from diagnostic_reading import Meridional_Slice
dirname = sys.argv[1]
radatadir = dirname + '/Meridional_Slices/'
datadir = dirname + '/data/'
if (not os.path.isdir(datadir)):
os.makedirs(datadir)
files = os.listdir(radatadir)
nfiles = len(files)
files.sort()
#times,dtimes,weights = np.load(datadir + 'mer_times.npy')
mer0 = Meridional_Slice(radatadir + files[0], '')
nr = mer0.nr
nt = mer0.ntheta
vavg = np.load(datadir + 'vavg.npy')
vr_av = vavg[0]
# make 100 bins for vr in the range [-300 m/s, 200 m/s]
nbins = 100
binedges = np.linspace(-300., 200., nbins + 1)
minvr = np.min(binedges)
maxvr = np.max(binedges)
counts = np.zeros((nt, nr, nbins))
for ii in range(nfiles):
vr_vp_dist_df = np.zeros((nt, nr, nbins_vr, nbins_vp))
for i in range(index_first, index_last):
# Log the progress we are making!
if (not opened_only_once):
logfile = open(datadir + logname, 'a')
else:
opened_only_once = False
logfile.write('adding %s/Meridional_Slices/%s to the distribution...\n'\
%(dirname.split('/')[-1],file_list[i]))
logfile.close()
# Print the message for good measure
print('adding %s/Meridional_Slices/%s to the distribution...\n'\
%(dirname.split('/')[-1],file_list[i]))
mer = Meridional_Slice(radatadir + file_list[i], '')
niter = mer.niter
nphi = mer.nphi
# Loop through each phi-value the Meridional_Slice and each
# time in it.
for pindex in range(nphi):
for tindex in range(mer.niter):
# Compute the vr and vp values for this phi-value and time
# convert data from (cm/s) --> (m/s)
vr_mer = mer.vals[pindex,:,:,mer.lut[1],tindex]/100.
vp_mer = mer.vals[pindex,:,:,mer.lut[3],tindex]/100.
# Loop through the current slice in theta-r space,
# binning each value of vr and s accordingly.
# self.time[0:niter-1] : The simulation time corresponding to each time step # self.version : The version code for this particular output (internal use) # self.lut : Lookup table for the different diagnostics output # """ from diagnostic_reading import Meridional_Slice import numpy as np import matplotlib.pyplot as plt timestep = '00005000' quantity_code = 64 # read in temperature remove_mean = True # remove the ell=0 mean tindex = 0 # Display the first timestep from the file pindex = 4 # Display the 5th phi-value output a = Meridional_Slice(timestep) #Set up the grid nr = a.nr ntheta = a.ntheta r = a.radius / np.max(a.radius) # We apply a shift in theta so that theta=0 corresponds to equator and the poles appear where we expect them to... theta = np.arccos(a.costheta) - np.pi / 2 radius_matrix, theta_matrix = np.meshgrid(r, theta) X = radius_matrix * np.cos(theta_matrix) Y = radius_matrix * np.sin(theta_matrix) qindex = a.lut[quantity_code] field = np.zeros((ntheta, nr), dtype='float64')