' + + '' + + _("Hide Search Matches") + + "
" + ) + ); + }, + + /** + * helper function to hide the search marks again + */ + hideSearchWords: () => { + document + .querySelectorAll("#searchbox .highlight-link") + .forEach((el) => el.remove()); + document + .querySelectorAll("span.highlighted") + .forEach((el) => el.classList.remove("highlighted")); + localStorage.removeItem("sphinx_highlight_terms") + }, + + initEscapeListener: () => { + // only install a listener if it is really needed + if (!DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS) return; + + document.addEventListener("keydown", (event) => { + // bail for input elements + if (BLACKLISTED_KEY_CONTROL_ELEMENTS.has(document.activeElement.tagName)) return; + // bail with special keys + if (event.shiftKey || event.altKey || event.ctrlKey || event.metaKey) return; + if (DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS && (event.key === "Escape")) { + SphinxHighlight.hideSearchWords(); + event.preventDefault(); + } + }); + }, +}; + +_ready(SphinxHighlight.highlightSearchWords); +_ready(SphinxHighlight.initEscapeListener); diff --git a/about.html b/about.html new file mode 100644 index 00000000..4186ee8f --- /dev/null +++ b/about.html @@ -0,0 +1,207 @@ + + + + + + +
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+ pyTEMlib¶
+Python framework for model based analysis of TEM/STEM data
+What?¶
+-
+
The pyTEMlib:
+-
+
is a pycroscopy package based on python
+enables quantitative analysis through model based approach
+provides routines for the analysis of diffraction, image and spectroscopic datasets
+handles one, two, three, and four dimensional datasets
+works in jupyter notebooks and in python programs.
+provides dialog windows for metadata and analysis input in jupyter notebooks and in python programs.
+
+pyNSID is a python package that currently provides three areas of analysis:
+-
+
Diffraction: Single and poly crystalline diffraction data and analysis in parallel and convergent illumination
+Imaging: Image analysis, atom detection and image stack registration.
+EELS: It provides a framework for quantification of EELS spectra and spectrum images.
+
+Just as scipy uses numpy underneath, scientific packages like pyTEMlib use sidpy format for dataset representation
+and pyNSID for all file-handling.
+Dialogs are based on pyQt5 and some features require Ipython widgets
+The packages sidpy and pyNSID use popular packages such as numpy, h5py, dask, matplotlib, etc. for most of
+the storage, computation, and visualization.
+
+
+Note
+We are running weekly hackathons for pycroscopy development every Friday from 3-5 PM - USA Eastern time. +The requirements for participation are: knowledge of python, numpy, h5py, git. +Please email vasudevanrk at ornl.gov to be added to the hackathons
+Why?¶
+pyTEMlib originates in the need for teaching and the development of new techniques for TEM/STEM data analysis. +Please, see my lecture note(-books) for information on the background of analysis.
+-
+
- 1. Growing data sizes
-
+
Cannot use desktop computers for analysis
+Need: High performance computing, storage resources and compatible, scalable file structures
+
+- 2. Increasing data complexity
-
+
Sophisticated imaging and spectroscopy modes resulting in 5,6,7… dimensional data
+Need: Robust software and generalized data formatting
+
+- 3. Multiple file formats
-
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Different formats from each instrument. Proprietary in most cases
+Incompatible for correlation
+Need: Open, instrument-independent data format
+
+- 4. Expensive analysis software
-
+
Software supplied with instruments often insufficient / incapable of custom analysis routines
+Commercial software (Eg: Matlab, Origin..) are often prohibitively expensive.
+Need: Free, powerful, open source, user-friendly software
+
+- 5. Closed science
-
+
Analysis software and data not shared
+No guarantees of reproducibility or traceability
+Need: open source data structures, file formats, centralized code and data repositories
+
+
Who?¶
+-
+
We envision pyTEMlib to be a convenient package that facilitates all scientists to analyse data and develop new methods of anlysis, without being burdened with basic code functionality.
+This project is being led by staff members at Oak Ridge National Laboratory (ORNL), and professors at University of Tennessee, Knoxville
+We invite anyone interested to join our team to build better, free software for the scientific community
+Please visit our credits and acknowledgements page for more information.
+If you are interested in integrating our in your existing package, please get in touch with us.
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+ Contact us¶
+Here are a few options for you to get in touch with the developers and the user community +to ask questions, report bugs, request features etc:
+-
+
If you have a GitHub account (free), please raise an issue.
+If you have a GMail account (free), please start a new thread in our google group
+
-
+
When reporting a bug / asking certain questions, we will be able to respond faster if you can provide:
+-
+
a (simplified) script / snippet that reproduces the error(s) you are facing
+the full description of the error(s)
+details regarding your operating system (Mac / Windows / Linux)
+Software versions - python, pyNSID and core dependency packages (numpy, h5py, dask, matplotlib, etc.)
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+ Index
+ +
+ _
+ | A
+ | B
+ | C
+ | D
+ | E
+ | F
+ | G
+ | H
+ | I
+ | J
+ | K
+ | L
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+ | N
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+ pyTEMlib Documentation¶
+Model Based Analysis of TEM/STEM Data
+Last Update 03/25/2022
+Jump to our GitHub project page
+
+
+pyTEMlib
+ +Source code API¶
+| + | Created on Sat Jan 19 10:07:35 2019 |
+
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+Examples
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+ Installation¶
+Preparing for pyTEMlib¶
+pyTEMlib requires many commonly used scientific and numeric python packages such as numpy, h5py etc. +To simplify the installation process, we recommend the installation of +Anaconda which contains most of the prerequisite packages, +conda - a package / environment manager, +as well as an interactive development environment - Spyder.
