def test_volplot_manynegative():
qc_frame = pd.DataFrame([
{
"EQLNUM": 1,
"Z": 1000,
"SWATINIT": 0.9,
"PORV": 100000,
"SWAT": 0.2,
"VOLUME": 80,
"QC_FLAG": __SWL_TRUNC__,
"SATNUM": 1,
"PCOW_MAX": 2,
"PPCW": 4,
"PC_SCALING": 2,
"OIP_INIT": 0,
},
{
"EQLNUM": 1,
"Z": 1000,
"SWATINIT": 0.9,
"PORV": 100000,
"SWAT": 0.2,
"VOLUME": 80,
"QC_FLAG": __SWATINIT_1__,
"SATNUM": 1,
"PCOW_MAX": 2,
"PPCW": 4,
"PC_SCALING": 2,
"OIP_INIT": 0,
},
])
wvol_waterfall(qc_volumes(qc_frame))
print("Verify that y limits in particular are correct")
pyplot.show()
def test_volplot_negative_bars():
"""Test the volumetrics waterfall chart with negative values, giving negative bars,
interaticve plot test"""
qc_frame = pd.DataFrame([
# This dataframe is a minimum dataset for check_swatinit
# to run.
{
"EQLNUM": 1,
"Z": 1000,
"SWATINIT": 0.9,
"PORV": 100,
"SWAT": 0.8,
"VOLUME": 80,
"QC_FLAG": __SWL_TRUNC__,
"SATNUM": 1,
"PCOW_MAX": 2,
"PPCW": 4,
"PC_SCALING": 2,
"OIP_INIT": 0,
}
])
wvol_waterfall(qc_volumes(qc_frame))
print("Verify that all annotations are visible")
pyplot.show()
def main() -> None:
"""Executed when called from the command line.
Acts on command line arguments, loads data, performs qc and dumps to
CSV if requested."""
parser = get_parser()
args = parser.parse_args()
if args.DATAFILE.endswith(".csv"):
qc_frame = pd.read_csv(args.DATAFILE)
else:
eclfiles = ecl2df.EclFiles(args.DATAFILE)
# Fail hard if the deck is not suitable for this tool or
# give warnings/hints to the user:
check_applicability(eclfiles)
qc_frame = make_qc_gridframe(eclfiles)
if args.output != "":
logger.info("Exporting CSV to %s", args.output)
reorder_dframe_for_nonnans(qc_frame).to_csv(args.output,
index=False)
if "SWATINIT" not in qc_frame:
print("Model did not use SWATINIT")
return
qc_vols = qc_volumes(qc_frame)
print(human_report_qc_vols(qc_vols))
qcsum = qc_vols["SWATINIT_WVOL"] + sum(
[qc_vols[qc_flag] for qc_flag in QC_FLAGS])
diff = qc_vols["SWAT_WVOL"] - qcsum
if not np.isclose(diff, 0, atol=1e-6):
print(f"Unexplained difference: {diff} Rm3")
print()
print(human_report_pc_scaling(qc_frame))
if args.volplot or args.volplotfile:
plotter.wvol_waterfall(qc_vols)
if args.volplot:
pyplot.show()
if args.volplotfile:
print(f"Dumping volume plot to {args.volplotfile}")
pyplot.savefig(args.volplotfile)
if (args.plotfile
or args.plot) and args.eqlnum not in qc_frame["EQLNUM"].values:
sys.exit(
f"Error: EQLNUM {args.eqlnum} does not exist in grid. No plotting."
)
if args.plot or args.plotfile:
plotter.plot_qc_panels(qc_frame[qc_frame["EQLNUM"] == args.eqlnum])
if args.plot:
pyplot.show()
if args.plotfile:
print(f"Dumping plot to {args.plotfile}")
pyplot.savefig(args.plotfile)
def test_volplot_largenegative():
qc_frame = pd.DataFrame([{
"EQLNUM": 1,
"Z": 1000,
"SWATINIT": 0.9,
"PORV": 100000,
"SWAT": 0.2,
"VOLUME": 80,
"QC_FLAG": __SWL_TRUNC__,
"SATNUM": 1,
"PCOW_MAX": 2,
"PPCW": 4,
"PC_SCALING": 2,
"OIP_INIT": 0,
}])
wvol_waterfall(qc_volumes(qc_frame))
print("Verify that all annotations are visible and placed wisely")
pyplot.show()
def test_volplot_zerospan():
# Test when there is no difference from SWATINIT to SWAT:
qc_frame = pd.DataFrame([{
"EQLNUM": 1,
"Z": 1000,
"SWATINIT": 0.9,
"PORV": 100000,
"SWAT": 0.9,
"VOLUME": 80,
"QC_FLAG": __SWL_TRUNC__,
"SATNUM": 1,
"PCOW_MAX": 2,
"PPCW": 4,
"PC_SCALING": 2,
"OIP_INIT": 0,
}])
wvol_waterfall(qc_volumes(qc_frame))
print("Verify that all annotations are visible and placed wisely")
pyplot.show()