Metadata-Version: 2.0
Name: interpies
Version: 0.1.2
Summary: A collection of functions for reading, displaying, transforming and analyzing geophysical data.
Home-page: https://github.com/jobar8/interpies
Author: Joseph Barraud
Author-email: joseph.barraud@geophysicslabs.com
License: BSD
Keywords: geophysics raster gdal gravimetry magnetometry seismic
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Natural Language :: English
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Topic :: Scientific/Engineering
Requires-Dist: matplotlib
Requires-Dist: numpy
Requires-Dist: rasterio (>=1.0)
Requires-Dist: scikit-image
Requires-Dist: scikit-learn
Requires-Dist: scipy

Interpies
=========

``interpies`` is a collection of functions to read and analyse
geophysical data, especially non-seismic data such as magnetic and
gravity data.

Table of Contents
-----------------

-  `Getting Started <##GettingStarted>`__

   -  `Requirements <###Prerequisits>`__
   -  `Installation <###Installation>`__

-  `Examples <##Examples>`__
-  `Documentation <##Documentation>`__

Getting Started
---------------

Requirements
~~~~~~~~~~~~

Interpies requires ``Python 3.x`` and makes use of the following
libraries:

-  ``numpy``
-  ``matplotlib``
-  ``rasterio`` version > 1.0
-  ``gdal``
-  ``scikit-learn``
-  ``scikit-image``

Optional:

-  ``obspy`` for reading and writing SEG-Y files (seismic data)
-  ``geopandas`` for reading survey line data
-  ``ipykernel`` for working with ``interpies`` in Jupyter notebooks

Installation
~~~~~~~~~~~~

Dependencies
^^^^^^^^^^^^

I recommend using
`Anaconda <https://www.continuum.io/what-is-anaconda>`__ for the
installation of both Python and most of the dependencies.

Once Anaconda has been installed, I would suggest creating a new
environment for working with ``interpies``. If working with SEG-Y files
is not required (so you will not be able to load the ``segy_io``
module), you could start with this command:

``conda create --name interpies gdal scikit-learn scikit-image matplotlib ipykernel python=3.6``

Next, install ``rasterio``. You could try using
``conda install rasterio``. However, the only version available on
conda-forge might be the old 0.36. The alpha version 1.09a or better is
required for ``interpies`` to work. So carefully check which version is
going to be installed first.

On **Windows**, if the version does not match, simply download the
binaries for the required version from Christoph Gohlke's
`website <http://www.lfd.uci.edu/~gohlke/pythonlibs/#rasterio>`__. Then
run, for example:

``pip install rasterio-1.0a9-cp36-cp36m-win_amd64.whl``

And that should do. If you encounter other problems with this part of
the installation, please refer to the `rasterio
installation <https://mapbox.github.io/rasterio/installation.html>`__.

If you need SEG-Y files, then you need ``obspy``, which, at the time of
writing, would conflict with ``matplotlib 2.0``. So installing ``obspy``
would limit ``matplotlib`` to version 1.5.3. Use:

``conda create --name interpies gdal scikit-learn scikit-image matplotlib obspy ipykernel python=3.6``

Optionally, you could also install ``geopandas``, which is great for
reading line data from geophysical surveys. And don't forget to install
``ipykernel`` to run the notebooks in the ``interpies`` environment.

interpies
^^^^^^^^^

Installing ``interpies`` itself is done directly with:

``pip install interpies``

Or you could do it manually by first cloning the current repository:

``$ git clone https://github.com/jobar8/interpies.git``

Then run the following command in the repository directory:

``$ python setup.py install``

Examples
--------

The basic usage of ``interpies`` is to load gridded data into a *grid*
object, which then gives access to various methods for transforming and
displaying the data. So, loading magnetic data and creating a map with
the grid is simply done with:

::

    import interpies 
    grid1 = interpies.open(r'..\data\brtpgrd.gxf')
    grid1.show()

.. figure:: /doc/mag_survey_example.png
   :alt: image of magnetic data

   image of magnetic data

For more advanced examples, please see the notebooks.

Documentation
-------------

Under construction.


