.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_graphs/plot_graphs_basics.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_auto_graphs_plot_graphs_basics.py>`
        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
==============================

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.. code-block:: Python

    # sphinx_gallery_thumbnail_number = 4







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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.

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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.

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.. code-block:: Python

    import openturns as ot
    import openturns.viewer as viewer
    import matplotlib.pyplot as plt

    ot.Log.Show(ot.Log.NONE)








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.. code-block:: Python

    n = ot.Normal()
    n






.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    Normal
    <ul>
      <li>name=Normal</li>
      <li>dimension=1</li>
      <li>weight=1</li>
      <li>range=]-inf (-7.65063), (7.65063) +inf[</li>
      <li>description=[X0]</li>
      <li>isParallel=true</li>
      <li>isCopula=false</li>
    </ul>

    </div>
    <br />
    <br />

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.. code-block:: Python

    graph = n.drawPDF()
    view = viewer.View(graph)




.. image-sg:: /auto_graphs/images/sphx_glr_plot_graphs_basics_001.png
   :alt: plot graphs basics
   :srcset: /auto_graphs/images/sphx_glr_plot_graphs_basics_001.png
   :class: sphx-glr-single-img





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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`.

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.. code-block:: Python

    graph = n.drawPDF()
    type(graph)








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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.

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.. code-block:: Python

    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-sg:: /auto_graphs/images/sphx_glr_plot_graphs_basics_002.png
   :alt: Probability density function of the standard gaussian distribution
   :srcset: /auto_graphs/images/sphx_glr_plot_graphs_basics_002.png
   :class: sphx-glr-single-img





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Combine several graphics
------------------------

In order to combine several graphics, we can use the `add` method.

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Let us create an empirical histogram from a sample.

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.. code-block:: Python

    sample = n.getSample(100)








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.. code-block:: Python

    histo = ot.HistogramFactory().build(sample).drawPDF()
    view = viewer.View(histo)




.. image-sg:: /auto_graphs/images/sphx_glr_plot_graphs_basics_003.png
   :alt: X0 PDF
   :srcset: /auto_graphs/images/sphx_glr_plot_graphs_basics_003.png
   :class: sphx-glr-single-img





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Then we add the histogram to the `graph` with the `add` method. The `graph` then contains two plots.

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.. code-block:: Python

    graph.add(histo)
    view = viewer.View(graph)




.. image-sg:: /auto_graphs/images/sphx_glr_plot_graphs_basics_004.png
   :alt: Probability density function of the standard gaussian distribution
   :srcset: /auto_graphs/images/sphx_glr_plot_graphs_basics_004.png
   :class: sphx-glr-single-img





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Draw a cloud
------------

The `Cloud` class creates clouds of bidimensional points. To demonstrate it, let us create two gaussian distributions in two dimensions.

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Create a Funky distribution

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.. code-block:: Python

    corr = ot.CorrelationMatrix(2)
    corr[0, 1] = 0.2
    copula = ot.NormalCopula(corr)
    x1 = ot.Normal(-1.0, 1)
    x2 = ot.Normal(2, 1)
    x_funk = ot.ComposedDistribution([x1, x2], copula)








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Create a Punk distribution

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.. code-block:: Python

    x1 = ot.Normal(1.0, 1)
    x2 = ot.Normal(-2, 1)
    x_punk = ot.ComposedDistribution([x1, x2], copula)








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Let us mix these two distributions.

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.. code-block:: Python

    mixture = ot.Mixture([x_funk, x_punk], [0.5, 1.0])








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.. code-block:: Python

    n = 500
    sample = mixture.getSample(n)








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.. code-block:: Python

    graph = ot.Graph("n=%d" % (n), "X1", "X2", True, "")
    cloud = ot.Cloud(sample)
    graph.add(cloud)
    view = viewer.View(graph)




.. image-sg:: /auto_graphs/images/sphx_glr_plot_graphs_basics_005.png
   :alt: n=500
   :srcset: /auto_graphs/images/sphx_glr_plot_graphs_basics_005.png
   :class: sphx-glr-single-img





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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.

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.. code-block:: Python

    ot.Drawable.GetValidPointStyles()






.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    [square,circle,triangleup,plus,times,diamond,triangledown,star,fsquare,fcircle,ftriangleup,fdiamond,bullet,dot,none,.,,,o,v,^,<,>,1,2,3,4,8,s,p,P,*,h,H,+,x,X,d,D,|,_,, ,None]
    </div>
    <br />
    <br />

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The following method returns the list of colors.

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.. code-block:: Python

    ot.Drawable.GetValidColors()[0:10]






.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    [aliceblue,antiquewhite,antiquewhite1,antiquewhite2,antiquewhite3,antiquewhite4,aquamarine,aquamarine1,aquamarine2,aquamarine3]
    </div>
    <br />
    <br />

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In the following graphics, we use the "aquamarine1" color with "fcircle" circles.

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.. code-block:: Python

    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-sg:: /auto_graphs/images/sphx_glr_plot_graphs_basics_006.png
   :alt: n=500
   :srcset: /auto_graphs/images/sphx_glr_plot_graphs_basics_006.png
   :class: sphx-glr-single-img





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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.

