def plot_datacoverage(self,
depth,
name='Megavolume',
filter='rff2',
conversion='EU60',
factor=2.):
fig = plt.figure(figsize=(6, 6))
d = np.argmin(np.abs(self.VOL.grid_depth - depth))
slice = self.VOL.volumeweight[:, :, d].copy()
xx, yy = np.meshgrid(self.VOL.grid_lon, self.VOL.grid_lat)
m = Basemap(projection='merc',
llcrnrlat=np.min(self.VOL.grid_lat),
urcrnrlat=np.max(self.VOL.grid_lat),
llcrnrlon=np.min(self.VOL.grid_lon),
urcrnrlon=np.max(self.VOL.grid_lon),
lat_ts=20,
resolution='i')
m.drawparallels(np.arange(self.VOL.latmin, self.VOL.latmax, 2.),
labels=[1, 0, 0, 1],
linewidth=0.5,
dashes=[4, 2],
labelstyle='+/-',
fontsize=10)
m.drawmeridians(np.arange(self.VOL.lonmin, self.VOL.lonmax, 2.),
labels=[1, 0, 0, 1],
linewidth=0.5,
dashes=[4, 2],
labelstyle='+/-',
fontsize=10)
m.drawcountries()
coasts = m.drawcoastlines(zorder=2, color='k', linewidth=1)
m.drawmapboundary(fill_color=[1.0, 1.0, 1.0])
x, y = m(xx, yy)
contours = [1., 15, 1.e2, 1.e3, 1.e4] #[1.e0,1.e1,1.e2,1.e3,1.e4]
im = plt.contourf(x, y, slice.T, contours, norm=LogNorm(), zorder=1)
fig.subplots_adjust(bottom=.2)
cbar_ax = fig.add_axes([0.2, 0.1, 0.6, 0.05])
cb = fig.colorbar(im, cax=cbar_ax, orientation='horizontal')
cb.set_label('Sum of weights at ' + str(depth) + ' km')
def plot_mtzwidth_write(self,
name='Megavolume',
filter='rff2',
conversion='EU60',
factor=2.):
#This routine is also used to make a txt file with the significant depths of the 410 and the 660
#depth410660 = open('/raid3/annemijn/scripts/CCP/mincov40MTZ_'+conversion+'_'+filter+'_'+str(int(factor))+'.txt', 'w')
depth410660 = open(
'/raid1/annemijn/scripts/CCP/MTZsign_mincov40_' + conversion +
'_' + filter + '_' + str(int(factor)) + '.txt', 'w')
plt.figure(figsize=(18, 8))
depths = self.VOL.grid_depth
l410 = [
x for x in range(len(depths))
if depths[x] > 380 and depths[x] < 430
]
l660 = [
x for x in range(len(depths))
if depths[x] > 630 and depths[x] < 700
]
thickness1D = np.empty(
(len(self.VOL.grid_lon), len(self.VOL.grid_lat)))
d4101D = np.empty((len(self.VOL.grid_lon), len(self.VOL.grid_lat)))
d6601D = np.empty((len(self.VOL.grid_lon), len(self.VOL.grid_lat)))
for i in range(len(self.VOL.grid_lon)):
for j in range(len(self.VOL.grid_lat)):
RF = self.VOL.volume[i, j, :] / self.VOL.volumeweight[i, j, :]
std = 1.96 * np.sqrt(self.VOL.volumesigma[i, j, :] /
(self.VOL.volumeweight[i, j, :] *
self.VOL.volumeweight[i, j, :]))
max410 = np.argmax(RF[l410])
max660 = np.argmax(RF[l660])
maxamp410 = np.max(RF[l410])
maxamp660 = np.max(RF[l660])
# If both picks are significant, store thickness
if RF[l410[max410]] > std[l410[max410]] and RF[
l660[max660]] > std[l660[max660]]:
d4101D[i, j] = depths[l410[max410]]
d6601D[i, j] = depths[l660[max660]]
thickness1D[i, j] = (depths[l660[max660]] -
depths[l410[max410]])
if self.VOL.volumeweight[i, j, l410[max410]] >= 40:
#This routine is also used to make a txt file with the depth of the 410 and the 660
depth410660.write(str(self.VOL.grid_lat[j]) + '\t')
depth410660.write(str(self.VOL.grid_lon[i]) + '\t')
depth410660.write(str(depths[l410[max410]]) + '\t')
depth410660.write(str(depths[l660[max660]]) + '\t')
depth410660.write(str(maxamp410) + '\t')
depth410660.write(str(maxamp660) + '\n')
# Prepare map
m = Basemap(projection='merc',
llcrnrlat=np.min(self.VOL.grid_lat),
urcrnrlat=np.max(self.VOL.grid_lat),
llcrnrlon=np.min(self.VOL.grid_lon),
urcrnrlon=np.max(self.VOL.grid_lon),
lat_ts=20,
resolution='i')
m.drawparallels(np.arange(np.min(self.VOL.grid_lat),
np.max(self.VOL.grid_lat), 10.),
labels=[0, 0, 0, 0]) #[1,0,0,1])
m.drawmeridians(np.arange(np.min(self.VOL.grid_lon),
np.max(self.VOL.grid_lon), 10.),
labels=[0, 0, 0, 0]) #[1,0,0,1])
m.drawcoastlines(color='k')
m.drawcountries(color='k')
m.drawmapboundary(fill_color=[1.0, 1.0, 1.0])
xx, yy = np.meshgrid(self.VOL.grid_lon, self.VOL.grid_lat)
x, y = m(xx, yy)
cs = plt.contourf(x,
y,
thickness1D.T,
levels=np.linspace(220., 300., 81.),
cmap=cm.gist_earth_r)
cs.cmap.set_under('w')
cs.cmap.set_over('w')
plt.colorbar()
plt.title('MTZ width')
#This routine is also used to make a txt file with the depth of the 410 and the 660
depth410660.close()
def plot_mtzwidth(self,
name='Megavolume',
filter='rff2',
conversion='EU60',
factor=2.,
mincoverage=10.):
