def __init__(self, vel_dir, params):
# Initialize the base class
super(SimpleVelocityContainer, self).__init__(params)
self.vel_dir = vel_dir # used by __str__
self.profiles = {}
count = 0
for profile in fnmatch.filter(os.listdir(vel_dir), '*.txt'):
count += 1
with open(os.path.join(vel_dir, profile), 'r') as f:
# Read the location out of the file
header = False
loc = None
while not header:
l = f.readline().lstrip()
if l.startswith('#'):
header = True
elif l.startswith('coordinates'):
x, y = l.split(',')[1:]
x = float(x)
y = float(y)
loc = Point((x, y))
header = True
if not loc:
# There were no coordinates.
loc = Point((0, 0))
# Build up the time depth profile
self.profiles[loc] = []
for line in f.readlines():
# Ignore comments
if line.strip().startswith('#'):
continue
if len(line.strip().split(',')) == 2:
time, depth = line.strip().split(',')
elif len(line.strip().split()) == 2:
time, depth = line.strip().split()
else:
Notice.warning("Could not read velocity file.")
continue
self.profiles[loc].append([float(time), float(depth)])
self.count = count
def __init__(self, vel_dir, params):
# Initialize the base class
super(SimpleVelocityContainer, self).__init__(params)
self.vel_dir = vel_dir # used by __str__
self.profiles = {}
count = 0
for profile in fnmatch.filter(os.listdir(vel_dir), '*.txt'):
count += 1
with open(os.path.join(vel_dir, profile), 'r') as f:
# Read the location out of the file
header = False
loc = None
while not header:
l = f.readline().lstrip()
if l.startswith('#'):
header = True
elif l.startswith('coordinates'):
x, y = l.split(',')[1:]
x = float(x)
y = float(y)
loc = Point((x, y))
header = True
if not loc:
# There were no coordinates.
loc = Point((0, 0))
# Build up the time depth profile
self.profiles[loc] = []
for line in f.readlines():
# Ignore comments
if line.strip().startswith('#'):
continue
if len(line.strip().split(',')) == 2:
time, depth = line.strip().split(',')
elif len(line.strip().split()) == 2:
time, depth = line.strip().split()
else:
Notice.warning("Could not read velocity file.")
continue
self.profiles[loc].append([float(time), float(depth)])
self.count = count
def plot_feature_well(tc, gs):
"""
Plotting function for the feature well.
Args:
tc (TransectContainer): The container for the main plot.
log (axis): A matplotlib axis.
gs (GridSpec): A matplotlib gridspec.
"""
fname = tc.settings['curve_display']
logs = tc.log.get(tc.feature_well)
if not logs:
# There was no data for this well, so there won't be a feature plot.
Notice.fail("There's no well data for feature well " + tc.feature_well)
return gs
Z = logs.data['DEPT']
curves = ['GR', 'DT',
'DPHI_SAN',
'NPHI_SAN',
'DTS',
'RT_HRLT',
'RHOB',
'DRHO']
window = tc.settings.get('curve_smooth_window') or 51
ntracks = 5
lw = 1.0
smooth = True
naxes = 0
ncurv_per_track = np.zeros(ntracks)
if getattr(tc.log, 'striplog', None):
ncurv_per_track[0] = 1
for curve in curves:
naxes += 1
params = get_curve_params(curve, fname)
ncurv_per_track[params['track']] += 1
axss = plt.subplot(gs[2:, -5])
axs0 = [axss, axss.twiny()]
axs1 = [plt.subplot(gs[2:, -4])]
axs2 = [plt.subplot(gs[2:, -3])]
axs3 = [plt.subplot(gs[2:, -2])]
axs4 = [plt.subplot(gs[2:, -1])]
axs = [axs0, axs1, axs2, axs3, axs4]
if getattr(tc.log, 'striplog', None):
legend = Legend.default()
try:
logs.striplog[tc.log.striplog].plot_axis(axs0[0], legend=legend)
except KeyError:
# In fact, this striplog doesn't exist.
Notice.fail("There is no such striplog" + tc.log.striplog)
# And move on...
axs0[0].set_ylim([Z[-1], 0])
label_shift = np.zeros(len(axs))
for curve in curves:
try:
values = logs.data[curve]
except ValueError:
Notice.warning("Curve not present: "+curve)
values = np.empty_like(Z)
values[:] = np.nan
params = get_curve_params(curve, fname)
i = params['track']
j = 0
label_shift[i] += 1
linOrlog = params['logarithmic']
sxticks = np.array(params['xticks'])
xticks = np.array(sxticks, dtype=float)
whichticks = 'major'
if linOrlog == 'log':
midline = np.log(np.mean(xticks))
xpos = midline
whichticks = 'minor'
else:
midline = np.mean(xticks)
xpos = midline
if smooth:
values = utils.rolling_median(values, window)
if curve == 'GR':
j = 1 # second axis in first track
label_shift[i] = 1
if params['fill_left_cond']:
# do the fill for the lithology track
axs[i][j].fill_betweenx(Z, params['xleft'], values,
facecolor=params['fill_left'],
alpha=1.0, zorder=11)
if (curve == 'DPHI_SAN') and params['fill_left_cond']:
# do the fill for the neutron porosity track
try:
nphi = utils.rolling_median(logs.data['NPHI_SAN'], window)
except ValueError:
Notice.warning("No NPHI in this well")
nphi = np.empty_like(Z)
nphi[:] = np.nan
axs[i][j].fill_betweenx(Z,
nphi,
values,
where=nphi >= values,
facecolor=params['fill_left'],
alpha=1.0,
zorder=11)
axs[i][j].fill_betweenx(Z,
nphi,
values,
where=nphi <= values,
facecolor='#8C1717',
alpha=0.5,
zorder=12)
if curve == 'DRHO':
blk_drho = 3.2
values += blk_drho # this is a hack to get DRHO on RHOB scale
axs[i][j].fill_betweenx(Z,
blk_drho,
values,
where=nphi <= values,
facecolor='#CCCCCC',
alpha=0.5,
zorder=12)
# fill right
if params['fill_right_cond']:
axs[i][j].fill_betweenx(Z, values, params['xright'],
facecolor=params['fill_right'],
alpha=1.0, zorder=12)
# plot curve
axs[i][j].plot(values, Z, color=params['hexcolor'],
lw=lw, zorder=13)
# set scale of curve
axs[i][j].set_xlim([params['xleft'], params['xright']])
# ------------------------------------------------- #
# curve labels
# ------------------------------------------------- #
trans = transforms.blended_transform_factory(axs[i][j].transData,
axs[i][j].transData)
magic = -Z[-1] / 12.
