Metadata-Version: 2.0
Name: interpies
Version: 0.3.1
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
Description-Content-Type: UNKNOWN
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 (>=1.0a9)
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 (alpha)
* `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
* `basemap` and `cartopy` for making maps

### Installation

#### Dependencies

I recommend using [Anaconda](https://www.anaconda.com/what-is-anaconda/) for the installation of both Python and most of the dependencies.

Once Anaconda has been installed, make sure the `conda-forge` channel is added to your configuration:

`conda config --add channels conda-forge`

Next, I would suggest creating a new environment for working with `interpies`. You could start with this command:

`conda create --name interpies gdal scikit-learn scikit-image matplotlib ipykernel obspy 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 1.0a9 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-1.0a12-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).

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`

#### Upgrading

Because a version of `rasterio` > 1.0 is not directly available to `pip`, upgrading an existing installation of `interpies` must be done without trying to upgrade dependencies (or do it separately). Here is the command:

`pip install --upgrade --no-deps interpies`

## 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:

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

![image of magnetic data](/doc/mag_survey_example.png)

For more advanced examples, please see the notebooks.

## Documentation

Under construction.