# Plots topography of maximum between mindepth and maxdepth, masking if sum of weights is beneath mincoverage.
#depth410660 = open('/raid3/annemijn/scripts/CCP/mincov20MTZ_'+conversion+'_'+filter+'_'+str(int(factor))+'.txt', 'w')
plt.figure(figsize=(10, 8))
depths = self.VOL.grid_depth
print(depths)
l410 = [
x for x in range(len(depths))
if depths[x] > 380 and depths[x] < 430
]
l660 = [
x for x in range(len(depths))
if depths[x] > 630 and depths[x] < 700
]
thickness = np.empty((len(self.VOL.grid_lon), len(self.VOL.grid_lat)))
dmap = np.empty((len(self.VOL.grid_lon), len(self.VOL.grid_lat)))
coverage = np.empty((len(self.VOL.grid_lon), len(self.VOL.grid_lat)))
amparray = []
for i in range(len(self.VOL.grid_lon)):
for j in range(len(self.VOL.grid_lat)):
RF = self.VOL.volume[i, j, :] / self.VOL.volumeweight[i, j, :]
plt.plot(RF)
std = 1.96 * np.sqrt(self.VOL.volumesigma[i, j, :] /
(self.VOL.volumeweight[i, j, :] *
self.VOL.volumeweight[i, j, :]))
maxmap410 = np.argmax(RF[l410])
maxmap660 = np.argmax(RF[l660])
if RF[l410[maxmap410]] > std[l410[maxmap410]] and RF[
l660[maxmap660]] > std[l660[maxmap660]]:
dmap[i,
j] = depths[l660[maxmap660]] - depths[l410[maxmap410]]
#depth410660.write(str(self.VOL.grid_lat[j])+'\t')
#depth410660.write(str(self.VOL.grid_lon[i])+'\t')
#depth410660.write(str(depths[l410[maxmap410]])+'\t')
#depth410660.write(str(depths[l660[maxmap660]])+'\t')
if self.VOL.volumeweight[i, j, l410[maxmap410]] < mincoverage:
dmap[i, j] = 1000.
# Prepare map
m = Basemap(projection='merc',
llcrnrlat=np.min(self.VOL.grid_lat),
urcrnrlat=np.max(self.VOL.grid_lat),
llcrnrlon=np.min(self.VOL.grid_lon),
urcrnrlon=np.max(self.VOL.grid_lon),
lat_ts=20,
resolution='i')
m.drawparallels(np.arange(0, 90, 5.),
labels=[1, 0, 0, 1],
linewidth=0.5,
dashes=[4, 2],
labelstyle='+/-',
fontsize=20)
m.drawmeridians(np.arange(-180, -110, 10.),
labels=[1, 0, 0, 1],
linewidth=0.5,
dashes=[4, 2],
labelstyle='+/-',
fontsize=20)
m.drawcountries()
coasts = m.drawcoastlines(zorder=1, color='k', linewidth=1)
xx, yy = np.meshgrid(self.VOL.grid_lon, self.VOL.grid_lat)
x, y = m(xx, yy)
#cs = plt.contourf(x, y, dmap.T, vmin=220.,levels=np.linspace(220., 280., 81.), cmap=cm.RdBu)
cs = plt.pcolor(x,
y,
dmap.T,
vmin=220.,
vmax=280.,
cmap=cm.RdBu,
linewidth=0,
rasterized=True)
cs.cmap.set_under([0.8, 0.8, 0.8])
cs.cmap.set_over([0.8, 0.8, 0.8])
cb = plt.colorbar()
cb.set_label('Transition zone thickness (km)', size=30)
cb.set_ticks([220, 235, 250, 265, 280])
cb.ax.tick_params(labelsize=30)
cb.solids.set_rasterized(True)
xt, yt = m(-13.2, 70.6)
m.drawcoastlines(zorder=1, color='k', linewidth=1)
dmapall = np.ravel(dmap)
lonmin = -158
lonmax = -154
latmin = 57.5
latmax = 60
def plot_topography(self,
mindepth,
maxdepth,
name='Megavolume',
filter='rff2',
conversion='prem',
factor=2.,
mincoverage=10.,
amplitude=True,
blobs=True):
