parser = argparse.ArgumentParser(
description='Convert a RAD file to SEG-Y.')
parser.add_argument(
'filename',
metavar='RAD file',
type=str,
nargs='*',
default='./*.RA[D,1,2]',
help=
'The path to one or more RAD files. Uses Unix-style pathname expansion. Omit to find all RAD files in current directory.'
)
parser.add_argument(
'-o',
'--out',
metavar='output file',
type=str,
nargs='?',
default='',
help=
'The path to an output file. Default: same as input file, but with the nominal frequency and sgy file extension.'
)
args = parser.parse_args()
Notice.header("This is rad2segy. Stand back.")
for f in args.filename:
Notice.info("{}".format(f), hold=True)
Notice.ok(" >>> ", hold=True)
outfile = rad2segy(f, args.out)
Notice.info(outfile)
Notice.header("Done")
def main(target, cfg):
"""
Puts everything together.
"""
t0 = time.time()
#####################################################################
#
# READ SEGY
#
#####################################################################
if cfg['segy_library'].lower() == 'obspy':
s = Seismic.from_segy_with_obspy(target, params={'ndim': cfg['ndim']})
else:
s = Seismic.from_segy(target, params={'ndim': cfg['ndim']})
# Set the line and/or xline number.
try:
n, xl = cfg['number']
except:
n, xl = cfg['number'], 0.5
# Set the direction.
if (s.ndim) == 2:
direction = ['inline']
elif cfg['direction'].lower()[0] == 'i':
direction = ['inline']
elif cfg['direction'].lower()[0] in ['x', 'c']: # Allow 'crossline' too.
direction = ['xline']
elif cfg['direction'].lower()[0] == 't':
direction = ['tslice']
else:
direction = ['xline', 'inline']
# Get the data.
try:
ss = [
Seismic.from_seismic(s, n=n, direction=d)
for n, d in zip((n, xl), direction)
]
except IndexError:
# Perhaps misinterpreted 2D as 3D
s = Seismic.from_segy(target, params={'ndim': 2})
direction = ['inline']
ss = [
Seismic.from_seismic(s, n=n, direction=d)
for n, d in zip((n, xl), direction)
]
clip_val = np.percentile(s.data, cfg['percentile'])
if clip_val < 10:
fstr = '{:.3f}'
elif clip_val < 100:
fstr = '{:.2f}'
elif clip_val < 1000:
fstr = '{:.1f}'
else:
fstr = '{:.0f}'
# Notify user of parameters.
Notice.info("n_traces {}".format(s.ntraces))
Notice.info("n_samples {}".format(s.nsamples))
Notice.info("dt {}".format(s.dt))
Notice.info("t_start {}".format(s.tstart))
Notice.info("t_end {}".format(s.tend))
Notice.info("max_val " + fstr.format(np.amax(s.data)))
Notice.info("min_val " + fstr.format(np.amin(s.data)))
Notice.info("clip_val " + fstr.format(clip_val))
t1 = time.time()
Notice.ok("Read data in {:.1f} s".format(t1 - t0))
#####################################################################
#
# MAKE PLOT
#
#####################################################################
Notice.hr_header("Plotting")
# Plot size parameters.
wsl = 6 # Width of sidelabel, inches
mih = 11 # Minimum plot height, inches
fhh = 5 # File header box height, inches
m = 0.75 # basic unit of margins, inches
# Margins, CSS like: top, right, bottom, left.
mt, mr, mb, ml = m, 1.5 * m, m, 1.5 * m
mm = 2 * m # padded margin between seismic and label
# Determine plot dimensions. Kind of laborious and repetitive (see below).
if cfg['plot_width']:
seismic_width = cfg['plot_width'] - wsl - mm - ml - mr
tpi = max([s.ntraces for s in ss]) / seismic_width
else:
tpi = cfg['tpi']
if cfg['plot_height']:
seismic_height = max(
mih, cfg['plot_height']) - mb - 0.75 * (len(ss) - 1) - mt
seismic_height_raw = seismic_height / len(ss)
ips = seismic_height_raw / (s.tbasis[-1] - s.tbasis[0])
else:
ips = cfg['ips']
# Width is determined by seismic width, plus sidelabel, plus margins.
# Height is given by ips, but with a minimum of mih inches.
if 'tslice' in direction:
seismic_width = [s.ntraces / tpi for s in ss]
seismic_height_raw = max([s.nxlines for s in ss]) / tpi
else:
seismic_width = [s.ntraces / tpi for s in ss]
seismic_height_raw = ips * (s.tbasis[-1] - s.tbasis[0])
w = ml + max(seismic_width) + mm + wsl + mr # inches
seismic_height = len(ss) * seismic_height_raw
h_reqd = mb + seismic_height + 0.75 * (len(ss) - 1) + mt # inches
h = max(mih, h_reqd)
