minmax=minmax)
# label the subplot
varlabel = texlabels.get(varname, 0)
if varlabel == 0:
varlabel = varname.replace('plus', ' + ')
varlabel = varlabel.replace('times',
' ' + r'$\times$' + ' ')
varlabel = varlabel.replace('smooth', '')
varlabel = varlabel[3:]
varlabel = 'qvals = ' + varlabel
ax.set_title(varlabel, verticalalignment='bottom', **csfont)
# Make title
if iplot == 0:
ax_xmin, ax_xmax, ax_ymin, ax_ymax = axis_range(ax)
ax_delta_x = ax_xmax - ax_xmin
ax_delta_y = ax_ymax - ax_ymin
ax_center_x = ax_xmin + 0.5 * ax_delta_x
if rotation:
time_string = ('t = %.1f ' %(t_loc/time_unit)) + time_label +\
' (1 ' + time_label + (' = %.2f days)'\
%(time_unit/86400.))
else:
time_string = ('t = %.3f ' %(t_loc/time_unit)) + time_label +\
' (1 ' + time_label + (' = %.1f days)'\
%(time_unit/86400.))
title = dirname_stripped +\
'\n' + r'$\rm{Mollweide}$' + ' ' + time_string +\
ax1.set_yticks(tickvals)
ax1.set_yticklabels(ticklabels)
else:
im1 = ax1.pcolormesh(times2, lvals2, br_trace, cmap='Greys',\
norm=colors.LogNorm(vmin=my_mins[0], vmax=my_maxes[0]))
im2 = ax2.pcolormesh(times2, lvals2, bt_trace, cmap='Greys',\
norm=colors.LogNorm(vmin=my_mins[1], vmax=my_maxes[1]))
im3 = ax3.pcolormesh(times2, lvals2, bp_trace, cmap='Greys',\
norm=colors.LogNorm(vmin=my_mins[2], vmax=my_maxes[2]))
# Put colorbar next to all plots (possibly normalized separately)
# First make room and then find location of subplots
plt.subplots_adjust(left=0.1, right=0.85, wspace=0.03, top=0.9)
# First, B_r:
ax_xmin, ax_xmax, ax_ymin, ax_ymax = axis_range(ax1)
ax_delta_x = ax_xmax - ax_xmin
ax_delta_y = ax_ymax - ax_ymin
ax_center_x = ax_xmin + 0.5 * ax_delta_x
# Make the y label
if separate:
fig.text(0.5*ax_xmin, ax_ymin + 0.25*ax_delta_y, 'l odd',\
rotation=90, va='center', ha='right')
fig.text(0.5*ax_xmin, ax_ymin + 0.75*ax_delta_y, 'l even',\
rotation=90, va='center', ha='right')
else:
ax1.set_ylabel('l-degree')
cbar_left = ax_xmax + 0.3 * (1 - ax_xmax)
cbar_bottom = ax_ymin
power_not0 = power_not0[power_not0 != 0.]
minmax_loc = get_satvals(power_not0, logscale=True)
else:
minmax_loc = minmax
# Make plot
fig = plt.figure(figsize=(fig_width_inches, fig_height_inches))
ax = fig.add_axes([margin_left, margin_bottom, subplot_width,\
subplot_height])
plt.sca(ax)
im = plt.pcolormesh(lvals_2d_new, mvals_2d_new, power_loc,\
cmap='jet',\
norm=colors.LogNorm(vmin=minmax_loc[0], vmax=minmax_loc[1]))
# Set up the colorbar "by hand"
ax_left, ax_right, ax_bottom, ax_top = axis_range(ax)
ax_width = ax_right - ax_left
ax_height = ax_top - ax_bottom
cbax_center_y = ax_bottom + ax_height/2.
cbax_left = ax_right + 1/8/fig_width_inches
cbax_width = 1/8/fig_width_inches
cbax_aspect = 20.
cbax_height = cbax_width*cbax_aspect/fig_aspect
cbax_bottom = cbax_center_y - cbax_height/2.
cbaxes = fig.add_axes([cbax_left, cbax_bottom,\
cbax_width, cbax_height])
cbar = plt.colorbar(im, cax=cbaxes)
plt.sca(ax)
# set bounds
def plot_eqslice(field, rr, phi, fig=None, ax=None, cmap='RdYlBu_r',\
units='', minmax=None, posdef=False, logscale=False, symlog=False,\
plotcontours=True, plotfield=True, nlevs=None, levels=None,\
plotlonlines=False, rvals=None, rvals_norm=None, cbar_fs=10,\
showplot=False, plot_cbar=True, lw=1., linthresh=None, linscale=None,\
plotboundary=True):
''' Takes (or creates) set of axes with physical aspect ratio 1x1
and adds a plot of [field] in the equatorial plane to the axes,
with colorbar beneath the equatorial plane.'''
