updating documentation

README.rst

@@ -40,16 +40,40 @@ This documentation in full is available at https://savu.readthedocs.org/en/lates
 
 .. image:: files_and_images/Savu_logo_2_L_Res_trans.png
    :scale: 40 %
-   :align: left
+   :align: right
 
 
 Tomography Reconstruction and Processing Pipeline
 =================================================
-
-Savu is a Python package to assist with the processing and reconstruction of tomography data.  The project was started at Diamond Light Source when a new pipeline was required for dealing with the more complex tomography reconstruction processes that were appearing at the facility. `[1]`_
+
+Savu is a Python package to assist with the processing and reconstruction of parallel-beam tomography data.  The project originated in the Data Analysis Group at the Diamond Light Source (UK synchrotron) to address the growing, and increasingly complex, needs of the tomography community.
+
+Designed to allow greater flexibility in tomography data processing, Savu is capable of processing N-dimensional full-field tomography and mapping tomography data, along with concurrent processing of multiple datasets such as those collected as part of a multi-modal setup.  Savu process lists, tailored to a specific experiment and passed to the framework at runtime along with the data, detail the processing steps that are required.
+
+A Savu process list is created using the Savu configurator tool, which stacks together plugins chosen from a repository. Each plugin performs a specific independent task, such as correction, filtering, reconstruction. For a list of available plugins see plugin API.
+
+Savu is currently in use across the tomography beamlines at Diamond to reconstruct both full-field tomography data and multi-modal, mapping tomography data.
+
 
 .. _[1]: https://dx.doi.org/10.1098/rsta.2014.0398
 
 Features
 ========
 
+- Full-field and mapping tomography data processing
+- multi-modal data processing
+- Absorption, fluorescence, diffraction and ptychography data processing
+- Handles N-dimensional data and multiple datasets
+- Supports multiple data formats
+- Runs in serial or parallel on your local machine
+- Runs in parallel across a cluster
+- Supports very large data processing with parallel HDF5 (not limited by RAM)
+- Allows flexible data slicing (e.g. alternate between projection and sinogram processing)
+- Plugin architecture with CPU and GPU plugins
+- Processing tailored to a specific experimental setup
+- Easy integration of new functionality
+
+
+
+
+

doc/source/conf.py

@@ -167,7 +167,7 @@
 
 # The name of an image file (relative to this directory) to place at the top
 # of the sidebar.
-#html_logo = 'files_and_images/logo_downsample.png'
+html_logo = 'files_and_images/Savu_black_downsample.png'
 
 # The name of an image file (within the static path) to use as favicon of the
 # docs.  This file should be a Windows icon file (.ico) being 16x16 or 32x32

doc/source/dls_installer.rst

@@ -0,0 +1,55 @@
+Notes for installing Savu at Diamond
+====================================
+
+(1) Install Python Anaconda for Python 2.7 version (https://www.continuum.io/downloads). Then:
+    >> export PATH=/path/to/anaconda/bin:$PATH
+
+(2) >> conda install conda-build
+
+# These library versions have been tested but any versions can be tried.
+(3) >> module load openmpi/1.6.5   # potentially any MPI library
+    >> module load cuda/7.0
+    >> module load fftw
+
+(4)(a) To install a stable version of Savu:
+        # replace 1.2 with newest version
+        >> conda install -c savu savu=1.2
+   (b) To install from the savu_test recipe (which installs from the master repository):
+        >> conda build savu_test
+        >> savubuild=`conda build savu_test --output`
+        >> conda install --use-local $savubuild
+
+==================================================================================
+NB: Case of (4)(b): If changes are required to conda recipes and they have not
+been pushed to the master repository then, before running step (5), do
+>> export RECIPES=/path/to/folder/containing/recipes
+==================================================================================
+
+(5) >> savu_installer.sh dls
+
+# Savu should now be installed!
+# Test the installation.
+(6) Copy the Savu module template at /dls/science/groups/das/savu/savu_module_template
+    to your local module folder (/home/username/privatemodules), changing the name if
+    you prefer, and update the relevant paths inside the file. Then
+    >> module load your_savu_module
+
+(7) Update launcher scripts, to module load your_savu_module.
+    (just type 'which savu_launcher.sh' to find the location).
+    (a) savu_launcher.sh and savu_mpijob.sh if you will run across the cluster
+    (b) savu_mpijob_local.sh if you will run locally in mpi mode.
+
+(8) From a fresh terminal:
+    >> source savu_setup.sh
+
+    # single-threaded tests
+    >> savu_quick_tests
+    >> savu_full_tests
+
+    # local mpi tests
+    >> mpi_cpu_local_test.sh
+    >> mpi_gpu_local_test.sh
+
+    # cluster mpi tests
+    >> mpi_cpu_cluster_test.sh /path/to/output/folder
+    >> mpi_gpu_cluster_test.sh /path/to/output/folder

doc/source/installation.rst

@@ -1,5 +1,11 @@
 Installation Guide
 ******************
 
-Description of how to install Savu (internal/external)
+Table of Contents
+=================
+
+.. toctree::
+   :maxdepth: 2
+
+    dls_installer