def test_rst2df():
"""Test producing dataframes from restart files"""
eclfiles = EclFiles(REEK)
assert grid.rst2df(eclfiles, "first").shape == (35817, 24)
assert grid.rst2df(eclfiles, "last").shape == (35817, 24)
assert grid.rst2df(eclfiles, "all").shape == (35817, 23 * 4 + 1)
assert "SOIL" in grid.rst2df(eclfiles, date="first", dateinheaders=False)
assert (
"SOIL@2000-01-01" in grid.rst2df(eclfiles, "first", dateinheaders=True).columns
)
rst_df = grid.rst2df(eclfiles, "first", stackdates=True)
assert "DATE" in rst_df
assert rst_df["DATE"].unique()[0] == "2000-01-01"
rst_df = grid.rst2df(eclfiles, "all", stackdates=True)
assert len(rst_df["DATE"].unique()) == len(grid.get_available_rst_dates(eclfiles))
# "DATE" and "active" are now the extra columns:
assert rst_df.shape == (4 * 35817, 23 + 2)
# Test that only the PPCW column contains NaN's (only defined for selected cells)
nancols = rst_df.isna().any()
assert nancols["PPCW"]
assert (
len(rst_df[["PPCW", "DATE"]].dropna()["DATE"].unique()) == 4
) # All dates present
assert sum(nancols) == 1 # All other columns are "False"
# Check vector slicing:
rst_df = grid.rst2df(eclfiles, "first", vectors="S???")
assert rst_df.shape == (35817, 4)
assert "SGAS" in rst_df
assert "SWAT" in rst_df
assert "SOIL" in rst_df # This is actually computed
assert "FIPWAT" not in rst_df
rst_df = grid.rst2df(eclfiles, "first", vectors=["PRESSURE", "SWAT"])
assert "PRESSURE" in rst_df
assert "SWAT" in rst_df
assert "SGAS" not in rst_df
assert "SOIL" not in rst_df
# Check that we can avoid getting SOIL if we are explicit:
rst_df = grid.rst2df(eclfiles, "first", vectors=["SGAS", "SWAT"])
assert "SOIL" not in rst_df
assert "SGAS" in rst_df
assert "SWAT" in rst_df
def test_rst2df():
"""Test producing dataframes from restart files"""
eclfiles = EclFiles(DATAFILE)
assert grid.rst2df(eclfiles, "first").shape == (35817, 23)
assert grid.rst2df(eclfiles, "last").shape == (35817, 23)
assert grid.rst2df(eclfiles, "all").shape == (35817, 23 * 4)
assert "SOIL" in grid.rst2df(eclfiles, date="first", dateinheaders=False)
assert ("SOIL@2000-01-01" in grid.rst2df(eclfiles,
"first",
dateinheaders=True).columns)
rst_df = grid.rst2df(eclfiles, "first", stackdates=True)
assert "DATE" in rst_df
assert rst_df["DATE"].unique()[0] == "2000-01-01"
rst_df = grid.rst2df(eclfiles, "all", stackdates=True)
assert len(rst_df["DATE"].unique()) == len(
grid.get_available_rst_dates(eclfiles))
assert rst_df.shape == (4 * 35817, 23 + 1
) # "DATE" is now the extra column
# Check vector slicing:
rst_df = grid.rst2df(eclfiles, "first", vectors="S???")
assert rst_df.shape == (35817, 3)
assert "SGAS" in rst_df
assert "SWAT" in rst_df
assert "SOIL" in rst_df # This is actually computed
assert "FIPWAT" not in rst_df
rst_df = grid.rst2df(eclfiles, "first", vectors=["PRESSURE", "SWAT"])
assert "PRESSURE" in rst_df
assert "SWAT" in rst_df
assert "SGAS" not in rst_df
assert "SOIL" not in rst_df
# Check that we can avoid getting SOIL if we are explicit:
rst_df = grid.rst2df(eclfiles, "first", vectors=["SGAS", "SWAT"])
assert "SOIL" not in rst_df
assert "SGAS" in rst_df
assert "SWAT" in rst_df