# Calculate where to start sidelabel and seismic data.
# Depends on whether sidelabel is on the left or right.
if cfg['sidelabel'] == 'right':
ssl = (ml + max(seismic_width) + mm) / w # Start of side label (ratio)
seismic_left = ml / w
else:
ssl = ml / w
seismic_left = (ml + wsl + mm) / w
adj = max(0, h - h_reqd) / 2
seismic_bottom = (mb / h) + adj / h
seismic_width_fraction = [sw / w for sw in seismic_width]
seismic_height_fraction = seismic_height_raw / h
# Publish some notices so user knows plot size.
Notice.info("plot width {:.2f} in".format(w))
Notice.info("plot height {:.2f} in".format(h))
# Make the figure.
fig = plt.figure(figsize=(w, h), facecolor='w')
# Set the tickformat.
tickfmt = mtick.FormatStrFormatter('%.0f')
# Could definitely do better for default fontsize than 10.
# Ideally would be adaptive to plot size.
cfg['fontsize'] = cfg['fontsize'] or 10
# Plot title.
if cfg['title']:
# Deal with Windows paths: \1 gets interpreted as a group by regex.
newt = re.sub(r'\\', '@@@@@', target)
temp = re.sub(r'_filename', newt, cfg['title'])
title = re.sub(r'@@@', r'\\', temp)
title_ax = fig.add_axes([ssl, 1 - mt / h, wsl / w, mt / h])
title_ax = plotter.plot_title(title_ax,
title,
fs=1.4 * cfg['fontsize'],
cfg=cfg)
# Plot title.
if cfg['subtitle']:
date = str(datetime.date.today())
subtitle = re.sub(r'_date', date, cfg['subtitle'])
subtitle_ax = fig.add_axes([ssl, 1 - mt / h, wsl / w, mt / h],
label='subtitle')
title_ax = plotter.plot_subtitle(subtitle_ax,
subtitle,
fs=0.75 * cfg['fontsize'],
cfg=cfg)
# Plot text header.
start = (h - 1.5 * mt - fhh) / h
head_ax = fig.add_axes([ssl, start, wsl / w, fhh / h])
head_ax = plotter.plot_header(head_ax,
s.header,
fs=9,
cfg=cfg,
version=__version__)
# Plot histogram.
# Params for histogram plot.
pady = 0.75 / h # 0.75 inch
padx = 0.75 / w # 0.75 inch
cstrip = 0.3 / h # color_strip height = 0.3 in
charth = 1.25 / h # height of charts = 1.25 in
chartw = wsl / w - mr / w - padx # or ml/w for left-hand sidelabel; same thing
chartx = (ssl + padx)
histy = 1.5 * mb / h + charth + pady
# Plot colourbar under histogram.
clrbar_ax = fig.add_axes([chartx, histy - cstrip, chartw, cstrip])
clrbar_ax = plotter.plot_colourbar(clrbar_ax, cmap=cfg['cmap'])
# Plot histogram itself.
hist_ax = fig.add_axes([chartx, histy, chartw, charth])
hist_ax = plotter.plot_histogram(hist_ax, s.data, tickfmt, cfg)
# Plot spectrum.
specy = 1.5 * mb / h
spec_ax = fig.add_axes([chartx, specy, chartw, charth])
try:
colour = utils.rgb_to_hex(cfg['highlight_colour'])
spec_ax = s.plot_spectrum(
ax=spec_ax,
tickfmt=tickfmt,
ntraces=20,
fontsize=cfg['fontsize'],
colour=colour,
)
except:
pass # No spectrum, oh well.
for i, line in enumerate(ss):
# Add the seismic axis.
ax = fig.add_axes([
seismic_left,
seismic_bottom + i * seismic_height_fraction + i * pady,
seismic_width_fraction[i], seismic_height_fraction
])
# Plot seismic data.
if cfg['display'].lower() in ['vd', 'varden', 'variable', 'both']:
im = ax.imshow(line.data.T,
cmap=cfg['cmap'],
clim=[-clip_val, clip_val],
extent=[
line.olineidx[0], line.olineidx[-1],
1000 * line.tbasis[-1], line.tbasis[0]
],
aspect='auto',
interpolation=cfg['interpolation'])
if np.argmin(seismic_width) == i:
cax = utils.add_subplot_axes(ax, [1.01, 0.02, 0.01, 0.2])
_ = plt.colorbar(im, cax=cax)
if cfg['display'].lower() in ['wiggle', 'both']:
ax = line.wiggle_plot(
cfg['number'],
direction,
ax=ax,
skip=cfg['skip'],
gain=cfg['gain'],
rgb=cfg['colour'],
alpha=cfg['opacity'],
lw=cfg['lineweight'],
)
valid = ['vd', 'varden', 'variable', 'wiggle', 'both']
if cfg['display'].lower() not in valid:
Notice.fail("You must specify the display: wiggle, vd, both.")