# First things first, make sure Python does not modify any of the
# arrays it was passed (shouldn't f*****g have to do this)
field = np.copy(field)
rr = np.copy(rr)
phi = np.copy(phi)
# Derivative grid info
ri, ro = np.min(rr), np.max(rr) # inner/ outer radii
nr = len(rr)
nphi = len(phi) + 1 # I predict I will extend phi...
# now extend phi ...
phi = np.hstack((phi, phi[0]))
cosphi = np.cos(phi)
sinphi = np.sin(phi)
# Extend the field
field = np.vstack((field, field[0].reshape((1, nr))))
rr_2d = rr.reshape((1, nr))
phi_2d = phi.reshape((nphi, 1))
xx = rr_2d * np.cos(phi_2d) / ro
yy = rr_2d * np.sin(phi_2d) / ro
# Deal with saturation values for the field
# If using logscale, you better have positive values!
if logscale:
posdef = True
# Get default bounds if not specified
if minmax is None:
minmax = get_satvals(field, posdef=posdef,\
logscale=logscale, symlog=symlog)
# Factor out the exponent on the field and put it on the color bar
# for the linear-scaled color bars (default and posdef)
if not (logscale or symlog) and plotfield:
maxabs = max(np.abs(minmax[0]), np.abs(minmax[1]))
exp = float(np.floor(np.log10(maxabs)))
divisor = 10.**exp
# Normalize field by divisor
field /= divisor
minmax = minmax[0] / divisor, minmax[1] / divisor
# Saturate the array (otherwise contourf will show white areas)
saturate_array(field, minmax[0], minmax[1])
# Create a default set of figure axes if they weren't already
# specified by user
if fig is None or ax is None:
fig, ax = default_axes_1by1()
showplot = True # probably in this case the user just
# ran plot_azav from the command line wanting to view
# view the plot
# Specify linewidths to be used in the meridional plane, one for the
# boundary (lw) and one for the contours (contour_lw)
contour_lw = 0.2
if (plotfield):
if logscale:
log_min, log_max = np.log10(minmax[0]), np.log10(minmax[1])
levs = np.logspace(log_min, log_max, 150)
im = ax.contourf(xx, yy, field, cmap='Greys',\
norm=colors.LogNorm(vmin=minmax[0], vmax=minmax[1]),\
levels=levs)
elif posdef:
levs = np.linspace(minmax[0], minmax[1], 150)
im = ax.contourf(xx, yy, field, cmap='plasma', levels=levs)
elif symlog:
linthresh_default, linscale_default =\
get_symlog_params(field, field_max=minmax[1])
if linthresh is None:
linthresh = linthresh_default
if linscale is None:
linscale = linscale_default
log_thresh = np.log10(linthresh)
log_max = np.log10(minmax[1])
nlevs_per_interval = 100
levels_neg = -np.logspace(log_max, log_thresh,\
nlevs_per_interval,\
endpoint=False)
levels_mid = np.linspace(-linthresh, linthresh,\
nlevs_per_interval, endpoint=False)
levels_pos = np.logspace(log_thresh, log_max,\
nlevs_per_interval)
levs = np.hstack((levels_neg, levels_mid, levels_pos))
im = ax.contourf(xx, yy, field, cmap='RdYlBu_r',\
norm=colors.SymLogNorm(linthresh=linthresh,\
linscale=linscale, vmin=minmax[0], vmax=minmax[1]),\
levels=levs)
else:
im = ax.contourf(xx, yy, field, cmap='RdYlBu_r',\
levels=np.linspace(minmax[0], minmax[1], 150))
if plot_cbar:
# Get the position of the axes on the figure
ax_left, ax_right, ax_bottom, ax_top = axis_range(ax)
ax_width = ax_right - ax_left
ax_height = ax_top - ax_bottom
fig_width_inches, fig_height_inches = fig.get_size_inches()
fig_aspect = fig_height_inches / fig_width_inches
# Set the colorbar ax to be just below equatorial plane
cbax_aspect = 1. / 20.