axs[i][j].text(xpos, magic - (magic/4)*(label_shift[i]-1),
curve,
horizontalalignment='center',
verticalalignment='bottom',
fontsize=12, color=params['hexcolor'],
transform=trans)
# curve units
units = '${}$'.format(params['units'])
if label_shift[i] <= 1:
axs[i][j].text(xpos, magic*0.5,
units,
horizontalalignment='center',
verticalalignment='top',
fontsize=12, color='k',
transform=trans)
# ------------------------------------------------- #
# scales and tickmarks
# ------------------------------------------------- #
axs[i][j].set_xscale(linOrlog)
axs[i][j].set_ylim([Z[-1], 0])
axs[i][j].axes.xaxis.set_ticks(xticks)
axs[i][j].axes.xaxis.set_ticklabels(sxticks, fontsize=8)
for label in axs[i][j].axes.xaxis.get_ticklabels():
label.set_rotation(90)
axs[i][j].tick_params(axis='x', direction='out')
axs[i][j].xaxis.tick_top()
axs[i][j].xaxis.set_label_position('top')
axs[i][j].xaxis.grid(True, which=whichticks,
linewidth=0.25, linestyle='-',
color='0.75', zorder=100)
axs[i][j].yaxis.grid(True, which=whichticks,
linewidth=0.25, linestyle='-',
color='0.75', zorder=100)
axs[i][j].yaxis.set_ticks(np.arange(0, max(Z), 100))
if i != 0:
axs[i][j].set_yticklabels("")
# ------------------------------------------------- #
# End of curve loop
# ------------------------------------------------- #
# Add Depth label
axs[0][0].text(0, 1.05, 'MD\n$m$', fontsize='10',
horizontalalignment='center',
verticalalignment='center',
transform=axs[0][0].transAxes)
axs[0][0].axes.yaxis.get_ticklabels()
axs[0][0].axes.xaxis.set_ticklabels('')
for label in axs[0][0].axes.yaxis.get_ticklabels():
label.set_rotation(90)
label.set_fontsize(10)
for label in axs[1][0].axes.xaxis.get_ticklabels():
label.set_rotation(90)
label.set_fontsize(10)
# Add Tops
try:
if os.path.exists(tc.tops_file):
tops = utils.get_tops(tc.tops_file)
topx = get_curve_params('DT', fname)
topmidpt = np.amax((topx)['xright'])
# plot tops
for i in range(ntracks):
for mkr, depth in tops.iteritems():
# draw horizontal bars at the top position
axs[i][-1].axhline(y=depth,
xmin=0.01, xmax=.99,
color='b', lw=2,
alpha=0.5,
zorder=100)
# draw text box at the right edge of the last track
axs[-1][-1].text(x=topmidpt, y=depth, s=mkr,
alpha=0.5, color='k',
fontsize='8',
horizontalalignment='center',
verticalalignment='center',
zorder=10000,
bbox=dict(facecolor='white',
edgecolor='k',
alpha=0.25,
lw=0.25),
weight='light')
except AttributeError:
Notice.warning("No tops for this well")
except TypeError:
# We didn't get a tops file so move along.
print "No tops for this well"
return gs
def plot_feature_well(tc, gs):
"""
Plotting function for the feature well.
Args:
tc (TransectContainer): The container for the main plot.
log (axis): A matplotlib axis.
gs (GridSpec): A matplotlib gridspec.
"""
fname = tc.settings['curve_display']
logs = tc.log.get(tc.feature_well)
if not logs:
# There was no data for this well, so there won't be a feature plot.
Notice.fail("There's no well data for feature well " + tc.feature_well)
return gs
Z = logs.data['DEPT']
curves = [
'GR', 'DT', 'DPHI_SAN', 'NPHI_SAN', 'DTS', 'RT_HRLT', 'RHOB', 'DRHO'
]
window = tc.settings.get('curve_smooth_window') or 51
ntracks = 5
lw = 1.0
smooth = True
naxes = 0
ncurv_per_track = np.zeros(ntracks)
if getattr(tc.log, 'striplog', None):
ncurv_per_track[0] = 1
for curve in curves:
naxes += 1
params = get_curve_params(curve, fname)
ncurv_per_track[params['track']] += 1
axss = plt.subplot(gs[2:, -5])
axs0 = [axss, axss.twiny()]
axs1 = [plt.subplot(gs[2:, -4])]
axs2 = [plt.subplot(gs[2:, -3])]
axs3 = [plt.subplot(gs[2:, -2])]
axs4 = [plt.subplot(gs[2:, -1])]
axs = [axs0, axs1, axs2, axs3, axs4]
if getattr(tc.log, 'striplog', None):
legend = Legend.default()
try:
logs.striplog[tc.log.striplog].plot_axis(axs0[0], legend=legend)
except KeyError:
