Helper functions

UPDATE THIS, but for now, working examples.

from tristanSim  import TristanSim
from helperFuncs import hist1D, hist2D, avg1D, avg2D
import os
import matplotlib.pyplot as plt
import numpy as np

###
# Some helper functions. So far we have hist1d, avg1,
# hist2D, avg2D.
###

# Use TristanSim class to get access to data.
myRun = TristanSim('/Path/To/Output/')

Further documentation explanation may follow. For now, these examples will have to suffice

# you can take a histogram of particle quantity as
hist1D(myRun[0].xe)
plt.show()

Admittedly this isn’t much better than plt.hist, except about 20 faster. You can pass the hist1D any kwargs that go to plt.plot(), and you can pass an Axes object if you want. As in plt.plot(). hist1D returns as Line2D object.

# Here's a spectrum
fig, ax = plt.subplots()
xmin = min(myRun[0].gammae.min(), 
  myRun[0].gammai.min())
xmax = max(myRun[0].gammae.max(),
  myRun[0].gammai.max())
hist1D(myRun[0].gammae-1, ax = ax, 
  range=(xmin,xmax), 
  bins=200, xscale='log', yscale='log',
  c='r', label ='lecs')
hist1D(myRun[0].gammai-1, ax = ax, 
  range=(xmin,xmax), 
  bins=200, xscale='log', yscale='log', 
  c='b', label ='ions')
plt.xlabel('$\gamma-1$')
plt.ylabel('$EdN/dE$')
plt.legend()
plt.show()

Much more valuable is the ability to make phase plots and averages

hist2D(myRun[0].xi, myRun[0].gammai-1, clabel='$f_i(p)$')
plt.xlabel('$x_i$')
plt.ylabel('$KE_i$')
plt.show()

# And you can average over a y quantity in bins of x. 
# Here is the average ion energy as function of distance.

avg1D(myRun[0].xi, myRun[0].gammai-1)
plt.xlabel('$x_i$')
plt.ylabel(r'$\langle \gamma_i-1 \rangle$')
plt.show()

# Or you can do the same in 2D. (now electrons).
avg2D(myRun[0].xe, myRun[0].ye, myRun[0].gammae-1, 
  cnorm = 'log', bins = [100,50], 
  clabel=r'$\langle KE \rangle$')
plt.xlabel('$x_e$')
plt.ylabel('$y_e$')
plt.show()