def test_wo_fromtable_multiindex():
"""Test that we accept multiindex dataframes,
(but a warning will be issued)"""
# Test an example dataframe that easily gets sent in from ecl2df.satfunc:
df1 = pd.DataFrame(
columns=["KEYWORD", "SATNUM", "SW", "KRW", "KROW", "PC"],
data=[
["SWOF", 1, 0, 0, 1, 2],
["SWOF", 1, 0.5, 0.5, 0.5, 1],
["SWOF", 1, 1, 1, 0, 0],
],
).set_index(["KEYWORD", "SATNUM"])
# Check that we have a MultiIndex:
assert len(df1.index.names) == 2
wateroil = WaterOil(h=0.1)
wateroil.add_fromtable(df1,
swcolname="SW",
krwcolname="KRW",
krowcolname="KROW",
pccolname="PC")
assert "krw" in wateroil.table.columns
assert "krow" in wateroil.table.columns
assert "pc" in wateroil.table.columns
check_table(wateroil.table)
def test_linear_input(h, sw_mid):
"""Linear input creates difficulties with sorw, which is used in
add_fromtable(). The intention of the test is to avoid crashes when
add_fromtable().
estimate_sorw() is unreliable on linear input, and returns 0 or 1 on the
given test dataset. Correctness of sorw should not be needed for
add_fromtable().
This tests fails in pyscal v0.7.7"""
dframe = pd.DataFrame(
columns=["SW", "KRW", "KROW", "PC"],
data=[[sw, sw, 1 - sw, 1 - sw] for sw in [0, sw_mid, 1.0]],
)
wateroil = WaterOil(h=h, swl=0)
wateroil.add_fromtable(dframe)
assert wateroil.selfcheck()
# GasOil did not fail in v0.7.7, but test anyway:
gasoil = GasOil(h=h, swl=0)
gasoil.add_fromtable(dframe,
sgcolname="SW",
krgcolname="KRW",
krogcolname="KROW",
pccolname="PCOW")
assert gasoil.selfcheck()
def test_wo_fromtable_simple():
"""Test loading a simple curve from a table"""
df1 = pd.DataFrame(columns=["SW", "KRW", "KROW", "PC"],
data=[[0, 0, 1, 2], [1, 1, 0, 0]])
wateroil = WaterOil(h=0.1)
# With wrong names:
with pytest.raises(ValueError):
# Here we also get a deprecation warning
wateroil.add_oilwater_fromtable(df1)
# Set names:
wateroil.add_fromtable(df1, swcolname="SW")
# This didn't do anything, because we did not provide any relperm names
assert "krw" not in wateroil.table.columns
assert "krow" not in wateroil.table.columns
assert "pc" not in wateroil.table.columns
# Try again:
wateroil.add_fromtable(df1,
swcolname="SW",
krwcolname="KRW",
krowcolname="KROW",
pccolname="PC")
assert "krw" in wateroil.table.columns
assert "krow" in wateroil.table.columns
assert "pc" in wateroil.table.columns
check_table(wateroil.table)
def test_ow_fromtable_h(h):
df1 = pd.DataFrame(
columns=["Sw", "krw", "krow", "pcow"],
data=[[0.15, 0, 1, 3], [0.89, 1, 0, 0.1], [1, 1, 0, 0]],
)
wo = WaterOil(h=h, swl=0.15, sorw=1 - 0.89)
wo.add_fromtable(df1)
check_wo_table(wo.table)
def test_wo_fromtable_h(h):
"""Test making curves from tabular data with random stepsize h"""
df1 = pd.DataFrame(
columns=["Sw", "krw", "krow", "pcow"],
data=[[0.15, 0, 1, 3], [0.89, 1, 0, 0.1], [1, 1, 0, 0]],
)
wateroil = WaterOil(h=h, swl=0.15, sorw=1 - 0.89)
wateroil.add_fromtable(df1)
check_table(wateroil.table)
def test_fromtable_types():
"""Test loading from a table with incorrect types"""
