Figure 1

Start by loading some boiler plate: matplotlib, numpy, scipy, json, functools, and a convenience class.



In [2]:

    
%matplotlib inline
import matplotlib
matplotlib.rcParams['figure.figsize'] = (10.0, 16.0)
import matplotlib.pyplot as plt
import numpy as np
from scipy.interpolate import interp1d, InterpolatedUnivariateSpline
from scipy.optimize import bisect
import json
from functools import partial
class Foo: pass

And some more specialized dependencies:

Slict provides a convenient slice-able dictionary interface
Chest is an out-of-core dictionary that we'll hook directly to a globus remote using...
glopen is an open-like context manager for remote globus files



In [3]:

    
from chest import Chest
from slict import CachedSlict
from glopen import glopen, glopen_many

Configuration for this figure.



In [3]:

    
config = Foo()
config.name     = "HighAspect/HA_visc/HA_visc"
#config.arch_end = "alcf#dtn_mira/projects/alpha-nek"
config.arch_end = "maxhutch#alpha-admin/pub/"
config.frame = 1
config.lower = .25
config.upper = .75

Open a chest located on a remote globus endpoint and load a remote json configuration file.



In [4]:

    
c = Chest(path      = "{:s}-results".format(config.name),
          open      = partial(glopen,      endpoint=config.arch_end),
          open_many = partial(glopen_many, endpoint=config.arch_end))
sc = CachedSlict(c)
with glopen(
            "{:s}.json".format(config.name), mode='r',
            endpoint = config.arch_end,
            ) as f:
    params = json.load(f)

We want to grab all the data for the selected frame.



In [5]:

    
T = sc[:,'H'].keys()[config.frame]
frame = sc[T,:]
c.prefetch(frame.full_keys())



In [4]:

    
import yt
#test = frame['t_yz'] + 1.
test = np.tile(frame['t_yz'].transpose(),(1,1,1)).transpose() + 1.
data = dict(
    density = (test, "g/cm**3")
)
bbox = np.array([[params['root_mesh'][1], params['extent_mesh'][1]],
                 [params['root_mesh'][2], params['extent_mesh'][2]],
                 [0., 1.]])
#bbox = np.array([[params['root_mesh'][1], params['extent_mesh'][1]],
#                 [params['root_mesh'][2], params['extent_mesh'][2]]])
ds = yt.load_uniform_grid(data, test.shape, bbox=bbox, periodicity=(False,True,False), length_unit="m")

slc = yt.SlicePlot(ds, "z", "density",
                   width=(1,16))
slc.set_buff_size((14336,448))
#slc.pan((.25,7))
slc.show()









    



---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-4-75d0baf2092d> in <module>()
      1 import yt
      2 #test = frame['t_yz'] + 1.
----> 3 test = np.tile(frame['t_yz'].transpose(),(1,1,1)).transpose() + 1.
      4 data = dict(
      5     density = (test, "g/cm**3")

NameError: name 'frame' is not defined



In [ ]:

    
sl = ds.slice("z", 0).to_frb((1., 'm'), (128,128), height=(32.,'m'))
plt.imshow(sl['density'].d)
plt.show()



In [ ]:

    
plt.figure()
plt.imshow(test[:,7000:7500,0].transpose())
plt.show()