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gcages.typing#

Type hints that are used throughout

Attributes:

Name Type Description
NP_ARRAY_OF_FLOAT_OR_INT TypeAlias

Type alias for an array of numpy float or int (not complex)
NP_FLOAT_OR_INT TypeAlias

Type alias for a numpy float or int (not complex)
NUMERIC_DATA TypeAlias

Type alias for a value that can be used in the data of a TimeseriesDataFrame
PINT_SCALAR TypeAlias

Type alias for a pint quantity that wraps a numpy scalar
TIME_POINT TypeAlias

Type alias for a value that can be used in the columns of a TimeseriesDataFrame
TimeseriesDataFrame TypeAlias

Type alias for the pd.DataFrame shape we use throughout

NP_ARRAY_OF_FLOAT_OR_INT module-attribute #

NP_ARRAY_OF_FLOAT_OR_INT: TypeAlias = NDArray[
    NP_FLOAT_OR_INT
]

Type alias for an array of numpy float or int (not complex)

NP_FLOAT_OR_INT module-attribute #

NP_FLOAT_OR_INT: TypeAlias = Union[
    floating[Any], integer[Any]
]

Type alias for a numpy float or int (not complex)

NUMERIC_DATA module-attribute #

NUMERIC_DATA: TypeAlias = Union[float, int, NP_FLOAT_OR_INT]

Type alias for a value that can be used in the data of a TimeseriesDataFrame

PINT_SCALAR module-attribute #

PINT_SCALAR: TypeAlias = NumpyQuantity[NP_FLOAT_OR_INT]

Type alias for a pint quantity that wraps a numpy scalar

TIME_POINT module-attribute #

TIME_POINT: TypeAlias = Union[float, int]

Type alias for a value that can be used in the columns of a TimeseriesDataFrame

TimeseriesDataFrame module-attribute #

TimeseriesDataFrame: TypeAlias = DataFrame

Type alias for the pd.DataFrame shape we use throughout

For typing purposes, this is just a direct alias of pd.DataFrame. However, the point of defining this is to provide greater clarity of the kind of data we expect.

We expect a collection of timeseries. These timeseries are defined by the columns, which we expect to be timepoints. We expect that the index contains metadata about each timeseries. As a result, the data itself should be numerical only (no strings, no lists, no dicts).

An example of this kind of data is given below. Note, in line with the description above:

  1. Data is in the body of the pd.DataFrame
  2. The columns define the time axis
  3. All metadata is contained in the index
                        2015  2100
scenario variable unit
sa       va       W      1.0   2.1
         vb       W      3.0   2.0