def _render_surface(
surfacepath,
surface_type,
gridparameter,
color_values,
hillshade,
):
surface = xtgeo.surface_from_file(get_path(surfacepath))
min_val = None
max_val = None
if surface_type == "attribute":
min_val = color_values[0] if color_values else None
max_val = color_values[1] if color_values else None
grid = load_grid(get_path(self.gridfile))
gridparameter = load_grid_parameter(grid,
get_path(gridparameter))
surface.slice_grid3d(grid, gridparameter)
return [
SurfaceLeafletModel(
surface,
name="surface",
clip_min=min_val,
clip_max=max_val,
apply_shading=hillshade.get("value", False),
).layer
]
def _render_fence(coords, gridparameter, surfacepath, color_values,
colorscale):
if not coords:
raise PreventUpdate
grid = load_grid(get_path(self.gridfile))
gridparameter = load_grid_parameter(grid, get_path(gridparameter))
fence = get_fencespec(coords)
hmin, hmax, vmin, vmax, values = grid.get_randomline(
fence, gridparameter, zincrement=0.5)
surface = xtgeo.surface_from_file(get_path(surfacepath))
s_arr = get_surface_fence(fence, surface)
return make_heatmap(
values,
s_arr=s_arr,
theme=self.plotly_theme,
s_name=self.surfacenames[self.surfacefiles.index(surfacepath)],
colorscale=colorscale,
xmin=hmin,
xmax=hmax,
ymin=vmin,
ymax=vmax,
zmin=color_values[0],
zmax=color_values[1],
xaxis_title="Distance along polyline",
yaxis_title=self.zunit,
)
def _render_fence(coords, cubepath, surfacepath, color_values,
colorscale):
if not coords:
raise PreventUpdate
cube = load_cube_data(get_path(cubepath))
fence = get_fencespec(coords)
hmin, hmax, vmin, vmax, values = cube.get_randomline(fence)
surface = xtgeo.surface_from_file(get_path(surfacepath))
s_arr = get_surface_fence(fence, surface)
return make_heatmap(
values,
s_arr=s_arr,
theme=self.plotly_theme,
s_name=self.surfacenames[self.surfacefiles.index(surfacepath)],
colorscale=colorscale,
xmin=hmin,
xmax=hmax,
ymin=vmin,
ymax=vmax,
zmin=color_values[0],
zmax=color_values[1],
xaxis_title="Distance along polyline",
yaxis_title=self.zunit,
)
def sum_running_stats_bytestream():
"""Find avg per realisation and do a cumulative rolling mean.
Memory consumption shall be very low.
"""
for irel in range(NRUN):
# load as Eclipse run; this will look for EGRID, INIT, UNRST
print("Loading realization no {}".format(irel))
with open(EXPATH1, "rb") as myfile:
stream = io.BytesIO(myfile.read())
srf = xtgeo.surface_from_file(stream, fformat="irap_binary")
nnum = float(irel + 1)
srf.values += irel * 1 # just to mimic variability
if irel == 0:
pcum = srf.values1d
else:
pavg = srf.values1d / nnum
pcum = pcum * (nnum - 1) / nnum
pcum = npma.vstack([pcum, pavg])
pcum = pcum.sum(axis=0)
# find the averages:
print(pcum)
print(pcum.mean())
return pcum.mean()
def get_realization_surface(
self,
name: str,
attribute: str,
realization: int,
date: Optional[str] = None) -> xtgeo.RegularSurface:
"""Returns a Xtgeo surface instance of a single realization surface"""
columns = ["name", "attribute", "REAL"]
column_values = [name, attribute, realization]
if date is not None:
columns.append("date")
column_values.append(date)
df = self._filter_surface_table(name=name,
attribute=attribute,
date=date,
realizations=[int(realization)])
if len(df.index) == 0:
warnings.warn(
f"No surface found for name: {name}, attribute: {attribute}, date: {date}, "
f"realization: {realization}")
return xtgeo.RegularSurface(ncol=1, nrow=1, xinc=1,
yinc=1) # 1's as input is required
if len(df.index) > 1:
warnings.warn(
f"Multiple surfaces found for name: {name}, attribute: {attribute}, date: {date}, "
f"realization: {realization}. Returning first surface")
return xtgeo.surface_from_file(
get_stored_surface_path(df.iloc[0]["path"]))
def _get_observed_surface(
self, address: ObservedSurfaceAddress
) -> Optional[xtgeo.RegularSurface]:
"""Returns a Xtgeo surface instance for an observed surface"""
timer = PerfTimer()
surf_fns: List[str] = self._locate_observed_surfaces(
attribute=address.attribute,
name=address.name,
datestr=address.datestr if address.datestr is not None else "",
)
if len(surf_fns) == 0:
LOGGER.warning(f"No observed surface found for {address}")
return None
if len(surf_fns) > 1:
LOGGER.warning(
f"Multiple observed surfaces found for: {address}"
"Returning first surface."