return
# Seismic axis annotations.
ax.set_ylabel(utils.LABELS[line.ylabel], fontsize=cfg['fontsize'])
ax.set_xlabel(utils.LABELS[line.xlabel],
fontsize=cfg['fontsize'],
ha='center')
ax.tick_params(axis='both', labelsize=cfg['fontsize'] - 2)
ax.xaxis.set_major_formatter(tickfmt)
ax.yaxis.set_major_formatter(tickfmt)
if ('tslice' not in direction):
ax.set_ylim(1000 * cfg['trange'][1] or 1000 * line.tbasis[-1],
1000 * cfg['trange'][0])
# Crossing point. Will only work for non-arb lines.
try:
ax.axvline(ss[i - 1].slineidx[0],
c=utils.rgb_to_hex(cfg['highlight_colour']),
alpha=0.5)
except IndexError:
pass # Nevermind.
# Grid, optional.
if cfg['grid_time'] or cfg['grid_traces']:
ax.grid()
for l in ax.get_xgridlines():
l.set_color(utils.rgb_to_hex(cfg['grid_colour']))
l.set_linestyle('-')
if cfg['grid_traces']:
l.set_linewidth(1)
else:
l.set_linewidth(0)
l.set_alpha(min(1, cfg['grid_alpha']))
for l in ax.get_ygridlines():
l.set_color(utils.rgb_to_hex(cfg['grid_colour']))
l.set_linestyle('-')
if cfg['grid_time']:
if 'tslice' in direction:
l.set_linewidth(1)
else:
l.set_linewidth(1.4)
else:
l.set_linewidth(0)
l.set_alpha(min(1, 2 * cfg['grid_alpha']))
# Watermark.
if cfg['watermark_text']:
ax = plotter.watermark_seismic(ax, cfg)
# Make parasitic (top) axis for labeling CDP number.
if (s.data.ndim > 2) and ('tslice' not in direction):
ylim = ax.get_ylim()
par1 = ax.twiny()
par1.spines["top"].set_position(("axes", 1.0))
par1.plot(line.slineidx, np.zeros_like(line.slineidx), alpha=0)
par1.set_xlabel(utils.LABELS[line.slabel],
fontsize=cfg['fontsize'])
par1.set_ylim(ylim)
# Adjust ticks
tx = par1.get_xticks()
newtx = [
line.slineidx[len(line.slineidx) * (i // len(tx))]
for i, _ in enumerate(tx)
]
par1.set_xticklabels(newtx, fontsize=cfg['fontsize'] - 2)
t2 = time.time()
Notice.ok("Built plot in {:.1f} s".format(t2 - t1))
#####################################################################
#
# SAVE FILE
#
#####################################################################
Notice.hr_header("Saving")
dname, fname, ext = utils.path_bits(target)
outfile = cfg['outfile'] or ''
if not os.path.splitext(outfile)[1]:
outfile = os.path.join(cfg['outfile'] or dname, fname + '.png')
fig.savefig(outfile)
t3 = time.time()
Notice.info("output file {}".format(outfile))
Notice.ok("Saved output in {:.1f} s".format(t3 - t2))
if cfg['stain_paper'] or cfg['coffee_rings'] or cfg['distort'] or cfg[
'scribble']:
fname = os.path.splitext(outfile)[0] + ".stupid.png"
fig.savefig(fname)
else:
return
#####################################################################
#
# SAVE STUPID FILE
#
#####################################################################
Notice.hr_header("Applying the stupidity")
stupid_image = Image.open(fname)
if cfg['stain_paper']:
utils.stain_paper(stupid_image)
utils.add_rings(stupid_image, cfg['coffee_rings'])
if cfg['scribble']:
utils.add_scribble(stupid_image)
# Trick to remove remaining semi-transparent pixels.
result = Image.new("RGB", stupid_image.size, (255, 255, 255))
result.paste(stupid_image)
result.save(fname)
t4 = time.time()
Notice.info("output file {}".format(fname))
Notice.ok("Saved stupidity in {:.1f} s".format(t4 - t3))
return
def main(target, cfg):
"""
Puts everything together.
