In [1]:

    

"""
Script to test the SAMRAI data reader for data from all levels.
"""

from floatpy.readers import samrai_reader
import numpy

%matplotlib inline
from matplotlib import pyplot as plt


    

In [2]:

    

"""
Get the SAMRAI data reader.
"""

data_reader = \
    samrai_reader.SamraiDataReader('/mnt/b9e17de4-9838-4425-ad4c-dc2ad3e41075/manlong/LANL_summer/' + \
                                  '2D_Poggi_Richtmyer_Meshkov_instability/2D_Poggi_Richtmyer_Meshkov_instability_1/' + \
                                  'viz_2D_Poggi_Richtmyer_Meshkov_instability/', \
                                  periodic_dimensions = (False, True), \
                                  upsampling_method = 'sixth_order_Lagrange')


    

In [3]:

    

"""
Try to set a new step.
"""

steps = data_reader.steps
data_reader.setStep(steps[-1])


    

In [4]:

    

"""
Try to read the full domain shape refined to the highest level. 
"""

domain_shape = data_reader.getRefinedDomainSize()

print domain_shape


    

    




(5000, 500)

In [5]:

    

"""
Try to read the density and velocity data from all levels.
"""

var_names = ('density', 'velocity')
num_ghosts = (0, 4)

data_reader.readCombinedDataInSubdomainFromAllLevels(var_names, num_ghosts)

x_coords, y_coords = data_reader.getCombinedCoordinatesInSubdomainFromAllLevels(num_ghosts)
data_rho = data_reader.getData('density')
data_vel = data_reader.getData('velocity')

print data_rho.shape
print data_vel.shape

print numpy.isfortran(data_rho)
print numpy.isfortran(data_vel)


    

    




(5000, 508, 1)
(5000, 508, 2)
True
True

In [6]:

    

"""
Check the values of the ghost cells.
"""

print data_rho[10, 0:4, 0]
print data_rho[10, -4*2:-4, 0]

print data_rho[10, -4:, 0]
print data_rho[10, 4:8, 0]


    

    




[ 12.74021721  12.74021721  12.74021721  12.74021721]
[ 12.74021721  12.74021721  12.74021721  12.74021721]
[ 12.74021721  12.74021721  12.74021721  12.74021721]
[ 12.74021721  12.74021721  12.74021721  12.74021721]

In [7]:

    

"""
Plot the level of data. (NAN for non-existing data)
"""

data_masked = numpy.ma.masked_where(numpy.isnan(data_rho), data_rho)
X, Y = numpy.meshgrid(x_coords, y_coords)

fig=plt.figure(figsize=(20, 2), dpi= 150)

plt.pcolormesh(X, Y, data_masked[:, :, 0].T)

plt.axes().set_aspect('equal', 'datalim')
plt.xlim([x_coords[0], x_coords[-1]])
plt.ylim([y_coords[0], y_coords[-1]])
plt.xlabel('x', fontsize=16)
plt.ylabel('y', fontsize=16)
plt.xticks(fontsize=16)
plt.yticks(fontsize=16)
plt.show()


    

    




/usr/lib/python2.7/dist-packages/matplotlib/collections.py:571: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison
  if self._edgecolors == str('face'):






    

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