)
surf = xtgeo.surface_from_file(surf_fns[0])
LOGGER.debug(f"Loaded simulated surface in: {timer.elapsed_s():.2f}s")
return surf
def fixture_create_project():
"""Create a tmp RMS project for testing, populate with basic data.
After the yield command, the teardown phase will remove the tmp RMS project.
"""
prj1 = str(PRJ)
print("\n******** Setup RMS project!\n")
if isdir(prj1):
print("Remove existing project! (1)")
shutil.rmtree(prj1)
project = roxar.Project.create()
rox = xtgeo.RoxUtils(project)
print("Roxar version is", rox.roxversion)
print("RMS version is", rox.rmsversion(rox.roxversion))
assert "1." in rox.roxversion
for wfile in WELLS1:
wobj = xtgeo.well_from_file(WELLSFOLDER1 / wfile)
if "XP_with" in wfile:
wobj.name = "OP2_w_repeat"
wobj.to_roxar(project,
wobj.name,
logrun="log",
trajectory="My trajectory")
# populate with cube data
cube = xtgeo.cube_from_file(CUBEDATA1)
cube.to_roxar(project, CUBENAME1, domain="depth")
# populate with surface data
rox.create_horizons_category(SURFCAT1)
for num, name in enumerate(SURFNAMES1):
srf = xtgeo.surface_from_file(SURFTOPS1[num])
project.horizons.create(name, roxar.HorizonType.interpreted)
srf.to_roxar(project, name, SURFCAT1)
# populate with grid and props
grd = xtgeo.grid_from_file(GRIDDATA1)
grd.to_roxar(project, GRIDNAME1)
por = xtgeo.gridproperty_from_file(PORODATA1, name=PORONAME1)
por.to_roxar(project, GRIDNAME1, PORONAME1)
zon = xtgeo.gridproperty_from_file(ZONEDATA1, name=ZONENAME1)
zon.values = zon.values.astype(np.uint8)
zon.to_roxar(project, GRIDNAME1, ZONENAME1)
# save project (both an initla version and a work version) and exit
project.save_as(prj1)
project.close()
yield project
print("\n******* Teardown RMS project!\n")
if isdir(prj1):
print("Remove existing project! (1)")
shutil.rmtree(prj1)
def _get_regsurff(i):
logger.info("Start %s", i)
sfile = TESTFILE
logger.info("File is %s", sfile)
rf = xtgeo.surface_from_file(sfile)
logger.info("End %s", i)
return rf
def surface_from_zone_prop(surface_table: pd.DataFrame, zone: str, prop: str,
ensemble: str, stype: str) -> xtgeo.RegularSurface:
df = surface_table[(surface_table["zone"] == zone)
& (surface_table["prop"] == prop)
& (surface_table["ensemble"] == ensemble)
& (surface_table["statistic"] == stype)]
if df.empty or len(df["path"].unique()) > 1:
return make_undefined_surface()
path = get_path(pathlib.Path(df["path"].unique()[0]))
return xtgeo.surface_from_file(path.resolve())
def _get_regsurfi(i):
logger.info("Start %s", i)
sfile = TESTFILE
with open(sfile, "rb") as fin:
stream = io.BytesIO(fin.read())
logger.info("File is %s", sfile)
rf = xtgeo.surface_from_file(stream, fformat="irap_binary")
logger.info("End %s", i)
return rf
def append(self, slist):
"""Append surfaces from either a list of RegularSurface objects,
a list of files, or a mix."""
