Viscid¶

Tools¶

One way to analyze the data used by PSC is using Python, Jupyter and Viscid. Python is hopefully well known. Project Jupyter let’s you interact with Python (and other languages) through your web browser. With some setup, it is possible to run Jupyter remotely and interact with it through a local web broswer, which has the advantage that the data can remain in the remote location, only plots / movies are sent across the network.

Viscid is Python viz library developed by a graduate student at UNH. It is built on top of matplotlib and helps to seamlessly read various data formats.

An example¶

Let’s presume you’ve run the small 2-d flatfoil sample case. The basics of making some plots based on the data generated are shown below.

Importing modules¶

The below imports the modules needed for reading the PSC data and making some plots. Other than viscid, they are pretty standard.

[1]:

%matplotlib inline

import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
import viscid
viscid.calculator.evaluator.enabled = True
from viscid.plot import vpyplot as vlt

%config InlineBackend.figure_format = 'retina'

Open the data files¶

The path to the data will vary for your own run. You usually want to open the top-level pfd.xdmf file that encompasses all the individual output steps.

[2]:

run = "/Users/kai/src/pppl-project/flatfoil/flatfoil_702/pfd.xdmf"
vf = viscid.load_file(run, force_reload=True)

Make a plot¶

Select a particular output step (they are simply numbered consecutively). You can then plot a particular field by name.

[3]:

vf.activate_time(0)
vlt.plot(vf["n_e"]);

Make another plot¶

Here, I select a later output and plot two quantities, which shows how some simple computations can be done.

[4]:

vf.activate_time(10)
plt.figure(figsize=(12, 6))
plt.subplot(1, 2, 1)
vlt.plot(vf["$n_e$=log10(n_e)"], clim=(-1,1), cmap="inferno");
plt.subplot(1, 2, 2)
vlt.plot(vf["$T_e$=log10(Txx_e+Tyy_e+Tzz_e)"], clim=(-2,-1), cmap="inferno");

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