fakecbed 0.5.2

A Python library for generating quickly images that imitate convergent beam electron diffraction patterns.

Fake Convergence Beam Electron Diffraction (FakeCBED)

fakecbed is a Python library for generating quickly images that imitate convergent beam electron diffraction patterns.

Visit the fakecbed website for a web version of the installation instructions, the reference guide, and the examples archive.

The source code can be found in the fakecbed GitHub repository.

Table of contents

• Instructions for installing and uninstalling fakecbed
  • Installing fakecbed
    • Installing fakecbed using pip
    • Installing fakecbed using conda
  • Uninstalling fakecbed
• Learning how to use fakecbed

Instructions for installing and uninstalling fakecbed

Installing fakecbed

For all installation scenarios, first open up the appropriate command line interface. On Unix-based systems, you could open e.g. a terminal. On Windows systems you could open e.g. an Anaconda Prompt as an administrator.

Before installing fakecbed, it is recommended that users install PyTorch in the same environment that they intend to install fakecbed according to the instructions given here for their preferred PyTorch installation option.

Installing fakecbed using pip

Before installing fakecbed, make sure that you have activated the (virtual) environment in which you intend to install said package. After which, simply run the following command:

pip install fakecbed

The above command will install the latest stable version of fakecbed.

To install the latest development version from the main branch of the fakecbed GitHub repository, one must first clone the repository by running the following command:

git clone https://github.com/mrfitzpa/fakecbed.git

Next, change into the root of the cloned repository, and then run the following command:

pip install .

Note that you must include the period as well. The above command executes a standard installation of fakecbed.

Optionally, for additional features in fakecbed, one can install additional dependencies upon installing fakecbed. To install a subset of additional dependencies (along with the standard installation), run the following command from the root of the repository:

pip install .[<selector>]

where <selector> can be one of the following:

• tests: to install the dependencies necessary for running unit tests;
• examples: to install the dependencies necessary for executing files stored in <root>/examples, where <root> is the root of the repository;
• docs: to install the dependencies necessary for documentation generation;
• all: to install all of the above optional dependencies.

Alternatively, one can run:

pip install fakecbed[<selector>]

elsewhere in order to install the latest stable version of fakecbed, along with the subset of additional dependencies specified by <selector>.

Installing fakecbed using conda

Before proceeding, make sure that you have activated the (virtual) conda environment in which you intend to install said package. For Windows systems, users must install PyTorch separately prior to following the remaining instructions below.

To install fakecbed using the conda package manager, run the following command:

conda install -c conda-forge fakecbed

The above command will install the latest stable version of fakecbed.

Uninstalling fakecbed

If fakecbed was installed using pip, then to uninstall, run the following command:

pip uninstall fakecbed

If fakecbed was installed using conda, then to uninstall, run the following command:

conda remove fakecbed

Learning how to use fakecbed

For those new to the fakecbed library, it is recommended that they take a look at the Examples page, which contain code examples that show how one can use the fakecbed library. While going through the examples, readers can consult the fakecbed reference guide to understand what each line of code is doing.