def test_formularef():
cset = wrap(
schema.Correction(
name="reftest",
version=2,
inputs=[
schema.Variable(name="x", type="real"),
],
output=schema.Variable(name="a scale", type="real"),
generic_formulas=[
schema.Formula(
nodetype="formula",
expression="[0] + [1]*x",
parser="TFormula",
variables=["x"],
),
],
data=schema.Binning(
nodetype="binning",
input="x",
edges=[0, 1, 2, 3],
content=[
schema.FormulaRef(
nodetype="formularef", index=0, parameters=[0.1, 0.2]
),
schema.FormulaRef(
nodetype="formularef", index=0, parameters=[1.1, -0.2]
),
schema.FormulaRef(
nodetype="formularef", index=0, parameters=[3.1, 0.5]
),
],
flow="error",
),
)
)
corr = cset["reftest"]
assert corr.evaluate(0.5) == 0.1 + 0.2 * 0.5
assert corr.evaluate(1.5) == 1.1 + -0.2 * 1.5
assert corr.evaluate(2.5) == 3.1 + 0.5 * 2.5
def test_transform():
cset = wrap(
schema.Correction(
name="test",
version=2,
inputs=[
schema.Variable(name="torewrite", type="real"),
],
output=schema.Variable(name="a scale", type="real"),
data=schema.Transform(
nodetype="transform",
input="torewrite",
rule=0.1,
content=schema.Formula(
nodetype="formula",
expression="x",
parser="TFormula",
variables=["torewrite"],
),
),
))
corr = cset["test"]
assert corr.evaluate(0.5) == 0.1
assert corr.evaluate(1.5) == 0.1
cset = wrap(
schema.Correction(
name="test",
version=2,
inputs=[
schema.Variable(name="torewrite", type="int"),
],
output=schema.Variable(name="a scale", type="real"),
data=schema.Transform(
nodetype="transform",
input="torewrite",
rule=schema.Category(
nodetype="category",
input="torewrite",
content=[
{
"key": 0,
"value": 0
},
{
"key": 1,
"value": 4
},
{
"key": 2,
"value": 0
},
{
"key": 9,
"value": 3.000001
},
{
"key": 10,
"value": 2.999999
},
],
),
content=schema.Category(
nodetype="category",
input="torewrite",
content=[
{
"key": 0,
"value": 0.0
},
{
"key": 3,
"value": 0.1
},
{
"key": 4,
"value": 0.2
},
],
),
),
))
corr = cset["test"]
assert corr.evaluate(0) == 0.0
assert corr.evaluate(1) == 0.2
assert corr.evaluate(2) == 0.0
with pytest.raises(IndexError):
corr.evaluate(3)
assert corr.evaluate(9) == 0.1
assert corr.evaluate(10) == 0.1
def test_binning():
def binning(flow):
cset = wrap(
schema.Correction(
name="test",
version=2,
inputs=[schema.Variable(name="x", type="real")],
output=schema.Variable(name="a scale", type="real"),
data=schema.Binning(
nodetype="binning",
input="x",
edges=[0.0, 1.0, 3.0],
content=[1.0, 2.0],
flow=flow,
),
))
return cset["test"]
corr = binning(flow="error")
with pytest.raises(RuntimeError):
corr.evaluate(-1.0)
assert corr.evaluate(0.0) == 1.0
assert corr.evaluate(0.2) == 1.0
assert corr.evaluate(1.0) == 2.0
with pytest.raises(RuntimeError):
corr.evaluate(3.0)
corr = binning(flow="clamp")
assert corr.evaluate(-1.0) == 1.0
assert corr.evaluate(1.0) == 2.0
assert corr.evaluate(3.0) == 2.0
assert corr.evaluate(3000.0) == 2.0
corr = binning(flow=42.0)
assert corr.evaluate(-1.0) == 42.0
assert corr.evaluate(0.0) == 1.0
assert corr.evaluate(1.0) == 2.0
assert corr.evaluate(2.9) == 2.0
assert corr.evaluate(3.0) == 42.0
def multibinning(flow):
cset = wrap(
schema.Correction(
name="test",
version=2,
inputs=[
schema.Variable(name="x", type="real"),
schema.Variable(name="y", type="real"),
],
output=schema.Variable(name="a scale", type="real"),
data=schema.MultiBinning(
nodetype="multibinning",
inputs=["x", "y"],
edges=[
[0.0, 1.0, 3.0],
[10.0, 20.0, 30.0, 40.0],
],
content=[float(i) for i in range(2 * 3)],
flow=flow,
),
))
return cset["test"]
corr = multibinning(flow="error")
with pytest.raises(RuntimeError):
corr.evaluate(0.0, 5.0)
with pytest.raises(RuntimeError):
corr.evaluate(-1.0, 5.0)
assert corr.evaluate(0.0, 10.0) == 0.0
assert corr.evaluate(0.0, 20.0) == 1.0
assert corr.evaluate(0.0, 30.0) == 2.0
with pytest.raises(RuntimeError):
corr.evaluate(0.0, 40.0)
assert corr.evaluate(1.0, 10.0) == 3.0
assert corr.evaluate(1.0, 20.0) == 4.0
assert corr.evaluate(1.0, 30.0) == 5.0
with pytest.raises(RuntimeError):
corr.evaluate(2.0, 5.0)
corr = multibinning(flow="clamp")
assert corr.evaluate(-1.0, 5.0) == 0.0
assert corr.evaluate(-1.0, 25.0) == 1.0
assert corr.evaluate(-1.0, 35.0) == 2.0
assert corr.evaluate(-1.0, 45.0) == 2.0
assert corr.evaluate(0.0, 45.0) == 2.0
assert corr.evaluate(2.0, 45.0) == 5.0
assert corr.evaluate(3.0, 45.0) == 5.0
assert corr.evaluate(3.0, 35.0) == 5.0
assert corr.evaluate(3.0, 25.0) == 4.0
assert corr.evaluate(3.0, 15.0) == 3.0
assert corr.evaluate(3.0, 5.0) == 3.0
assert corr.evaluate(0.0, 5.0) == 0.0
corr = multibinning(flow=42.0)
assert corr.evaluate(-1.0, 5.0) == 42.0
assert corr.evaluate(2.0, 45.0) == 42.0
assert corr.evaluate(3.0, 5.0) == 42.0
corr = multibinning(flow=schema.Formula(
nodetype="formula",
expression="2.*x + 5.*y",
parser="TFormula",
variables=["x", "y"],
))
assert corr.evaluate(-1.0, 5.0) == 2.0 * -1 + 5.0 * 5.0
assert corr.evaluate(0.0, 10.0) == 0.0