Metadata-Version: 2.4
Name: datview
Version: 1.2.0
Summary: GUI software for viewing images, text, cine, and HDF files.
Home-page: https://github.com/algotom/datview
Download-URL: https://github.com/algotom/datview.git
Author: Nghia Vo
Author-email: nvo@bnl.gov
License: Apache 2.0
Keywords: HDF Viewer,CINE viewer,NXS Viewer,Image viewer,Data viewer
Platform: Any
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: OS Independent
Classifier: Natural Language :: English
Classifier: Topic :: Scientific/Engineering
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: h5py
Requires-Dist: hdf5plugin
Requires-Dist: pillow
Requires-Dist: matplotlib
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Dynamic: description
Dynamic: description-content-type
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# DatView
### (Dat)a (View)er software 
![Datview_Logo](https://github.com/algotom/datview/raw/main/icon.png)

---

*Python GUI software for folder browsing and viewing text, image, Cine, and HDF files*

---


Motivation
==========
In synchrotron facilities, where Linux OS and open-source software are the primary tools, 
users often need to switch between multiple GUI applications for different tasks such as 
Nautilus for folder browsing, NeXpy or HDFView for viewing HDF files, Gedit for 
text files, and ImageJ for image viewing.

This separation of tools is inconvenient, especially since many users are not familiar 
with the Linux OS. **DatView** provides a unified GUI for all these tasks, improving 
efficiency and user experience. **DatView** runs across multiple operating systems.

Design Philosophy
=================

DatView has been developed following a few key guidelines:
-   Minimize dependencies and the codebase.
-   Maximize functionality and maintainability.

With these principles in mind, DatView was built using only a few dependencies:
-   H5py, Hdf5Plugin, Pillow, and Matplotlib.
-   The GUI components are built with Tkinter, a built-in Python library.

For distributing the software through Pip and Conda, the software is structured based on 
the RUI (Rendering-Utilities-Interactions) concept, which is a user-friendly 
adaptation of the MVC design pattern.

For the easiest usage, a monolithic codebase (**datview.py**, approximately 1,850 lines) 
is provided, allowing users to simply copy the file and run it without needing to install 
the software through Pip or Conda, provided that their Python environment includes H5py, Pillow, 
and Matplotlib.

Features
========

-   Fast folder browsing and file listing. Note that the GUI appears more visually 
    refined on Windows OS compared to the demonstration below, which was captured on Red Hat Linux.

    ![Fig1](https://github.com/algotom/datview/raw/main/figs/fig1.png)

-   Viewing metadata in an HDF file or Cine file. Displaying the contents of a text file.

    ![Fig2](https://github.com/algotom/datview/raw/main/figs/fig2.png)

-   Interactive viewing 1D, 2D, or 3D datasets in an HDF file. Supports ROI zooming, line profile 
    selection, contrast adjustment, and slicing along axis 0 and 1 

    ![Fig3](https://github.com/algotom/datview/raw/main/figs/fig3.png)

-   Interactive viewing of TIF files in a folder or frames of a Cine file.
-   Interactive viewing of an image (JPG, PNG, TIF,...)
-   Viewing 1D or 2D datasets of an HDF file in table format.
-   Opening multiple interactive viewers simultaneously.
-   Saving a 2D array in a 3D dataset of an HDF file or Cine file as an image.
-   Saving a 1D or 2D dataset of an HDF file or the current line profile as a CSV file.

    ![Fig4](https://github.com/algotom/datview/raw/main/figs/fig4.png)

Installation
============

Install [Miniconda, Anaconda or Miniforge](https://docs.conda.io/projects/conda/en/latest/user-guide/install/index.html), then 
open a Linux terminal or the Miniconda/Anaconda PowerShell prompt and use the following commands
for installation.

Using pip:
```commandline
pip install datview
```
Using conda:
```commandline
conda install -c conda-forge datview
```
Once installed, launching Datview with
```commandline
datview
```
Using -h for option usage
```commandline
datview -h
```
---
Installing from source:
- If using a single file:
    + Copy the file *datview.py*. Install python, h5py, pillow, and matplotlib
    + Run:
        ```commandline
        python datview.py
        ```
- If using setup.py
    + Create conda environment
      ```commandline
      conda create -n datview python=3.11
      conda activate datview
      ``` 
    + Clone the source (git needs to be installed)
      ```commandline
      git clone https://github.com/algotom/datview.git
      ```
    + Navigate to the cloned directory (having setup.py file)
      ```commandline
      pip install .
      ```