+Do you already have Anaconda installed?
+-
+
No?
+-
+
Download and install Anaconda for Python 3.6
+
+Yes?
+-
+
Is your Anaconda based on python 3.5+?
+-
+
No?
+-
+
Uninstall existing Python / Anaconda distribution(s).
+Restart computer
+
+Yes?
+-
+
Proceed to install pyTEMlib
+
+
+
+
Compatibility¶
+-
+
pyTEMlib is compatible with python 3.5 onwards. Please raise an issue if you find a bug.
+We do not support 32 bit architectures
+We only support text that is UTF-8 compliant due to restrictions posed by HDF5
+
Terminal¶
+Installing, uninstalling, or updating pyTEMlib (or any other python package for that matter) can be performed using the Terminal application.
+You will need to open the Terminal to type any command shown on this page.
+Here is how you can access the Terminal on your computer:
-
+
Windows - Open
+Command Promptby clicking on the Start button on the bottom left and typingcmdin the search box. +You can either click on theCommand Promptthat appears in the search result or just hit the Enter button on your keyboard.-
+
Note - be sure to install in a location where you have write access. Do not install as administrator unless you are required to do so.
+
+MacOS - Click on the
Launchpad. You will be presented a screen with a list of all your applications with a search box at the top. +Alternatively, simultaneously hold down theCommandandSpacekeys on the keyboard to launch theSpotlight search. +Typeterminalin the search box and click on theTerminalapplication.
+Linux (e.g - Ubuntu) - Open the Dash by clicking the Ubuntu (or equivalent) icon in the upper-left, type “terminal”. +Select the Terminal application from the results that appear.
+
Installing pyTEMlib¶
+-
+
Ensure that a compatible Anaconda distribution has been successfully installed
+Open a terminal window.
+You can now install pyTEMlib via
+pipas shown below. +Type the following command into the terminal / command prompt and hit the Return / Enter key:-
+
pip:
+++pip install pyTEMlib +
+
+
Installing from a specific branch (advanced users ONLY)¶
+Note that we do not recommend installing pyTEMlib this way since branches other than the master branch may contain bugs.
+
+
+
+
+Note
+Windows users will need to install git before proceeding. Please type the following command in the Command Prompt:
conda install git
+Install a specific branch of pyTEMlib (dev in this case):
pip install -U git+https://github.com/pycroscopy/pyTEMlib@dev
+Updating pyTEMlib¶
+We recommend periodically updating your conda / anaconda distribution. Please see these instructions to update anaconda.
+If you already have pyTEMlib installed and want to update to the latest version, use the following command in a terminal window:
+pip install -U --no-deps pyTEMlib
+If it does not work try reinstalling the package:
+pip uninstall pyTEMlib
+pip install pyTEMlib
+Other software¶
+We recommend HDF View for exploring HDF5 files generated by and used in pyTEMlib.
+
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+ EELS_tools¶
+part of
+pyTEMlib, a pycroscopy library
+by
+Gerd Duscher
+Materials Science & Engineering +Joint Institute of Advanced Materials +The University of Tennessee, Knoxville
+Usage of the EELS Tools of pyTEMlib
+ +
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+ Image_tools¶
+part of
+pyTEMlib, a pycroscopy library
+by
+Gerd Duscher
+Materials Science & Engineering +Joint Institute of Advanced Materials +The University of Tennessee, Knoxville
+Usage of the Image Tools of pyTEMlib
+ +
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+ Revisions¶
+Starting with revision from version 0.2021.2.22
+Revision 0.2021.3.1¶
+-
+
Moved read_poscar function from kinematic_scattering to file_tools.py and added read_cif function.
+Revised kinematic scattering library and renamed to kinematic_scattering.py. This function handles tilted samples
+
better. +- added image_dialog to interactive_image with interactive histogram to change contrast in images +- added multislice tools in dynamic_scattering.py (supercell potential is rather basic)
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+Search.setIndex({"docnames": ["_autosummary/pyTEMlib", "_autosummary/pyTEMlib.animation", "_autosummary/pyTEMlib.animation.InteractiveAberration", "_autosummary/pyTEMlib.animation.InteractiveRonchigramMagnification", "_autosummary/pyTEMlib.animation.add_aperture", "_autosummary/pyTEMlib.animation.add_lens", "_autosummary/pyTEMlib.animation.deficient_holz_line", "_autosummary/pyTEMlib.animation.deficient_kikuchi_line", "_autosummary/pyTEMlib.animation.geometric_ray_diagram", "_autosummary/pyTEMlib.animation.propagate_beam", "_autosummary/pyTEMlib.atom_tools", "_autosummary/pyTEMlib.atom_tools.atom_refine", "_autosummary/pyTEMlib.atom_tools.atoms_clustering", "_autosummary/pyTEMlib.atom_tools.find_atoms", "_autosummary/pyTEMlib.atom_tools.gauss_difference", "_autosummary/pyTEMlib.atom_tools.intensity_area", "_autosummary/pyTEMlib.config_dir", "_autosummary/pyTEMlib.crystal_tools", "_autosummary/pyTEMlib.crystal_tools.atoms_from_dictionary", 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"module-pyTEMlib.xrpa_x_sections"]]}})
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