"""
t0 = time.time()
# Read the file.
section = readSEGY(target, unpack_headers=True)
# Calculate some things.
# NB Getting nsamples and dt from the first trace assumes that all
# traces are the same length, which is not a safe assumption in SEGY v2.
ninlines = section.traces[-1].header.trace_sequence_number_within_line
last_tr = section.traces[-1].header.trace_sequence_number_within_segy_file
nxlines = last_tr / ninlines
nsamples = section.traces[0].header.number_of_samples_in_this_trace
dt = section.traces[0].header.sample_interval_in_ms_for_this_trace
ntraces = len(section.traces)
tbase = 0.001 * np.arange(0, nsamples * dt, dt)
tstart = 0
tend = np.amax(tbase)
# Make the data array.
data = np.vstack([t.data for t in section.traces]).T
threed = False
if nxlines > 1: # Then it's a 3D and `data` is an ensemble.
threed = True
cube = np.reshape(data.T, (ninlines, nxlines, nsamples))
l = cfg['number']
if cfg['direction'].lower()[0] == 'i':
direction = 'inline'
ntraces = nxlines
l *= ninlines if (l < 1) else 1
data = cube[l, :, :].T
else:
direction = 'xline'
ntraces = ninlines
l *= nxlines if (l < 1) else 1
data = cube[:, l, :].T
# Collect some other data. Use a for loop because there are several.
elev, esp, ens, tsq = [], [], [], []
for i, trace in enumerate(section.traces):
elev.append(trace.header.receiver_group_elevation)
esp.append(trace.header.energy_source_point_number)
tsq.append(trace.header.trace_sequence_number_within_line)
if threed:
trs = []
if direction == 'inline':
cdp_label_text = 'Crossline number'
trace_label_text = 'Trace number'
ens.append(trace.header.for_3d_poststack_data_this_field_is_for_cross_line_number)
trs.append(trace.header.for_3d_poststack_data_this_field_is_for_in_line_number)
else:
cdp_label_text = 'Inline number'
trace_label_text = 'Trace number'
ens.append(trace.header.for_3d_poststack_data_this_field_is_for_in_line_number)
trs.append(trace.header.for_3d_poststack_data_this_field_is_for_cross_line_number)
line_no = min(trs)
else:
cdp_label_text = 'CDP number'
trace_label_text = 'Trace number'
ens.append(trace.header.ensemble_number)
min_tr, max_tr = 0, ntraces
traces = (min_tr, max_tr)
clip_val = np.percentile(data, cfg['percentile'])
# Notify user of parameters
Notice.info("n_traces {}".format(ntraces))
Notice.info("n_samples {}".format(nsamples))
Notice.info("dt {}".format(dt))
Notice.info("t_start {}".format(tstart))
Notice.info("t_end {}".format(tend))
Notice.info("max_val {}".format(np.amax(data)))
Notice.info("min_val {}".format(np.amin(data)))
Notice.info("clip_val {}".format(clip_val))
t1 = time.time()
Notice.ok("Read data in {:.1f} s".format(t1-t0))
#####################################################################
#
# MAKE PLOT
#
#####################################################################
Notice.hr_header("Plotting")
##################################
# Plot size parameters
# Some constants
fs = cfg['fontsize']
wsl = 6 # Width of sidelabel, inches
mih = 12 # Minimum plot height, inches
fhh = 5 # File header box height, inches
m = 0.5 # basic unit of margins, inches
# Margins, CSS like: top, right, bottom, left.
mt, mr, mb, ml = m, 2 * m, m, 2 * m
mm = m # padded margin between seismic and label
# Width is determined by seismic width, plus sidelabel, plus margins.
seismic_width = ntraces / cfg['tpi']
w = ml + seismic_width + mm + wsl + mr # inches
# Height is given by ips, but with a minimum of mih inches
seismic_height = cfg['ips'] * (tbase[-1] - tbase[0]) / 1000
h_reqd = mb + seismic_height + mt # inches
h = max(mih, h_reqd)
# Calculate where to start sidelabel and seismic data.
# Depends on whether sidelabel is on the left or right.
if cfg['sidelabel'] == 'right':
ssl = (ml + seismic_width + mm) / w # Start of side label (ratio)
seismic_left = ml / w
else:
ssl = ml / w
seismic_left = (ml + wsl + mm) / w
adj = max(0, h - h_reqd) / 2
seismic_bottom = (mb / h) + adj / h
seismic_width_fraction = seismic_width / w
seismic_height_fraction = seismic_height / h
# Publish some notices so user knows plot size.
Notice.info("Width of plot {} in".format(w))
Notice.info("Height of plot {} in".format(h))
##################################
# Make the figure.
fig = plt.figure(figsize=(w, h), facecolor='w')
# Add the main seismic axis.
ax = fig.add_axes([seismic_left,
seismic_bottom,
seismic_width_fraction,
seismic_height_fraction
])
# make parasitic axes for labeling CDP number
par1 = ax.twiny()
par1.spines["top"].set_position(("axes", 1.0))
tickfmt = mtick.FormatStrFormatter('%.0f')
par1.plot(ens, np.zeros_like(ens))
par1.set_xlabel(cdp_label_text, fontsize=fs-2)
par1.set_xticklabels(par1.get_xticks(), fontsize=fs-2)
par1.xaxis.set_major_formatter(tickfmt)
# Plot title
title_ax = fig.add_axes([ssl, 1-mt/h, wsl/w, mt/(h)])
title_ax = plotter.plot_title(title_ax, target, fs=1.5*fs, cfg=cfg)
if threed:
title_ax.text(0.0, 0.0, '{} {}'.format(direction.title(), line_no))
# Plot text header.
s = section.textual_file_header.decode()
start = (h - 1.5*mt - fhh) / h
head_ax = fig.add_axes([ssl, start, wsl/w, fhh/h])
head_ax = plotter.plot_header(head_ax, s, fs=fs-1, cfg=cfg)
