def show_the_data(paths, t=None, x=None, y=None, z=None, **kwargs):
"""Function which plots the data.
Parameters
----------
paths : tuple
The paths of the runs
t : slice
The desired t slice of showdata
x : slice
The desired x slice of showdata
y : slice
The desired y slice of showdata
z : slice
The desired z slice of showdata
**kwargs : key word arguments
Not used here, but acts like a "dumpster" for additional keyword
arguments
"""
for path in paths:
print("Showing data from {}".format(path))
n = collect('n', xguards=False, yguards=False, path=path, info=False)
# Show the data
showdata(n[t, x, y, z])
def show_the_data(paths, t=None, x=None, y=None, z=None, **kwargs):
"""Function which plots the data.
Parameters
----------
paths : tuple
The paths of the runs
t : slice
The desired t slice of showdata
x : slice
The desired x slice of showdata
y : slice
The desired y slice of showdata
z : slice
The desired z slice of showdata
**kwargs : key word arguments
Not used here, but acts like a "dumpster" for additional keyword
arguments
"""
for path in paths:
print("Showing data from {}".format(path))
n = collect('n', xguards=False, yguards=False, path=path, info=False)
# Show the data
showdata(n[t,x,y,z])
def showScanData(self, quant, simType, interval=5, filename='blah',
movie=0, fps=5, dpi=300):
'''
can only be used on ypi laptop with ffmpeg installed
gotta make sure path to dataDir is the laptop one
'''
if filename == 'blah':
filename = '{}-{}.mp4'.format(quant, simType)
else:
filename = filename
dataDir = self.dataDir.split('/')[1:-1] # [4:]
newDir = ''
for i in dataDir:
newDir += '/' + i
quant = self.scanCollect(quant, simType)
interval = slice(0, -1, interval)
titles = self.scanParams
tme = self.scanCollect('t_array', simType)
times = []
for i in tme:
times.append(i.shape[0])
uniqTimes = list(set(times))
uniqTimesIdx = []
for i in uniqTimes:
uniqTimesIdx.append(listDuplicates(times, i))
quantIdx = max(uniqTimesIdx, key=len)
newQuant = []
newTitles = []
for i in quantIdx:
newQuant.append(quant[i][interval])
newTitles.append(titles[i])
newTme = tme[quantIdx[0]][interval]
# print(newQuant[0].shape)
# print(newTme.shape)
# print(newTitles)
if movie == 1:
vidDir = newDir + '/analysis/vid'
if os.path.isdir(vidDir) is not True:
os.mkdir(vidDir)
os.chdir(vidDir)
# return newQuant, newTitles, newTme
showdata(newQuant, titles=newTitles, t_array=newTme,
movie=movie, fps=fps, dpi=dpi, cmap='plasma')
if movie == 1:
os.system('mv animation.mp4 {}'.format(filename))
def show_the_data(path, t=None, x=None, y=None, z=None):
"""Function which plots the data.
Input
path - the path of a run
t - the desired t slice of showdata
x - the desired x slice of showdata
y - the desired y slice of showdata
z - the desired z slice of showdata
"""
print("Showing data from " + path)
n = collect('n', xguards=False, yguards=False, path=path, info=False)
# Show the data
showdata(n[t, x, y, z])
def show_the_data(path, t=None, x=None, y=None, z=None):
"""Function which plots the data.
Input
path - the path of a run
t - the desired t slice of showdata
x - the desired x slice of showdata
y - the desired y slice of showdata
z - the desired z slice of showdata
"""
print("Showing data from " + path)
n = collect('n', xguards=False, yguards=False, path=path, info=False)
# Show the data
showdata(n[t,x,y,z])
# get some parameters
A = max(options['blob']['A'],
options['blob2']['A']) # amplitude of the largest filament
Lx = options['mesh']['Lx'] # radial width of domain, in units of rho_s
Lz = options['mesh']['Lz'] # binormal width of domain, in units of rho_s
# x-coordinate in units of rho_s
# make coordinates 2d arrays so that they broadcast correctly with data arrays
x = numpy.linspace(0.5 / nx * Lx, Lx * (1. - 0.5 / nx), nx)[:, numpy.newaxis]
# z-coordinate in units of rho_s
z = numpy.linspace(0., Lz, nz, endpoint=False)[numpy.newaxis, :]
# make a movie of the density
showdata(data['n'][inds], t_array=data['t_array'], x=x[:, 0], y=z[0, :])
# find the centre-of-mass position of the filaments
# take 'filament' to be the density above this level
nmin = 1. + threshold * A
nFilament = data['n'][inds] - nmin
# zero all negative entries, which represent density below the threshold
nFilament[nFilament < 0.] = 0.
