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Computational Physics

Software for UB's Computational Physics class.

This updates the now-deprecated project of PHY410.

This software package is to demonstrate the example code in the UB Computational Physics class, PHY 410/505 and 411/506, developed by Prof. Richard Gonsalves (and updated by Prof. Salvatore Rappoccio, and Prof. Tim Thomay). This also includes software from the following sources :

Docker:

git clone https://github.com/ubsuny/CompPhys.git
chmod a+w CompPhys
cd CompPhys
  • Execute docker image (execute every time you log in):
    • Linux/Unix/Mac: ./runDocker.sh ubsuny/compphys:latest
    • Windows: ./runDockerWindows.sh ubsuny/compphys:latest
  • To run a jupyter notebook, when in the container:
    • jupyter notebook --ip 0.0.0.0 --no-browser

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compphys's Issues

Metropolis Hastings trial distribution

While reimplementing the metropolis Hastings algorithm in Tensorflow the data in the Jupiter notebook cannot be reproduced if a normal distribution is used for the trial step.

Possible reason is the following line:

auto x_trial = x_walker + delta*a1;

which is unclear to me why to use the same distribution for the trial as for the walker. In particular since in general this should be a symmetric distribution.

Test data array typo

The test data is partially overlapped with the training data:

train = normalize(df).iloc[0:train_size].values
test = normalize(df).iloc[0:train_size].values

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