Metadata-Version: 2.4
Name: mplstereonet
Version: 0.6.3
Summary: Stereonets for matplotlib
Home-page: https://github.com/joferkington/mplstereonet/
Author: Joe Kington
Author-email: joferkington@gmail.com
License: MIT
Description-Content-Type: text/x-rst
License-File: LICENSE
Requires-Dist: matplotlib>=1.1
Requires-Dist: numpy>=1.1
Dynamic: author
Dynamic: author-email
Dynamic: description
Dynamic: description-content-type
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mplstereonet
============
``mplstereonet`` provides lower-hemisphere equal-area and equal-angle stereonets
for matplotlib.

.. image:: http://joferkington.github.io/mplstereonet/images/equal_area_equal_angle_comparison.png
    :alt: Comparison of equal angle and equal area stereonets.
    :align: center
    :target: https://github.com/joferkington/mplstereonet/blob/master/examples/equal_area_equal_angle_comparison.py


What's New
----------

  * Polar overlays and arbitrary rotated grid overlays. See
    https://mplstereonet.readthedocs.io/en/latest/examples/polar_overlay.html
    for more details.
  * Numerous bugfixes and compatibility with recent versions of matplotlib and
    numpy

Install
-------

``mplstereonet`` can be installed from PyPi using ``pip`` by::

    pip install mplstereonet

Alternatively, you can download the source and install locally using (from the
main directory of the repository)::

    python setup.py install

If you're planning on developing ``mplstereonet`` or would like to experiment
with making local changes, consider setting up a development installation so
that your changes are reflected when you import the package::

    python setup.py develop

Basic Usage
-----------
In most cases, you'll want to ``import mplstereonet`` and then make an axes
with ``projection="stereonet"`` (By default, this is an equal-area stereonet).
Alternately, you can use ``mplstereonet.subplots``, which functions identically
to ``matplotlib.pyplot.subplots``, but creates stereonet axes.

As an example::

    import matplotlib.pyplot as plt
    import mplstereonet

    fig = plt.figure()
    ax = fig.add_subplot(111, projection='stereonet')

    strike, dip = 315, 30
    ax.plane(strike, dip, 'g-', linewidth=2)
    ax.pole(strike, dip, 'g^', markersize=18)
    ax.rake(strike, dip, -25)
    ax.grid()

    plt.show()

.. image:: http://joferkington.github.io/mplstereonet/images/basic.png
    :alt: A basic stereonet with a plane, pole to the plane, and rake along the plane
    :align: center
    :target: https://github.com/joferkington/mplstereonet/blob/master/examples/basic.py
    
Planes, lines, poles, and rakes can be plotted using axes methods (e.g.
``ax.line(plunge, bearing)`` or ``ax.rake(strike, dip, rake_angle)``).

All planar measurements are expected to follow the right-hand-rule to indicate
dip direction. As an example, 315/30S would be 135/30 following the right-hand
rule.

Density Contouring
------------------
``mplstereonet`` also provides a few different methods of producing contoured
orientation density diagrams.

The ``ax.density_contour`` and ``ax.density_contourf`` axes methods provide density
contour lines and filled density contours, respectively.  "Raw" density grids
can be produced with the ``mplstereonet.density_grid`` function.

As a basic example::

    import matplotlib.pyplot as plt
    import numpy as np
    import mplstereonet
    
    fig, ax = mplstereonet.subplots()
    
    strike, dip = 90, 80
    num = 10
    strikes = strike + 10 * np.random.randn(num)
    dips = dip + 10 * np.random.randn(num)
    
    cax = ax.density_contourf(strikes, dips, measurement='poles')
                              
    ax.pole(strikes, dips)
    ax.grid(True)
    fig.colorbar(cax)
    
    plt.show()

.. image:: http://joferkington.github.io/mplstereonet/images/contouring.png
    :alt: Orientation density contours.
    :align: center
    :target: https://github.com/joferkington/mplstereonet/blob/master/examples/contouring.py


By default, a modified Kamb method with exponential smoothing [Vollmer1995]_ is
used to estimate the orientation density distribution. Other methods (such as
the "traditional" Kamb [Kamb1956]_ and "Schmidt" (a.k.a. 1%) methods) are
available as well. The method and expected count (in standard deviations) can
be controlled by the ``method`` and ``sigma`` keyword arguments, respectively.

.. image:: http://joferkington.github.io/mplstereonet/images/contour_angelier_data.png
    :alt: Orientation density contours.
    :align: center
    :target: https://github.com/joferkington/mplstereonet/blob/master/examples/contour_angelier_data.py

Utilities
---------
``mplstereonet`` also includes a number of utilities to parse structural
measurements in either quadrant or azimuth form such that they follow the
right-hand-rule. 

For an example, see parsing_example.py_::

    Parse quadrant azimuth measurements
    "N30E" --> 30.0
    "E30N" --> 60.0
    "W10S" --> 260.0
    "N 10 W" --> 350.0
    
    Parse quadrant strike/dip measurements.
    Note that the output follows the right-hand-rule.
    "215/10" --> Strike: 215.0, Dip: 10.0
    "215/10E" --> Strike: 35.0, Dip: 10.0
    "215/10NW" --> Strike: 215.0, Dip: 10.0
    "N30E/45NW" --> Strike: 210.0, Dip: 45.0
    "E10N   20 N" --> Strike: 260.0, Dip: 20.0
    "W30N/46.7 S" --> Strike: 120.0, Dip: 46.7
    
    Similarly, you can parse rake measurements that don't follow the RHR.
    "N30E/45NW 10NE" --> Strike: 210.0, Dip: 45.0, Rake: 170.0
    "210 45 30N" --> Strike: 210.0, Dip: 45.0, Rake: 150.0
    "N30E/45NW raking 10SW" --> Strike: 210.0, Dip: 45.0, Rake: 10.0

Additionally, you can find plane intersections and make other calculations by
combining utility functions.  See plane_intersection.py_ and
parse_anglier_data.py_ for examples.

Analysis
--------

``mplstereonet`` contains orientation data analysis methods, as well as
plotting functionality.  For example, you can `fit planes to girdles
<https://mplstereonet.readthedocs.io/en/latest/examples/fit_girdle_example.html>`_
or `fit a pole to points
<https://mplstereonet.readthedocs.io/en/latest/mplstereonet.html#mplstereonet.fit_pole>`_,
identify different `modes of conjugate sets of faults
<https://mplstereonet.readthedocs.io/en/latest/examples/kmeans_example.html>`_,
or calculate `flattening values for Flinn plots
<https://mplstereonet.readthedocs.io/en/latest/mplstereonet.html#mplstereonet.eigenvectors>`_.

Full Documentation
------------------

Full documentation is available at https://mplstereonet.readthedocs.io/en/latest/mplstereonet.html

References
----------

.. [Kamb1956] Kamb, 1959. Ice Petrofabric Observations from Blue Glacier,
       Washington, in Relation to Theory and Experiment. Journal of
       Geophysical Research, Vol. 64, No. 11, pp. 1891--1909.

.. [Vollmer1995] Vollmer, 1995. C Program for Automatic Contouring of Spherical
       Orientation Data Using a Modified Kamb Method. Computers &
       Geosciences, Vol. 21, No. 1, pp. 31--49.

.. _parsing_example.py: https://mplstereonet.readthedocs.io/en/latest/examples/parsing_example.html

.. _plane_intersection.py: https://mplstereonet.readthedocs.io/en/latest/examples/plane_intersection.html

.. _parse_anglier_data.py: https://mplstereonet.readthedocs.io/en/latest/examples/parse_angelier_data.html
