def test_segyiotests_writer_from_ds(temp_dir, segyio3d_test_files, il_chunks):
file, segyio_kwargs = segyio3d_test_files
ds = segy_loader(str(file), silent=True, **segyio_kwargs)
outfile = temp_dir / file.name
segy_writer(ds, outfile, il_chunks=il_chunks)
del ds
ds = segy_loader(str(outfile), silent=True, **well_known_byte_locs("standard_3d"))
assert isinstance(ds, xr.Dataset)
def test_segyiotests_writer_from_seisnc(temp_dir, segyio3d_test_files):
file, segyio_kwargs = segyio3d_test_files
seisnc = temp_dir / file.with_suffix(".siesnc").name
segy_converter(str(file), ncfile=seisnc, silent=True, **segyio_kwargs)
outfile = temp_dir / file.name
segy_writer(seisnc, outfile)
ds = segy_loader(str(outfile), silent=True, **well_known_byte_locs("standard_3d"))
assert isinstance(ds, xr.Dataset)
def test_segyiotests_2ds_wheaderscrap(segyio3d_test_files):
file, segyio_kwargs = segyio3d_test_files
scrape_args = dict()
try:
scrape_args["endian"] = segyio_kwargs["endian"]
except KeyError:
pass
header = segy_header_scrape(str(file), silent=True, **scrape_args)
ds = segy_loader(str(file), silent=True, **segyio_kwargs, head_df=header)
assert isinstance(ds, xr.Dataset)
def test_seisnc_return(temp_dir, empty):
dims = list(empty.dims)
shp = [empty.dims[d] for d in dims]
domain = empty.d3_domain
empty["data"] = (dims, np.zeros(shp))
if "offset" in empty:
empty["offset"] = empty["offset"].astype(np.int32)
segy_writer(empty, temp_dir / "temp_empty.segy")
back = segy_loader(temp_dir / "temp_empty.segy", vert_domain=domain)
assert empty == back
def convert(output_file, input_file, iline, xline, crop, output_type):
input_file = pathlib.Path(input_file)
if output_type is None and output_file is not None:
output_type = guess_file_type(output_file)
elif output_type is None and output_file is None:
"""Because currently only one conversion exists we can guess the output from the input"""
input_type = guess_file_type(input_file)
if input_type:
output_type = "SEGY" if input_type == "NETCDF" else "NETCDF"
if output_type is None:
click.echo(
"Output type not recognised! Please provide the desired output file type explicitly using the --output-type option"
)
raise SystemExit
click.echo(f"Converting file {input_file.name} to {output_type}")
if len(crop) == 0:
crop = None
if output_type == "NETCDF":
if output_file is None:
output_file = input_file.stem + ".SEISNC"
_ = segy_loader(input_file,
ncfile=output_file,
iline=iline,
xline=xline,
ix_crop=crop)
click.echo(f"Converted file saved as {output_file}")
LOGGER.info(f"NetCDF output written to {output_file}")
elif output_type == "SEGY":
if output_file is None:
output_file = input_file.stem + ".segy"
ncdf2segy(input_file, output_file, iline=iline, xline=xline)
click.echo(f"Converted file saved as {output_file}")
LOGGER.info(f"SEGY output written to {output_file}")
else:
click.echo(
f"Conversion to output-type {output_type} is not implemented yet")
raise SystemExit
def main():
# how to track down warnings
#import warnings
#warnings.filterwarnings('error', category=UnicodeWarning)
#warnings.filterwarnings('error', category=DeprecationWarning, module='numpy')
#parse args
sys_parser = segysakArgsParser()
args = sys_parser.parse_args()
# gaffe
print(f'SEGY-SAK - v{version}')
# initialise logging
LOGGER.info(f'segysak v{version}')
# check inputs
checked_files = check_file(args.files)
# Generate or Load Configuration File
for input_file in checked_files:
print(input_file.name)
# Print EBCIDC header
if args.ebcidc:
try:
print(get_segy_texthead(input_file))
except IOError:
LOGGER.error(
"Input SEGY file was not found - check name and path")
if args.scan > 0:
hscan, nscan = segy_header_scan(input_file,
max_traces_scan=args.scan)
width = 10
print(f'Traces scanned: {nscan}')
print("{:>40s} {:>8s} {:>10s} {:>10s}".format(
'Item', 'Byte Loc', 'Min', 'Max'))
for key, item in hscan.items():
print("{:>40s} {:>8d} {:>10.0f} {:>10.0f}".format(
key, item[0], item[1], item[2]))
iline = args.iline
xline = args.xline
if args.netCDF is None or args.netCDF is not False:
if args.netCDF is None:
outfile = input_file.stem + '.SEISNC'
else:
outfile = args.netCDF
_ = segy_loader(input_file,
ncfile=outfile,
iline=iline,
xline=xline,
ix_crop=args.crop)
LOGGER.info(f"NetCDF output written to {outfile}")
if args.SEGY is None or args.SEGY is not False:
if args.SEGY is None:
outfile = input_file.stem + '.segy'
else:
outfile = args.SEGY
ncdf2segy(input_file, outfile, iline=iline,
xline=xline) #, crop=args.crop)
LOGGER.info(f"SEGY output written to {outfile}")
def test_segyiotests_ps_2ds(segyio3dps_test_files):
file, segyio_kwargs = segyio3dps_test_files
ds = segy_loader(str(file), silent=True, **segyio_kwargs)
assert isinstance(ds, xr.Dataset)
scrape
# %% [markdown]
# ## Load SEG-Y data
# %% [markdown]
# All SEGY (2D, 2D gathers, 3D & 3D gathers) are ingested into `xarray.Dataset` objects through the
# `segy_loader` function. It is best to be explicit about the byte locations of key information but
# `segy_loader` can attempt to guess the shape of your dataset. Some standard byte positions are
# defined in the `well_known_bytes` function and others can be added via pull requests to the Github
# repository if desired.
# %%
from segysak.segy import segy_loader, well_known_byte_locs
V3D = segy_loader(V3D_path, iline=189, xline=193, cdpx=73, cdpy=77, vert_domain="TWT")
V3D
# %% [markdown]
# ## Visualising data
#
# `xarray` objects use smart label based indexing techniques to retreive subsets of data. More
# details on `xarray` techniques for *segysak* are covered in the examples, but this demonstrates
# a general syntax for selecting data by label with `xarray`. Plottnig is done by `matploblib` and
# `xarray` selections can be passed to normal `matplotlib.pyplot` functions.
# %%
fig, ax1 = plt.subplots(ncols=1, figsize=(15, 8))
iline_sel = 10093
V3D.data.transpose("twt", "iline", "xline", transpose_coords=True).sel(
iline=iline_sel
def test_segyiotests_nohead_2ncdf(temp_dir, segyio_nohead_test_files):
file, segyio_kwargs = segyio_nohead_test_files
seisnc = temp_dir / file.with_suffix(".siesnc").name
ds = segy_loader(str(file), ncfile=seisnc, silent=True, **segyio_kwargs)
assert isinstance(ds, xr.Dataset)
