atoti.math.erfc module

atoti.math.erfc(measure)

Return the complementary error function of the input measure.

This is the complementary of atoti.math.erf(). It is defined as 1.0 - erf. It can be used for large values of x where a subtraction from one would cause a loss of significance.

Example

>>> df = pd.DataFrame(
...     columns=["City", "A", "B", "C", "D"],
...     data=[
...         ("Berlin", 15.0, 10.0, 10.1, 1.0),
...         ("London", 24.0, 16.0, 20.5, 3.14),
...         ("New York", -27.0, 15.0, 30.7, 10.0),
...         ("Paris", 0.0, 0.0, 0.0, 0.0),
...     ],
... )
>>> table = session.read_pandas(df, keys=["City"], table_name="Math")
>>> cube = session.create_cube(table)
>>> l, m = cube.levels, cube.measures
>>> m["erfc"] = tt.math.erfc(m["D.SUM"])
>>> m["1-erf"] = 1 - tt.math.erf(m["D.SUM"])
>>> m["erfc"].formatter = "DOUBLE[#.00E]"
>>> m["1-erf"].formatter = "DOUBLE[#.00E]"
>>> cube.query(m["D.SUM"], m["erfc"], m["1-erf"], levels=[l["City"]])
          D.SUM                    erfc                1-erf
City
Berlin     1.00     0.15729920705028488  0.15729920705028488
London     3.14    8.969565553264981E-6   8.9695655532962E-6
New York  10.00  2.0884875837625685E-45                  0.0
Paris       .00                     1.0                  1.0

Return type

MeasureDescription