# In fact, this striplog doesn't exist.
Notice.fail("There is no such striplog" + tc.log.striplog)
# And move on...
axs0[0].set_ylim([Z[-1], 0])
label_shift = np.zeros(len(axs))
for curve in curves:
try:
values = logs.data[curve]
except ValueError:
Notice.warning("Curve not present: " + curve)
values = np.empty_like(Z)
values[:] = np.nan
params = get_curve_params(curve, fname)
i = params['track']
j = 0
label_shift[i] += 1
linOrlog = params['logarithmic']
sxticks = np.array(params['xticks'])
xticks = np.array(sxticks, dtype=float)
whichticks = 'major'
if linOrlog == 'log':
midline = np.log(np.mean(xticks))
xpos = midline
whichticks = 'minor'
else:
midline = np.mean(xticks)
xpos = midline
if smooth:
values = utils.rolling_median(values, window)
if curve == 'GR':
j = 1 # second axis in first track
label_shift[i] = 1
if params['fill_left_cond']:
# do the fill for the lithology track
axs[i][j].fill_betweenx(Z,
params['xleft'],
values,
facecolor=params['fill_left'],
alpha=1.0,
zorder=11)
if (curve == 'DPHI_SAN') and params['fill_left_cond']:
# do the fill for the neutron porosity track
try:
nphi = utils.rolling_median(logs.data['NPHI_SAN'], window)
except ValueError:
Notice.warning("No NPHI in this well")
nphi = np.empty_like(Z)
nphi[:] = np.nan
axs[i][j].fill_betweenx(Z,
nphi,
values,
where=nphi >= values,
facecolor=params['fill_left'],
alpha=1.0,
zorder=11)
axs[i][j].fill_betweenx(Z,
nphi,
values,
where=nphi <= values,
facecolor='#8C1717',
alpha=0.5,
zorder=12)
if curve == 'DRHO':
blk_drho = 3.2
values += blk_drho # this is a hack to get DRHO on RHOB scale
axs[i][j].fill_betweenx(Z,
blk_drho,
values,
where=nphi <= values,
facecolor='#CCCCCC',
alpha=0.5,
zorder=12)
# fill right
if params['fill_right_cond']:
axs[i][j].fill_betweenx(Z,
values,
params['xright'],
facecolor=params['fill_right'],
alpha=1.0,
zorder=12)
# plot curve
axs[i][j].plot(values, Z, color=params['hexcolor'], lw=lw, zorder=13)
# set scale of curve
axs[i][j].set_xlim([params['xleft'], params['xright']])
# ------------------------------------------------- #
# curve labels
# ------------------------------------------------- #
trans = transforms.blended_transform_factory(axs[i][j].transData,
axs[i][j].transData)
magic = -Z[-1] / 12.
axs[i][j].text(xpos,
magic - (magic / 4) * (label_shift[i] - 1),
curve,
horizontalalignment='center',
verticalalignment='bottom',
fontsize=12,
color=params['hexcolor'],
transform=trans)
# curve units
units = '${}$'.format(params['units'])
if label_shift[i] <= 1:
axs[i][j].text(xpos,
magic * 0.5,
units,
horizontalalignment='center',
verticalalignment='top',
fontsize=12,
color='k',
transform=trans)
# ------------------------------------------------- #
# scales and tickmarks
# ------------------------------------------------- #
axs[i][j].set_xscale(linOrlog)
axs[i][j].set_ylim([Z[-1], 0])
axs[i][j].axes.xaxis.set_ticks(xticks)
axs[i][j].axes.xaxis.set_ticklabels(sxticks, fontsize=8)
for label in axs[i][j].axes.xaxis.get_ticklabels():
label.set_rotation(90)
axs[i][j].tick_params(axis='x', direction='out')
axs[i][j].xaxis.tick_top()
axs[i][j].xaxis.set_label_position('top')
axs[i][j].xaxis.grid(True,
which=whichticks,
linewidth=0.25,
linestyle='-',
color='0.75',
zorder=100)
axs[i][j].yaxis.grid(True,
which=whichticks,
linewidth=0.25,
linestyle='-',
color='0.75',
zorder=100)
axs[i][j].yaxis.set_ticks(np.arange(0, max(Z), 100))
if i != 0:
axs[i][j].set_yticklabels("")
# ------------------------------------------------- #
# End of curve loop
# ------------------------------------------------- #
# Add Depth label
axs[0][0].text(0,
1.05,
'MD\n$m$',
fontsize='10',
horizontalalignment='center',
verticalalignment='center',
transform=axs[0][0].transAxes)
axs[0][0].axes.yaxis.get_ticklabels()
axs[0][0].axes.xaxis.set_ticklabels('')
for label in axs[0][0].axes.yaxis.get_ticklabels():
label.set_rotation(90)
label.set_fontsize(10)
for label in axs[1][0].axes.xaxis.get_ticklabels():
label.set_rotation(90)
label.set_fontsize(10)
# Add Tops
try:
if os.path.exists(tc.tops_file):
tops = utils.get_tops(tc.tops_file)
topx = get_curve_params('DT', fname)
topmidpt = np.amax((topx)['xright'])
# plot tops
for i in range(ntracks):
for mkr, depth in tops.iteritems():
# draw horizontal bars at the top position
axs[i][-1].axhline(y=depth,
xmin=0.01,
xmax=.99,
color='b',
lw=2,
alpha=0.5,
zorder=100)
# draw text box at the right edge of the last track
axs[-1][-1].text(x=topmidpt,
y=depth,
s=mkr,
alpha=0.5,
color='k',
fontsize='8',
horizontalalignment='center',
verticalalignment='center',
zorder=10000,
bbox=dict(facecolor='white',
edgecolor='k',
alpha=0.25,
lw=0.25),
weight='light')
except AttributeError:
Notice.warning("No tops for this well")
except TypeError:
# We didn't get a tops file so move along.
print "No tops for this well"
return gs
def plot(tc):
"""
Constructs a multi-subplot matplotlib figure.
Args:
transect (TransectContainer): A transect container.
"""
h = 15
mw = 16 # width of main section (inches) must be div by 4
fw = 5 # width of the feature plot (inches) must be div by 5
n_grids = len(tc.potfield.data)
# We will save the same figure we make, to ensure the saved figure
# has everything in the right places. For example, see this discussion:
# http://stackoverflow.com/questions/7906365/
save_dpi = getattr(tc, 'save_dpi', tc.settings.get('default_dpi'))
dpi = save_dpi or 80
fig = plt.figure(figsize=(mw + fw + 1, 15),
facecolor='w',
edgecolor='k',
dpi=dpi,
frameon=True)
gs = gridspec.GridSpec(h, mw + fw + 1)
# Left-hand column.
header = fig.add_subplot(gs[0:1, 0:mw / 2])
description = fig.add_subplot(gs[1:3, 0:mw / 2])
locmap = fig.add_subplot(gs[0:3, mw / 2:mw]) # Aspect = 8:3
elevation = fig.add_subplot(gs[3, :mw])
xsection = fig.add_subplot(gs[4:h - n_grids, :mw])
xsec_logs = fig.add_subplot(gs[4:h - n_grids, :mw])
potfield = fig.add_subplot(gs[h - n_grids:, :mw])