cbax_width = 0.5 * ax_width
if symlog:
cbax_width *= 1.5
cbax_aspect /= 1.5
cbax_height = cbax_width * cbax_aspect / fig_aspect
cbax_left = ax_left + 0.5 * (ax_width - cbax_width)
cbax_bottom = ax_bottom - 1 / 8 / fig_height_inches - cbax_height
cbaxes = fig.add_axes([cbax_left, cbax_bottom,\
cbax_width, cbax_height])
cbar = plt.colorbar(im, cax=cbaxes, orientation='horizontal')
cbaxes.tick_params(labelsize=cbar_fs)
cbar.ax.tick_params(labelsize=cbar_fs) #font size for the ticks
if logscale:
locator = ticker.LogLocator(subs='all')
cbar.set_ticks(locator)
cbar_label = units
elif posdef:
cbar_label = (r'$\times10^{%i}\ $' % exp) + units
cbar.set_ticks([minmax[0], minmax[1]])
cbar.set_ticklabels(['%1.1f' % minmax[0], '%1.1f' % minmax[1]])
elif symlog:
cbar_label = units
cbar.set_ticks([-minmax[1], -linthresh, 0, linthresh,\
minmax[1]])
cbar.set_ticklabels([sci_format(-minmax[1]),\
sci_format(-linthresh), '0', sci_format(linthresh),\
sci_format(minmax[1])])
# cax.minorticks_on()
else:
cbar_label = (r'$\times10^{%i}\ $' % exp) + units
cbar.set_ticks([minmax[0], 0, minmax[1]])
cbar.set_ticklabels(['%1.1f' %minmax[0], '0', '%1.1f'\
%minmax[1]])
# Put the units (and possibly the exponent) to left of colorbar
fig.text(cbax_left + cbax_width + 1/16/fig_width_inches,\
cbax_bottom + 0.5*cbax_height, cbar_label, ha='left',\
va='center', fontsize=cbar_fs)
# Plot contours in the equatorial plane, if desired
if plotcontours:
# Determine the contour levels
if levels is None:
if nlevs is None:
nlevs = 11 # Default nlevs to 11
if logscale:
min_log = np.log10(minmax[0])
max_log = np.log10(minmax[1])
levels = np.logspace(min_log, max_log, nlevs)
elif symlog:
log_thresh = np.log10(linthresh)
log_max = np.log10(minmax[1])
nlevs_per_interval = nlevs // 3
levels_neg = -np.logspace(log_max, log_thresh,\
nlevs_per_interval, endpoint=False)
levels_mid = np.linspace(-linthresh, linthresh,\
nlevs_per_interval, endpoint=False)
levels_pos = np.logspace(log_thresh, log_max,\
nlevs_per_interval)
levels = np.hstack((levels_neg, levels_mid, levels_pos))
else:
levels = np.linspace(minmax[0], minmax[1], nlevs)
else: # the caller specified specific contour levels to plot!
levels = np.array(levels)
# Determine how to color the contours
if logscale:
contour_color = 'r'
elif posdef:
contour_color = 'w'
else:
contour_color = 'k'
# plot the contours
ax.contour(xx, yy, field, colors=contour_color, levels=levels,\
linewidths=contour_lw)
# Plot the boundary of the meridional plane, if desired
if plotboundary:
plt.sca(ax)
plt.plot(rr[0] / ro * cosphi, rr[0] / ro * sinphi, 'k', linewidth=lw)
plt.plot(rr[-1] / ro * cosphi, rr[-1] / ro * sinphi, 'k', linewidth=lw)
# Plot longititude lines, if desired
if plotlonlines:
lons = phi * 180. / np.pi
lons_to_plot = np.arange(0., 360., 15.)
for lon in lons_to_plot:
iphi = np.argmin(np.abs(lons - lon))
xx_in, yy_in = rr[-1] / ro * cosphi[iphi], rr[-1] / ro * sinphi[
iphi]
xx_out, yy_out = rr[0] / ro * cosphi[iphi], rr[0] / ro * sinphi[
iphi]
plt.sca(ax)
plt.plot([xx_in, xx_out], [yy_in, yy_out], 'k',\
linewidth=contour_lw)
# Plot various radii, if desired
# rvals must be given normalized to outer rr
if not rvals is None:
if rvals_norm is None:
rvals_norm = rsun
for rval in rvals:
plt.sca(ax)
rval_dim = rval * rvals_norm / ro
# "dimensional" rval (in dimensions of ro!)
plt.plot(rval_dim * cosphi, rval_dim * sinphi, 'k--', linewidth=.7)
# Set ax ranges to be just outside the boundary lines
lilbit = 0.01
ax.set_xlim((-1 - lilbit, 1 + lilbit))
ax.set_ylim((-1 - lilbit, 1 + lilbit))
ax.axis('off')
if showplot:
plt.show()