# This frame is valid, but the type was wrong. This
# can happen if data is via CSV files, and some other rows
# ruin the numerical interpretation of a column.
df1 = pd.DataFrame(
columns=["SW", "KRW", "KROW", "PC"],
data=[["0", "0", "1", "2"], ["1", "1", "0", "0"]],
)
wateroil = WaterOil(h=0.1)
wateroil.add_fromtable(df1,
swcolname="SW",
krwcolname="KRW",
krowcolname="KROW",
pccolname="PC")
assert "krw" in wateroil.table.columns
assert "krow" in wateroil.table.columns
assert "pc" in wateroil.table.columns
check_table(wateroil.table)
gasoil = GasOil(h=0.1)
gasoil.add_fromtable(df1,
sgcolname="SW",
krgcolname="KRW",
krogcolname="KROW",
pccolname="PC")
assert "krg" in gasoil.table.columns
assert "krog" in gasoil.table.columns
assert "pc" in gasoil.table.columns
check_table(gasoil.table)
# But this should not make sense.
df2 = pd.DataFrame(
columns=["SW", "KRW", "KROW", "PC"],
data=[["0", dict(foo="bar"), "1", "2"], ["1", "1", "0", "0"]],
)
wateroil = WaterOil(h=0.1)
with pytest.raises((ValueError, TypeError)):
wateroil.add_fromtable(df2,
swcolname="SW",
krwcolname="KRW",
krowcolname="KROW",
pccolname="PC")
gasoil = GasOil(h=0.1)
with pytest.raises((ValueError, TypeError)):
gasoil.add_fromtable(df2,
sgcolname="SW",
krgcolname="KRW",
krogcolname="KROW",
pccolname="PC")
def test_wo_fromtable_simple():
"""Test loading a simple curve from a table"""
df1 = pd.DataFrame(columns=["SW", "KRW", "KROW", "PC"],
data=[[0, 0, 1, 2], [1, 1, 0, 0]])
wateroil = WaterOil(h=0.1)
# With wrong names:
with pytest.raises(ValueError):
wateroil.add_fromtable(df1, swcolname="sw")
# Set names:
wateroil.add_fromtable(df1, swcolname="SW", pccolname="PC")
assert "KRW" in wateroil.table.columns
assert "KROW" in wateroil.table.columns
assert "PC" in wateroil.table.columns
assert sum(wateroil.table["KRW"]) > 0
assert sum(wateroil.table["KROW"]) > 0
assert np.isclose(sum(wateroil.table["PC"]), 11) # Linearly increasing PC
check_table(wateroil.table)
def test_interpolations_wo_fromtable():
"""Analog test as test_interpolations_go_fromtable().
Pyscal 0.6.1 and earlier fails this test sorw.
"""
base = pd.DataFrame(
columns=["Sw", "krw", "krow"],
data=[
[0.0, 0.0, 1.0],
[0.1, 0.0, 1.0],
[0.2, 0.0, 1.0], # swcr
[0.3, 0.1, 0.9],
[0.8, 0.8, 0.0], # sorw
[0.9, 0.9, 0.0],
[1.0, 1.0, 0.0],
],
)
opt = pd.DataFrame(
columns=["Sw", "krw", "krow"],
data=[
[0.0, 0.0, 1.0],
[0.1, 0.0, 1.0],
[0.3, 0.0, 1.0],
[0.4, 0.1, 0.2], # swcr
[0.9, 0.9, 0.0], # sorw
[0.95, 0.95, 0.0],
[1.0, 1.0, 0.0],
],
)
wo_base = WaterOil(h=0.01)
wo_base.add_fromtable(base)
assert np.isclose(wo_base.estimate_swcr(), 0.2)
assert np.isclose(wo_base.estimate_sorw(), 0.2)
wo_opt = WaterOil(h=0.01)
wo_opt.add_fromtable(opt)
assert np.isclose(wo_opt.estimate_swcr(), 0.3)
assert np.isclose(wo_opt.estimate_sorw(), 0.1)
wo_ip = interpolate_wo(wo_base, wo_opt, 0.5, h=0.01)
assert np.isclose(wo_ip.estimate_swcr(), 0.25)
assert np.isclose(wo_ip.estimate_sorw(), 0.15)
def test_wo_fromtable_problems():
"""Test wateroil from tables with problematic data"""
