scmdata.time

Time period handling and interpolation

A large portion of this module was originally from openscm. Thanks to the original author, Sven Willner

TimePoints

class TimePoints(values)[source]

Bases: object

Handles time points by wrapping numpy.ndarray of numpy.datetime64..

as_cftime(date_cls=<class 'cftime._cftime.DatetimeGregorian'>)[source]

Format time points as cftime.datetime

Parameters:: date_cls (cftime.datetime) – The time points will be returned as instances of date_cls
Returns:: list of cftime.datetime – Time points as a list of date_cls objects

days()[source]

Get day of each time point.

Returns:: numpy.ndarray of int – Day of each time point

hours()[source]

Get hour of each time point.

Returns:: numpy.ndarray of int – Hour of each time point

months()[source]

Get month of each time point.

Returns:: numpy.ndarray of int – Month of each time point

to_index()[source]

Get time points as pandas.Index.

Returns:: pandas.Index – pandas.Index of numpy.dtype object with name "time" made from the time points represented as datetime.datetime.

property values: ndarray: Time points

weekdays()[source]

Get weekday of each time point.

Returns:: numpy.ndarray of int – Day of the week of each time point

years()[source]

Get year of each time point.

Returns:: numpy.ndarray of int – Year of each time point

TimeseriesConverter

class TimeseriesConverter(source_time_points, target_time_points, interpolation_type='linear', extrapolation_type='linear')[source]

Bases: object

Interpolator used to convert data between different time bases

This is a modified version originally in openscm.time.TimeseriesConverter. The integral preserving interpolation was removed as it is outside the scope of this package.

Parameters:

source_time_points (np.ndarray) – Source timeseries time points
target_time_points (np.ndarray) – Target timeseries time points
interpolation_type ({"linear"}) – Interpolation type. Options are ‘linear’
extrapolation_type ({"linear", "constant", None}) – Extrapolation type. Options are None, ‘linear’ or ‘constant’

Raises:

InsufficientDataError – Timeseries too short to extrapolate

convert_from(values)[source]

Convert value from source timeseries time points to target timeseries time points.

Parameters:: values (np.ndarray) – Value
Returns:: np.ndarray – Converted data for timeseries values into the target timebase

convert_to(values)[source]

Convert value from target timeseries time points to source timeseries time points.

Parameters:: values (np.ndarray) – Value
Returns:: np.ndarray – Converted data for timeseries values into the source timebase

points_are_compatible(source, target)[source]

Are the two sets of time points compatible i.e. can I convert between the two?

Parameters:

source (numpy.ndarray) – Source timeseries time points
target (numpy.ndarray) – Target timeseries time points

Returns:

bool – Can I convert between the time points?