

.. _sphx_glr_gallery_axisartist_demo_curvelinear_grid.py:


=====================
Demo Curvelinear Grid
=====================

Custom grid and ticklines.

This example demonstrates how to use GridHelperCurveLinear to define
custom grids and ticklines by applying a transformation on the grid.
This can be used, as showcase on the second plot, to create polar
projections in a rectangular box.




.. image:: /gallery/axisartist/images/sphx_glr_demo_curvelinear_grid_001.png
    :align: center





.. code-block:: python


    import numpy as np

    import matplotlib.pyplot as plt
    import matplotlib.cbook as cbook

    from mpl_toolkits.axisartist import Subplot
    from mpl_toolkits.axisartist import SubplotHost, \
        ParasiteAxesAuxTrans
    from mpl_toolkits.axisartist.grid_helper_curvelinear import \
        GridHelperCurveLinear


    def curvelinear_test1(fig):
        """
        grid for custom transform.
        """

        def tr(x, y):
            x, y = np.asarray(x), np.asarray(y)
            return x, y - x

        def inv_tr(x, y):
            x, y = np.asarray(x), np.asarray(y)
            return x, y + x

        grid_helper = GridHelperCurveLinear((tr, inv_tr))

        ax1 = Subplot(fig, 1, 2, 1, grid_helper=grid_helper)
        # ax1 will have a ticks and gridlines defined by the given
        # transform (+ transData of the Axes). Note that the transform of
        # the Axes itself (i.e., transData) is not affected by the given
        # transform.

        fig.add_subplot(ax1)

        xx, yy = tr([3, 6], [5.0, 10.])
        ax1.plot(xx, yy, linewidth=2.0)

        ax1.set_aspect(1.)
        ax1.set_xlim(0, 10.)
        ax1.set_ylim(0, 10.)

        ax1.axis["t"] = ax1.new_floating_axis(0, 3.)
        ax1.axis["t2"] = ax1.new_floating_axis(1, 7.)
        ax1.grid(True, zorder=0)


    import mpl_toolkits.axisartist.angle_helper as angle_helper

    from matplotlib.projections import PolarAxes
    from matplotlib.transforms import Affine2D


    def curvelinear_test2(fig):
        """
        polar projection, but in a rectangular box.
        """

        # PolarAxes.PolarTransform takes radian. However, we want our coordinate
        # system in degree
        tr = Affine2D().scale(np.pi/180., 1.) + PolarAxes.PolarTransform()

        # polar projection, which involves cycle, and also has limits in
        # its coordinates, needs a special method to find the extremes
        # (min, max of the coordinate within the view).

        # 20, 20 : number of sampling points along x, y direction
        extreme_finder = angle_helper.ExtremeFinderCycle(20, 20,
                                                         lon_cycle=360,
                                                         lat_cycle=None,
                                                         lon_minmax=None,
                                                         lat_minmax=(0, np.inf),
                                                         )

        grid_locator1 = angle_helper.LocatorDMS(12)
        # Find a grid values appropriate for the coordinate (degree,
        # minute, second).

        tick_formatter1 = angle_helper.FormatterDMS()
        # And also uses an appropriate formatter.  Note that,the
        # acceptable Locator and Formatter class is a bit different than
        # that of mpl's, and you cannot directly use mpl's Locator and
        # Formatter here (but may be possible in the future).

        grid_helper = GridHelperCurveLinear(tr,
                                            extreme_finder=extreme_finder,
                                            grid_locator1=grid_locator1,
                                            tick_formatter1=tick_formatter1
                                            )

        ax1 = SubplotHost(fig, 1, 2, 2, grid_helper=grid_helper)

        # make ticklabels of right and top axis visible.
        ax1.axis["right"].major_ticklabels.set_visible(True)
        ax1.axis["top"].major_ticklabels.set_visible(True)

        # let right axis shows ticklabels for 1st coordinate (angle)
        ax1.axis["right"].get_helper().nth_coord_ticks = 0
        # let bottom axis shows ticklabels for 2nd coordinate (radius)
        ax1.axis["bottom"].get_helper().nth_coord_ticks = 1

        fig.add_subplot(ax1)

        # A parasite axes with given transform
        ax2 = ParasiteAxesAuxTrans(ax1, tr, "equal")
        # note that ax2.transData == tr + ax1.transData
        # Anything you draw in ax2 will match the ticks and grids of ax1.
        ax1.parasites.append(ax2)
        intp = cbook.simple_linear_interpolation
        ax2.plot(intp(np.array([0, 30]), 50),
                 intp(np.array([10., 10.]), 50),
                 linewidth=2.0)

        ax1.set_aspect(1.)
        ax1.set_xlim(-5, 12)
        ax1.set_ylim(-5, 10)

        ax1.grid(True, zorder=0)

    if 1:
        fig = plt.figure(1, figsize=(7, 4))
        fig.clf()

        curvelinear_test1(fig)
        curvelinear_test2(fig)

        plt.draw()
        plt.show()

**Total running time of the script:** ( 0 minutes  0.614 seconds)



.. container:: sphx-glr-footer


  .. container:: sphx-glr-download

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



  .. container:: sphx-glr-download

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

.. rst-class:: sphx-glr-signature

    `Generated by Sphinx-Gallery <https://sphinx-gallery.readthedocs.io>`_