for item in slist:
if isinstance(item, xtgeo.RegularSurface):
self._surfaces.append(item)
else:
try:
sobj = xtgeo.surface_from_file(item, fformat="guess")
self._surfaces.append(sobj)
except OSError:
xtg.warnuser("Cannot read as file, skip: {}".format(item))
def surface_to_json(surfacepath: Path) -> str:
surface = xtgeo.surface_from_file(str(surfacepath), fformat="irap_binary")
return json.dumps({
"ncol": surface.ncol,
"nrow": surface.nrow,
"xori": surface.xori,
"yori": surface.yori,
"rotation": surface.rotation,
"xinc": surface.xinc,
"yinc": surface.yinc,
"values": surface.values.copy().filled(np.nan).tolist(),
})
def fetch(
self, address: StatisticalSurfaceAddress
) -> Optional[xtgeo.RegularSurface]:
full_surf_path = self.cache_dir / _compose_stat_surf_file_name(
address, FILE_EXTENSION)
try:
surf = xtgeo.surface_from_file(full_surf_path,
fformat=FILE_FORMAT_READ)
return surf
# pylint: disable=bare-except
except:
return None
def first_surface_geometry(self) -> Dict:
surface = xtgeo.surface_from_file(
get_stored_surface_path(self._surface_table.iloc[0]["path"]))
return {
"xmin": surface.xmin,
"xmax": surface.xmax,
"ymin": surface.ymin,
"ymax": surface.ymax,
"xori": surface.xori,
"yori": surface.yori,
"ncol": surface.ncol,
"nrow": surface.nrow,
"xinc": surface.xinc,
"yinc": surface.yinc,
}
def surface_from_zone_prop(
parent, zone: str, prop: str, ensemble: str, stype: str
) -> dict:
path = get_surface_path(
ens_path=parent.surface_folders[ensemble],
statistic=stype,
zone=zone,
prop=prop,
)
try:
return xtgeo.surface_from_file(path.resolve())
except OSError:
surf = xtgeo.RegularSurface()
surf.values = 0
return surf
def test_regsurf_aggregated_diffdata(fmurun_w_casemetadata, rmsglobalconfig, regsurf):
"""Test surfaces, where input is diffdata."""
logger.info("Active folder is %s", fmurun_w_casemetadata)
os.chdir(fmurun_w_casemetadata)
edata = dataio.ExportData(
config=rmsglobalconfig, # read from global config
)
aggs = []
# create "forward" files
for i in range(10):
use_regsurf = regsurf.copy()
use_regsurf.values += float(i)
expfile = edata.export(
use_regsurf,
name="mymap_" + str(i),
realization=i,
timedata=[[20300201], [19990204]],
)
aggs.append(expfile)
# next task is to do an aggradation, and now the metadata already exists
# per input element which shall be re-used
surfs = xtgeo.Surfaces()
metas = []
for mapfile in aggs:
surf = xtgeo.surface_from_file(mapfile)
meta = dataio.read_metadata(mapfile)
metas.append(meta)
surfs.append([surf])
aggregated = surfs.statistics()
logger.info("Aggr. mean is %s", aggregated["mean"].values.mean()) # shall be 1238.5
aggdata = dataio.AggregatedData(
configs=metas,
operation="mean",
name="myaggrd",
verbosity="INFO",
aggregation_id="789politipoliti",
)
newmeta = aggdata.generate_aggregation_metadata(aggregated["mean"])
logger.info("New metadata:\n%s", utils.prettyprint_dict(newmeta))
def surface_from_zone_prop(parent: "PropertyStatistics", zone: str, prop: str,
ensemble: str, stype: str) -> xtgeo.RegularSurface:
if not isinstance(parent.surface_folders, dict):
raise TypeError("parent.surface_folders must be of type dict")
path = get_surface_path(
ens_path=parent.surface_folders[ensemble],
