Metadata-Version: 1.1
Name: pyplis
Version: 0.11.2
Summary: A Python library for the analysis UV SO2 camera data
Home-page: https://github.com/jgliss/pyplis
Author: Jonas Gliss
Author-email: jg@nilu.no
License: GPLv3+
Description: pyplis is a Python toolbox for the analysis of UV SO2 camera data. It includes a large collection of routines for the analysis of such data, for instance:

        

        - Several routines for plume background estimation

        - Automatic cell calibration 

        - DOAS calibration routine including two methods to identify the field of view of a DOAS instrument within the camera images

        - Plume velocity retrieval either using an optical flow analysis or using signal cross correlation

        - Detailed analysis of the measurement geometry including automized retrieval of distances to the emission plume and/or to topographic features in the camera images (on a pixel basis)

        - Routine for image based light dilution correction

          

        .. note::

        

          The software was renamed from **piscope** to **pyplis** on 17.02.2017 

          

        Requirements

        ============

        

        Requirements are listed ordered in decreasing likelyhood to run into problems when using pip for installation (on Windows machines you may use the pre-compiled binary wheels on Christoph Gohlke's `webpage <http://www.lfd.uci.edu/~gohlke/pythonlibs/>`_)

        

        - numpy >= 1.11.0

        - scipy >= 0.17.0

        - opencv (cv2) >= 2.4.11

        - Pillow (PIL fork) >= 3.3.0 (installs scipy.misc.pilutil)

        - astropy >= 1.0.3

        - geonum >= 1.0.0

            

          - latlon >= 1.0.2

          - srtm.py >= 0.3.2

          - pyproj  >= 1.9.5.1

            

        - pandas == 0.16.2

        - matplotlib >= 1.4.3

        

        **Optional dependencies (to use extra features)**

        

        - pydoas >= 1.0.0

        

        We recommend using `Anaconda <https://www.continuum.io/downloads>`_ as package manager since it includes most of the required dependencies and is updated on a regular basis. Moreover, it is probably the most comfortable way to postinstall and upgrade dependencies such as OpenCV (`see here <http://stackoverflow.com/questions/23119413/how-to-install-python-opencv-through-conda>`__) or the scipy stack.

        

        Installation

        ============

        pyplis can be installed from `PyPi <https://pypi.python.org/pypi/pyplis>`_ using::

        

          pip install pyplis

          

        or from source by downloading and extracting the latest release. After navigating to the source folder (where the setup.py file is located), call::

        

          python setup.py install

        

        On Linux::

          

          sudo python setup.py install 

          

        In case the installation fails make sure that all dependencies (see above) are installed correctly. pyplis is currently only supported for Python v2.7.

        

        .. note::

        

          The code currently still undergoes improvements and changes to the repo are commited on a daily basis. PyPi and Github releases are only made for stable versions.

        

        Code documentation

        ==================

        

        The code documentation of pyplis is hosted on `Read the Docs <http://pyplis.readthedocs.io/en/latest/code_lib.html>`__. It corresponds to the documentation of the latest commit of this repo.

        

        Getting started

        ===============

        

        After installation try running and understanding the `example scripts <https://github.com/jgliss/pyplis/tree/master/scripts>`_. The scripts require downloading an example dataset (see following section for instructions).

        

        Example and test data

        =====================

        

        The pyplis example data (required to run example scripts) is not part of the installation. It can be downloaded `here <https://folk.nilu.no/~gliss/pyplis_testdata/pyplis_etna_testdata.zip>`__ or automatically within a Python shell (after installation) using::

        

          import pyplis

          pyplis.inout.download_test_data(LOCAL_DIR)

          

        which downloads the data to the installation **data** directory if ``LOCAL_DIR`` is unspecified. Else, (and if ``LOCAL_DIR`` is a valid location) it will be downloaded into ``LOCAL_DIR`` which will then be added to the supplementary file **_paths.txt** located in the installation **data** directory. It can then be found by the test data search method::

        

          pyplis.inout.find_test_data()

          

        The latter searches all paths provided in the file **_paths.txt** whenever access to the test data is required. It raises an Exception, if the data cannot be found.

        

        .. note::

        

          If you download the data manually (e.g. using the link provided above), please unzip it into a suitable directory ``LOCAL_DIR`` and let pyplis know about it using::

          

            import pyplis

            pyplis.inout.set_test_data_path(``LOCAL_DIR``)

            

            

        TODO's

        ======

        

        1. Write high level analysis class for signal cross correlation (currently only a low level method exists)

          

          

        Future developments / ideas

        ===========================

        

        1. Re-implementation of GUI framework

        #. Include DOAS analysis for camera calibration by combining `pydoas <https://pypi.python.org/pypi/pydoas/1.0.1>`__ with `flexDOAS <https://github.com/gkuhl/flexDOAS>`__. 

        #. Include online access to meteorological databases (e.g. to estimate wind direction, velocity)

          

        .. note::

        

          Open for collaboration

        
Keywords: sample setuptools development
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Education
Classifier: License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)
Classifier: Programming Language :: Python :: 2.7
