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DataViewer README

中文说明

INTRODUCTION

This tool is for dataset visualization.

  1. 2dViewer : designed for 2D dataset visualization
  2. maskMaker : designed for making 2D masks
  3. 3dViewer : designed for 3D volume dataset visualization

SETUP

The programs are based on Anaconda environment.

  1. Install Anaconda 3
  2. Run 'make.sh' (for Linux and MacOS user), or create conda environment using 'environment.yaml' by yourself

USAGE

  1. View 2D patterns
python ./2dViewer/viewer.py
  1. Make 2D mask
python ./2dViewer/maskMaker.py
  1. View 3D volume
python ./3dViewer/viewer.py

DETAILS

(1) 3dViewer

The first thing you need to do is to choose data file , then click "Import Selected File" button. You can choose different plotting types (The select list named "Plot") as you want.

[Movie Maker]

Click "Rorate and Movie" button to rotate the scene or create a gif movie.

  • To make a movie, you should set the total length first and click "Make movie" (There is a progress bar at the left-bottom corner of the pop window).
  • Just click "Rotate" if you only want a rotation view of the model.

[Data Format]

  • Now support ".npy"(numpy), ".mat"(matlab), “.h5”(HDF5) and ".bin"(binary) files. Please store your matrix into file in these formats.

  • "scalar" plot means your data contains a scalar field, which requires that the input should have 3 dimensions.

    • shape=(Nx,Ny,Nz)

  • "vector" plot means your data contains a vector field, which requires that the input should have 2 dimensions, with 6 rows and Num_of_points columns.

    • s=[X,Y,Z,Vx,Vy,Vz] , shape=(6, Num_of_points)

  • "points plot" means your data contains a set of points (with or without intensity) in 3D space, and the input should have 2 dimensions, with 3 or 4 rows and Num_of_points columns.

    • s=[X,Y,Z] or s=[X,Y,Z,Intensity] , shape=(3 or 4, Num_of_points)

(2) 2dViewer

Just drag HDF5 file into the "File List" tab and double click dataset to show image / plot figure.

There are several parameters to adjust the visualization in "Parameter" tab.

(3) 2D mask maker

There are three types of mask making tools:

  • circle tool
  • rectangle tool
  • polygon tool

By adjusting the ROI (region of interest) of these mask making tools, users could define mask shape freely.

  • Single Right Click on the ROI : Merge this ROI into current mask.

  • Double Left Click on the ROI : Remove this ROI from current mask.

  • Right Click dataset in File List : Show context menu, users could set the chosen data(2D) as current mask or merge the chosen data(2D) into current mask.

In "Parameters" tab, there are some important configuration settings on data input / output and viewing. For example, "Mask Good" and "Mask Bad" define the values of unmasked and masked pixels in mask file.