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.. code-block:: Python

    g = ot.SymbolicFunction("x", "sin(x)")








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.. code-block:: Python

    graph = g.draw(-2, 2)
    view = viewer.View(graph)




.. image-sg:: /auto_graphs/images/sphx_glr_plot_graphs_basics_007.png
   :alt: y0 as a function of x
   :srcset: /auto_graphs/images/sphx_glr_plot_graphs_basics_007.png
   :class: sphx-glr-single-img





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I would rather get a dashed curve: let us search for the available line styles.

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.. code-block:: Python

    ot.Drawable.GetValidLineStyles()







.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    [blank,solid,dashed,dotted,dotdash,longdash,twodash]
    </div>
    <br />
    <br />

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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.

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.. code-block:: Python

    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









.. GENERATED FROM PYTHON SOURCE LINES 171-174

.. code-block:: Python

    x = linearSample(-2, 2, 50)
    y = g(x)








.. GENERATED FROM PYTHON SOURCE LINES 175-183

.. code-block:: Python

    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-sg:: /auto_graphs/images/sphx_glr_plot_graphs_basics_008.png
   :alt: Sinus
   :srcset: /auto_graphs/images/sphx_glr_plot_graphs_basics_008.png
   :class: sphx-glr-single-img





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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.

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.. code-block:: Python

    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









.. GENERATED FROM PYTHON SOURCE LINES 202-204

.. code-block:: Python

    pofa = ot.HermiteFactory()








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.. code-block:: Python

    graph = ot.Graph("Orthonormal Hermite polynomials", "x", "y", True, "lower right")
    degreemax = 5
    for k in range(degreemax):
        pk = pofa.build(k)
        curve = pk.draw(-3.0, 3.0, 50)
        curve.setLegends(["P%d" % (k)])
        curve.setColors([createHSVColor(k, degreemax)])
        graph.add(curve)
    view = viewer.View(graph)




.. image-sg:: /auto_graphs/images/sphx_glr_plot_graphs_basics_009.png
   :alt: Orthonormal Hermite polynomials
   :srcset: /auto_graphs/images/sphx_glr_plot_graphs_basics_009.png
   :class: sphx-glr-single-img





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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..

.. GENERATED FROM PYTHON SOURCE LINES 224-228

.. code-block:: Python

    n = ot.Normal()
    myPDF = n.drawPDF()
    myCDF = n.drawCDF()








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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`.

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.. code-block:: Python

    fig = plt.figure(figsize=(12, 4))
    ax_pdf = fig.add_subplot(1, 2, 1)
    _ = viewer.View(myPDF, figure=fig, axes=[ax_pdf])
    ax_cdf = fig.add_subplot(1, 2, 2)
    _ = viewer.View(myCDF, figure=fig, axes=[ax_cdf])
    _ = fig.suptitle("The gaussian")




.. image-sg:: /auto_graphs/images/sphx_glr_plot_graphs_basics_010.png
   :alt: The gaussian
   :srcset: /auto_graphs/images/sphx_glr_plot_graphs_basics_010.png
   :class: sphx-glr-single-img





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Save a plot into a file
-----------------------

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The `View` class has a `save` method which saves the graph into an image.

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.. code-block:: Python

    n = ot.Normal()
    graph = n.drawPDF()
    view = viewer.View(graph)
    view.save("normal.png")




.. image-sg:: /auto_graphs/images/sphx_glr_plot_graphs_basics_011.png
   :alt: plot graphs basics
   :srcset: /auto_graphs/images/sphx_glr_plot_graphs_basics_011.png
   :class: sphx-glr-single-img





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We can use the `dpi` option to configure the resolution in dots per inch.

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.. code-block:: Python

    view.save("normal-100dpi.png", dpi=100)








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Configure the size of a graph with matplotlib
---------------------------------------------

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We first create a graph containing the PDF of a gaussian distribution

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.. code-block:: Python

    n = ot.Normal()
    graph = n.drawPDF()








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The `figure_kw` keyword argument sets the optional arguments of the figure. In the following statement, we set the figure size in inches

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.. code-block:: Python

    view = viewer.View(graph, figure_kw={"figsize": (12, 8)})




.. image-sg:: /auto_graphs/images/sphx_glr_plot_graphs_basics_012.png
   :alt: plot graphs basics
   :srcset: /auto_graphs/images/sphx_glr_plot_graphs_basics_012.png
   :class: sphx-glr-single-img





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The `getFigure` method returns the current figure. This allows one to configure it as any other Matplotlib figure. In the following example, we configure the `suptitle`.

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.. code-block:: Python

    fig = view.getFigure()
    fig.suptitle("The suptitle")
    fig





.. rst-class:: sphx-glr-script-out

 .. code-block:: none


    <Figure size 1200x800 with 1 Axes>



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The `plot_kw` optional argument sets the arguments of the plot. In the following example, we set the color of the plot in blue.

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.. code-block:: Python

    view = viewer.View(graph, plot_kw={"color": "blue"})
    plt.show()



.. image-sg:: /auto_graphs/images/sphx_glr_plot_graphs_basics_013.png
   :alt: plot graphs basics
   :srcset: /auto_graphs/images/sphx_glr_plot_graphs_basics_013.png
   :class: sphx-glr-single-img






.. _sphx_glr_download_auto_graphs_plot_graphs_basics.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: plot_graphs_basics.ipynb <plot_graphs_basics.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: plot_graphs_basics.py <plot_graphs_basics.py>`