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

.. only:: html

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

        :ref:`Go to the end <sphx_glr_download_auto_examples_plot_slips_and_def.py>`
        to download the full example code

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

.. _sphx_glr_auto_examples_plot_slips_and_def.py:


Slip and deformation figure of a Stochastic generation
============================================================================================================
    This example makes an 3d plot of Slip distribution
    :param X_array: Longitude grid
    :param Y_array: Latitude grid
    :param depth: Depth grid
    :param Slip: Slip grid
    :param filename: Optional, filename if you wanna save fig
    :return: Figure of Slip and deformation distribution

.. GENERATED FROM PYTHON SOURCE LINES 12-67



.. rst-class:: sphx-glr-horizontal


    *

      .. image-sg:: /auto_examples/images/sphx_glr_plot_slips_and_def_001.png
         :alt: plot slips and def
         :srcset: /auto_examples/images/sphx_glr_plot_slips_and_def_001.png
         :class: sphx-glr-multi-img

    *

      .. image-sg:: /auto_examples/images/sphx_glr_plot_slips_and_def_002.png
         :alt: Seafloor deformation
         :srcset: /auto_examples/images/sphx_glr_plot_slips_and_def_002.png
         :class: sphx-glr-multi-img





.. code-block:: Python

    import geostochpy
    import matplotlib.pyplot as plt
    import numpy as np
    from geostochpy import modokada as mo
    # shorelines
    shorelines_file = geostochpy.get_data('pacific_shorelines_east_4min.npy')
    shore = np.load(shorelines_file)
    #
    route_trench = geostochpy.get_data('trench-chile.txt')
    # load trench
    lonfosa, latfosa  = geostochpy.load_trench(route_trench)
    nx=18
    ny=50
    width=180
    length=500
    dx=width/nx
    dy=length/ny
    region=[-78,-68,-38,-28]
    slabdep,slabdip,slabstrike,slabrake=geostochpy.load_files_slab2(zone='south_america',rake=True)
    # Se realiza la falla a lo largo del trench, y se le da el valor más al norte de la falla. 
    # 
    # Luego, se deben tener las profundidades en cada subfalla, para ello se interpolan los datos de Slab2 con geostochpy.interp_slabtofault
    north=-29.5
    lons,lons_ep,lats,lats_ep=geostochpy.make_fault_alongtrench(lonfosa,latfosa,north, nx,ny,width,length)
    [X_grid,Y_grid,dep,dip,strike,rake]=geostochpy.interp_slabtofault(lons,lats,nx,ny,slabdep,slabdip,slabstrike,slabrake)
    # ##### Se crea la matriz de slips medios con geostochpy.matriz_media(mean,dep)
    ## Creation slip models
    # mean matrix
    Mw=9.0
    media,rigidez=geostochpy.media_slip(Mw,dx*1000,dy*1000,dep)
    leveque_taper=geostochpy.taper_LeVeque(dep,55000)
    villarroel_taper=geostochpy.taper_except_trench_tukey(dep,alpha_dip=0.3,alpha_strike=0.3)
    taper=leveque_taper*villarroel_taper
    mu = geostochpy.matriz_medias_villarroel(media,taper)
    # matriz de covarianza
    C    = geostochpy.matriz_covarianza_optimized(dip, dep, X_grid, Y_grid,length*1000,width*1000)
    Slip=geostochpy.distribucion_slip(C, mu, 20)
    Slip,rigidez,Mo_original,Mo_deseado=geostochpy.escalar_magnitud_momento(Mw, Slip, dep, dy*1000, dx*1000,prem=True) # se escala el Slip a la magnitud deseada <--------- Slip final
    # Hypocenter=geostochpy.hypocenter(X_grid,Y_grid,dep,length,width) se tiene en cuenta la rigidez con el modelo PREM incluido @fetched with Rockhound
    geostochpy.plot_slip(X_grid,Y_grid,lonfosa,latfosa,Slip,'slip.png',show=True)
    dtopo = mo.okada_solucion_optimized( X_grid, Y_grid, 550/180, strike, dip, dep, rake, Slip, 550000, resolucion = 1/30., tamano_buffer = 1., verbose = False ) # calculo deformacion
    deformation=dtopo.dZ_at_t(0)
    X_deformation=dtopo.X
    Y_deformation=dtopo.Y
    geostochpy.plot_deformation(X_deformation,Y_deformation,lonfosa,latfosa,deformation.reshape(X_deformation.shape),'deformation.png')
    dtopo.plot_dZ_colors(t=0,dZ_interval=1)
    plt.plot(shore[:,0]-360, shore[:,1], 'g')
    plt.plot(lonfosa,latfosa,'darkgreen')
    plt.axis(region)
    plt.grid(visible=True,axis='both')
    plt.plot(-71.63, -33.03,'o',color='gold')
    plt.text(-71.63, -33.03,'Valparaíso',ha='left')
    plt.show()
    # dtopo.write(filename_def,dtopo_type=3)
    # geostochpy.plot_slip_gmt(region,X_grid,Y_grid,lonfosa,latfosa,Slip,dx,dy,filename)


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

   **Total running time of the script:** (0 minutes 25.884 seconds)


.. _sphx_glr_download_auto_examples_plot_slips_and_def.py:

.. only:: html

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

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

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

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

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


.. only:: html

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

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