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def separate_method_kwargs(method_args, init_method, fit_method):
# inspect the methods
init_kwargs = get_valid_kwargs(init_method, method_args)
fit_kwargs = get_valid_kwargs(fit_method, method_args)
# Warn about unknown kwargs
known_kwargs = set(init_kwargs) | set(fit_kwargs)
unknown_kwargs = set(method_args) - known_kwargs
if unknown_kwargs:
raise PlotnineError(
"The following method arguments could not be recognised: "
"{}".format(list(unknown_kwargs))
)
return init_kwargs, fit_kwargs
def separate_method_kwargs(method_args, init_method, fit_method):
# inspect the methods
init_kwargs = get_valid_kwargs(init_method, method_args)
fit_kwargs = get_valid_kwargs(fit_method, method_args)
# Warn about unknown kwargs
known_kwargs = set(init_kwargs) | set(fit_kwargs)
unknown_kwargs = set(method_args) - known_kwargs
if unknown_kwargs:
raise PlotnineError(
"The following method arguments could not be recognised: "
"{}".format(list(unknown_kwargs))
)
return init_kwargs, fit_kwargs
if any([fun_y, fun_ymin, fun_ymax]):
def func(df):
d = {}
if fun_y:
kwargs = get_valid_kwargs(fun_y, fun_args)
d['y'] = [fun_y(df['y'], **kwargs)]
if fun_ymin:
kwargs = get_valid_kwargs(fun_ymin, fun_args)
d['ymin'] = [fun_ymin(df['y'], **kwargs)]
if fun_ymax:
kwargs = get_valid_kwargs(fun_ymax, fun_args)
d['ymax'] = [fun_ymax(df['y'], **kwargs)]
return pd.DataFrame(d)
elif fun_data:
kwargs = get_valid_kwargs(fun_data, fun_args)
def func(df):
return fun_data(df['y'], **kwargs)
return func