# Plots topography of maximum between mindepth and maxdepth, masking if sum of weights is beneath mincoverage.
# If amplitude =True, it will plot the amplitude and not the depth
plt.figure(figsize=(10, 8))
depths = self.VOL.grid_depth
#print('depths are ', depths)
val_list = [
x for x in range(len(depths))
if depths[x] > mindepth and depths[x] < maxdepth
]
thickness = np.empty((len(self.VOL.grid_lon), len(self.VOL.grid_lat)))
dmap = np.empty((len(self.VOL.grid_lon), len(self.VOL.grid_lat)))
coverage = np.empty((len(self.VOL.grid_lon), len(self.VOL.grid_lat)))
dsign = np.empty((len(self.VOL.grid_lon), len(self.VOL.grid_lat)))
amparray = []
for i in range(len(self.VOL.grid_lon)):
for j in range(len(self.VOL.grid_lat)):
RF = self.VOL.volume[i, j, :] / self.VOL.volumeweight[i, j, :]
plt.plot(RF)
std = 1.96 * np.sqrt(self.VOL.volumesigma[i, j, :] /
(self.VOL.volumeweight[i, j, :] *
self.VOL.volumeweight[i, j, :]))
maxmap = np.argmax(RF[val_list])
if amplitude == False:
dmap[i, j] = depths[val_list[maxmap]]
else:
dmap[i, j] = RF[val_list[maxmap]]
#array for significance, 0=significant, 1=not significant
if abs(RF[val_list[maxmap]]) > std[val_list[maxmap]]:
dsign[i, j] = 0.0
else:
dsign[i, j] = 1.
if self.VOL.volumeweight[i, j, val_list[maxmap]] < mincoverage:
dmap[i, j] = 1000.
dsign[i, j] = 0.
#plt.show()
# Prepare map
m = Basemap(projection='merc',
llcrnrlat=np.min(self.VOL.grid_lat),
urcrnrlat=np.max(self.VOL.grid_lat),
llcrnrlon=np.min(self.VOL.grid_lon),
urcrnrlon=np.max(self.VOL.grid_lon),
lat_ts=20,
resolution='i')
m.drawparallels(np.arange(0, 90, 5.),
labels=[1, 0, 0, 1],
linewidth=0.5,
dashes=[4, 2],
labelstyle='+/-',
fontsize=20)
m.drawmeridians(np.arange(-180, -110, 10.),
labels=[1, 0, 0, 1],
linewidth=0.5,
dashes=[4, 2],
labelstyle='+/-',
fontsize=20)
m.drawcountries()
coasts = m.drawcoastlines(zorder=1, color='k', linewidth=1)
xx, yy = np.meshgrid(self.VOL.grid_lon, self.VOL.grid_lat)
x, y = m(xx, yy)
if amplitude is False:
cs = plt.pcolor(x,
y,
dmap.T,
vmin=mindepth,
vmax=maxdepth,
cmap=cm.BrBG,
linewidth=0,
rasterized=True)
#mask area if not significant
dsign = ma.masked_array(dsign, dsign == 0)
sign = plt.contourf(x,
y,
dsign.T,
vmin=0.5,
vmax=1.0,
cmap=cm.Greys,
linewidth=0,
alpha=0.7,
rasterized=False)
else:
cs = plt.pcolor(x,
y,
dmap.T,
vmin=0.02,
vmax=0.12,
cmap=cm.pink_r,
linewidth=0,
rasterized=True)
cs.cmap.set_under([0.8, 0.8, 0.8])
cs.cmap.set_over([0.8, 0.8, 0.8])
#mindepth=np.argmin(dmap.T)
#maxdepth=np.argmax(dmap.T)
cb = plt.colorbar(cs,
ticks=[
mindepth, mindepth + (maxdepth - mindepth) / 6,
mindepth + 2 * (maxdepth - mindepth) / 6,
mindepth + 3 * (maxdepth - mindepth) / 6,
mindepth + 4 * (maxdepth - mindepth) / 6,
mindepth + 5 * (maxdepth - mindepth) / 6,
maxdepth
])
#cb.set_label('Maximum map between ' + str(mindepth)+' and ' + str(maxdepth)+' (km)', size=30)
if mindepth == 380:
cb.set_label('Depth of 410 (km)', size=30)
else:
cb.set_label('Depth of 660 (km)', size=30)
cb.ax.tick_params(labelsize=30)
#cb.set_label('Amplitude')
# cb.set_ticks([380,400,420,440])
cb.solids.set_rasterized(True)
xt, yt = m(-13.2, 70.6)
m.drawcoastlines(zorder=1, color='k', linewidth=1)
dmapall = np.ravel(dmap)
if amplitude == False:
l = [
l for l in range(len(dmapall))
if dmapall[l] > mindepth + 1. and dmapall[l] < maxdepth - 1.
