cwatm.plot_annual_coeff

cwatm.plot_annual_coeff(filepath, *, extension='.csv', date_format='%d/%m', to_file=False, **kwargs)

Convert a sparse timeseries tabular data (or a set of data) into a 10-day, and plot it (or them).

Particularly handy to have a quick overview of cropCoefficients and interceptCap annual timeseries.

Important: in this kind of sparse timeseries, it is assumed that values correspond to their first occurence, and will be propagated foward (01/10 | 5, 20/10 | 2 means that the value 5 applies from 01/10 to 19/10, followed by the value 2).

Parameters

datastr or pathlib.Path

File (tabular data) or folder.

extensionstr, optional, default ‘.csv’

Used only when data is a folder. Define the file types that will be taken into account.

date_formatstr, optional, default “%d/%m”

Argument to load data ( with pandas.read_csv).

to_filebool or path (str or pathlib.Path), default False

If True and if data is a path (str or pathlib.Path), the resulting dataset will be exported to the same location as data, while appending ‘_prolonged’ to its name. If to_file is a path, the resulting dataset will be exported to this specified filepath.

**kwargs :

Keys arguments for pandas.read_csv():

• sep

• index_col

• decimal

• …

Returns

Create 10day timeseries (in a 10day folder) as well as a html figure (in a continuous folder).