# Plot histogram.
# Params for histogram plot
pady = 0.75 / h # 0.75 inch
padx = 0.75 / w # 0.75 inch
cstrip = 0.3/h # color_strip height = 0.3 in
charth = 1.5/h # height of charts = 1.5 in
chartw = wsl/w - mr/w - padx # or ml/w for left-hand sidelabel; same thing
chartx = (ssl + padx)
histy = 1.5 * mb/h + charth + pady
# Plot colourbar under histogram
clrbar_ax = fig.add_axes([chartx, histy - cstrip, chartw, cstrip])
clrbar_ax = plotter.plot_colourbar(clrbar_ax, cmap=cfg['cmap'])
# Plot histogram itself
hist_ax = fig.add_axes([chartx, histy, chartw, charth])
hist_ax = plotter.plot_histogram(hist_ax,
data,
tickfmt,
percentile=cfg['percentile'],
fs=fs)
# Plot spectrum.
specy = 1.5 * mb/h
spec_ax = fig.add_axes([chartx, specy, chartw, charth])
try:
spec_ax = plotter.plot_spectrum(spec_ax,
data,
dt,
tickfmt,
ntraces=20,
fontsize=fs)
except:
pass
# Plot seismic data.
if cfg['display'].lower() in ['vd', 'varden', 'variable']:
_ = ax.imshow(data,
cmap=cfg['cmap'],
clim=[-clip_val, clip_val],
extent=[0, ntraces, tbase[-1], tbase[0]],
aspect='auto'
)
elif cfg['display'].lower() == 'wiggle':
ax = plotter.wiggle_plot(ax,
data,
tbase,
ntraces,
skip=cfg['skip'],
gain=cfg['gain'],
rgb=cfg['colour'],
alpha=cfg['opacity'],
lw=cfg['lineweight']
)
ax.set_ylim(ax.get_ylim()[::-1])
elif cfg['display'].lower() == 'both':
# variable density goes on first
_ = ax.imshow(data,
cmap=cfg['cmap'],
clim=[-clip_val, clip_val],
extent=[0, ntraces, tbase[-1], tbase[0]],
aspect='auto'
)
# wiggle plots go on top
ax = plotter.wiggle_plot(ax,
data,
tbase,
ntraces,
skip=cfg['skip'],
gain=cfg['gain'],
rgb=cfg['colour'],
alpha=cfg['opacity'],
lw=cfg['lineweight']
)
# ax.set_ylim(ax.get_ylim()[::-1])
else:
Notice.fail("You need to specify the type of display: wiggle or vd")
# Seismic axis annotations.
ax = plotter.decorate_seismic(ax, traces, trace_label_text, tickfmt, cfg)
# Watermark.
if cfg['watermark_text']:
Notice.info("Adding watermark")
ax = plotter.watermark_seismic(ax, cfg)
t2 = time.time()
Notice.ok("Built plot in {:.1f} s".format(t2-t1))
#####################################################################
#
# SAVE FILE
#
#####################################################################
Notice.hr_header("Saving")
if cfg['stain_paper'] or cfg['coffee_rings'] or cfg['distort'] or cfg['scribble']:
stupid = True
else:
stupid = False
s = "Saved image file {} in {:.1f} s"
if cfg['outfile']:
if os.path.isfile(cfg['outfile']):
outfile = cfg['outfile']
else: # is directory
stem, ext = os.path.splitext(os.path.split(target)[1])
outfile = os.path.join(cfg['outfile'], stem + '.png')
stem, _ = os.path.splitext(outfile) # Needed for stupidity.
fig.savefig(outfile)
t3 = time.time()
Notice.ok(s.format(outfile, t3-t2))
else: # Do the default: save a PNG in the same dir as the target.
stem, _ = os.path.splitext(target)
fig.savefig(stem)
t3 = time.time()
Notice.ok(s.format(stem+'.png', t3-t2))
if stupid:
fig.savefig(stem + ".stupid.png")
else:
return
#####################################################################
#
# SAVE STUPID FILE
#
#####################################################################
Notice.hr_header("Applying the stupidity")
stupid_image = Image.open(stem + ".stupid.png")
if cfg['stain_paper']:
utils.stain_paper(stupid_image)
utils.add_rings(stupid_image, cfg['coffee_rings'])
if cfg['scribble']:
utils.add_scribble(stupid_image)
stupid_image.save(stem + ".stupid.png")
s = "Saved stupid file stupid.png in {:.1f} s"
t4 = time.time()
Notice.ok(s.format(t4-t3))
return
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 main(target, cfg):
"""
Puts everything together.
