pyfigures 0.1.10

PyFigures will assist you assemble publication ready scientific figures in no time.

PyFigures

Effortless creation of high-quality scientific figures in Python.

Since a video is better than a thousand (click on the image above to view the demo). Or click here to access the complete demo playlist.

Note: Most demo images are public domain and sourced from the Cell Image Library.

Installation

1. Conda Installation (Advanced Users)

For advanced users, we recommend installing the software using Conda. This will offer unlimited scripting capabilities.

Prerequisites

• Install Miniconda if it is not already installed on your system.

Installation Steps

Perform the following steps only once to set up your environment:

1. Open a Command Prompt or Terminal.

   • To open a command prompt on Windows, press Windows+R then type cmd.
   • To open a command prompt on MacOS, press Command+Space then type Terminal.
   • To open a command prompt on Ubuntu, press Ctrl+Alt+T.

2. Create and activate a new Conda environment:

   conda create -y -n PyFigures python==3.10.12
   conda activate PyFigures
   

3. Upgrade pip:

   pip install -U pip
   

4. Install the pyfigures package:

   pip install -U pyfigures
   

5. Optional: Install openjdk8 if you plan to use bioformats

   pip install install-jdk
   python -c "import os; import jdk; jdk_path = os.path.join(os.path.expanduser('~'), '.jdk/jdk8'); jre_path = os.path.join(os.path.expanduser('~'), '.jre/jdk8'); os.makedirs(jdk_path, exist_ok=True); os.makedirs(jre_path, exist_ok=True); jdk.install('8', path=jdk_path); jdk.install('8', path=jre_path, jre=True)"
   

6. Optional: Install additional dependencies for bioformats support:

   pip install -U pyfigures[all]
   

   Note: if you received errors, you may not have a compiler installed (see the Troubleshooting section after)

Run

Note: The following steps need to be performed only after the software has been installed.

Open a command prompt and type:

conda activate PyFigures
python -m pyfigures

Optional: After running the software, you may deactivate the Conda environment if you wish:

conda deactivate

2. Standalone Executable Installation (Easy)

Alternatively, you can install the software as a standalone executable. This does not require Conda and can be run on any system without the need for additional dependencies, but scripting capabilities will be limited to the bundled dependencies.

• Windows coming soon!
• MacOS coming soon!
• Linux coming soon!

Troubleshooting Installation Issues

If you encounter issues related to installing the python-javabridge package, follow these steps:

1. Prerequisites for All Systems Before installing python-javabridge, ensure the following:

   • Ensure a C Compiler is Available:

     • The package requires a C compiler to build C extensions. Depending on your operating system, this will be different.

2. Windows-Specific Instructions

   If you are on Windows and encounter the error Microsoft Visual C++ 14.0 or greater is required, follow these steps to resolve it:

   • Download the Build Tools:

     • Visit the Microsoft C++ Build Tools download page.

   • Run the installer.

     • During the installation process, select the "Desktop development with C++" workload.

   • Verify Installation:

     • Open a command prompt and run 'cl'. If the command is recognized and provides output, the installation was successful.

   • Retry Installation:

     • After installing the build tools, try to install the python-javabridge package again:

       pip install python-javabridge
       

3. MacOS and Linux

   For MacOS and Linux systems, ensure you have the necessary build tools:

   • MacOS:

     Install Xcode Command Line Tools by running:

     xcode-select --install
     

   • Linux:

     Install build-essential (on Debian-based systems) or the equivalent development tools package for your distribution. For example, on Ubuntu, you can run:

     sudo apt-get install build-essential
     

   After ensuring that a suitable compiler is available, retry the installation:

   pip install python-javabridge
   

   By following these steps, you should be able to resolve issues and successfully install python-javabridge. If you continue to experience problems, consult the relevant documentation or seek support from the community

Third party libraries

Below is a list of the 3^rd party libraries used by PyFigures.

IMPORTANTLY: if you disagree with any license below, please uninstall PyFigures.

Library name	Use	Link	License
Markdown	Python implementation of Markdown	https://pypi.org/project/Markdown/	BSD
matplotlib	Plots images and graphs	https://pypi.org/project/matplotlib/	PSF
numpy	Array/Image computing	https://pypi.org/project/numpy/	BSD
Pillow	Reads 'basic' images (.bmp, .png, .pnm, ...)	https://pypi.org/project/Pillow/	HPND
PyQt6	Graphical user interface (GUI)	https://pypi.org/project/PyQt6/	GPL v3
QtPy	An abstraction layer for PyQt and PySide	https://pypi.org/project/QtPy/	MIT
read-lif	Reads Leica .lif files	https://pypi.org/project/read-lif/	GPL v3
czifile	Reads Zeiss .czi files	https://pypi.org/project/czifile/	BSD (BSD-3-Clause)
tifffile	Reads .tiff files (also reads Zeiss .lsm files)	https://pypi.org/project/tifffile/	BSD
python-bioformats	A library to open scientific images	https://pypi.org/project/python-bioformats/	GPLv2
python-javabridge	A library to run java executables (required for bioformats)	https://pypi.org/project/python-javabridge/	BSD
scikit-image	Image processing	https://pypi.org/project/scikit-image/	BSD (Modified BSD)
scipy	Great library to work with numpy arrays	https://pypi.org/project/scipy/	BSD
scikit-learn	Great library for machine learning	https://pypi.org/project/scikit-learn/	BSD
tqdm	Command line progress	https://pypi.org/project/tqdm/	MIT, MPL 2.0
natsort	'Human' like sorting of strings	https://pypi.org/project/natsort/	MIT
numexpr	Speeds up image math	https://pypi.org/project/numexpr/	MIT
urllib3	Model architecture and trained models download	https://pypi.org/project/urllib3/	MIT
qtawesome	Elegant icons for PyQT/PySide	https://pypi.org/project/QtAwesome/	MIT
pandas	Data analysis toolkit	https://pypi.org/project/pandas/	BSD (BSD-3-Clause)
numba	GPU acceleration of numpy ops	https://pypi.org/project/numba/	BSD
roifile	A library to read ImageJ ROIs	https://pypi.org/project/roifile/	BSD 3-Clause

Other Figure-Making Software

FigureJ

ScientiFig

omero.figure

EzFig

QuickFigures