pyplis 0.11.2

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)

• 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 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) or the scipy stack.

Installation

pyplis can be installed from PyPi 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.

Code documentation

The code documentation of pyplis is hosted on Read the Docs. It corresponds to the documentation of the latest commit of this repo.

Getting started

After installation try running and understanding the example 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 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.

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

2. Include DOAS analysis for camera calibration by combining pydoas with flexDOAS.

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