"""
t0 = time.time()
# Read the file.
section = readSEGY(target, unpack_headers=True)
# Calculate some things
nsamples = section.traces[0].header.number_of_samples_in_this_trace
dt = section.traces[0].header.sample_interval_in_ms_for_this_trace
ntraces = len(section.traces)
tbase = 0.001 * np.arange(0, nsamples * dt, dt)
tstart = 0
tend = np.amax(tbase)
wsd = ntraces / cfg['tpi']
# Build the data container
elev, esp, ens, tsq = [], [], [], [] # energy source point number
data = np.zeros((nsamples, ntraces))
for i, trace in enumerate(section.traces):
data[:, i] = trace.data
elev.append(trace.header.receiver_group_elevation)
esp.append(trace.header.energy_source_point_number)
ens.append(trace.header.ensemble_number)
tsq.append(trace.header.trace_sequence_number_within_line)
clip_val = np.percentile(data, 99.0)
# Notify user of parameters
Notice.info("n_traces {}".format(ntraces))
Notice.info("n_samples {}".format(nsamples))
Notice.info("dt {}".format(dt))
Notice.info("t_start {}".format(tstart))
Notice.info("t_end {}".format(tend))
Notice.info("max_val {}".format(np.amax(data)))
Notice.info("min_val {}".format(np.amin(data)))
Notice.info("clip_val {}".format(clip_val))
t1 = time.time()
Notice.ok("Read data successfully in {:.1f} s".format(t1-t0))
#####################################################################
#
# MAKE PLOT
#
#####################################################################
Notice.hr_header("Plotting")
##################################
# Plot size parameters
# Some constants
wsl = 6 # Width of sidelabel
mih = 10 # Minimum plot height
fhh = 5 # File header height
m = 0.5 # margin in inches
# Margins, CSS like
mt, mb, ml, mr = m, m, 2 * m, 2 * m
mm = mr / 2 # padded margin between seismic and label
# Width is determined by tpi, plus a constant for the sidelabel, plus 1 in
w = ml + wsd + wsl + mr + mm
# Height is given by ips, but with a minimum of 8 inches, plus 1 in
h = max(mih, cfg['ips'] * (np.amax(tbase) - np.amin(tbase)) / 1000 + mt + mb)
# More settings
ssl = (ml + wsd + mm) / w # Start of side label (ratio)
fs = cfg['fontsize']
Notice.info("Width of plot {} in".format(w))
Notice.info("Height of plot {} in".format(h))
##################################
# Make the figure.
fig = plt.figure(figsize=(w, h), facecolor='w')
ax = fig.add_axes([ml / w, mb / h, wsd / w, (h - mb - mt) / h])
# make parasitic axes for labeling CDP number
par1 = ax.twiny()
par1.spines["top"].set_position(("axes", 1.0))
tickfmt = mtick.FormatStrFormatter('%.0f')
par1.plot(ens, np.zeros_like(ens))
par1.set_xlabel("CDP number", fontsize=fs-2)
par1.set_xticklabels(par1.get_xticks(), fontsize=fs-2)
par1.xaxis.set_major_formatter(tickfmt)
ax = wiggle_plot(ax,
data,
tbase,
ntraces,
skip=cfg['skip'],
gain=cfg['gain'],
rgb=cfg['colour'],
alpha=cfg['opacity'],
lw=cfg['lineweight']
)
ax = decorate_seismic(ax, ntraces, tickfmt, fs)
# Plot title
title_ax = fig.add_axes([ssl, 1-mt/h, wsl/w, mt/(2*h)])
title_ax = plot_title(title_ax, target, fs=fs)
# Plot text header.
s = str(section.textual_file_header)[2:-1]
start = (h - mt - fhh) / h
head_ax = fig.add_axes([ssl, start, wsl/w, fhh/h])
head_ax = plot_header(head_ax, s, fs)
# Plot histogram.
pad = 0.05
charty = 0.125 # height of chart
xhist = (ssl + pad)
whist = (1 - ssl - (ml/w)) - 2 * pad
hist_ax = fig.add_axes([xhist, 1.5 * mb/h + charty + pad, whist, charty])
hist_ax = plot_histogram(hist_ax, data, fs)
# Plot spectrum.
spec_ax = fig.add_axes([xhist, 1.5 * mb/h, whist, charty])
spec_ax = plot_spectrum(spec_ax, data, dt, fs)
t2 = time.time()
Notice.ok("Built plot in {:.1f} s".format(t2-t1))
#####################################################################
#
# SAVE FILE
#
#####################################################################
Notice.hr_header("Saving")
s = "Saved image file {} in {:.1f} s"
if cfg['outfile']:
fig.savefig(cfg['outfile'])
t3 = time.time()
Notice.ok(s.format(cfg['outfile'], t3-t2))
else:
stem, _ = os.path.splitext(target)
fig.savefig(stem)
t3 = time.time()
Notice.ok(s.format(stem+'.png', t3-t2))
return
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 main(target, cfg):
"""
Puts everything together.