# Implicit swl and sorw in the input, how do we handle that?
df1 = pd.DataFrame(
columns=["Sw", "krw", "krow", "pcow"],
data=[[0.15, 0, 1, 3], [0.89, 1, 0, 0.1], [1, 1, 0, 0]],
)
# With default object:
wateroil = WaterOil(h=0.1)
with pytest.raises(ValueError):
wateroil.add_fromtable(df1)
# This results in krw and krow overshooting 0 and 1
# Fix left endpoint:
wateroil = WaterOil(h=0.1, swl=df1["Sw"].min())
wateroil.add_fromtable(df1)
# The table is now valid, but we did not preserve the 0.89 point
check_table(wateroil.table)
# If we also tell the WaterOil object about sorw, we are guaranteed
# to have it expclitly included:
wateroil = WaterOil(h=0.1, swl=df1["Sw"].min(), sorw=1 - 0.89)
wateroil.add_fromtable(df1)
check_table(wateroil.table)
# For low enough h, this will however NOT matter.
df2 = pd.DataFrame(columns=["Sw", "KRW", "KROW", "PCOW"],
data=[[0, -0.01, 1, 0], [1, 1, 0, 0]])
wateroil = WaterOil(h=0.1)
with pytest.raises(ValueError):
# Should say krw is negative
wateroil.add_fromtable(df2, krwcolname="KRW")
df3 = pd.DataFrame(
columns=["Sw", "KRW", "KROW", "PCOW"],
data=[[0, 0, 1, 0], [1, 1.000000001, 0, 0]],
)
wateroil = WaterOil(h=0.1)
with pytest.raises(ValueError):
# Should say krw is above 1.0
wateroil.add_fromtable(df3, krwcolname="KRW")
def test_ow_fromtable_problems():
# Implicit swl and sorw in the input, how do we handle that?
df1 = pd.DataFrame(
columns=["Sw", "krw", "krow", "pcow"],
data=[[0.15, 0, 1, 3], [0.89, 1, 0, 0.1], [1, 1, 0, 0]],
)
# With default object:
wo = WaterOil(h=0.1)
with pytest.raises(ValueError):
wo.add_fromtable(df1)
# This results in krw and krow overshooting 0 and 1
# Fix left endpoint:
wo = WaterOil(h=0.1, swl=df1["Sw"].min())
wo.add_fromtable(df1)
# The table is now valid, but we did not preserve the 0.89 point
check_wo_table(wo.table)
# If we also tell the WaterOil object about sorw, we are guaranteed
# to have it expclitly included:
wo = WaterOil(h=0.1, swl=df1["Sw"].min(), sorw=1 - 0.89)
wo.add_fromtable(df1)
check_wo_table(wo.table)
def test_wo_fromtable_problems():
"""Test wateroil from tables with problematic data"""
# With default object:
df1 = pd.DataFrame(
columns=["SW", "KRW", "KROW", "PCOW"],
data=[[0.15, 0, 1, 3], [0.89, 1, 0, 0.1], [1, 1, 0, 0]],
)
# With default object:
wateroil = WaterOil(h=0.1)
with pytest.raises(ValueError):
wateroil.add_fromtable(df1)
# This results in krw and krow overshooting 0 and 1
# Fix left endpoint:
wateroil = WaterOil(h=0.1, swl=df1["SW"].min())
wateroil.add_fromtable(df1)
# The table is now valid, but we did not preserve the 0.89 point
check_table(wateroil.table)
# If we also tell the WaterOil object about sorw, we are guaranteed
# to have it expclitly included:
wateroil = WaterOil(h=0.1, swl=df1["SW"].min(), sorw=1 - 0.89)
wateroil.add_fromtable(df1)
check_table(wateroil.table)
def test_wo_invalidcurves():
"""Test what happens when we give in invalid data"""
# Sw data not ordered:
krw1 = pd.DataFrame(columns=["Sw", "krw"],
data=[[0.15, 0], [0.1, 1], [1, 1]])
wateroil = WaterOil(swl=krw1["Sw"].min(), h=0.1)
with pytest.raises(ValueError):
# pchip-interpolator raises this error;
# x coordinates are not in increasing order
wateroil.add_fromtable(krw1, krwcolname="krw")
krw2 = pd.DataFrame(columns=["Sw", "krw"],
data=[[0.15, 0], [0.4, 0.6], [0.6, 0.4], [1, 1]])
wateroil = WaterOil(swl=krw2["Sw"].min(), h=0.1)
with pytest.raises(ValueError):
# Should get notified that krw is not monotonous
wateroil.add_fromtable(krw2, krwcolname="krw")
krow2 = pd.DataFrame(columns=["Sw", "krow"],
data=[[0.15, 1], [0.4, 0.4], [0.6, 0.6], [1, 0]])
wateroil = WaterOil(swl=krow2["Sw"].min(), h=0.1)
with pytest.raises(ValueError):
# Should get notified that krow is not monotonous
wateroil.add_fromtable(krow2, krowcolname="krow")
pc2 = pd.DataFrame(columns=["Sw", "pc"],
data=[[0.15, 1], [0.4, 0.4], [0.6, 0.6], [1, 0]])
wateroil = WaterOil(swl=pc2["Sw"].min(), h=0.1)
with pytest.raises(ValueError):
# Should get notified that pc is not monotonous
wateroil.add_fromtable(pc2, pccolname="pc")
pc3 = pd.DataFrame(
columns=["Sw", "pc"],
data=[[0, np.inf], [0.1, 1], [0.4, 0.4], [0.6, 0.2], [1, 0]],
)
wateroil = WaterOil(swl=pc3["Sw"].min(), h=0.1)