]
print('median', np.median((dmapall[l])))
print('variance', np.var((dmapall[l])))
if blobs == True:
latblob = []
lonblob = []
with open('/raid1/annemijn/scripts/CCP/areared.txt') as blobs:
for line in blobs:
row = line.split()
latblob.append(float(row[0]))
lonblob.append(float(row[1]))
print(latblob)
x, y = m(lonblob, latblob)
m.scatter(x, y, marker='o', color='firebrick')
latblob = []
lonblob = []
with open('/raid1/annemijn/scripts/CCP/areayellow.txt') as blobs:
for line in blobs:
row = line.split()
latblob.append(float(row[0]))
lonblob.append(float(row[1]))
print(latblob)
x, y = m(lonblob, latblob)
m.scatter(x, y, marker='o', color='gold')
latblob = []
lonblob = []
with open('/raid1/annemijn/scripts/CCP/areagreen.txt') as blobs:
for line in blobs:
row = line.split()
latblob.append(float(row[0]))
lonblob.append(float(row[1]))
print(latblob)
x, y = m(lonblob, latblob)
m.scatter(x, y, marker='o', color='forestgreen')
latblob = []
lonblob = []
with open('/raid1/annemijn/scripts/CCP/areablue.txt') as blobs:
for line in blobs:
row = line.split()
latblob.append(float(row[0]))
lonblob.append(float(row[1]))
print(latblob)
x, y = m(lonblob, latblob)
m.scatter(x, y, marker='o', color='dodgerblue')
lonmin = -142.1
lonmax = -128
latmin = 69
latmax = 74
#plot_rectangle(m, lonmin,lonmax,latmin,latmax)
lonmin = -136
lonmax = -128
latmin = 54
latmax = 63
#plot_rectangle(m, lonmin,lonmax,latmin,latmax)
lonmin = -157
lonmax = -150
latmin = 67.5
latmax = 69
#plot_rectangle(m, lonmin,lonmax,latmin,latmax)
lonmin = -154
lonmax = -149
latmin = 66
latmax = 68
#plot_rectangle(m, lonmin,lonmax,latmin,latmax, col="Black")
lonmin = -155
lonmax = -150
latmin = 56.5
latmax = 59.5
#plot_rectangle(m, lonmin,lonmax,latmin,latmax, col="Black")
lonmin = -159
lonmax = -131
latmin = 59.5
latmax = 66.5
#plot_line (m,lonmin,lonmax,latmin,latmax,col="Black")#BB
lonmin = -160
lonmax = -142
latmin = 58
latmax = 63
#plot_line (m,lonmin,lonmax,latmin,latmax,col="Black")#CC
lonmin = -157
lonmax = -140
latmin = 57
latmax = 69
def plot_datacoverage(self,
depth,
name='Megavolume',
filter='rff2',
conversion='EU60',
factor=2.):
fig = plt.figure(figsize=(6, 6))
d = np.argmin(np.abs(self.VOL.grid_depth - depth))
slice = self.VOL.volumeweight[:, :, d].copy()
xx, yy = np.meshgrid(self.VOL.grid_lon, self.VOL.grid_lat)
m = Basemap(projection='merc',
llcrnrlat=np.min(self.VOL.grid_lat),
urcrnrlat=np.max(self.VOL.grid_lat),
llcrnrlon=np.min(self.VOL.grid_lon),
urcrnrlon=np.max(self.VOL.grid_lon),
lat_ts=20,
resolution='i')
m.drawparallels(np.arange(0, 80, 10.),
labels=[1, 0, 0, 1],
linewidth=0.5,
dashes=[4, 2],
labelstyle='+/-',
fontsize=22)
m.drawmeridians(np.arange(-160, -130, 20.),
labels=[1, 0, 0, 1],
linewidth=0.5,
dashes=[4, 2],
labelstyle='+/-',
fontsize=22)
m.drawcountries()
coasts = m.drawcoastlines(zorder=2, color='k', linewidth=1)
m.drawmapboundary(fill_color=[1.0, 1.0, 1.0])
x, y = m(xx, yy)
contours = [1., 1.e1, 1.e2, 1.e3, 1.e4] #[1.e0,1.e1,1.e2,1.e3,1.e4]
im = plt.contourf(x, y, slice.T, contours, norm=LogNorm(), zorder=1)
lonmin = -157
lonmax = -143
latmin = 58
latmax = 67
#plot_line (m,lonmin,lonmax,latmin,latmax,col="Black")
lonmin = -159
lonmax = -131
latmin = 59.5
latmax = 66.5
plot_line(m, lonmin, lonmax, latmin, latmax, col="Black") #BB
lonmin = -160
lonmax = -142
latmin = 58
latmax = 63
plot_line(m, lonmin, lonmax, latmin, latmax, col="Black") #CC
lonmin = -157
lonmax = -140
latmin = 57
latmax = 69
plot_line(m, lonmin, lonmax, latmin, latmax, col="Black") #AA
lonmin = -164
lonmax = -154
latmin = 56.5
latmax = 60.5
plot_line(m, lonmin, lonmax, latmin, latmax, col="Black") #DD
lonmin = -155.5
lonmax = -152
latmin = 66
latmax = 68
#plot_rectangle(m, lonmin,lonmax,latmin,latmax, col="Black")
lonmin = -154
lonmax = -148.5
latmin = 58
latmax = 60.5
#plot_rectangle(m, lonmin,lonmax,latmin,latmax, col="Black")
fig.subplots_adjust(bottom=.2)
cbar_ax = fig.add_axes([0.2, 0.1, 0.6, 0.05])
cb = fig.colorbar(im, cax=cbar_ax, orientation='horizontal')
cb.set_label('Sum of weights at ' + str(depth) + ' km', fontsize=36)
def plot_crosssection_any(self,
lon1,
lon2,
lat1,
lat2,
numpoints=200,
amplify=1.,
name='Megavolume',
filter='rff2',
conversion='EU60',
factor=2.,
zoom=False,
mincoverage=10.):
# set volume lats and lons
inv = geo.WGS84.Inverse(lat1, lon1, lat2, lon2)
points = np.linspace(0, inv['s12'], numpoints)
line = geo.WGS84.Line(lat1, lon1, inv['azi1'])
lats = []
lons = []
for i in range(len(points)):
lats.append(line.Position(points[i])['lat2'])
lons.append(line.Position(points[i])['lon2'])
lats = np.array(lats)
lons = np.array(lons)
crossec = []
vol_sig = []
w = []
dist = []
for i in range(len(lats)):
dist.append(
haversine(lats[0], lons[0], [lats[i]], [lons[i]]) / 111194.)
