def make_3DWB_water_profile(final_profile,
water_ppmH2O_initial=None,
initial_profile=None,
initial_area_list=None,
initial_area_positions_microns=None,
show_plot=True,
top=1.2,
fig_ax=None):
"""Take a profile and initial water content.
Returns the whole-block water concentration profile based on
the profile's attribute wb_areas. If wb_areas have not been made,
some initial profile information and various options are passed
to make_3DWB_area_profile().
Default makes a plot showing A/Ao and water on parasite y-axis
"""
fin = final_profile
init = initial_profile
# Set initial water
if water_ppmH2O_initial is not None:
w0 = water_ppmH2O_initial
else:
if fin.sample is not None:
if fin.sample.initial_water is not None:
w0 = fin.sample.initial_water
elif init is not None:
if init.sample is not None:
if init.sample.initial_water is not None:
w0 = init.sample.initial_water
else:
print 'Need initial water content.'
return False
# Set whole-block areas
if (fin.wb_areas is not None) and (len(fin.wb_areas) > 0):
wb_areas = fin.wb_areas
else:
wb_areas = make_3DWB_area_profile(fin, initial_profile,
initial_area_list,
initial_area_positions_microns)
water = wb_areas * w0
if show_plot is True:
# Use a parasite y-axis to show water content
fig = plt.figure()
ax_areas = SubplotHost(fig, 1, 1, 1)
fig.add_subplot(ax_areas)
area_tick_marks = np.arange(0, 100, 0.2)
ax_areas.set_yticks(area_tick_marks)
ax_water = ax_areas.twin()
ax_water.set_yticks(area_tick_marks)
if isinstance(w0, uncertainties.Variable):
ax_water.set_yticklabels(area_tick_marks * w0.n)
else:
ax_water.set_yticklabels(area_tick_marks * w0)
ax_areas.axis["bottom"].set_label('Position ($\mu$m)')
ax_areas.axis["left"].set_label('Final area / Initial area')
ax_water.axis["right"].set_label('ppm H$_2$O')
ax_water.axis["top"].major_ticklabels.set_visible(False)
ax_water.axis["right"].major_ticklabels.set_visible(True)
ax_areas.grid()
ax_areas.set_ylim(0, 1.2)
if fin.len_microns is not None:
leng = fin.len_microns
else:
leng = fin.set_len()
ax_areas.set_xlim(-leng / 2.0, leng / 2.0)
style = fin.choose_marker_style()
ax_areas.plot([-leng / 2.0, leng / 2.0], [1, 1], **style_1)
ax_areas.plot(fin.positions_microns - leng / 2.0, wb_areas, **style)
return water, fig, ax_areas
else:
return water
# now make the plot
site_seq = plottingutils.getwtseq(infofn[namedict[fn]],barcodefn,datafnbase)
fig = plt.figure()
ax1 = SubplotHost(fig, 1,1,1)
fig.add_subplot(ax1)
ax2 = ax1.twin()
ax1.imshow(emat,interpolation='nearest')
ax1.set_xlabel('Position w.r.t. transcription start site')
ax1.set_yticks([0,1,2,3])
ax1.set_yticklabels(['A','C','G','T'])
# label positions with respect to transcription start site
tick_start = int(start_dict[info_dict['exp_name']])+int(info_dict['mut_region_start'])
tick_end = int(start_dict[info_dict['exp_name']])+int(info_dict['mut_region_start']) + int(info_dict['mut_region_length'])
indices, xtick_labels = clean_up_xticklabels(tick_start,tick_end-tick_start)
ax1.set_xticks(indices)
ax1.set_xticklabels(xtick_labels)
# put the sequence above it
ax2.set_yticks([])
ax2.set_yticklabels([])
ax2.set_xticks(range(20))
ax2.set_xticklabels([bp for bp in site_seq])
emat0 = emat_mean
emat = emat0 - emat0.min(axis=0)
# now make the plot
site_seq = plottingutils.getwtseq(infofn[namedict[fn]], barcodefn,
datafnbase)
fig = plt.figure()
ax1 = SubplotHost(fig, 1, 1, 1)
fig.add_subplot(ax1)
ax2 = ax1.twin()
ax1.imshow(emat, interpolation='nearest')
ax1.set_xlabel('Position w.r.t. transcription start site')
ax1.set_yticks([0, 1, 2, 3])
ax1.set_yticklabels(['A', 'C', 'G', 'T'])
# label positions with respect to transcription start site
tick_start = int(start_dict[info_dict['exp_name']]) + int(
info_dict['mut_region_start'])
tick_end = int(start_dict[info_dict['exp_name']]) + int(
info_dict['mut_region_start']) + int(
info_dict['mut_region_length'])
indices, xtick_labels = clean_up_xticklabels(tick_start,
tick_end - tick_start)
ax1.set_xticks(indices)
ax1.set_xticklabels(xtick_labels)
# put the sequence above it
ax2.set_yticks([])
stressSod[i] = np.max(s.sigmaEq)
stressSod *= 1e-6
bar1 = (stressSod[-1], stressSod[1]-stressSod[-1])
bar2 = (stressSod[1], stressSod[0]-stressSod[1])
ax1.broken_barh([bar1, bar2], (31, 4),
facecolors=(fillSod, fill),
edgecolor=edgeSod,)
for i in range(len(youngs)):
ax1.annotate('${0:g}$'.format(youngs[i]*1e-9), \
xy=(stressSod[i], 36), \
xycoords='data', horizontalalignment=alignRev[i],
fontsize=fs)
#ax1.set_title('\\textbf{(b)} Molten salt')
ax1.set_ylim(0, 40)
ax1.set_yticks([5, 15, 25, 35])
ax1.set_yticklabels(
['$\\mathrm{DN}$\n\small{(-)}',
'$\\lambda$\n\small{(\si{\watt\per\meter\per\kelvin})}',
'$\\alpha$\n\small{(\SI{e-6}{\per\kelvin})}',
'$E$\n\small{(GPa)}'], fontsize='large'
)
ax1.set_xlim(150, 450)
ax1.set_xlabel(r'\textsc{max. equiv. stress}, '+\
'$\max\sigma_\mathrm{Eq}$ (MPa)')
fig1.tight_layout()
#plt.show()
fig1.savefig('S31609_sensitivityTubeProperties.pdf',
transparent=True)
plt.close(fig1)
