def plot_6plot_thresh(dms_plot=0):
minvalD = 0
maxvalD = 255
sizex = np.amax(xT) - np.amin(xT)
sizey = np.amax(yT) - np.amin(yT)
ratio = sizey / sizex
minvalL = 0
if (found_ridges == 1):
elevation2d_ridge_comp = ma.compressed(elevation2d_ridge_maL)
maxvalL = np.round(np.percentile(elevation2d_ridge_comp, 99),
decimals=1)
else:
maxvalL = min_ridge_height
lowerp = 5
upperp = 99.5
minval = np.round(np.percentile(elevation_ma, lowerp), decimals=1)
maxval = np.round(np.percentile(elevation_ma, upperp), decimals=1)
res = 2
#dms_plot=0
textwidth = 5.5
fig = figure(figsize=(textwidth, textwidth * 1.25 * ratio))
ax1 = subplot(321)
ax1.annotate('(a) Raw DMS',
xy=(0.03, 0.9),
textcoords='axes fraction',
color='k',
horizontalalignment='middle',
verticalalignment='middle')
if (dms_plot == 1):
im1 = pcolormesh(xT[::res, ::res],
yT[::res, ::res],
dms[::res, ::res],
vmin=minvalD,
vmax=maxvalD,
cmap=cm.gist_gray,
rasterized=True)
ax2 = subplot(322)
ax2.annotate('(b) Raw DMS + ATM',
xy=(0.03, 0.9),
textcoords='axes fraction',
color='k',
horizontalalignment='middle',
verticalalignment='middle')
if (dms_plot == 1):
im2 = pcolormesh(xT[::res, ::res],
yT[::res, ::res],
dms[::res, ::res],
vmin=minvalD,
vmax=maxvalD,
cmap=cm.gist_gray,
rasterized=True)
im21 = scatter(xatm,
yatm,
c=elevation_ma,
vmin=minval,
vmax=maxval,
s=1,
lw=0,
cmap=cm.RdYlBu_r,
rasterized=True)
ax3 = subplot(323)
xe = [i for i in xrange(100)]
ye = [np.percentile(elevation_ma, i) for i in xrange(100)]
im3 = plot(xe, ye, 'k')
mid_percent = (pint * min_index) + (pwidth / 2)
low_percent = (pint * min_index)
up_percent = (pint * min_index) + pwidth
#axhline(y=level_elev, xmin=0, xmax=mid_percent, color='b')
axhline(y=level_elev, linestyle='--', color='b')
axhline(thresh, color='r')
ax3.annotate('Elevation threshold',
xy=(10, thresh),
xycoords='data',
color='r',
horizontalalignment='left',
verticalalignment='bottom')
ax3.annotate('Level ice (' + str(low_percent) + '-' + str(up_percent) +
'%)',
xy=(10, level_elev),
xycoords='data',
color='b',
horizontalalignment='left',
verticalalignment='top')
xlim([0, 100])
ax3.annotate('(c) Elevation distribution',
xy=(0.03, 0.9),
xycoords='axes fraction',
color='k',
horizontalalignment='middle',
verticalalignment='middle')
ax3.annotate(str(min_ridge_height) + ' m',
xy=(mid_percent - 15,
level_elevl + (thresh - level_elevu) * 0.5),
color='k',
horizontalalignment='left',
verticalalignment='bottom')
#ax4.annotate('(d)' , xy=(0.03, 0.93), textcoords='axes fraction', color='k', horizontalalignment='middle', verticalalignment='middle')
ax3.set_ylim(np.amin(ye), np.amax(ye))
norm = ro.MidpointNormalize(midpoint=0)
ax4 = subplot(324)
ax4.annotate('(d) Gridded (' + str(xy_res) + ' m) ATM',
xy=(0.03, 0.9),
textcoords='axes fraction',
color='k',
horizontalalignment='middle',
verticalalignment='middle')
im4 = pcolormesh(xx2d,
yy2d,
elevation2d - level_elev,
norm=norm,
vmin=minvalEL,
vmax=maxvalEL,
cmap=cm.RdBu_r)
#
im4.set_clim(minvalEL, maxvalEL)
im41 = contour(xx2d,
yy2d,
level_ice,
levels=[np.amin(level_ice),
np.amax(level_ice)],
colors='k',
linewidths=0.5)
#cs.set_clim(50, 210)
ax5 = subplot(325)
ax5.annotate('(e) High topography (>0.2 m)',
xy=(0.03, 0.9),
textcoords='axes fraction',
color='k',
horizontalalignment='middle',
verticalalignment='middle')
#im3 = pcolormesh(xx2d, yy2d, level_ice, vmin = minvalL, vmax = maxvalL, cmap = cm.RdYlBu_r)
if (found_ridges == 1):
im31 = pcolormesh(xx2d,
yy2d,
elevation2d_ridge_maL,
vmin=minvalL,
vmax=maxvalL,
cmap=cm.RdYlBu_r)
im51 = contour(xx2d,
yy2d,
label_im,