# Right-hand column.
log_header = fig.add_subplot(gs[0:1, -1 * fw:])
# log_plot is dealt with by passing gs to feature_plot.plot_feature_well()
# Adjust white space between subplots
# ------------------------------------------------------------ #
left = 0.05 # left side of the subplots of the figure
right = 0.95 # right side of the subplots of the figure
bottom = 0.05 # bottom of the subplots of the figure
top = 0.95 # top of the subplots of the figure
wspace = 0.05 # blank w space between subplots
hspace = 0.1 # blank h space between subplots
fig.subplots_adjust(left, bottom, right, top, wspace, hspace)
bbox = {'fc': 'w', 'pad': 0, 'ec': 'none', 'alpha': 0.5}
props = {'ha': 'left', 'va': 'center', 'bbox': bbox}
# Header
# ---------------------------------------------------------#
print "Header"
header.axis("off")
dy = 0.2
header.text(0.0,
0.5 + dy,
tc.title,
props,
fontsize=30,
horizontalalignment='left',
verticalalignment='bottom')
# horizontal line
header.axhline(y=0.5, xmin=0, xmax=1.25, linewidth=1.5, color='k')
# Subtitle
header.text(1.0,
0.5 + dy, (tc.subtitle),
fontsize=15,
horizontalalignment='right',
verticalalignment='bottom',
weight='bold')
descr = tc.description
if tc.meta:
description.text(0,
1.0,
tc.domain.upper(),
horizontalalignment='left',
verticalalignment='bottom',
fontsize=14)
description.text(1.0,
1.0,
tc.velocity,
horizontalalignment='right',
verticalalignment='bottom',
fontsize=12)
descr_pos = 0.8 # Where to position the rest.
else:
descr_pos = 1.0
# Paragraph description
# -----------------------------------------------------#
description.text(0,
descr_pos,
descr,
horizontalalignment='left',
verticalalignment='top',
fontsize=12,
family='serif')
description.axis('off')
# Wrap text
fig.canvas.mpl_connect('draw_event',
lambda event: on_draw(event, description))
# Map
# ---------------------------------------------------------#
print "Locmap"
tx, ty = tc.data.coords.xy
res = 'h' # c, l, i, h, f
# Generate Basemap object.
m = Basemap(projection='tmerc',
lon_0=tc.locmap.mid.x,
lat_0=tc.locmap.mid.y,
resolution=res,
llcrnrlon=tc.locmap.ll.x,
llcrnrlat=tc.locmap.ll.y,
urcrnrlon=tc.locmap.ur.x,
urcrnrlat=tc.locmap.ur.y,
ax=locmap)
# Finish drawing the basemap.
draw_basemap(m, tc)
for layer, details in tc.locmap.layers.items():
data = getattr(tc.locmap, layer)
for l in data:
line_t = utils.utm2lola(l)
params = details.get('params', None)
if params:
plot_line(m, line_t, **params)
else:
plot_line(m, line_t, colour='k', alpha=0.5)
if layer == "wells":
for p in data:
point_t = utils.utm2lola(p)
params = details.get('params', None)
if params:
plot_point(m, point_t, zorder=100, **params)
else:
plot_point(m, point_t, zorder=100, colour='k', alpha=0.5)
lo, la = point_t.xy
x, y = m(lo, la)
# Plot the names of wells in the xsection
# When we have names we can also plot special symbol
# for the feature well.
# Plot this transect line
line_t = utils.utm2lola(tc.data)
plot_line(m, line_t, colour='r', lw=3)
# Adjust border thickness
[i.set_linewidth(8) for i in locmap.spines.itervalues()]
[i.set_color("white") for i in locmap.spines.itervalues()]
# Elevation and bedrock plot
# -----------------------------------------------------------#
print "Elevation"
for i, geo in enumerate(tc.bedrock.data[:-1]):
lim1 = tc.bedrock.coords[i]
lim2 = tc.bedrock.coords[i + 1]
idx = np.where(
np.logical_and(tc.elevation.coords >= lim1,
tc.elevation.coords <= lim2))[0]
if len(idx) > 1:
if idx[-1] < tc.elevation.coords.size - 1:
idx = np.append(idx, (idx[-1] + 1))
hsv = np.array([[geo["AV_HUE"], geo["AV_SAT"],
geo["AV_VAL"]]]).reshape(1, 1, 3)
color = hsv_to_rgb(hsv / 255.)
elevation.bar(tc.elevation.coords[idx],
tc.elevation.data[idx],
width=1.0,
linewidth=0,
color=color.flatten())
elevation.plot(tc.elevation.coords[idx],
tc.elevation.data[idx],
lw=0.5,
color='k')
max_height = np.amax(tc.elevation.all_data)
elevation.set_ylim((0, max_height))
elevation.set_xlim(tc.extents[:2])
elevation.set_yticks([0, int(max_height), int(np.amax(tc.elevation.data))])
elevation.set_xticklabels([])
elevation.tick_params(axis='y', which='major', labelsize=8)
elevation.patch.set_alpha(0.1)
elevation.set_ylabel("Elevation [m]", fontsize=8)
elevation.grid(True)
elevation.tick_params(axis='x', which='major', labelsize=0)
elevation.xaxis.grid(True, which='major')
elevation.text(0.01,
0.8,
"Elevation",
props,
va='bottom',
fontsize=11,
weight='bold',
transform=elevation.transAxes)
elevation.text(0.01,
0.75,
"Surface geology",
props,
va='top',
fontsize=10,
transform=elevation.transAxes)
elevation.set_frame_on(False)
for tick in elevation.get_xaxis().get_major_ticks():
tick.set_pad(-8.)
tick.label1 = tick._get_text1()
# Seismic cross section
# ------------------------------------------------------------#
print "Seismic"
for coords, data in zip(tc.seismic.coords, tc.seismic.data):
max_z = data["traces"].shape[0] * data["sample_interval"]
im = xsection.imshow(data["traces"],
extent=[
np.amin(coords) / 1000.0,
np.amax(coords) / 1000.0, max_z, 0
],
aspect="auto",
cmap=tc.seismic_cmap)
# Horizons
colours = ['b', 'g', 'orange', 'c', 'magenta', 'pink']
for i, (horizon, data) in enumerate(tc.horizons.data.items()):
coords = tc.horizons.coords[horizon]
xsection.scatter(coords / 1000, data, color=colours[i], marker='.')
