Skip to content
Snippets Groups Projects
Commit c3dbfd46 authored by Jesse Mapel's avatar Jesse Mapel
Browse files

Added a quick start guide to the docs & restructured Pythong docs (#378)

* Added loads docs

* Added other base driver mix-ins

* Simple quick start guide

* minor clean up

* Added quick start and cleaned up

* Combined mix-in files

* Fixed label data name

* Restructured Python docs

* Added Python rotation docs

* PR review updates

* Updated label_data description
parent a2c93cf1
No related branches found
No related tags found
No related merge requests found
Showing
with 178 additions and 15 deletions
...@@ -2,24 +2,14 @@ ...@@ -2,24 +2,14 @@
=================================== ===================================
.. autofunction:: ale.drivers.load .. autofunction:: ale.drivers.load
.. autofunction:: ale.drivers.loads
.. toctree:: .. toctree::
base base
co_driver
dawn_driver
hayabusa2_driver
isis_ideal_driver
juno_driver
lro_driver
mess_driver
mex_driver
mro_driver
nh_driver
ody_driver
selene_driver
tgo_driver
viking_driver
voyager_driver
util util
rotation
transformation
mix_ins/index
concrete_drivers/index
:mod:`Distortion Model` --- Distortion Model Type Mix-ins
=========================================================
The mix-ins in this module are for common distortion models that are shared
between multiple sensors. Distortion models that are unique to a sensor or
mission are kept in the driver module for that mission.
.. versionadded:: 0.1.0
.. automodule:: ale.base.type_distortion
:synopsis:
:members:
:show-inheritance:
:mod:`mix-ins` --- Mix-in Classes
=================================
The classes in these modules are mix-ins that combined with the base
:py:class:`ale.base.base.Driver` class create the concrete drivers.
.. toctree::
supplementary_data
label_data
sensor_type
distortion_model
:mod:`Label Data` --- Label Data Mix-ins
========================================
Modules for accessing label data.
.. versionadded:: 0.1.0
.. automodule:: ale.base.label_isis
:synopsis:
:members:
:show-inheritance:
.. versionadded:: 0.1.0
.. automodule:: ale.base.label_pds3
:synopsis:
:members:
:show-inheritance:
:mod:`Sensor Type` --- Sensor Type Mix-ins
==========================================
The mix-ins in this module are for different types of imaging sensors.
.. versionadded:: 0.1.0
.. automodule:: ale.base.type_sensor
:synopsis:
:members:
:show-inheritance:
:mod:`Supplementary Data` --- Supplementary Data Mix-ins
========================================================
Modules for accessing supplementary data when computing exterior orientation.
.. versionadded:: 0.1.0
.. automodule:: ale.base.data_naif
:synopsis:
:members:
:show-inheritance:
.. versionadded:: 0.1.0
.. automodule:: ale.base.data_isis
:synopsis:
:members:
:show-inheritance:
:mod:`rotation` --- Python Rotations
====================================
The :mod:`ale.rotation` module
.. versionadded:: 0.1.0
.. automodule:: ale.rotation
:synopsis:
:members:
:mod:`transformation` --- Python Frame Transformations
======================================================
The :mod:`ale.transformation` module
.. versionadded:: 0.1.0
.. automodule:: ale.transformation
:synopsis:
:members:
#########
Tutorials
#########
:Release: |version|
:Date: |today|
-----------------------------------------
.. toctree::
:maxdepth: 2
quick_start
===============
ALE Quick Start
===============
This document provides a set of steps to get setup for generating Image Support
Data (ISD) for an image.
Installation
============
The easiest way to setup ALE is using Anaconda. Once you have
`Anaconda <https://www.anaconda.com/products/individual>`_ or
`Miniconda <https://docs.conda.io/en/latest/miniconda.html>`_ installed install
ALE from conda-forge by running
.. code-block::
conda install -c conda-forge ale
.. note::
It is highly recommended that you use
`environments <https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html>`_
to manage the packages you install with Anaconda.
Data
====
Planetary imagery is not archived with sufficient data to generate an ISD
from only the image and its label. ALE currently supports two supplementary data
sources: ISIS cubes with attached SPICE, and NAIF SPICE Kernels.
If you are working with ISIS cubes that have attached SPICE (the
`spiceinit <https://isis.astrogeology.usgs.gov/Application/presentation/Tabbed/spiceinit/spiceinit.html>`_
application has been run on them) then ALE will use the data embedded in the
cube file.
If you are working with PDS3 images or ISIS cubes that do not have attached
SPICE, then you will need to download the required NAIF SPICE Kernels for your
image. It is recommended that you use the metakernels provided in the
`PDS kernel archives <https://naif.jpl.nasa.gov/naif/data_archived.html>`_.
You can specify the path for ALE to search for metakernels via the
``ALESPICEROOT`` environment variable. This should be set to the directory where
you have the PDS kernel archives downloaded. An example structure would be
* $ALESPICEROOT
* mro-m-spice-6-v1.0
* dawn-m_a-spice-6-v1.0
* mess-e_v_h-spice-6-v1.0
See :py:attr:`ale.base.data_naif.NaifSpice.kernels` for more information about how to
specify NAIF SPICE kernels.
Load/Loads
==========
The :py:meth:`ale.drivers.load` and :py:meth:`ale.drivers.loads` functions are
the main interface for generating ISDs. Simply pass them the path to your image
file/label and they will attempt to generate an ISD for it.
.. code-block:: python
import ale
image_label_path = "/path/to/my/image.lbl"
isd_string = ale.loads(image_label_path)
0% Loading or .
You are about to add 0 people to the discussion. Proceed with caution.
Please register or to comment