statistic=stype,
zone=zone,
prop=prop,
)
try:
return xtgeo.surface_from_file(path.resolve())
except OSError:
surf = xtgeo.RegularSurface()
surf.values = 0
return surf
def test_create_project():
"""Create a tmp RMS project for testing, populate with basic data"""
prj1 = PRJ
prj2 = PRJ + "_initial"
if isdir(prj1):
print("Remove existing project! (1)")
shutil.rmtree(prj1)
if isdir(prj2):
print("Remove existing project! (2)")
shutil.rmtree(prj2)
project = roxar.Project.create()
rox = xtgeo.RoxUtils(project)
print("Roxar version is", rox.roxversion)
print("RMS version is", rox.rmsversion(rox.roxversion))
assert "1." in rox.roxversion
# populate with cube data
cube = xtgeo.cube_from_file(CUBEDATA1)
cube.to_roxar(project, CUBENAME1, domain="depth")
# populate with surface data
rox.create_horizons_category(SURFCAT1)
for num, name in enumerate(SURFNAMES1):
srf = xtgeo.surface_from_file(SURFTOPS1[num])
project.horizons.create(name, roxar.HorizonType.interpreted)
srf.to_roxar(project, name, SURFCAT1)
# populate with grid and props
grd = xtgeo.grid_from_file(GRIDDATA1)
grd.to_roxar(project, GRIDNAME1)
por = xtgeo.gridproperty_from_file(PORODATA1, name=PORONAME1)
por.to_roxar(project, GRIDNAME1, PORONAME1)
# populate with well data (postponed)
# save project (both an initla version and a work version) and exit
project.save_as(prj1)
project.save_as(prj2)
project.close()
def test_dataframe_simple():
"""Get a pandas Dataframe object"""
xmap = xtgeo.RegularSurface(TESTSET1)
dfrc = xmap.dataframe(ijcolumns=True, order="C", activeonly=True)
tsetup.assert_almostequal(dfrc["X_UTME"][2], 465956.274, 0.01)
xmap = xtgeo.surface_from_file(TESTSET2)
dfrc = xmap.dataframe()
tsetup.assert_almostequal(dfrc["X_UTME"][2], 461582.562498, 0.01)
xmap.coarsen(2)
dfrc = xmap.dataframe()
tsetup.assert_almostequal(dfrc["X_UTME"][2], 461577.5575, 0.01)
def slice_a_cube_with_surface():
"""Slice a seismic cube with a surface on OW dat/map format"""
cubefile = EXPATH1 / "ib_test_cube2.segy"
surfacefile = EXPATH2 / "h1.dat"
mycube = xtgeo.cube_from_file(cubefile)
# import map/dat surface using cube as template (inline/xline
# must match)
mysurf = xtgeo.surface_from_file(surfacefile,
fformat="ijxyz",
template=mycube)
# sample cube values to mysurf (replacing current depth values)
mysurf.slice_cube(mycube, sampling="trilinear")
# export result
mysurf.to_file(TMPDIR / "slice.dat", fformat="ijxyz")
def test_integration_values(values_flag, expected_result):
result = xtgeo.surface_from_file(
StringIO("""! Example 2x2 grid
@zmap_example.zmap HEADER , GRID, 5
15, -99999.0000, , 4, 1
2, 2, 1.0000, 2.0000, 1.0000, 2.0000
0.0000, 0.0000, 0.0000
@
+ Grid data starts after this line
1.0000 2.0000 3.0000 4.0000
"""),
fformat="zmap",
values=values_flag,
)
assert result.xmax == 2.0
assert result.ymax == 2.0
assert result.xinc == 1.0
assert result.yinc == 1.0
assert list(result.values.data.flatten()) == expected_result
def test_bytesio_string_encoded():
"""Test a case where the string is encoded, then decoded"""
with open(TESTSET1, "rb") as fin:
stream = io.BytesIO(fin.read())
mystream = stream.read()
# this mimics data from a browser that are base64 encoded
encodedstream = base64.urlsafe_b64encode(mystream).decode("utf-8")