# labels
xsection.text(0.01,
0.025 * (i + 1),
horizon,
transform=xsection.transAxes,
ha='left',
color=colours[i],
va='center',
fontsize=12)
# Axes etc.
plot_axis = [
tc.extents[0] / 1000., tc.extents[1] / 1000., tc.extents[2],
tc.extents[3]
]
xsection.axis(plot_axis)
xsection.set_xticklabels([])
if tc.domain.lower() in ['depth', 'd', 'z']:
xsection.set_ylabel("Depth [m]", fontsize=8)
else:
xsection.set_ylabel("TWTT [ms]", fontsize=8)
xsection.tick_params(axis='y', which='major', labelsize=8)
xsection.tick_params(axis='x', which='major', labelsize=0)
xsection.yaxis.grid(True, which='major')
xsection.xaxis.grid(True, which='major')
xsection.set_frame_on(False)
# Seismic colorbar
colorbar_ax = add_subplot_axes(xsection, [0.975, 0.025, 0.01, 0.1])
fig.colorbar(im, cax=colorbar_ax)
colorbar_ax.text(0.5,
0.9,
"+",
transform=colorbar_ax.transAxes,
ha='center',
color='white',
va='center',
fontsize=12)
colorbar_ax.text(0.5,
0.15,
"-",
transform=colorbar_ax.transAxes,
color='k',
ha='center',
va='center',
fontsize=16)
colorbar_ax.set_axis_off()
# Title
xsection.text(0.01,
0.99,
"Seismic",
color='k',
ha='left',
va='top',
fontsize=12,
weight='bold',
transform=xsec_logs.transAxes)
# Potential field data
# -----------------------------------------------------------#
print "Potfields"
for i, (field, payload) in enumerate(tc.potfield.data.items()):
bot = 1 - (i + 1.) / n_grids
height = (1. / n_grids) - 0.05
rect = [0, bot, 1, height]
this_ax = add_subplot_axes(potfield, rect)
sc = this_ax.scatter(payload['coords'],
payload['data'],
c=payload['colour'],
cmap=payload['cmap'],
s=1,
edgecolor='',
vmin=-50,
vmax=150)
this_ax.set_xlim(tc.extents[:2])
this_ax.set_frame_on(False)
this_ax.set_xticks([])
this_ax.tick_params(axis='y', which='major', labelsize=8)
this_ax.grid(True)
scale = payload['scale']
if scale:
this_ax.set_ylim(float(scale[1]), float(scale[0]))
if payload['colour_is_file']:
tcol = '#555555'
else:
tcol = payload['colour']
this_ax.text(0.01,
0.01,
field,
ha='left',
va='bottom',
fontsize=10,
color=tcol,
transform=this_ax.transAxes)
# potfield colorbar
# TODO: This doesn't work.
if payload.get('cmap'):
# pf_cbar_ax = add_subplot_axes(this_ax, [0.975, 0.1, 0.01, 0.8])
# fig.colorbar(sc, cax=pf_cbar_ax)
# pf_cbar_ax.set_axis_off()
pass
potfield.axis(plot_axis)
potfield.set_frame_on(False)
potfield.set_yticks([])
potfield.xaxis.grid(True, which='major')
potfield.tick_params(axis='x', which='major', labelsize=10)
potfield.set_xlabel("Transect range [km]", fontsize=10, ha='center')
potfield.text(0.01,
1.0,
"Potential fields",
ha='left',
va='top',
fontsize=11,
weight='bold',
color='k',
transform=potfield.transAxes)
# Log overlays
# --------------------------------------------------------#
print "Logs"
if tc.locmap.layers.get('wells'):
if tc.locmap.layers['wells'].get('colour'):
well_colour = tc.locmap.layers['wells']['colour']
else:
well_colour = tc.settings.get('default_colour')
if not well_colour:
well_colour = 'k'
c = tc.seismic_log_colour
for name, las, pos in zip(tc.log.names, tc.log.data, tc.log.coords):
if name == tc.feature_well:
alpha, lw = 0.5, 1.5
weight = 'bold'
else:
alpha, lw = 0.25, 1.0
weight = 'normal'
if las:
data = np.nan_to_num(las.data[tc.seismic_log])
data /= np.amax(data)
z = las.data['DEPT']
if tc.domain.lower() in ['time', 'twt', 'twtt', 't']:
dt = 0.001
data = tc.seismic.velocity.depth2time(data, pos, dz=z, dt=dt)
start = tc.seismic.velocity.depth2timept(las.start, pos)
z = np.arange(0, len(data), 1) + 1000 * start # ms
# Some post-processing for display
lgsc = 0.015 # hack to compress the log width
data *= lgsc * (tc.extents[1] - tc.extents[0])
if data.size > 0:
data += pos - 0.5 * np.amax(data)
xsec_logs.axvline(x=pos,
color=well_colour,
alpha=alpha,
lw=lw,
ymin=0,
ymax=z[-1])
xsec_logs.plot(data, z, c, lw=0.5, alpha=0.75)
else:
# Need to get TD from SHP or well header sheet.
z = [tc.extents[2] - 40]
xsec_logs.axvline(x=pos, color=well_colour, alpha=0.25)
elevation.axvline(x=pos, color=well_colour, alpha=alpha, lw=lw)
potfield.axvline(x=pos / 1000, color=well_colour, alpha=alpha, lw=lw)
# Well name annotation
elevation.text(pos,
max_height - 10,
name,
color=well_colour,
va='top',
ha='center',
fontsize=10,
weight=weight)
xsec_logs.set_xlim((tc.extents[0], tc.extents[1]))
xsec_logs.set_ylim((tc.extents[2], tc.extents[3]))
xsec_logs.axis("off")
# Log type annotation, top left
xsec_logs.text(0.01,
0.965,
tc.seismic_log + ' log',
color=c,
ha='left',
va='top',
fontsize=12,
transform=xsec_logs.transAxes)
# Feature plot
# -----------------------------------------------------#
if tc.feature_well:
print "Feature well:", tc.feature_well
log_header.text(0.0,
1.0, ("Well " + tc.feature_well),
verticalalignment='top',
horizontalalignment='left',
fontsize=14,
fontweight='bold')
# horizontal line
log_header.axhline(y=0.5, xmin=0, xmax=1.25, linewidth=1, color='k')
plot_feature_well(tc, gs)
else:
Notice.warning("No feature well")
log_header.axis("off")