# pixelize lon and lat
row = (lons - np.min(self.VOL.grid_lon)) / (self.VOL.grid_lon[1] -
self.VOL.grid_lon[0])
for i in range(len(row)):
if row[i] < 0:
row[i] = row[i] + len(self.lon)
col = (lats - np.min(self.VOL.grid_lat)) / (self.VOL.grid_lat[1] -
self.VOL.grid_lat[0])
for dp in range(len(self.VOL.grid_depth)):
crossec.append(
scipy.ndimage.map_coordinates(self.VOL.volume[:, :, dp],
np.vstack((row, col))))
vol_sig.append(
scipy.ndimage.map_coordinates(self.VOL.volumesigma[:, :, dp],
np.vstack((row, col))))
w.append(
scipy.ndimage.map_coordinates(self.VOL.volumeweight[:, :, dp],
np.vstack((row, col))))
crossec = np.array(crossec)
vol_sig = np.array(vol_sig)
w = np.array(w)
xaxis = self.VOL.grid_lat
xlabel = 'latitude (dg)'
xends = [lon1, lon2]
yends = [lat1, lat2]
depths = self.VOL.grid_depth
# normalize
for i in range(np.shape(w)[0]):
for j in range(np.shape(w)[1]):
if w[i, j] > mincoverage:
crossec[i, j] = crossec[i, j] / w[i, j]
if crossec[i, j] > 0:
vol_sig[i, j] = crossec[i, j] - 1.96 * np.sqrt(
vol_sig[i, j] / (w[i, j] * w[i, j]))
if vol_sig[i, j] < 0:
vol_sig[i, j] = 0.
if crossec[i, j] < 0:
vol_sig[i, j] = crossec[i, j] + 1.96 * np.sqrt(
vol_sig[i, j] / (w[i, j] * w[i, j]))
if vol_sig[i, j] > 0:
vol_sig[i, j] = 0.
else:
crossec[i, j] = 100.
plt.subplot(2, 2, 2)
m = Basemap(projection='merc',
llcrnrlat=self.VOL.latmin,
urcrnrlat=self.VOL.latmax,
llcrnrlon=self.VOL.lonmin,
urcrnrlon=self.VOL.lonmax,
lat_ts=20,
resolution='i')
m.drawparallels(np.arange(0, 90, 10.),
labels=[1, 0, 0, 1],
labelstyle='+/-',
fontsize=10)
m.drawmeridians(np.arange(-180, 60, 10.),
labels=[1, 0, 0, 1],
labelstyle='+/-',
fontsize=10)
m.drawcoastlines()
m.drawcountries()
m.drawmapboundary(fill_color=[1.0, 1.0, 1.0])
x1, y1 = m(xends[0], yends[0])
x2, y2 = m(xends[1], yends[1])
m.plot([x1, x2], [y1, y2], color='r', linewidth=1, zorder=1)
plt.subplot(2, 2, 1)
xx, yy = np.meshgrid(dist, depths)
cs = plt.pcolor(xx,
yy,
crossec,
vmin=-0.15,
vmax=0.15,
rasterized=True,
cmap=cm.coolwarm)
plt.colorbar()
cs.cmap.set_over([0.8, 0.8, 0.8])
if zoom:
plt.ylim([200, 900])
else:
plt.ylim([min(depths), max(depths)])
plt.gca().invert_yaxis()
# corrected by 3D model
# normalize
norm = 0.2 / amplify #np.max(np.max(np.abs(crossec_3D)))/amplify
ax = plt.subplot(2, 1, 2)
pos1 = ax.get_position() # get the original position
pos2 = [pos1.x0, pos1.y0, pos1.width / 14 * 8, pos1.height]
pos2 = [pos1.x0, pos1.y0, pos1.width, pos1.height]
print(pos1, pos2)
ax.set_position(pos2) # set a new position
print(ax.get_position()) #
print(ax.get_position())
# plot
for t in np.arange(0, len(dist), 1):
lx = [
x for x in range(len(depths))
if (np.abs(w[x, t]) > mincoverage)
] # and np.abs(vol_sig[x,t])>std[x,t]/1.96)]
RF = vol_sig[lx, t] / norm + dist[t]
RFfull = crossec[lx, t] / norm + dist[t]
plt.fill_betweenx(depths[lx],
RFfull,
dist[t],
where=RFfull >= dist[t],
facecolor='k',
rasterized=True)
plt.fill_betweenx(depths[lx],
RFfull,
dist[t],
where=dist[t] >= RFfull,
facecolor='k',
rasterized=True)
plt.fill_betweenx(depths[lx],
RF,
dist[t],
where=RF >= dist[t],
facecolor=[1.0, 0., 0.],
rasterized=True)
plt.fill_betweenx(depths[lx],