np.arange(0, num_ridges + 1),
colors='k',
linewidths=1)
ax6 = subplot(326)
ax6.annotate(r'(f) Unique features',
xy=(0.03, 0.9),
textcoords='axes fraction',
color='k',
horizontalalignment='middle',
verticalalignment='middle')
if (found_big_ridge == 1):
minvalLAB = 0
maxvalLAB = np.amax(label_im)
label_im_ma = ma.masked_where(label_im < 0.5, label_im)
im6 = pcolormesh(xx2d,
yy2d,
label_im_ma,
vmin=minvalLAB,
vmax=maxvalLAB,
cmap=my_cmap)
im61 = plot(ridge_stats[:, 0],
ridge_stats[:, 1],
marker='o',
markersize=2,
linestyle='None',
color='k')
#for i in xrange(ridge_stats.shape[0]):
# im62 = plot([ridge_stats[i, 0]-2*ridge_stats[i, 2], ridge_stats[i, 0]+2*ridge_stats[i, 2]], [ridge_stats[i, 1]-2*ridge_stats[i, 3], ridge_stats[i, 1]+2*ridge_stats[i, 3]], marker='None', linestyle = '-', color='k')
ax3.set_xlabel('Percentile (%)', labelpad=1)
ax3.set_ylabel('Relative elevation (m)', labelpad=1)
axesname = ['ax1', 'ax2', 'ax3', 'ax4', 'ax5', 'ax6']
for plotnum in [0, 1, 3, 4, 5]:
vars()[axesname[plotnum]].set_xlim(np.amin(xT), np.amax(xT))
vars()[axesname[plotnum]].set_ylim(np.amin(yT), np.amax(yT))
for plotnum in [0, 4, 5]:
vars()[axesname[plotnum]].set_xlabel('y (m)', labelpad=1)
for plotnum in [0, 3, 4]:
vars()[axesname[plotnum]].set_ylabel('x (m)', labelpad=1)
for plotnum in xrange(6):
vars()[axesname[plotnum]].yaxis.grid(True)
vars()[axesname[plotnum]].xaxis.grid(True)
letters = ['(a)', '(b)', '(c)', '(d)', '(e)', '(f)']
#for plotnum in xrange(6):
fig.text(
0.15, 0.98, 'DMS Date: ' + date + ' DMS Time: ' + dms_time + ' ' +
latDMS_str + 'N, ' + lonDMS_str + 'E')
cax = fig.add_axes([0.58, 0.71, 0.02, 0.08])
cbar = colorbar(im21,
cax=cax,
orientation='vertical',
extend='both',
use_gridspec=True)
cbar.set_label('Elevation to \n WGS84 (m)', labelpad=28, rotation=0)
xticks1 = np.linspace(minval, maxval, 3)
cbar.set_ticks(xticks1)
cax1 = fig.add_axes([0.58, 0.4, 0.02, 0.08])
cbar1 = colorbar(im4,
cax=cax1,
orientation='vertical',
extend='max',
use_gridspec=True)
cbar1.set_label('Elevation to \n level ice (m)', labelpad=28, rotation=0)
xticksL = np.linspace(minvalEL, maxvalEL, 4)
cbar1.set_ticks(xticksL)
cax2 = fig.add_axes([0.1, 0.08, 0.02, 0.08])
cbar2 = colorbar(im31,
cax=cax2,
orientation='vertical',
extend='max',
use_gridspec=True)
cbar2.set_label('Elevation to \n level ice (m)', labelpad=30, rotation=0)
xticks2 = np.linspace(minvalL, maxvalL, 3)
cbar2.set_ticks(xticks2)
if (found_big_ridge == 1):
cax3 = fig.add_axes([0.58, 0.08, 0.02, 0.08])
cbar3 = colorbar(im6,
cax=cax3,
orientation='vertical',
extend='neither',
use_gridspec=True)
cbar3.set_label('Feature\nidentifier', labelpad=20, rotation=0)
xticks2 = np.linspace(minvalLAB, maxvalLAB, 2)
cbar3.set_ticks(xticks2)
cbar3.solids.set_rasterized(True)
cbar.solids.set_rasterized(True)
cbar1.solids.set_rasterized(True)
cbar2.solids.set_rasterized(True)
im4.cmap.set_under('w')
#plt.tight_layout()
print 'Saving figure...'
subplots_adjust(bottom=0.07, left=0.09, top=0.96, right=0.98, hspace=0.22)
savefig(figpath + 'figure3.png', dpi=300)
'_cm2.png',
dpi=300)
datapath = './Data_output/'
rawdatapath = '../../../DATA/ICEBRIDGE/'
ATM_path = rawdatapath + '/ATM/ARCTIC/'
dms_path = rawdatapath + '/DMS/'
posAV_path = rawdatapath + '/POSAV/'
figpath = './Figures/'
my_cmap = ro.perceptual_colormap("cube1",
'../../../DATA/OTHER/CMAPS/',
reverse=1)
norm = ro.MidpointNormalize(midpoint=0)
xy_res = 2
pwidth = 20
pint = 5
min_ridge_size = 100
dms_image = 1
min_ridge_height = .2
minvalEL = -1
maxvalEL = 1
sh = 0
if (sh == 1):
print sys.argv[1]
dms_image = int(sys.argv[1])