# Logo etc.
# --------------------------------------------------------------#
print "Logo"
try:
path = os.path.join(tc.data_dir, tc.settings['logo_file'])
im = Image.open(path)
im.thumbnail((fig.dpi, fig.dpi), Image.ANTIALIAS)
except IOError:
print "Image is missing", path
im = np.zeros((1, 1, 3))
w, h = im.size
# We need a float array between 0-1, rather than
# a uint8 array between 0-255
im = np.array(im).astype(np.float) / 255
# With newer (1.0) versions of matplotlib, you can
# use the "zorder" kwarg to make the image overlay
# the plot, rather than hide behind it... (e.g. zorder=10)
fig.figimage(im, (0.95 * fig.bbox.xmax) - w, (0.96 * fig.bbox.ymax) - h)
# Annotate config file and creation date
plt.figtext(0.950,
0.030,
tc.time,
ha="right",
va="bottom",
color="gray",
size=8)
plt.figtext(0.950,
0.04,
tc.config_file,
ha="right",
va="bottom",
color="gray",
size=8)
year = datetime.datetime.now().year
text = "$\copyright$ {} Department of Energy".format(year)
plt.figtext(0.750,
0.03,
text,
ha="left",
va="bottom",
color="gray",
size=8)
# Finish
# --------------------------------------------------------------#
save_file = getattr(tc, 'save_file', None)
if save_file:
if type(save_file) != 'str':
# Then it's probably a bool from 'yes' or 'true' in the config
save_file = tc.config_file.split('.')[0] + '.png'
if save_file == 'config.png':
save_file = 'temp.png'
Notice.ok("Saving file " + save_file + "...", hold=True)
plt.savefig(save_file, dpi=fig.dpi)
Notice.ok("Done")
Notice.warning("The displayed image is not identical to the saved one")
plt.show()
else:
plt.show()
def plot(tc):
"""
Constructs a multi-subplot matplotlib figure.
Args:
transect (TransectContainer): A transect container.
"""
h = 15
mw = 16 # width of main section (inches) must be div by 4
fw = 5 # width of the feature plot (inches) must be div by 5
n_grids = len(tc.potfield.data)
# We will save the same figure we make, to ensure the saved figure
# has everything in the right places. For example, see this discussion:
# http://stackoverflow.com/questions/7906365/
save_dpi = getattr(tc, 'save_dpi', tc.settings.get('default_dpi'))
dpi = save_dpi or 80
fig = plt.figure(figsize=(mw + fw + 1, 15),
facecolor='w',
edgecolor='k',
dpi=dpi,
frameon=True)
gs = gridspec.GridSpec(h, mw + fw + 1)
# Left-hand column.
header = fig.add_subplot(gs[0:1, 0:mw/2])
description = fig.add_subplot(gs[1:3, 0:mw/2])
locmap = fig.add_subplot(gs[0:3, mw/2:mw]) # Aspect = 8:3
elevation = fig.add_subplot(gs[3, :mw])
xsection = fig.add_subplot(gs[4:h-n_grids, :mw])
xsec_logs = fig.add_subplot(gs[4:h-n_grids, :mw])
potfield = fig.add_subplot(gs[h-n_grids:, :mw])
# Right-hand column.
log_header = fig.add_subplot(gs[0:1, -1*fw:])
# log_plot is dealt with by passing gs to feature_plot.plot_feature_well()
# Adjust white space between subplots
# ------------------------------------------------------------ #
left = 0.05 # left side of the subplots of the figure
right = 0.95 # right side of the subplots of the figure
bottom = 0.05 # bottom of the subplots of the figure
top = 0.95 # top of the subplots of the figure
wspace = 0.05 # blank w space between subplots
hspace = 0.1 # blank h space between subplots
fig.subplots_adjust(left, bottom, right, top, wspace, hspace)
bbox = {'fc': 'w', 'pad': 0, 'ec': 'none', 'alpha': 0.5}
props = {'ha': 'left', 'va': 'center', 'bbox': bbox}
# Header
# ---------------------------------------------------------#
print "Header"
header.axis("off")
dy = 0.2
header.text(0.0, 0.5 + dy, tc.title,
props,
fontsize=30,
horizontalalignment='left',
verticalalignment='bottom'
)
# horizontal line
header.axhline(y=0.5,
xmin=0,
xmax=1.25,
linewidth=1.5,
color='k')
# Subtitle
header.text(1.0, 0.5 + dy,
(tc.subtitle),
fontsize=15,
horizontalalignment='right',
verticalalignment='bottom', weight='bold')
descr = tc.description
if tc.meta:
description.text(0, 1.0,
tc.domain.upper(),
horizontalalignment='left',
verticalalignment='bottom',
fontsize=14
)
description.text(1.0, 1.0,
tc.velocity,
horizontalalignment='right',
verticalalignment='bottom',
fontsize=12
)
descr_pos = 0.8 # Where to position the rest.