RF,
dist[t],
where=dist[t] >= RF,
facecolor=[0.0, 0.0, 1.],
rasterized=True)
RF2 = crossec[lx, t] / norm
l410 = [
x for x in range(len(depths[lx]))
if depths[lx[x]] > 366 and depths[lx[x]] < 454
]
l660 = [
x for x in range(len(depths[lx]))
if depths[lx[x]] > 616 and depths[lx[x]] < 704
]
if len(l410) > 20:
max410 = np.argmax(RF2[l410])
ind = lx[l410[max410]]
plt.plot([dist[t] + 0.1, 0.5 * RF2[l410[max410]] + dist[t]],
[depths[ind], depths[ind]],
'y',
linewidth=2)
if len(l660) > 20:
max660 = np.argmax(RF2[l660])
ind = lx[l660[max660]]
plt.plot([dist[t] + 0.1, 0.5 * RF2[l660[max660]] + dist[t]],
[depths[ind], depths[ind]],
'y',
linewidth=2)
plt.ylabel('Depth (km)', fontsize=28)
plt.xlabel('Angular distance (dg)', fontsize=28)
plt.xlim([min(dist), max(dist)])
plt.plot([-5, 40], [410, 410], '--k', linewidth=2)
plt.plot([-5, 40], [660, 660], '--k', linewidth=2)
if zoom:
plt.ylim([200, 800])
else:
plt.ylim([min(depths), max(depths)])
plt.gca().invert_yaxis()
print(ax.get_position())
def plot_crosssection(self,
direction,
lonorlat,
amplify=1.,
name='Megavolume',
filter='rff2',
conversion='EU60',
factor=2.,
zoom=False,
mincoverage=10):
# set volume lats and lons
if direction == 'NS':
lon = lonorlat
n = np.argmin(np.abs(self.VOL.grid_lon - lon))
crossec = self.VOL.volume[n, :, :].T.copy()
vol_sig = self.VOL.volumesigma[n, :, :].T.copy()
w = self.VOL.volumeweight[n, :, :].T
xaxis = self.VOL.grid_lat
xlabel = 'latitude (dg)'
yends = [lon, lon]
xends = [self.VOL.latmin, self.VOL.latmax]
lons = lon * np.ones_like(xaxis)
lats = xaxis
if direction == 'EW':
lat = lonorlat
n = np.argmin(np.abs(self.VOL.grid_lat - lat))
crossec = self.VOL.volume[:, n, :].T.copy()
vol_sig = self.VOL.volumesigma[:, n, :].T.copy()
w = self.VOL.volumeweight[:, n, :].T
xaxis = self.VOL.grid_lon
xlabel = 'longitude (dg)'
xends = [self.VOL.lonmin, self.VOL.lonmax]
yends = [lat, lat]
lons = xaxis
lats = lat * np.ones_like(xaxis)
depths = self.VOL.grid_depth
# normalize
for i in range(np.shape(w)[0]):
for j in range(np.shape(w)[1]):
if w[i, j] > mincoverage:
crossec[i, j] = crossec[i, j] / w[i, j]
if crossec[i, j] > 0:
vol_sig[i, j] = crossec[i, j] - 1.96 * np.sqrt(
vol_sig[i, j] / (w[i, j] * w[i, j]))
if vol_sig[i, j] < 0:
vol_sig[i, j] = 0.
if crossec[i, j] < 0:
vol_sig[i, j] = crossec[i, j] + 1.96 * np.sqrt(
vol_sig[i, j] / (w[i, j] * w[i, j]))
if vol_sig[i, j] > 0:
vol_sig[i, j] = 0.
else:
crossec[i, j] = 1000.
plt.figure(figsize=(14, 8))
plt.subplot(2, 2, 2)
m = Basemap(projection='merc',
llcrnrlat=self.VOL.latmin,
urcrnrlat=self.VOL.latmax,
llcrnrlon=self.VOL.lonmin,
urcrnrlon=self.VOL.lonmax,
lat_ts=20,
resolution='i')
m.drawparallels(np.arange(0, 70, 10.),
labels=[1, 0, 0, 1],
labelstyle='+/-',
fontsize=10)
m.drawmeridians(np.arange(-10, 60, 10.),
labels=[1, 0, 0, 1],
labelstyle='+/-',
fontsize=10)
m.drawcoastlines()
m.drawcountries()
m.drawmapboundary(fill_color=[1.0, 1.0, 1.0])
if direction == 'NS':
x1, y1 = m(yends[0], xends[0])
x2, y2 = m(yends[1], xends[1])
m.plot([x1, x2], [y1, y2], color='r', linewidth=1, zorder=1)
x3, y3 = m(lon * np.ones(len(xaxis), ),
np.round(xaxis / 10.) * 10.)
