import pandas
# +
##########################
# #########################
# Save impact vector
# #########################
# #########################
# -
[docs]
def save_impact_vector(impact_matrix, savedir, cst_import=False, residual=False):
"""Function to save the impact matrix.
Parameters
----------
impact matrix: pandas.DataFrame
the table with the impact factors
savedir: str
the directory where to save
cst_import: bool, default to False
if constant exchange impacts are considered
residual: bool, default to False
if a residual is considered
"""
add_on = ""
if cst_import: add_on += "_CstImp"
if residual: add_on += "_Res"
file_name = f"Unit_Impact_Vector{add_on}.csv"
impact_matrix.to_csv(savedir + file_name, index=True)
# +
##########################
# #########################
# Save Dataset
# #########################
# #########################
# -
[docs]
def save_dataset(data, savedir, name, target=None, freq='H'):
"""Function to save the datasets with information of the frequency.
Parameters
----------
data: pandas.DataFrame
the dataset to save
savedir: str
the directory where to save
name: str
the name of the file (excluding extension and frequency info)
target: str, default to None
tag of target country, to be added to the name if given.
freq: str, default to 'H'
the frequency
"""
### Formating the time extension
tPass = {'15min':'15min','30min':'30min',"H":"hour","D":"day",'d':'day','W':"week",
"w":"week","MS":"month","M":"month","YS":"year","Y":"year"}
as_target = "" if target is None else f"_{target}"
### Saving
data.to_csv(savedir+f"{name}{as_target}_{tPass[freq]}.csv",index=True, float_format='%.3g')