"""
t0 = time.time()
#####################################################################
#
# READ SEGY
#
#####################################################################
s = Seismic.from_segy(target, params={'ndim': cfg['ndim']})
# Set the line and/or xline number.
try:
n, xl = cfg['number']
except:
n, xl = cfg['number'], 0.5
# Set the direction.
if (s.ndim) == 2:
direction = ['inline']
elif cfg['direction'].lower()[0] == 'i':
direction = ['inline']
elif cfg['direction'].lower()[0] == 'x':
direction = ['xline']
elif cfg['direction'].lower()[0] == 't':
direction = ['tslice']
else:
direction = ['inline', 'xline']
# Get the data.
ss = [Seismic.from_seismic(s, n=n, direction=d) for n, d in zip((n, xl), direction)]
data = [s.data for s in ss]
clip_val = np.percentile(s.data, cfg['percentile'])
# Notify user of parameters.
Notice.info("n_traces {}".format(s.ntraces))
Notice.info("n_samples {}".format(s.nsamples))
Notice.info("dt {}".format(s.dt))
Notice.info("t_start {}".format(s.tstart))
Notice.info("t_end {}".format(s.tend))
Notice.info("max_val {:.3f}".format(np.amax(s.data)))
Notice.info("min_val {:.3f}".format(np.amin(s.data)))
Notice.info("clip_val {:.3f}".format(clip_val))
t1 = time.time()
Notice.ok("Read data in {:.1f} s".format(t1-t0))
#####################################################################
#
# MAKE PLOT
#
#####################################################################
Notice.hr_header("Plotting")
# Plot size parameters.
fs = cfg['fontsize']
wsl = 6 # Width of sidelabel, inches
mih = 12 # Minimum plot height, inches
fhh = 5 # File header box height, inches
m = 0.5 # basic unit of margins, inches
# Margins, CSS like: top, right, bottom, left.
mt, mr, mb, ml = m, 2 * m, m, 2 * m
mm = m # padded margin between seismic and label
# Width is determined by seismic width, plus sidelabel, plus margins.
# Height is given by ips, but with a minimum of mih inches.
if 'tslice' in direction:
print('doing tslice')
seismic_width = max([s.ninlines for s in ss]) / cfg['tpi']
seismic_height_raw = max([s.nxlines for s in ss]) / cfg['tpi']
print(seismic_width, seismic_height_raw)
else:
seismic_width = max([s.ntraces for s in ss]) / cfg['tpi']
seismic_height_raw = cfg['ips'] * (s.tbasis[-1] - s.tbasis[0])
w = ml + seismic_width + mm + wsl + mr # inches
seismic_height = len(ss) * seismic_height_raw
h_reqd = mb + seismic_height + 0.75*(len(ss)-1) + mt # inches
h = max(mih, h_reqd)
# Calculate where to start sidelabel and seismic data.
# Depends on whether sidelabel is on the left or right.
if cfg['sidelabel'] == 'right':
ssl = (ml + seismic_width + mm) / w # Start of side label (ratio)
seismic_left = ml / w
else:
ssl = ml / w
seismic_left = (ml + wsl + mm) / w
adj = max(0, h - h_reqd) / 2
seismic_bottom = (mb / h) + adj / h
seismic_width_fraction = seismic_width / w
seismic_height_fraction = seismic_height_raw / h
# Publish some notices so user knows plot size.
Notice.info("Width of plot {} in".format(w))
Notice.info("Height of plot {} in".format(h))
# Make the figure.
fig = plt.figure(figsize=(w, h), facecolor='w')
# Set the tickformat.
tickfmt = mtick.FormatStrFormatter('%.0f')
# Plot title.
if cfg['filename']:
title_ax = fig.add_axes([ssl, 1-mt/h, wsl/w, mt/h])
title_ax = plotter.plot_title(title_ax, target, fs=1.5*fs, cfg=cfg)
# Plot text header.
start = (h - 1.5*mt - fhh) / h
head_ax = fig.add_axes([ssl, start, wsl/w, fhh/h])
head_ax = plotter.plot_header(head_ax, s.header, fs=fs-1, cfg=cfg)