# calculate centre-of-mass
# sum over x- and z-dimensions
# don't need area element dx*dz because we only want ratios of integrals
nTotal = numpy.sum(nFilament, axis=(1, 2))
xCoM = numpy.sum(x * nFilament, axis=(1, 2)) / nTotal
plt.colorbar()
plt.subplot(133)
plt.title('neutral gas density')
plt.contourf(xx, t, ng[:, :, 0, 0], 100)
plt.xlabel('position')
plt.ylabel(r'time [$\mu$s]')
plt.colorbar()
plt.tight_layout()
plt.show()
# plot energy density
plt.figure(figsize=(5, 5))
plt.subplot(111)
plt.title('electron energy density')
plt.contourf(xx, t, NeE[:, :, 0, 0], 100)
plt.xlabel('position')
plt.ylabel(r'time [$\mu$s]')
plt.colorbar()
plt.tight_layout()
plt.show()
showdata(ne[::2, :, ny // 2, :])
showdata(ni[::2, :, ny // 2, :])
showdata(ng[::2, :, ny // 2, :])
showdata(phi[:, :, 0, :])
plt.plot(phiext[:, -1, ny // 2, 0])
plt.grid()
plt.show()
#!/usr/bin/env python3
from boututils.showdata import showdata
from boutdata import collect
from numpy import *
from matplotlib import pyplot as plt
import sys
import os
# T = collect('T', tind = [5500,6000], yguards = False)
phi = collect('phi', yguards=False)
n = collect('n', yguards=False)
vort = collect('vort', yguards=False)
x = slice(2, -2)
y = 0
z = slice(None)
t = slice(None)
n = n[t, x, y, z]
phi = phi[t, x, y, z]
# T = T[t,x,y,z]
vort = vort[t, x, y, z]
showdata([[n], [phi], [vort]], titles=['n', 'phi', 'vort'])
# along with STORM. If not, see <https://www.gnu.org/licenses/>.
from boutdata.data import BoutOutputs
from boututils.showdata import showdata
import numpy
from sys import exit, argv
# get object that provides access to output from BOUT++
outputs = BoutOutputs(path='.', xguards=False, yguards=False)
# choose variables to plot
varlist = ['n', 'T', 'vort', 'phi', 'U', 'V']
# get y-index (giving position in direction parallel to B)
if len(argv) > 1:
# get from command line argument
yindex = int(argv[1])
else:
# choose midpoint of grid as default
yindex = outputs['n'].shape[2] // 2
# make a numpy index slice
# indices are {t,x,y,z} so we will make an animation of values on the x-z plane
# at y=yindex
plot_indices = numpy.index_exp[:, :, yindex, :]
# show animation
showdata([outputs[var][plot_indices] for var in varlist], titles=varlist)
exit(0)
plt.subplot(131)
plt.title('electron density')
plt.contourf(xx, t, ne[:, :, 0], 100)
plt.xlabel('position')
plt.ylabel(r'time [$\mu$s]')
plt.colorbar()
plt.subplot(132)
plt.title('ion density')
plt.contourf(xx, t, ni[:, :, 0], 100)
plt.xlabel('position')
plt.ylabel(r'time [$\mu$s]')
plt.colorbar()
plt.subplot(133)
plt.title('electron energy density')
plt.contourf(xx, t, np.log(E[:, :, 0]), 100)
plt.xlabel('position')
plt.ylabel(r'time [$\mu$s]')
plt.colorbar()
plt.tight_layout()
plt.show()
showdata(ne[::2, :, 0])
showdata(ni[::2, :, 0])
# showdata(ng[::2,:,0])
showdata(E[:, :, 0])
showdata(phi[:, :, 0])
plt.plot(phiext[:, -1, 0])
plt.grid()
plt.show()