# Will get warning that infinite numbers are ignored.
# In this case the extrapolation is quite bad.
wateroil.add_fromtable(pc3, pccolname="pc")
# But when we later set swl larger, then we should
# not bother about the infinity:
wateroil = WaterOil(swl=0.1, h=0.1)
wateroil.add_fromtable(pc3, pccolname="pc")
assert np.isclose(wateroil.table["pc"].max(), pc3.iloc[1:]["pc"].max())
# Choosing endpoint slightly to the left of 0.1 incurs
# extrapolation. A warning will be given
wateroil = WaterOil(swl=0.05, h=0.1)
wateroil.add_fromtable(pc3, pccolname="pc")
# Inequality due to extrapolation:
assert wateroil.table["pc"].max() > pc3.iloc[1:]["pc"].max()
def test_wo_singlecolumns():
"""Test that we can load single columns from individual dataframes"""
krw = pd.DataFrame(columns=["Sw", "krw"],
data=[[0.15, 0], [0.89, 1], [1, 1]])
krow = pd.DataFrame(columns=["Sw", "krow"],
data=[[0.15, 1], [0.89, 0], [1, 0]])
pc1 = pd.DataFrame(columns=["Sw", "pcow"],
data=[[0.15, 3], [0.89, 0.1], [1, 0]])
wateroil = WaterOil(h=0.1, swl=0.15, sorw=1 - 0.89)
wateroil.add_fromtable(krw)
assert "krw" in wateroil.table
assert "krow" not in wateroil.table
wateroil.add_fromtable(krow)
assert "krow" in wateroil.table
wateroil.add_fromtable(pc1)
assert "pc" in wateroil.table
# We want to allow a pc dataframe where sw starts from zero:
# then should not preserve pc(sw=0)
pc2 = pd.DataFrame(columns=["Sw", "pcow"],
data=[[0, 3], [0.5, 0.1], [1, 0]])
wateroil.add_fromtable(pc2)
assert "pc" in wateroil.table
assert wateroil.table["sw"].min() == 0.15
assert wateroil.table["pc"].max() < 3
# But we should refuse a pc dataframe not covering our sw range:
wateroil = WaterOil(h=0.1, swl=0)
with pytest.raises(ValueError):
pc3 = pd.DataFrame(columns=["Sw", "pcow"],
data=[[0.1, 3], [0.5, 0.1], [1, 0]])
wateroil.add_fromtable(pc3)
with pytest.raises(ValueError):
pc3 = pd.DataFrame(columns=["Sw", "pcow"], data=[[0, 3], [0.5, 0.1]])
wateroil.add_fromtable(pc3)
# Disallow non-monotonous capillary pressure:
pc4 = pd.DataFrame(columns=["Sw", "pcow"],
data=[[0.15, 3], [0.89, 0.1], [1, 0.1]])
with pytest.raises(ValueError):
wateroil.add_fromtable(pc4)
# But if capillary pressure is all zero, accept it:
pc5 = pd.DataFrame(columns=["Sw", "pcow"], data=[[0, 0], [1, 0]])
wateroil = WaterOil(h=0.1)
wateroil.add_fromtable(pc5)
assert wateroil.table["pc"].sum() == 0
def test_wo_from_table_exceptions(dframe, swl, exception, message):
wateroil = WaterOil(h=0.1, swl=swl)
with pytest.raises(exception, match=message):
wateroil.add_fromtable(dframe)