else:
descr_pos = 1.0
# Paragraph description
# -----------------------------------------------------#
description.text(0, descr_pos,
descr,
horizontalalignment='left',
verticalalignment='top',
fontsize=12, family='serif'
)
description.axis('off')
# Wrap text
fig.canvas.mpl_connect('draw_event', lambda event: on_draw(event, description))
# Map
# ---------------------------------------------------------#
print "Locmap"
tx, ty = tc.data.coords.xy
res = 'h' # c, l, i, h, f
# Generate Basemap object.
m = Basemap(projection='tmerc',
lon_0=tc.locmap.mid.x, lat_0=tc.locmap.mid.y,
resolution=res,
llcrnrlon=tc.locmap.ll.x, llcrnrlat=tc.locmap.ll.y,
urcrnrlon=tc.locmap.ur.x, urcrnrlat=tc.locmap.ur.y,
ax=locmap)
# Finish drawing the basemap.
draw_basemap(m, tc)
for layer, details in tc.locmap.layers.items():
data = getattr(tc.locmap, layer)
for l in data:
line_t = utils.utm2lola(l)
params = details.get('params', None)
if params:
plot_line(m, line_t, **params)
else:
plot_line(m, line_t, colour='k', alpha=0.5)
if layer == "wells":
for p in data:
point_t = utils.utm2lola(p)
params = details.get('params', None)
if params:
plot_point(m,
point_t,
zorder=100,
**params)
else:
plot_point(m,
point_t,
zorder=100,
colour='k',
alpha=0.5)
lo, la = point_t.xy
x, y = m(lo, la)
# Plot the names of wells in the xsection
# When we have names we can also plot special symbol
# for the feature well.
# Plot this transect line
line_t = utils.utm2lola(tc.data)
plot_line(m, line_t, colour='r', lw=3)
# Adjust border thickness
[i.set_linewidth(8) for i in locmap.spines.itervalues()]
[i.set_color("white") for i in locmap.spines.itervalues()]
# Elevation and bedrock plot
# -----------------------------------------------------------#
print "Elevation"
for i, geo in enumerate(tc.bedrock.data[:-1]):
lim1 = tc.bedrock.coords[i]
lim2 = tc.bedrock.coords[i + 1]
idx = np.where(np.logical_and(tc.elevation.coords >= lim1,
tc.elevation.coords <= lim2))[0]
if len(idx) > 1:
if idx[-1] < tc.elevation.coords.size - 1:
idx = np.append(idx, (idx[-1] + 1))
hsv = np.array([[geo["AV_HUE"], geo["AV_SAT"],
geo["AV_VAL"]]]).reshape(1, 1, 3)
color = hsv_to_rgb(hsv / 255.)
elevation.bar(tc.elevation.coords[idx],
tc.elevation.data[idx],
width=1.0,
linewidth=0,
color=color.flatten())
elevation.plot(tc.elevation.coords[idx],
tc.elevation.data[idx],
lw=0.5, color='k')
max_height = np.amax(tc.elevation.all_data)
elevation.set_ylim((0, max_height))
elevation.set_xlim(tc.extents[:2])
elevation.set_yticks([0, int(max_height),
int(np.amax(tc.elevation.data))])
elevation.set_xticklabels([])
elevation.tick_params(axis='y', which='major', labelsize=8)
elevation.patch.set_alpha(0.1)
elevation.set_ylabel("Elevation [m]", fontsize=8)
elevation.grid(True)
elevation.tick_params(axis='x', which='major', labelsize=0)
elevation.xaxis.grid(True, which='major')
elevation.text(0.01, 0.8,
"Elevation",
props, va='bottom',
fontsize=11, weight='bold',
transform=elevation.transAxes)
elevation.text(0.01, 0.75,
"Surface geology",
props, va='top',
fontsize=10,
transform=elevation.transAxes)
elevation.set_frame_on(False)
for tick in elevation.get_xaxis().get_major_ticks():
tick.set_pad(-8.)
tick.label1 = tick._get_text1()
# Seismic cross section
# ------------------------------------------------------------#
print "Seismic"
for coords, data in zip(tc.seismic.coords, tc.seismic.data):
max_z = data["traces"].shape[0] * data["sample_interval"]
im = xsection.imshow(data["traces"],
extent=[np.amin(coords) / 1000.0,
np.amax(coords) / 1000.0,
max_z, 0],
aspect="auto", cmap=tc.seismic_cmap)
# Horizons
colours = ['b', 'g', 'orange', 'c', 'magenta', 'pink']
for i, (horizon, data) in enumerate(tc.horizons.data.items()):
coords = tc.horizons.coords[horizon]
xsection.scatter(coords/1000, data,
color=colours[i],
marker='.')
# labels
xsection.text(0.01, 0.025*(i+1),
horizon,
transform=xsection.transAxes,
ha='left', color=colours[i],
va='center', fontsize=12)
# Axes etc.
plot_axis = [tc.extents[0] / 1000., tc.extents[1] / 1000.,
tc.extents[2], tc.extents[3]]
xsection.axis(plot_axis)
xsection.set_xticklabels([])
if tc.domain.lower() in ['depth', 'd', 'z']:
xsection.set_ylabel("Depth [m]", fontsize=8)
else:
xsection.set_ylabel("TWTT [ms]", fontsize=8)
xsection.tick_params(axis='y', which='major', labelsize=8)
xsection.tick_params(axis='x', which='major', labelsize=0)
xsection.yaxis.grid(True, which='major')
xsection.xaxis.grid(True, which='major')
xsection.set_frame_on(False)
# Seismic colorbar
colorbar_ax = add_subplot_axes(xsection, [0.975, 0.025, 0.01, 0.1])
fig.colorbar(im, cax=colorbar_ax)
colorbar_ax.text(0.5, 0.9, "+",
transform=colorbar_ax.transAxes,
ha='center', color='white',
va='center', fontsize=12)
colorbar_ax.text(0.5, 0.15, "-",
transform=colorbar_ax.transAxes, color='k',
ha='center', va='center', fontsize=16)
colorbar_ax.set_axis_off()
# Title
xsection.text(0.01, 0.99,
"Seismic",
color='k',
ha='left', va='top',
fontsize=12, weight='bold',
transform=xsec_logs.transAxes)
# Potential field data
# -----------------------------------------------------------#
print "Potfields"
for i, (field, payload) in enumerate(tc.potfield.data.items()):
bot = 1 - (i+1.)/n_grids
height = (1./n_grids) - 0.05
rect = [0, bot, 1, height]
this_ax = add_subplot_axes(potfield, rect)
sc = this_ax.scatter(payload['coords'],
payload['data'],
c=payload['colour'],
cmap=payload['cmap'],
s=1,
edgecolor='',
vmin=-50, vmax=150)
this_ax.set_xlim(tc.extents[:2])
this_ax.set_frame_on(False)
this_ax.set_xticks([])
this_ax.tick_params(axis='y', which='major', labelsize=8)
this_ax.grid(True)
scale = payload['scale']
if scale:
this_ax.set_ylim(float(scale[1]), float(scale[0]))
if payload['colour_is_file']:
tcol = '#555555'
else:
tcol = payload['colour']
this_ax.text(0.01, 0.01, field,
ha='left', va='bottom',
fontsize=10, color=tcol,
transform=this_ax.transAxes)