assert isinstance(encodedstream, str)
# now decode this and read
decodedstream = base64.urlsafe_b64decode(encodedstream)
assert isinstance(decodedstream, bytes)
content_string = io.BytesIO(decodedstream)
xsurf = xtgeo.surface_from_file(content_string, fformat="irap_binary")
assert xsurf.ncol == 554
assert xsurf.nrow == 451
def main():
"""Exporting maps from clipboard"""
surf = xtgeo.surface_from_file(INPUT_FOLDER / FILE)
print(f"Average value of map is {surf.values.mean()}")
ed = dataio.ExportData(
config=CFG,
name="noname_here",
unit="fraction",
vertical_domain={"depth": "msl"},
content="property",
timedata=None,
is_prediction=True,
is_observation=False,
tagname="average_poro",
workflow="rms property model",
)
fname = ed.export(surf, name="all") # note that 'name' here will be used
print(f"File name is {fname}")
def _render_surface(surfacepath, surface_type, cubepath, color_values,
hillshade):
surface = xtgeo.surface_from_file(get_path(surfacepath))
min_val = None
max_val = None
if surface_type == "attribute":
min_val = color_values[0] if color_values else None
max_val = color_values[1] if color_values else None
cube = load_cube_data(get_path(cubepath))
surface.slice_cube(cube)
return [
SurfaceLeafletModel(
surface,
name="surface",
clip_min=min_val,
clip_max=max_val,
apply_shading=hillshade.get("value", False),
).layer
]
def attribute_around_surface_symmetric():
"""Get atttribute around a surface (symmetric)"""
cubefile = EXPATH1 / "ib_test_cube2.segy"
surfacefile = EXPATH2 / "h1.dat"
mycube = xtgeo.cube_from_file(cubefile)
mysurf = xtgeo.surface_from_file(surfacefile,
fformat="ijxyz",
template=mycube)
attrs = ["max", "mean"]
myattrs = mysurf.slice_cube_window(mycube,
attribute=attrs,
sampling="trilinear",
zrange=10.0)
for attr in myattrs.keys():
myattrs[attr].to_file(TMPDIR / ("myfile_symmetric_" + attr + ".dat"),
fformat="ijxyz")
def _render_fence(coords, gridparameter, surfacepath, color_values,
colorscale):
if not coords:
raise PreventUpdate
grid = load_grid(get_path(self.gridfile))
if (grid.subgrids is not None and
sum([len(subgrid)
for subgrid in grid.subgrids.values()]) != grid.nlay):
warnings.warn(
(f"Subgrid information in {self.gridfile} does not correspond "
"with number of grid layers. Subgrid information will be removed. "
"This is a bug in xtgeo==2.15.2 for grids exported from RMS using Xtgeo. "
"Export the grid with xtgeo>2.15.2 to remove this warning. "
),
FutureWarning,
)
grid.subgrids = None
gridparameter = load_grid_parameter(grid, get_path(gridparameter))
fence = get_fencespec(coords)
hmin, hmax, vmin, vmax, values = grid.get_randomline(
fence, gridparameter, zincrement=0.5)
surface = xtgeo.surface_from_file(get_path(surfacepath))
s_arr = get_surface_fence(fence, surface)
return make_heatmap(
values,
s_arr=s_arr,
theme=self.plotly_theme,
s_name=self.surfacenames[self.surfacefiles.index(surfacepath)],
colorscale=colorscale,
xmin=hmin,
xmax=hmax,
ymin=vmin,
ymax=vmax,
zmin=color_values[0],
zmax=color_values[1],
xaxis_title="Distance along polyline",
yaxis_title=self.zunit,
)
def attribute_around_surface_asymmetric():
"""Get attribute around a surface (asymmetric)"""
