ir_vals = np.arange(nr)
else:
for i in range(len(desired_rvals)):
rval = desired_rvals[i]
ir_vals.append(np.argmin(np.abs(rvals - rval)))
# What is given is now what is desired
desired_rvals = rvals[ir_vals]
# Get power associated with desired quantity (should really have a contigency
# where the routine exits if the desired quantity isn't present
if not (varname == 'vtot' or varname == 'btot' or varname == 'omtot'):
desired_qv = var_indices[varname]
iq = np.argmin(np.abs(qv - desired_qv))
varlabel = texlabels.get(varname, 'qval = ' + varname)
units = texunits.get(varname, 'cgs')
else:
if varname == 'vtot':
desired_qv_vals = [1, 2, 3]
varlabel = r'$|\mathbf{v}|$'
units = r'$\rm{m}\ \rm{s}^{-1}$'
elif varname == 'btot':
desired_qv_vals = [801, 802, 803]
varlabel = r'$|\mathbf{B}|$'
units = r'$\rm{G}$'
elif varname == 'omtot':
desired_qv_vals = [301, 302, 303]
varlabel = r'$|\mathbf{\omega}|$'
units = r'$\rm{s}^{-1}$'
iq_vals = []
for desired_qv in desired_qv_vals:
field = vals[:, :, ir]
plot_moll(field, cost, fig=fig, ax=ax_moll, varname=varname,\
minmax=(min_slice, max_slice), clon=clon, symlog=symlog,\
linscale=linscale_slice, linthresh=linthresh_slice)
time_string = '%.1f' % time
time_string = time_string.zfill(tlabel_string_width)
title = varlabel + ' ' +\
(r'$r/R_\odot\ =\ %0.3f$' %rval) +\
' ' + (r'$t = %s\ P_{\rm{rot}}$' %time_string)
fig.text(margin_x + 0.5*moll_width, 1. - 0.5*margin_top,\
title, ha='center', va='center', **csfont, fontsize=14)
# Make the AZ_Avgs plot:
field = az.vals[:, :, az.lut[var_index], 0]
plot_azav (field, rr, cost, fig=fig, ax=ax_azav,\
units=texunits.get(varname, 'cgs'), minmax=(min_az, max_az),\
plotcontours=False, plotlatlines=True, cbar_fs=10,\
rvals=[rval], symlog=symlog, linthresh=linthresh_az,\
linscale=linscale_az)
# Make the time-latitude plot underneath everything
# Arrays for plotting time-latitude diagram (use two, with the one
# after the current time greyed out)
#times2, lats2 = np.meshgrid(times, tt_lat, indexing='ij')
it_current = np.argmin(np.abs(times - time))
times_1 = times[:it_current + 2]
# Have some overlap to prevent getting
# empty arrays at the first and last times
times_2 = times[it_current:]
times_2d_1, lats_2d_1 = np.meshgrid(times_1, tt_lat, indexing='ij')