m.scatter(x3, y3, 80, xaxis, zorder=2)
if direction == 'EW':
x1, y1 = m(xends[0], yends[0])
x2, y2 = m(xends[1], yends[1])
m.plot([x1, x2], [y1, y2], color='r', linewidth=1, zorder=1)
x3, y3 = m(np.round(xaxis / 10.) * 10, lat * np.ones(len(xaxis), ))
m.scatter(x3, y3, 80, xaxis, zorder=2)
norm = 0.2 / amplify
# plot
plt.subplot(2, 2, 1)
xx, yy = np.meshgrid(xaxis, depths)
print(xx)
cs = plt.pcolor(xx,
yy,
crossec,
vmin=-0.3,
vmax=0.3,
rasterized=True,
cmap=cm.coolwarm)
#cs = plt.pcolor(xx, yy, crossec, vmin=-0.15, vmax=0.15, rasterized=True,cmap=cm.coolwarm)
plt.colorbar()
cs.cmap.set_over([0.8, 0.8, 0.8])
if zoom:
plt.ylim([300, 800])
else:
plt.ylim([min(depths), max(depths)])
plt.gca().invert_yaxis()
plt.xlim(xends)
plt.subplot(2, 1, 2)
for t in np.arange(0, len(xaxis), 1):
lx = [
x for x in range(0, len(depths))
if (np.abs(w[x, t]) > mincoverage)
] # and np.abs(vol_sig[x,t])>std[x,t]/1.96)]
RF = vol_sig[lx, t] / norm + xaxis[t]
RFfull = crossec[lx, t] / norm + xaxis[t]
plt.fill_betweenx(depths[lx],
RFfull,
xaxis[t],
where=RFfull >= xaxis[t],
facecolor='k',
rasterized=True)
plt.fill_betweenx(depths[lx],
RFfull,
xaxis[t],
where=xaxis[t] >= RFfull,
facecolor='k',
rasterized=True)
plt.fill_betweenx(depths[lx],
RF,
xaxis[t],
where=RF >= xaxis[t],
facecolor=[1.0, 0., 0.],
rasterized=True)
plt.fill_betweenx(depths[lx],
RF,
xaxis[t],
where=xaxis[t] >= RF,
facecolor=[0.0, 0.0, 1.],
rasterized=True)
plt.scatter(np.round(xaxis / 10.) * 10.,
80. * np.ones(len(xaxis), ),
80,
xaxis,
rasterized=True)
plt.plot([-180, 140], [410, 410], '--k', linewidth=2)
#plt.plot([-180, 140], [520, 520], '--k', linewidth=2)
plt.plot([-180, 140], [660, 660], '--k', linewidth=2)
plt.ylabel('Depth (km)')
plt.xlabel(xlabel, fontsize=12)
plt.xlim([min(xaxis), max(xaxis)])
if zoom:
plt.ylim([300, 800])
else:
plt.ylim([min(depths), max(depths)])
plt.gca().invert_yaxis()
print(min(depths))
def plot_mtzwidth(self,
name='Megavolume',
filter='rff2',
conversion='prem',
factor=2.,
Max_Thickness=290,
Min_Thickness=230):
plt.figure(figsize=(18, 8))
depths = self.VOL.grid_depth
l410 = [
x for x in range(len(depths))
if depths[x] > 370 and depths[x] < 460
] # limit between 370 and 460
l660 = [
x for x in range(len(depths))
if depths[x] > 630 and depths[x] < 710
] # limit between 630 and 710
thickness1D = np.empty(
(len(self.VOL.grid_lon), len(self.VOL.grid_lat)
)) # create grids the size of the box to plot the data into
d4101D = np.empty((len(self.VOL.grid_lon), len(self.VOL.grid_lat)))
d6601D = np.empty((len(self.VOL.grid_lon), len(self.VOL.grid_lat)))
with open(
root + 'CCP_Stack/MTZ_' + conversion + '_' + filter + '_' +
str(int(factor)) + '.txt', 'w') as output:
for i in range(len(self.VOL.grid_lon)):
for j in range(len(self.VOL.grid_lat)):
RF = self.VOL.volume[i, j, :] / self.VOL.volumeweight[i,
j, :]
std = 1.96 * np.sqrt(self.VOL.volumesigma[i, j, :] /
(self.VOL.volumeweight[i, j, :] *
self.VOL.volumeweight[i, j, :]))
max410 = np.argmax(RF[l410])
max660 = np.argmax(RF[l660])
# If both picks are significant, store thickness
if RF[l410[max410]] > std[l410[max410]] and RF[
l660[max660]] > std[l660[max660]]:
d4101D[i, j] = depths[l410[max410]]
d6601D[i, j] = depths[l660[max660]]
thickness1D[i, j] = (depths[l660[max660]] -
depths[l410[max410]])
output.write(
str(depths[l410[max410]]) + '\t' +
str(depths[l660[max660]]) + '\n')
output.close()
# Prepare map
m = Basemap(projection='merc',
llcrnrlat=np.min(self.VOL.grid_lat),
urcrnrlat=np.max(self.VOL.grid_lat),
llcrnrlon=np.min(self.VOL.grid_lon),
urcrnrlon=np.max(self.VOL.grid_lon),
lat_ts=20,
resolution='i')
m.drawparallels(np.arange(np.min(self.VOL.grid_lat),
np.max(self.VOL.grid_lat), 5.),
labels=[1, 0, 0, 1])
m.drawmeridians(np.arange(np.min(self.VOL.grid_lon),
np.max(self.VOL.grid_lon), 5.),
labels=[1, 0, 0, 1])
m.drawcoastlines(color='k')
m.drawcountries(color='k')
m.drawstates()
m.drawmapboundary(fill_color=[1.0, 1.0, 1.0])
xx, yy = np.meshgrid(self.VOL.grid_lon, self.VOL.grid_lat)
x, y = m(xx, yy)
cs = plt.contourf(x,
y,
thickness1D.T,
levels=np.linspace(Min_Thickness, Max_Thickness,
81.),
cmap=cm.RdYlBu)
cs.cmap.set_under('w') #Max_Thickness = 290, Min_Thickness=230
cs.cmap.set_over('w')
plt.colorbar()
plt.title('MTZ width')
def plot_topography(self,
mindepth,
maxdepth,
name='Megavolume',
filter='rff2',
conversion='prem',
factor=2.,
mincoverage=15.,
amplitude=False,
color_scheme='spectral',
reverse=False):