cubefile = EXPATH1 / "ib_test_cube2.segy"
surfacefile = EXPATH2 / "h1.dat"
above = 10
below = 20
mycube = xtgeo.cube_from_file(cubefile)
mysurf = xtgeo.surface_from_file(surfacefile,
fformat="ijxyz",
template=mycube)
# instead of using zrange, we make some tmp surfaces that
# reflects the assymmetric
sabove = mysurf.copy()
sbelow = mysurf.copy()
sabove.values -= above
sbelow.values += below
if DEBUG:
sabove.describe()
sbelow.describe()
attrs = "all"
myattrs = mysurf.slice_cube_window(mycube,
attribute=attrs,
sampling="trilinear",
zsurf=sabove,
other=sbelow)
for attr in myattrs.keys():
if DEBUG:
myattrs[attr].describe()
myattrs[attr].to_file(TMPDIR / ("myfile_asymmetric_" + attr + ".dat"),
fformat="ijxyz")
def slice_a_grid():
"""Slice a 3D grid property with maps (looping)"""
expath1 = pathlib.Path("../../xtgeo-testdata/3dgrids/reek")
expath2 = pathlib.Path("../../xtgeo-testdata/surfaces/reek/1")
gridfileroot = expath1 / "REEK"
surfacefile = expath2 / "midreek_rota.gri"
initprops = ["PORO", "PERMX"]
grd = xtgeo.grid_from_file(gridfileroot,
fformat="eclipserun",
initprops=initprops)
# read a surface, which is used for "template"
surf = xtgeo.surface_from_file(surfacefile)
surf.refine(2) # make finer for nicer sampling (NB takes time then)
slices = [1700, 1720, 1740]
for myslice in slices:
print("Slice is {}".format(myslice))
for prp in grd.props:
sconst = surf.copy()
sconst.values = myslice # set constant value for surface
print("Work with {}, slice at {}".format(prp.name, myslice))
sconst.slice_grid3d(grd, prp)
fname = "{}_{}.gri".format(prp.name, myslice)
sconst.to_file(TMPDIR / fname)
fname = TMPDIR / ("{}_{}.png".format(prp.name, myslice))
if "SKIP_PLOT" not in os.environ:
sconst.quickplot(filename=fname)
def main():
"""Exporting maps from clipboard"""
files = INPUT_FOLDER.glob("*.gri")
for file in files:
surf = xtgeo.surface_from_file(file)
attribute = "unset"
for pattern, attr in TRANSLATE.items():
if pattern in str(file).lower():
attribute = attr
name = "unset"
for pattern, attr in NAMETRANSLATE.items():
if pattern in str(file).lower():
name = attr
ed = dataio.ExportData(
config=CFG,
name=name,
unit="fraction",
content={
"property": {
"attribute": attribute,
"is_discrete": False
}
},
vertical_domain={"depth": "msl"},
timedata=None,
is_prediction=True,
is_observation=False,
tagname="average_" + attribute,
verbosity="INFO",
workflow="rms property model",
)
fname = ed.export(surf)
print(f"File name is {fname}")
def calculate_statistical_surface(
self,
name: str,
attribute: str,
calculation: Optional[str] = "Mean",
date: Optional[str] = None,
realizations: Optional[List[int]] = None,
) -> xtgeo.RegularSurface:
"""Returns a Xtgeo surface instance for a calculated surface"""
df = self._filter_surface_table(name=name,
attribute=attribute,
date=date,
realizations=realizations)
# When portable check if the surface has been stored
# if not calculate
try:
surface_stream = save_statistical_surface(sorted(list(df["path"])),
calculation)
except OSError:
surface_stream = save_statistical_surface_no_store(
sorted(list(df["path"])), calculation)
return xtgeo.surface_from_file(surface_stream, fformat="irap_binary")