xinychen / academic-drawing

Providing codes (including Matlab and Python) for visualizing numerical experiment results.

Academic drawing

This is a project providing source codes (including Matlab and Python) for presenting experiment results.

Contents

• Usage
• Our examples
• Our publications

Usage

It is not necessary to open each file in this repository because you can follow this readme document to find your needs.

Our examples

• Download
  • mu10.mat
  • mu_curve10.m

and evaluate these in Matlab, then, you will see the following picture:

• Download
  • BCPF_fiber_rmselb_m30_r5.csv
  • BCPF_fiber_rmselb_m30_r10.csv
  • overfitting.m

and evaluate these in Matlab, then, you will see the following pictures:

• Download
  • bias10.mat
  • heat_map10.m

and evaluate these in Matlab, then, you will see the following picture:

• Download
  • latent_factors.mat
  • latent_factors.m

and evaluate these in Matlab, then, you will see the following pictures:

• Download
  • rmse.mat
  • rmse_curves.m

and evaluate these in Matlab, then, you will see the following picture:

• Download
  • rmse10.mat
  • rmse_curve10.m

and evaluate these in Matlab, then, you will see the following picture:

• Download
  • road1_fiber_ms50_r10.csv
  • time_series_speed1.py
  • time_series_speed2.py

and evaluate these in Python, then, you will see the following pictures:

• Download
  • road1_fiber_ms50_r10.csv
  • speed_curve.m

and evaluate these in Matlab, then, you will see the following picture:

• Download
  • nyc_data_completeness.mat
  • nyc_data_completeness.m

and evaluate these in Matlab, then, you will see the following picture:

Our Publications

Most of these examples are from our publications:

• Xinyu Chen, Zhaocheng He, Yixian Chen, Yuhuan Lu, Jiawei Wang (2019). Missing traffic data imputation and pattern discovery with a Bayesian augmented tensor factorization model. Transportation Research Part C: Emerging Technologies, 104: 66-77. [preprint] [doi] [slide] [data] [Matlab code]

• Xinyu Chen, Zhaocheng He, Lijun Sun (2019). A Bayesian tensor decomposition approach for spatiotemporal traffic data imputation. Transportation Research Part C: Emerging Technologies, 98: 73-84. [preprint] [doi] [data] [Matlab code] [Python code]

  Please consider citing our papers if you find these codes help your research.