carpet_concentrations.time

Time handling

MONTHS_PER_YEAR

class NonUniqueYearMonths(unique_vals, counts)[source]

Raised when the user tries to convert to year-month with non-unique values

This happens when the datetime values lead to year-month values that are not unique

class CftimeConverter(*args, **kwargs)[source]

Callable that supports converting stacked time co-ordinates to cftime.datetime

convert_year_month_to_time(inp, day=1, **kwargs)[source]

Convert year and month co-ordinates into a time axis

This is a facade to convert_to_time()

Parameters

Returns

xarray.core.dataset.Dataset – Data with time axis

convert_to_time(inp, time_coords, cftime_converter)[source]

Convert some co-ordinates representing time into a time axis

Parameters

inp (xarray.core.dataset.Dataset) – Data to convert
time_coords (tuple[str, ...]) – Co-ordinates from which to create the time axis
cftime_converter (carpet_concentrations.time.CftimeConverter) – Callable that converts the stacked time co-ordinates to cftime.datetime

Returns

xarray.core.dataset.Dataset – Data with time axis

split_time_to_year_month(inp, time_axis='time')[source]

Convert the time dimension to year and month without stacking

This means there is still a single time dimension in the output, but there is now also accompanying year and month information

Parameters: inp (xarray.core.dataset.Dataset) – Data to convert
Returns: xarray.core.dataset.Dataset – Data with year and month information for the time axis
Raises: NonUniqueYearMonths – The years and months are not unique

convert_time_to_year_month(inp, time_axis='time')[source]

Convert the time dimension to year and month co-ordinates

Parameters: inp (xarray.core.dataset.Dataset) – Data to convert
Returns: xarray.core.dataset.Dataset – Data with year and month co-ordinates

get_start_of_next_month(y, m)[source]

Get start of next month

Parameters

Returns

cftime._cftime.datetime – Start of next month