 1) x2 = ot.Normal(2, 1) x_funk = ot.ComposedDistribution([x1, x2], copula) Create a Punk distribution .. code-block:: default x1 = ot.Normal(1.,1) x2 = ot.Normal(-2,1) x_punk = ot.ComposedDistribution([x1, x2], copula) Let us mix these two distributions. .. code-block:: default mixture = ot.Mixture([x_funk, x_punk], [0.5,1.]) .. code-block:: default n=500 sample = mixture.getSample(n) .. code-block:: default graph = ot.Graph("n=%d" % (n), "X1", "X2", True, '') cloud = ot.Cloud(sample) graph.add(cloud) view = viewer.View(graph) .. image:: /auto_graphs/images/sphx_glr_plot_graphs_basics_005.png :alt: n=500 :class: sphx-glr-single-img We sometimes want to customize the graphics by choosing the type of point (square, triangle, circle, etc...), of line (continuous, dashed, etc...) or another parameter. We can know the list of possible values with the corresponding `getValid` method. For example, the following function returns the possible values of the `PointStyle` parameter. .. code-block:: default ot.Drawable.GetValidPointStyles() .. raw:: html

[bullet,circle,diamond,dot,fcircle,fdiamond,fsquare,ftriangleup,none,plus,square,star,times,triangledown,triangleup]#15

The following method returns the list of colors. .. code-block:: default ot.Drawable.GetValidColors()[0:10] .. raw:: html

[aliceblue,antiquewhite,antiquewhite1,antiquewhite2,antiquewhite3,antiquewhite4,aquamarine,aquamarine1,aquamarine2,aquamarine3]#10

In the following graphics, we use the "aquamarine1" color with "fcircle" circles. .. code-block:: default graph = ot.Graph("n=%d" % (n), "X1", "X2", True, '') cloud = ot.Cloud(sample) cloud.setColor("aquamarine1") cloud.setPointStyle("fcircle") graph.add(cloud) view = viewer.View(graph) .. image:: /auto_graphs/images/sphx_glr_plot_graphs_basics_006.png :alt: n=500 :class: sphx-glr-single-img Configure the style of points and the thickness of a curve ---------------------------------------------------------- Assume that we want to plot the sine curve from -2 to 2. The simplest way is to use the `draw` method of the function. .. code-block:: default g = ot.SymbolicFunction("x","sin(x)") .. code-block:: default graph = g.draw(-2,2) view = viewer.View(graph) .. image:: /auto_graphs/images/sphx_glr_plot_graphs_basics_007.png :alt: y0 as a function of x :class: sphx-glr-single-img I would rather get a dashed curve: let us search for the available line styles. .. code-block:: default ot.Drawable.GetValidLineStyles() .. raw:: html

[blank,solid,dashed,dotted,dotdash,longdash,twodash]

In order to use the `Curve` class, it will be easier if we have a method to generate a `Sample` containing points regularly spaced in an interval. .. code-block:: default def linearSample(xmin,xmax,npoints): '''Returns a sample created from a regular grid from xmin to xmax with npoints points.''' step = (xmax-xmin)/(npoints-1) rg = ot.RegularGrid(xmin, step, npoints) vertices = rg.getVertices() return vertices .. code-block:: default x = linearSample(-2,2,50) y = g(x) .. code-block:: default graph = ot.Graph("Sinus","x","sin(x)",True) curve = ot.Curve(x,y) curve.setLineStyle("dashed") curve.setLineWidth(4) graph.add(curve) view = viewer.View(graph) .. image:: /auto_graphs/images/sphx_glr_plot_graphs_basics_008.png :alt: Sinus :class: sphx-glr-single-img Create colored curves --------------------- In some situations, we want to create curves with different colors. In this case, the following function generates a color corresponding to the `indexCurve` integer in a ensemble of `maximumNumberOfCurves` curves. .. code-block:: default def createHSVColor(indexCurve,maximumNumberOfCurves): '''Create a HSV color for the indexCurve-th curve from a sample with maximum size equal to maximumNumberOfCurves''' color = ot.Drawable.ConvertFromHSV(indexCurve * 360.0/maximumNumberOfCurves, 1.0, 1.0) return color .. code-block:: default pofa = ot.HermiteFactory() .. code-block:: default graph = ot.Graph("Orthonormal Hermite polynomials","x","y",True,"bottomright") degreemax = 5 for k in range(degreemax): pk = pofa.build(k) curve = pk.draw(-3.,3.,50) curve.setLegends(["P%d" % (k)]) curve.setColors([createHSVColor(k,degreemax)]) graph.add(curve) view = viewer.View(graph) .. image:: /auto_graphs/images/sphx_glr_plot_graphs_basics_009.png :alt: Orthonormal Hermite polynomials :class: sphx-glr-single-img Create matrices of graphics --------------------------- The library does *not* has objects to create a grid of graphics. However, we can use the `add_subplot` function from Matplotlib. Let us create two graphics of the PDF and CDF of the following gaussian distribution.. .. code-block:: default n = ot.Normal() myPDF = n.drawPDF() myCDF = n.drawCDF() .. code-block:: default import pylab as pl import openturns.viewer as otv We create a figure with the `figure` function from Matplotlib, then we add two graphics with the `add_subplot` function. We use the `viewer.View` function to create the required Matplotlib object. Since we are not interested by the output of the `View` function, we use the dummy variable `_` as output. The title is finally configured with `suptitle`. .. code-block:: default fig = pl.figure(figsize=(12, 4)) ax_pdf = fig.add_subplot(1, 2, 1) _ = otv.View(myPDF, figure=fig, axes=[ax_pdf]) ax_cdf = fig.add_subplot(1, 2, 2) _ = otv.View(myCDF, figure=fig, axes=[ax_cdf]) _ = fig.suptitle("The gaussian") .. image:: /auto_graphs/images/sphx_glr_plot_graphs_basics_010.png :alt: The gaussian :class: sphx-glr-single-img Save a plot into a file ----------------------- The `View` class has a `save` method which saves the graph into an image. .. code-block:: default import openturns.viewer as otv .. code-block:: default n = ot.Normal() graph = n.drawPDF() view = otv.View(graph) view.save("normal.png") .. image:: /auto_graphs/images/sphx_glr_plot_graphs_basics_011.png :alt: plot graphs basics :class: sphx-glr-single-img We can use the `dpi` option to configure the resolution in dots per inch. .. code-block:: default view.save("normal-100dpi.png", dpi=100) Configure the size of a graph with matplotlib --------------------------------------------- .. code-block:: default import openturns.viewer as otv We first create a graph containing the PDF of a gaussian distribution .. code-block:: default n = ot.Normal() graph = n.drawPDF() The `figure_kwargs` keyword argument sets the optional arguments of the figure. In the following statement, we set the figure size in inches .. code-block:: default view = otv.View(graph, figure_kwargs = {"figsize": (12, 8)}) .. image:: /auto_graphs/images/sphx_glr_plot_graphs_basics_012.png :alt: plot graphs basics :class: sphx-glr-single-img The `getFigure` method returns the current figure. This allows to configure it as any other Matplotlib figure. In the following example, we configure the `suptitle`. .. code-block:: default fig = view.getFigure() fig.suptitle("The suptitle") fig .. rst-class:: sphx-glr-script-out Out: .. code-block:: none