# potfield colorbar
# TODO: This doesn't work.
if payload.get('cmap'):
# pf_cbar_ax = add_subplot_axes(this_ax, [0.975, 0.1, 0.01, 0.8])
# fig.colorbar(sc, cax=pf_cbar_ax)
# pf_cbar_ax.set_axis_off()
pass
potfield.axis(plot_axis)
potfield.set_frame_on(False)
potfield.set_yticks([])
potfield.xaxis.grid(True, which='major')
potfield.tick_params(axis='x', which='major', labelsize=10)
potfield.set_xlabel("Transect range [km]", fontsize=10, ha='center')
potfield.text(0.01, 1.0, "Potential fields",
ha='left', va='top',
fontsize=11, weight='bold', color='k',
transform=potfield.transAxes)
# Log overlays
# --------------------------------------------------------#
print "Logs"
if tc.locmap.layers.get('wells'):
if tc.locmap.layers['wells'].get('colour'):
well_colour = tc.locmap.layers['wells']['colour']
else:
well_colour = tc.settings.get('default_colour')
if not well_colour:
well_colour = 'k'
c = tc.seismic_log_colour
for name, las, pos in zip(tc.log.names, tc.log.data, tc.log.coords):
if name == tc.feature_well:
alpha, lw = 0.5, 1.5
weight = 'bold'
else:
alpha, lw = 0.25, 1.0
weight = 'normal'
if las:
data = np.nan_to_num(las.data[tc.seismic_log])
data /= np.amax(data)
z = las.data['DEPT']
if tc.domain.lower() in ['time', 'twt', 'twtt', 't']:
dt = 0.001
data = tc.seismic.velocity.depth2time(data, pos, dz=z, dt=dt)
start = tc.seismic.velocity.depth2timept(las.start, pos)
z = np.arange(0, len(data), 1) + 1000*start # ms
# Some post-processing for display
lgsc = 0.015 # hack to compress the log width
data *= lgsc * (tc.extents[1] - tc.extents[0])
if data.size > 0:
data += pos - 0.5 * np.amax(data)
xsec_logs.axvline(x=pos,
color=well_colour,
alpha=alpha,
lw=lw,
ymin=0,
ymax=z[-1])
xsec_logs.plot(data, z, c, lw=0.5, alpha=0.75)
else:
# Need to get TD from SHP or well header sheet.
z = [tc.extents[2]-40]
xsec_logs.axvline(x=pos, color=well_colour, alpha=0.25)
elevation.axvline(x=pos, color=well_colour, alpha=alpha, lw=lw)
potfield.axvline(x=pos/1000, color=well_colour, alpha=alpha, lw=lw)
# Well name annotation
elevation.text(pos, max_height-10,
name,
color=well_colour,
va='top',
ha='center',
fontsize=10,
weight=weight)
xsec_logs.set_xlim((tc.extents[0], tc.extents[1]))
xsec_logs.set_ylim((tc.extents[2], tc.extents[3]))
xsec_logs.axis("off")
# Log type annotation, top left
xsec_logs.text(0.01, 0.965,
tc.seismic_log+' log',
color=c,
ha='left', va='top',
fontsize=12,
transform=xsec_logs.transAxes)
# Feature plot
# -----------------------------------------------------#
if tc.feature_well:
print "Feature well:", tc.feature_well
log_header.text(0.0, 1.0,
("Well " + tc.feature_well),
verticalalignment='top',
horizontalalignment='left',
fontsize=14,
fontweight='bold'
)
# horizontal line
log_header.axhline(y=0.5,
xmin=0,
xmax=1.25,
linewidth=1,
color='k')
plot_feature_well(tc, gs)
else:
Notice.warning("No feature well")
log_header.axis("off")
# Logo etc.
# --------------------------------------------------------------#
print "Logo"
try:
path = os.path.join(tc.data_dir, tc.settings['logo_file'])
im = Image.open(path)
im.thumbnail((fig.dpi, fig.dpi), Image.ANTIALIAS)
except IOError:
print "Image is missing", path
im = np.zeros((1, 1, 3))
w, h = im.size
# We need a float array between 0-1, rather than
# a uint8 array between 0-255
im = np.array(im).astype(np.float) / 255
# With newer (1.0) versions of matplotlib, you can
# use the "zorder" kwarg to make the image overlay
# the plot, rather than hide behind it... (e.g. zorder=10)
fig.figimage(im, (0.95*fig.bbox.xmax) - w, (0.96*fig.bbox.ymax) - h)
# Annotate config file and creation date
plt.figtext(0.950, 0.030, tc.time,
ha="right", va="bottom", color="gray", size=8)
plt.figtext(0.950, 0.04, tc.config_file,
ha="right", va="bottom", color="gray", size=8)
year = datetime.datetime.now().year
text = "$\copyright$ {} Department of Energy".format(year)
plt.figtext(0.750, 0.03, text,
ha="left", va="bottom", color="gray", size=8)
# Finish
# --------------------------------------------------------------#
save_file = getattr(tc, 'save_file', None)
if save_file:
if type(save_file) != 'str':
# Then it's probably a bool from 'yes' or 'true' in the config
save_file = tc.config_file.split('.')[0] + '.png'
if save_file == 'config.png':
save_file = 'temp.png'
Notice.ok("Saving file "+save_file+"...", hold=True)
plt.savefig(save_file, dpi=fig.dpi)
Notice.ok("Done")
Notice.warning("The displayed image is not identical to the saved one")
plt.show()
else:
plt.show()