# Plots topography of maximum between mindepth and maxdepth, masking if sum of weights is beneath mincoverage.
# If amplitude =True, it will plot the amplitude and not the depth
plt.figure(figsize=(10, 8))
depths = self.VOL.grid_depth
val_list = [
x for x in range(len(depths))
if depths[x] > mindepth and depths[x] < maxdepth
]
thickness = np.empty((len(self.VOL.grid_lon), len(self.VOL.grid_lat)))
dmap = np.empty((len(self.VOL.grid_lon), len(self.VOL.grid_lat)))
coverage = np.empty((len(self.VOL.grid_lon), len(self.VOL.grid_lat)))
for i in range(len(self.VOL.grid_lon)):
for j in range(len(self.VOL.grid_lat)):
RF = self.VOL.volume[i, j, :] / self.VOL.volumeweight[i, j, :]
std = 1.96 * np.sqrt(self.VOL.volumesigma[i, j, :] /
(self.VOL.volumeweight[i, j, :] *
self.VOL.volumeweight[i, j, :]))
maxmap = np.argmax(RF[val_list])
if amplitude == False:
dmap[i, j] = depths[val_list[maxmap]]
else:
dmap[i, j] = RF[val_list[maxmap]]
if self.VOL.volumeweight[i, j, val_list[maxmap]] < mincoverage:
dmap[i, j] = 1000.
# Prepare map
m = Basemap(projection='merc',
llcrnrlat=np.min(self.VOL.grid_lat) - 0,
urcrnrlat=np.max(self.VOL.grid_lat) + 0,
llcrnrlon=np.min(self.VOL.grid_lon) - 0,
urcrnrlon=np.max(self.VOL.grid_lon) + 0,
lat_ts=10,
resolution='i')
m.drawparallels(np.arange(0, 70, 10.),
labels=[1, 0, 0, 1],
linewidth=0.5,
dashes=[4, 2],
labelstyle='+/-',
fontsize=8) #[1,0,0,1])
m.drawmeridians(np.arange(-20, 60, 10.),
labels=[1, 0, 0, 1],
linewidth=0.5,
dashes=[4, 2],
labelstyle='+/-',
fontsize=8) #[1,0,0,1])
m.drawcountries()
m.drawstates()
m.drawcoastlines()
coasts = m.drawcoastlines(zorder=1, color='k', linewidth=0.1)
xx, yy = np.meshgrid(self.VOL.grid_lon, self.VOL.grid_lat)
x, y = m(xx, yy)
#-----------------------------------------------------------------------
if color_scheme == 'rainbow' and reverse == True: cmap = cm.rainbow_r
if color_scheme == 'rainbow' and reverse == False: cmap = cm.rainbow
if color_scheme == 'spectral' and reverse == True: cmap = cm.Spectral_r
if color_scheme == 'spectral' and reverse == False: cmap = cm.Spectral
#------------------------------------------------------------------------
if amplitude is False:
cs = plt.pcolor(x,
y,
dmap.T,
vmin=mindepth,
vmax=maxdepth,
cmap=cmap,
linewidth=0,
rasterized=False)
else:
cs = plt.pcolor(x,
y,
dmap.T,
vmin=0.01,
vmax=0.12,
cmap=cm.cmap,
linewidth=0,
rasterized=False)
cs.cmap.set_under([0.8, 0.8, 0.8])
cs.cmap.set_over([0.8, 0.8, 0.8])
cb = plt.colorbar()
cb.set_label('Maximum map between ' + str(mindepth) + ' and ' +
str(maxdepth) + ' (km)')
# cb.set_ticks([380,400,420,440])
cb.solids.set_rasterized(True)
xt, yt = m(-13.2, 70.6)
m.drawcoastlines(zorder=1, color='k', linewidth=1)
dmapall = np.ravel(dmap)
if amplitude == False:
l = [
l for l in range(len(dmapall))
if dmapall[l] > mindepth + 1. and dmapall[l] < maxdepth - 1.
]
print('median', np.median((dmapall[l])))
print('variance', np.var((dmapall[l])))
