.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "examples/batch_mode/16-tetration_spring.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

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

        Click :ref:`here <sphx_glr_download_examples_batch_mode_16-tetration_spring.py>`
        to download the full example code

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_examples_batch_mode_16-tetration_spring.py:


===========================================
16 - Tetration (power tower) zoom: "Spring"
===========================================

Coloring based on attracting cycle order and attractivity.
This zoom is quite shallow however already features complex structures

Note: due to the long running time and high antialising needed, this image
has been precomputed.

Reference:
`fractalshades.models.Power_tower`

.. GENERATED FROM PYTHON SOURCE LINES 16-142



.. image-sg:: /examples/batch_mode/images/sphx_glr_16-tetration_spring_001.png
   :alt: 16 tetration spring
   :srcset: /examples/batch_mode/images/sphx_glr_16-tetration_spring_001.png
   :class: sphx-glr-single-img





.. code-block:: default


    import os
    import numpy as np

    import fractalshades as fs
    import fractalshades.models as fsm

    import fractalshades.colors as fscolors
    from fractalshades.postproc import (
        Postproc_batch,
        Raw_pp,
    )
    from fractalshades.colors.layers import (
        Color_layer,
        Bool_layer,
        Virtual_layer,
    )



    def plot(plot_dir):

        fractal = fsm.Power_tower(plot_dir)
        calc_name = 'test'

        x = 1.4073514628685297
        y = -3.362771439936941
        dx = 0.0005297704717647524
        xy_ratio = 1.8
        theta_deg = 135.0

        nx = 800
        compute_order = True
        max_order = 10000
        eps_newton_cv = 1e-12

        interior_color = (
            0.40784314274787903,
            0.5882353186607361,
            0.2823529541492462
        )
        colormap = colormap = fscolors.cmap_register["lily"]
        zmin = 0.9 * 1.0376274585723877 + 0.1 * 1.2009856700897217
        zmax = 0.3 * 1.0376274585723877 + 0.7 * 1.2009856700897217


        fractal.zoom(x=x, y=y, dx=dx, nx=nx, xy_ratio=xy_ratio,
             theta_deg=theta_deg, projection="cartesian")

        fractal.newton_calc(
            calc_name=calc_name,
            subset=None,
            compute_order=compute_order,
            max_order=max_order,
            max_newton=20,
            eps_newton_cv=eps_newton_cv
        )


        layer_name = "cycle_order"

        pp = Postproc_batch(fractal, calc_name)
        pp.add_postproc(layer_name, Raw_pp("order"))
        pp.add_postproc("attr", Raw_pp("dzrdz", func=lambda x: np.abs(x)))
        pp.add_postproc("interior", Raw_pp("stop_reason",
                        func=lambda x: x != 1)
        )

        plotter = fs.Fractal_plotter(pp)   
        plotter.add_layer(Bool_layer("interior", output=False))

        plotter.add_layer(Color_layer(
                layer_name,
                func=lambda x: np.log(np.log(np.log(x + 1.) + 1.) + 1.),
                colormap=colormap,
                probes_z=[zmin, zmax],
                output=True))
        plotter[layer_name].set_mask(plotter["interior"],
                                     mask_color=interior_color)
        plotter.add_layer(Virtual_layer("attr", func=None, output=False))
    
        plotter[layer_name].set_twin_field(plotter["attr"], 0.3)

        plotter.plot()
    
        # Renaming output to match expected from the Fractal GUI
        layer = plotter[layer_name]
        file_name = "{}_{}".format(type(layer).__name__, layer.postname)
        src_path = os.path.join(fractal.directory, file_name + ".png")
        dest_path = os.path.join(fractal.directory, calc_name + ".png")
        if os.path.isfile(dest_path):
            os.unlink(dest_path)
        os.link(src_path, dest_path) 


    def _plot_from_data(plot_dir):
        # Private function only used when building fractalshades documentation
        # This example takes too long too run to autogenerate the image for the
        # gallery each - so just grabbing the file from the html doc static path
        import PIL

        data_path = fs.settings.output_context["doc_data_dir"]
        im = PIL.Image.open(os.path.join(data_path, "tetration_spring.jpg"))
        rgb_im = im.convert('RGB')
        tag_dict = {"Software": "fractalshades " + fs.__version__,
                    "example_plot": "tetration_spring"}
        pnginfo = PIL.PngImagePlugin.PngInfo()
        for k, v in tag_dict.items():
            pnginfo.add_text(k, str(v))
        if fs.settings.output_context["doc"]:
            fs.settings.add_figure(fs._Pillow_figure(rgb_im, pnginfo))
        else:
            # Should not happen
            raise RuntimeError()


    if __name__ == "__main__":
        # Some magic to get the directory for plotting: with a name that matches
        # the file or a temporary dir if we are building the documentation
        try:
            realpath = os.path.realpath(__file__)
            plot_dir = os.path.splitext(realpath)[0]
            plot(plot_dir)
        except NameError:
            import tempfile
            with tempfile.TemporaryDirectory() as plot_dir:
                fs.utils.exec_no_output(_plot_from_data, plot_dir)

.. rst-class:: sphx-glr-timing

   **Total running time of the script:** ( 0 minutes  0.109 seconds)


.. _sphx_glr_download_examples_batch_mode_16-tetration_spring.py:

.. only:: html

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


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

      :download:`Download Python source code: 16-tetration_spring.py <16-tetration_spring.py>`

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

      :download:`Download Jupyter notebook: 16-tetration_spring.ipynb <16-tetration_spring.ipynb>`


.. only:: html

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

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_