# Plot histogram.
# Params for histogram plot.
pady = 0.75 / h # 0.75 inch
padx = 0.75 / w # 0.75 inch
cstrip = 0.3/h # color_strip height = 0.3 in
charth = 1.5/h # height of charts = 1.5 in
chartw = wsl/w - mr/w - padx # or ml/w for left-hand sidelabel; same thing
chartx = (ssl + padx)
histy = 1.5 * mb/h + charth + pady
# Plot colourbar under histogram.
clrbar_ax = fig.add_axes([chartx, histy - cstrip, chartw, cstrip])
clrbar_ax = plotter.plot_colourbar(clrbar_ax, cmap=cfg['cmap'])
# Plot histogram itself.
hist_ax = fig.add_axes([chartx, histy, chartw, charth])
hist_ax = plotter.plot_histogram(hist_ax,
s.data,
tickfmt,
percentile=cfg['percentile'],
fs=fs)
# Plot spectrum.
specy = 1.5 * mb/h
spec_ax = fig.add_axes([chartx, specy, chartw, charth])
try:
spec_ax = s.plot_spectrum(ax=spec_ax,
tickfmt=tickfmt,
ntraces=20,
fontsize=fs)
except:
pass
for i, line in enumerate(ss):
# Add the seismic axis.
ax = fig.add_axes([seismic_left,
seismic_bottom + i*seismic_height_fraction + i*pady,
seismic_width_fraction,
seismic_height_fraction
])
# Plot seismic data.
if cfg['display'].lower() in ['vd', 'varden', 'variable', 'both']:
_ = ax.imshow(line.data.T,
cmap=cfg['cmap'],
clim=[-clip_val, clip_val],
extent=[0,
line.ntraces,
1000*line.tbasis[-1],
line.tbasis[0]],
aspect='auto'
)
# This does not work: should cut off line at cfg['tmax']
# ax.set_ylim(1000*cfg['tmax'] or 1000*line.tbasis[-1], line.tbasis[0])
if cfg['display'].lower() in ['wiggle', 'both']:
ax = line.wiggle_plot(cfg['number'], direction,
ax=ax,
skip=cfg['skip'],
gain=cfg['gain'],
rgb=cfg['colour'],
alpha=cfg['opacity'],
lw=cfg['lineweight'],
tmax=cfg['tmax'],
)
if cfg['display'].lower() not in ['vd', 'varden', 'variable', 'wiggle', 'both']:
Notice.fail("You must specify the type of display: wiggle, vd, both.")
return
# Seismic axis annotations.
fs = cfg['fontsize'] - 2
ax.set_xlim([0, line.data.shape[0]])
ax.set_ylabel(line.ylabel, fontsize=fs)
ax.set_xlabel(line.xlabel, fontsize=fs, horizontalalignment='center')
ax.set_xticklabels(ax.get_xticks(), fontsize=fs)
ax.set_yticklabels(ax.get_yticks(), fontsize=fs)
ax.xaxis.set_major_formatter(tickfmt)
ax.yaxis.set_major_formatter(tickfmt)
# Watermark.
if cfg['watermark_text']:
ax = plotter.watermark_seismic(ax, cfg)
# Make parasitic axes for labeling CDP number.
par1 = ax.twiny()
par1.spines["top"].set_position(("axes", 1.0))
par1.plot(s.xlines, np.zeros_like(s.xlines))
par1.set_xlabel(line.xlabel, fontsize=fs)
par1.set_xticklabels(par1.get_xticks(), fontsize=fs)
par1.xaxis.set_major_formatter(tickfmt)
t2 = time.time()
Notice.ok("Built plot in {:.1f} s".format(t2-t1))
#####################################################################
#
# SAVE FILE
#
#####################################################################
Notice.hr_header("Saving")
dname, fname, ext = utils.path_bits(target)
outfile = cfg['outfile'] or ''
if not os.path.splitext(outfile)[1]:
outfile = os.path.join(cfg['outfile'] or dname, fname + '.png')
fig.savefig(outfile)
t3 = time.time()
Notice.ok("Saved image file {} in {:.1f} s".format(outfile, t3-t2))
if cfg['stain_paper'] or cfg['coffee_rings'] or cfg['distort'] or cfg['scribble']:
fname = os.path.splitext(outfile)[0] + ".stupid.png"
fig.savefig(fname)
else:
return
#####################################################################
#
# SAVE STUPID FILE
#
#####################################################################
Notice.hr_header("Applying the stupidity")
stupid_image = Image.open(fname)
if cfg['stain_paper']: utils.stain_paper(stupid_image)
utils.add_rings(stupid_image, cfg['coffee_rings'])
if cfg['scribble']: utils.add_scribble(stupid_image)
stupid_image.save(fname)
t4 = time.time()
Notice.ok("Saved stupid file {} in {:.1f} s".format(fname, t4-t3))
return
